@article {639, title = {Frailty in older adults: evidence for a phenotype.}, journal = {J Gerontol A Biol Sci Med Sci}, volume = {56}, year = {2001}, month = {2001 Mar}, pages = {M146-56}, abstract = {

BACKGROUND: Frailty is considered highly prevalent in old age and to confer high risk for falls, disability, hospitalization, and mortality. Frailty has been considered synonymous with disability, comorbidity, and other characteristics, but it is recognized that it may have a biologic basis and be a distinct clinical syndrome. A standardized definition has not yet been established.

METHODS: To develop and operationalize a phenotype of frailty in older adults and assess concurrent and predictive validity, the study used data from the Cardiovascular Health Study. Participants were 5,317 men and women 65 years and older (4,735 from an original cohort recruited in 1989-90 and 582 from an African American cohort recruited in 1992-93). Both cohorts received almost identical baseline evaluations and 7 and 4 years of follow-up, respectively, with annual examinations and surveillance for outcomes including incident disease, hospitalization, falls, disability, and mortality.

RESULTS: Frailty was defined as a clinical syndrome in which three or more of the following criteria were present: unintentional weight loss (10 lbs in past year), self-reported exhaustion, weakness (grip strength), slow walking speed, and low physical activity. The overall prevalence of frailty in this community-dwelling population was 6.9\%; it increased with age and was greater in women than men. Four-year incidence was 7.2\%. Frailty was associated with being African American, having lower education and income, poorer health, and having higher rates of comorbid chronic diseases and disability. There was overlap, but not concordance, in the cooccurrence of frailty, comorbidity, and disability. This frailty phenotype was independently predictive (over 3 years) of incident falls, worsening mobility or ADL disability, hospitalization, and death, with hazard ratios ranging from 1.82 to 4.46, unadjusted, and 1.29-2.24, adjusted for a number of health, disease, and social characteristics predictive of 5-year mortality. Intermediate frailty status, as indicated by the presence of one or two criteria, showed intermediate risk of these outcomes as well as increased risk of becoming frail over 3-4 years of follow-up (odds ratios for incident frailty = 4.51 unadjusted and 2.63 adjusted for covariates, compared to those with no frailty criteria at baseline).

CONCLUSIONS: This study provides a potential standardized definition for frailty in community-dwelling older adults and offers concurrent and predictive validity for the definition. It also finds that there is an intermediate stage identifying those at high risk of frailty. Finally, it provides evidence that frailty is not synonymous with either comorbidity or disability, but comorbidity is an etiologic risk factor for, and disability is an outcome of, frailty. This provides a potential basis for clinical assessment for those who are frail or at risk, and for future research to develop interventions for frailty based on a standardized ascertainment of frailty.

}, keywords = {Aged, Aged, 80 and over, Cohort Studies, Disabled Persons, Fatigue, Female, Frail Elderly, Humans, Incidence, Male, Muscle Weakness, Phenotype, Prevalence, Sex Distribution, United States, Weight Loss}, issn = {1079-5006}, doi = {10.1093/gerona/56.3.m146}, author = {Fried, L P and Tangen, C M and Walston, J and Newman, A B and Hirsch, C and Gottdiener, J and Seeman, T and Tracy, R and Kop, W J and Burke, G and McBurnie, M A} } @article {857, title = {Haptoglobin phenotype, sleep-disordered breathing, and the prevalence of cardiovascular disease: the Sleep Heart Health Study.}, journal = {Sleep}, volume = {28}, year = {2005}, month = {2005 Feb}, pages = {207-13}, abstract = {

BACKGROUND: Diabetes is an independent risk factor for cardiovascular disease, and there is growing evidence that sleep-disordered breathing also may increase the risk of cardiovascular disease. The mechanism responsible for increased susceptibility of people with diabetes to cardiovascular disease is thought to share several features with sleep-disordered breathing, notably increased oxidative stress. We recently demonstrated that a particular haptoglobin phenotype that is associated with differential antioxidant activity is an independent risk factor for cardiovascular disease in individuals with diabetes. We therefore sought to determine whether sleep-disordered breathing and cardiovascular disease are more strongly associated among people with the unfavorable haptoglobin phenotype.

METHODS: We tested this hypothesis in 2612 middle-aged and older participants from the Sleep Heart Health Study. Haptoglobin phenotyping was performed by gel electrophoresis. Respiratory disturbance index was assessed by standard methods. Logistic regression analysis was performed to estimate the association between haptoglobin phenotype and cardiovascular disease, adjusting for known cardiovascular risk factors (age, sex, diabetes, smoking, lipid levels, and hypertension). Possible modification by haptoglobin phenotype of the association of sleep-disordered breathing with cardiovascular disease prevalence was explored by examining interaction terms.

RESULTS: We found no significant association between haptoglobin phenotype and prevalent cardiovascular disease in this cohort, nor were significant interactions found between haptoglobin phenotype and sleep-disordered breathing on the prevalence of cardiovascular disease.

CONCLUSIONS: Sleep-disordered breathing did not appear to interact with haptoglobin phenotype in modifying the association with prevalent cardiovascular disease in the Sleep Heart Health Study. These findings could be due to the absence of association or to survivor bias in these cross-sectional analyses.

}, keywords = {Aged, Angioplasty, Balloon, Coronary, Coronary Artery Bypass, Cross-Sectional Studies, Female, Haptoglobins, Humans, Male, Middle Aged, Myocardial Infarction, Oxidative Stress, Phenotype, Polysomnography, Prevalence, Sleep Apnea Syndromes}, issn = {0161-8105}, doi = {10.1093/sleep/28.2.207}, author = {Levy, Andrew P and Zhang, Lin and Miller-Lotan, Rachel and Redline, Susan and O{\textquoteright}Connor, George T and Quan, Stuart F and Resnick, Helaine E} } @article {817, title = {Population structure, admixture, and aging-related phenotypes in African American adults: the Cardiovascular Health Study.}, journal = {Am J Hum Genet}, volume = {76}, year = {2005}, month = {2005 Mar}, pages = {463-77}, abstract = {

U.S. populations are genetically admixed, but surprisingly little empirical data exists documenting the impact of such heterogeneity on type I and type II error in genetic-association studies of unrelated individuals. By applying several complementary analytical techniques, we characterize genetic background heterogeneity among 810 self-identified African American subjects sampled as part of a multisite cohort study of cardiovascular disease in older adults. On the basis of the typing of 24 ancestry-informative biallelic single-nucleotide-polymorphism markers, there was evidence of substantial population substructure and admixture. We used an allele-sharing-based clustering algorithm to infer evidence for four genetically distinct subpopulations. Using multivariable regression models, we demonstrate the complex interplay of genetic and socioeconomic factors on quantitative phenotypes related to cardiovascular disease and aging. Blood glucose level correlated with individual African ancestry, whereas body mass index was associated more strongly with genetic similarity. Blood pressure, HDL cholesterol level, C-reactive protein level, and carotid wall thickness were not associated with genetic background. Blood pressure and HDL cholesterol level varied by geographic site, whereas C-reactive protein level differed by occupation. Both ancestry and genetic similarity predicted the number and quality of years lived during follow-up, but socioeconomic factors largely accounted for these associations. When the 24 genetic markers were tested individually, there were an excess number of marker-trait associations, most of which were attenuated by adjustment for genetic ancestry. We conclude that the genetic demography underlying older individuals who self identify as African American is complex, and that controlling for both genetic admixture and socioeconomic characteristics will be required in assessing genetic associations with chronic-disease-related traits in African Americans. Complementary methods that identify discrete subgroups on the basis of genetic similarity may help to further characterize the complex biodemographic structure of human populations.

}, keywords = {African Americans, Aged, Aging, Algorithms, Cardiovascular Diseases, Cohort Studies, Female, Genetics, Population, Genotype, Humans, Male, Models, Genetic, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Risk Factors, Socioeconomic Factors}, issn = {0002-9297}, doi = {10.1086/428654}, author = {Reiner, Alexander P and Ziv, Elad and Lind, Denise L and Nievergelt, Caroline M and Schork, Nicholas J and Cummings, Steven R and Phong, Angie and Burchard, Esteban Gonz{\'a}lez and Harris, Tamara B and Psaty, Bruce M and Kwok, Pui-Yan} } @article {989, title = {Genome-wide association of sleep and circadian phenotypes.}, journal = {BMC Med Genet}, volume = {8 Suppl 1}, year = {2007}, month = {2007 Sep 19}, pages = {S9}, abstract = {

BACKGROUND: Numerous studies suggest genetic influences on sleepiness and circadian rhythms. The Sleep Heart Health Study collected questionnaire data on sleep habits and sleepiness from 2848 Framingham Heart Study Offspring Cohort participants. More than 700 participants were genotyped using the Affymetrix 100K SNP GeneChip, providing a unique opportunity to assess genetic linkage and association of these traits.

METHODS: Sleepiness (defined as the Epworth Sleepiness Scale score), usual bedtime and usual sleep duration were assessed by self-completion questionnaire. Standardized residual measures adjusted for age, sex and BMI were analyzed. Multipoint variance components linkage analysis was performed. Association of SNPs to sleep phenotypes was analyzed with both population-based and family-based association tests, with analysis limited to 70,987 autosomal SNPs with minor allele frequency > or =10\%, call rate > or =80\%, and no significant deviation from Hardy-Weinberg equilibrium (p > or = 0.001).

RESULTS: Heritability of sleepiness was 0.29, bedtime 0.22, and sleep duration 0.17. Both genotype and sleep phenotype data were available for 749 subjects. Linkage analysis revealed five linkage peaks of LOD >2: four to usual bedtime, one to sleep duration. These peaks include several candidate sleep-related genes, including CSNK2A2, encoding a known component of the circadian molecular clock, and PROK2, encoding a putative transmitter of the behavioral circadian rhythm from the suprachiasmatic nucleus. Association tests identified an association of usual bedtime with a non-synonymous coding SNP in NPSR1 that has been shown to encode a gain of function mutation of the neuropeptide S receptor, whose endogenous ligand is a potent promoter of wakefulness. Each copy of the minor allele of this SNP was associated with a 15 minute later mean bedtime. The lowest p value was for association of sleepiness with a SNP located in an intron of PDE4D, which encodes a cAMP-specific phosphodiesterase widely expressed in human brain. Full association results are posted at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 webcite.

CONCLUSION: This analysis confirms prior reports of significant heritability of sleepiness, usual bedtime, and usual sleep duration. Several genetic loci with suggestive linkage to these traits are identified, including linkage peaks containing circadian clock-related genes. Association tests identify NPSR1 and PDE4D as possible mediators of bedtime and sleepiness.

}, keywords = {Adult, Alleles, Cardiovascular Diseases, Circadian Rhythm, Cohort Studies, Female, Gene Frequency, Genetic Linkage, Genome, Human, Genotype, Humans, Male, Middle Aged, Phenotype, Polymorphism, Single Nucleotide, Sleep, Surveys and Questionnaires}, issn = {1471-2350}, doi = {10.1186/1471-2350-8-S1-S9}, author = {Gottlieb, Daniel J and O{\textquoteright}Connor, George T and Wilk, Jemma B} } @article {985, title = {USF1 gene variants, cardiovascular risk, and mortality in European Americans: analysis of two US cohort studies.}, journal = {Arterioscler Thromb Vasc Biol}, volume = {27}, year = {2007}, month = {2007 Dec}, pages = {2736-42}, abstract = {

OBJECTIVE: A common haplotype of the upstream transcription factor 1 gene (USF1) has been associated with decreased susceptibility to familial combined hyperlipidemia (FCHL) and, paradoxically, with increased risk of cardiovascular disease (CVD) and all-cause mortality.

METHODS AND RESULTS: We assessed associations between USF1 tagSNPs, CVD risk factors, and aging-related phenotypes using data from 2 large population-based cohorts, Coronary Artery Risk Development in Young Adults (CARDIA) and the Cardiovascular Health Study (CHS), comprising younger and older adults, respectively. In CARDIA, each additional copy of the FCHL low-risk allele was associated with 2.4 mg/dL lower levels of LDL cholesterol (P=0.01) and decreased risk of subclinical atherosclerosis as assessed by coronary artery calcium (odds ratio 0.79; 95\%CI 0.63 to 0.98). Whereas there was little association between USF1 genotype and metabolic or CVD traits in older adults from CHS, the USF1 low-risk dyslipidemia allele was associated with higher plasma C-reactive protein and interleukin (IL)-6 levels and with increased risk of mortality, particularly attributable to noncardiovascular causes.

CONCLUSIONS: There appears to be a complex and possibly age-dependent relationship between USF1 genotype, atherosclerosis phenotypes, and CVD risk. USF1 may influence mortality through pathways distinct from atherosclerosis. Alternatively, linkage disequilibrium with neighboring polymorphisms in other genes such as F11R may be responsible for the observed USF1 genotype-phenotype associations in older adults.

}, keywords = {Adult, Age Factors, Aged, Aged, 80 and over, Aging, Blood Glucose, C-Reactive Protein, Calcium, Cardiovascular Diseases, Carotid Artery, Common, Cohort Studies, Coronary Artery Disease, Coronary Vessels, European Continental Ancestry Group, Female, Follow-Up Studies, Genetic Predisposition to Disease, Humans, Hyperlipidemia, Familial Combined, Insulin, Interleukin-6, Linkage Disequilibrium, Lipids, Male, Odds Ratio, Phenotype, Polymorphism, Single Nucleotide, Prospective Studies, Risk Assessment, Risk Factors, Time Factors, United States, Upstream Stimulatory Factors}, issn = {1524-4636}, doi = {10.1161/ATVBAHA.107.154559}, author = {Reiner, Alexander P and Carlson, Christopher S and Jenny, Nancy S and Durda, J Peter and Siscovick, David S and Nickerson, Deborah A and Tracy, Russell P} } @article {1152, title = {Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium: Design of prospective meta-analyses of genome-wide association studies from 5 cohorts.}, journal = {Circ Cardiovasc Genet}, volume = {2}, year = {2009}, month = {2009 Feb}, pages = {73-80}, abstract = {

BACKGROUND: The primary aim of genome-wide association studies is to identify novel genetic loci associated with interindividual variation in the levels of risk factors, the degree of subclinical disease, or the risk of clinical disease. The requirement for large sample sizes and the importance of replication have served as powerful incentives for scientific collaboration. Methods- The Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium was formed to facilitate genome-wide association studies meta-analyses and replication opportunities among multiple large population-based cohort studies, which collect data in a standardized fashion and represent the preferred method for estimating disease incidence. The design of the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium includes 5 prospective cohort studies from the United States and Europe: the Age, Gene/Environment Susceptibility-Reykjavik Study, the Atherosclerosis Risk in Communities Study, the Cardiovascular Health Study, the Framingham Heart Study, and the Rotterdam Study. With genome-wide data on a total of about 38 000 individuals, these cohort studies have a large number of health-related phenotypes measured in similar ways. For each harmonized trait, within-cohort genome-wide association study analyses are combined by meta-analysis. A prospective meta-analysis of data from all 5 cohorts, with a properly selected level of genome-wide statistical significance, is a powerful approach to finding genuine phenotypic associations with novel genetic loci.

CONCLUSIONS: The Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium and collaborating non-member studies or consortia provide an excellent framework for the identification of the genetic determinants of risk factors, subclinical-disease measures, and clinical events.

}, keywords = {Adult, Aged, Aging, Cohort Studies, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Heart Diseases, Humans, Male, Meta-Analysis as Topic, Middle Aged, Phenotype, Research Design, Risk Factors}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.108.829747}, author = {Psaty, Bruce M and O{\textquoteright}Donnell, Christopher J and Gudnason, Vilmundur and Lunetta, Kathryn L and Folsom, Aaron R and Rotter, Jerome I and Uitterlinden, Andr{\'e} G and Harris, Tamara B and Witteman, Jacqueline C M and Boerwinkle, Eric} } @article {1154, title = {Common coding variants of the HNF1A gene are associated with multiple cardiovascular risk phenotypes in community-based samples of younger and older European-American adults: the Coronary Artery Risk Development in Young Adults Study and The Cardiovascula}, journal = {Circ Cardiovasc Genet}, volume = {2}, year = {2009}, month = {2009 Jun}, pages = {244-54}, abstract = {

BACKGROUND: The transcription factor hepatocyte nuclear factor (HNF)-1 alpha regulates the activity of a number of genes involved in innate immunity, blood coagulation, lipid and glucose transport and metabolism, and cellular detoxification. Common polymorphisms of the HNF-1 alpha gene (HNF1A) were recently associated with plasma C-reactive protein and gamma-glutamyl transferase concentration in middle-aged to older European Americans (EA).

METHODS AND RESULTS: We assessed whether common variants of HNF1A are associated with C-reactive protein, gamma-glutamyl transferase, and other atherosclerotic and metabolic risk factors, in the large, population-based Coronary Artery Risk Development in Young Adults Study of healthy young EA (n=2154) and African American (AA; n=2083) adults. The minor alleles of Ile27Leu (rs1169288) and Ser486Asn (rs2464196) were associated with 0.10 to 0.15 standard deviation units lower C-reactive protein and gamma-glutamyl transferase levels in EA. The same HNF1A coding variants were associated with higher low-density lipoprotein cholesterol, apolipoprotein B, creatinine, and fibrinogen in EA. We replicated the associations between HNF1A coding variants and C-reactive protein, fibrinogen, low-density lipoprotein cholesterol, and renal function in a second population-based sample of EA adults 65 years and older from the Cardiovascular Health Study. The HNF1A Ser486Asn and/or Ile27Leu variants were also associated with increased risk of subclinical coronary atherosclerosis in Coronary Artery Risk Development in Young Adults and with incident coronary heart disease in Cardiovascular Health Study. The Ile27Leu and Ser486Asn variants were 3-fold less common in AA than in EA. There was little evidence of association between HNF1A genotype and atherosclerosis-related phenotypes in AA.

CONCLUSIONS: Common polymorphisms of HNF1A seem to influence multiple phenotypes related to cardiovascular risk in the general population of younger and older EA adults.

}, keywords = {Adolescent, Adult, African Americans, Aged, Aged, 80 and over, C-Reactive Protein, Cardiovascular Diseases, Cholesterol, LDL, Cohort Studies, European Continental Ancestry Group, Female, Fibrinogen, gamma-Glutamyltransferase, Genetic Predisposition to Disease, Genotype, Hepatocyte Nuclear Factor 1-alpha, Humans, Male, Middle Aged, Phenotype, Polymorphism, Single Nucleotide, Risk Factors}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.108.839506}, author = {Reiner, Alexander P and Gross, Myron D and Carlson, Christopher S and Bielinski, Suzette J and Lange, Leslie A and Fornage, Myriam and Jenny, Nancy S and Walston, Jeremy and Tracy, Russell P and Williams, O Dale and Jacobs, David R and Nickerson, Deborah A} } @article {1108, title = {Genetic variants associated with cardiac structure and function: a meta-analysis and replication of genome-wide association data.}, journal = {JAMA}, volume = {302}, year = {2009}, month = {2009 Jul 08}, pages = {168-78}, abstract = {

CONTEXT: Echocardiographic measures of left ventricular (LV) structure and function are heritable phenotypes of cardiovascular disease.

OBJECTIVE: To identify common genetic variants associated with cardiac structure and function by conducting a meta-analysis of genome-wide association data in 5 population-based cohort studies (stage 1) with replication (stage 2) in 2 other community-based samples.

DESIGN, SETTING, AND PARTICIPANTS: Within each of 5 community-based cohorts comprising the EchoGen consortium (stage 1; n = 12 612 individuals of European ancestry; 55\% women, aged 26-95 years; examinations between 1978-2008), we estimated the association between approximately 2.5 million single-nucleotide polymorphisms (SNPs; imputed to the HapMap CEU panel) and echocardiographic traits. In stage 2, SNPs significantly associated with traits in stage 1 were tested for association in 2 other cohorts (n = 4094 people of European ancestry). Using a prespecified P value threshold of 5 x 10(-7) to indicate genome-wide significance, we performed an inverse variance-weighted fixed-effects meta-analysis of genome-wide association data from each cohort.

MAIN OUTCOME MEASURES: Echocardiographic traits: LV mass, internal dimensions, wall thickness, systolic dysfunction, aortic root, and left atrial size.

RESULTS: In stage 1, 16 genetic loci were associated with 5 echocardiographic traits: 1 each with LV internal dimensions and systolic dysfunction, 3 each with LV mass and wall thickness, and 8 with aortic root size. In stage 2, 5 loci replicated (6q22 locus associated with LV diastolic dimensions, explaining <1\% of trait variance; 5q23, 12p12, 12q14, and 17p13 associated with aortic root size, explaining 1\%-3\% of trait variance).

CONCLUSIONS: We identified 5 genetic loci harboring common variants that were associated with variation in LV diastolic dimensions and aortic root size, but such findings explained a very small proportion of variance. Further studies are required to replicate these findings, identify the causal variants at or near these loci, characterize their functional significance, and determine whether they are related to overt cardiovascular disease.

}, keywords = {Adult, Aged, Aged, 80 and over, Aorta, Cardiovascular Diseases, Echocardiography, European Continental Ancestry Group, Female, Genome-Wide Association Study, Genotype, Heart Atria, Heart Ventricles, Humans, Male, Middle Aged, Organ Size, Phenotype, Polymorphism, Single Nucleotide, Risk Factors, Ventricular Dysfunction, Left, Ventricular Function, Left}, issn = {1538-3598}, doi = {10.1001/jama.2009.978-a}, author = {Vasan, Ramachandran S and Glazer, Nicole L and Felix, Janine F and Lieb, Wolfgang and Wild, Philipp S and Felix, Stephan B and Watzinger, Norbert and Larson, Martin G and Smith, Nicholas L and Dehghan, Abbas and Grosshennig, Anika and Schillert, Arne and Teumer, Alexander and Schmidt, Reinhold and Kathiresan, Sekar and Lumley, Thomas and Aulchenko, Yurii S and K{\"o}nig, Inke R and Zeller, Tanja and Homuth, Georg and Struchalin, Maksim and Aragam, Jayashri and Bis, Joshua C and Rivadeneira, Fernando and Erdmann, Jeanette and Schnabel, Renate B and D{\"o}rr, Marcus and Zweiker, Robert and Lind, Lars and Rodeheffer, Richard J and Greiser, Karin Halina and Levy, Daniel and Haritunians, Talin and Deckers, Jaap W and Stritzke, Jan and Lackner, Karl J and V{\"o}lker, Uwe and Ingelsson, Erik and Kullo, Iftikhar and Haerting, Johannes and O{\textquoteright}Donnell, Christopher J and Heckbert, Susan R and Stricker, Bruno H and Ziegler, Andreas and Reffelmann, Thorsten and Redfield, Margaret M and Werdan, Karl and Mitchell, Gary F and Rice, Kenneth and Arnett, Donna K and Hofman, Albert and Gottdiener, John S and Uitterlinden, Andr{\'e} G and Meitinger, Thomas and Blettner, Maria and Friedrich, Nele and Wang, Thomas J and Psaty, Bruce M and van Duijn, Cornelia M and Wichmann, H-Erich and Munzel, Thomas F and Kroemer, Heyo K and Benjamin, Emelia J and Rotter, Jerome I and Witteman, Jacqueline C and Schunkert, Heribert and Schmidt, Helena and V{\"o}lzke, Henry and Blankenberg, Stefan} } @article {1098, title = {Genome-wide association study of blood pressure and hypertension.}, journal = {Nat Genet}, volume = {41}, year = {2009}, month = {2009 Jun}, pages = {677-87}, abstract = {

Blood pressure is a major cardiovascular disease risk factor. To date, few variants associated with interindividual blood pressure variation have been identified and replicated. Here we report results of a genome-wide association study of systolic (SBP) and diastolic (DBP) blood pressure and hypertension in the CHARGE Consortium (n = 29,136), identifying 13 SNPs for SBP, 20 for DBP and 10 for hypertension at P < 4 {\texttimes} 10(-7). The top ten loci for SBP and DBP were incorporated into a risk score; mean BP and prevalence of hypertension increased in relation to the number of risk alleles carried. When ten CHARGE SNPs for each trait were included in a joint meta-analysis with the Global BPgen Consortium (n = 34,433), four CHARGE loci attained genome-wide significance (P < 5 {\texttimes} 10(-8)) for SBP (ATP2B1, CYP17A1, PLEKHA7, SH2B3), six for DBP (ATP2B1, CACNB2, CSK-ULK3, SH2B3, TBX3-TBX5, ULK4) and one for hypertension (ATP2B1). Identifying genes associated with blood pressure advances our understanding of blood pressure regulation and highlights potential drug targets for the prevention or treatment of hypertension.

}, keywords = {Blood Pressure, Cell Line, Chromosome Mapping, Chromosomes, Human, Diastole, Gene Expression Regulation, Genetic Association Studies, Genome-Wide Association Study, Humans, Hypertension, Liver, Lymphocytes, Meta-Analysis as Topic, Odds Ratio, Phenotype, Prevalence, Risk Assessment, Systole}, issn = {1546-1718}, doi = {10.1038/ng.384}, author = {Levy, Daniel and Ehret, Georg B and Rice, Kenneth and Verwoert, Germaine C and Launer, Lenore J and Dehghan, Abbas and Glazer, Nicole L and Morrison, Alanna C and Johnson, Andrew D and Aspelund, Thor and Aulchenko, Yurii and Lumley, Thomas and K{\"o}ttgen, Anna and Vasan, Ramachandran S and Rivadeneira, Fernando and Eiriksdottir, Gudny and Guo, Xiuqing and Arking, Dan E and Mitchell, Gary F and Mattace-Raso, Francesco U S and Smith, Albert V and Taylor, Kent and Scharpf, Robert B and Hwang, Shih-Jen and Sijbrands, Eric J G and Bis, Joshua and Harris, Tamara B and Ganesh, Santhi K and O{\textquoteright}Donnell, Christopher J and Hofman, Albert and Rotter, Jerome I and Coresh, Josef and Benjamin, Emelia J and Uitterlinden, Andr{\'e} G and Heiss, Gerardo and Fox, Caroline S and Witteman, Jacqueline C M and Boerwinkle, Eric and Wang, Thomas J and Gudnason, Vilmundur and Larson, Martin G and Chakravarti, Aravinda and Psaty, Bruce M and van Duijn, Cornelia M} } @article {1081, title = {Inflammation and stress-related candidate genes, plasma interleukin-6 levels, and longevity in older adults.}, journal = {Exp Gerontol}, volume = {44}, year = {2009}, month = {2009 May}, pages = {350-5}, abstract = {

Interleukin-6 (IL-6) is an inflammatory cytokine that influences the development of inflammatory and aging-related disorders and ultimately longevity. In order to study the influence of variants in genes that regulate inflammatory response on IL-6 levels and longevity, we screened a panel of 477 tag SNPs across 87 candidate genes in >5000 older participants from the population-based Cardiovascular Health Study (CHS). Baseline plasma IL-6 concentration was first confirmed as a strong predictor of all-cause mortality. Functional alleles of the IL6R and PARP1 genes were significantly associated with 15\%-20\% higher baseline IL-6 concentration per copy among CHS European-American (EA) participants (all p<10(-4)). In a case/control analysis nested within this EA cohort, the minor allele of PARP1 rs1805415 was nominally associated with decreased longevity (p=0.001), but there was no evidence of association between IL6R genotype and longevity. The PARP1 rs1805415--longevity association was subsequently replicated in one of two independent case/control studies. In a pooled analysis of all three studies, the "risk" of longevity associated with the minor allele of PARP1 rs1805415 was 0.79 (95\%CI 0.62-1.02; p=0.07). These findings warrant further study of the potential role of PARP1 genotype in inflammatory and aging-related phenotypes.

}, keywords = {Aged, Aged, 80 and over, Aging, Cardiovascular Diseases, Case-Control Studies, Female, Genetic Variation, Genotype, Humans, Inflammation, Interleukin-6, Longevity, Male, Phenotype, Poly (ADP-Ribose) Polymerase-1, Poly(ADP-ribose) Polymerases, Risk Factors}, issn = {1873-6815}, doi = {10.1016/j.exger.2009.02.004}, author = {Walston, Jeremy D and Matteini, Amy M and Nievergelt, Caroline and Lange, Leslie A and Fallin, Dani M and Barzilai, Nir and Ziv, Elad and Pawlikowska, Ludmila and Kwok, Pui and Cummings, Steve R and Kooperberg, Charles and LaCroix, Andrea and Tracy, Russell P and Atzmon, Gil and Lange, Ethan M and Reiner, Alex P} } @article {1141, title = {Multiple loci influence erythrocyte phenotypes in the CHARGE Consortium.}, journal = {Nat Genet}, volume = {41}, year = {2009}, month = {2009 Nov}, pages = {1191-8}, abstract = {

Measurements of erythrocytes within the blood are important clinical traits and can indicate various hematological disorders. We report here genome-wide association studies (GWAS) for six erythrocyte traits, including hemoglobin concentration (Hb), hematocrit (Hct), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC) and red blood cell count (RBC). We performed an initial GWAS in cohorts of the CHARGE Consortium totaling 24,167 individuals of European ancestry and replication in additional independent cohorts of the HaemGen Consortium totaling 9,456 individuals. We identified 23 loci significantly associated with these traits in a meta-analysis of the discovery and replication cohorts (combined P values ranging from 5 x 10(-8) to 7 x 10(-86)). Our findings include loci previously associated with these traits (HBS1L-MYB, HFE, TMPRSS6, TFR2, SPTA1) as well as new associations (EPO, TFRC, SH2B3 and 15 other loci). This study has identified new determinants of erythrocyte traits, offering insight into common variants underlying variation in erythrocyte measures.

}, keywords = {Blood Pressure, Cell Line, Cohort Studies, Endothelial Cells, Erythrocytes, Gene Expression, Genome, Human, Genome-Wide Association Study, Humans, Hypertension, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci}, issn = {1546-1718}, doi = {10.1038/ng.466}, author = {Ganesh, Santhi K and Zakai, Neil A and van Rooij, Frank J A and Soranzo, Nicole and Smith, Albert V and Nalls, Michael A and Chen, Ming-Huei and K{\"o}ttgen, Anna and Glazer, Nicole L and Dehghan, Abbas and Kuhnel, Brigitte and Aspelund, Thor and Yang, Qiong and Tanaka, Toshiko and Jaffe, Andrew and Bis, Joshua C M and Verwoert, Germaine C and Teumer, Alexander and Fox, Caroline S and Guralnik, Jack M and Ehret, Georg B and Rice, Kenneth and Felix, Janine F and Rendon, Augusto and Eiriksdottir, Gudny and Levy, Daniel and Patel, Kushang V and Boerwinkle, Eric and Rotter, Jerome I and Hofman, Albert and Sambrook, Jennifer G and Hernandez, Dena G and Zheng, Gang and Bandinelli, Stefania and Singleton, Andrew B and Coresh, Josef and Lumley, Thomas and Uitterlinden, Andr{\'e} G and Vangils, Janine M and Launer, Lenore J and Cupples, L Adrienne and Oostra, Ben A and Zwaginga, Jaap-Jan and Ouwehand, Willem H and Thein, Swee-Lay and Meisinger, Christa and Deloukas, Panos and Nauck, Matthias and Spector, Tim D and Gieger, Christian and Gudnason, Vilmundur and van Duijn, Cornelia M and Psaty, Bruce M and Ferrucci, Luigi and Chakravarti, Aravinda and Greinacher, Andreas and O{\textquoteright}Donnell, Christopher J and Witteman, Jacqueline C M and Furth, Susan and Cushman, Mary and Harris, Tamara B and Lin, Jing-Ping} } @article {1171, title = {Bayesian methods for meta-analysis of causal relationships estimated using genetic instrumental variables.}, journal = {Stat Med}, volume = {29}, year = {2010}, month = {2010 May 30}, pages = {1298-311}, abstract = {

Genetic markers can be used as instrumental variables, in an analogous way to randomization in a clinical trial, to estimate the causal relationship between a phenotype and an outcome variable. Our purpose is to extend the existing methods for such Mendelian randomization studies to the context of multiple genetic markers measured in multiple studies, based on the analysis of individual participant data. First, for a single genetic marker in one study, we show that the usual ratio of coefficients approach can be reformulated as a regression with heterogeneous error in the explanatory variable. This can be implemented using a Bayesian approach, which is next extended to include multiple genetic markers. We then propose a hierarchical model for undertaking a meta-analysis of multiple studies, in which it is not necessary that the same genetic markers are measured in each study. This provides an overall estimate of the causal relationship between the phenotype and the outcome, and an assessment of its heterogeneity across studies. As an example, we estimate the causal relationship of blood concentrations of C-reactive protein on fibrinogen levels using data from 11 studies. These methods provide a flexible framework for efficient estimation of causal relationships derived from multiple studies. Issues discussed include weak instrument bias, analysis of binary outcome data such as disease risk, missing genetic data, and the use of haplotypes.

}, keywords = {Bayes Theorem, Biostatistics, C-Reactive Protein, Fibrinogen, Genetic Markers, Humans, Meta-Analysis as Topic, Models, Statistical, Phenotype, Polymorphism, Single Nucleotide}, issn = {1097-0258}, doi = {10.1002/sim.3843}, author = {Burgess, Stephen and Thompson, Simon G and Burgess, S and Thompson, S G and Andrews, G and Samani, N J and Hall, A and Whincup, P and Morris, R and Lawlor, D A and Davey Smith, G and Timpson, N and Ebrahim, S and Ben-Shlomo, Y and Davey Smith, G and Timpson, N and Brown, M and Ricketts, S and Sandhu, M and Reiner, A and Psaty, B and Lange, L and Cushman, M and Hung, J and Thompson, P and Beilby, J and Warrington, N and Palmer, L J and Nordestgaard, B G and Tybjaerg-Hansen, A and Zacho, J and Wu, C and Lowe, G and Tzoulaki, I and Kumari, M and Sandhu, M and Yamamoto, J F and Chiodini, B and Franzosi, M and Hankey, G J and Jamrozik, K and Palmer, L and Rimm, E and Pai, J and Psaty, B and Heckbert, S and Bis, J and Anand, S and Engert, J and Collins, R and Clarke, R and Melander, O and Berglund, G and Ladenvall, P and Johansson, L and Jansson, J-H and Hallmans, G and Hingorani, A and Humphries, S and Rimm, E and Manson, J and Pai, J and Watkins, H and Clarke, R and Hopewell, J and Saleheen, D and Frossard, R and Danesh, J and Sattar, N and Robertson, M and Shepherd, J and Schaefer, E and Hofman, A and Witteman, J C M and Kardys, I and Ben-Shlomo, Y and Davey Smith, G and Timpson, N and de Faire, U and Bennet, A and Sattar, N and Ford, I and Packard, C and Kumari, M and Manson, J and Lawlor, Debbie A and Davey Smith, George and Anand, S and Collins, R and Casas, J P and Danesh, J and Davey Smith, G and Franzosi, M and Hingorani, A and Lawlor, D A and Manson, J and Nordestgaard, B G and Samani, N J and Sandhu, M and Smeeth, L and Wensley, F and Anand, S and Bowden, J and Burgess, S and Casas, J P and Di Angelantonio, E and Engert, J and Gao, P and Shah, T and Smeeth, L and Thompson, S G and Verzilli, C and Walker, M and Whittaker, J and Hingorani, A and Danesh, J} } @article {1221, title = {Biological, clinical and population relevance of 95 loci for blood lipids.}, journal = {Nature}, volume = {466}, year = {2010}, month = {2010 Aug 05}, pages = {707-13}, abstract = {

Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.

}, keywords = {African Americans, Animals, Asian Continental Ancestry Group, Cholesterol, HDL, Cholesterol, LDL, Coronary Artery Disease, Europe, European Continental Ancestry Group, Female, Genetic Loci, Genome-Wide Association Study, Genotype, Humans, Lipid Metabolism, Lipids, Liver, Male, Mice, N-Acetylgalactosaminyltransferases, Phenotype, Polymorphism, Single Nucleotide, Protein Phosphatase 1, Reproducibility of Results, Triglycerides}, issn = {1476-4687}, doi = {10.1038/nature09270}, author = {Teslovich, Tanya M and Musunuru, Kiran and Smith, Albert V and Edmondson, Andrew C and Stylianou, Ioannis M and Koseki, Masahiro and Pirruccello, James P and Ripatti, Samuli and Chasman, Daniel I and Willer, Cristen J and Johansen, Christopher T and Fouchier, Sigrid W and Isaacs, Aaron and Peloso, Gina M and Barbalic, Maja and Ricketts, Sally L and Bis, Joshua C and Aulchenko, Yurii S and Thorleifsson, Gudmar and Feitosa, Mary F and Chambers, John and Orho-Melander, Marju and Melander, Olle and Johnson, Toby and Li, Xiaohui and Guo, Xiuqing and Li, Mingyao and Shin Cho, Yoon and Jin Go, Min and Jin Kim, Young and Lee, Jong-Young and Park, Taesung and Kim, Kyunga and Sim, Xueling and Twee-Hee Ong, Rick and Croteau-Chonka, Damien C and Lange, Leslie A and Smith, Joshua D and Song, Kijoung and Hua Zhao, Jing and Yuan, Xin and Luan, Jian{\textquoteright}an and Lamina, Claudia and Ziegler, Andreas and Zhang, Weihua and Zee, Robert Y L and Wright, Alan F and Witteman, Jacqueline C M and Wilson, James F and Willemsen, Gonneke and Wichmann, H-Erich and Whitfield, John B and Waterworth, Dawn M and Wareham, Nicholas J and Waeber, G{\'e}rard and Vollenweider, Peter and Voight, Benjamin F and Vitart, Veronique and Uitterlinden, Andr{\'e} G and Uda, Manuela and Tuomilehto, Jaakko and Thompson, John R and Tanaka, Toshiko and Surakka, Ida and Stringham, Heather M and Spector, Tim D and Soranzo, Nicole and Smit, Johannes H and Sinisalo, Juha and Silander, Kaisa and Sijbrands, Eric J G and Scuteri, Angelo and Scott, James and Schlessinger, David and Sanna, Serena and Salomaa, Veikko and Saharinen, Juha and Sabatti, Chiara and Ruokonen, Aimo and Rudan, Igor and Rose, Lynda M and Roberts, Robert and Rieder, Mark and Psaty, Bruce M and Pramstaller, Peter P and Pichler, Irene and Perola, Markus and Penninx, Brenda W J H and Pedersen, Nancy L and Pattaro, Cristian and Parker, Alex N and Par{\'e}, Guillaume and Oostra, Ben A and O{\textquoteright}Donnell, Christopher J and Nieminen, Markku S and Nickerson, Deborah A and Montgomery, Grant W and Meitinger, Thomas and McPherson, Ruth and McCarthy, Mark I and McArdle, Wendy and Masson, David and Martin, Nicholas G and Marroni, Fabio and Mangino, Massimo and Magnusson, Patrik K E and Lucas, Gavin and Luben, Robert and Loos, Ruth J F and Lokki, Marja-Liisa and Lettre, Guillaume and Langenberg, Claudia and Launer, Lenore J and Lakatta, Edward G and Laaksonen, Reijo and Kyvik, Kirsten O and Kronenberg, Florian and K{\"o}nig, Inke R and Khaw, Kay-Tee and Kaprio, Jaakko and Kaplan, Lee M and Johansson, Asa and Jarvelin, Marjo-Riitta and Janssens, A Cecile J W and Ingelsson, Erik and Igl, Wilmar and Kees Hovingh, G and Hottenga, Jouke-Jan and Hofman, Albert and Hicks, Andrew A and Hengstenberg, Christian and Heid, Iris M and Hayward, Caroline and Havulinna, Aki S and Hastie, Nicholas D and Harris, Tamara B and Haritunians, Talin and Hall, Alistair S and Gyllensten, Ulf and Guiducci, Candace and Groop, Leif C and Gonzalez, Elena and Gieger, Christian and Freimer, Nelson B and Ferrucci, Luigi and Erdmann, Jeanette and Elliott, Paul and Ejebe, Kenechi G and D{\"o}ring, Angela and Dominiczak, Anna F and Demissie, Serkalem and Deloukas, Panagiotis and de Geus, Eco J C and de Faire, Ulf and Crawford, Gabriel and Collins, Francis S and Chen, Yii-der I and Caulfield, Mark J and Campbell, Harry and Burtt, Noel P and Bonnycastle, Lori L and Boomsma, Dorret I and Boekholdt, S Matthijs and Bergman, Richard N and Barroso, In{\^e}s and Bandinelli, Stefania and Ballantyne, Christie M and Assimes, Themistocles L and Quertermous, Thomas and Altshuler, David and Seielstad, Mark and Wong, Tien Y and Tai, E-Shyong and Feranil, Alan B and Kuzawa, Christopher W and Adair, Linda S and Taylor, Herman A and Borecki, Ingrid B and Gabriel, Stacey B and Wilson, James G and Holm, Hilma and Thorsteinsdottir, Unnur and Gudnason, Vilmundur and Krauss, Ronald M and Mohlke, Karen L and Ordovas, Jose M and Munroe, Patricia B and Kooner, Jaspal S and Tall, Alan R and Hegele, Robert A and Kastelein, John J P and Schadt, Eric E and Rotter, Jerome I and Boerwinkle, Eric and Strachan, David P and Mooser, Vincent and Stefansson, Kari and Reilly, Muredach P and Samani, Nilesh J and Schunkert, Heribert and Cupples, L Adrienne and Sandhu, Manjinder S and Ridker, Paul M and Rader, Daniel J and van Duijn, Cornelia M and Peltonen, Leena and Abecasis, Goncalo R and Boehnke, Michael and Kathiresan, Sekar} } @article {1188, title = {Candidate gene association resource (CARe): design, methods, and proof of concept.}, journal = {Circ Cardiovasc Genet}, volume = {3}, year = {2010}, month = {2010 Jun}, pages = {267-75}, abstract = {

BACKGROUND: The National Heart, Lung, and Blood Institute{\textquoteright}s Candidate Gene Association Resource (CARe), a planned cross-cohort analysis of genetic variation in cardiovascular, pulmonary, hematologic, and sleep-related traits, comprises >40,000 participants representing 4 ethnic groups in 9 community-based cohorts. The goals of CARe include the discovery of new variants associated with traits using a candidate gene approach and the discovery of new variants using the genome-wide association mapping approach specifically in African Americans.

METHODS AND RESULTS: CARe has assembled DNA samples for >40,000 individuals self-identified as European American, African American, Hispanic, or Chinese American, with accompanying data on hundreds of phenotypes that have been standardized and deposited in the CARe Phenotype Database. All participants were genotyped for 7 single-nucleotide polymorphisms (SNPs) selected based on prior association evidence. We performed association analyses relating each of these SNPs to lipid traits, stratified by sex and ethnicity, and adjusted for age and age squared. In at least 2 of the ethnic groups, SNPs near CETP, LIPC, and LPL strongly replicated for association with high-density lipoprotein cholesterol concentrations, PCSK9 with low-density lipoprotein cholesterol levels, and LPL and APOA5 with serum triglycerides. Notably, some SNPs showed varying effect sizes and significance of association in different ethnic groups.

CONCLUSIONS: The CARe Pilot Study validates the operational framework for phenotype collection, SNP genotyping, and analytic pipeline of the CARe project and validates the planned candidate gene study of approximately 2000 biological candidate loci in all participants and genome-wide association study in approximately 8000 African American participants. CARe will serve as a valuable resource for the scientific community.

}, keywords = {African Americans, Cholesterol, HDL, Cholesterol, LDL, Cohort Studies, Databases, Genetic, European Continental Ancestry Group, Genetic Association Studies, Genotype, Humans, Phenotype, Pilot Projects, Polymorphism, Single Nucleotide, Research Design, Triglycerides}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.109.882696}, author = {Musunuru, Kiran and Lettre, Guillaume and Young, Taylor and Farlow, Deborah N and Pirruccello, James P and Ejebe, Kenechi G and Keating, Brendan J and Yang, Qiong and Chen, Ming-Huei and Lapchyk, Nina and Crenshaw, Andrew and Ziaugra, Liuda and Rachupka, Anthony and Benjamin, Emelia J and Cupples, L Adrienne and Fornage, Myriam and Fox, Ervin R and Heckbert, Susan R and Hirschhorn, Joel N and Newton-Cheh, Christopher and Nizzari, Marcia M and Paltoo, Dina N and Papanicolaou, George J and Patel, Sanjay R and Psaty, Bruce M and Rader, Daniel J and Redline, Susan and Rich, Stephen S and Rotter, Jerome I and Taylor, Herman A and Tracy, Russell P and Vasan, Ramachandran S and Wilson, James G and Kathiresan, Sekar and Fabsitz, Richard R and Boerwinkle, Eric and Gabriel, Stacey B} } @article {1191, title = {Genome-wide meta-analyses identify multiple loci associated with smoking behavior.}, journal = {Nat Genet}, volume = {42}, year = {2010}, month = {2010 May}, pages = {441-7}, abstract = {

Consistent but indirect evidence has implicated genetic factors in smoking behavior. We report meta-analyses of several smoking phenotypes within cohorts of the Tobacco and Genetics Consortium (n = 74,053). We also partnered with the European Network of Genetic and Genomic Epidemiology (ENGAGE) and Oxford-GlaxoSmithKline (Ox-GSK) consortia to follow up the 15 most significant regions (n > 140,000). We identified three loci associated with number of cigarettes smoked per day. The strongest association was a synonymous 15q25 SNP in the nicotinic receptor gene CHRNA3 (rs1051730[A], beta = 1.03, standard error (s.e.) = 0.053, P = 2.8 x 10(-73)). Two 10q25 SNPs (rs1329650[G], beta = 0.367, s.e. = 0.059, P = 5.7 x 10(-10); and rs1028936[A], beta = 0.446, s.e. = 0.074, P = 1.3 x 10(-9)) and one 9q13 SNP in EGLN2 (rs3733829[G], beta = 0.333, s.e. = 0.058, P = 1.0 x 10(-8)) also exceeded genome-wide significance for cigarettes per day. For smoking initiation, eight SNPs exceeded genome-wide significance, with the strongest association at a nonsynonymous SNP in BDNF on chromosome 11 (rs6265[C], odds ratio (OR) = 1.06, 95\% confidence interval (Cl) 1.04-1.08, P = 1.8 x 10(-8)). One SNP located near DBH on chromosome 9 (rs3025343[G], OR = 1.12, 95\% Cl 1.08-1.18, P = 3.6 x 10(-8)) was significantly associated with smoking cessation.

}, keywords = {Age Factors, Alleles, Chromosome Mapping, Female, Genome, Genome-Wide Association Study, Genotype, Humans, Male, Molecular Epidemiology, Odds Ratio, Phenotype, Polymorphism, Single Nucleotide, Receptors, Nicotinic, Smoking}, issn = {1546-1718}, doi = {10.1038/ng.571} } @article {1234, title = {Hundreds of variants clustered in genomic loci and biological pathways affect human height.}, journal = {Nature}, volume = {467}, year = {2010}, month = {2010 Oct 14}, pages = {832-8}, abstract = {

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10\% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16\% of phenotypic variation (approximately 20\% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

}, keywords = {Body Height, Chromosomes, Human, Pair 3, Genetic Loci, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Metabolic Networks and Pathways, Multifactorial Inheritance, Phenotype, Polymorphism, Single Nucleotide}, issn = {1476-4687}, doi = {10.1038/nature09410}, author = {Lango Allen, Hana and Estrada, Karol and Lettre, Guillaume and Berndt, Sonja I and Weedon, Michael N and Rivadeneira, Fernando and Willer, Cristen J and Jackson, Anne U and Vedantam, Sailaja and Raychaudhuri, Soumya and Ferreira, Teresa and Wood, Andrew R and Weyant, Robert J and Segr{\`e}, Ayellet V and Speliotes, Elizabeth K and Wheeler, Eleanor and Soranzo, Nicole and Park, Ju-Hyun and Yang, Jian and Gudbjartsson, Daniel and Heard-Costa, Nancy L and Randall, Joshua C and Qi, Lu and Vernon Smith, Albert and M{\"a}gi, Reedik and Pastinen, Tomi and Liang, Liming and Heid, Iris M and Luan, Jian{\textquoteright}an and Thorleifsson, Gudmar and Winkler, Thomas W and Goddard, Michael E and Sin Lo, Ken and Palmer, Cameron and Workalemahu, Tsegaselassie and Aulchenko, Yurii S and Johansson, Asa and Zillikens, M Carola and Feitosa, Mary F and Esko, T{\~o}nu and Johnson, Toby and Ketkar, Shamika and Kraft, Peter and Mangino, Massimo and Prokopenko, Inga and Absher, Devin and Albrecht, Eva and Ernst, Florian and Glazer, Nicole L and Hayward, Caroline and Hottenga, Jouke-Jan and Jacobs, Kevin B and Knowles, Joshua W and Kutalik, Zolt{\'a}n and Monda, Keri L and Polasek, Ozren and Preuss, Michael and Rayner, Nigel W and Robertson, Neil R and Steinthorsdottir, Valgerdur and Tyrer, Jonathan P and Voight, Benjamin F and Wiklund, Fredrik and Xu, Jianfeng and Zhao, Jing Hua and Nyholt, Dale R and Pellikka, Niina and Perola, Markus and Perry, John R B and Surakka, Ida and Tammesoo, Mari-Liis and Altmaier, Elizabeth L and Amin, Najaf and Aspelund, Thor and Bhangale, Tushar and Boucher, Gabrielle and Chasman, Daniel I and Chen, Constance and Coin, Lachlan and Cooper, Matthew N and Dixon, Anna L and Gibson, Quince and Grundberg, Elin and Hao, Ke and Juhani Junttila, M and Kaplan, Lee M and Kettunen, Johannes and K{\"o}nig, Inke R and Kwan, Tony and Lawrence, Robert W and Levinson, Douglas F and Lorentzon, Mattias and McKnight, Barbara and Morris, Andrew P and M{\"u}ller, Martina and Suh Ngwa, Julius and Purcell, Shaun and Rafelt, Suzanne and Salem, Rany M and Salvi, Erika and Sanna, Serena and Shi, Jianxin and Sovio, Ulla and Thompson, John R and Turchin, Michael C and Vandenput, Liesbeth and Verlaan, Dominique J and Vitart, Veronique and White, Charles C and Ziegler, Andreas and Almgren, Peter and Balmforth, Anthony J and Campbell, Harry and Citterio, Lorena and De Grandi, Alessandro and Dominiczak, Anna and Duan, Jubao and Elliott, Paul and Elosua, Roberto and Eriksson, Johan G and Freimer, Nelson B and Geus, Eco J C and Glorioso, Nicola and Haiqing, Shen and Hartikainen, Anna-Liisa and Havulinna, Aki S and Hicks, Andrew A and Hui, Jennie and Igl, Wilmar and Illig, Thomas and Jula, Antti and Kajantie, Eero and Kilpel{\"a}inen, Tuomas O and Koiranen, Markku and Kolcic, Ivana and Koskinen, Seppo and Kovacs, Peter and Laitinen, Jaana and Liu, Jianjun and Lokki, Marja-Liisa and Marusic, Ana and Maschio, Andrea and Meitinger, Thomas and Mulas, Antonella and Par{\'e}, Guillaume and Parker, Alex N and Peden, John F and Petersmann, Astrid and Pichler, Irene and Pietil{\"a}inen, Kirsi H and Pouta, Anneli and Ridderstr{\r a}le, Martin and Rotter, Jerome I and Sambrook, Jennifer G and Sanders, Alan R and Schmidt, Carsten Oliver and Sinisalo, Juha and Smit, Jan H and Stringham, Heather M and Bragi Walters, G and Widen, Elisabeth and Wild, Sarah H and Willemsen, Gonneke and Zagato, Laura and Zgaga, Lina and Zitting, Paavo and Alavere, Helene and Farrall, Martin and McArdle, Wendy L and Nelis, Mari and Peters, Marjolein J and Ripatti, Samuli and van Meurs, Joyce B J and Aben, Katja K and Ardlie, Kristin G and Beckmann, Jacques S and Beilby, John P and Bergman, Richard N and Bergmann, Sven and Collins, Francis S and Cusi, Daniele and den Heijer, Martin and Eiriksdottir, Gudny and Gejman, Pablo V and Hall, Alistair S and Hamsten, Anders and Huikuri, Heikki V and Iribarren, Carlos and K{\"a}h{\"o}nen, Mika and Kaprio, Jaakko and Kathiresan, Sekar and Kiemeney, Lambertus and Kocher, Thomas and Launer, Lenore J and Lehtim{\"a}ki, Terho and Melander, Olle and Mosley, Tom H and Musk, Arthur W and Nieminen, Markku S and O{\textquoteright}Donnell, Christopher J and Ohlsson, Claes and Oostra, Ben and Palmer, Lyle J and Raitakari, Olli and Ridker, Paul M and Rioux, John D and Rissanen, Aila and Rivolta, Carlo and Schunkert, Heribert and Shuldiner, Alan R and Siscovick, David S and Stumvoll, Michael and T{\"o}njes, Anke and Tuomilehto, Jaakko and van Ommen, Gert-Jan and Viikari, Jorma and Heath, Andrew C and Martin, Nicholas G and Montgomery, Grant W and Province, Michael A and Kayser, Manfred and Arnold, Alice M and Atwood, Larry D and Boerwinkle, Eric and Chanock, Stephen J and Deloukas, Panos and Gieger, Christian and Gr{\"o}nberg, Henrik and Hall, Per and Hattersley, Andrew T and Hengstenberg, Christian and Hoffman, Wolfgang and Lathrop, G Mark and Salomaa, Veikko and Schreiber, Stefan and Uda, Manuela and Waterworth, Dawn and Wright, Alan F and Assimes, Themistocles L and Barroso, In{\^e}s and Hofman, Albert and Mohlke, Karen L and Boomsma, Dorret I and Caulfield, Mark J and Cupples, L Adrienne and Erdmann, Jeanette and Fox, Caroline S and Gudnason, Vilmundur and Gyllensten, Ulf and Harris, Tamara B and Hayes, Richard B and Jarvelin, Marjo-Riitta and Mooser, Vincent and Munroe, Patricia B and Ouwehand, Willem H and Penninx, Brenda W and Pramstaller, Peter P and Quertermous, Thomas and Rudan, Igor and Samani, Nilesh J and Spector, Timothy D and V{\"o}lzke, Henry and Watkins, Hugh and Wilson, James F and Groop, Leif C and Haritunians, Talin and Hu, Frank B and Kaplan, Robert C and Metspalu, Andres and North, Kari E and Schlessinger, David and Wareham, Nicholas J and Hunter, David J and O{\textquoteright}Connell, Jeffrey R and Strachan, David P and Wichmann, H-Erich and Borecki, Ingrid B and van Duijn, Cornelia M and Schadt, Eric E and Thorsteinsdottir, Unnur and Peltonen, Leena and Uitterlinden, Andr{\'e} G and Visscher, Peter M and Chatterjee, Nilanjan and Loos, Ruth J F and Boehnke, Michael and McCarthy, Mark I and Ingelsson, Erik and Lindgren, Cecilia M and Abecasis, Goncalo R and Stefansson, Kari and Frayling, Timothy M and Hirschhorn, Joel N} } @article {1176, title = {Novel associations of multiple genetic loci with plasma levels of factor VII, factor VIII, and von Willebrand factor: The CHARGE (Cohorts for Heart and Aging Research in Genome Epidemiology) Consortium.}, journal = {Circulation}, volume = {121}, year = {2010}, month = {2010 Mar 30}, pages = {1382-92}, abstract = {

BACKGROUND: Plasma levels of coagulation factors VII (FVII), VIII (FVIII), and von Willebrand factor (vWF) influence risk of hemorrhage and thrombosis. We conducted genome-wide association studies to identify new loci associated with plasma levels.

METHODS AND RESULTS: The setting of the study included 5 community-based studies for discovery comprising 23 608 European-ancestry participants: Atherosclerosis Risk In Communities Study, Cardiovascular Health Study, British 1958 Birth Cohort, Framingham Heart Study, and Rotterdam Study. All subjects had genome-wide single-nucleotide polymorphism (SNP) scans and at least 1 phenotype measured: FVII activity/antigen, FVIII activity, and vWF antigen. Each study used its genotype data to impute to HapMap SNPs and independently conducted association analyses of hemostasis measures using an additive genetic model. Study findings were combined by meta-analysis. Replication was conducted in 7604 participants not in the discovery cohort. For FVII, 305 SNPs exceeded the genome-wide significance threshold of 5.0x10(-8) and comprised 5 loci on 5 chromosomes: 2p23 (smallest P value 6.2x10(-24)), 4q25 (3.6x10(-12)), 11q12 (2.0x10(-10)), 13q34 (9.0x10(-259)), and 20q11.2 (5.7x10(-37)). Loci were within or near genes, including 4 new candidate genes and F7 (13q34). For vWF, 400 SNPs exceeded the threshold and marked 8 loci on 6 chromosomes: 6q24 (1.2x10(-22)), 8p21 (1.3x10(-16)), 9q34 (<5.0x10(-324)), 12p13 (1.7x10(-32)), 12q23 (7.3x10(-10)), 12q24.3 (3.8x10(-11)), 14q32 (2.3x10(-10)), and 19p13.2 (1.3x10(-9)). All loci were within genes, including 6 new candidate genes, as well as ABO (9q34) and VWF (12p13). For FVIII, 5 loci were identified and overlapped vWF findings. Nine of the 10 new findings were replicated.

CONCLUSIONS: New genetic associations were discovered outside previously known biological pathways and may point to novel prevention and treatment targets of hemostasis disorders.

}, keywords = {Adult, Factor VII, Factor VIII, Female, Genome-Wide Association Study, Hemostasis, Humans, Male, Middle Aged, Phenotype, Polymorphism, Single Nucleotide, Thrombosis, von Willebrand Factor}, issn = {1524-4539}, doi = {10.1161/CIRCULATIONAHA.109.869156}, author = {Smith, Nicholas L and Chen, Ming-Huei and Dehghan, Abbas and Strachan, David P and Basu, Saonli and Soranzo, Nicole and Hayward, Caroline and Rudan, Igor and Sabater-Lleal, Maria and Bis, Joshua C and de Maat, Moniek P M and Rumley, Ann and Kong, Xiaoxiao and Yang, Qiong and Williams, Frances M K and Vitart, Veronique and Campbell, Harry and M{\"a}larstig, Anders and Wiggins, Kerri L and van Duijn, Cornelia M and McArdle, Wendy L and Pankow, James S and Johnson, Andrew D and Silveira, Angela and McKnight, Barbara and Uitterlinden, Andr{\'e} G and Aleksic, Nena and Meigs, James B and Peters, Annette and Koenig, Wolfgang and Cushman, Mary and Kathiresan, Sekar and Rotter, Jerome I and Bovill, Edwin G and Hofman, Albert and Boerwinkle, Eric and Tofler, Geoffrey H and Peden, John F and Psaty, Bruce M and Leebeek, Frank and Folsom, Aaron R and Larson, Martin G and Spector, Timothy D and Wright, Alan F and Wilson, James F and Hamsten, Anders and Lumley, Thomas and Witteman, Jacqueline C M and Tang, Weihong and O{\textquoteright}Donnell, Christopher J} } @article {1273, title = {Association of genetic variation with systolic and diastolic blood pressure among African Americans: the Candidate Gene Association Resource study.}, journal = {Hum Mol Genet}, volume = {20}, year = {2011}, month = {2011 Jun 01}, pages = {2273-84}, abstract = {

The prevalence of hypertension in African Americans (AAs) is higher than in other US groups; yet, few have performed genome-wide association studies (GWASs) in AA. Among people of European descent, GWASs have identified genetic variants at 13 loci that are associated with blood pressure. It is unknown if these variants confer susceptibility in people of African ancestry. Here, we examined genome-wide and candidate gene associations with systolic blood pressure (SBP) and diastolic blood pressure (DBP) using the Candidate Gene Association Resource (CARe) consortium consisting of 8591 AAs. Genotypes included genome-wide single-nucleotide polymorphism (SNP) data utilizing the Affymetrix 6.0 array with imputation to 2.5 million HapMap SNPs and candidate gene SNP data utilizing a 50K cardiovascular gene-centric array (ITMAT-Broad-CARe [IBC] array). For Affymetrix data, the strongest signal for DBP was rs10474346 (P= 3.6 {\texttimes} 10(-8)) located near GPR98 and ARRDC3. For SBP, the strongest signal was rs2258119 in C21orf91 (P= 4.7 {\texttimes} 10(-8)). The top IBC association for SBP was rs2012318 (P= 6.4 {\texttimes} 10(-6)) near SLC25A42 and for DBP was rs2523586 (P= 1.3 {\texttimes} 10(-6)) near HLA-B. None of the top variants replicated in additional AA (n = 11 882) or European-American (n = 69 899) cohorts. We replicated previously reported European-American blood pressure SNPs in our AA samples (SH2B3, P= 0.009; TBX3-TBX5, P= 0.03; and CSK-ULK3, P= 0.0004). These genetic loci represent the best evidence of genetic influences on SBP and DBP in AAs to date. More broadly, this work supports that notion that blood pressure among AAs is a trait with genetic underpinnings but also with significant complexity.

}, keywords = {Adult, African Americans, Aged, Blood Pressure, Cohort Studies, Diastole, European Continental Ancestry Group, Female, Genetic Loci, Genome-Wide Association Study, Genotype, Humans, Hypertension, Male, Middle Aged, Phenotype, Polymorphism, Single Nucleotide, Systole}, issn = {1460-2083}, doi = {10.1093/hmg/ddr092}, author = {Fox, Ervin R and Young, J Hunter and Li, Yali and Dreisbach, Albert W and Keating, Brendan J and Musani, Solomon K and Liu, Kiang and Morrison, Alanna C and Ganesh, Santhi and Kutlar, Abdullah and Ramachandran, Vasan S and Polak, Josef F and Fabsitz, Richard R and Dries, Daniel L and Farlow, Deborah N and Redline, Susan and Adeyemo, Adebowale and Hirschorn, Joel N and Sun, Yan V and Wyatt, Sharon B and Penman, Alan D and Palmas, Walter and Rotter, Jerome I and Townsend, Raymond R and Doumatey, Ayo P and Tayo, Bamidele O and Mosley, Thomas H and Lyon, Helen N and Kang, Sun J and Rotimi, Charles N and Cooper, Richard S and Franceschini, Nora and Curb, J David and Martin, Lisa W and Eaton, Charles B and Kardia, Sharon L R and Taylor, Herman A and Caulfield, Mark J and Ehret, Georg B and Johnson, Toby and Chakravarti, Aravinda and Zhu, Xiaofeng and Levy, Daniel} } @article {1562, title = {Association of genomic loci from a cardiovascular gene SNP array with fibrinogen levels in European Americans and African-Americans from six cohort studies: the Candidate Gene Association Resource (CARe).}, journal = {Blood}, volume = {117}, year = {2011}, month = {2011 Jan 06}, pages = {268-75}, abstract = {

Several common genomic loci, involving various immunity- and metabolism-related genes, have been associated with plasma fibrinogen in European Americans (EAs). The genetic determinants of fibrinogen in African Americans (AAs) are poorly characterized. Using a vascular gene-centric array in 23,634 EA and 6657 AA participants from 6 studies comprising the Candidate Gene Association Resource project, we examined the association of 47,539 common and lower frequency variants with fibrinogen concentration. We identified a rare Pro265Leu variant in FGB (rs6054) associated with lower fibrinogen. Common fibrinogen gene single nucleotide polymorphisms (FGB rs1800787 and FGG rs2066861) significantly associated with fibrinogen in EAs were prevalent in AAs and showed consistent associations. Several fibrinogen locus single nucleotide polymorphism associated with lower fibrinogen were exclusive to AAs; these include a newly reported association with FGA rs10050257. For IL6R, IL1RN, and NLRP3 inflammatory gene loci, associations with fibrinogen were concordant between EAs and AAs, but not at other loci (CPS1, PCCB, and SCL22A5-IRF1). The association of FGG rs2066861 with fibrinogen differed according to assay type used to measure fibrinogen. Further characterization of common and lower-frequency genetic variants that contribute to interpopulation differences in fibrinogen phenotype may help refine our understanding of the contribution of hemostasis and inflammation to atherothrombotic risk.

}, keywords = {Adult, African Americans, Aged, Cardiovascular Diseases, Cohort Studies, European Continental Ancestry Group, Female, Fibrinogen, Genetic Predisposition to Disease, Haplotypes, Humans, Male, Middle Aged, Phenotype, Polymorphism, Single Nucleotide, Risk Factors}, issn = {1528-0020}, doi = {10.1182/blood-2010-06-289546}, author = {Wassel, Christina L and Lange, Leslie A and Keating, Brendan J and Taylor, Kira C and Johnson, Andrew D and Palmer, Cameron and Ho, Lindsey A and Smith, Nicholas L and Lange, Ethan M and Li, Yun and Yang, Qiong and Delaney, Joseph A and Tang, Weihong and Tofler, Geoffrey and Redline, Susan and Taylor, Herman A and Wilson, James G and Tracy, Russell P and Jacobs, David R and Folsom, Aaron R and Green, David and O{\textquoteright}Donnell, Christopher J and Reiner, Alexander P} } @article {1274, title = {A bivariate genome-wide approach to metabolic syndrome: STAMPEED consortium.}, journal = {Diabetes}, volume = {60}, year = {2011}, month = {2011 Apr}, pages = {1329-39}, abstract = {

OBJECTIVE The metabolic syndrome (MetS) is defined as concomitant disorders of lipid and glucose metabolism, central obesity, and high blood pressure, with an increased risk of type 2 diabetes and cardiovascular disease. This study tests whether common genetic variants with pleiotropic effects account for some of the correlated architecture among five metabolic phenotypes that define MetS. RESEARCH DESIGN AND METHODS Seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, underwent genome-wide association analyses of metabolic traits using a panel of \~{}2.5 million imputed single nucleotide polymorphisms (SNPs). Phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS in pairwise combinations. Individuals exceeding the NCEP thresholds for both traits of a pair were considered affected. RESULTS Twenty-nine common variants were associated with MetS or a pair of traits. Variants in the genes LPL, CETP, APOA5 (and its cluster), GCKR (and its cluster), LIPC, TRIB1, LOC100128354/MTNR1B, ABCB11, and LOC100129150 were further tested for their association with individual qualitative and quantitative traits. None of the 16 top SNPs (one per gene) associated simultaneously with more than two individual traits. Of them 11 variants showed nominal associations with MetS per se. The effects of 16 top SNPs on the quantitative traits were relatively small, together explaining from \~{}9\% of the variance in triglycerides, 5.8\% of high-density lipoprotein cholesterol, 3.6\% of fasting glucose, and 1.4\% of systolic blood pressure. CONCLUSIONS Qualitative and quantitative pleiotropic tests on pairs of traits indicate that a small portion of the covariation in these traits can be explained by the reported common genetic variants.

}, keywords = {Adult, Aged, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Male, Meta-Analysis as Topic, Metabolic Syndrome, Middle Aged, Phenotype, Polymorphism, Single Nucleotide}, issn = {1939-327X}, doi = {10.2337/db10-1011}, author = {Kraja, Aldi T and Vaidya, Dhananjay and Pankow, James S and Goodarzi, Mark O and Assimes, Themistocles L and Kullo, Iftikhar J and Sovio, Ulla and Mathias, Rasika A and Sun, Yan V and Franceschini, Nora and Absher, Devin and Li, Guo and Zhang, Qunyuan and Feitosa, Mary F and Glazer, Nicole L and Haritunians, Talin and Hartikainen, Anna-Liisa and Knowles, Joshua W and North, Kari E and Iribarren, Carlos and Kral, Brian and Yanek, Lisa and O{\textquoteright}Reilly, Paul F and McCarthy, Mark I and Jaquish, Cashell and Couper, David J and Chakravarti, Aravinda and Psaty, Bruce M and Becker, Lewis C and Province, Michael A and Boerwinkle, Eric and Quertermous, Thomas and Palotie, Leena and Jarvelin, Marjo-Riitta and Becker, Diane M and Kardia, Sharon L R and Rotter, Jerome I and Chen, Yii-Der Ida and Borecki, Ingrid B} } @article {1288, title = {Enhanced statistical tests for GWAS in admixed populations: assessment using African Americans from CARe and a Breast Cancer Consortium.}, journal = {PLoS Genet}, volume = {7}, year = {2011}, month = {2011 Apr}, pages = {e1001371}, abstract = {

While genome-wide association studies (GWAS) have primarily examined populations of European ancestry, more recent studies often involve additional populations, including admixed populations such as African Americans and Latinos. In admixed populations, linkage disequilibrium (LD) exists both at a fine scale in ancestral populations and at a coarse scale (admixture-LD) due to chromosomal segments of distinct ancestry. Disease association statistics in admixed populations have previously considered SNP association (LD mapping) or admixture association (mapping by admixture-LD), but not both. Here, we introduce a new statistical framework for combining SNP and admixture association in case-control studies, as well as methods for local ancestry-aware imputation. We illustrate the gain in statistical power achieved by these methods by analyzing data of 6,209 unrelated African Americans from the CARe project genotyped on the Affymetrix 6.0 chip, in conjunction with both simulated and real phenotypes, as well as by analyzing the FGFR2 locus using breast cancer GWAS data from 5,761 African-American women. We show that, at typed SNPs, our method yields an 8\% increase in statistical power for finding disease risk loci compared to the power achieved by standard methods in case-control studies. At imputed SNPs, we observe an 11\% increase in statistical power for mapping disease loci when our local ancestry-aware imputation framework and the new scoring statistic are jointly employed. Finally, we show that our method increases statistical power in regions harboring the causal SNP in the case when the causal SNP is untyped and cannot be imputed. Our methods and our publicly available software are broadly applicable to GWAS in admixed populations.

}, keywords = {African Americans, Algorithms, Breast Neoplasms, Chromosome Mapping, Coronary Disease, Diabetes Mellitus, Type 2, Female, Gene Frequency, Genetic Variation, Genetics, Population, Genome, Human, Genome-Wide Association Study, Genotype, Humans, Linkage Disequilibrium, Male, Odds Ratio, Phenotype, Polymorphism, Single Nucleotide, Principal Component Analysis, Receptor, Fibroblast Growth Factor, Type 2, Software}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1001371}, author = {Pasaniuc, Bogdan and Zaitlen, Noah and Lettre, Guillaume and Chen, Gary K and Tandon, Arti and Kao, W H Linda and Ruczinski, Ingo and Fornage, Myriam and Siscovick, David S and Zhu, Xiaofeng and Larkin, Emma and Lange, Leslie A and Cupples, L Adrienne and Yang, Qiong and Akylbekova, Ermeg L and Musani, Solomon K and Divers, Jasmin and Mychaleckyj, Joe and Li, Mingyao and Papanicolaou, George J and Millikan, Robert C and Ambrosone, Christine B and John, Esther M and Bernstein, Leslie and Zheng, Wei and Hu, Jennifer J and Ziegler, Regina G and Nyante, Sarah J and Bandera, Elisa V and Ingles, Sue A and Press, Michael F and Chanock, Stephen J and Deming, Sandra L and Rodriguez-Gil, Jorge L and Palmer, Cameron D and Buxbaum, Sarah and Ekunwe, Lynette and Hirschhorn, Joel N and Henderson, Brian E and Myers, Simon and Haiman, Christopher A and Reich, David and Patterson, Nick and Wilson, James G and Price, Alkes L} } @article {1327, title = {Genetic association for renal traits among participants of African ancestry reveals new loci for renal function.}, journal = {PLoS Genet}, volume = {7}, year = {2011}, month = {2011 Sep}, pages = {e1002264}, abstract = {

Chronic kidney disease (CKD) is an increasing global public health concern, particularly among populations of African ancestry. We performed an interrogation of known renal loci, genome-wide association (GWA), and IBC candidate-gene SNP association analyses in African Americans from the CARe Renal Consortium. In up to 8,110 participants, we performed meta-analyses of GWA and IBC array data for estimated glomerular filtration rate (eGFR), CKD (eGFR <60 mL/min/1.73 m(2)), urinary albumin-to-creatinine ratio (UACR), and microalbuminuria (UACR >30 mg/g) and interrogated the 250 kb flanking region around 24 SNPs previously identified in European Ancestry renal GWAS analyses. Findings were replicated in up to 4,358 African Americans. To assess function, individually identified genes were knocked down in zebrafish embryos by morpholino antisense oligonucleotides. Expression of kidney-specific genes was assessed by in situ hybridization, and glomerular filtration was evaluated by dextran clearance. Overall, 23 of 24 previously identified SNPs had direction-consistent associations with eGFR in African Americans, 2 of which achieved nominal significance (UMOD, PIP5K1B). Interrogation of the flanking regions uncovered 24 new index SNPs in African Americans, 12 of which were replicated (UMOD, ANXA9, GCKR, TFDP2, DAB2, VEGFA, ATXN2, GATM, SLC22A2, TMEM60, SLC6A13, and BCAS3). In addition, we identified 3 suggestive loci at DOK6 (p-value = 5.3{\texttimes}10(-7)) and FNDC1 (p-value = 3.0{\texttimes}10(-7)) for UACR, and KCNQ1 with eGFR (p = 3.6{\texttimes}10(-6)). Morpholino knockdown of kcnq1 in the zebrafish resulted in abnormal kidney development and filtration capacity. We identified several SNPs in association with eGFR in African Ancestry individuals, as well as 3 suggestive loci for UACR and eGFR. Functional genetic studies support a role for kcnq1 in glomerular development in zebrafish.

}, keywords = {Adaptor Proteins, Vesicular Transport, Adult, African Continental Ancestry Group, Aged, Animals, Female, Gene Knockdown Techniques, Genetic Association Studies, Genetic Loci, Genome-Wide Association Study, Glomerular Filtration Rate, Humans, KCNQ1 Potassium Channel, Kidney, Kidney Failure, Chronic, Male, Middle Aged, Neoplasm Proteins, Phenotype, Polymorphism, Single Nucleotide, Zebrafish}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1002264}, author = {Liu, Ching-Ti and Garnaas, Maija K and Tin, Adrienne and K{\"o}ttgen, Anna and Franceschini, Nora and Peralta, Carmen A and de Boer, Ian H and Lu, Xiaoning and Atkinson, Elizabeth and Ding, Jingzhong and Nalls, Michael and Shriner, Daniel and Coresh, Josef and Kutlar, Abdullah and Bibbins-Domingo, Kirsten and Siscovick, David and Akylbekova, Ermeg and Wyatt, Sharon and Astor, Brad and Mychaleckjy, Josef and Li, Man and Reilly, Muredach P and Townsend, Raymond R and Adeyemo, Adebowale and Zonderman, Alan B and de Andrade, Mariza and Turner, Stephen T and Mosley, Thomas H and Harris, Tamara B and Rotimi, Charles N and Liu, Yongmei and Kardia, Sharon L R and Evans, Michele K and Shlipak, Michael G and Kramer, Holly and Flessner, Michael F and Dreisbach, Albert W and Goessling, Wolfram and Cupples, L Adrienne and Kao, W Linda and Fox, Caroline S} } @article {1343, title = {Genetic variants of the NOTCH3 gene in the elderly and magnetic resonance imaging correlates of age-related cerebral small vessel disease.}, journal = {Brain}, volume = {134}, year = {2011}, month = {2011 Nov}, pages = {3384-97}, abstract = {

Cerebral small vessel disease-related brain lesions such as white matter lesions and lacunes are common findings of magnetic resonance imaging in the elderly. These lesions are thought to be major contributors to disability in old age, and risk factors that include age and hypertension have been established. The radiological, histopathologic and clinical phenotypes of age-related cerebral small vessel disease remarkably resemble autosomal dominant arteriopathy with subcortical infarcts and leucoencephalopathy, which is caused by mutations in NOTCH3. We hypothesized that genetic variations in NOTCH3 also play a role in age-related cerebral small vessel disease. We directly sequenced all 33 exons, the promoter and 3{\textquoteright}-untranslated region of NOTCH3 in 195 participants with either coalescent white matter lesions or lacunes and compared the results to 82 randomly selected participants with no focal changes on magnetic resonance images in the Austrian Stroke Prevention Study. We detected nine common and 33 rare single nucleotide polymorphisms, of which 20 were novel. All common single nucleotide polymorphisms were genotyped in the entire cohort (n = 888), and four of them, rs1043994, rs10404382, rs10423702 and rs1043997, were associated significantly with both the presence and progression of white matter lesions. The association was confined to hypertensives, a result which we replicated in the Cohorts for Heart and Ageing Research in Genomic Epidemiology Consortium on an independent sample of 4773 stroke-free hypertensive elderly individuals of European descent (P = 0.04). The 33 rare single nucleotide polymorphisms were scattered over the NOTCH3 gene with three being located in the promoter region, 24 in exons (18 non-synonymous), three in introns and three in the 3{\textquoteright}-untranslated region. None of the single nucleotide polymorphisms affected a cysteine residue. Sorting Intolerant From Tolerant, PolyPhen2 analyses and protein structure simulation consistently predicted six of the non-synonymous single nucleotide polymorphisms (H170R, P496L, V1183M, L1518M, D1823N and V1952M) to be functional, with four being exclusively or mainly detected in subjects with severe white matter lesions. In four individuals with rare non-synonymous single nucleotide polymorphisms, we noted anterior temporal lobe hyperintensity, hyperintensity in the external capsule, lacunar infarcts or subcortical lacunar lesions. None of the observed abnormalities were specific to cerebral autosomal dominant arteriopathy with subcortical infarcts and leucoencephalopathy. This is the first comprehensive study investigating (i) the frequency of NOTCH3 variations in community-dwelling elderly and (ii) their effect on cerebral small vessel disease related magnetic resonance imaging phenotypes. We show that the NOTCH3 gene is highly variable with both common and rare single nucleotide polymorphisms spreading across the gene, and that common variants at the NOTCH3 gene increase the risk of age-related white matter lesions in hypertensives. Additional investigations are required to explore the biological mechanisms underlying the observed association.

}, keywords = {Aged, Aged, 80 and over, Alleles, Brain, Cerebral Small Vessel Diseases, Exons, Female, Follow-Up Studies, Genetic Association Studies, Genotype, Humans, Hypertension, Magnetic Resonance Imaging, Male, Middle Aged, Phenotype, Promoter Regions, Genetic, Prospective Studies, Receptor, Notch3, Receptors, Notch}, issn = {1460-2156}, doi = {10.1093/brain/awr252}, author = {Schmidt, Helena and Zeginigg, Marion and Wiltgen, Marco and Freudenberger, Paul and Petrovic, Katja and Cavalieri, Margherita and Gider, Pierre and Enzinger, Christian and Fornage, Myriam and Debette, Stephanie and Rotter, Jerome I and Ikram, Mohammad A and Launer, Lenore J and Schmidt, Reinhold} } @article {1323, title = {Meta-analysis of genome-wide association studies from the CHARGE consortium identifies common variants associated with carotid intima media thickness and plaque.}, journal = {Nat Genet}, volume = {43}, year = {2011}, month = {2011 Sep 11}, pages = {940-7}, abstract = {

Carotid intima media thickness (cIMT) and plaque determined by ultrasonography are established measures of subclinical atherosclerosis that each predicts future cardiovascular disease events. We conducted a meta-analysis of genome-wide association data in 31,211 participants of European ancestry from nine large studies in the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. We then sought additional evidence to support our findings among 11,273 individuals using data from seven additional studies. In the combined meta-analysis, we identified three genomic regions associated with common carotid intima media thickness and two different regions associated with the presence of carotid plaque (P < 5 {\texttimes} 10(-8)). The associated SNPs mapped in or near genes related to cellular signaling, lipid metabolism and blood pressure homeostasis, and two of the regions were associated with coronary artery disease (P < 0.006) in the Coronary Artery Disease Genome-Wide Replication and Meta-Analysis (CARDIoGRAM) consortium. Our findings may provide new insight into pathways leading to subclinical atherosclerosis and subsequent cardiovascular events.

}, keywords = {Adult, Aged, Aging, Atherosclerosis, Carotid Intima-Media Thickness, Cohort Studies, Coronary Artery Disease, European Continental Ancestry Group, Genetic Loci, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Genotype, Heart, Humans, Middle Aged, Phenotype, Plaque, Atherosclerotic, Polymorphism, Single Nucleotide, Risk Factors}, issn = {1546-1718}, doi = {10.1038/ng.920}, author = {Bis, Joshua C and Kavousi, Maryam and Franceschini, Nora and Isaacs, Aaron and Abecasis, Goncalo R and Schminke, Ulf and Post, Wendy S and Smith, Albert V and Cupples, L Adrienne and Markus, Hugh S and Schmidt, Reinhold and Huffman, Jennifer E and Lehtim{\"a}ki, Terho and Baumert, Jens and M{\"u}nzel, Thomas and Heckbert, Susan R and Dehghan, Abbas and North, Kari and Oostra, Ben and Bevan, Steve and Stoegerer, Eva-Maria and Hayward, Caroline and Raitakari, Olli and Meisinger, Christa and Schillert, Arne and Sanna, Serena and V{\"o}lzke, Henry and Cheng, Yu-Ching and Thorsson, Bolli and Fox, Caroline S and Rice, Kenneth and Rivadeneira, Fernando and Nambi, Vijay and Halperin, Eran and Petrovic, Katja E and Peltonen, Leena and Wichmann, H Erich and Schnabel, Renate B and D{\"o}rr, Marcus and Parsa, Afshin and Aspelund, Thor and Demissie, Serkalem and Kathiresan, Sekar and Reilly, Muredach P and Taylor, Kent and Uitterlinden, Andre and Couper, David J and Sitzer, Matthias and K{\"a}h{\"o}nen, Mika and Illig, Thomas and Wild, Philipp S and Orr{\`u}, Marco and L{\"u}demann, Jan and Shuldiner, Alan R and Eiriksdottir, Gudny and White, Charles C and Rotter, Jerome I and Hofman, Albert and Seissler, Jochen and Zeller, Tanja and Usala, Gianluca and Ernst, Florian and Launer, Lenore J and D{\textquoteright}Agostino, Ralph B and O{\textquoteright}Leary, Daniel H and Ballantyne, Christie and Thiery, Joachim and Ziegler, Andreas and Lakatta, Edward G and Chilukoti, Ravi Kumar and Harris, Tamara B and Wolf, Philip A and Psaty, Bruce M and Polak, Joseph F and Li, Xia and Rathmann, Wolfgang and Uda, Manuela and Boerwinkle, Eric and Klopp, Norman and Schmidt, Helena and Wilson, James F and Viikari, Jorma and Koenig, Wolfgang and Blankenberg, Stefan and Newman, Anne B and Witteman, Jacqueline and Heiss, Gerardo and Duijn, Cornelia van and Scuteri, Angelo and Homuth, Georg and Mitchell, Braxton D and Gudnason, Vilmundur and O{\textquoteright}Donnell, Christopher J} } @article {1313, title = {The Next PAGE in understanding complex traits: design for the analysis of Population Architecture Using Genetics and Epidemiology (PAGE) Study.}, journal = {Am J Epidemiol}, volume = {174}, year = {2011}, month = {2011 Oct 01}, pages = {849-59}, abstract = {

Genetic studies have identified thousands of variants associated with complex traits. However, most association studies are limited to populations of European descent and a single phenotype. The Population Architecture using Genomics and Epidemiology (PAGE) Study was initiated in 2008 by the National Human Genome Research Institute to investigate the epidemiologic architecture of well-replicated genetic variants associated with complex diseases in several large, ethnically diverse population-based studies. Combining DNA samples and hundreds of phenotypes from multiple cohorts, PAGE is well-suited to address generalization of associations and variability of effects in diverse populations; identify genetic and environmental modifiers; evaluate disease subtypes, intermediate phenotypes, and biomarkers; and investigate associations with novel phenotypes. PAGE investigators harmonize phenotypes across studies where possible and perform coordinated cohort-specific analyses and meta-analyses. PAGE researchers are genotyping thousands of genetic variants in up to 121,000 DNA samples from African-American, white, Hispanic/Latino, Asian/Pacific Islander, and American Indian participants. Initial analyses will focus on single nucleotide polymorphisms (SNPs) associated with obesity, lipids, cardiovascular disease, type 2 diabetes, inflammation, various cancers, and related biomarkers. PAGE SNPs are also assessed for pleiotropy using the "phenome-wide association study" approach, testing each SNP for associations with hundreds of phenotypes. PAGE data will be deposited into the National Center for Biotechnology Information{\textquoteright}s Database of Genotypes and Phenotypes and made available via a custom browser.

}, keywords = {Epidemiologic Methods, Epidemiologic Research Design, Ethnic Groups, Genetic Association Studies, Genetics, Population, Genome-Wide Association Study, Humans, Interinstitutional Relations, Multifactorial Inheritance, National Human Genome Research Institute (U.S.), Phenotype, Pilot Projects, Research Design, Risk Factors, United States}, issn = {1476-6256}, doi = {10.1093/aje/kwr160}, author = {Matise, Tara C and Ambite, Jose Luis and Buyske, Steven and Carlson, Christopher S and Cole, Shelley A and Crawford, Dana C and Haiman, Christopher A and Heiss, Gerardo and Kooperberg, Charles and Marchand, Loic Le and Manolio, Teri A and North, Kari E and Peters, Ulrike and Ritchie, Marylyn D and Hindorff, Lucia A and Haines, Jonathan L} } @article {1346, title = {NK-like T cells and plasma cytokines, but not anti-viral serology, define immune fingerprints of resilience and mild disability in exceptional aging.}, journal = {PLoS One}, volume = {6}, year = {2011}, month = {2011}, pages = {e26558}, abstract = {

Exceptional aging has been defined as maintenance of physical and cognitive function beyond the median lifespan despite a history of diseases and/or concurrent subclinical conditions. Since immunity is vital to individual fitness, we examined immunologic fingerprint(s) of highly functional elders. Therefore, survivors of the Cardiovascular Health Study in Pittsburgh, Pennsylvania, USA were recruited (n = 140; mean age = 86 years) and underwent performance testing. Blood samples were collected and examined blindly for humoral factors and T cell phenotypes. Based on results of physical and cognitive performance testing, elders were classified as "impaired" or "unimpaired", accuracy of group assignment was verified by discriminant function analysis. The two groups showed distinct immune profiles as determined by factor analysis. The dominant immune signature of impaired elders consisted of interferon (IFN)-γ, interleukin (IL)-6, tumor necrosis factor-α, and T cells expressing inhibitory natural killer-related receptors (NKR) CD158a, CD158e, and NKG2A. In contrast, the dominant signature of unimpaired elders consisted of IL-5, IL-12p70, and IL-13 with co-expression of IFN-γ, IL-4, and IL-17, and T cells expressing stimulatory NKRs CD56, CD16, and NKG2D. In logistic regression models, unimpaired phenotype was predicted independently by IL-5 and by CD4(+)CD28(null)CD56(+)CD57(+) T cells. All elders had high antibody titers to common viruses including cytomegalovirus. In cellular bioassays, T cell receptor (TCR)-independent ligation of either CD56 or NKG2D elicited activation of T cells. Collectively, these data demonstrate the importance of immunological parameters in distinguishing between health phenotypes of older adults. NKR(+) T cells and cytokine upregulation indicate a unique physiologic environment in old age. Correlation of particular NKR(+) T cell subsets and IL-5 with unimpaired performance, and NKR-driven TCR-independent activation of T cells suggest novel immunopathway(s) that could be exploited to improve immunity in old age.

}, keywords = {Adolescent, Adult, Aged, 80 and over, Aging, Cardiovascular Physiological Phenomena, CD56 Antigen, Cognition Disorders, Cytokines, Gene Expression Regulation, Humans, Immunity, Humoral, Killer Cells, Natural, Longevity, Male, NK Cell Lectin-Like Receptor Subfamily K, Phenotype, Physical Fitness, T-Lymphocyte Subsets, Young Adult}, issn = {1932-6203}, doi = {10.1371/journal.pone.0026558}, author = {Vallejo, Abbe N and Hamel, David L and Mueller, Robert G and Ives, Diane G and Michel, Joshua J and Boudreau, Robert M and Newman, Anne B} } @article {1345, title = {A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains.}, journal = {PLoS Genet}, volume = {7}, year = {2011}, month = {2011 Oct}, pages = {e1002322}, abstract = {

Despite evidence of the clustering of metabolic syndrome components, current approaches for identifying unifying genetic mechanisms typically evaluate clinical categories that do not provide adequate etiological information. Here, we used data from 19,486 European American and 6,287 African American Candidate Gene Association Resource Consortium participants to identify loci associated with the clustering of metabolic phenotypes. Six phenotype domains (atherogenic dyslipidemia, vascular dysfunction, vascular inflammation, pro-thrombotic state, central obesity, and elevated plasma glucose) encompassing 19 quantitative traits were examined. Principal components analysis was used to reduce the dimension of each domain such that >55\% of the trait variance was represented within each domain. We then applied a statistically efficient and computational feasible multivariate approach that related eight principal components from the six domains to 250,000 imputed SNPs using an additive genetic model and including demographic covariates. In European Americans, we identified 606 genome-wide significant SNPs representing 19 loci. Many of these loci were associated with only one trait domain, were consistent with results in African Americans, and overlapped with published findings, for instance central obesity and FTO. However, our approach, which is applicable to any set of interval scale traits that is heritable and exhibits evidence of phenotypic clustering, identified three new loci in or near APOC1, BRAP, and PLCG1, which were associated with multiple phenotype domains. These pleiotropic loci may help characterize metabolic dysregulation and identify targets for intervention.

}, keywords = {African Americans, Apolipoprotein C-I, Blood Glucose, Dyslipidemias, European Continental Ancestry Group, Genetic Association Studies, Genetic Predisposition to Disease, Genome, Human, Humans, Metabolic Syndrome, Obesity, Abdominal, Phenotype, Phospholipase C gamma, Polymorphism, Single Nucleotide, Quantitative Trait, Heritable, Ubiquitin-Protein Ligases, Vascular Diseases}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1002322}, author = {Avery, Christy L and He, Qianchuan and North, Kari E and Ambite, Jos{\'e} L and Boerwinkle, Eric and Fornage, Myriam and Hindorff, Lucia A and Kooperberg, Charles and Meigs, James B and Pankow, James S and Pendergrass, Sarah A and Psaty, Bruce M and Ritchie, Marylyn D and Rotter, Jerome I and Taylor, Kent D and Wilkens, Lynne R and Heiss, Gerardo and Lin, Dan Yu} } @article {1359, title = {Association between chromosome 9p21 variants and the ankle-brachial index identified by a meta-analysis of 21 genome-wide association studies.}, journal = {Circ Cardiovasc Genet}, volume = {5}, year = {2012}, month = {2012 Feb 01}, pages = {100-12}, abstract = {

BACKGROUND: Genetic determinants of peripheral arterial disease (PAD) remain largely unknown. To identify genetic variants associated with the ankle-brachial index (ABI), a noninvasive measure of PAD, we conducted a meta-analysis of genome-wide association study data from 21 population-based cohorts.

METHODS AND RESULTS: Continuous ABI and PAD (ABI <=0.9) phenotypes adjusted for age and sex were examined. Each study conducted genotyping and imputed data to the ≈2.5 million single nucleotide polymorphisms (SNPs) in HapMap. Linear and logistic regression models were used to test each SNP for association with ABI and PAD using additive genetic models. Study-specific data were combined using fixed effects inverse variance weighted meta-analyses. There were a total of 41 692 participants of European ancestry (≈60\% women, mean ABI 1.02 to 1.19), including 3409 participants with PAD and with genome-wide association study data available. In the discovery meta-analysis, rs10757269 on chromosome 9 near CDKN2B had the strongest association with ABI (β=-0.006, P=2.46{\texttimes}10(-8)). We sought replication of the 6 strongest SNP associations in 5 population-based studies and 3 clinical samples (n=16 717). The association for rs10757269 strengthened in the combined discovery and replication analysis (P=2.65{\texttimes}10(-9)). No other SNP associations for ABI or PAD achieved genome-wide significance. However, 2 previously reported candidate genes for PAD and 1 SNP associated with coronary artery disease were associated with ABI: DAB21P (rs13290547, P=3.6{\texttimes}10(-5)), CYBA (rs3794624, P=6.3{\texttimes}10(-5)), and rs1122608 (LDLR, P=0.0026).

CONCLUSIONS: Genome-wide association studies in more than 40 000 individuals identified 1 genome wide significant association on chromosome 9p21 with ABI. Two candidate genes for PAD and 1 SNP for coronary artery disease are associated with ABI.

}, keywords = {Adult, Age Factors, Aged, Aged, 80 and over, Alleles, Ankle Brachial Index, Chromosomes, Human, Pair 9, Cohort Studies, Cyclin-Dependent Kinase Inhibitor p15, Female, Genome-Wide Association Study, Genotype, HapMap Project, Humans, Logistic Models, Male, Middle Aged, Peripheral Vascular Diseases, Phenotype, Polymorphism, Single Nucleotide, Risk Factors, Sex Factors}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.111.961292}, author = {Murabito, Joanne M and White, Charles C and Kavousi, Maryam and Sun, Yan V and Feitosa, Mary F and Nambi, Vijay and Lamina, Claudia and Schillert, Arne and Coassin, Stefan and Bis, Joshua C and Broer, Linda and Crawford, Dana C and Franceschini, Nora and Frikke-Schmidt, Ruth and Haun, Margot and Holewijn, Suzanne and Huffman, Jennifer E and Hwang, Shih-Jen and Kiechl, Stefan and Kollerits, Barbara and Montasser, May E and Nolte, Ilja M and Rudock, Megan E and Senft, Andrea and Teumer, Alexander and van der Harst, Pim and Vitart, Veronique and Waite, Lindsay L and Wood, Andrew R and Wassel, Christina L and Absher, Devin M and Allison, Matthew A and Amin, Najaf and Arnold, Alice and Asselbergs, Folkert W and Aulchenko, Yurii and Bandinelli, Stefania and Barbalic, Maja and Boban, Mladen and Brown-Gentry, Kristin and Couper, David J and Criqui, Michael H and Dehghan, Abbas and den Heijer, Martin and Dieplinger, Benjamin and Ding, Jingzhong and D{\"o}rr, Marcus and Espinola-Klein, Christine and Felix, Stephan B and Ferrucci, Luigi and Folsom, Aaron R and Fraedrich, Gustav and Gibson, Quince and Goodloe, Robert and Gunjaca, Grgo and Haltmayer, Meinhard and Heiss, Gerardo and Hofman, Albert and Kieback, Arne and Kiemeney, Lambertus A and Kolcic, Ivana and Kullo, Iftikhar J and Kritchevsky, Stephen B and Lackner, Karl J and Li, Xiaohui and Lieb, Wolfgang and Lohman, Kurt and Meisinger, Christa and Melzer, David and Mohler, Emile R and Mudnic, Ivana and Mueller, Thomas and Navis, Gerjan and Oberhollenzer, Friedrich and Olin, Jeffrey W and O{\textquoteright}Connell, Jeff and O{\textquoteright}Donnell, Christopher J and Palmas, Walter and Penninx, Brenda W and Petersmann, Astrid and Polasek, Ozren and Psaty, Bruce M and Rantner, Barbara and Rice, Ken and Rivadeneira, Fernando and Rotter, Jerome I and Seldenrijk, Adrie and Stadler, Marietta and Summerer, Monika and Tanaka, Toshiko and Tybjaerg-Hansen, Anne and Uitterlinden, Andr{\'e} G and van Gilst, Wiek H and Vermeulen, Sita H and Wild, Sarah H and Wild, Philipp S and Willeit, Johann and Zeller, Tanja and Zemunik, Tatijana and Zgaga, Lina and Assimes, Themistocles L and Blankenberg, Stefan and Boerwinkle, Eric and Campbell, Harry and Cooke, John P and de Graaf, Jacqueline and Herrington, David and Kardia, Sharon L R and Mitchell, Braxton D and Murray, Anna and M{\"u}nzel, Thomas and Newman, Anne B and Oostra, Ben A and Rudan, Igor and Shuldiner, Alan R and Snieder, Harold and van Duijn, Cornelia M and V{\"o}lker, Uwe and Wright, Alan F and Wichmann, H-Erich and Wilson, James F and Witteman, Jacqueline C M and Liu, Yongmei and Hayward, Caroline and Borecki, Ingrid B and Ziegler, Andreas and North, Kari E and Cupples, L Adrienne and Kronenberg, Florian} } @article {6178, title = {Association of genetic loci with sleep apnea in European Americans and African-Americans: the Candidate Gene Association Resource (CARe).}, journal = {PLoS One}, volume = {7}, year = {2012}, month = {2012}, pages = {e48836}, abstract = {

Although obstructive sleep apnea (OSA) is known to have a strong familial basis, no genetic polymorphisms influencing apnea risk have been identified in cross-cohort analyses. We utilized the National Heart, Lung, and Blood Institute (NHLBI) Candidate Gene Association Resource (CARe) to identify sleep apnea susceptibility loci. Using a panel of 46,449 polymorphisms from roughly 2,100 candidate genes on a customized Illumina iSelect chip, we tested for association with the apnea hypopnea index (AHI) as well as moderate to severe OSA (AHI>=15) in 3,551 participants of the Cleveland Family Study and two cohorts participating in the Sleep Heart Health Study.Among 647 African-Americans, rs11126184 in the pleckstrin (PLEK) gene was associated with OSA while rs7030789 in the lysophosphatidic acid receptor 1 (LPAR1) gene was associated with AHI using a chip-wide significance threshold of p-value<2{\texttimes}10(-6). Among 2,904 individuals of European ancestry, rs1409986 in the prostaglandin E2 receptor (PTGER3) gene was significantly associated with OSA. Consistency of effects between rs7030789 and rs1409986 in LPAR1 and PTGER3 and apnea phenotypes were observed in independent clinic-based cohorts.Novel genetic loci for apnea phenotypes were identified through the use of customized gene chips and meta-analyses of cohort data with replication in clinic-based samples. The identified SNPs all lie in genes associated with inflammation suggesting inflammation may play a role in OSA pathogenesis.

}, keywords = {Adult, African Americans, Aged, Alleles, European Continental Ancestry Group, Female, Genetic Association Studies, Genetic Loci, Genetic Predisposition to Disease, Genotype, Humans, Male, Middle Aged, Phenotype, Polymorphism, Single Nucleotide, Polysomnography, Sleep Apnea, Obstructive}, issn = {1932-6203}, doi = {10.1371/journal.pone.0048836}, author = {Patel, Sanjay R and Goodloe, Robert and De, Gourab and Kowgier, Matthew and Weng, Jia and Buxbaum, Sarah G and Cade, Brian and Fulop, Tibor and Gharib, Sina A and Gottlieb, Daniel J and Hillman, David and Larkin, Emma K and Lauderdale, Diane S and Li, Li and Mukherjee, Sutapa and Palmer, Lyle and Zee, Phyllis and Zhu, Xiaofeng and Redline, Susan} } @article {6175, title = {FTO genotype is associated with phenotypic variability of body mass index.}, journal = {Nature}, volume = {490}, year = {2012}, month = {2012 Oct 11}, pages = {267-72}, abstract = {

There is evidence across several species for genetic control of phenotypic variation of complex traits, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using \~{}170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype), is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7\%, corresponding to a difference of \~{}0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI, possibly mediated by DNA methylation. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.

}, keywords = {Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Body Height, Body Mass Index, Co-Repressor Proteins, Female, Genetic Variation, Genome-Wide Association Study, Humans, Male, Nerve Tissue Proteins, Phenotype, Polymorphism, Single Nucleotide, Proteins, Repressor Proteins}, issn = {1476-4687}, doi = {10.1038/nature11401}, author = {Yang, Jian and Loos, Ruth J F and Powell, Joseph E and Medland, Sarah E and Speliotes, Elizabeth K and Chasman, Daniel I and Rose, Lynda M and Thorleifsson, Gudmar and Steinthorsdottir, Valgerdur and M{\"a}gi, Reedik and Waite, Lindsay and Smith, Albert Vernon and Yerges-Armstrong, Laura M and Monda, Keri L and Hadley, David and Mahajan, Anubha and Li, Guo and Kapur, Karen and Vitart, Veronique and Huffman, Jennifer E and Wang, Sophie R and Palmer, Cameron and Esko, T{\~o}nu and Fischer, Krista and Zhao, Jing Hua and Demirkan, Ayse and Isaacs, Aaron and Feitosa, Mary F and Luan, Jian{\textquoteright}an and Heard-Costa, Nancy L and White, Charles and Jackson, Anne U and Preuss, Michael and Ziegler, Andreas and Eriksson, Joel and Kutalik, Zolt{\'a}n and Frau, Francesca and Nolte, Ilja M and van Vliet-Ostaptchouk, Jana V and Hottenga, Jouke-Jan and Jacobs, Kevin B and Verweij, Niek and Goel, Anuj and Medina-G{\'o}mez, Carolina and Estrada, Karol and Bragg-Gresham, Jennifer Lynn and Sanna, Serena and Sidore, Carlo and Tyrer, Jonathan and Teumer, Alexander and Prokopenko, Inga and Mangino, Massimo and Lindgren, Cecilia M and Assimes, Themistocles L and Shuldiner, Alan R and Hui, Jennie and Beilby, John P and McArdle, Wendy L and Hall, Per and Haritunians, Talin and Zgaga, Lina and Kolcic, Ivana and Polasek, Ozren and Zemunik, Tatijana and Oostra, Ben A and Junttila, M Juhani and Gr{\"o}nberg, Henrik and Schreiber, Stefan and Peters, Annette and Hicks, Andrew A and Stephens, Jonathan and Foad, Nicola S and Laitinen, Jaana and Pouta, Anneli and Kaakinen, Marika and Willemsen, Gonneke and Vink, Jacqueline M and Wild, Sarah H and Navis, Gerjan and Asselbergs, Folkert W and Homuth, Georg and John, Ulrich and Iribarren, Carlos and Harris, Tamara and Launer, Lenore and Gudnason, Vilmundur and O{\textquoteright}Connell, Jeffrey R and Boerwinkle, Eric and Cadby, Gemma and Palmer, Lyle J and James, Alan L and Musk, Arthur W and Ingelsson, Erik and Psaty, Bruce M and Beckmann, Jacques S and Waeber, G{\'e}rard and Vollenweider, Peter and Hayward, Caroline and Wright, Alan F and Rudan, Igor and Groop, Leif C and Metspalu, Andres and Khaw, Kay Tee and van Duijn, Cornelia M and Borecki, Ingrid B and Province, Michael A and Wareham, Nicholas J and Tardif, Jean-Claude and Huikuri, Heikki V and Cupples, L Adrienne and Atwood, Larry D and Fox, Caroline S and Boehnke, Michael and Collins, Francis S and Mohlke, Karen L and Erdmann, Jeanette and Schunkert, Heribert and Hengstenberg, Christian and Stark, Klaus and Lorentzon, Mattias and Ohlsson, Claes and Cusi, Daniele and Staessen, Jan A and van der Klauw, Melanie M and Pramstaller, Peter P and Kathiresan, Sekar and Jolley, Jennifer D and Ripatti, Samuli and Jarvelin, Marjo-Riitta and de Geus, Eco J C and Boomsma, Dorret I and Penninx, Brenda and Wilson, James F and Campbell, Harry and Chanock, Stephen J and van der Harst, Pim and Hamsten, Anders and Watkins, Hugh and Hofman, Albert and Witteman, Jacqueline C and Zillikens, M Carola and Uitterlinden, Andr{\'e} G and Rivadeneira, Fernando and Zillikens, M Carola and Kiemeney, Lambertus A and Vermeulen, Sita H and Abecasis, Goncalo R and Schlessinger, David and Schipf, Sabine and Stumvoll, Michael and T{\"o}njes, Anke and Spector, Tim D and North, Kari E and Lettre, Guillaume and McCarthy, Mark I and Berndt, Sonja I and Heath, Andrew C and Madden, Pamela A F and Nyholt, Dale R and Montgomery, Grant W and Martin, Nicholas G and McKnight, Barbara and Strachan, David P and Hill, William G and Snieder, Harold and Ridker, Paul M and Thorsteinsdottir, Unnur and Stefansson, Kari and Frayling, Timothy M and Hirschhorn, Joel N and Goddard, Michael E and Visscher, Peter M} } @article {1364, title = {Genetic variation in F3 (tissue factor) and the risk of incident venous thrombosis: meta-analysis of eight studies.}, journal = {J Thromb Haemost}, volume = {10}, year = {2012}, month = {2012 Apr}, pages = {719-22}, keywords = {Female, Gene Frequency, Genetic Predisposition to Disease, Genetic Variation, Humans, Incidence, Male, Middle Aged, Phenotype, Regression Analysis, Risk Assessment, Risk Factors, Thromboplastin, Venous Thrombosis}, issn = {1538-7836}, doi = {10.1111/j.1538-7836.2012.04665.x}, author = {Smith, N L and Heit, J A and Tang, W and Teichert, M and Chasman, D I and Morange, P-E} } @article {6804, title = {Genome-wide meta-analyses of smoking behaviors in African Americans.}, journal = {Transl Psychiatry}, volume = {2}, year = {2012}, month = {2012}, pages = {e119}, abstract = {

The identification and exploration of genetic loci that influence smoking behaviors have been conducted primarily in populations of the European ancestry. Here we report results of the first genome-wide association study meta-analysis of smoking behavior in African Americans in the Study of Tobacco in Minority Populations Genetics Consortium (n = 32,389). We identified one non-coding single-nucleotide polymorphism (SNP; rs2036527[A]) on chromosome 15q25.1 associated with smoking quantity (cigarettes per day), which exceeded genome-wide significance (β = 0.040, s.e. = 0.007, P = 1.84 {\texttimes} 10(-8)). This variant is present in the 5{\textquoteright}-distal enhancer region of the CHRNA5 gene and defines the primary index signal reported in studies of the European ancestry. No other SNP reached genome-wide significance for smoking initiation (SI, ever vs never smoking), age of SI, or smoking cessation (SC, former vs current smoking). Informative associations that approached genome-wide significance included three modestly correlated variants, at 15q25.1 within PSMA4, CHRNA5 and CHRNA3 for smoking quantity, which are associated with a second signal previously reported in studies in European ancestry populations, and a signal represented by three SNPs in the SPOCK2 gene on chr10q22.1. The association at 15q25.1 confirms this region as an important susceptibility locus for smoking quantity in men and women of African ancestry. Larger studies will be needed to validate the suggestive loci that did not reach genome-wide significance and further elucidate the contribution of genetic variation to disparities in cigarette consumption, SC and smoking-attributable disease between African Americans and European Americans.

}, keywords = {Adult, African Americans, Aged, Chromosomes, Human, Pair 10, Chromosomes, Human, Pair 15, Female, Genetic Loci, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Genotype, Humans, Male, Middle Aged, Nerve Tissue Proteins, Phenotype, Polymorphism, Single Nucleotide, Proteoglycans, Receptors, Nicotinic, Smoking, Statistics as Topic}, issn = {2158-3188}, doi = {10.1038/tp.2012.41}, author = {David, S P and Hamidovic, A and Chen, G K and Bergen, A W and Wessel, J and Kasberger, J L and Brown, W M and Petruzella, S and Thacker, E L and Kim, Y and Nalls, M A and Tranah, G J and Sung, Y J and Ambrosone, C B and Arnett, D and Bandera, E V and Becker, D M and Becker, L and Berndt, S I and Bernstein, L and Blot, W J and Broeckel, U and Buxbaum, S G and Caporaso, N and Casey, G and Chanock, S J and Deming, S L and Diver, W R and Eaton, C B and Evans, D S and Evans, M K and Fornage, M and Franceschini, N and Harris, T B and Henderson, B E and Hernandez, D G and Hitsman, B and Hu, J J and Hunt, S C and Ingles, S A and John, E M and Kittles, R and Kolb, S and Kolonel, L N and Le Marchand, L and Liu, Y and Lohman, K K and McKnight, B and Millikan, R C and Murphy, A and Neslund-Dudas, C and Nyante, S and Press, M and Psaty, B M and Rao, D C and Redline, S and Rodriguez-Gil, J L and Rybicki, B A and Signorello, L B and Singleton, A B and Smoller, J and Snively, B and Spring, B and Stanford, J L and Strom, S S and Swan, G E and Taylor, K D and Thun, M J and Wilson, A F and Witte, J S and Yamamura, Y and Yanek, L R and Yu, K and Zheng, W and Ziegler, R G and Zonderman, A B and Jorgenson, E and Haiman, C A and Furberg, H} } @article {1544, title = {Ultraconserved elements in the human genome: association and transmission analyses of highly constrained single-nucleotide polymorphisms.}, journal = {Genetics}, volume = {192}, year = {2012}, month = {2012 Sep}, pages = {253-66}, abstract = {

Ultraconserved elements in the human genome likely harbor important biological functions as they are dosage sensitive and are able to direct tissue-specific expression. Because they are under purifying selection, variants in these elements may have a lower frequency in the population but a higher likelihood of association with complex traits. We tested a set of highly constrained SNPs (hcSNPs) distributed genome-wide among ultraconserved and nearly ultraconserved elements for association with seven traits related to reproductive (age at natural menopause, number of children, age at first child, and age at last child) and overall [longevity, body mass index (BMI), and height] fitness. Using up to 24,047 European-American samples from the National Heart, Lung, and Blood Institute Candidate Gene Association Resource (CARe), we observed an excess of associations with BMI and height. In an independent replication panel the most strongly associated SNPs showed an 8.4-fold enrichment of associations at the nominal level, including three variants in previously identified loci and one in a locus (DENND1A) previously shown to be associated with polycystic ovary syndrome. Finally, using 1430 family trios, we showed that the transmissions from heterozygous parents to offspring of the derived alleles of rare (frequency <= 0.5\%) hcSNPs are not biased, particularly after adjusting for the rates of genotype missingness and error in the data. The lack of transmission bias ruled out an immediately and strongly deleterious effect due to the rare derived alleles, consistent with the observation that mice homozygous for the deletion of ultraconserved elements showed no overt phenotype. Our study also illustrated the importance of carefully modeling potential technical confounders when analyzing genotype data of rare variants.

}, keywords = {Alleles, Animals, Body Height, Body Mass Index, Child, Conserved Sequence, Dogs, Evolution, Molecular, Female, Genetic Fitness, Genetic Variation, Genome, Human, Genotype, Humans, Inheritance Patterns, Male, Mice, Pedigree, Phenotype, Polymorphism, Single Nucleotide, Rats, Reproduction, Young Adult}, issn = {1943-2631}, doi = {10.1534/genetics.112.141945}, author = {Chiang, Charleston W K and Liu, Ching-Ti and Lettre, Guillaume and Lange, Leslie A and Jorgensen, Neal W and Keating, Brendan J and Vedantam, Sailaja and Nock, Nora L and Franceschini, Nora and Reiner, Alex P and Demerath, Ellen W and Boerwinkle, Eric and Rotter, Jerome I and Wilson, James G and North, Kari E and Papanicolaou, George J and Cupples, L Adrienne and Murabito, Joanne M and Hirschhorn, Joel N} } @article {6288, title = {Common variants in Mendelian kidney disease genes and their association with renal function.}, journal = {J Am Soc Nephrol}, volume = {24}, year = {2013}, month = {2013 Dec}, pages = {2105-17}, abstract = {

Many common genetic variants identified by genome-wide association studies for complex traits map to genes previously linked to rare inherited Mendelian disorders. A systematic analysis of common single-nucleotide polymorphisms (SNPs) in genes responsible for Mendelian diseases with kidney phenotypes has not been performed. We thus developed a comprehensive database of genes for Mendelian kidney conditions and evaluated the association between common genetic variants within these genes and kidney function in the general population. Using the Online Mendelian Inheritance in Man database, we identified 731 unique disease entries related to specific renal search terms and confirmed a kidney phenotype in 218 of these entries, corresponding to mutations in 258 genes. We interrogated common SNPs (minor allele frequency >5\%) within these genes for association with the estimated GFR in 74,354 European-ancestry participants from the CKDGen Consortium. However, the top four candidate SNPs (rs6433115 at LRP2, rs1050700 at TSC1, rs249942 at PALB2, and rs9827843 at ROBO2) did not achieve significance in a stage 2 meta-analysis performed in 56,246 additional independent individuals, indicating that these common SNPs are not associated with estimated GFR. The effect of less common or rare variants in these genes on kidney function in the general population and disease-specific cohorts requires further research.

}, keywords = {Databases, Genetic, European Continental Ancestry Group, Gene Frequency, Genetic Variation, Genome-Wide Association Study, Humans, Kidney, Mendelian Randomization Analysis, Phenotype, Polymorphism, Single Nucleotide, Renal Insufficiency, Chronic}, issn = {1533-3450}, doi = {10.1681/ASN.2012100983}, author = {Parsa, Afshin and Fuchsberger, Christian and K{\"o}ttgen, Anna and O{\textquoteright}Seaghdha, Conall M and Pattaro, Cristian and de Andrade, Mariza and Chasman, Daniel I and Teumer, Alexander and Endlich, Karlhans and Olden, Matthias and Chen, Ming-Huei and Tin, Adrienne and Kim, Young J and Taliun, Daniel and Li, Man and Feitosa, Mary and Gorski, Mathias and Yang, Qiong and Hundertmark, Claudia and Foster, Meredith C and Glazer, Nicole and Isaacs, Aaron and Rao, Madhumathi and Smith, Albert V and O{\textquoteright}Connell, Jeffrey R and Struchalin, Maksim and Tanaka, Toshiko and Li, Guo and Hwang, Shih-Jen and Atkinson, Elizabeth J and Lohman, Kurt and Cornelis, Marilyn C and Johansson, Asa and T{\"o}njes, Anke and Dehghan, Abbas and Couraki, Vincent and Holliday, Elizabeth G and Sorice, Rossella and Kutalik, Zolt{\'a}n and Lehtim{\"a}ki, Terho and Esko, T{\~o}nu and Deshmukh, Harshal and Ulivi, Sheila and Chu, Audrey Y and Murgia, Federico and Trompet, Stella and Imboden, Medea and Kollerits, Barbara and Pistis, Giorgio and Harris, Tamara B and Launer, Lenore J and Aspelund, Thor and Eiriksdottir, Gudny and Mitchell, Braxton D and Boerwinkle, Eric and Schmidt, Helena and Hofer, Edith and Hu, Frank and Demirkan, Ayse and Oostra, Ben A and Turner, Stephen T and Ding, Jingzhong and Andrews, Jeanette S and Freedman, Barry I and Giulianini, Franco and Koenig, Wolfgang and Illig, Thomas and D{\"o}ring, Angela and Wichmann, H-Erich and Zgaga, Lina and Zemunik, Tatijana and Boban, Mladen and Minelli, Cosetta and Wheeler, Heather E and Igl, Wilmar and Zaboli, Ghazal and Wild, Sarah H and Wright, Alan F and Campbell, Harry and Ellinghaus, David and N{\"o}thlings, Ute and Jacobs, Gunnar and Biffar, Reiner and Ernst, Florian and Homuth, Georg and Kroemer, Heyo K and Nauck, Matthias and Stracke, Sylvia and V{\"o}lker, Uwe and V{\"o}lzke, Henry and Kovacs, Peter and Stumvoll, Michael and M{\"a}gi, Reedik and Hofman, Albert and Uitterlinden, Andr{\'e} G and Rivadeneira, Fernando and Aulchenko, Yurii S and Polasek, Ozren and Hastie, Nick and Vitart, Veronique and Helmer, Catherine and Wang, Jie Jin and Stengel, B{\'e}n{\'e}dicte and Ruggiero, Daniela and Bergmann, Sven and K{\"a}h{\"o}nen, Mika and Viikari, Jorma and Nikopensius, Tiit and Province, Michael and Colhoun, Helen and Doney, Alex and Robino, Antonietta and Kr{\"a}mer, Bernhard K and Portas, Laura and Ford, Ian and Buckley, Brendan M and Adam, Martin and Thun, Gian-Andri and Paulweber, Bernhard and Haun, Margot and Sala, Cinzia and Mitchell, Paul and Ciullo, Marina and Vollenweider, Peter and Raitakari, Olli and Metspalu, Andres and Palmer, Colin and Gasparini, Paolo and Pirastu, Mario and Jukema, J Wouter and Probst-Hensch, Nicole M and Kronenberg, Florian and Toniolo, Daniela and Gudnason, Vilmundur and Shuldiner, Alan R and Coresh, Josef and Schmidt, Reinhold and Ferrucci, Luigi and van Duijn, Cornelia M and Borecki, Ingrid and Kardia, Sharon L R and Liu, Yongmei and Curhan, Gary C and Rudan, Igor and Gyllensten, Ulf and Wilson, James F and Franke, Andre and Pramstaller, Peter P and Rettig, Rainer and Prokopenko, Inga and Witteman, Jacqueline and Hayward, Caroline and Ridker, Paul M and Bochud, Murielle and Heid, Iris M and Siscovick, David S and Fox, Caroline S and Kao, W Linda and B{\"o}ger, Carsten A} } @article {1620, title = {Genetic analysis of a population heavy drinking phenotype identifies risk variants in whites.}, journal = {J Clin Psychopharmacol}, volume = {33}, year = {2013}, month = {2013 Apr}, pages = {206-10}, chapter = {206}, abstract = {

Genetic association studies thus far have used detailed diagnoses of alcoholism to identify loci associated with risk. This proof-of-concept analysis examined whether population data of lifetime heaviest alcohol consumption may be used to identify genetic loci that modulate risk. We conducted a genetic association study in European Americans between variants in approximately 2100 genes and alcohol consumption as part of the Candidate gene Association Resource project. We defined cases as individuals with a history of drinking 5 or more drinks per day almost every day of the week and controls as current light drinkers (1-5 drinks per week). We cross-validated identified single nucleotide polymorphisms in a meta-analysis of 2 cohorts of unrelated individuals--Atherosclerosis Risk in Communities (ARIC) and Cardiovascular Health Study (CHS)--and in a separate cohort of related individuals--Framingham Heart Study (FHS). The most significant variant in the meta-analysis of ARIC and CHS was rs6933598 in methylenetetrahydrofolate dehydrogenase (P = 7.46 {\texttimes} 10(-05)) with a P value in FHS of 0.042. The top variants in FHS were rs12249562 in cubulin (P = 3.03 {\texttimes} 10(-05)) and rs9839267 near cholecystokinin (P = 3.05 {\texttimes} 10(-05)) with a P value of 0.019 for rs9839267 in CHS. We have here shown feasibility in evaluating lifetime incidence of heavy alcohol drinking from population-based studies for the purpose of conducting genetic association analyses.

}, keywords = {Aged, Alcohol Drinking, Alcoholism, Case-Control Studies, European Continental Ancestry Group, Feasibility Studies, Genetic Association Studies, Genetic Loci, Genetic Predisposition to Disease, Genetic Variation, Humans, Incidence, Male, Middle Aged, Phenotype, Polymorphism, Single Nucleotide, Risk}, issn = {1533-712X}, doi = {10.1097/JCP.0b013e318287009a}, author = {Hamidovic, Ajna and Goodloe, Robert J and Young, Taylor R and Styn, Mindi A and Mukamal, Kenneth J and Choquet, Helene and Kasberger, Jay L and Buxbaum, Sarah G and Papanicolaou, George J and White, Wendy and Volcik, Kelly and Spring, Bonnie and Hitsman, Brian and Levy, Daniel and Jorgenson, Eric} } @article {6631, title = {Genetic risk factors for BMI and obesity in an ethnically diverse population: results from the population architecture using genomics and epidemiology (PAGE) study.}, journal = {Obesity (Silver Spring)}, volume = {21}, year = {2013}, month = {2013 Apr}, pages = {835-46}, abstract = {

OBJECTIVE: Several genome-wide association studies (GWAS) have demonstrated that common genetic variants contribute to obesity. However, studies of this complex trait have focused on ancestrally European populations, despite the high prevalence of obesity in some minority groups.

DESIGN AND METHODS: As part of the "Population Architecture using Genomics and Epidemiology (PAGE)" Consortium, we investigated the association between 13 GWAS-identified single-nucleotide polymorphisms (SNPs) and BMI and obesity in 69,775 subjects, including 6,149 American Indians, 15,415 African-Americans, 2,438 East Asians, 7,346 Hispanics, 604 Pacific Islanders, and 37,823 European Americans. For the BMI-increasing allele of each SNP, we calculated β coefficients using linear regression (for BMI) and risk estimates using logistic regression (for obesity defined as BMI >= 30) followed by fixed-effects meta-analysis to combine results across PAGE sites. Analyses stratified by racial/ethnic group assumed an additive genetic model and were adjusted for age, sex, and current smoking. We defined "replicating SNPs" (in European Americans) and "generalizing SNPs" (in other racial/ethnic groups) as those associated with an allele frequency-specific increase in BMI.

RESULTS: By this definition, we replicated 9/13 SNP associations (5 out of 8 loci) in European Americans. We also generalized 8/13 SNP associations (5/8 loci) in East Asians, 7/13 (5/8 loci) in African Americans, 6/13 (4/8 loci) in Hispanics, 5/8 in Pacific Islanders (5/8 loci), and 5/9 (4/8 loci) in American Indians.

CONCLUSION: Linkage disequilibrium patterns suggest that tagSNPs selected for European Americans may not adequately tag causal variants in other ancestry groups. Accordingly, fine-mapping in large samples is needed to comprehensively explore these loci in diverse populations.

}, keywords = {Alleles, Body Mass Index, Ethnic Groups, Gene Frequency, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Metagenomics, Obesity, Phenotype, Polymorphism, Single Nucleotide, Risk Factors}, issn = {1930-739X}, doi = {10.1002/oby.20268}, author = {Fesinmeyer, Megan D and North, Kari E and Ritchie, Marylyn D and Lim, Unhee and Franceschini, Nora and Wilkens, Lynne R and Gross, Myron D and B{\r u}zkov{\'a}, Petra and Glenn, Kimberly and Quibrera, P Miguel and Fernandez-Rhodes, Lindsay and Li, Qiong and Fowke, Jay H and Li, Rongling and Carlson, Christopher S and Prentice, Ross L and Kuller, Lewis H and Manson, JoAnn E and Matise, Tara C and Cole, Shelley A and Chen, Christina T L and Howard, Barbara V and Kolonel, Laurence N and Henderson, Brian E and Monroe, Kristine R and Crawford, Dana C and Hindorff, Lucia A and Buyske, Steven and Haiman, Christopher A and Le Marchand, Lo{\"\i}c and Peters, Ulrike} } @article {6632, title = {Genome-wide association study of cardiac structure and systolic function in African Americans: the Candidate Gene Association Resource (CARe) study.}, journal = {Circ Cardiovasc Genet}, volume = {6}, year = {2013}, month = {2013 Feb}, pages = {37-46}, abstract = {

BACKGROUND: Using data from 4 community-based cohorts of African Americans, we tested the association between genome-wide markers (single-nucleotide polymorphisms) and cardiac phenotypes in the Candidate-gene Association Resource study.

METHODS AND RESULTS: Among 6765 African Americans, we related age, sex, height, and weight-adjusted residuals for 9 cardiac phenotypes (assessed by echocardiogram or magnetic resonance imaging) to 2.5 million single-nucleotide polymorphisms genotyped using Genome-wide Affymetrix Human SNP Array 6.0 (Affy6.0) and the remainder imputed. Within the cohort, genome-wide association analysis was conducted, followed by meta-analysis across cohorts using inverse variance weights (genome-wide significance threshold=4.0 {\texttimes}10(-7)). Supplementary pathway analysis was performed. We attempted replication in 3 smaller cohorts of African ancestry and tested lookups in 1 consortium of European ancestry (EchoGEN). Across the 9 phenotypes, variants in 4 genetic loci reached genome-wide significance: rs4552931 in UBE2V2 (P=1.43{\texttimes}10(-7)) for left ventricular mass, rs7213314 in WIPI1 (P=1.68{\texttimes}10(-7)) for left ventricular internal diastolic diameter, rs1571099 in PPAPDC1A (P=2.57{\texttimes}10(-8)) for interventricular septal wall thickness, and rs9530176 in KLF5 (P=4.02{\texttimes}10(-7)) for ejection fraction. Associated variants were enriched in 3 signaling pathways involved in cardiac remodeling. None of the 4 loci replicated in cohorts of African ancestry was confirmed in lookups in EchoGEN.

CONCLUSIONS: In the largest genome-wide association study of cardiac structure and function to date in African Americans, we identified 4 genetic loci related to left ventricular mass, interventricular septal wall thickness, left ventricular internal diastolic diameter, and ejection fraction, which reached genome-wide significance. Replication results suggest that these loci may be unique to individuals of African ancestry. Additional large-scale studies are warranted for these complex phenotypes.

}, keywords = {African Americans, Aged, Cohort Studies, Diastole, Echocardiography, European Continental Ancestry Group, Female, Genome-Wide Association Study, Genotype, Heart, Humans, Male, Middle Aged, Phenotype, Polymorphism, Single Nucleotide, Systole}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.111.962365}, author = {Fox, Ervin R and Musani, Solomon K and Barbalic, Maja and Lin, Honghuang and Yu, Bing and Ogunyankin, Kofo O and Smith, Nicholas L and Kutlar, Abdullah and Glazer, Nicole L and Post, Wendy S and Paltoo, Dina N and Dries, Daniel L and Farlow, Deborah N and Duarte, Christine W and Kardia, Sharon L and Meyers, Kristin J and Sun, Yan V and Arnett, Donna K and Patki, Amit A and Sha, Jin and Cui, Xiangqui and Samdarshi, Tandaw E and Penman, Alan D and Bibbins-Domingo, Kirsten and B{\r u}zkov{\'a}, Petra and Benjamin, Emelia J and Bluemke, David A and Morrison, Alanna C and Heiss, Gerardo and Carr, J Jeffrey and Tracy, Russell P and Mosley, Thomas H and Taylor, Herman A and Psaty, Bruce M and Heckbert, Susan R and Cappola, Thomas P and Vasan, Ramachandran S} } @article {6152, title = {Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture.}, journal = {Nat Genet}, volume = {45}, year = {2013}, month = {2013 May}, pages = {501-12}, abstract = {

Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.

}, keywords = {Anthropometry, Body Height, Body Mass Index, Case-Control Studies, European Continental Ancestry Group, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Meta-Analysis as Topic, Obesity, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Waist-Hip Ratio}, issn = {1546-1718}, doi = {10.1038/ng.2606}, author = {Berndt, Sonja I and Gustafsson, Stefan and M{\"a}gi, Reedik and Ganna, Andrea and Wheeler, Eleanor and Feitosa, Mary F and Justice, Anne E and Monda, Keri L and Croteau-Chonka, Damien C and Day, Felix R and Esko, T{\~o}nu and Fall, Tove and Ferreira, Teresa and Gentilini, Davide and Jackson, Anne U and Luan, Jian{\textquoteright}an and Randall, Joshua C and Vedantam, Sailaja and Willer, Cristen J and Winkler, Thomas W and Wood, Andrew R and Workalemahu, Tsegaselassie and Hu, Yi-Juan and Lee, Sang Hong and Liang, Liming and Lin, Dan-Yu and Min, Josine L and Neale, Benjamin M and Thorleifsson, Gudmar and Yang, Jian and Albrecht, Eva and Amin, Najaf and Bragg-Gresham, Jennifer L and Cadby, Gemma and den Heijer, Martin and Eklund, Niina and Fischer, Krista and Goel, Anuj and Hottenga, Jouke-Jan and Huffman, Jennifer E and Jarick, Ivonne and Johansson, Asa and Johnson, Toby and Kanoni, Stavroula and Kleber, Marcus E and K{\"o}nig, Inke R and Kristiansson, Kati and Kutalik, Zolt{\'a}n and Lamina, Claudia and Lecoeur, C{\'e}cile and Li, Guo and Mangino, Massimo and McArdle, Wendy L and Medina-G{\'o}mez, Carolina and M{\"u}ller-Nurasyid, Martina and Ngwa, Julius S and Nolte, Ilja M and Paternoster, Lavinia and Pechlivanis, Sonali and Perola, Markus and Peters, Marjolein J and Preuss, Michael and Rose, Lynda M and Shi, Jianxin and Shungin, Dmitry and Smith, Albert Vernon and Strawbridge, Rona J and Surakka, Ida and Teumer, Alexander and Trip, Mieke D and Tyrer, Jonathan and van Vliet-Ostaptchouk, Jana V and Vandenput, Liesbeth and Waite, Lindsay L and Zhao, Jing Hua and Absher, Devin and Asselbergs, Folkert W and Atalay, Mustafa and Attwood, Antony P and Balmforth, Anthony J and Basart, Hanneke and Beilby, John and Bonnycastle, Lori L and Brambilla, Paolo and Bruinenberg, Marcel and Campbell, Harry and Chasman, Daniel I and Chines, Peter S and Collins, Francis S and Connell, John M and Cookson, William O and de Faire, Ulf and de Vegt, Femmie and Dei, Mariano and Dimitriou, Maria and Edkins, Sarah and Estrada, Karol and Evans, David M and Farrall, Martin and Ferrario, Marco M and Ferrieres, Jean and Franke, Lude and Frau, Francesca and Gejman, Pablo V and Grallert, Harald and Gr{\"o}nberg, Henrik and Gudnason, Vilmundur and Hall, Alistair S and Hall, Per and Hartikainen, Anna-Liisa and Hayward, Caroline and Heard-Costa, Nancy L and Heath, Andrew C and Hebebrand, Johannes and Homuth, Georg and Hu, Frank B and Hunt, Sarah E and Hypp{\"o}nen, Elina and Iribarren, Carlos and Jacobs, Kevin B and Jansson, John-Olov and Jula, Antti and K{\"a}h{\"o}nen, Mika and Kathiresan, Sekar and Kee, Frank and Khaw, Kay-Tee and Kivimaki, Mika and Koenig, Wolfgang and Kraja, Aldi T and Kumari, Meena and Kuulasmaa, Kari and Kuusisto, Johanna and Laitinen, Jaana H and Lakka, Timo A and Langenberg, Claudia and Launer, Lenore J and Lind, Lars and Lindstr{\"o}m, Jaana and Liu, Jianjun and Liuzzi, Antonio and Lokki, Marja-Liisa and Lorentzon, Mattias and Madden, Pamela A and Magnusson, Patrik K and Manunta, Paolo and Marek, Diana and M{\"a}rz, Winfried and Mateo Leach, Irene and McKnight, Barbara and Medland, Sarah E and Mihailov, Evelin and Milani, Lili and Montgomery, Grant W and Mooser, Vincent and M{\"u}hleisen, Thomas W and Munroe, Patricia B and Musk, Arthur W and Narisu, Narisu and Navis, Gerjan and Nicholson, George and Nohr, Ellen A and Ong, Ken K and Oostra, Ben A and Palmer, Colin N A and Palotie, Aarno and Peden, John F and Pedersen, Nancy and Peters, Annette and Polasek, Ozren and Pouta, Anneli and Pramstaller, Peter P and Prokopenko, Inga and P{\"u}tter, Carolin and Radhakrishnan, Aparna and Raitakari, Olli and Rendon, Augusto and Rivadeneira, Fernando and Rudan, Igor and Saaristo, Timo E and Sambrook, Jennifer G and Sanders, Alan R and Sanna, Serena and Saramies, Jouko and Schipf, Sabine and Schreiber, Stefan and Schunkert, Heribert and Shin, So-Youn and Signorini, Stefano and Sinisalo, Juha and Skrobek, Boris and Soranzo, Nicole and Stan{\v c}{\'a}kov{\'a}, Alena and Stark, Klaus and Stephens, Jonathan C and Stirrups, Kathleen and Stolk, Ronald P and Stumvoll, Michael and Swift, Amy J and Theodoraki, Eirini V and Thorand, Barbara and Tr{\'e}gou{\"e}t, David-Alexandre and Tremoli, Elena and van der Klauw, Melanie M and van Meurs, Joyce B J and Vermeulen, Sita H and Viikari, Jorma and Virtamo, Jarmo and Vitart, Veronique and Waeber, G{\'e}rard and Wang, Zhaoming and Widen, Elisabeth and Wild, Sarah H and Willemsen, Gonneke and Winkelmann, Bernhard R and Witteman, Jacqueline C M and Wolffenbuttel, Bruce H R and Wong, Andrew and Wright, Alan F and Zillikens, M Carola and Amouyel, Philippe and Boehm, Bernhard O and Boerwinkle, Eric and Boomsma, Dorret I and Caulfield, Mark J and Chanock, Stephen J and Cupples, L Adrienne and Cusi, Daniele and Dedoussis, George V and Erdmann, Jeanette and Eriksson, Johan G and Franks, Paul W and Froguel, Philippe and Gieger, Christian and Gyllensten, Ulf and Hamsten, Anders and Harris, Tamara B and Hengstenberg, Christian and Hicks, Andrew A and Hingorani, Aroon and Hinney, Anke and Hofman, Albert and Hovingh, Kees G and Hveem, Kristian and Illig, Thomas and Jarvelin, Marjo-Riitta and J{\"o}ckel, Karl-Heinz and Keinanen-Kiukaanniemi, Sirkka M and Kiemeney, Lambertus A and Kuh, Diana and Laakso, Markku and Lehtim{\"a}ki, Terho and Levinson, Douglas F and Martin, Nicholas G and Metspalu, Andres and Morris, Andrew D and Nieminen, Markku S and Nj{\o}lstad, Inger and Ohlsson, Claes and Oldehinkel, Albertine J and Ouwehand, Willem H and Palmer, Lyle J and Penninx, Brenda and Power, Chris and Province, Michael A and Psaty, Bruce M and Qi, Lu and Rauramaa, Rainer and Ridker, Paul M and Ripatti, Samuli and Salomaa, Veikko and Samani, Nilesh J and Snieder, Harold and S{\o}rensen, Thorkild I A and Spector, Timothy D and Stefansson, Kari and T{\"o}njes, Anke and Tuomilehto, Jaakko and Uitterlinden, Andr{\'e} G and Uusitupa, Matti and van der Harst, Pim and Vollenweider, Peter and Wallaschofski, Henri and Wareham, Nicholas J and Watkins, Hugh and Wichmann, H-Erich and Wilson, James F and Abecasis, Goncalo R and Assimes, Themistocles L and Barroso, In{\^e}s and Boehnke, Michael and Borecki, Ingrid B and Deloukas, Panos and Fox, Caroline S and Frayling, Timothy and Groop, Leif C and Haritunian, Talin and Heid, Iris M and Hunter, David and Kaplan, Robert C and Karpe, Fredrik and Moffatt, Miriam F and Mohlke, Karen L and O{\textquoteright}Connell, Jeffrey R and Pawitan, Yudi and Schadt, Eric E and Schlessinger, David and Steinthorsdottir, Valgerdur and Strachan, David P and Thorsteinsdottir, Unnur and van Duijn, Cornelia M and Visscher, Peter M and Di Blasio, Anna Maria and Hirschhorn, Joel N and Lindgren, Cecilia M and Morris, Andrew P and Meyre, David and Scherag, Andre and McCarthy, Mark I and Speliotes, Elizabeth K and North, Kari E and Loos, Ruth J F and Ingelsson, Erik} } @article {6136, title = {Kidney function and prevalent and incident frailty.}, journal = {Clin J Am Soc Nephrol}, volume = {8}, year = {2013}, month = {2013 Dec}, pages = {2091-9}, abstract = {

BACKGROUND AND OBJECTIVES: Kidney disease is associated with physiologic changes that may predispose to frailty. This study sought to investigate whether lower levels of kidney function were associated with prevalent or incident frailty in Cardiovascular Health Study (CHS) participants.

DESIGN, SETTING, PARTICIPANTS, \& MEASUREMENTS: CHS enrolled community-dwelling adults age >=65 years between 1989-1990 and 1992-1993. To examine prevalent frailty, included were 4150 participants without stroke, Parkinson disease, prescribed medications for Alzheimer disease or depression, or severely impaired cognition. To examine incident frailty, included were a subset of 3459 participants without baseline frailty or development of exclusion criteria during follow-up. The primary predictor was estimated GFR (eGFR) calculated using serum cystatin C (eGFR(cys)). Secondary analyses examined eGFR using serum creatinine (eGFR(SCr)). Outcomes were prevalent frailty and incident frailty at 4 years of follow-up. Frailty was ascertained on the basis of weight loss, exhaustion, weakness, slowness, and low physical activity.

RESULTS: The mean age was 75 years and the median eGFR(cys) was 73 ml/min per 1.73 m(2). Among participants with an eGFR(cys) <45 ml/min per 1.73 m(2), 24\% had prevalent frailty. In multivariable analysis and compared with eGFR(cys) >=90 ml/min per 1.73 m(2), eGFR(cys) categories of 45-59 (odds ratio [OR], 1.80; 95\% confidence interval [CI], 1.17 to 2.75) and 15-44 (OR, 2.87; 95\% CI, 1.72 to 4.77) were associated with higher odds of frailty, whereas 60-75 (OR, 1.14; 95\% CI, 0.76 to 1.70) was not. In multivariable analysis, eGFR(cys) categories of 60-75 (incidence rate ratio [IRR], 1.72; 95\% CI, 1.07 to 2.75) and 15-44 (IRR, 2.28; 95\% CI, 1.23 to 4.22) were associated with higher incidence of frailty whereas 45-59 (IRR, 1.53; 95\% CI, 0.90 to 2.60) was not. Lower levels of eGFR(SCr) were not associated with higher risk of prevalent or incident frailty.

CONCLUSIONS: In community-dwelling elders, lower eGFR(cys) was associated with a higher risk of prevalent and incident frailty whereas lower eGFR(SCr) was not. These findings highlight the importance of considering non-GFR determinants of kidney function.

}, keywords = {Age Factors, Aged, Aged, 80 and over, Aging, Biomarkers, Creatinine, Cross-Sectional Studies, Cystatin C, Fatigue, Female, Frail Elderly, Geriatric Assessment, Glomerular Filtration Rate, Humans, Incidence, Independent Living, Kidney, Kidney Diseases, Logistic Models, Male, Motor Activity, Multivariate Analysis, Muscle Weakness, Odds Ratio, Phenotype, Prevalence, Prospective Studies, Risk Factors, Time Factors, United States, Weight Loss}, issn = {1555-905X}, doi = {10.2215/CJN.02870313}, author = {Dalrymple, Lorien S and Katz, Ronit and Rifkin, Dena E and Siscovick, David and Newman, Anne B and Fried, Linda F and Sarnak, Mark J and Odden, Michelle C and Shlipak, Michael G} } @article {6094, title = {Lack of associations of ten candidate coronary heart disease risk genetic variants and subclinical atherosclerosis in four US populations: the Population Architecture using Genomics and Epidemiology (PAGE) study.}, journal = {Atherosclerosis}, volume = {228}, year = {2013}, month = {2013 Jun}, pages = {390-9}, abstract = {

BACKGROUND: A number of genetic variants have been discovered by recent genome-wide association studies for their associations with clinical coronary heart disease (CHD). However, it is unclear whether these variants are also associated with the development of CHD as measured by subclinical atherosclerosis phenotypes, ankle brachial index (ABI), carotid artery intima-media thickness (cIMT) and carotid plaque.

METHODS: Ten CHD risk single nucleotide polymorphisms (SNPs) were genotyped in individuals of European American (EA), African American (AA), American Indian (AI), and Mexican American (MA) ancestry in the Population Architecture using Genomics and Epidemiology (PAGE) study. In each individual study, we performed linear or logistic regression to examine population-specific associations between SNPs and ABI, common and internal cIMT, and plaque. The results from individual studies were meta-analyzed using a fixed effect inverse variance weighted model.

RESULTS: None of the ten SNPs was significantly associated with ABI and common or internal cIMT, after Bonferroni correction. In the sample of 13,337 EA, 3809 AA, and 5353 AI individuals with carotid plaque measurement, the GCKR SNP rs780094 was significantly associated with the presence of plaque in AI only (OR~=~1.32, 95\% confidence interval: 1.17, 1.49, P~=~1.08~{\texttimes}~10(-5)), but not in the other populations (P~=~0.90 in EA and P~=~0.99 in AA). A 9p21 region SNP, rs1333049, was nominally associated with plaque in EA (OR~=~1.07, P~=~0.02) and in AI (OR~=~1.10, P~=~0.05).

CONCLUSIONS: We identified a significant association between rs780094 and plaque in AI populations, which needs to be replicated in future studies. There was little evidence that the index CHD risk variants identified through genome-wide association studies in EA influence the development of CHD through subclinical atherosclerosis as assessed by cIMT and ABI across ancestries.

}, keywords = {African Americans, Aged, Ankle Brachial Index, Asymptomatic Diseases, Carotid Artery Diseases, Carotid Intima-Media Thickness, Coronary Disease, European Continental Ancestry Group, Female, Gene Frequency, Genetic Association Studies, Genetic Predisposition to Disease, Humans, Indians, North American, Linear Models, Logistic Models, Male, Mexican Americans, Middle Aged, Odds Ratio, Phenotype, Polymorphism, Single Nucleotide, Predictive Value of Tests, Risk Assessment, Risk Factors, United States}, issn = {1879-1484}, doi = {10.1016/j.atherosclerosis.2013.02.038}, author = {Zhang, Lili and B{\r u}zkov{\'a}, Petra and Wassel, Christina L and Roman, Mary J and North, Kari E and Crawford, Dana C and Boston, Jonathan and Brown-Gentry, Kristin D and Cole, Shelley A and Deelman, Ewa and Goodloe, Robert and Wilson, Sarah and Heiss, Gerardo and Jenny, Nancy S and Jorgensen, Neal W and Matise, Tara C and McClellan, Bob E and Nato, Alejandro Q and Ritchie, Marylyn D and Franceschini, Nora and Kao, W H Linda} } @article {6281, title = {Lipoprotein receptor-related protein 1 variants and dietary fatty acids: meta-analysis of European origin and African American studies.}, journal = {Int J Obes (Lond)}, volume = {37}, year = {2013}, month = {2013 Sep}, pages = {1211-20}, abstract = {

OBJECTIVE: Low-density lipoprotein-related receptor protein 1 (LRP1) is a multi-functional endocytic receptor and signaling molecule that is expressed in adipose and the hypothalamus. Evidence for a role of LRP1 in adiposity is accumulating from animal and in vitro models, but data from human studies are limited. The study objectives were to evaluate (i) relationships between LRP1 genotype and anthropometric traits, and (ii) whether these relationships were modified by dietary fatty acids.

DESIGN AND METHODS: We conducted race/ethnic-specific meta-analyses using data from 14 studies of US and European whites and 4 of African Americans to evaluate associations of dietary fatty acids and LRP1 genotypes with body mass index (BMI), waist circumference and hip circumference, as well as interactions between dietary fatty acids and LRP1 genotypes. Seven single-nucleotide polymorphisms (SNPs) of LRP1 were evaluated in whites (N up to 42 000) and twelve SNPs in African Americans (N up to 5800).

RESULTS: After adjustment for age, sex and population substructure if relevant, for each one unit greater intake of percentage of energy from saturated fat (SFA), BMI was 0.104 kg m(-2) greater, waist was 0.305 cm larger and hip was 0.168 cm larger (all P<0.0001). Other fatty acids were not associated with outcomes. The association of SFA with outcomes varied by genotype at rs2306692 (genotyped in four studies of whites), where the magnitude of the association of SFA intake with each outcome was greater per additional copy of the T allele: 0.107 kg m(-2) greater for BMI (interaction P=0.0001), 0.267 cm for waist (interaction P=0.001) and 0.21 cm for hip (interaction P=0.001). No other significant interactions were observed.

CONCLUSION: Dietary SFA and LRP1 genotype may interactively influence anthropometric traits. Further exploration of this, and other diet x genotype interactions, may improve understanding of interindividual variability in the relationships of dietary factors with anthropometric traits.

}, keywords = {Adipose Tissue, Adult, African Continental Ancestry Group, Aged, Aged, 80 and over, Body Mass Index, Europe, European Continental Ancestry Group, Fatty Acids, Female, Gene Frequency, Gene-Environment Interaction, Genetic Predisposition to Disease, Genotype, Humans, Low Density Lipoprotein Receptor-Related Protein-1, Male, Middle Aged, Obesity, Phenotype, Polymorphism, Single Nucleotide, Prevalence, United States}, issn = {1476-5497}, doi = {10.1038/ijo.2012.215}, author = {Smith, C E and Ngwa, J and Tanaka, T and Qi, Q and Wojczynski, M K and Lemaitre, R N and Anderson, J S and Manichaikul, A and Mikkil{\"a}, V and van Rooij, F J A and Ye, Z and Bandinelli, S and Frazier-Wood, A C and Houston, D K and Hu, F and Langenberg, C and McKeown, N M and Mozaffarian, D and North, K E and Viikari, J and Zillikens, M C and Djouss{\'e}, L and Hofman, A and K{\"a}h{\"o}nen, M and Kabagambe, E K and Loos, R J F and Saylor, G B and Forouhi, N G and Liu, Y and Mukamal, K J and Chen, Y-D I and Tsai, M Y and Uitterlinden, A G and Raitakari, O and van Duijn, C M and Arnett, D K and Borecki, I B and Cupples, L A and Ferrucci, L and Kritchevsky, S B and Lehtim{\"a}ki, T and Qi, Lu and Rotter, J I and Siscovick, D S and Wareham, N J and Witteman, J C M and Ordov{\'a}s, J M and Nettleton, J A} } @article {5877, title = {A meta-analysis of thyroid-related traits reveals novel loci and gender-specific differences in the regulation of thyroid function.}, journal = {PLoS Genet}, volume = {9}, year = {2013}, month = {2013}, pages = {e1003266}, abstract = {

Thyroid hormone is essential for normal metabolism and development, and overt abnormalities in thyroid function lead to common endocrine disorders affecting approximately 10\% of individuals over their life span. In addition, even mild alterations in thyroid function are associated with weight changes, atrial fibrillation, osteoporosis, and psychiatric disorders. To identify novel variants underlying thyroid function, we performed a large meta-analysis of genome-wide association studies for serum levels of the highly heritable thyroid function markers TSH and FT4, in up to 26,420 and 17,520 euthyroid subjects, respectively. Here we report 26 independent associations, including several novel loci for TSH (PDE10A, VEGFA, IGFBP5, NFIA, SOX9, PRDM11, FGF7, INSR, ABO, MIR1179, NRG1, MBIP, ITPK1, SASH1, GLIS3) and FT4 (LHX3, FOXE1, AADAT, NETO1/FBXO15, LPCAT2/CAPNS2). Notably, only limited overlap was detected between TSH and FT4 associated signals, in spite of the feedback regulation of their circulating levels by the hypothalamic-pituitary-thyroid axis. Five of the reported loci (PDE8B, PDE10A, MAF/LOC440389, NETO1/FBXO15, and LPCAT2/CAPNS2) show strong gender-specific differences, which offer clues for the known sexual dimorphism in thyroid function and related pathologies. Importantly, the TSH-associated loci contribute not only to variation within the normal range, but also to TSH values outside the reference range, suggesting that they may be involved in thyroid dysfunction. Overall, our findings explain, respectively, 5.64\% and 2.30\% of total TSH and FT4 trait variance, and they improve the current knowledge of the regulation of hypothalamic-pituitary-thyroid axis function and the consequences of genetic variation for hypo- or hyperthyroidism.

}, keywords = {Female, Genome-Wide Association Study, Humans, Hyperthyroidism, Hypothyroidism, Male, Phenotype, Polymorphism, Genetic, Polymorphism, Single Nucleotide, Sex Characteristics, Signal Transduction, Thyroid Gland, Thyrotropin, Thyroxine}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1003266}, author = {Porcu, Eleonora and Medici, Marco and Pistis, Giorgio and Volpato, Claudia B and Wilson, Scott G and Cappola, Anne R and Bos, Steffan D and Deelen, Joris and den Heijer, Martin and Freathy, Rachel M and Lahti, Jari and Liu, Chunyu and Lopez, Lorna M and Nolte, Ilja M and O{\textquoteright}Connell, Jeffrey R and Tanaka, Toshiko and Trompet, Stella and Arnold, Alice and Bandinelli, Stefania and Beekman, Marian and B{\"o}hringer, Stefan and Brown, Suzanne J and Buckley, Brendan M and Camaschella, Clara and de Craen, Anton J M and Davies, Gail and de Visser, Marieke C H and Ford, Ian and Forsen, Tom and Frayling, Timothy M and Fugazzola, Laura and G{\"o}gele, Martin and Hattersley, Andrew T and Hermus, Ad R and Hofman, Albert and Houwing-Duistermaat, Jeanine J and Jensen, Richard A and Kajantie, Eero and Kloppenburg, Margreet and Lim, Ee M and Masciullo, Corrado and Mariotti, Stefano and Minelli, Cosetta and Mitchell, Braxton D and Nagaraja, Ramaiah and Netea-Maier, Romana T and Palotie, Aarno and Persani, Luca and Piras, Maria G and Psaty, Bruce M and R{\"a}ikk{\"o}nen, Katri and Richards, J Brent and Rivadeneira, Fernando and Sala, Cinzia and Sabra, Mona M and Sattar, Naveed and Shields, Beverley M and Soranzo, Nicole and Starr, John M and Stott, David J and Sweep, Fred C G J and Usala, Gianluca and van der Klauw, Melanie M and van Heemst, Diana and van Mullem, Alies and Vermeulen, Sita H and Visser, W Edward and Walsh, John P and Westendorp, Rudi G J and Widen, Elisabeth and Zhai, Guangju and Cucca, Francesco and Deary, Ian J and Eriksson, Johan G and Ferrucci, Luigi and Fox, Caroline S and Jukema, J Wouter and Kiemeney, Lambertus A and Pramstaller, Peter P and Schlessinger, David and Shuldiner, Alan R and Slagboom, Eline P and Uitterlinden, Andr{\'e} G and Vaidya, Bijay and Visser, Theo J and Wolffenbuttel, Bruce H R and Meulenbelt, Ingrid and Rotter, Jerome I and Spector, Tim D and Hicks, Andrew A and Toniolo, Daniela and Sanna, Serena and Peeters, Robin P and Naitza, Silvia} } @article {6074, title = {Resequencing and clinical associations of the 9p21.3 region: a comprehensive investigation in the Framingham heart study.}, journal = {Circulation}, volume = {127}, year = {2013}, month = {2013 Feb 19}, pages = {799-810}, abstract = {

BACKGROUND: 9p21.3 is among the most strongly replicated regions for cardiovascular disease. There are few reports of sequencing the associated 9p21.3 interval. We set out to sequence the 9p21.3 region followed by a comprehensive study of genetic associations with clinical and subclinical cardiovascular disease and its risk factors, as well as with copy number variation and gene expression, in the Framingham Heart Study (FHS).

METHODS AND RESULTS: We sequenced 281 individuals (94 with myocardial infarction, 94 with high coronary artery calcium levels, and 93 control subjects free of elevated coronary artery calcium or myocardial infarction), followed by genotyping and association in >7000 additional FHS individuals. We assessed genetic associations with clinical and subclinical cardiovascular disease, risk factor phenotypes, and gene expression levels of the protein-coding genes CDKN2A and CDKN2B and the noncoding gene ANRIL in freshly harvested leukocytes and platelets. Within this large sample, we found strong associations of 9p21.3 variants with increased risk for myocardial infarction, higher coronary artery calcium levels, and larger abdominal aorta diameters and no evidence for association with traditional cardiovascular disease risk factors. No common protein-coding variation, variants in splice donor or acceptor sites, or copy number variation events were observed. By contrast, strong associations were observed between genetic variants and gene expression, particularly for a short isoform of ANRIL and for CDKN2B.

CONCLUSIONS: Our thorough genomic characterization of 9p21.3 suggests common variants likely account for observed disease associations and provides further support for the hypothesis that complex regulatory variation affecting ANRIL and CDKN2B gene expression may contribute to increased risk for clinically apparent and subclinical coronary artery disease and aortic disease.

}, keywords = {Calcinosis, Chromosomes, Human, Pair 9, Coronary Artery Disease, Cyclin-Dependent Kinase Inhibitor p15, Cyclin-Dependent Kinase Inhibitor p16, DNA Copy Number Variations, Female, Follow-Up Studies, Genetic Predisposition to Disease, Genotype, Humans, Longitudinal Studies, Male, Massachusetts, Middle Aged, Myocardial Infarction, Phenotype, Polymorphism, Single Nucleotide, Risk Factors, RNA, Long Noncoding, Sequence Analysis, DNA}, issn = {1524-4539}, doi = {10.1161/CIRCULATIONAHA.112.111559}, author = {Johnson, Andrew D and Hwang, Shih-Jen and Voorman, Arend and Morrison, Alanna and Peloso, Gina M and Hsu, Yi-Hsiang and Thanassoulis, George and Newton-Cheh, Christopher and Rogers, Ian S and Hoffmann, Udo and Freedman, Jane E and Fox, Caroline S and Psaty, Bruce M and Boerwinkle, Eric and Cupples, L Adrienne and O{\textquoteright}Donnell, Christopher J} } @article {1564, title = {Soluble CD14: genomewide association analysis and relationship to cardiovascular risk and mortality in older adults.}, journal = {Arterioscler Thromb Vasc Biol}, volume = {33}, year = {2013}, month = {2013 Jan}, pages = {158-64}, abstract = {

OBJECTIVE: CD14 is a glycosylphosphotidylinositol-anchored membrane glycoprotein expressed on neutrophils and monocytes/macrophages that also circulates as a soluble form (sCD14). Despite the well-recognized role of CD14 in inflammation, relatively little is known about the genetic determinants of sCD14 or the relationship of sCD14 to vascular- and aging-related phenotypes.

METHODS AND RESULTS: We measured baseline levels of sCD14 in >5000 European-American and black adults aged 65 years and older from the Cardiovascular Health Study, who were well characterized at baseline for atherosclerotic risk factors and subclinical cardiovascular disease, and who have been followed for clinical cardiovascular disease and mortality outcomes up to 20 years. At baseline, sCD14 generally showed strong positive correlations with traditional cardio-metabolic risk factors and with subclinical measures of vascular disease such as carotid wall thickness and ankle-brachial index (independently of traditional cardiovascular disease risk factors), and was also inversely correlated with body mass index. In genomewide association analyses of sCD14, we (1) confirmed the importance of the CD14 locus on chromosome 5q21 in European-American; (2) identified a novel African ancestry-specific allele of CD14 associated with lower sCD14 in blacks; and (3) identified a putative novel association in European-American of a nonsynonymous variant of PIGC, which encodes an enzyme required for the first step in glycosylphosphotidylinositol anchor biosynthesis. Finally, we show that, like other acute phase inflammatory biomarkers, sCD14 predicts incident cardiovascular disease, and strongly and independently predicts all-cause mortality in older adults.

CONCLUSIONS: CD14 independently predicts risk mortality in older adults.

}, keywords = {African Americans, Age Factors, Aged, Biomarkers, Cardiovascular Diseases, Chromosomes, Human, Pair 5, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Haplotypes, Hexosyltransferases, Humans, Incidence, Inflammation Mediators, Linear Models, Lipopolysaccharide Receptors, Logistic Models, Male, Membrane Proteins, Multivariate Analysis, Phenotype, Polymorphism, Single Nucleotide, Principal Component Analysis, Prognosis, Proportional Hazards Models, Prospective Studies, Risk Assessment, Risk Factors, Time Factors, United States}, issn = {1524-4636}, doi = {10.1161/ATVBAHA.112.300421}, author = {Reiner, Alex P and Lange, Ethan M and Jenny, Nancy S and Chaves, Paulo H M and Ellis, Jaclyn and Li, Jin and Walston, Jeremy and Lange, Leslie A and Cushman, Mary and Tracy, Russell P} } @article {6590, title = {Association of low-frequency and rare coding-sequence variants with blood lipids and coronary heart disease in 56,000 whites and blacks.}, journal = {Am J Hum Genet}, volume = {94}, year = {2014}, month = {2014 Feb 06}, pages = {223-32}, abstract = {

Low-frequency coding DNA sequence variants in the proprotein convertase subtilisin/kexin type 9 gene (PCSK9) lower plasma low-density lipoprotein cholesterol (LDL-C), protect against risk of coronary heart disease (CHD), and have prompted the development of a new class of therapeutics. It is uncertain whether the PCSK9 example represents a paradigm or an isolated exception. We used the "Exome Array" to genotype >200,000 low-frequency and rare coding sequence variants across the genome in 56,538 individuals (42,208 European ancestry [EA] and 14,330 African ancestry [AA]) and tested these variants for association with LDL-C, high-density lipoprotein cholesterol (HDL-C), and triglycerides. Although we did not identify new genes associated with LDL-C, we did identify four low-frequency (frequencies between 0.1\% and 2\%) variants (ANGPTL8 rs145464906 [c.361C>T; p.Gln121*], PAFAH1B2 rs186808413 [c.482C>T; p.Ser161Leu], COL18A1 rs114139997 [c.331G>A; p.Gly111Arg], and PCSK7 rs142953140 [c.1511G>A; p.Arg504His]) with large effects on HDL-C and/or triglycerides. None of these four variants was associated with risk for CHD, suggesting that examples of low-frequency coding variants with robust effects on both lipids and CHD will be limited.

}, keywords = {1-Alkyl-2-acetylglycerophosphocholine Esterase, Adult, African Continental Ancestry Group, Aged, Alleles, Animals, Cholesterol, HDL, Cholesterol, LDL, Cohort Studies, Coronary Disease, European Continental Ancestry Group, Female, Gene Frequency, Genetic Association Studies, Genetic Code, Genetic Variation, Humans, Linear Models, Male, Mice, Mice, Inbred C57BL, Microtubule-Associated Proteins, Middle Aged, Phenotype, Sequence Analysis, DNA, Subtilisins, Triglycerides}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2014.01.009}, author = {Peloso, Gina M and Auer, Paul L and Bis, Joshua C and Voorman, Arend and Morrison, Alanna C and Stitziel, Nathan O and Brody, Jennifer A and Khetarpal, Sumeet A and Crosby, Jacy R and Fornage, Myriam and Isaacs, Aaron and Jakobsdottir, Johanna and Feitosa, Mary F and Davies, Gail and Huffman, Jennifer E and Manichaikul, Ani and Davis, Brian and Lohman, Kurt and Joon, Aron Y and Smith, Albert V and Grove, Megan L and Zanoni, Paolo and Redon, Valeska and Demissie, Serkalem and Lawson, Kim and Peters, Ulrike and Carlson, Christopher and Jackson, Rebecca D and Ryckman, Kelli K and Mackey, Rachel H and Robinson, Jennifer G and Siscovick, David S and Schreiner, Pamela J and Mychaleckyj, Josyf C and Pankow, James S and Hofman, Albert and Uitterlinden, Andr{\'e} G and Harris, Tamara B and Taylor, Kent D and Stafford, Jeanette M and Reynolds, Lindsay M and Marioni, Riccardo E and Dehghan, Abbas and Franco, Oscar H and Patel, Aniruddh P and Lu, Yingchang and Hindy, George and Gottesman, Omri and Bottinger, Erwin P and Melander, Olle and Orho-Melander, Marju and Loos, Ruth J F and Duga, Stefano and Merlini, Piera Angelica and Farrall, Martin and Goel, Anuj and Asselta, Rosanna and Girelli, Domenico and Martinelli, Nicola and Shah, Svati H and Kraus, William E and Li, Mingyao and Rader, Daniel J and Reilly, Muredach P and McPherson, Ruth and Watkins, Hugh and Ardissino, Diego and Zhang, Qunyuan and Wang, Judy and Tsai, Michael Y and Taylor, Herman A and Correa, Adolfo and Griswold, Michael E and Lange, Leslie A and Starr, John M and Rudan, Igor and Eiriksdottir, Gudny and Launer, Lenore J and Ordovas, Jose M and Levy, Daniel and Chen, Y-D Ida and Reiner, Alexander P and Hayward, Caroline and Polasek, Ozren and Deary, Ian J and Borecki, Ingrid B and Liu, Yongmei and Gudnason, Vilmundur and Wilson, James G and van Duijn, Cornelia M and Kooperberg, Charles and Rich, Stephen S and Psaty, Bruce M and Rotter, Jerome I and O{\textquoteright}Donnell, Christopher J and Rice, Kenneth and Boerwinkle, Eric and Kathiresan, Sekar and Cupples, L Adrienne} } @article {6563, title = {Effects of long-term averaging of quantitative blood pressure traits on the detection of genetic associations.}, journal = {Am J Hum Genet}, volume = {95}, year = {2014}, month = {2014 Jul 03}, pages = {49-65}, abstract = {

Blood pressure (BP) is a heritable, quantitative trait with intraindividual variability and susceptibility to measurement error. Genetic studies of BP generally use single-visit measurements and thus cannot remove variability occurring over months or years. We leveraged the idea that averaging BP measured across time would improve phenotypic accuracy and thereby increase statistical power to detect genetic associations. We studied systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP) averaged over multiple years in 46,629 individuals of European ancestry. We identified 39 trait-variant associations across 19 independent loci (p < 5 {\texttimes} 10(-8)); five associations (in four loci) uniquely identified by our LTA analyses included those of SBP and MAP at 2p23 (rs1275988, near KCNK3), DBP at 2q11.2 (rs7599598, in FER1L5), and PP at 6p21 (rs10948071, near CRIP3) and 7p13 (rs2949837, near IGFBP3). Replication analyses conducted in cohorts with single-visit BP data showed positive replication of associations and a nominal association (p < 0.05). We estimated a 20\% gain in statistical power with long-term average (LTA) as compared to single-visit BP association studies. Using LTA analysis, we identified genetic loci influencing BP. LTA might be one way of increasing the power of genetic associations for continuous traits in extant samples for other phenotypes that are measured serially over time.

}, keywords = {Blood Pressure, Genome-Wide Association Study, Humans, Longitudinal Studies, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2014.06.002}, author = {Ganesh, Santhi K and Chasman, Daniel I and Larson, Martin G and Guo, Xiuqing and Verwoert, Germain and Bis, Joshua C and Gu, Xiangjun and Smith, Albert V and Yang, Min-Lee and Zhang, Yan and Ehret, Georg and Rose, Lynda M and Hwang, Shih-Jen and Papanicolau, George J and Sijbrands, Eric J and Rice, Kenneth and Eiriksdottir, Gudny and Pihur, Vasyl and Ridker, Paul M and Vasan, Ramachandran S and Newton-Cheh, Christopher and Raffel, Leslie J and Amin, Najaf and Rotter, Jerome I and Liu, Kiang and Launer, Lenore J and Xu, Ming and Caulfield, Mark and Morrison, Alanna C and Johnson, Andrew D and Vaidya, Dhananjay and Dehghan, Abbas and Li, Guo and Bouchard, Claude and Harris, Tamara B and Zhang, He and Boerwinkle, Eric and Siscovick, David S and Gao, Wei and Uitterlinden, Andr{\'e} G and Rivadeneira, Fernando and Hofman, Albert and Willer, Cristen J and Franco, Oscar H and Huo, Yong and Witteman, Jacqueline C M and Munroe, Patricia B and Gudnason, Vilmundur and Palmas, Walter and van Duijn, Cornelia and Fornage, Myriam and Levy, Daniel and Psaty, Bruce M and Chakravarti, Aravinda} } @article {6598, title = {Evidence of heterogeneity by race/ethnicity in genetic determinants of QT interval.}, journal = {Epidemiology}, volume = {25}, year = {2014}, month = {2014 Nov}, pages = {790-8}, abstract = {

BACKGROUND: QT interval (QT) prolongation is an established risk factor for ventricular tachyarrhythmia and sudden cardiac death. Previous genome-wide association studies in populations of the European descent have identified multiple genetic loci that influence QT, but few have examined these loci in ethnically diverse populations.

METHODS: Here, we examine the direction, magnitude, and precision of effect sizes for 21 previously reported SNPs from 12 QT loci, in populations of European (n = 16,398), African (n = 5,437), American Indian (n = 5,032), Hispanic (n = 1,143), and Asian (n = 932) descent as part of the Population Architecture using Genomics and Epidemiology (PAGE) study. Estimates obtained from linear regression models stratified by race/ethnicity were combined using inverse-variance weighted meta-analysis. Heterogeneity was evaluated using Cochran{\textquoteright}s Q test.

RESULTS: Of 21 SNPs, 7 showed consistent direction of effect across all 5 populations, and an additional 9 had estimated effects that were consistent across 4 populations. Despite consistent direction of effect, 9 of 16 SNPs had evidence (P < 0.05) of heterogeneity by race/ethnicity. For these 9 SNPs, linkage disequilibrium plots often indicated substantial variation in linkage disequilibrium patterns among the various racial/ethnic groups, as well as possible allelic heterogeneity.

CONCLUSIONS: These results emphasize the importance of analyzing racial/ethnic groups separately in genetic studies. Furthermore, they underscore the possible utility of trans-ethnic studies to pinpoint underlying casual variants influencing heritable traits such as QT.

}, keywords = {Aged, Continental Population Groups, Electrocardiography, Female, Genetic Predisposition to Disease, Haplotypes, Humans, Long QT Syndrome, Male, Middle Aged, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Quantitative Trait, Heritable, Risk Factors}, issn = {1531-5487}, doi = {10.1097/EDE.0000000000000168}, author = {Seyerle, Amanda A and Young, Alicia M and Jeff, Janina M and Melton, Phillip E and Jorgensen, Neal W and Lin, Yi and Carty, Cara L and Deelman, Ewa and Heckbert, Susan R and Hindorff, Lucia A and Jackson, Rebecca D and Martin, Lisa W and Okin, Peter M and Perez, Marco V and Psaty, Bruce M and Soliman, Elsayed Z and Whitsel, Eric A and North, Kari E and Laston, Sandra and Kooperberg, Charles and Avery, Christy L} } @article {7019, title = {Genetic determinants of age-related macular degeneration in diverse populations from the PAGE study.}, journal = {Invest Ophthalmol Vis Sci}, volume = {55}, year = {2014}, month = {2014 Sep 9}, pages = {6839-50}, abstract = {

PURPOSE: Substantial progress has been made in identifying susceptibility variants for AMD in European populations; however, few studies have been conducted to understand the role these variants play in AMD risk in diverse populations. The present study aims to examine AMD risk across diverse populations in known and suspected AMD complement factor and lipid-related loci.

METHODS: Targeted genotyping was performed across study sites for AMD and lipid trait-associated single nucleotide polymorphism (SNPs). Genetic association tests were performed at individual sites and then meta-analyzed using logistic regression assuming an additive genetic model stratified by self-described race/ethnicity. Participants included cases with early or late AMD and controls with no signs of AMD as determined by fundus photography. Populations included in this study were European Americans, African Americans, Mexican Americans, and Singaporeans from the Population Architecture using Genomics and Epidemiology (PAGE) study.

RESULTS: Index variants of AMD, rs1061170 (CFH) and rs10490924 (ARMS2), were associated with AMD at P=3.05{\texttimes}10(-8) and P=6.36{\texttimes}10(-6), respectively, in European Americans. In general, none of the major AMD index variants generalized to our non-European populations with the exception of rs10490924 in Mexican Americans at an uncorrected P value<0.05. Four lipid-associated SNPS (LPL rs328, TRIB1 rs6987702, CETP rs1800775, and KCTD10/MVK rs2338104) were associated with AMD in African Americans and Mexican Americans (P<0.05), but these associations did not survive strict corrections for multiple testing.

CONCLUSIONS: While most associations did not generalize in the non-European populations, variants within lipid-related genes were found to be associated with AMD. This study highlights the need for larger well-powered studies in non-European populations.

}, keywords = {Adult, Aged, Aged, 80 and over, Complement Factor H, DNA, Ethnic Groups, Female, Gene Frequency, Genetic Predisposition to Disease, Genotype, Humans, Macular Degeneration, Male, Middle Aged, Phenotype, Polymorphism, Single Nucleotide, Prevalence, Prospective Studies, Proteins, Risk Factors, United States}, issn = {1552-5783}, doi = {10.1167/iovs.14-14246}, author = {Restrepo, Nicole A and Spencer, Kylee L and Goodloe, Robert and Garrett, Tiana A and Heiss, Gerardo and B{\r u}zkov{\'a}, Petra and Jorgensen, Neal and Jensen, Richard A and Matise, Tara C and Hindorff, Lucia A and Klein, Barbara E K and Klein, Ronald and Wong, Tien Y and Cheng, Ching-Yu and Cornes, Belinda K and Tai, E-Shyong and Ritchie, Marylyn D and Haines, Jonathan L and Crawford, Dana C} } @article {6367, title = {Genome-wide association study for circulating tissue plasminogen activator levels and functional follow-up implicates endothelial STXBP5 and STX2.}, journal = {Arterioscler Thromb Vasc Biol}, volume = {34}, year = {2014}, month = {2014 May}, pages = {1093-101}, abstract = {

OBJECTIVE: Tissue plasminogen activator (tPA), a serine protease, catalyzes the conversion of plasminogen to plasmin, the major enzyme responsible for endogenous fibrinolysis. In some populations, elevated plasma levels of tPA have been associated with myocardial infarction and other cardiovascular diseases. We conducted a meta-analysis of genome-wide association studies to identify novel correlates of circulating levels of tPA.

APPROACH AND RESULTS: Fourteen cohort studies with tPA measures (N=26 929) contributed to the meta-analysis. Three loci were significantly associated with circulating tPA levels (P<5.0{\texttimes}10(-8)). The first locus is on 6q24.3, with the lead single nucleotide polymorphism (SNP; rs9399599; P=2.9{\texttimes}10(-14)) within STXBP5. The second locus is on 8p11.21. The lead SNP (rs3136739; P=1.3{\texttimes}10(-9)) is intronic to POLB and <200 kb away from the tPA encoding the gene PLAT. We identified a nonsynonymous SNP (rs2020921) in modest linkage disequilibrium with rs3136739 (r(2)=0.50) within exon 5 of PLAT (P=2.0{\texttimes}10(-8)). The third locus is on 12q24.33, with the lead SNP (rs7301826; P=1.0{\texttimes}10(-9)) within intron 7 of STX2. We further found evidence for the association of lead SNPs in STXBP5 and STX2 with expression levels of the respective transcripts. In in vitro cell studies, silencing STXBP5 decreased the release of tPA from vascular endothelial cells, whereas silencing STX2 increased the tPA release. Through an in silico lookup, we found no associations of the 3 lead SNPs with coronary artery disease or stroke.

CONCLUSIONS: We identified 3 loci associated with circulating tPA levels, the PLAT region, STXBP5, and STX2. Our functional studies implicate a novel role for STXBP5 and STX2 in regulating tPA release.

}, keywords = {Aged, Cells, Cultured, Coronary Artery Disease, Endothelial Cells, Europe, Female, Gene Expression Regulation, Gene Silencing, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Middle Aged, Nerve Tissue Proteins, Phenotype, Polymorphism, Single Nucleotide, R-SNARE Proteins, Risk Factors, Stroke, Syntaxin 1, Tissue Plasminogen Activator, Transfection, United States, Up-Regulation}, issn = {1524-4636}, doi = {10.1161/ATVBAHA.113.302088}, author = {Huang, Jie and Huffman, Jennifer E and Yamakuchi, Munekazu and Yamkauchi, Munekazu and Trompet, Stella and Asselbergs, Folkert W and Sabater-Lleal, Maria and Tr{\'e}gou{\"e}t, David-Alexandre and Chen, Wei-Min and Smith, Nicholas L and Kleber, Marcus E and Shin, So-Youn and Becker, Diane M and Tang, Weihong and Dehghan, Abbas and Johnson, Andrew D and Truong, Vinh and Folkersen, Lasse and Yang, Qiong and Oudot-Mellkah, Tiphaine and Buckley, Brendan M and Moore, Jason H and Williams, Frances M K and Campbell, Harry and Silbernagel, G{\"u}nther and Vitart, Veronique and Rudan, Igor and Tofler, Geoffrey H and Navis, Gerjan J and DeStefano, Anita and Wright, Alan F and Chen, Ming-Huei and de Craen, Anton J M and Worrall, Bradford B and Rudnicka, Alicja R and Rumley, Ann and Bookman, Ebony B and Psaty, Bruce M and Chen, Fang and Keene, Keith L and Franco, Oscar H and B{\"o}hm, Bernhard O and Uitterlinden, Andr{\'e} G and Carter, Angela M and Jukema, J Wouter and Sattar, Naveed and Bis, Joshua C and Ikram, Mohammad A and Sale, Mich{\`e}le M and McKnight, Barbara and Fornage, Myriam and Ford, Ian and Taylor, Kent and Slagboom, P Eline and McArdle, Wendy L and Hsu, Fang-Chi and Franco-Cereceda, Anders and Goodall, Alison H and Yanek, Lisa R and Furie, Karen L and Cushman, Mary and Hofman, Albert and Witteman, Jacqueline C M and Folsom, Aaron R and Basu, Saonli and Matijevic, Nena and van Gilst, Wiek H and Wilson, James F and Westendorp, Rudi G J and Kathiresan, Sekar and Reilly, Muredach P and Tracy, Russell P and Polasek, Ozren and Winkelmann, Bernhard R and Grant, Peter J and Hillege, Hans L and Cambien, Francois and Stott, David J and Lowe, Gordon D and Spector, Timothy D and Meigs, James B and M{\"a}rz, Winfried and Eriksson, Per and Becker, Lewis C and Morange, Pierre-Emmanuel and Soranzo, Nicole and Williams, Scott M and Hayward, Caroline and van der Harst, Pim and Hamsten, Anders and Lowenstein, Charles J and Strachan, David P and O{\textquoteright}Donnell, Christopher J} } @article {6280, title = {Heritability of and mortality prediction with a longevity phenotype: the healthy aging index.}, journal = {J Gerontol A Biol Sci Med Sci}, volume = {69}, year = {2014}, month = {2014 Apr}, pages = {479-85}, abstract = {

BACKGROUND: Longevity-associated genes may modulate risk for age-related diseases and survival. The Healthy Aging Index (HAI) may be a subphenotype of longevity, which can be constructed in many studies for genetic analysis. We investigated the HAI{\textquoteright}s association with survival in the Cardiovascular Health Study and heritability in the Long Life Family Study.

METHODS: The HAI includes systolic blood pressure, pulmonary vital capacity, creatinine, fasting glucose, and Modified Mini-Mental Status Examination score, each scored 0, 1, or 2 using approximate tertiles and summed from 0 (healthy) to 10 (unhealthy). In Cardiovascular Health Study, the association with mortality and accuracy predicting death were determined with Cox proportional hazards analysis and c-statistics, respectively. In Long Life Family Study, heritability was determined with a variance component-based family analysis using a polygenic model.

RESULTS: Cardiovascular Health Study participants with unhealthier index scores (7-10) had 2.62-fold (95\% confidence interval: 2.22, 3.10) greater mortality than participants with healthier scores (0-2). The HAI alone predicted death moderately well (c-statistic = 0.643, 95\% confidence interval: 0.626, 0.661, p < .0001) and slightly worse than age alone (c-statistic = 0.700, 95\% confidence interval: 0.684, 0.717, p < .0001; p < .0001 for comparison of c-statistics). Prediction increased significantly with adjustment for demographics, health behaviors, and clinical comorbidities (c-statistic = 0.780, 95\% confidence interval: 0.765, 0.794, p < .0001). In Long Life Family Study, the heritability of the HAI was 0.295 (p < .0001) overall, 0.387 (p < .0001) in probands, and 0.238 (p = .0004) in offspring.

CONCLUSION: The HAI should be investigated further as a candidate phenotype for uncovering longevity-associated genes in humans.

}, keywords = {Aged, Aging, Cardiovascular Diseases, Female, Genetic Predisposition to Disease, Genotype, Health Behavior, Humans, Longevity, Male, Phenotype, Retrospective Studies, Risk Factors, Survival Rate, United States}, issn = {1758-535X}, doi = {10.1093/gerona/glt117}, author = {Sanders, Jason L and Minster, Ryan L and Barmada, M Michael and Matteini, Amy M and Boudreau, Robert M and Christensen, Kaare and Mayeux, Richard and Borecki, Ingrid B and Zhang, Qunyuan and Perls, Thomas and Newman, Anne B} } @article {6370, title = {Shared genetic susceptibility to ischemic stroke and coronary artery disease: a genome-wide analysis of common variants.}, journal = {Stroke}, volume = {45}, year = {2014}, month = {2014 Jan}, pages = {24-36}, abstract = {

BACKGROUND AND PURPOSE: Ischemic stroke (IS) and coronary artery disease (CAD) share several risk factors and each has a substantial heritability. We conducted a genome-wide analysis to evaluate the extent of shared genetic determination of the two diseases.

METHODS: Genome-wide association data were obtained from the METASTROKE, Coronary Artery Disease Genome-wide Replication and Meta-analysis (CARDIoGRAM), and Coronary Artery Disease (C4D) Genetics consortia. We first analyzed common variants reaching a nominal threshold of significance (P<0.01) for CAD for their association with IS and vice versa. We then examined specific overlap across phenotypes for variants that reached a high threshold of significance. Finally, we conducted a joint meta-analysis on the combined phenotype of IS or CAD. Corresponding analyses were performed restricted to the 2167 individuals with the ischemic large artery stroke (LAS) subtype.

RESULTS: Common variants associated with CAD at P<0.01 were associated with a significant excess risk for IS and for LAS and vice versa. Among the 42 known genome-wide significant loci for CAD, 3 and 5 loci were significantly associated with IS and LAS, respectively. In the joint meta-analyses, 15 loci passed genome-wide significance (P<5{\texttimes}10(-8)) for the combined phenotype of IS or CAD and 17 loci passed genome-wide significance for LAS or CAD. Because these loci had prior evidence for genome-wide significance for CAD, we specifically analyzed the respective signals for IS and LAS and found evidence for association at chr12q24/SH2B3 (PIS=1.62{\texttimes}10(-7)) and ABO (PIS=2.6{\texttimes}10(-4)), as well as at HDAC9 (PLAS=2.32{\texttimes}10(-12)), 9p21 (PLAS=3.70{\texttimes}10(-6)), RAI1-PEMT-RASD1 (PLAS=2.69{\texttimes}10(-5)), EDNRA (PLAS=7.29{\texttimes}10(-4)), and CYP17A1-CNNM2-NT5C2 (PLAS=4.9{\texttimes}10(-4)).

CONCLUSIONS: Our results demonstrate substantial overlap in the genetic risk of IS and particularly the LAS subtype with CAD.

}, keywords = {Brain Ischemia, Coronary Artery Disease, Data Interpretation, Statistical, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Phenotype, Polymorphism, Single Nucleotide, Reproducibility of Results, Risk Factors, Stroke}, issn = {1524-4628}, doi = {10.1161/STROKEAHA.113.002707}, author = {Dichgans, Martin and Malik, Rainer and K{\"o}nig, Inke R and Rosand, Jonathan and Clarke, Robert and Gretarsdottir, Solveig and Thorleifsson, Gudmar and Mitchell, Braxton D and Assimes, Themistocles L and Levi, Christopher and O{\textquoteright}Donnell, Christopher J and Fornage, Myriam and Thorsteinsdottir, Unnur and Psaty, Bruce M and Hengstenberg, Christian and Seshadri, Sudha and Erdmann, Jeanette and Bis, Joshua C and Peters, Annette and Boncoraglio, Giorgio B and M{\"a}rz, Winfried and Meschia, James F and Kathiresan, Sekar and Ikram, M Arfan and McPherson, Ruth and Stefansson, Kari and Sudlow, Cathie and Reilly, Muredach P and Thompson, John R and Sharma, Pankaj and Hopewell, Jemma C and Chambers, John C and Watkins, Hugh and Rothwell, Peter M and Roberts, Robert and Markus, Hugh S and Samani, Nilesh J and Farrall, Martin and Schunkert, Heribert} } @article {6594, title = {Telomere length and the risk of atrial fibrillation: insights into the role of biological versus chronological aging.}, journal = {Circ Arrhythm Electrophysiol}, volume = {7}, year = {2014}, month = {2014 Dec}, pages = {1026-32}, abstract = {

BACKGROUND: Advanced age is the most important risk factor for atrial fibrillation (AF); however, the mechanism remains unknown. Telomeres, regions of DNA that shorten with cell division, are considered reliable markers of biological aging. We sought to examine the association between leukocyte telomere length (LTL) and incident AF in a large population-based cohort using direct LTL measurements and genetic data. To further explore our findings, we compared atrial cell telomere length and LTL in cardiac surgery patients.

METHODS AND RESULTS: Mean LTL and the TERT rs2736100 single nucleotide polymorphism were assessed as predictors of incident AF in the Cardiovascular Health Study (CHS). Among the surgical patients, within subject comparison of atrial cell telomere length versus LTL was assessed. Among 1639 CHS participants, we observed no relationship between mean LTL and incident AF before and after adjustment for potential confounders (adjusted hazard ratio, 1.09; 95\% confidence interval: 0.92-1.29; P=0.299); chronologic age remained strongly associated with AF in the same model. No association was observed between the TERT rs2736100 single nucleotide polymorphism and incident AF (adjusted hazard ratio: 0.95; 95\% confidence interval: 0.88-1.04; P=0.265). In 35 cardiac surgery patients (26 with AF), atrial cell telomere length was longer than LTL (1.19 {\textpm} 0.20 versus 1.02 {\textpm} 0.25 [T/S ratio], P<0.001), a finding that remained consistent within the AF subgroup.

CONCLUSIONS: Our study revealed no evidence of an association between LTL and incident AF and no evidence of relative atrial cell telomere shortening in AF. Chronological aging independent of biological markers of aging is the primary risk factor for AF.

}, keywords = {Age Factors, Aged, Aging, Atrial Fibrillation, California, Cardiac Surgical Procedures, Cellular Senescence, Cross-Sectional Studies, Female, Genetic Predisposition to Disease, Humans, Incidence, Leukocytes, Male, Phenotype, Polymorphism, Single Nucleotide, Prospective Studies, Risk Assessment, Risk Factors, Telomerase, Telomere, Time Factors}, issn = {1941-3084}, doi = {10.1161/CIRCEP.114.001781}, author = {Roberts, Jason D and Dewland, Thomas A and Longoria, James and Fitzpatrick, Annette L and Ziv, Elad and Hu, Donglei and Lin, Jue and Glidden, David V and Psaty, Bruce M and Burchard, Esteban G and Blackburn, Elizabeth H and Olgin, Jeffrey E and Heckbert, Susan R and Marcus, Gregory M} } @article {6573, title = {Trans-ethnic meta-analysis of white blood cell phenotypes.}, journal = {Hum Mol Genet}, volume = {23}, year = {2014}, month = {2014 Dec 20}, pages = {6944-60}, abstract = {

White blood cell (WBC) count is a common clinical measure used as a predictor of certain aspects of human health, including immunity and infection status. WBC count is also a complex trait that varies among individuals and ancestry groups. Differences in linkage disequilibrium structure and heterogeneity in allelic effects are expected to play a role in the associations observed between populations. Prior genome-wide association study (GWAS) meta-analyses have identified genomic loci associated with WBC and its subtypes, but much of the heritability of these phenotypes remains unexplained. Using GWAS summary statistics for over 50 000 individuals from three diverse populations (Japanese, African-American and European ancestry), a Bayesian model methodology was employed to account for heterogeneity between ancestry groups. This approach was used to perform a trans-ethnic meta-analysis of total WBC, neutrophil and monocyte counts. Ten previously known associations were replicated and six new loci were identified, including several regions harboring genes related to inflammation and immune cell function. Ninety-five percent credible interval regions were calculated to narrow the association signals and fine-map the putatively causal variants within loci. Finally, a conditional analysis was performed on the most significant SNPs identified by the trans-ethnic meta-analysis (MA), and nine secondary signals within loci previously associated with WBC or its subtypes were identified. This work illustrates the potential of trans-ethnic analysis and ascribes a critical role to multi-ethnic cohorts and consortia in exploring complex phenotypes with respect to variants that lie outside the European-biased GWAS pool.

}, keywords = {African Americans, Asian Continental Ancestry Group, Bayes Theorem, European Continental Ancestry Group, Genome, Human, Genome-Wide Association Study, Genotype, Humans, Leukocyte Count, Leukocytes, Linkage Disequilibrium, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci}, issn = {1460-2083}, doi = {10.1093/hmg/ddu401}, author = {Keller, Margaux F and Reiner, Alexander P and Okada, Yukinori and van Rooij, Frank J A and Johnson, Andrew D and Chen, Ming-Huei and Smith, Albert V and Morris, Andrew P and Tanaka, Toshiko and Ferrucci, Luigi and Zonderman, Alan B and Lettre, Guillaume and Harris, Tamara and Garcia, Melissa and Bandinelli, Stefania and Qayyum, Rehan and Yanek, Lisa R and Becker, Diane M and Becker, Lewis C and Kooperberg, Charles and Keating, Brendan and Reis, Jared and Tang, Hua and Boerwinkle, Eric and Kamatani, Yoichiro and Matsuda, Koichi and Kamatani, Naoyuki and Nakamura, Yusuke and Kubo, Michiaki and Liu, Simin and Dehghan, Abbas and Felix, Janine F and Hofman, Albert and Uitterlinden, Andr{\'e} G and van Duijn, Cornelia M and Franco, Oscar H and Longo, Dan L and Singleton, Andrew B and Psaty, Bruce M and Evans, Michelle K and Cupples, L Adrienne and Rotter, Jerome I and O{\textquoteright}Donnell, Christopher J and Takahashi, Atsushi and Wilson, James G and Ganesh, Santhi K and Nalls, Mike A} } @article {6577, title = {Whole-exome sequencing identifies rare and low-frequency coding variants associated with LDL cholesterol.}, journal = {Am J Hum Genet}, volume = {94}, year = {2014}, month = {2014 Feb 06}, pages = {233-45}, abstract = {

Elevated low-density lipoprotein cholesterol (LDL-C) is a treatable, heritable risk factor for cardiovascular disease. Genome-wide association studies (GWASs) have identified 157 variants associated with lipid levels but are not well suited to assess the impact of rare and low-frequency variants. To determine whether rare or low-frequency coding variants are associated with LDL-C, we exome sequenced 2,005 individuals, including 554 individuals selected for extreme LDL-C (>98(th) or <2(nd) percentile). Follow-up analyses included sequencing of 1,302 additional individuals and genotype-based analysis of 52,221 individuals. We observed significant evidence of association between LDL-C and the burden of rare or low-frequency variants in PNPLA5, encoding a phospholipase-domain-containing protein, and both known and previously unidentified variants in PCSK9, LDLR and APOB, three known lipid-related genes. The effect sizes for the burden of rare variants for each associated gene were substantially higher than those observed for individual SNPs identified from GWASs. We replicated the PNPLA5 signal in an independent large-scale sequencing study of 2,084 individuals. In conclusion, this large whole-exome-sequencing study for LDL-C identified a gene not known to be implicated in LDL-C and provides unique insight into the design and analysis of similar experiments.

}, keywords = {Adult, Aged, Apolipoproteins E, Cholesterol, LDL, Cohort Studies, Dyslipidemias, Exome, Female, Follow-Up Studies, Gene Frequency, Genetic Code, Genome-Wide Association Study, Genotype, Humans, Lipase, Male, Middle Aged, Phenotype, Polymorphism, Single Nucleotide, Proprotein Convertase 9, Proprotein Convertases, Receptors, LDL, Sequence Analysis, DNA, Serine Endopeptidases}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2014.01.010}, author = {Lange, Leslie A and Hu, Youna and Zhang, He and Xue, Chenyi and Schmidt, Ellen M and Tang, Zheng-Zheng and Bizon, Chris and Lange, Ethan M and Smith, Joshua D and Turner, Emily H and Jun, Goo and Kang, Hyun Min and Peloso, Gina and Auer, Paul and Li, Kuo-Ping and Flannick, Jason and Zhang, Ji and Fuchsberger, Christian and Gaulton, Kyle and Lindgren, Cecilia and Locke, Adam and Manning, Alisa and Sim, Xueling and Rivas, Manuel A and Holmen, Oddgeir L and Gottesman, Omri and Lu, Yingchang and Ruderfer, Douglas and Stahl, Eli A and Duan, Qing and Li, Yun and Durda, Peter and Jiao, Shuo and Isaacs, Aaron and Hofman, Albert and Bis, Joshua C and Correa, Adolfo and Griswold, Michael E and Jakobsdottir, Johanna and Smith, Albert V and Schreiner, Pamela J and Feitosa, Mary F and Zhang, Qunyuan and Huffman, Jennifer E and Crosby, Jacy and Wassel, Christina L and Do, Ron and Franceschini, Nora and Martin, Lisa W and Robinson, Jennifer G and Assimes, Themistocles L and Crosslin, David R and Rosenthal, Elisabeth A and Tsai, Michael and Rieder, Mark J and Farlow, Deborah N and Folsom, Aaron R and Lumley, Thomas and Fox, Ervin R and Carlson, Christopher S and Peters, Ulrike and Jackson, Rebecca D and van Duijn, Cornelia M and Uitterlinden, Andr{\'e} G and Levy, Daniel and Rotter, Jerome I and Taylor, Herman A and Gudnason, Vilmundur and Siscovick, David S and Fornage, Myriam and Borecki, Ingrid B and Hayward, Caroline and Rudan, Igor and Chen, Y Eugene and Bottinger, Erwin P and Loos, Ruth J F and S{\ae}trom, P{\r a}l and Hveem, Kristian and Boehnke, Michael and Groop, Leif and McCarthy, Mark and Meitinger, Thomas and Ballantyne, Christie M and Gabriel, Stacey B and O{\textquoteright}Donnell, Christopher J and Post, Wendy S and North, Kari E and Reiner, Alexander P and Boerwinkle, Eric and Psaty, Bruce M and Altshuler, David and Kathiresan, Sekar and Lin, Dan-Yu and Jarvik, Gail P and Cupples, L Adrienne and Kooperberg, Charles and Wilson, James G and Nickerson, Deborah A and Abecasis, Goncalo R and Rich, Stephen S and Tracy, Russell P and Willer, Cristen J} } @article {6810, title = {Coagulation factor~XII genetic variation, ex~vivo thrombin generation, and stroke risk in the elderly: results from the Cardiovascular Health Study.}, journal = {J Thromb Haemost}, volume = {13}, year = {2015}, month = {2015 Oct}, pages = {1867-77}, abstract = {

BACKGROUND: The relationships of thrombin generation (TG) with cardiovascular disease risk are underevaluated in population-based cohorts.

OBJECTIVES: To evaluate the relationships of TG influenced by the contact and tissue factor coagulation pathways ex~vivo with common single-nucleotide polymorphisms (SNPs) and incident cardiovascular disease and stroke.

PATIENTS/METHODS: We measured peak TG (pTG) in baseline plasma samples of Cardiovascular Health Study participants (n~=~5411), both with and without inhibitory anti-factor~XIa antibody (pTG/FXIa(-) ). We evaluated their associations with ~~50~000 SNPs by using the IBCv2 genotyping array, and with incident cardiovascular disease and stroke events over a median follow-up of 13.2~years.

RESULTS: The minor allele for an SNP in the FXII gene (F12), rs1801020, was associated with lower pTG in European-Americans (β~=~-~34.2~{\textpm}~3.5~nm; P~=~3.3~{\texttimes}~10(-22) ; minor allele frequency [MAF]~=~0.23) and African-Americans (β~=~-~31.1~{\textpm}~7.9~nm; P~=~9.0~{\texttimes} 10(-5) ; MAF~=~0.42). Lower FXIa-independent pTG (pTG/FXIa(-) ) was associated with the F12 rs1801020 minor allele, and higher pTG/FXIa(-) was associated with the ABO SNP rs657152 minor allele (β~=~16.3~nm; P~=~4.3~{\texttimes}~10(-9) ; MAF~=~0.37). The risk factor-adjusted ischemic stroke hazard ratios were 1.09 (95\% confidence interval CI~1.01-1.17; P~=~0.03) for pTG, 1.06 (95\% CI~0.98-1.15; P~=~0.17) for pTG/FXIa(-) , and 1.11 (95\% CI~1.02-1.21; P~=~0.02) for FXIa-dependent pTG (pTG/FXIa(+) ), per one standard deviation increment (n~=~834 ischemic strokes). In a multicohort candidate gene analysis, rs1801020 was not associated with incident ischemic stroke (β~=~-~0.02; standard error~=~0.08; P~=~0.81).

CONCLUSIONS: These results support the importance of contact activation pathway-dependent TG as a risk factor for ischemic stroke, and indicate the importance of F12 SNPs for TG ex~vivo and in~vivo.

}, keywords = {African Americans, Age Factors, Aged, Blood Coagulation, Brain Ischemia, European Continental Ancestry Group, Factor XII, Female, Gene Frequency, Genetic Predisposition to Disease, Humans, Incidence, Male, Phenotype, Polymorphism, Single Nucleotide, Prospective Studies, Risk Assessment, Risk Factors, Stroke, Thrombin, Time Factors, United States}, issn = {1538-7836}, doi = {10.1111/jth.13111}, author = {Olson, N C and Butenas, S and Lange, L A and Lange, E M and Cushman, M and Jenny, N S and Walston, J and Souto, J C and Soria, J M and Chauhan, G and Debette, S and Longstreth, W T and Seshadri, S and Reiner, A P and Tracy, R P} } @article {6927, title = {Gene-Environment Interactions of Circadian-Related Genes for Cardiometabolic Traits.}, journal = {Diabetes Care}, volume = {38}, year = {2015}, month = {2015 Aug}, pages = {1456-66}, abstract = {

OBJECTIVE: Common circadian-related gene variants associate with increased risk for metabolic alterations including type 2 diabetes. However, little is known about whether diet and sleep could modify associations between circadian-related variants (CLOCK-rs1801260, CRY2-rs11605924, MTNR1B-rs1387153, MTNR1B-rs10830963, NR1D1-rs2314339) and cardiometabolic traits (fasting glucose [FG], HOMA-insulin resistance, BMI, waist circumference, and HDL-cholesterol) to facilitate personalized recommendations.

RESEARCH DESIGN AND METHODS: We conducted inverse-variance weighted, fixed-effect meta-analyses of results of adjusted associations and interactions between dietary intake/sleep duration and selected variants on cardiometabolic traits from 15 cohort studies including up to 28,190 participants of European descent from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium.

RESULTS: We observed significant associations between relative macronutrient intakes and glycemic traits and short sleep duration (<7 h) and higher FG and replicated known MTNR1B associations with glycemic traits. No interactions were evident after accounting for multiple comparisons. However, we observed nominally significant interactions (all P < 0.01) between carbohydrate intake and MTNR1B-rs1387153 for FG with a 0.003 mmol/L higher FG with each additional 1\% carbohydrate intake in the presence of the T allele, between sleep duration and CRY2-rs11605924 for HDL-cholesterol with a 0.010 mmol/L higher HDL-cholesterol with each additional hour of sleep in the presence of the A allele, and between long sleep duration (>=9 h) and MTNR1B-rs1387153 for BMI with a 0.60 kg/m(2) higher BMI with long sleep duration in the presence of the T allele relative to normal sleep duration (>=7 to <9 h).

CONCLUSIONS: Our results suggest that lower carbohydrate intake and normal sleep duration may ameliorate cardiometabolic abnormalities conferred by common circadian-related genetic variants. Until further mechanistic examination of the nominally significant interactions is conducted, recommendations applicable to the general population regarding diet{\textemdash}specifically higher carbohydrate and lower fat composition{\textemdash}and normal sleep duration should continue to be emphasized among individuals with the investigated circadian-related gene variants.

}, keywords = {Adult, Alleles, Blood Glucose, Circadian Rhythm Signaling Peptides and Proteins, Cohort Studies, Diabetes Mellitus, Type 2, Diet, Fat-Restricted, European Continental Ancestry Group, Fasting, Female, Gene-Environment Interaction, Humans, Insulin Resistance, Male, Middle Aged, Multicenter Studies as Topic, Observational Studies as Topic, Phenotype, Polymorphism, Single Nucleotide, Sleep, Waist Circumference}, issn = {1935-5548}, doi = {10.2337/dc14-2709}, author = {Dashti, Hassan S and Follis, Jack L and Smith, Caren E and Tanaka, Toshiko and Garaulet, Marta and Gottlieb, Daniel J and Hruby, Adela and Jacques, Paul F and Kiefte-de Jong, Jessica C and Lamon-Fava, Stefania and Scheer, Frank A J L and Bartz, Traci M and Kovanen, Leena and Wojczynski, Mary K and Frazier-Wood, Alexis C and Ahluwalia, Tarunveer S and Per{\"a}l{\"a}, Mia-Maria and Jonsson, Anna and Muka, Taulant and Kalafati, Ioanna P and Mikkil{\"a}, Vera and Ordovas, Jose M} } @article {6816, title = {Genetic contributions to variation in general cognitive function: a meta-analysis of genome-wide association studies in the CHARGE consortium (N=53949).}, journal = {Mol Psychiatry}, volume = {20}, year = {2015}, month = {2015 Feb}, pages = {183-92}, abstract = {

General cognitive function is substantially heritable across the human life course from adolescence to old age. We investigated the genetic contribution to variation in this important, health- and well-being-related trait in middle-aged and older adults. We conducted a meta-analysis of genome-wide association studies of 31 cohorts (N=53,949) in which the participants had undertaken multiple, diverse cognitive tests. A general cognitive function phenotype was tested for, and created in each cohort by principal component analysis. We report 13 genome-wide significant single-nucleotide polymorphism (SNP) associations in three genomic regions, 6q16.1, 14q12 and 19q13.32 (best SNP and closest gene, respectively: rs10457441, P=3.93 {\texttimes} 10(-9), MIR2113; rs17522122, P=2.55 {\texttimes} 10(-8), AKAP6; rs10119, P=5.67 {\texttimes} 10(-9), APOE/TOMM40). We report one gene-based significant association with the HMGN1 gene located on chromosome 21 (P=1 {\texttimes} 10(-6)). These genes have previously been associated with neuropsychiatric phenotypes. Meta-analysis results are consistent with a polygenic model of inheritance. To estimate SNP-based heritability, the genome-wide complex trait analysis procedure was applied to two large cohorts, the Atherosclerosis Risk in Communities Study (N=6617) and the Health and Retirement Study (N=5976). The proportion of phenotypic variation accounted for by all genotyped common SNPs was 29\% (s.e.=5\%) and 28\% (s.e.=7\%), respectively. Using polygenic prediction analysis, ~1.2\% of the variance in general cognitive function was predicted in the Generation Scotland cohort (N=5487; P=1.5 {\texttimes} 10(-17)). In hypothesis-driven tests, there was significant association between general cognitive function and four genes previously associated with Alzheimer{\textquoteright}s disease: TOMM40, APOE, ABCG1 and MEF2C.

}, keywords = {Aged, Aged, 80 and over, Atherosclerosis, Cognition, Cognition Disorders, Cohort Studies, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, HMGN1 Protein, Humans, Male, Middle Aged, Neuropsychological Tests, Phenotype, Polymorphism, Single Nucleotide, Scotland}, issn = {1476-5578}, doi = {10.1038/mp.2014.188}, author = {Davies, G and Armstrong, N and Bis, J C and Bressler, J and Chouraki, V and Giddaluru, S and Hofer, E and Ibrahim-Verbaas, C A and Kirin, M and Lahti, J and van der Lee, S J and Le Hellard, S and Liu, T and Marioni, R E and Oldmeadow, C and Postmus, I and Smith, A V and Smith, J A and Thalamuthu, A and Thomson, R and Vitart, V and Wang, J and Yu, L and Zgaga, L and Zhao, W and Boxall, R and Harris, S E and Hill, W D and Liewald, D C and Luciano, M and Adams, H and Ames, D and Amin, N and Amouyel, P and Assareh, A A and Au, R and Becker, J T and Beiser, A and Berr, C and Bertram, L and Boerwinkle, E and Buckley, B M and Campbell, H and Corley, J and De Jager, P L and Dufouil, C and Eriksson, J G and Espeseth, T and Faul, J D and Ford, I and Gottesman, R F and Griswold, M E and Gudnason, V and Harris, T B and Heiss, G and Hofman, A and Holliday, E G and Huffman, J and Kardia, S L R and Kochan, N and Knopman, D S and Kwok, J B and Lambert, J-C and Lee, T and Li, G and Li, S-C and Loitfelder, M and Lopez, O L and Lundervold, A J and Lundqvist, A and Mather, K A and Mirza, S S and Nyberg, L and Oostra, B A and Palotie, A and Papenberg, G and Pattie, A and Petrovic, K and Polasek, O and Psaty, B M and Redmond, P and Reppermund, S and Rotter, J I and Schmidt, H and Schuur, M and Schofield, P W and Scott, R J and Steen, V M and Stott, D J and van Swieten, J C and Taylor, K D and Trollor, J and Trompet, S and Uitterlinden, A G and Weinstein, G and Widen, E and Windham, B G and Jukema, J W and Wright, A F and Wright, M J and Yang, Q and Amieva, H and Attia, J R and Bennett, D A and Brodaty, H and de Craen, A J M and Hayward, C and Ikram, M A and Lindenberger, U and Nilsson, L-G and Porteous, D J and R{\"a}ikk{\"o}nen, K and Reinvang, I and Rudan, I and Sachdev, P S and Schmidt, R and Schofield, P R and Srikanth, V and Starr, J M and Turner, S T and Weir, D R and Wilson, J F and van Duijn, C and Launer, L and Fitzpatrick, A L and Seshadri, S and Mosley, T H and Deary, I J} } @article {6688, title = {Genetic overlap between diagnostic subtypes of ischemic stroke.}, journal = {Stroke}, volume = {46}, year = {2015}, month = {2015 Mar}, pages = {615-9}, abstract = {

BACKGROUND AND PURPOSE: Despite moderate heritability, the phenotypic heterogeneity of ischemic stroke has hampered gene discovery, motivating analyses of diagnostic subtypes with reduced sample sizes. We assessed evidence for a shared genetic basis among the 3 major subtypes: large artery atherosclerosis (LAA), cardioembolism, and small vessel disease (SVD), to inform potential cross-subtype analyses.

METHODS: Analyses used genome-wide summary data for 12 389 ischemic stroke cases (including 2167 LAA, 2405 cardioembolism, and 1854 SVD) and 62 004 controls from the Metastroke consortium. For 4561 cases and 7094 controls, individual-level genotype data were also available. Genetic correlations between subtypes were estimated using linear mixed models and polygenic profile scores. Meta-analysis of a combined LAA-SVD phenotype (4021 cases and 51 976 controls) was performed to identify shared risk alleles.

RESULTS: High genetic correlation was identified between LAA and SVD using linear mixed models (rg=0.96, SE=0.47, P=9{\texttimes}10(-4)) and profile scores (rg=0.72; 95\% confidence interval, 0.52-0.93). Between LAA and cardioembolism and SVD and cardioembolism, correlation was moderate using linear mixed models but not significantly different from zero for profile scoring. Joint meta-analysis of LAA and SVD identified strong association (P=1{\texttimes}10(-7)) for single nucleotide polymorphisms near the opioid receptor μ1 (OPRM1) gene.

CONCLUSIONS: Our results suggest that LAA and SVD, which have been hitherto treated as genetically distinct, may share a substantial genetic component. Combined analyses of LAA and SVD may increase power to identify small-effect alleles influencing shared pathophysiological processes.

}, keywords = {Alleles, Atherosclerosis, Cerebral Small Vessel Diseases, Cohort Studies, Data Interpretation, Statistical, Embolism, Genome-Wide Association Study, Genotype, Humans, Ischemia, Linear Models, Meta-Analysis as Topic, Phenotype, Polymorphism, Single Nucleotide, Stroke}, issn = {1524-4628}, doi = {10.1161/STROKEAHA.114.007930}, author = {Holliday, Elizabeth G and Traylor, Matthew and Malik, Rainer and Bevan, Steve and Falcone, Guido and Hopewell, Jemma C and Cheng, Yu-Ching and Cotlarciuc, Ioana and Bis, Joshua C and Boerwinkle, Eric and Boncoraglio, Giorgio B and Clarke, Robert and Cole, John W and Fornage, Myriam and Furie, Karen L and Ikram, M Arfan and Jannes, Jim and Kittner, Steven J and Lincz, Lisa F and Maguire, Jane M and Meschia, James F and Mosley, Thomas H and Nalls, Mike A and Oldmeadow, Christopher and Parati, Eugenio A and Psaty, Bruce M and Rothwell, Peter M and Seshadri, Sudha and Scott, Rodney J and Sharma, Pankaj and Sudlow, Cathie and Wiggins, Kerri L and Worrall, Bradford B and Rosand, Jonathan and Mitchell, Braxton D and Dichgans, Martin and Markus, Hugh S and Levi, Christopher and Attia, John and Wray, Naomi R} } @article {6606, title = {Genome-wide meta-analysis identifies six novel loci associated with habitual coffee consumption.}, journal = {Mol Psychiatry}, volume = {20}, year = {2015}, month = {2015 May}, pages = {647-56}, abstract = {

Coffee, a major dietary source of caffeine, is among the most widely consumed beverages in the world and has received considerable attention regarding health risks and benefits. We conducted a genome-wide (GW) meta-analysis of predominately regular-type coffee consumption (cups per day) among up to 91,462 coffee consumers of European ancestry with top single-nucleotide polymorphisms (SNPs) followed-up in ~30 062 and 7964 coffee consumers of European and African-American ancestry, respectively. Studies from both stages were combined in a trans-ethnic meta-analysis. Confirmed loci were examined for putative functional and biological relevance. Eight loci, including six novel loci, met GW significance (log10Bayes factor (BF)>5.64) with per-allele effect sizes of 0.03-0.14 cups per day. Six are located in or near genes potentially involved in pharmacokinetics (ABCG2, AHR, POR and CYP1A2) and pharmacodynamics (BDNF and SLC6A4) of caffeine. Two map to GCKR and MLXIPL genes related to metabolic traits but lacking known roles in coffee consumption. Enhancer and promoter histone marks populate the regions of many confirmed loci and several potential regulatory SNPs are highly correlated with the lead SNP of each. SNP alleles near GCKR, MLXIPL, BDNF and CYP1A2 that were associated with higher coffee consumption have previously been associated with smoking initiation, higher adiposity and fasting insulin and glucose but lower blood pressure and favorable lipid, inflammatory and liver enzyme profiles (P<5 {\texttimes} 10(-8)).Our genetic findings among European and African-American adults reinforce the role of caffeine in mediating habitual coffee consumption and may point to molecular mechanisms underlying inter-individual variability in pharmacological and health effects of coffee.

}, keywords = {Adaptor Proteins, Signal Transducing, Basic Helix-Loop-Helix Leucine Zipper Transcription Factors, Brain-Derived Neurotrophic Factor, Coffea, Cytochrome P-450 CYP1A2, Food Habits, Genome-Wide Association Study, Humans, Phenotype, Polymorphism, Single Nucleotide}, issn = {1476-5578}, doi = {10.1038/mp.2014.107}, author = {Cornelis, M C and Byrne, E M and Esko, T and Nalls, M A and Ganna, A and Paynter, N and Monda, K L and Amin, N and Fischer, K and Renstrom, F and Ngwa, J S and Huikari, V and Cavadino, A and Nolte, I M and Teumer, A and Yu, K and Marques-Vidal, P and Rawal, R and Manichaikul, A and Wojczynski, M K and Vink, J M and Zhao, J H and Burlutsky, G and Lahti, J and Mikkil{\"a}, V and Lemaitre, R N and Eriksson, J and Musani, S K and Tanaka, T and Geller, F and Luan, J and Hui, J and M{\"a}gi, R and Dimitriou, M and Garcia, M E and Ho, W-K and Wright, M J and Rose, L M and Magnusson, P K E and Pedersen, N L and Couper, D and Oostra, B A and Hofman, A and Ikram, M A and Tiemeier, H W and Uitterlinden, A G and van Rooij, F J A and Barroso, I and Johansson, I and Xue, L and Kaakinen, M and Milani, L and Power, C and Snieder, H and Stolk, R P and Baumeister, S E and Biffar, R and Gu, F and Bastardot, F and Kutalik, Z and Jacobs, D R and Forouhi, N G and Mihailov, E and Lind, L and Lindgren, C and Micha{\"e}lsson, K and Morris, A and Jensen, M and Khaw, K-T and Luben, R N and Wang, J J and M{\"a}nnist{\"o}, S and Per{\"a}l{\"a}, M-M and K{\"a}h{\"o}nen, M and Lehtim{\"a}ki, T and Viikari, J and Mozaffarian, D and Mukamal, K and Psaty, B M and D{\"o}ring, A and Heath, A C and Montgomery, G W and Dahmen, N and Carithers, T and Tucker, K L and Ferrucci, L and Boyd, H A and Melbye, M and Treur, J L and Mellstr{\"o}m, D and Hottenga, J J and Prokopenko, I and T{\"o}njes, A and Deloukas, P and Kanoni, S and Lorentzon, M and Houston, D K and Liu, Y and Danesh, J and Rasheed, A and Mason, M A and Zonderman, A B and Franke, L and Kristal, B S and Karjalainen, J and Reed, D R and Westra, H-J and Evans, M K and Saleheen, D and Harris, T B and Dedoussis, G and Curhan, G and Stumvoll, M and Beilby, J and Pasquale, L R and Feenstra, B and Bandinelli, S and Ordov{\'a}s, J M and Chan, A T and Peters, U and Ohlsson, C and Gieger, C and Martin, N G and Waldenberger, M and Siscovick, D S and Raitakari, O and Eriksson, J G and Mitchell, P and Hunter, D J and Kraft, P and Rimm, E B and Boomsma, D I and Borecki, I B and Loos, R J F and Wareham, N J and Vollenweider, P and Caporaso, N and Grabe, H J and Neuhouser, M L and Wolffenbuttel, B H R and Hu, F B and Hypponen, E and J{\"a}rvelin, M-R and Cupples, L A and Franks, P W and Ridker, P M and van Duijn, C M and Heiss, G and Metspalu, A and North, K E and Ingelsson, E and Nettleton, J A and van Dam, R M and Chasman, D I} } @article {6860, title = {Integrative pathway genomics of lung function and airflow obstruction.}, journal = {Hum Mol Genet}, volume = {24}, year = {2015}, month = {2015 Dec 1}, pages = {6836-48}, abstract = {

Chronic respiratory disorders are important contributors to the global burden of disease. Genome-wide association studies (GWASs) of lung function measures have identified several trait-associated loci, but explain only a modest portion of the phenotypic variability. We postulated that integrating pathway-based methods with GWASs of pulmonary function and airflow obstruction would identify a broader repertoire of genes and processes influencing these traits. We performed two independent GWASs of lung function and applied gene set enrichment analysis to one of the studies and validated the results using the second GWAS. We identified 131 significantly enriched gene sets associated with lung function and clustered them into larger biological modules involved in diverse processes including development, immunity, cell signaling, proliferation and arachidonic acid. We found that enrichment of gene sets was not driven by GWAS-significant variants or loci, but instead by those with less stringent association P-values. Next, we applied pathway enrichment analysis to a meta-analyzed GWAS of airflow obstruction. We identified several biologic modules that functionally overlapped with those associated with pulmonary function. However, differences were also noted, including enrichment of extracellular matrix (ECM) processes specifically in the airflow obstruction study. Network analysis of the ECM module implicated a candidate gene, matrix metalloproteinase 10 (MMP10), as a putative disease target. We used a knockout mouse model to functionally validate MMP10{\textquoteright}s role in influencing lung{\textquoteright}s susceptibility to cigarette smoke-induced emphysema. By integrating pathway analysis with population-based genomics, we unraveled biologic processes underlying pulmonary function traits and identified a candidate gene for obstructive lung disease.

}, keywords = {Airway Obstruction, Animals, Cell Proliferation, European Continental Ancestry Group, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Humans, Immune System, Lung, Male, Metabolic Networks and Pathways, Mice, Phenotype, Polymorphism, Single Nucleotide, Signal Transduction}, issn = {1460-2083}, doi = {10.1093/hmg/ddv378}, author = {Gharib, Sina A and Loth, Daan W and Soler Artigas, Maria and Birkland, Timothy P and Wilk, Jemma B and Wain, Louise V and Brody, Jennifer A and Obeidat, Ma{\textquoteright}en and Hancock, Dana B and Tang, Wenbo and Rawal, Rajesh and Boezen, H Marike and Imboden, Medea and Huffman, Jennifer E and Lahousse, Lies and Alves, Alexessander C and Manichaikul, Ani and Hui, Jennie and Morrison, Alanna C and Ramasamy, Adaikalavan and Smith, Albert Vernon and Gudnason, Vilmundur and Surakka, Ida and Vitart, Veronique and Evans, David M and Strachan, David P and Deary, Ian J and Hofman, Albert and Gl{\"a}ser, Sven and Wilson, James F and North, Kari E and Zhao, Jing Hua and Heckbert, Susan R and Jarvis, Deborah L and Probst-Hensch, Nicole and Schulz, Holger and Barr, R Graham and Jarvelin, Marjo-Riitta and O{\textquoteright}Connor, George T and K{\"a}h{\"o}nen, Mika and Cassano, Patricia A and Hysi, Pirro G and Dupuis, Jos{\'e}e and Hayward, Caroline and Psaty, Bruce M and Hall, Ian P and Parks, William C and Tobin, Martin D and London, Stephanie J} } @article {6735, title = {Older Adults, "Malignant" Left Ventricular Hypertrophy, and Associated Cardiac-Specific Biomarker Phenotypes to Identify the Differential Risk of New-Onset Reduced Versus Preserved Ejection Fraction Heart Failure: CHS (Cardiovascular Health Study).}, journal = {JACC Heart Fail}, volume = {3}, year = {2015}, month = {2015 Jun}, pages = {445-55}, abstract = {

OBJECTIVES: This study hypothesized that biomarkers of subclinical myocardial injury (high-sensitivity cardiac troponin T [hs-cTnT]) and hemodynamic stress (N-terminal pro-B-type natriuretic peptide [NT-proBNP]) would differentiate heart~failure (HF) risk among older adults with left ventricular hypertrophy (LVH).

BACKGROUND: The natural history of LVH, an important risk factor for HF, is heterogeneous.

METHODS: NT-proBNP and hs-cTnT were measured at baseline and after 2 to 3 years in older adults without prior HF or myocardial infarction in the CHS (Cardiovascular Health Study). LVH and left ventricular ejection fraction were determined by echocardiography. HF events were adjudicated over a median of 13.1 years and classified as preserved or reduced left ventricular ejection fraction (heart failure with preserved ejection fraction or heart failure with reduced ejection fraction [HFrEF]). Adjusted risk of HF by LVH and biomarker tertiles, and by LVH and longitudinal increase in each biomarker was estimated using Cox regression.

RESULTS: Prevalence of LVH was 12.5\% among 2,347 participants with complete measures. Adjusted risk of HF (N~=~643 events) was approximately 3.8-fold higher among participants with LVH and in the highest biomarker tertile, compared with those with low biomarker levels without LVH (NT-proBNP, hazard ratio [HR]: 3.78; 95\% confidence interval [CI]: 2.78 to 5.15 and hs-cTnT, HR: 3.86; 95\% CI: 2.84 to 5.26). The adjusted risk of HFrEF was 7.8 times higher among those with the highest tertile of hs-cTnT and LVH (HR: 7.83; 95\% CI: 4.43 to 13.83). Those with LVH and longitudinal increases in hs-cTnT or NT-proBNP were approximately 3-fold more likely to develop HF, primarily HFrEF, compared with those without LVH and with stable biomarkers.

CONCLUSIONS: The combination of LVH with greater hs-cTnT or NT-proBNP levels, and their longitudinal increase, identifies older adults at highest risk for symptomatic HF, especially HFrEF. These biomarkers may characterize sub-phenotypes in the transition from LVH to HF and suggest modifiable targets for prevention.

}, keywords = {Aged, Biomarkers, Echocardiography, Female, Heart Failure, Humans, Hypertrophy, Left Ventricular, Male, Natriuretic Peptide, Brain, Peptide Fragments, Phenotype, Prospective Studies, Risk Factors, Troponin T}, issn = {2213-1787}, doi = {10.1016/j.jchf.2014.12.018}, author = {Seliger, Stephen L and de Lemos, James and Neeland, Ian J and Christenson, Robert and Gottdiener, John and Drazner, Mark H and Berry, Jarett and Sorkin, John and DeFilippi, Christopher} } @article {6931, title = {APOL1 Genotype, Kidney and Cardiovascular Disease, and Death in Older Adults.}, journal = {Arterioscler Thromb Vasc Biol}, volume = {36}, year = {2016}, month = {2016 Feb}, pages = {398-403}, abstract = {

OBJECTIVE: We sought to evaluate the cardiovascular impact of coding variants in the apolipoprotein L1 gene APOL1 that protect against trypanosome infection but have been associated with kidney disease among African Americans.

APPROACH AND RESULTS: As part of the Cardiovascular Health Study, a population-based cohort of Americans aged >=65 years, we genotyped APOL1 polymorphisms rs73885319 and rs71785153 and examined kidney function, subclinical atherosclerosis, and incident cardiovascular disease and death over 13 years of follow-up among 91 African Americans with 2 risk alleles, 707 other African Americans, and 4964 white participants. The high-risk genotype with 2 risk alleles was associated with 2-fold higher levels of albuminuria and lower ankle-brachial indices but similar carotid intima-media thickness among African Americans. Median survival among high-risk African Americans was 9.9 years (95\% confidence interval [CI], 8.7-11.9), compared with 13.6 years (95\% CI, 12.5-14.3) among other African Americans and 13.3 years (95\% CI, 13.0-13.6) among whites (P=0.03). The high-risk genotype was also associated with increased risk for incident myocardial infarction (adjusted hazard ratio 1.8; 95\% CI, 1.1-3.0) and mortality (adjusted hazard ratio 1.3; 95\% CI 1.0-1.7). Albuminuria and risk for myocardial infarction and mortality were nearly identical between African Americans with 0 to 1 risk alleles and whites.

CONCLUSIONS: APOL1 genotype is associated with albuminuria, subclinical atherosclerosis, incident myocardial infarction, and mortality in older African Americans. African Americans without 2 risk alleles do not differ significantly in risk of myocardial infarction or mortality from whites. APOL1 trypanolytic variants may account for a substantial proportion of the excess risk of chronic disease in African Americans.

}, keywords = {African Americans, Age Factors, Aged, Albuminuria, Apolipoproteins, Atherosclerosis, Cardiovascular Diseases, Cause of Death, European Continental Ancestry Group, Female, Gene Frequency, Genetic Predisposition to Disease, Health Status Disparities, Heterozygote, Homozygote, Humans, Incidence, Kaplan-Meier Estimate, Kidney Diseases, Lipoproteins, HDL, Male, Myocardial Infarction, Phenotype, Proportional Hazards Models, Prospective Studies, Risk Assessment, Risk Factors, Time Factors, United States}, issn = {1524-4636}, doi = {10.1161/ATVBAHA.115.305970}, author = {Mukamal, Kenneth J and Tremaglio, Joseph and Friedman, David J and Ix, Joachim H and Kuller, Lewis H and Tracy, Russell P and Pollak, Martin R} } @article {6990, title = {Fibroblast Growth Factor-23 and Frailty in Elderly Community-Dwelling Individuals: The Cardiovascular Health Study.}, journal = {J Am Geriatr Soc}, volume = {64}, year = {2016}, month = {2016 Feb}, pages = {270-6}, abstract = {

OBJECTIVES: To evaluate whether fibroblast growth factor 23 (FGF-23) is related to frailty and to characterize the nature of their joint association with mortality.

DESIGN: Cross-sectional analysis for frailty and longitudinal cohort analysis for mortality.

SETTING: Cardiovascular Health Study.

PARTICIPANTS: Community-dwelling individuals (N = 2,977; mean age 77.9 {\textpm} 4.7, 40\% male, 83\% white).

MEASUREMENTS: The predictor was serum FGF-23 concentration (C-terminal enzyme-linked immunosorbent assay), and the outcomes were frailty status (determined according to frailty phenotype criteria of weight loss, weakness, exhaustion, slowness, and low physical activity) and mortality. Multinomial logistic regression was used to assess the cross-sectional association between FGF-23 and frailty and prefrailty, adjusting for demographic characteristics, cardiovascular disease and risk factors, and kidney markers. Proportional hazards Cox proportional hazards regression was used to assess the association between FGF-23, frailty, and all-cause mortality.

RESULTS: Mean estimated glomerular filtration rate (eGFR) was 64 {\textpm} 17 mL/min per 1.73 m(2) . Median FGF-23 was 70.3 RU/mL (interquartile range 53.4-99.2); 52\% were prefrail, and 13\% were frail. After multivariate adjustment, each doubling in FGF-23 concentration was associated with 38\% (95\% confidence interval (CI) = 17-62\%) higher odds of frailty than of nonfrailty and 16\% (95\% CI = 3-30\%) higher odds of prefrailty. FGF-23 (hazard ratio (HR) = 1.16, 95\% CI = 1.10-1.23) and frailty (HR = 1.82, 95\% CI = 1.57-2.12) were independently associated with mortality, but neither association was meaningfully attenuated when adjusted for the other.

CONCLUSION: In a large cohort of older adults, higher FGF-23 was independently associated with prevalent frailty and prefrailty. FGF-23 and frailty were independent and additive risk factors for mortality. FGF-23 may be a marker for functional outcomes.

}, keywords = {Aged, Anthropometry, Biomarkers, Cardiovascular Diseases, Cross-Sectional Studies, Enzyme-Linked Immunosorbent Assay, Female, Fibroblast Growth Factors, Frail Elderly, Glomerular Filtration Rate, Humans, Independent Living, Longitudinal Studies, Male, Phenotype, Risk Factors, Surveys and Questionnaires}, issn = {1532-5415}, doi = {10.1111/jgs.13951}, author = {Beben, Tomasz and Ix, Joachim H and Shlipak, Michael G and Sarnak, Mark J and Fried, Linda F and Hoofnagle, Andrew N and Chonchol, Michel and Kestenbaum, Bryan R and de Boer, Ian H and Rifkin, Dena E} } @article {7573, title = {Exome-wide association study of plasma lipids in >300,000 individuals.}, journal = {Nat Genet}, volume = {49}, year = {2017}, month = {2017 Dec}, pages = {1758-1766}, abstract = {

We screened variants on an exome-focused genotyping array in >300,000 participants (replication in >280,000 participants) and identified 444 independent variants in 250 loci significantly associated with total cholesterol (TC), high-density-lipoprotein cholesterol (HDL-C), low-density-lipoprotein cholesterol (LDL-C), and/or triglycerides (TG). At two loci (JAK2 and A1CF), experimental analysis in mice showed lipid changes consistent with the human data. We also found that: (i) beta-thalassemia trait carriers displayed lower TC and were protected from coronary artery disease (CAD); (ii) excluding the CETP locus, there was not a predictable relationship between plasma HDL-C and risk for age-related macular degeneration; (iii) only some mechanisms of lowering LDL-C appeared to increase risk for type 2 diabetes (T2D); and (iv) TG-lowering alleles involved in hepatic production of TG-rich lipoproteins (TM6SF2 and PNPLA3) tracked with higher liver fat, higher risk for T2D, and lower risk for CAD, whereas TG-lowering alleles involved in peripheral lipolysis (LPL and ANGPTL4) had no effect on liver fat but decreased risks for both T2D and CAD.

}, keywords = {Coronary Artery Disease, Diabetes Mellitus, Type 2, Exome, Genetic Association Studies, Genetic Predisposition to Disease, Genetic Variation, Genotype, Humans, Lipids, Macular Degeneration, Phenotype, Risk Factors}, issn = {1546-1718}, doi = {10.1038/ng.3977}, author = {Liu, Dajiang J and Peloso, Gina M and Yu, Haojie and Butterworth, Adam S and Wang, Xiao and Mahajan, Anubha and Saleheen, Danish and Emdin, Connor and Alam, Dewan and Alves, Alexessander Couto and Amouyel, Philippe and Di Angelantonio, Emanuele and Arveiler, Dominique and Assimes, Themistocles L and Auer, Paul L and Baber, Usman and Ballantyne, Christie M and Bang, Lia E and Benn, Marianne and Bis, Joshua C and Boehnke, Michael and Boerwinkle, Eric and Bork-Jensen, Jette and Bottinger, Erwin P and Brandslund, Ivan and Brown, Morris and Busonero, Fabio and Caulfield, Mark J and Chambers, John C and Chasman, Daniel I and Chen, Y Eugene and Chen, Yii-Der Ida and Chowdhury, Rajiv and Christensen, Cramer and Chu, Audrey Y and Connell, John M and Cucca, Francesco and Cupples, L Adrienne and Damrauer, Scott M and Davies, Gail and Deary, Ian J and Dedoussis, George and Denny, Joshua C and Dominiczak, Anna and Dub{\'e}, Marie-Pierre and Ebeling, Tapani and Eiriksdottir, Gudny and Esko, T{\~o}nu and Farmaki, Aliki-Eleni and Feitosa, Mary F and Ferrario, Marco and Ferrieres, Jean and Ford, Ian and Fornage, Myriam and Franks, Paul W and Frayling, Timothy M and Frikke-Schmidt, Ruth and Fritsche, Lars G and Frossard, Philippe and Fuster, Valentin and Ganesh, Santhi K and Gao, Wei and Garcia, Melissa E and Gieger, Christian and Giulianini, Franco and Goodarzi, Mark O and Grallert, Harald and Grarup, Niels and Groop, Leif and Grove, Megan L and Gudnason, Vilmundur and Hansen, Torben and Harris, Tamara B and Hayward, Caroline and Hirschhorn, Joel N and Holmen, Oddgeir L and Huffman, Jennifer and Huo, Yong and Hveem, Kristian and Jabeen, Sehrish and Jackson, Anne U and Jakobsdottir, Johanna and Jarvelin, Marjo-Riitta and Jensen, Gorm B and J{\o}rgensen, Marit E and Jukema, J Wouter and Justesen, Johanne M and Kamstrup, Pia R and Kanoni, Stavroula and Karpe, Fredrik and Kee, Frank and Khera, Amit V and Klarin, Derek and Koistinen, Heikki A and Kooner, Jaspal S and Kooperberg, Charles and Kuulasmaa, Kari and Kuusisto, Johanna and Laakso, Markku and Lakka, Timo and Langenberg, Claudia and Langsted, Anne and Launer, Lenore J and Lauritzen, Torsten and Liewald, David C M and Lin, Li An and Linneberg, Allan and Loos, Ruth J F and Lu, Yingchang and Lu, Xiangfeng and M{\"a}gi, Reedik and M{\"a}larstig, Anders and Manichaikul, Ani and Manning, Alisa K and M{\"a}ntyselk{\"a}, Pekka and Marouli, Eirini and Masca, Nicholas G D and Maschio, Andrea and Meigs, James B and Melander, Olle and Metspalu, Andres and Morris, Andrew P and Morrison, Alanna C and Mulas, Antonella and M{\"u}ller-Nurasyid, Martina and Munroe, Patricia B and Neville, Matt J and Nielsen, Jonas B and Nielsen, Sune F and Nordestgaard, B{\o}rge G and Ordovas, Jose M and Mehran, Roxana and O{\textquoteright}Donnell, Christoper J and Orho-Melander, Marju and Molony, Cliona M and Muntendam, Pieter and Padmanabhan, Sandosh and Palmer, Colin N A and Pasko, Dorota and Patel, Aniruddh P and Pedersen, Oluf and Perola, Markus and Peters, Annette and Pisinger, Charlotta and Pistis, Giorgio and Polasek, Ozren and Poulter, Neil and Psaty, Bruce M and Rader, Daniel J and Rasheed, Asif and Rauramaa, Rainer and Reilly, Dermot F and Reiner, Alex P and Renstrom, Frida and Rich, Stephen S and Ridker, Paul M and Rioux, John D and Robertson, Neil R and Roden, Dan M and Rotter, Jerome I and Rudan, Igor and Salomaa, Veikko and Samani, Nilesh J and Sanna, Serena and Sattar, Naveed and Schmidt, Ellen M and Scott, Robert A and Sever, Peter and Sevilla, Raquel S and Shaffer, Christian M and Sim, Xueling and Sivapalaratnam, Suthesh and Small, Kerrin S and Smith, Albert V and Smith, Blair H and Somayajula, Sangeetha and Southam, Lorraine and Spector, Timothy D and Speliotes, Elizabeth K and Starr, John M and Stirrups, Kathleen E and Stitziel, Nathan and Strauch, Konstantin and Stringham, Heather M and Surendran, Praveen and Tada, Hayato and Tall, Alan R and Tang, Hua and Tardif, Jean-Claude and Taylor, Kent D and Trompet, Stella and Tsao, Philip S and Tuomilehto, Jaakko and Tybjaerg-Hansen, Anne and van Zuydam, Natalie R and Varbo, Anette and Varga, Tibor V and Virtamo, Jarmo and Waldenberger, Melanie and Wang, Nan and Wareham, Nick J and Warren, Helen R and Weeke, Peter E and Weinstock, Joshua and Wessel, Jennifer and Wilson, James G and Wilson, Peter W F and Xu, Ming and Yaghootkar, Hanieh and Young, Robin and Zeggini, Eleftheria and Zhang, He and Zheng, Neil S and Zhang, Weihua and Zhang, Yan and Zhou, Wei and Zhou, Yanhua and Zoledziewska, Magdalena and Howson, Joanna M M and Danesh, John and McCarthy, Mark I and Cowan, Chad A and Abecasis, Goncalo and Deloukas, Panos and Musunuru, Kiran and Willer, Cristen J and Kathiresan, Sekar} } @article {7571, title = {Genome-Wide Association Study Meta-Analysis of Long-Term Average Blood Pressure in East Asians.}, journal = {Circ Cardiovasc Genet}, volume = {10}, year = {2017}, month = {2017 Apr}, pages = {e001527}, abstract = {

BACKGROUND: Genome-wide single marker and gene-based meta-analyses of long-term average (LTA) blood pressure (BP) phenotypes may reveal novel findings for BP.

METHODS AND RESULTS: We conducted genome-wide analysis among 18 422 East Asian participants (stage 1) followed by replication study of <=46 629 participants of European ancestry (stage 2). Significant single-nucleotide polymorphisms and genes were determined by a P<5.0{\texttimes}10-8 and 2.5{\texttimes}10-6, respectively, in joint analyses of stage-1 and stage-2 data. We identified 1 novel ARL3 variant, rs4919669 at 10q24.32, influencing LTA systolic BP (stage-1 P=5.03{\texttimes}10-8, stage-2 P=8.64{\texttimes}10-3, joint P=2.63{\texttimes}10-8) and mean arterial pressure (stage-1 P=3.59{\texttimes}10-9, stage-2 P=2.35{\texttimes}10-2, joint P=2.64{\texttimes}10-8). Three previously reported BP loci (WBP1L, NT5C2, and ATP2B1) were also identified for all BP phenotypes. Gene-based analysis provided the first robust evidence for association of KCNJ11 with LTA systolic BP (stage-1 P=8.55{\texttimes}10-6, stage-2 P=1.62{\texttimes}10-5, joint P=3.28{\texttimes}10-9) and mean arterial pressure (stage-1 P=9.19{\texttimes}10-7, stage-2 P=9.69{\texttimes}10-5, joint P=2.15{\texttimes}10-9) phenotypes. Fourteen genes (TMEM180, ACTR1A, SUFU, ARL3, SFXN2, WBP1L, CYP17A1, C10orf32, C10orf32-ASMT, AS3MT, CNNM2, and NT5C2 at 10q24.32; ATP2B1 at 12q21.33; and NCR3LG1 at 11p15.1) implicated by previous genome-wide association study meta-analyses were also identified. Among the loci identified by the previous genome-wide association study meta-analysis of LTA BP, we transethnically replicated associations of the KCNK3 marker rs1275988 at 2p23.3 with LTA systolic BP and mean arterial pressure phenotypes (P=1.27{\texttimes}10-4 and 3.30{\texttimes}10-4, respectively).

CONCLUSIONS: We identified 1 novel variant and 1 novel gene and present the first direct evidence of relevance of the KCNK3 locus for LTA BP among East Asians.

}, keywords = {Asian Continental Ancestry Group, Blood Pressure, Far East, Female, Genetic Loci, Genome-Wide Association Study, Humans, Male, Phenotype, Polymorphism, Single Nucleotide}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.116.001527}, author = {Li, Changwei and Kim, Yun Kyoung and Dorajoo, Rajkumar and Li, Huaixing and Lee, I-Te and Cheng, Ching-Yu and He, Meian and Sheu, Wayne H-H and Guo, Xiuqing and Ganesh, Santhi K and He, Jiang and Lee, Juyoung and Liu, Jianjun and Hu, Yao and Rao, Dabeeru C and Tsai, Fuu-Jen and Koh, Jia Yu and Hu, Hua and Liang, Kae-Woei and Palmas, Walter and Hixson, James E and Han, Sohee and Teo, Yik-Ying and Wang, Yiqin and Chen, Jing and Lu, Chieh Hsiang and Zheng, Yingfeng and Gui, Lixuan and Lee, Wen-Jane and Yao, Jie and Gu, Dongfeng and Han, Bok-Ghee and Sim, Xueling and Sun, Liang and Zhao, Jinying and Chen, Chien-Hsiun and Kumari, Neelam and He, Yunfeng and Taylor, Kent D and Raffel, Leslie J and Moon, Sanghoon and Rotter, Jerome I and Ida Chen, Yii-Der and Wu, Tangchun and Wong, Tien Yin and Wu, Jer-Yuarn and Lin, Xu and Tai, E-Shyong and Kim, Bong-Jo and Kelly, Tanika N} } @article {7596, title = {Impact of common genetic determinants of Hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations: A transethnic genome-wide meta-analysis.}, journal = {PLoS Med}, volume = {14}, year = {2017}, month = {2017 Sep}, pages = {e1002383}, abstract = {

BACKGROUND: Glycated hemoglobin (HbA1c) is used to diagnose type 2 diabetes (T2D) and assess glycemic control in patients with diabetes. Previous genome-wide association studies (GWAS) have identified 18 HbA1c-associated genetic variants. These variants proved to be classifiable by their likely biological action as erythrocytic (also associated with erythrocyte traits) or glycemic (associated with other glucose-related traits). In this study, we tested the hypotheses that, in a very large scale GWAS, we would identify more genetic variants associated with HbA1c and that HbA1c variants implicated in erythrocytic biology would affect the diagnostic accuracy of HbA1c. We therefore expanded the number of HbA1c-associated loci and tested the effect of genetic risk-scores comprised of erythrocytic or glycemic variants on incident diabetes prediction and on prevalent diabetes screening performance. Throughout this multiancestry study, we kept a focus on interancestry differences in HbA1c genetics performance that might influence race-ancestry differences in health outcomes.

METHODS \& FINDINGS: Using genome-wide association meta-analyses in up to 159,940 individuals from 82 cohorts of European, African, East Asian, and South Asian ancestry, we identified 60 common genetic variants associated with HbA1c. We classified variants as implicated in glycemic, erythrocytic, or unclassified biology and tested whether additive genetic scores of erythrocytic variants (GS-E) or glycemic variants (GS-G) were associated with higher T2D incidence in multiethnic longitudinal cohorts (N = 33,241). Nineteen glycemic and 22 erythrocytic variants were associated with HbA1c at genome-wide significance. GS-G was associated with higher T2D risk (incidence OR = 1.05, 95\% CI 1.04-1.06, per HbA1c-raising allele, p = 3 {\texttimes} 10-29); whereas GS-E was not (OR = 1.00, 95\% CI 0.99-1.01, p = 0.60). In Europeans and Asians, erythrocytic variants in aggregate had only modest effects on the diagnostic accuracy of HbA1c. Yet, in African Americans, the X-linked G6PD G202A variant (T-allele frequency 11\%) was associated with an absolute decrease in HbA1c of 0.81\%-units (95\% CI 0.66-0.96) per allele in hemizygous men, and 0.68\%-units (95\% CI 0.38-0.97) in homozygous women. The G6PD variant may cause approximately 2\% (N = 0.65 million, 95\% CI 0.55-0.74) of African American adults with T2D to remain undiagnosed when screened with HbA1c. Limitations include the smaller sample sizes for non-European ancestries and the inability to classify approximately one-third of the variants. Further studies in large multiethnic cohorts with HbA1c, glycemic, and erythrocytic traits are required to better determine the biological action of the unclassified variants.

CONCLUSIONS: As G6PD deficiency can be clinically silent until illness strikes, we recommend investigation of the possible benefits of screening for the G6PD genotype along with using HbA1c to diagnose T2D in populations of African ancestry or groups where G6PD deficiency is common. Screening with direct glucose measurements, or genetically-informed HbA1c diagnostic thresholds in people with G6PD deficiency, may be required to avoid missed or delayed diagnoses.

}, keywords = {Diabetes Mellitus, Type 2, Genetic Variation, Genome-Wide Association Study, Glycated Hemoglobin A, Humans, Phenotype, Risk}, issn = {1549-1676}, doi = {10.1371/journal.pmed.1002383}, author = {Wheeler, Eleanor and Leong, Aaron and Liu, Ching-Ti and Hivert, Marie-France and Strawbridge, Rona J and Podmore, Clara and Li, Man and Yao, Jie and Sim, Xueling and Hong, Jaeyoung and Chu, Audrey Y and Zhang, Weihua and Wang, Xu and Chen, Peng and Maruthur, Nisa M and Porneala, Bianca C and Sharp, Stephen J and Jia, Yucheng and Kabagambe, Edmond K and Chang, Li-Ching and Chen, Wei-Min and Elks, Cathy E and Evans, Daniel S and Fan, Qiao and Giulianini, Franco and Go, Min Jin and Hottenga, Jouke-Jan and Hu, Yao and Jackson, Anne U and Kanoni, Stavroula and Kim, Young Jin and Kleber, Marcus E and Ladenvall, Claes and Lecoeur, C{\'e}cile and Lim, Sing-Hui and Lu, Yingchang and Mahajan, Anubha and Marzi, Carola and Nalls, Mike A and Navarro, Pau and Nolte, Ilja M and Rose, Lynda M and Rybin, Denis V and Sanna, Serena and Shi, Yuan and Stram, Daniel O and Takeuchi, Fumihiko and Tan, Shu Pei and van der Most, Peter J and van Vliet-Ostaptchouk, Jana V and Wong, Andrew and Yengo, Loic and Zhao, Wanting and Goel, Anuj and Martinez Larrad, Maria Teresa and Radke, D{\"o}rte and Salo, Perttu and Tanaka, Toshiko and van Iperen, Erik P A and Abecasis, Goncalo and Afaq, Saima and Alizadeh, Behrooz Z and Bertoni, Alain G and Bonnefond, Am{\'e}lie and B{\"o}ttcher, Yvonne and Bottinger, Erwin P and Campbell, Harry and Carlson, Olga D and Chen, Chien-Hsiun and Cho, Yoon Shin and Garvey, W Timothy and Gieger, Christian and Goodarzi, Mark O and Grallert, Harald and Hamsten, Anders and Hartman, Catharina A and Herder, Christian and Hsiung, Chao Agnes and Huang, Jie and Igase, Michiya and Isono, Masato and Katsuya, Tomohiro and Khor, Chiea-Chuen and Kiess, Wieland and Kohara, Katsuhiko and Kovacs, Peter and Lee, Juyoung and Lee, Wen-Jane and Lehne, Benjamin and Li, Huaixing and Liu, Jianjun and Lobbens, Stephane and Luan, Jian{\textquoteright}an and Lyssenko, Valeriya and Meitinger, Thomas and Miki, Tetsuro and Miljkovic, Iva and Moon, Sanghoon and Mulas, Antonella and M{\"u}ller, Gabriele and M{\"u}ller-Nurasyid, Martina and Nagaraja, Ramaiah and Nauck, Matthias and Pankow, James S and Polasek, Ozren and Prokopenko, Inga and Ramos, Paula S and Rasmussen-Torvik, Laura and Rathmann, Wolfgang and Rich, Stephen S and Robertson, Neil R and Roden, Michael and Roussel, Ronan and Rudan, Igor and Scott, Robert A and Scott, William R and Sennblad, Bengt and Siscovick, David S and Strauch, Konstantin and Sun, Liang and Swertz, Morris and Tajuddin, Salman M and Taylor, Kent D and Teo, Yik-Ying and Tham, Yih Chung and T{\"o}njes, Anke and Wareham, Nicholas J and Willemsen, Gonneke and Wilsgaard, Tom and Hingorani, Aroon D and Egan, Josephine and Ferrucci, Luigi and Hovingh, G Kees and Jula, Antti and Kivimaki, Mika and Kumari, Meena and Nj{\o}lstad, Inger and Palmer, Colin N A and Serrano R{\'\i}os, Manuel and Stumvoll, Michael and Watkins, Hugh and Aung, Tin and Bl{\"u}her, Matthias and Boehnke, Michael and Boomsma, Dorret I and Bornstein, Stefan R and Chambers, John C and Chasman, Daniel I and Chen, Yii-Der Ida and Chen, Yduan-Tsong and Cheng, Ching-Yu and Cucca, Francesco and de Geus, Eco J C and Deloukas, Panos and Evans, Michele K and Fornage, Myriam and Friedlander, Yechiel and Froguel, Philippe and Groop, Leif and Gross, Myron D and Harris, Tamara B and Hayward, Caroline and Heng, Chew-Kiat and Ingelsson, Erik and Kato, Norihiro and Kim, Bong-Jo and Koh, Woon-Puay and Kooner, Jaspal S and K{\"o}rner, Antje and Kuh, Diana and Kuusisto, Johanna and Laakso, Markku and Lin, Xu and Liu, Yongmei and Loos, Ruth J F and Magnusson, Patrik K E and M{\"a}rz, Winfried and McCarthy, Mark I and Oldehinkel, Albertine J and Ong, Ken K and Pedersen, Nancy L and Pereira, Mark A and Peters, Annette and Ridker, Paul M and Sabanayagam, Charumathi and Sale, Michele and Saleheen, Danish and Saltevo, Juha and Schwarz, Peter Eh and Sheu, Wayne H H and Snieder, Harold and Spector, Timothy D and Tabara, Yasuharu and Tuomilehto, Jaakko and van Dam, Rob M and Wilson, James G and Wilson, James F and Wolffenbuttel, Bruce H R and Wong, Tien Yin and Wu, Jer-Yuarn and Yuan, Jian-Min and Zonderman, Alan B and Soranzo, Nicole and Guo, Xiuqing and Roberts, David J and Florez, Jose C and Sladek, Robert and Dupuis, Jos{\'e}e and Morris, Andrew P and Tai, E-Shyong and Selvin, Elizabeth and Rotter, Jerome I and Langenberg, Claudia and Barroso, In{\^e}s and Meigs, James B} } @article {8555, title = {Phenotype-Specific Association of Single-Nucleotide Polymorphisms with Heart Failure and Preserved Ejection Fraction: a Genome-Wide Association Analysis of the Cardiovascular Health Study.}, journal = {J Cardiovasc Transl Res}, volume = {10}, year = {2017}, month = {2017 Jun}, pages = {285-294}, abstract = {

Little is known about genetics of heart failure with preserved ejection fraction (HFpEF) in part because of the many comorbidities in this population. To identify single-nucleotide polymorphisms (SNPs) associated with HFpEF, we analyzed phenotypic and genotypic data from the Cardiovascular Health Study, which profiled patients using a 50,000 SNP array. Results were explored using novel SNP- and gene-centric tools. We performed analyses to determine whether some SNPs were relevant only in certain phenotypes. Among 3804 patients, 7 clinical factors and 9 SNPs were significantly associated with HFpEF; the most notable of which was rs6996224, a SNP associated with transforming growth factor-beta receptor 3. Most SNPs were associated with HFpEF only in the absence of a clinical predictor. Significant SNPs represented genes involved in myocyte proliferation, transforming growth factor-beta/erbB signaling, and extracellular matrix formation. These findings suggest that genetic factors may be more important in some phenotypes than others.

}, keywords = {Aged, Computational Biology, Databases, Genetic, European Continental Ancestry Group, Female, Gene Expression Profiling, Genetic Markers, Genetic Predisposition to Disease, Genome-Wide Association Study, Heart Failure, Humans, Male, Oligonucleotide Array Sequence Analysis, Phenotype, Polymorphism, Single Nucleotide, Predictive Value of Tests, Prognosis, Proteoglycans, Receptors, Transforming Growth Factor beta, Risk Assessment, Risk Factors, Stroke Volume, United States}, issn = {1937-5395}, doi = {10.1007/s12265-017-9729-1}, author = {Kao, David P and Stevens, Laura M and Hinterberg, Michael A and G{\"o}rg, Carsten} } @article {7577, title = {Rare coding variants pinpoint genes that control human hematological traits.}, journal = {PLoS Genet}, volume = {13}, year = {2017}, month = {2017 Aug}, pages = {e1006925}, abstract = {

The identification of rare coding or splice site variants remains the most straightforward strategy to link genes with human phenotypes. Here, we analyzed the association between 137,086 rare (minor allele frequency (MAF) <1\%) coding or splice site variants and 15 hematological traits in up to 308,572 participants. We found 56 such rare coding or splice site variants at P<5x10-8, including 31 that are associated with a blood-cell phenotype for the first time. All but one of these 31 new independent variants map to loci previously implicated in hematopoiesis by genome-wide association studies (GWAS). This includes a rare splice acceptor variant (rs146597587, MAF = 0.5\%) in interleukin 33 (IL33) associated with reduced eosinophil count (P = 2.4x10-23), and lower risk of asthma (P = 2.6x10-7, odds ratio [95\% confidence interval] = 0.56 [0.45-0.70]) and allergic rhinitis (P = 4.2x10-4, odds ratio = 0.55 [0.39-0.76]). The single new locus identified in our study is defined by a rare p.Arg172Gly missense variant (rs145535174, MAF = 0.05\%) in plasminogen (PLG) associated with increased platelet count (P = 6.8x10-9), and decreased D-dimer concentration (P = 0.018) and platelet reactivity (P<0.03). Finally, our results indicate that searching for rare coding or splice site variants in very large sample sizes can help prioritize causal genes at many GWAS loci associated with complex human diseases and traits.

}, keywords = {Asthma, Databases, Genetic, Endometriosis, Female, Fibrin Fibrinogen Degradation Products, Gene Frequency, Genetic Loci, Genome, Human, Genome-Wide Association Study, Humans, Interleukin-33, Linear Models, Logistic Models, Male, Mutation, Missense, Phenotype, Plasminogen, Platelet Count, Polymorphism, Single Nucleotide, Principal Component Analysis, Protein Splicing, Rhinitis, Allergic, Sequence Analysis, DNA}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1006925}, author = {Mousas, Abdou and Ntritsos, Georgios and Chen, Ming-Huei and Song, Ci and Huffman, Jennifer E and Tzoulaki, Ioanna and Elliott, Paul and Psaty, Bruce M and Auer, Paul L and Johnson, Andrew D and Evangelou, Evangelos and Lettre, Guillaume and Reiner, Alexander P} } @article {8109, title = {A catalog of genetic loci associated with kidney function from analyses of a million individuals.}, journal = {Nat Genet}, volume = {51}, year = {2019}, month = {2019 06}, pages = {957-972}, abstract = {

Chronic kidney disease (CKD) is responsible for a public health burden with multi-systemic complications. Through trans-ancestry meta-analysis of genome-wide association studies of estimated glomerular filtration rate (eGFR) and independent replication (n = 1,046,070), we identified 264 associated loci (166 new). Of these, 147 were likely to be relevant for kidney function on the basis of associations with the alternative kidney function marker blood urea nitrogen (n = 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A genetic risk score for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Colocalization analyses of associations with eGFR among 783,978 European-ancestry individuals and gene expression across 46 human tissues, including tubulo-interstitial and glomerular kidney compartments, identified 17 genes differentially expressed in kidney. Fine-mapping highlighted missense driver variants in 11 genes and kidney-specific regulatory variants. These results provide a comprehensive priority list of molecular targets for translational research.

}, keywords = {Chromosome Mapping, European Continental Ancestry Group, Genetic Association Studies, Genetic Predisposition to Disease, Genome-Wide Association Study, Glomerular Filtration Rate, Humans, Inheritance Patterns, Kidney Function Tests, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Quantitative Trait, Heritable, Renal Insufficiency, Chronic, Uromodulin}, issn = {1546-1718}, doi = {10.1038/s41588-019-0407-x}, author = {Wuttke, Matthias and Li, Yong and Li, Man and Sieber, Karsten B and Feitosa, Mary F and Gorski, Mathias and Tin, Adrienne and Wang, Lihua and Chu, Audrey Y and Hoppmann, Anselm and Kirsten, Holger and Giri, Ayush and Chai, Jin-Fang and Sveinbjornsson, Gardar and Tayo, Bamidele O and Nutile, Teresa and Fuchsberger, Christian and Marten, Jonathan and Cocca, Massimiliano and Ghasemi, Sahar and Xu, Yizhe and Horn, Katrin and Noce, Damia and van der Most, Peter J and Sedaghat, Sanaz and Yu, Zhi and Akiyama, Masato and Afaq, Saima and Ahluwalia, Tarunveer S and Almgren, Peter and Amin, Najaf and Arnl{\"o}v, Johan and Bakker, Stephan J L and Bansal, Nisha and Baptista, Daniela and Bergmann, Sven and Biggs, Mary L and Biino, Ginevra and Boehnke, Michael and Boerwinkle, Eric and Boissel, Mathilde and Bottinger, Erwin P and Boutin, Thibaud S and Brenner, Hermann and Brumat, Marco and Burkhardt, Ralph and Butterworth, Adam S and Campana, Eric and Campbell, Archie and Campbell, Harry and Canouil, Micka{\"e}l and Carroll, Robert J and Catamo, Eulalia and Chambers, John C and Chee, Miao-Ling and Chee, Miao-Li and Chen, Xu and Cheng, Ching-Yu and Cheng, Yurong and Christensen, Kaare and Cifkova, Renata and Ciullo, Marina and Concas, Maria Pina and Cook, James P and Coresh, Josef and Corre, Tanguy and Sala, Cinzia Felicita and Cusi, Daniele and Danesh, John and Daw, E Warwick and de Borst, Martin H and De Grandi, Alessandro and de Mutsert, Ren{\'e}e and de Vries, Aiko P J and Degenhardt, Frauke and Delgado, Graciela and Demirkan, Ayse and Di Angelantonio, Emanuele and Dittrich, Katalin and Divers, Jasmin and Dorajoo, Rajkumar and Eckardt, Kai-Uwe and Ehret, Georg and Elliott, Paul and Endlich, Karlhans and Evans, Michele K and Felix, Janine F and Foo, Valencia Hui Xian and Franco, Oscar H and Franke, Andre and Freedman, Barry I and Freitag-Wolf, Sandra and Friedlander, Yechiel and Froguel, Philippe and Gansevoort, Ron T and Gao, He and Gasparini, Paolo and Gaziano, J Michael and Giedraitis, Vilmantas and Gieger, Christian and Girotto, Giorgia and Giulianini, Franco and G{\"o}gele, Martin and Gordon, Scott D and Gudbjartsson, Daniel F and Gudnason, Vilmundur and Haller, Toomas and Hamet, Pavel and Harris, Tamara B and Hartman, Catharina A and Hayward, Caroline and Hellwege, Jacklyn N and Heng, Chew-Kiat and Hicks, Andrew A and Hofer, Edith and Huang, Wei and Hutri-K{\"a}h{\"o}nen, Nina and Hwang, Shih-Jen and Ikram, M Arfan and Indridason, Olafur S and Ingelsson, Erik and Ising, Marcus and Jaddoe, Vincent W V and Jakobsdottir, Johanna and Jonas, Jost B and Joshi, Peter K and Josyula, Navya Shilpa and Jung, Bettina and K{\"a}h{\"o}nen, Mika and Kamatani, Yoichiro and Kammerer, Candace M and Kanai, Masahiro and Kastarinen, Mika and Kerr, Shona M and Khor, Chiea-Chuen and Kiess, Wieland and Kleber, Marcus E and Koenig, Wolfgang and Kooner, Jaspal S and K{\"o}rner, Antje and Kovacs, Peter and Kraja, Aldi T and Krajcoviechova, Alena and Kramer, Holly and Kr{\"a}mer, Bernhard K and Kronenberg, Florian and Kubo, Michiaki and Kuhnel, Brigitte and Kuokkanen, Mikko and Kuusisto, Johanna and La Bianca, Martina and Laakso, Markku and Lange, Leslie A and Langefeld, Carl D and Lee, Jeannette Jen-Mai and Lehne, Benjamin and Lehtim{\"a}ki, Terho and Lieb, Wolfgang and Lim, Su-Chi and Lind, Lars and Lindgren, Cecilia M and Liu, Jun and Liu, Jianjun and Loeffler, Markus and Loos, Ruth J F and Lucae, Susanne and Lukas, Mary Ann and Lyytik{\"a}inen, Leo-Pekka and M{\"a}gi, Reedik and Magnusson, Patrik K E and Mahajan, Anubha and Martin, Nicholas G and Martins, Jade and M{\"a}rz, Winfried and Mascalzoni, Deborah and Matsuda, Koichi and Meisinger, Christa and Meitinger, Thomas and Melander, Olle and Metspalu, Andres and Mikaelsdottir, Evgenia K and Milaneschi, Yuri and Miliku, Kozeta and Mishra, Pashupati P and Mohlke, Karen L and Mononen, Nina and Montgomery, Grant W and Mook-Kanamori, Dennis O and Mychaleckyj, Josyf C and Nadkarni, Girish N and Nalls, Mike A and Nauck, Matthias and Nikus, Kjell and Ning, Boting and Nolte, Ilja M and Noordam, Raymond and O{\textquoteright}Connell, Jeffrey and O{\textquoteright}Donoghue, Michelle L and Olafsson, Isleifur and Oldehinkel, Albertine J and Orho-Melander, Marju and Ouwehand, Willem H and Padmanabhan, Sandosh and Palmer, Nicholette D and Palsson, Runolfur and Penninx, Brenda W J H and Perls, Thomas and Perola, Markus and Pirastu, Mario and Pirastu, Nicola and Pistis, Giorgio and Podgornaia, Anna I and Polasek, Ozren and Ponte, Belen and Porteous, David J and Poulain, Tanja and Pramstaller, Peter P and Preuss, Michael H and Prins, Bram P and Province, Michael A and Rabelink, Ton J and Raffield, Laura M and Raitakari, Olli T and Reilly, Dermot F and Rettig, Rainer and Rheinberger, Myriam and Rice, Kenneth M and Ridker, Paul M and Rivadeneira, Fernando and Rizzi, Federica and Roberts, David J and Robino, Antonietta and Rossing, Peter and Rudan, Igor and Rueedi, Rico and Ruggiero, Daniela and Ryan, Kathleen A and Saba, Yasaman and Sabanayagam, Charumathi and Salomaa, Veikko and Salvi, Erika and Saum, Kai-Uwe and Schmidt, Helena and Schmidt, Reinhold and Sch{\"o}ttker, Ben and Schulz, Christina-Alexandra and Schupf, Nicole and Shaffer, Christian M and Shi, Yuan and Smith, Albert V and Smith, Blair H and Soranzo, Nicole and Spracklen, Cassandra N and Strauch, Konstantin and Stringham, Heather M and Stumvoll, Michael and Svensson, Per O and Szymczak, Silke and Tai, E-Shyong and Tajuddin, Salman M and Tan, Nicholas Y Q and Taylor, Kent D and Teren, Andrej and Tham, Yih-Chung and Thiery, Joachim and Thio, Chris H L and Thomsen, Hauke and Thorleifsson, Gudmar and Toniolo, Daniela and T{\"o}njes, Anke and Tremblay, Johanne and Tzoulaki, Ioanna and Uitterlinden, Andr{\'e} G and Vaccargiu, Simona and van Dam, Rob M and van der Harst, Pim and van Duijn, Cornelia M and Velez Edward, Digna R and Verweij, Niek and Vogelezang, Suzanne and V{\"o}lker, Uwe and Vollenweider, Peter and Waeber, G{\'e}rard and Waldenberger, Melanie and Wallentin, Lars and Wang, Ya Xing and Wang, Chaolong and Waterworth, Dawn M and Bin Wei, Wen and White, Harvey and Whitfield, John B and Wild, Sarah H and Wilson, James F and Wojczynski, Mary K and Wong, Charlene and Wong, Tien-Yin and Xu, Liang and Yang, Qiong and Yasuda, Masayuki and Yerges-Armstrong, Laura M and Zhang, Weihua and Zonderman, Alan B and Rotter, Jerome I and Bochud, Murielle and Psaty, Bruce M and Vitart, Veronique and Wilson, James G and Dehghan, Abbas and Parsa, Afshin and Chasman, Daniel I and Ho, Kevin and Morris, Andrew P and Devuyst, Olivier and Akilesh, Shreeram and Pendergrass, Sarah A and Sim, Xueling and B{\"o}ger, Carsten A and Okada, Yukinori and Edwards, Todd L and Snieder, Harold and Stefansson, Kari and Hung, Adriana M and Heid, Iris M and Scholz, Markus and Teumer, Alexander and K{\"o}ttgen, Anna and Pattaro, Cristian} } @article {8400, title = {Chronic obstructive pulmonary disease and related phenotypes: polygenic risk scores in population-based and case-control cohorts.}, journal = {Lancet Respir Med}, volume = {8}, year = {2020}, month = {2020 07}, pages = {696-708}, abstract = {

BACKGROUND: Genetic factors influence chronic obstructive pulmonary disease (COPD) risk, but the individual variants that have been identified have small effects. We hypothesised that a polygenic risk score using additional variants would predict COPD and associated phenotypes.

METHODS: We constructed a polygenic risk score using a genome-wide association study of lung function (FEV and FEV/forced vital capacity [FVC]) from the UK Biobank and SpiroMeta. We tested this polygenic risk score in nine cohorts of multiple ethnicities for an association with moderate-to-severe COPD (defined as FEV/FVC <0{\textperiodcentered}7 and FEV <80\% of predicted). Associations were tested using logistic regression models, adjusting for age, sex, height, smoking pack-years, and principal components of genetic ancestry. We assessed predictive performance of models by area under the curve. In a subset of studies, we also studied quantitative and qualitative CT imaging phenotypes that reflect parenchymal and airway pathology, and patterns of reduced lung growth.

FINDINGS: The polygenic risk score was associated with COPD in European (odds ratio [OR] per SD 1{\textperiodcentered}81 [95\% CI 1{\textperiodcentered}74-1{\textperiodcentered}88] and non-European (1{\textperiodcentered}42 [1{\textperiodcentered}34-1{\textperiodcentered}51]) populations. Compared with the first decile, the tenth decile of the polygenic risk score was associated with COPD, with an OR of 7{\textperiodcentered}99 (6{\textperiodcentered}56-9{\textperiodcentered}72) in European ancestry and 4{\textperiodcentered}83 (3{\textperiodcentered}45-6{\textperiodcentered}77) in non-European ancestry cohorts. The polygenic risk score was superior to previously described genetic risk scores and, when combined with clinical risk factors (ie, age, sex, and smoking pack-years), showed improved prediction for COPD compared with a model comprising clinical risk factors alone (AUC 0{\textperiodcentered}80 [0{\textperiodcentered}79-0{\textperiodcentered}81] vs 0{\textperiodcentered}76 [0{\textperiodcentered}75-0{\textperiodcentered}76]). The polygenic risk score was associated with CT imaging phenotypes, including wall area percent, quantitative and qualitative measures of emphysema, local histogram emphysema patterns, and destructive emphysema subtypes. The polygenic risk score was associated with a reduced lung growth pattern.

INTERPRETATION: A risk score comprised of genetic variants can identify a small subset of individuals at markedly increased risk for moderate-to-severe COPD, emphysema subtypes associated with cigarette smoking, and patterns of reduced lung growth.

FUNDING: US National Institutes of Health, Wellcome Trust.

}, keywords = {Adult, Case-Control Studies, Cohort Studies, Female, Forced Expiratory Volume, Genome-Wide Association Study, Humans, Male, Middle Aged, Phenotype, Pulmonary Disease, Chronic Obstructive, Risk Factors, Vital Capacity}, issn = {2213-2619}, doi = {10.1016/S2213-2600(20)30101-6}, author = {Moll, Matthew and Sakornsakolpat, Phuwanat and Shrine, Nick and Hobbs, Brian D and DeMeo, Dawn L and John, Catherine and Guyatt, Anna L and McGeachie, Michael J and Gharib, Sina A and Obeidat, Ma{\textquoteright}en and Lahousse, Lies and Wijnant, Sara R A and Brusselle, Guy and Meyers, Deborah A and Bleecker, Eugene R and Li, Xingnan and Tal-Singer, Ruth and Manichaikul, Ani and Rich, Stephen S and Won, Sungho and Kim, Woo Jin and Do, Ah Ra and Washko, George R and Barr, R Graham and Psaty, Bruce M and Bartz, Traci M and Hansel, Nadia N and Barnes, Kathleen and Hokanson, John E and Crapo, James D and Lynch, David and Bakke, Per and Gulsvik, Amund and Hall, Ian P and Wain, Louise and Weiss, Scott T and Silverman, Edwin K and Dudbridge, Frank and Tobin, Martin D and Cho, Michael H} } @article {8918, title = {Rare variants in the endocytic pathway are associated with Alzheimer{\textquoteright}s disease, its related phenotypes, and functional consequences.}, journal = {PLoS Genet}, volume = {17}, year = {2021}, month = {2021 09}, pages = {e1009772}, abstract = {

Late-onset Alzheimer{\textquoteright}s disease (LOAD) is the most common type of dementia causing irreversible brain damage to the elderly and presents a major public health challenge. Clinical research and genome-wide association studies have suggested a potential contribution of the endocytic pathway to AD, with an emphasis on common loci. However, the contribution of rare variants in this pathway to AD has not been thoroughly investigated. In this study, we focused on the effect of rare variants on AD by first applying a rare-variant gene-set burden analysis using genes in the endocytic pathway on over 3,000 individuals with European ancestry from three large whole-genome sequencing (WGS) studies. We identified significant associations of rare-variant burden within the endocytic pathway with AD, which were successfully replicated in independent datasets. We further demonstrated that this endocytic rare-variant enrichment is associated with neurofibrillary tangles (NFTs) and age-related phenotypes, increasing the risk of obtaining severer brain damage, earlier age-at-onset, and earlier age-of-death. Next, by aggregating rare variants within each gene, we sought to identify single endocytic genes associated with AD and NFTs. Careful examination using NFTs revealed one significantly associated gene, ANKRD13D. To identify functional associations, we integrated bulk RNA-Seq data from over 600 brain tissues and found two endocytic expression genes (eGenes), HLA-A and SLC26A7, that displayed significant influences on their gene expressions. Differential expressions between AD patients and controls of these three identified genes were further examined by incorporating scRNA-Seq data from 48 post-mortem brain samples and demonstrated distinct expression patterns across cell types. Taken together, our results demonstrated strong rare-variant effect in the endocytic pathway on AD risk and progression and functional effect of gene expression alteration in both bulk and single-cell resolution, which may bring more insight and serve as valuable resources for future AD genetic studies, clinical research, and therapeutic targeting.

}, keywords = {Alzheimer Disease, Endocytosis, Genome-Wide Association Study, Humans, Phenotype, Polymorphism, Single Nucleotide, Whole Genome Sequencing}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1009772}, author = {Zhan, Lingyu and Li, Jiajin and Jew, Brandon and Sul, Jae Hoon} } @article {8779, title = {Whole-genome sequencing association analysis of quantitative red blood cell phenotypes: The NHLBI TOPMed program.}, journal = {Am J Hum Genet}, volume = {108}, year = {2021}, month = {2021 05 06}, pages = {874-893}, abstract = {

Whole-genome sequencing (WGS), a powerful tool for detecting novel coding and non-coding disease-causing variants, has largely been applied to clinical diagnosis of inherited disorders. Here we leveraged WGS data in up to 62,653 ethnically diverse participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and assessed statistical association of variants with seven red blood cell (RBC) quantitative traits. We discovered 14 single variant-RBC trait associations at 12 genomic loci, which have not been reported previously. Several of the RBC trait-variant associations (RPN1, ELL2, MIDN, HBB, HBA1, PIEZO1, and G6PD) were replicated in independent GWAS datasets imputed to the TOPMed reference panel. Most of these discovered variants are rare/low frequency, and several are observed disproportionately among non-European Ancestry (African, Hispanic/Latino, or East Asian) populations. We identified a 3~bp indel p.Lys2169del (g.88717175_88717177TCT[4]) (common only in the Ashkenazi Jewish population) of PIEZO1, a gene responsible for the Mendelian red cell disorder hereditary xerocytosis (MIM: 194380), associated with higher mean corpuscular hemoglobin concentration (MCHC). In stepwise conditional analysis and in gene-based rare variant aggregated association analysis, we identified several of the variants in HBB, HBA1, TMPRSS6, and G6PD that represent the carrier state for known coding, promoter, or splice site loss-of-function variants that cause inherited RBC disorders. Finally, we applied base and nuclease editing to demonstrate that the sentinel variant rs112097551 (nearest gene RPN1) acts through a cis-regulatory element that exerts long-range control of the gene RUVBL1 which is essential for hematopoiesis. Together, these results demonstrate the utility of WGS in ethnically diverse population-based samples and gene editing for expanding knowledge of the genetic architecture of quantitative hematologic traits and suggest a continuum between complex trait and Mendelian red cell disorders.

}, keywords = {Adult, Aged, Chromosomes, Human, Pair 16, Datasets as Topic, Erythrocytes, Female, Gene Editing, Genetic Variation, Genome-Wide Association Study, HEK293 Cells, Humans, Male, Middle Aged, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Quality Control, Reproducibility of Results, United States}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2021.04.003}, author = {Hu, Yao and Stilp, Adrienne M and McHugh, Caitlin P and Rao, Shuquan and Jain, Deepti and Zheng, Xiuwen and Lane, John and M{\'e}ric de Bellefon, S{\'e}bastian and Raffield, Laura M and Chen, Ming-Huei and Yanek, Lisa R and Wheeler, Marsha and Yao, Yao and Ren, Chunyan and Broome, Jai and Moon, Jee-Young and de Vries, Paul S and Hobbs, Brian D and Sun, Quan and Surendran, Praveen and Brody, Jennifer A and Blackwell, Thomas W and Choquet, Helene and Ryan, Kathleen and Duggirala, Ravindranath and Heard-Costa, Nancy and Wang, Zhe and Chami, Nathalie and Preuss, Michael H and Min, Nancy and Ekunwe, Lynette and Lange, Leslie A and Cushman, Mary and Faraday, Nauder and Curran, Joanne E and Almasy, Laura and Kundu, Kousik and Smith, Albert V and Gabriel, Stacey and Rotter, Jerome I and Fornage, Myriam and Lloyd-Jones, Donald M and Vasan, Ramachandran S and Smith, Nicholas L and North, Kari E and Boerwinkle, Eric and Becker, Lewis C and Lewis, Joshua P and Abecasis, Goncalo R and Hou, Lifang and O{\textquoteright}Connell, Jeffrey R and Morrison, Alanna C and Beaty, Terri H and Kaplan, Robert and Correa, Adolfo and Blangero, John and Jorgenson, Eric and Psaty, Bruce M and Kooperberg, Charles and Walton, Russell T and Kleinstiver, Benjamin P and Tang, Hua and Loos, Ruth J F and Soranzo, Nicole and Butterworth, Adam S and Nickerson, Debbie and Rich, Stephen S and Mitchell, Braxton D and Johnson, Andrew D and Auer, Paul L and Li, Yun and Mathias, Rasika A and Lettre, Guillaume and Pankratz, Nathan and Laurie, Cathy C and Laurie, Cecelia A and Bauer, Daniel E and Conomos, Matthew P and Reiner, Alexander P} } @article {8914, title = {Whole-genome sequencing in diverse subjects identifies genetic correlates of leukocyte traits: The NHLBI TOPMed program.}, journal = {Am J Hum Genet}, volume = {108}, year = {2021}, month = {2021 10 07}, pages = {1836-1851}, abstract = {

Many common and rare variants associated with hematologic traits have been discovered through imputation on large-scale reference panels. However, the majority of genome-wide association studies (GWASs) have been conducted in Europeans, and determining causal variants has proved challenging. We performed a GWAS of total leukocyte, neutrophil, lymphocyte, monocyte, eosinophil, and basophil counts generated from 109,563,748 variants in the autosomes and the X chromosome in the Trans-Omics for Precision Medicine (TOPMed) program, which included data from 61,802 individuals of diverse ancestry. We discovered and replicated 7 leukocyte trait associations, including (1) the association between a chromosome X, pseudo-autosomal region (PAR), noncoding variant located between cytokine receptor genes (CSF2RA and CLRF2) and lower eosinophil count; and (2) associations between single variants found predominantly among African Americans at the S1PR3 (9q22.1) and HBB (11p15.4) loci and monocyte and lymphocyte counts, respectively. We further provide evidence indicating that the newly discovered eosinophil-lowering chromosome X PAR variant might be associated with reduced susceptibility to common allergic diseases such as atopic dermatitis and asthma. Additionally, we found a burden of very rare FLT3 (13q12.2) variants associated with monocyte counts. Together, these results emphasize the utility of whole-genome sequencing in diverse samples in identifying associations missed by European-ancestry-driven GWASs.

}, keywords = {Asthma, Biomarkers, Dermatitis, Atopic, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Leukocytes, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Polymorphism, Single Nucleotide, Prognosis, Proteome, Pulmonary Disease, Chronic Obstructive, Quantitative Trait Loci, United Kingdom, United States, Whole Genome Sequencing}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2021.08.007}, author = {Mikhaylova, Anna V and McHugh, Caitlin P and Polfus, Linda M and Raffield, Laura M and Boorgula, Meher Preethi and Blackwell, Thomas W and Brody, Jennifer A and Broome, Jai and Chami, Nathalie and Chen, Ming-Huei and Conomos, Matthew P and Cox, Corey and Curran, Joanne E and Daya, Michelle and Ekunwe, Lynette and Glahn, David C and Heard-Costa, Nancy and Highland, Heather M and Hobbs, Brian D and Ilboudo, Yann and Jain, Deepti and Lange, Leslie A and Miller-Fleming, Tyne W and Min, Nancy and Moon, Jee-Young and Preuss, Michael H and Rosen, Jonathon and Ryan, Kathleen and Smith, Albert V and Sun, Quan and Surendran, Praveen and de Vries, Paul S and Walter, Klaudia and Wang, Zhe and Wheeler, Marsha and Yanek, Lisa R and Zhong, Xue and Abecasis, Goncalo R and Almasy, Laura and Barnes, Kathleen C and Beaty, Terri H and Becker, Lewis C and Blangero, John and Boerwinkle, Eric and Butterworth, Adam S and Chavan, Sameer and Cho, Michael H and Choquet, Helene and Correa, Adolfo and Cox, Nancy and DeMeo, Dawn L and Faraday, Nauder and Fornage, Myriam and Gerszten, Robert E and Hou, Lifang and Johnson, Andrew D and Jorgenson, Eric and Kaplan, Robert and Kooperberg, Charles and Kundu, Kousik and Laurie, Cecelia A and Lettre, Guillaume and Lewis, Joshua P and Li, Bingshan and Li, Yun and Lloyd-Jones, Donald M and Loos, Ruth J F and Manichaikul, Ani and Meyers, Deborah A and Mitchell, Braxton D and Morrison, Alanna C and Ngo, Debby and Nickerson, Deborah A and Nongmaithem, Suraj and North, Kari E and O{\textquoteright}Connell, Jeffrey R and Ortega, Victor E and Pankratz, Nathan and Perry, James A and Psaty, Bruce M and Rich, Stephen S and Soranzo, Nicole and Rotter, Jerome I and Silverman, Edwin K and Smith, Nicholas L and Tang, Hua and Tracy, Russell P and Thornton, Timothy A and Vasan, Ramachandran S and Zein, Joe and Mathias, Rasika A and Reiner, Alexander P and Auer, Paul L} } @article {9246, title = {Correlations between complex human phenotypes vary by genetic background, gender, and environment.}, journal = {Cell Rep Med}, volume = {3}, year = {2022}, month = {2022 Dec 20}, pages = {100844}, abstract = {

We develop a closed-form Haseman-Elston estimator for genetic and environmental correlation coefficients between complex phenotypes, which we term HEc, that is as precise as GCTA yet \~{}20{\texttimes} faster. We estimate genetic and environmental correlations between over 7,000 phenotype pairs in subgroups from the Trans-Omics in Precision Medicine (TOPMed) program. We demonstrate substantial differences in both heritabilities and genetic correlations for multiple phenotypes and phenotype pairs between individuals of self-reported Black, Hispanic/Latino, and White backgrounds. We similarly observe differences in many of the genetic and environmental correlations between genders. To estimate the contribution of genetics to the observed phenotypic correlation, we introduce "fractional genetic correlation" as the fraction of phenotypic correlation explained by genetics. Finally, we quantify the enrichment of correlations between phenotypic domains, each of which is comprised of multiple phenotypes. Altogether, we demonstrate that the observed correlations between complex human phenotypes depend on the genetic background of the individuals, their gender, and their environment.

}, keywords = {Female, Genetic Background, Humans, Male, Phenotype}, issn = {2666-3791}, doi = {10.1016/j.xcrm.2022.100844}, author = {Elgart, Michael and Goodman, Matthew O and Isasi, Carmen and Chen, Han and Morrison, Alanna C and de Vries, Paul S and Xu, Huichun and Manichaikul, Ani W and Guo, Xiuqing and Franceschini, Nora and Psaty, Bruce M and Rich, Stephen S and Rotter, Jerome I and Lloyd-Jones, Donald M and Fornage, Myriam and Correa, Adolfo and Heard-Costa, Nancy L and Vasan, Ramachandran S and Hernandez, Ryan and Kaplan, Robert C and Redline, Susan and Sofer, Tamar} } @article {9253, title = {A framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies.}, journal = {Nat Methods}, volume = {19}, year = {2022}, month = {2022 Dec}, pages = {1599-1611}, abstract = {

Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate multiple functional annotations. In non-gene-centric analysis, STAARpipeline uses SCANG-STAAR to incorporate dynamic window sizes and multiple functional annotations. We apply STAARpipeline to identify noncoding RV sets associated with four lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several of them in an additional 9,123 TOPMed samples. We also analyze five non-lipid TOPMed traits.

}, keywords = {Genetic Variation, Genome, Genome-Wide Association Study, Humans, Phenotype, Whole Genome Sequencing}, issn = {1548-7105}, doi = {10.1038/s41592-022-01640-x}, author = {Li, Zilin and Li, Xihao and Zhou, Hufeng and Gaynor, Sheila M and Selvaraj, Margaret Sunitha and Arapoglou, Theodore and Quick, Corbin and Liu, Yaowu and Chen, Han and Sun, Ryan and Dey, Rounak and Arnett, Donna K and Auer, Paul L and Bielak, Lawrence F and Bis, Joshua C and Blackwell, Thomas W and Blangero, John and Boerwinkle, Eric and Bowden, Donald W and Brody, Jennifer A and Cade, Brian E and Conomos, Matthew P and Correa, Adolfo and Cupples, L Adrienne and Curran, Joanne E and de Vries, Paul S and Duggirala, Ravindranath and Franceschini, Nora and Freedman, Barry I and G{\"o}ring, Harald H H and Guo, Xiuqing and Kalyani, Rita R and Kooperberg, Charles and Kral, Brian G and Lange, Leslie A and Lin, Bridget M and Manichaikul, Ani and Manning, Alisa K and Martin, Lisa W and Mathias, Rasika A and Meigs, James B and Mitchell, Braxton D and Montasser, May E and Morrison, Alanna C and Naseri, Take and O{\textquoteright}Connell, Jeffrey R and Palmer, Nicholette D and Peyser, Patricia A and Psaty, Bruce M and Raffield, Laura M and Redline, Susan and Reiner, Alexander P and Reupena, Muagututi{\textquoteright}a Sefuiva and Rice, Kenneth M and Rich, Stephen S and Smith, Jennifer A and Taylor, Kent D and Taub, Margaret A and Vasan, Ramachandran S and Weeks, Daniel E and Wilson, James G and Yanek, Lisa R and Zhao, Wei and Rotter, Jerome I and Willer, Cristen J and Natarajan, Pradeep and Peloso, Gina M and Lin, Xihong} } @article {8975, title = {Rare coding variants in 35 genes associate with circulating lipid levels-A multi-ancestry analysis of 170,000 exomes.}, journal = {Am J Hum Genet}, volume = {109}, year = {2022}, month = {2022 01 06}, pages = {81-96}, abstract = {

Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1\%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci based on aggregations of rare coding variants; three (EVI5, SH2B3, and PLIN1) had no prior association of rare coding variants with lipid levels. Most of our associated genes showed evidence of association among multiple ancestries. Finally, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes and for genes closest to GWAS index single-nucleotide polymorphisms (SNPs). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels.

}, keywords = {Alleles, Blood Glucose, Case-Control Studies, Computational Biology, Databases, Genetic, Diabetes Mellitus, Type 2, Exome, Genetic Predisposition to Disease, Genetic Variation, Genetics, Population, Genome-Wide Association Study, Humans, Lipid Metabolism, Lipids, Liver, Molecular Sequence Annotation, Multifactorial Inheritance, Open Reading Frames, Phenotype, Polymorphism, Single Nucleotide}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2021.11.021}, author = {Hindy, George and Dornbos, Peter and Chaffin, Mark D and Liu, Dajiang J and Wang, Minxian and Selvaraj, Margaret Sunitha and Zhang, David and Park, Joseph and Aguilar-Salinas, Carlos A and Antonacci-Fulton, Lucinda and Ardissino, Diego and Arnett, Donna K and Aslibekyan, Stella and Atzmon, Gil and Ballantyne, Christie M and Barajas-Olmos, Francisco and Barzilai, Nir and Becker, Lewis C and Bielak, Lawrence F and Bis, Joshua C and Blangero, John and Boerwinkle, Eric and Bonnycastle, Lori L and Bottinger, Erwin and Bowden, Donald W and Bown, Matthew J and Brody, Jennifer A and Broome, Jai G and Burtt, Noel P and Cade, Brian E and Centeno-Cruz, Federico and Chan, Edmund and Chang, Yi-Cheng and Chen, Yii-der I and Cheng, Ching-Yu and Choi, Won Jung and Chowdhury, Rajiv and Contreras-Cubas, Cecilia and C{\'o}rdova, Emilio J and Correa, Adolfo and Cupples, L Adrienne and Curran, Joanne E and Danesh, John and de Vries, Paul S and DeFronzo, Ralph A and Doddapaneni, Harsha and Duggirala, Ravindranath and Dutcher, Susan K and Ellinor, Patrick T and Emery, Leslie S and Florez, Jose C and Fornage, Myriam and Freedman, Barry I and Fuster, Valentin and Garay-Sevilla, Ma Eugenia and Garc{\'\i}a-Ortiz, Humberto and Germer, Soren and Gibbs, Richard A and Gieger, Christian and Glaser, Benjamin and Gonzalez, Clicerio and Gonzalez-Villalpando, Maria Elena and Graff, Mariaelisa and Graham, Sarah E and Grarup, Niels and Groop, Leif C and Guo, Xiuqing and Gupta, Namrata and Han, Sohee and Hanis, Craig L and Hansen, Torben and He, Jiang and Heard-Costa, Nancy L and Hung, Yi-Jen and Hwang, Mi Yeong and Irvin, Marguerite R and Islas-Andrade, Sergio and Jarvik, Gail P and Kang, Hyun Min and Kardia, Sharon L R and Kelly, Tanika and Kenny, Eimear E and Khan, Alyna T and Kim, Bong-Jo and Kim, Ryan W and Kim, Young Jin and Koistinen, Heikki A and Kooperberg, Charles and Kuusisto, Johanna and Kwak, Soo Heon and Laakso, Markku and Lange, Leslie A and Lee, Jiwon and Lee, Juyoung and Lee, Seonwook and Lehman, Donna M and Lemaitre, Rozenn N and Linneberg, Allan and Liu, Jianjun and Loos, Ruth J F and Lubitz, Steven A and Lyssenko, Valeriya and Ma, Ronald C W and Martin, Lisa Warsinger and Mart{\'\i}nez-Hern{\'a}ndez, Ang{\'e}lica and Mathias, Rasika A and McGarvey, Stephen T and McPherson, Ruth and Meigs, James B and Meitinger, Thomas and Melander, Olle and Mendoza-Caamal, Elvia and Metcalf, Ginger A and Mi, Xuenan and Mohlke, Karen L and Montasser, May E and Moon, Jee-Young and Moreno-Macias, Hortensia and Morrison, Alanna C and Muzny, Donna M and Nelson, Sarah C and Nilsson, Peter M and O{\textquoteright}Connell, Jeffrey R and Orho-Melander, Marju and Orozco, Lorena and Palmer, Colin N A and Palmer, Nicholette D and Park, Cheol Joo and Park, Kyong Soo and Pedersen, Oluf and Peralta, Juan M and Peyser, Patricia A and Post, Wendy S and Preuss, Michael and Psaty, Bruce M and Qi, Qibin and Rao, D C and Redline, Susan and Reiner, Alexander P and Revilla-Monsalve, Cristina and Rich, Stephen S and Samani, Nilesh and Schunkert, Heribert and Schurmann, Claudia and Seo, Daekwan and Seo, Jeong-Sun and Sim, Xueling and Sladek, Rob and Small, Kerrin S and So, Wing Yee and Stilp, Adrienne M and Tai, E Shyong and Tam, Claudia H T and Taylor, Kent D and Teo, Yik Ying and Thameem, Farook and Tomlinson, Brian and Tsai, Michael Y and Tuomi, Tiinamaija and Tuomilehto, Jaakko and Tusi{\'e}-Luna, Teresa and Udler, Miriam S and van Dam, Rob M and Vasan, Ramachandran S and Viaud Martinez, Karine A and Wang, Fei Fei and Wang, Xuzhi and Watkins, Hugh and Weeks, Daniel E and Wilson, James G and Witte, Daniel R and Wong, Tien-Yin and Yanek, Lisa R and Kathiresan, Sekar and Rader, Daniel J and Rotter, Jerome I and Boehnke, Michael and McCarthy, Mark I and Willer, Cristen J and Natarajan, Pradeep and Flannick, Jason A and Khera, Amit V and Peloso, Gina M} } @article {9419, title = {The genetic determinants of recurrent somatic mutations in 43,693 blood genomes.}, journal = {Sci Adv}, volume = {9}, year = {2023}, month = {2023 Apr 28}, pages = {eabm4945}, abstract = {

Nononcogenic somatic mutations are thought to be uncommon and inconsequential. To test this, we analyzed 43,693 National Heart, Lung and Blood Institute Trans-Omics for Precision Medicine blood whole genomes from 37 cohorts and identified 7131 non-missense somatic mutations that are recurrently mutated in at least 50 individuals. These recurrent non-missense somatic mutations (RNMSMs) are not clearly explained by other clonal phenomena such as clonal hematopoiesis. RNMSM prevalence increased with age, with an average 50-year-old having 27 RNMSMs. Inherited germline variation associated with RNMSM acquisition. These variants were found in genes involved in adaptive immune function, proinflammatory cytokine production, and lymphoid lineage commitment. In addition, the presence of eight specific RNMSMs associated with blood cell traits at effect sizes comparable to Mendelian genetic mutations. Overall, we found that somatic mutations in blood are an unexpectedly common phenomenon with ancestry-specific determinants and human health consequences.

}, keywords = {Germ-Line Mutation, Hematopoiesis, Humans, Middle Aged, Mutation, Mutation, Missense, Phenotype}, issn = {2375-2548}, doi = {10.1126/sciadv.abm4945}, author = {Weinstock, Joshua S and Laurie, Cecelia A and Broome, Jai G and Taylor, Kent D and Guo, Xiuqing and Shuldiner, Alan R and O{\textquoteright}Connell, Jeffrey R and Lewis, Joshua P and Boerwinkle, Eric and Barnes, Kathleen C and Chami, Nathalie and Kenny, Eimear E and Loos, Ruth J F and Fornage, Myriam and Redline, Susan and Cade, Brian E and Gilliland, Frank D and Chen, Zhanghua and Gauderman, W James and Kumar, Rajesh and Grammer, Leslie and Schleimer, Robert P and Psaty, Bruce M and Bis, Joshua C and Brody, Jennifer A and Silverman, Edwin K and Yun, Jeong H and Qiao, Dandi and Weiss, Scott T and Lasky-Su, Jessica and DeMeo, Dawn L and Palmer, Nicholette D and Freedman, Barry I and Bowden, Donald W and Cho, Michael H and Vasan, Ramachandran S and Johnson, Andrew D and Yanek, Lisa R and Becker, Lewis C and Kardia, Sharon and He, Jiang and Kaplan, Robert and Heckbert, Susan R and Smith, Nicholas L and Wiggins, Kerri L and Arnett, Donna K and Irvin, Marguerite R and Tiwari, Hemant and Correa, Adolfo and Raffield, Laura M and Gao, Yan and de Andrade, Mariza and Rotter, Jerome I and Rich, Stephen S and Manichaikul, Ani W and Konkle, Barbara A and Johnsen, Jill M and Wheeler, Marsha M and Custer, Brian S and Duggirala, Ravindranath and Curran, Joanne E and Blangero, John and Gui, Hongsheng and Xiao, Shujie and Williams, L Keoki and Meyers, Deborah A and Li, Xingnan and Ortega, Victor and McGarvey, Stephen and Gu, C Charles and Chen, Yii-Der Ida and Lee, Wen-Jane and Shoemaker, M Benjamin and Darbar, Dawood and Roden, Dan and Albert, Christine and Kooperberg, Charles and Desai, Pinkal and Blackwell, Thomas W and Abecasis, Goncalo R and Smith, Albert V and Kang, Hyun M and Mathias, Rasika and Natarajan, Pradeep and Jaiswal, Siddhartha and Reiner, Alexander P and Bick, Alexander G} } @article {9239, title = {Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies.}, journal = {Nat Genet}, volume = {55}, year = {2023}, month = {2023 Jan}, pages = {154-164}, abstract = {

Meta-analysis of whole genome sequencing/whole exome sequencing (WGS/WES) studies provides an attractive solution to the problem of collecting large sample sizes for discovering rare variants associated with complex phenotypes. Existing rare variant meta-analysis approaches are not scalable to biobank-scale WGS data. Here we present MetaSTAAR, a powerful and resource-efficient rare variant meta-analysis framework for large-scale WGS/WES studies. MetaSTAAR accounts for relatedness and population structure, can analyze both quantitative and dichotomous traits and boosts the power of rare variant tests by incorporating multiple variant functional annotations. Through meta-analysis of four lipid traits in 30,138 ancestrally diverse samples from 14 studies of the Trans Omics for Precision Medicine (TOPMed) Program, we show that MetaSTAAR performs rare variant meta-analysis at scale and produces results comparable to using pooled data. Additionally, we identified several conditionally significant rare variant associations with lipid traits. We further demonstrate that MetaSTAAR is scalable to biobank-scale cohorts through meta-analysis of TOPMed WGS data and UK Biobank WES data of ~200,000 samples.

}, keywords = {Exome Sequencing, Genome-Wide Association Study, Lipids, Phenotype, Whole Genome Sequencing}, issn = {1546-1718}, doi = {10.1038/s41588-022-01225-6}, author = {Li, Xihao and Quick, Corbin and Zhou, Hufeng and Gaynor, Sheila M and Liu, Yaowu and Chen, Han and Selvaraj, Margaret Sunitha and Sun, Ryan and Dey, Rounak and Arnett, Donna K and Bielak, Lawrence F and Bis, Joshua C and Blangero, John and Boerwinkle, Eric and Bowden, Donald W and Brody, Jennifer A and Cade, Brian E and Correa, Adolfo and Cupples, L Adrienne and Curran, Joanne E and de Vries, Paul S and Duggirala, Ravindranath and Freedman, Barry I and G{\"o}ring, Harald H H and Guo, Xiuqing and Haessler, Jeffrey and Kalyani, Rita R and Kooperberg, Charles and Kral, Brian G and Lange, Leslie A and Manichaikul, Ani and Martin, Lisa W and McGarvey, Stephen T and Mitchell, Braxton D and Montasser, May E and Morrison, Alanna C and Naseri, Take and O{\textquoteright}Connell, Jeffrey R and Palmer, Nicholette D and Peyser, Patricia A and Psaty, Bruce M and Raffield, Laura M and Redline, Susan and Reiner, Alexander P and Reupena, Muagututi{\textquoteright}a Sefuiva and Rice, Kenneth M and Rich, Stephen S and Sitlani, Colleen M and Smith, Jennifer A and Taylor, Kent D and Vasan, Ramachandran S and Willer, Cristen J and Wilson, James G and Yanek, Lisa R and Zhao, Wei and Rotter, Jerome I and Natarajan, Pradeep and Peloso, Gina M and Li, Zilin and Lin, Xihong} } @article {9445, title = {Substitution of self-reported measures for objectively assessed grip strength and slow walk in the Physical Frailty Phenotype: ramifications for validity.}, journal = {BMC Geriatr}, volume = {23}, year = {2023}, month = {2023 Jul 22}, pages = {451}, abstract = {

BACKGROUND: Frailty assessment promises to identify older adults at risk for adverse consequences following stressors and target interventions to improve health outcomes. The Physical Frailty Phenotype (PFP) is a widely-studied, well validated assessment but incorporates performance-based slow walk and grip strength criteria that challenge its use in some clinical settings. Variants replacing performance-based elements with self-reported proxies have been proposed. Our study evaluated whether commonly available disability self-reports could be substituted for the performance-based criteria in the PFP while still identifying as "frail" the same subpopulations of individuals.

METHODS: Parallel analyses were conducted in 3393 female and 2495 male Cardiovascular Health Study, Round 2 participants assessed in 1989-90. Candidate self-reported proxies for the phenotype{\textquoteright}s "slowness" and "weakness" criteria were evaluated for comparable prevalence and agreement by mode of measurement. For best-performing candidates: Frailty status (3 + positive criteria out of 5) was compared for prevalence and agreement between the PFP and mostly self-reported versions. Personal characteristics were compared between those adjudicated as frail by (a) only a self-reported version; (b) only the PFP; (c) both, using bivariable analyses and multinomial logistic regression.

RESULTS: Self-reported difficulty walking {\textonehalf} mile was selected as a proxy for the phenotype{\textquoteright}s slowness criterion. Two self-reported weakness proxies were examined: difficulty transferring from a bed or chair or gripping with hands, and difficulty as just defined or in lifting a 10-pound bag. Prevalences matched to within 4\% between self-reported and performance-based criteria in the whole sample, but in all cases the self-reported prevalence for women exceeded that for men by 11\% or more. Cross-modal agreement was moderate, with by-criterion and frailty-wide Kappa statistics of 0.55-0.60 in all cases. Frail subgroups (a), (b), (c) were independently discriminated (p < 0.05) by race, BMI, and depression in women; by age in men; and by self-reported health for both.

CONCLUSIONS: Commonly used self-reported disability items cannot be assumed to stand in for performance-based criteria in the PFP. We found subpopulations identified as frail by resultant phenotypes versus the original phenotype to systematically differ. Work to develop self-reported proxies that more closely replicate their objective phenotypic counterparts than standard disability self-reports is needed.

}, keywords = {Advance Directives, Female, Frailty, Hand Strength, Humans, Male, Phenotype, Self Report}, issn = {1471-2318}, doi = {10.1186/s12877-023-04105-8}, author = {Bandeen-Roche, Karen and Tian, Jing and Buta, Brian and Walston, Jeremy and Xue, Qian-Li} }