@article {1303, title = {Genetic determinants of lipid traits in diverse populations from the population architecture using genomics and epidemiology (PAGE) study.}, journal = {PLoS Genet}, volume = {7}, year = {2011}, month = {2011 Jun}, pages = {e1002138}, abstract = {

For the past five years, genome-wide association studies (GWAS) have identified hundreds of common variants associated with human diseases and traits, including high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels. Approximately 95 loci associated with lipid levels have been identified primarily among populations of European ancestry. The Population Architecture using Genomics and Epidemiology (PAGE) study was established in 2008 to characterize GWAS-identified variants in diverse population-based studies. We genotyped 49 GWAS-identified SNPs associated with one or more lipid traits in at least two PAGE studies and across six racial/ethnic groups. We performed a meta-analysis testing for SNP associations with fasting HDL-C, LDL-C, and ln(TG) levels in self-identified European American (~20,000), African American (~9,000), American Indian (~6,000), Mexican American/Hispanic (~2,500), Japanese/East Asian (~690), and Pacific Islander/Native Hawaiian (~175) adults, regardless of lipid-lowering medication use. We replicated 55 of 60 (92\%) SNP associations tested in European Americans at p<0.05. Despite sufficient power, we were unable to replicate ABCA1 rs4149268 and rs1883025, CETP rs1864163, and TTC39B rs471364 previously associated with HDL-C and MAFB rs6102059 previously associated with LDL-C. Based on significance (p<0.05) and consistent direction of effect, a majority of replicated genotype-phentoype associations for HDL-C, LDL-C, and ln(TG) in European Americans generalized to African Americans (48\%, 61\%, and 57\%), American Indians (45\%, 64\%, and 77\%), and Mexican Americans/Hispanics (57\%, 56\%, and 86\%). Overall, 16 associations generalized across all three populations. For the associations that did not generalize, differences in effect sizes, allele frequencies, and linkage disequilibrium offer clues to the next generation of association studies for these traits.

}, keywords = {Adolescent, Adult, Aged, Aged, 80 and over, Continental Population Groups, Female, Gene Frequency, Genetics, Population, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Lipid Metabolism, Lipoproteins, HDL, Lipoproteins, LDL, Male, Middle Aged, Molecular Epidemiology, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Risk Factors, Triglycerides, Young Adult}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1002138}, author = {Dumitrescu, Logan and Carty, Cara L and Taylor, Kira and Schumacher, Fredrick R and Hindorff, Lucia A and Ambite, Jos{\'e} L and Anderson, Garnet and Best, Lyle G and Brown-Gentry, Kristin and B{\r u}zkov{\'a}, Petra and Carlson, Christopher S and Cochran, Barbara and Cole, Shelley A and Devereux, Richard B and Duggan, Dave and Eaton, Charles B and Fornage, Myriam and Franceschini, Nora and Haessler, Jeff and Howard, Barbara V and Johnson, Karen C and Laston, Sandra and Kolonel, Laurence N and Lee, Elisa T and MacCluer, Jean W and Manolio, Teri A and Pendergrass, Sarah A and Quibrera, Miguel and Shohet, Ralph V and Wilkens, Lynne R and Haiman, Christopher A and Le Marchand, Lo{\"\i}c and Buyske, Steven and Kooperberg, Charles and North, Kari E and Crawford, Dana C} } @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 {6633, title = {Consistent directions of effect for established type 2 diabetes risk variants across populations: the population architecture using Genomics and Epidemiology (PAGE) Consortium.}, journal = {Diabetes}, volume = {61}, year = {2012}, month = {2012 Jun}, pages = {1642-7}, abstract = {

Common genetic risk variants for type 2 diabetes (T2D) have primarily been identified in populations of European and Asian ancestry. We tested whether the direction of association with 20 T2D risk variants generalizes across six major racial/ethnic groups in the U.S. as part of the Population Architecture using Genomics and Epidemiology Consortium (16,235 diabetes case and 46,122 control subjects of European American, African American, Hispanic, East Asian, American Indian, and Native Hawaiian ancestry). The percentage of positive (odds ratio [OR] >1 for putative risk allele) associations ranged from 69\% in American Indians to 100\% in European Americans. Of the nine variants where we observed significant heterogeneity of effect by racial/ethnic group (P(heterogeneity) < 0.05), eight were positively associated with risk (OR >1) in at least five groups. The marked directional consistency of association observed for most genetic variants across populations implies a shared functional common variant in each region. Fine-mapping of all loci will be required to reveal markers of risk that are important within and across populations.

}, keywords = {Adult, Aged, Aged, 80 and over, Alleles, Diabetes Mellitus, Type 2, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Male, Metagenomics, Middle Aged, Population Groups, Risk, Risk Factors}, issn = {1939-327X}, doi = {10.2337/db11-1296}, author = {Haiman, Christopher A and Fesinmeyer, Megan D and Spencer, Kylee L and B{\r u}zkov{\'a}, Petra and Voruganti, V Saroja and Wan, Peggy and Haessler, Jeff and Franceschini, Nora and Monroe, Kristine R and Howard, Barbara V and Jackson, Rebecca D and Florez, Jose C and Kolonel, Laurence N and Buyske, Steven and Goodloe, Robert J and Liu, Simin and Manson, JoAnn E and Meigs, James B and Waters, Kevin and Mukamal, Kenneth J and Pendergrass, Sarah A and Shrader, Peter and Wilkens, Lynne R and Hindorff, Lucia A and Ambite, Jose Luis and North, Kari E and Peters, Ulrike and Crawford, Dana C and Le Marchand, Lo{\"\i}c and Pankow, James S} } @article {6065, title = {Effects of smoking on the genetic risk of obesity: the population architecture using genomics and epidemiology study.}, journal = {BMC Med Genet}, volume = {14}, year = {2013}, month = {2013 Jan 11}, pages = {6}, abstract = {

BACKGROUND: Although smoking behavior is known to affect body mass index (BMI), the potential for smoking to influence genetic associations with BMI is largely unexplored.

METHODS: As part of the {\textquoteright}Population Architecture using Genomics and Epidemiology (PAGE){\textquoteright} Consortium, we investigated interaction between genetic risk factors associated with BMI and smoking for 10 single nucleotide polymorphisms (SNPs) previously identified in genome-wide association studies. We included 6 studies with a total of 56,466 subjects (16,750 African Americans (AA) and 39,716 European Americans (EA)). We assessed effect modification by testing an interaction term for each SNP and smoking (current vs. former/never) in the linear regression and by stratified analyses.

RESULTS: We did not observe strong evidence for interactions and only observed two interactions with p-values <0.1: for rs6548238/TMEM18, the risk allele (C) was associated with BMI only among AA females who were former/never smokers (β = 0.018, p = 0.002), vs. current smokers (β = 0.001, p = 0.95, p(interaction) = 0.10). For rs9939609/FTO, the A allele was more strongly associated with BMI among current smoker EA females (β = 0.017, p = 3.5 x 10(-5)), vs. former/never smokers (β = 0.006, p = 0.05, p(interaction) = 0.08).

CONCLUSIONS: These analyses provide limited evidence that smoking status may modify genetic effects of previously identified genetic risk factors for BMI. Larger studies are needed to follow up our results.

CLINICAL TRIAL REGISTRATION: NCT00000611.

}, keywords = {Adolescent, Adult, African Americans, Aged, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Body Mass Index, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Humans, Male, Membrane Proteins, Middle Aged, Obesity, Polymorphism, Single Nucleotide, Proteins, Risk Factors, Smoking, Young Adult}, issn = {1471-2350}, doi = {10.1186/1471-2350-14-6}, author = {Fesinmeyer, Megan D and North, Kari E and Lim, Unhee and B{\r u}zkov{\'a}, Petra and Crawford, Dana C and Haessler, Jeffrey and Gross, Myron D and Fowke, Jay H and Goodloe, Robert and Love, Shelley-Ann and Graff, Misa and Carlson, Christopher S and Kuller, Lewis H and Matise, Tara C and Hong, Ching-Ping and Henderson, Brian E and Allen, Melissa and Rohde, Rebecca R and Mayo, Ping and Schnetz-Boutaud, Nathalie and Monroe, Kristine R and Ritchie, Marylyn D and Prentice, Ross L and Kolonel, Lawrence N and Manson, JoAnn E and Pankow, James and Hindorff, Lucia A and Franceschini, Nora and Wilkens, Lynne R and Haiman, Christopher A and Le Marchand, Lo{\"\i}c and Peters, Ulrike} } @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 {6290, title = {Genetic variants associated with fasting glucose and insulin concentrations in an ethnically diverse population: results from the Population Architecture using Genomics and Epidemiology (PAGE) study.}, journal = {BMC Med Genet}, volume = {14}, year = {2013}, month = {2013 Sep 25}, pages = {98}, abstract = {

BACKGROUND: Multiple genome-wide association studies (GWAS) within European populations have implicated common genetic variants associated with insulin and glucose concentrations. In contrast, few studies have been conducted within minority groups, which carry the highest burden of impaired glucose homeostasis and type 2 diabetes in the U.S.

METHODS: As part of the {\textquoteright}Population Architecture using Genomics and Epidemiology (PAGE) Consortium, we investigated the association of up to 10 GWAS-identified single nucleotide polymorphisms (SNPs) in 8 genetic regions with glucose or insulin concentrations in up to 36,579 non-diabetic subjects including 23,323 European Americans (EA) and 7,526 African Americans (AA), 3,140 Hispanics, 1,779 American Indians (AI), and 811 Asians. We estimated the association between each SNP and fasting glucose or log-transformed fasting insulin, followed by meta-analysis to combine results across PAGE sites.

RESULTS: Overall, our results show that 9/9 GWAS SNPs are associated with glucose in EA (p = 0.04 to 9 {\texttimes} 10-15), versus 3/9 in AA (p= 0.03 to 6 {\texttimes} 10-5), 3/4 SNPs in Hispanics, 2/4 SNPs in AI, and 1/2 SNPs in Asians. For insulin we observed a significant association with rs780094/GCKR in EA, Hispanics and AI only.

CONCLUSIONS: Generalization of results across multiple racial/ethnic groups helps confirm the relevance of some of these loci for glucose and insulin metabolism. Lack of association in non-EA groups may be due to insufficient power, or to unique patterns of linkage disequilibrium.

}, keywords = {Adaptor Proteins, Signal Transducing, Adult, African Americans, Aged, Alleles, Asian Continental Ancestry Group, Blood Glucose, Diabetes Mellitus, Type 2, European Continental Ancestry Group, Female, Gene Frequency, Genetic Loci, Genome-Wide Association Study, Genomics, Hispanic Americans, Humans, Indians, North American, Insulin, Male, Middle Aged, Polymorphism, Single Nucleotide, Transcription Factor 7-Like 2 Protein}, issn = {1471-2350}, doi = {10.1186/1471-2350-14-98}, author = {Fesinmeyer, Megan D and Meigs, James B and North, Kari E and Schumacher, Fredrick R and B{\r u}zkov{\'a}, Petra and Franceschini, Nora and Haessler, Jeffrey and Goodloe, Robert and Spencer, Kylee L and Voruganti, Venkata Saroja and Howard, Barbara V and Jackson, Rebecca and Kolonel, Laurence N and Liu, Simin and Manson, JoAnn E and Monroe, Kristine R and Mukamal, Kenneth and Dilks, Holli H and Pendergrass, Sarah A and Nato, Andrew and Wan, Peggy and Wilkens, Lynne R and Le Marchand, Lo{\"\i}c and Ambite, Jose Luis and Buyske, Steven and Florez, Jose C and Crawford, Dana C and Hindorff, Lucia A and Haiman, Christopher A and Peters, Ulrike and Pankow, James S} } @article {6630, title = {The influence of obesity-related single nucleotide polymorphisms on BMI across the life course: the PAGE study.}, journal = {Diabetes}, volume = {62}, year = {2013}, month = {2013 May}, pages = {1763-7}, abstract = {

Evidence is limited as to whether heritable risk of obesity varies throughout adulthood. Among >34,000 European Americans, aged 18-100 years, from multiple U.S. studies in the Population Architecture using Genomics and Epidemiology (PAGE) Consortium, we examined evidence for heterogeneity in the associations of five established obesity risk variants (near FTO, GNPDA2, MTCH2, TMEM18, and NEGR1) with BMI across four distinct epochs of adulthood: 1) young adulthood (ages 18-25 years), adulthood (ages 26-49 years), middle-age adulthood (ages 50-69 years), and older adulthood (ages >=70 years); or 2) by menopausal status in women and stratification by age 50 years in men. Summary-effect estimates from each meta-analysis were compared for heterogeneity across the life epochs. We found heterogeneity in the association of the FTO (rs8050136) variant with BMI across the four adulthood epochs (P = 0.0006), with larger effects in young adults relative to older adults (β [SE] = 1.17 [0.45] vs. 0.09 [0.09] kg/m{\texttwosuperior}, respectively, per A allele) and smaller intermediate effects. We found no evidence for heterogeneity in the association of GNPDA2, MTCH2, TMEM18, and NEGR1 with BMI across adulthood. Genetic predisposition to obesity may have greater effects on body weight in young compared with older adulthood for FTO, suggesting changes by age, generation, or secular trends. Future research should compare and contrast our findings with results using longitudinal data.

}, keywords = {Adolescent, Adult, Aged, Aged, 80 and over, Aging, Body Mass Index, Cohort Studies, Cross-Sectional Studies, European Continental Ancestry Group, Female, Genetic Association Studies, Health Surveys, Humans, Male, Middle Aged, Obesity, Polymorphism, Single Nucleotide, Proteins, United States, Young Adult}, issn = {1939-327X}, doi = {10.2337/db12-0863}, author = {Graff, Mariaelisa and Gordon-Larsen, Penny and Lim, Unhee and Fowke, Jay H and Love, Shelly-Ann and Fesinmeyer, Megan and Wilkens, Lynne R and Vertilus, Shawyntee and Ritchie, Marilyn D and Prentice, Ross L and Pankow, Jim and Monroe, Kristine and Manson, JoAnn E and Le Marchand, Lo{\"\i}c and Kuller, Lewis H and Kolonel, Laurence N and Hong, Ching P and Henderson, Brian E and Haessler, Jeff and Gross, Myron D and Goodloe, Robert and Franceschini, Nora and Carlson, Christopher S and Buyske, Steven and B{\r u}zkov{\'a}, Petra and Hindorff, Lucia A and Matise, Tara C and Crawford, Dana C and Haiman, Christopher A and Peters, Ulrike and North, Kari E} } @article {6627, title = {Investigation of gene-by-sex interactions for lipid traits in diverse populations from the population architecture using genomics and epidemiology study.}, journal = {BMC Genet}, volume = {14}, year = {2013}, month = {2013}, pages = {33}, abstract = {

BACKGROUND: High-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels are influenced by both genes and the environment. Genome-wide association studies (GWAS) have identified ~100 common genetic variants associated with HDL-C, LDL-C, and/or TG levels, mostly in populations of European descent, but little is known about the modifiers of these associations. Here, we investigated whether GWAS-identified SNPs for lipid traits exhibited heterogeneity by sex in the Population Architecture using Genomics and Epidemiology (PAGE) study.

RESULTS: A sex-stratified meta-analysis was performed for 49 GWAS-identified SNPs for fasting HDL-C, LDL-C, and ln(TG) levels among adults self-identified as European American (25,013). Heterogeneity by sex was established when phet < 0.001. There was evidence for heterogeneity by sex for two SNPs for ln(TG) in the APOA1/C3/A4/A5/BUD13 gene cluster: rs28927680 (p(het) = 7.4 x 10(-7)) and rs3135506 (p(het) = 4.3 x 10(-4)one SNP in PLTP for HDL levels (rs7679; p(het) = 9.9 x 10(-4)), and one in HMGCR for LDL levels (rs12654264; p(het) = 3.1 x 10(-5)). We replicated heterogeneity by sex in five of seventeen loci previously reported by genome-wide studies (binomial p = 0.0009). We also present results for other racial/ethnic groups in the supplementary materials, to provide a resource for future meta-analyses.

CONCLUSIONS: We provide further evidence for sex-specific effects of SNPs in the APOA1/C3/A4/A5/BUD13 gene cluster, PLTP, and HMGCR on fasting triglyceride levels in European Americans from the PAGE study. Our findings emphasize the need for considering context-specific effects when interpreting genetic associations emerging from GWAS, and also highlight the difficulties in replicating interaction effects across studies and across racial/ethnic groups.

}, keywords = {Female, Genetic Heterogeneity, Genome, Human, Genome-Wide Association Study, Humans, Lipids, Male, Polymorphism, Single Nucleotide, Population Groups}, issn = {1471-2156}, doi = {10.1186/1471-2156-14-33}, author = {Taylor, Kira C and Carty, Cara L and Dumitrescu, Logan and B{\r u}zkov{\'a}, Petra and Cole, Shelley A and Hindorff, Lucia and Schumacher, Fred R and Wilkens, Lynne R and Shohet, Ralph V and Quibrera, P Miguel and Johnson, Karen C and Henderson, Brian E and Haessler, Jeff and Franceschini, Nora and Eaton, Charles B and Duggan, David J and Cochran, Barbara and Cheng, Iona and Carlson, Chris S and Brown-Gentry, Kristin and Anderson, Garnet and Ambite, Jose Luis and Haiman, Christopher and Le Marchand, Lo{\"\i}c and Kooperberg, Charles and Crawford, Dana C and Buyske, Steven and North, Kari E and Fornage, Myriam} } @article {6292, title = {No evidence of interaction between known lipid-associated genetic variants and smoking in the multi-ethnic PAGE population.}, journal = {Hum Genet}, volume = {132}, year = {2013}, month = {2013 Dec}, pages = {1427-31}, abstract = {

Genome-wide association studies (GWAS) have identified many variants that influence high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and/or triglycerides. However, environmental modifiers, such as smoking, of these known genotype-phenotype associations are just recently emerging in the literature. We have tested for interactions between smoking and 49 GWAS-identified variants in over 41,000 racially/ethnically diverse samples with lipid levels from the Population Architecture Using Genomics and Epidemiology (PAGE) study. Despite their biological plausibility, we were unable to detect significant SNP {\texttimes} smoking interactions.

}, keywords = {Cholesterol, HDL, Cholesterol, LDL, Cohort Studies, Ethnic Groups, Female, Gene Frequency, Gene-Environment Interaction, Genetics, Population, Genome-Wide Association Study, Humans, Lipid Metabolism, Male, Polymorphism, Single Nucleotide, Prevalence, Smoking, Triglycerides, Young Adult}, issn = {1432-1203}, doi = {10.1007/s00439-013-1375-3}, author = {Dumitrescu, Logan and Carty, Cara L and Franceschini, Nora and Hindorff, Lucia A and Cole, Shelley A and B{\r u}zkov{\'a}, Petra and Schumacher, Fredrick R and Eaton, Charles B and Goodloe, Robert J and Duggan, David J and Haessler, Jeff and Cochran, Barbara and Henderson, Brian E and Cheng, Iona and Johnson, Karen C and Carlson, Chris S and Love, Shelly-Anne and Brown-Gentry, Kristin and Nato, Alejandro Q and Quibrera, Miguel and Shohet, Ralph V and Ambite, Jose Luis and Wilkens, Lynne R and Le Marchand, Lo{\"\i}c and Haiman, Christopher A and Buyske, Steven and Kooperberg, Charles and North, Kari E and Fornage, Myriam and Crawford, Dana C} } @article {6111, title = {Post-genome-wide association study challenges for lipid traits: describing age as a modifier of gene-lipid associations in the Population Architecture using Genomics and Epidemiology (PAGE) study.}, journal = {Ann Hum Genet}, volume = {77}, year = {2013}, month = {2013 Sep}, pages = {416-25}, abstract = {

Numerous common genetic variants that influence plasma high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-C), and triglyceride distributions have been identified via genome-wide association studies (GWAS). However, whether or not these associations are age-dependent has largely been overlooked. We conducted an association study and meta-analysis in more than 22,000 European Americans between 49 previously identified GWAS variants and the three lipid traits, stratified by age (males: <50 or >=50 years of age; females: pre- or postmenopausal). For each variant, a test of heterogeneity was performed between the two age strata and significant Phet values were used as evidence of age-specific genetic effects. We identified seven associations in females and eight in males that displayed suggestive heterogeneity by age (Phet < 0.05). The association between rs174547 (FADS1) and LDL-C in males displayed the most evidence for heterogeneity between age groups (Phet = 1.74E-03, I(2) = 89.8), with a significant association in older males (P = 1.39E-06) but not younger males (P = 0.99). However, none of the suggestive modifying effects survived adjustment for multiple testing, highlighting the challenges of identifying modifiers of modest SNP-trait associations despite large sample sizes.

}, keywords = {Adult, Aged, European Continental Ancestry Group, Female, Genetic Association Studies, Genome-Wide Association Study, Humans, Lipids, Male, Middle Aged, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Quantitative Trait, Heritable, Risk Factors}, issn = {1469-1809}, doi = {10.1111/ahg.12027}, author = {Dumitrescu, Logan and Carty, Cara L and Franceschini, Nora and Hindorff, Lucia A and Cole, Shelley A and B{\r u}zkov{\'a}, Petra and Schumacher, Fredrick R and Eaton, Charles B and Goodloe, Robert J and Duggan, David J and Haessler, Jeff and Cochran, Barbara and Henderson, Brian E and Cheng, Iona and Johnson, Karen C and Carlson, Chris S and Love, Shelly-Ann and Brown-Gentry, Kristin and Nato, Alejandro Q and Quibrera, Miguel and Anderson, Garnet and Shohet, Ralph V and Ambite, Jose Luis and Wilkens, Lynne R and Marchand, Loic Le and Haiman, Christopher A and Buyske, Steven and Kooperberg, Charles and North, Kari E and Fornage, Myriam and Crawford, Dana C} } @article {6360, title = {Multiancestral analysis of inflammation-related genetic variants and C-reactive protein in the population architecture using genomics and epidemiology study.}, journal = {Circ Cardiovasc Genet}, volume = {7}, year = {2014}, month = {2014 Apr}, pages = {178-88}, abstract = {

BACKGROUND: C-reactive protein (CRP) is a biomarker of inflammation. Genome-wide association studies (GWAS) have identified single-nucleotide polymorphisms (SNPs) associated with CRP concentrations and inflammation-related traits such as cardiovascular disease, type 2 diabetes mellitus, and obesity. We aimed to replicate previous CRP-SNP associations, assess whether these associations generalize to additional race/ethnicity groups, and evaluate inflammation-related SNPs for a potentially pleiotropic association with CRP.

METHODS AND RESULTS: We selected and analyzed 16 CRP-associated and 250 inflammation-related GWAS SNPs among 40 473 African American, American Indian, Asian/Pacific Islander, European American, and Hispanic participants from 7 studies collaborating in the Population Architecture using Genomics and Epidemiology (PAGE) study. Fixed-effect meta-analyses combined study-specific race/ethnicity-stratified linear regression estimates to evaluate the association between each SNP and high-sensitivity CRP. Overall, 18 SNPs in 8 loci were significantly associated with CRP (Bonferroni-corrected P<3.1{\texttimes}10(-3) for replication, P<2.0{\texttimes}10(-4) for pleiotropy): Seven of these were specific to European Americans, while 9 additionally generalized to African Americans (1), Hispanics (5), or both (3); 1 SNP was seen only in African Americans and Hispanics. Two SNPs in the CELSR2/PSRC1/SORT1 locus showed a potentially novel association with CRP: rs599839 (P=2.0{\texttimes}10(-6)) and rs646776 (P=3.1{\texttimes}10(-5)).

CONCLUSIONS: We replicated 16 SNP-CRP associations, 10 of which generalized to African Americans and/or Hispanics. We also identified potentially novel pleiotropic associations with CRP for two SNPs previously associated with coronary artery disease and/or low-density lipoprotein-cholesterol. These findings demonstrate the benefit of evaluating genotype-phenotype associations in multiple race/ethnicity groups and looking for pleiotropic relationships among SNPs previously associated with related phenotypes.

}, keywords = {Adult, African Continental Ancestry Group, Aged, Asian Continental Ancestry Group, C-Reactive Protein, Female, Genetic Variation, Genome-Wide Association Study, Hispanic Americans, Humans, Indians, North American, Inflammation, Male, Middle Aged, Polymorphism, Single Nucleotide, United States, Young Adult}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.113.000173}, author = {Kocarnik, Jonathan M and Pendergrass, Sarah A and Carty, Cara L and Pankow, James S and Schumacher, Fredrick R and Cheng, Iona and Durda, Peter and Ambite, Jose Luis and Deelman, Ewa and Cook, Nancy R and Liu, Simin and Wactawski-Wende, Jean and Hutter, Carolyn and Brown-Gentry, Kristin and Wilson, Sarah and Best, Lyle G and Pankratz, Nathan and Hong, Ching-Ping and Cole, Shelley A and Voruganti, V Saroja and B{\r u}zkov{\'a}, Petra and Jorgensen, Neal W and Jenny, Nancy S and Wilkens, Lynne R and Haiman, Christopher A and Kolonel, Laurence N and LaCroix, Andrea and North, Kari and Jackson, Rebecca and Le Marchand, Lo{\"\i}c and Hindorff, Lucia A and Crawford, Dana C and Gross, Myron and Peters, Ulrike} } @article {9176, title = {Large-scale genome-wide association study of coronary artery disease in genetically diverse populations.}, journal = {Nat Med}, volume = {28}, year = {2022}, month = {2022 08}, pages = {1679-1692}, abstract = {

We report a genome-wide association study (GWAS) of coronary artery disease (CAD) incorporating nearly a quarter of a million cases, in which existing studies are integrated with data from cohorts of white, Black and Hispanic individuals from the Million Veteran Program. We document near equivalent heritability of CAD across multiple ancestral groups, identify 95 novel loci, including nine on the X chromosome, detect eight loci of genome-wide significance in Black and Hispanic individuals, and demonstrate that two common haplotypes at the 9p21 locus are responsible for risk stratification in all populations except those of African origin, in which these haplotypes are virtually absent. Moreover, in the largest GWAS for angiographically derived coronary atherosclerosis performed to date, we find 15 loci of genome-wide significance that robustly overlap with established loci for clinical CAD. Phenome-wide association analyses of novel loci and polygenic risk scores (PRSs) augment signals related to insulin resistance, extend pleiotropic associations of these loci to include smoking and family history, and precisely document the markedly reduced transferability of existing PRSs to Black individuals. Downstream integrative analyses reinforce the critical roles of vascular endothelial, fibroblast, and smooth muscle cells in CAD susceptibility, but also point to a shared biology between atherosclerosis and oncogenesis. This study highlights the value of diverse populations in further characterizing the genetic architecture of CAD.

}, keywords = {Coronary Artery Disease, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Risk Factors}, issn = {1546-170X}, doi = {10.1038/s41591-022-01891-3}, author = {Tcheandjieu, Catherine and Zhu, Xiang and Hilliard, Austin T and Clarke, Shoa L and Napolioni, Valerio and Ma, Shining and Lee, Kyung Min and Fang, Huaying and Chen, Fei and Lu, Yingchang and Tsao, Noah L and Raghavan, Sridharan and Koyama, Satoshi and Gorman, Bryan R and Vujkovic, Marijana and Klarin, Derek and Levin, Michael G and Sinnott-Armstrong, Nasa and Wojcik, Genevieve L and Plomondon, Mary E and Maddox, Thomas M and Waldo, Stephen W and Bick, Alexander G and Pyarajan, Saiju and Huang, Jie and Song, Rebecca and Ho, Yuk-Lam and Buyske, Steven and Kooperberg, Charles and Haessler, Jeffrey and Loos, Ruth J F and Do, Ron and Verbanck, Marie and Chaudhary, Kumardeep and North, Kari E and Avery, Christy L and Graff, Mariaelisa and Haiman, Christopher A and Le Marchand, Lo{\"\i}c and Wilkens, Lynne R and Bis, Joshua C and Leonard, Hampton and Shen, Botong and Lange, Leslie A and Giri, Ayush and Dikilitas, Ozan and Kullo, Iftikhar J and Stanaway, Ian B and Jarvik, Gail P and Gordon, Adam S and Hebbring, Scott and Namjou, Bahram and Kaufman, Kenneth M and Ito, Kaoru and Ishigaki, Kazuyoshi and Kamatani, Yoichiro and Verma, Shefali S and Ritchie, Marylyn D and Kember, Rachel L and Baras, Aris and Lotta, Luca A and Kathiresan, Sekar and Hauser, Elizabeth R and Miller, Donald R and Lee, Jennifer S and Saleheen, Danish and Reaven, Peter D and Cho, Kelly and Gaziano, J Michael and Natarajan, Pradeep and Huffman, Jennifer E and Voight, Benjamin F and Rader, Daniel J and Chang, Kyong-Mi and Lynch, Julie A and Damrauer, Scott M and Wilson, Peter W F and Tang, Hua and Sun, Yan V and Tsao, Philip S and O{\textquoteright}Donnell, Christopher J and Assimes, Themistocles L} } @article {9484, title = {WHOLE GENOME SEQUENCING ANALYSIS OF BODY MASS INDEX IDENTIFIES NOVEL AFRICAN ANCESTRY-SPECIFIC RISK ALLELE.}, journal = {medRxiv}, year = {2023}, month = {2023 Aug 22}, abstract = {

Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51\% were of non-European population groups. We discovered 18 BMI-associated signals ( < 5 {\texttimes} 10 ). Notably, we identified and replicated a novel low frequency single nucleotide polymorphism (SNP) in that was common in individuals of African descent. Using a diverse study population, we further identified two novel secondary signals in known BMI loci and pinpointed two likely causal variants in the and loci. Our work demonstrates the benefits of combining WGS and diverse cohorts in expanding current catalog of variants and genes confer risk for obesity, bringing us one step closer to personalized medicine.

}, doi = {10.1101/2023.08.21.23293271}, author = {Zhang, Xinruo and Brody, Jennifer A and Graff, Mariaelisa and Highland, Heather M and Chami, Nathalie and Xu, Hanfei and Wang, Zhe and Ferrier, Kendra and Chittoor, Geetha and Josyula, Navya S and Li, Xihao and Li, Zilin and Allison, Matthew A and Becker, Diane M and Bielak, Lawrence F and Bis, Joshua C and Boorgula, Meher Preethi and Bowden, Donald W and Broome, Jai G and Buth, Erin J and Carlson, Christopher S and Chang, Kyong-Mi and Chavan, Sameer and Chiu, Yen-Feng and Chuang, Lee-Ming and Conomos, Matthew P and DeMeo, Dawn L and Du, Margaret and Duggirala, Ravindranath and Eng, Celeste and Fohner, Alison E and Freedman, Barry I and Garrett, Melanie E and Guo, Xiuqing and Haiman, Chris and Heavner, Benjamin D and Hidalgo, Bertha and Hixson, James E and Ho, Yuk-Lam and Hobbs, Brian D and Hu, Donglei and Hui, Qin and Hwu, Chii-Min and Jackson, Rebecca D and Jain, Deepti and Kalyani, Rita R and Kardia, Sharon L R and Kelly, Tanika N and Lange, Ethan M and LeNoir, Michael and Li, Changwei and Marchand, Loic Le and McDonald, Merry-Lynn N and McHugh, Caitlin P and Morrison, Alanna C and Naseri, Take and O{\textquoteright}Connell, Jeffrey and O{\textquoteright}Donnell, Christopher J and Palmer, Nicholette D and Pankow, James S and Perry, James A and Peters, Ulrike and Preuss, Michael H and Rao, D C and Regan, Elizabeth A and Reupena, Sefuiva M and Roden, Dan M and Rodriguez-Santana, Jose and Sitlani, Colleen M and Smith, Jennifer A and Tiwari, Hemant K and Vasan, Ramachandran S and Wang, Zeyuan and Weeks, Daniel E and Wessel, Jennifer and Wiggins, Kerri L and Wilkens, Lynne R and Wilson, Peter W F and Yanek, Lisa R and Yoneda, Zachary T and Zhao, Wei and Z{\"o}llner, Sebastian and Arnett, Donna K and Ashley-Koch, Allison E and Barnes, Kathleen C and Blangero, John and Boerwinkle, Eric and Burchard, Esteban G and Carson, April P and Chasman, Daniel I and Chen, Yii-Der Ida and Curran, Joanne E and Fornage, Myriam and Gordeuk, Victor R and He, Jiang and Heckbert, Susan R and Hou, Lifang and Irvin, Marguerite R and Kooperberg, Charles and Minster, Ryan L and Mitchell, Braxton D and Nouraie, Mehdi and Psaty, Bruce M and Raffield, Laura M and Reiner, Alexander P and Rich, Stephen S and Rotter, Jerome I and Shoemaker, M Benjamin and Smith, Nicholas L and Taylor, Kent D and Telen, Marilyn J and Weiss, Scott T and Zhang, Yingze and Costa, Nancy Heard- and Sun, Yan V and Lin, Xihong and Cupples, L Adrienne and Lange, Leslie A and Liu, Ching-Ti and Loos, Ruth J F and North, Kari E and Justice, Anne E} } @article {9942, title = {Whole genome sequencing analysis of body mass index identifies novel African ancestry-specific risk allele.}, journal = {Nat Commun}, volume = {16}, year = {2025}, month = {2025 Apr 11}, pages = {3470}, abstract = {

Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51\% were of non-European population groups. We discovered 18 BMI-associated signals (P < 5 {\texttimes} 10), including two secondary signals. Notably, we identified and replicated a novel low-frequency single nucleotide polymorphism (SNP) in MTMR3 that was common in individuals of African descent. Using a diverse study population, we further identified two novel secondary signals in known BMI loci and pinpointed two likely causal variants in the POC5 and DMD loci. Our work demonstrates the benefits of combining WGS and diverse cohorts in expanding current catalog of variants and genes confer risk for obesity, bringing us one step closer to personalized medicine.

}, keywords = {Adult, African People, Alleles, Body Mass Index, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Middle Aged, Obesity, Polymorphism, Single Nucleotide, Population Groups, Whole Genome Sequencing}, issn = {2041-1723}, doi = {10.1038/s41467-025-58420-2}, author = {Zhang, Xinruo and Brody, Jennifer A and Graff, Mariaelisa and Highland, Heather M and Chami, Nathalie and Xu, Hanfei and Wang, Zhe and Ferrier, Kendra R and Chittoor, Geetha and Josyula, Navya Shilpa and Meyer, Mariah and Gupta, Shreyash and Li, Xihao and Li, Zilin and Allison, Matthew A and Becker, Diane M and Bielak, Lawrence F and Bis, Joshua C and Boorgula, Meher Preethi and Bowden, Donald W and Broome, Jai G and Buth, Erin J and Carlson, Christopher S and Chang, Kyong-Mi and Chavan, Sameer and Chiu, Yen-Feng and Chuang, Lee-Ming and Conomos, Matthew P and DeMeo, Dawn L and Du, Mengmeng and Duggirala, Ravindranath and Eng, Celeste and Fohner, Alison E and Freedman, Barry I and Garrett, Melanie E and Guo, Xiuqing and Haiman, Chris and Heavner, Benjamin D and Hidalgo, Bertha and Hixson, James E and Ho, Yuk-Lam and Hobbs, Brian D and Hu, Donglei and Hui, Qin and Hwu, Chii-Min and Jackson, Rebecca D and Jain, Deepti and Kalyani, Rita R and Kardia, Sharon L R and Kelly, Tanika N and Lange, Ethan M and LeNoir, Michael and Li, Changwei and Le Marchand, Lo{\"\i}c and McDonald, Merry-Lynn N and McHugh, Caitlin P and Morrison, Alanna C and Naseri, Take and O{\textquoteright}Connell, Jeffrey and O{\textquoteright}Donnell, Christopher J and Palmer, Nicholette D and Pankow, James S and Perry, James A and Peters, Ulrike and Preuss, Michael H and Rao, D C and Regan, Elizabeth A and Reupena, Sefuiva M and Roden, Dan M and Rodriguez-Santana, Jose and Sitlani, Colleen M and Smith, Jennifer A and Tiwari, Hemant K and Vasan, Ramachandran S and Wang, Zeyuan and Weeks, Daniel E and Wessel, Jennifer and Wiggins, Kerri L and Wilkens, Lynne R and Wilson, Peter W F and Yanek, Lisa R and Yoneda, Zachary T and Zhao, Wei and Z{\"o}llner, Sebastian and Arnett, Donna K and Ashley-Koch, Allison E and Barnes, Kathleen C and Blangero, John and Boerwinkle, Eric and Burchard, Esteban G and Carson, April P and Chasman, Daniel I and Ida Chen, Yii-Der and Curran, Joanne E and Fornage, Myriam and Gordeuk, Victor R and He, Jiang and Heckbert, Susan R and Hou, Lifang and Irvin, Marguerite R and Kooperberg, Charles and Minster, Ryan L and Mitchell, Braxton D and Nouraie, Mehdi and Psaty, Bruce M and Raffield, Laura M and Reiner, Alexander P and Rich, Stephen S and Rotter, Jerome I and Benjamin Shoemaker, M and Smith, Nicholas L and Taylor, Kent D and Telen, Marilyn J and Weiss, Scott T and Zhang, Yingze and Heard-Costa, Nancy and Sun, Yan V and Lin, Xihong and Cupples, L Adrienne and Lange, Leslie A and Liu, Ching-Ti and Loos, Ruth J F and North, Kari E and Justice, Anne E} }