@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 {1107, title = {NRXN3 is a novel locus for waist circumference: a genome-wide association study from the CHARGE Consortium.}, journal = {PLoS Genet}, volume = {5}, year = {2009}, month = {2009 Jun}, pages = {e1000539}, abstract = {

Central abdominal fat is a strong risk factor for diabetes and cardiovascular disease. To identify common variants influencing central abdominal fat, we conducted a two-stage genome-wide association analysis for waist circumference (WC). In total, three loci reached genome-wide significance. In stage 1, 31,373 individuals of Caucasian descent from eight cohort studies confirmed the role of FTO and MC4R and identified one novel locus associated with WC in the neurexin 3 gene [NRXN3 (rs10146997, p = 6.4x10(-7))]. The association with NRXN3 was confirmed in stage 2 by combining stage 1 results with those from 38,641 participants in the GIANT consortium (p = 0.009 in GIANT only, p = 5.3x10(-8) for combined analysis, n = 70,014). Mean WC increase per copy of the G allele was 0.0498 z-score units (0.65 cm). This SNP was also associated with body mass index (BMI) [p = 7.4x10(-6), 0.024 z-score units (0.10 kg/m(2)) per copy of the G allele] and the risk of obesity (odds ratio 1.13, 95\% CI 1.07-1.19; p = 3.2x10(-5) per copy of the G allele). The NRXN3 gene has been previously implicated in addiction and reward behavior, lending further evidence that common forms of obesity may be a central nervous system-mediated disorder. Our findings establish that common variants in NRXN3 are associated with WC, BMI, and obesity.

}, keywords = {Aged, Body Mass Index, Cohort Studies, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Middle Aged, Nerve Tissue Proteins, Obesity, Polymorphism, Single Nucleotide, Waist Circumference}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1000539}, author = {Heard-Costa, Nancy L and Zillikens, M Carola and Monda, Keri L and Johansson, Asa and Harris, Tamara B and Fu, Mao and Haritunians, Talin and Feitosa, Mary F and Aspelund, Thor and Eiriksdottir, Gudny and Garcia, Melissa and Launer, Lenore J and Smith, Albert V and Mitchell, Braxton D and McArdle, Patrick F and Shuldiner, Alan R and Bielinski, Suzette J and Boerwinkle, Eric and Brancati, Fred and Demerath, Ellen W and Pankow, James S and Arnold, Alice M and Chen, Yii-Der Ida and Glazer, Nicole L and McKnight, Barbara and Psaty, Bruce M and Rotter, Jerome I and Amin, Najaf and Campbell, Harry and Gyllensten, Ulf and Pattaro, Cristian and Pramstaller, Peter P and Rudan, Igor and Struchalin, Maksim and Vitart, Veronique and Gao, Xiaoyi and Kraja, Aldi and Province, Michael A and Zhang, Qunyuan and Atwood, Larry D and Dupuis, Jos{\'e}e and Hirschhorn, Joel N and Jaquish, Cashell E and O{\textquoteright}Donnell, Christopher J and Vasan, Ramachandran S and White, Charles C and Aulchenko, Yurii S and Estrada, Karol and Hofman, Albert and Rivadeneira, Fernando and Uitterlinden, Andr{\'e} G and Witteman, Jacqueline C M and Oostra, Ben A and Kaplan, Robert C and Gudnason, Vilmundur and O{\textquoteright}Connell, Jeffrey R and Borecki, Ingrid B and van Duijn, Cornelia M and Cupples, L Adrienne and Fox, Caroline S and North, Kari E} } @article {1197, title = {Association of genome-wide variation with the risk of incident heart failure in adults of European and African ancestry: a prospective meta-analysis from the cohorts for heart and aging research in genomic epidemiology (CHARGE) consortium.}, journal = {Circ Cardiovasc Genet}, volume = {3}, year = {2010}, month = {2010 Jun}, pages = {256-66}, abstract = {

BACKGROUND: Although genetic factors contribute to the onset of heart failure (HF), no large-scale genome-wide investigation of HF risk has been published to date. We have investigated the association of 2,478,304 single-nucleotide polymorphisms with incident HF by meta-analyzing data from 4 community-based prospective cohorts: the Atherosclerosis Risk in Communities Study, the Cardiovascular Health Study, the Framingham Heart Study, and the Rotterdam Study.

METHODS AND RESULTS: Eligible participants for these analyses were of European or African ancestry and free of clinical HF at baseline. Each study independently conducted genome-wide scans and imputed data to the approximately 2.5 million single-nucleotide polymorphisms in HapMap. Within each study, Cox proportional hazards regression models provided age- and sex-adjusted estimates of the association between each variant and time to incident HF. Fixed-effect meta-analyses combined results for each single-nucleotide polymorphism from the 4 cohorts to produce an overall association estimate and P value. A genome-wide significance P value threshold was set a priori at 5.0x10(-7). During a mean follow-up of 11.5 years, 2526 incident HF events (12\%) occurred in 20 926 European-ancestry participants. The meta-analysis identified a genome-wide significant locus at chromosomal position 15q22 (1.4x10(-8)), which was 58.8 kb from USP3. Among 2895 African-ancestry participants, 466 incident HF events (16\%) occurred during a mean follow-up of 13.7 years. One genome-wide significant locus was identified at 12q14 (6.7x10(-8)), which was 6.3 kb from LRIG3.

CONCLUSIONS: We identified 2 loci that were associated with incident HF and exceeded genome-wide significance. The findings merit replication in other community-based settings of incident HF.

}, keywords = {African Americans, Aged, Aged, 80 and over, Cohort Studies, Endopeptidases, European Continental Ancestry Group, Female, Genome-Wide Association Study, Heart Failure, Humans, Incidence, Male, Middle Aged, Polymorphism, Single Nucleotide, Risk, Ubiquitin-Specific Proteases}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.109.895763}, author = {Smith, Nicholas L and Felix, Janine F and Morrison, Alanna C and Demissie, Serkalem and Glazer, Nicole L and Loehr, Laura R and Cupples, L Adrienne and Dehghan, Abbas and Lumley, Thomas and Rosamond, Wayne D and Lieb, Wolfgang and Rivadeneira, Fernando and Bis, Joshua C and Folsom, Aaron R and Benjamin, Emelia and Aulchenko, Yurii S and Haritunians, Talin and Couper, David and Murabito, Joanne and Wang, Ying A and Stricker, Bruno H and Gottdiener, John S and Chang, Patricia P and Wang, Thomas J and Rice, Kenneth M and Hofman, Albert and Heckbert, Susan R and Fox, Ervin R and O{\textquoteright}Donnell, Christopher J and Uitterlinden, Andr{\'e} G and Rotter, Jerome I and Willerson, James T and Levy, Daniel and van Duijn, Cornelia M and Psaty, Bruce M and Witteman, Jacqueline C M and Boerwinkle, Eric and Vasan, Ramachandran S} } @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 {1187, title = {Genomic variation associated with mortality among adults of European and African ancestry with heart failure: the cohorts for heart and aging research in genomic epidemiology consortium.}, journal = {Circ Cardiovasc Genet}, volume = {3}, year = {2010}, month = {2010 Jun}, pages = {248-55}, abstract = {

BACKGROUND: Prognosis and survival are significant concerns for individuals with heart failure (HF). To better understand the pathophysiology of HF prognosis, the association between 2,366,858 single-nucleotide polymorphisms (SNPs) and all-cause mortality was evaluated among individuals with incident HF from 4 community-based prospective cohorts: the Atherosclerosis Risk in Communities Study, the Cardiovascular Health Study, the Framingham Heart Study, and the Rotterdam Study.

METHODS AND RESULTS: Participants were 2526 individuals of European ancestry and 466 individuals of African ancestry who experienced an incident HF event during follow-up in the respective cohorts. Within each study, the association between genetic variants and time to mortality among individuals with HF was assessed by Cox proportional hazards models that included adjustment for sex and age at the time of the HF event. Prospective fixed-effect meta-analyses were conducted for the 4 study populations of European ancestry (N=1645 deaths) and for the 2 populations of African ancestry (N=281 deaths). Genome-wide significance was set at P=5.0x10(-7). Meta-analytic findings among individuals of European ancestry revealed 1 genome-wide significant locus on chromosome 3p22 in an intron of CKLF-like MARVEL transmembrane domain containing 7 (CMTM7, P=3.2x10(-7)). Eight additional loci in individuals of European ancestry and 4 loci in individuals of African ancestry were identified by high-signal SNPs (P<1.0x10(-5)) but did not meet genome-wide significance.

CONCLUSIONS: This study identified a novel locus associated with all-cause mortality among individuals of European ancestry with HF. This finding warrants additional investigation, including replication, in other studies of HF.

}, keywords = {African Americans, Aged, Aged, 80 and over, Chemokines, Cohort Studies, European Continental Ancestry Group, Female, Genome-Wide Association Study, Genotype, Heart Failure, Humans, Introns, Male, MARVEL Domain-Containing Proteins, Membrane Proteins, Middle Aged, Polymorphism, Single Nucleotide, Risk Factors}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.109.895995}, author = {Morrison, Alanna C and Felix, Janine F and Cupples, L Adrienne and Glazer, Nicole L and Loehr, Laura R and Dehghan, Abbas and Demissie, Serkalem and Bis, Joshua C and Rosamond, Wayne D and Aulchenko, Yurii S and Wang, Ying A and Haritunians, Talin and Folsom, Aaron R and Rivadeneira, Fernando and Benjamin, Emelia J and Lumley, Thomas and Couper, David and Stricker, Bruno H and O{\textquoteright}Donnell, Christopher J and Rice, Kenneth M and Chang, Patricia P and Hofman, Albert and Levy, Daniel and Rotter, Jerome I and Fox, Ervin R and Uitterlinden, Andr{\'e} G and Wang, Thomas J and Psaty, Bruce M and Willerson, James T and van Duijn, Cornelia M and Boerwinkle, Eric and Witteman, Jacqueline C M and Vasan, Ramachandran S and Smith, Nicholas L} } @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 {1308, title = {Total zinc intake may modify the glucose-raising effect of a zinc transporter (SLC30A8) variant: a 14-cohort meta-analysis.}, journal = {Diabetes}, volume = {60}, year = {2011}, month = {2011 Sep}, pages = {2407-16}, abstract = {

OBJECTIVE: Many genetic variants have been associated with glucose homeostasis and type 2 diabetes in genome-wide association studies. Zinc is an essential micronutrient that is important for β-cell function and glucose homeostasis. We tested the hypothesis that zinc intake could influence the glucose-raising effect of specific variants.

RESEARCH DESIGN AND METHODS: We conducted a 14-cohort meta-analysis to assess the interaction of 20 genetic variants known to be related to glycemic traits and zinc metabolism with dietary zinc intake (food sources) and a 5-cohort meta-analysis to assess the interaction with total zinc intake (food sources and supplements) on fasting glucose levels among individuals of European ancestry without diabetes.

RESULTS: We observed a significant association of total zinc intake with lower fasting glucose levels (β-coefficient {\textpm} SE per 1 mg/day of zinc intake: -0.0012 {\textpm} 0.0003 mmol/L, summary P value = 0.0003), while the association of dietary zinc intake was not significant. We identified a nominally significant interaction between total zinc intake and the SLC30A8 rs11558471 variant on fasting glucose levels (β-coefficient {\textpm} SE per A allele for 1 mg/day of greater total zinc intake: -0.0017 {\textpm} 0.0006 mmol/L, summary interaction P value = 0.005); this result suggests a stronger inverse association between total zinc intake and fasting glucose in individuals carrying the glucose-raising A allele compared with individuals who do not carry it. None of the other interaction tests were statistically significant.

CONCLUSIONS: Our results suggest that higher total zinc intake may attenuate the glucose-raising effect of the rs11558471 SLC30A8 (zinc transporter) variant. Our findings also support evidence for the association of higher total zinc intake with lower fasting glucose levels.

}, keywords = {Blood Glucose, Cation Transport Proteins, Cohort Studies, Humans, Polymorphism, Single Nucleotide, Zinc, Zinc Transporter 8}, issn = {1939-327X}, doi = {10.2337/db11-0176}, author = {Kanoni, Stavroula and Nettleton, Jennifer A and Hivert, Marie-France and Ye, Zheng and van Rooij, Frank J A and Shungin, Dmitry and Sonestedt, Emily and Ngwa, Julius S and Wojczynski, Mary K and Lemaitre, Rozenn N and Gustafsson, Stefan and Anderson, Jennifer S and Tanaka, Toshiko and Hindy, George and Saylor, Georgia and Renstrom, Frida and Bennett, Amanda J and van Duijn, Cornelia M and Florez, Jose C and Fox, Caroline S and Hofman, Albert and Hoogeveen, Ron C and Houston, Denise K and Hu, Frank B and Jacques, Paul F and Johansson, Ingegerd and Lind, Lars and Liu, Yongmei and McKeown, Nicola and Ordovas, Jose and Pankow, James S and Sijbrands, Eric J G and Syv{\"a}nen, Ann-Christine and Uitterlinden, Andr{\'e} G and Yannakoulia, Mary and Zillikens, M Carola and Wareham, Nick J and Prokopenko, Inga and Bandinelli, Stefania and Forouhi, Nita G and Cupples, L Adrienne and Loos, Ruth J and Hallmans, G{\"o}ran and Dupuis, Jos{\'e}e and Langenberg, Claudia and Ferrucci, Luigi and Kritchevsky, Stephen B and McCarthy, Mark I and Ingelsson, Erik and Borecki, Ingrid B and Witteman, Jacqueline C M and Orho-Melander, Marju and Siscovick, David S and Meigs, James B and Franks, Paul W and Dedoussis, George V} } @article {1556, title = {Assessment of gene-by-sex interaction effect on bone mineral density.}, journal = {J Bone Miner Res}, volume = {27}, year = {2012}, month = {2012 Oct}, pages = {2051-64}, abstract = {

Sexual dimorphism in various bone phenotypes, including bone mineral density (BMD), is widely observed; however, the extent to which genes explain these sex differences is unclear. To identify variants with different effects by sex, we examined gene-by-sex autosomal interactions genome-wide, and performed expression quantitative trait loci (eQTL) analysis and bioinformatics network analysis. We conducted an autosomal genome-wide meta-analysis of gene-by-sex interaction on lumbar spine (LS) and femoral neck (FN) BMD in 25,353 individuals from 8 cohorts. In a second stage, we followed up the 12 top single-nucleotide polymorphisms (SNPs; p < 1 {\texttimes} 10(-5) ) in an additional set of 24,763 individuals. Gene-by-sex interaction and sex-specific effects were examined in these 12 SNPs. We detected one novel genome-wide significant interaction associated with LS-BMD at the Chr3p26.1-p25.1 locus, near the GRM7 gene (male effect = 0.02 and p = 3.0 {\texttimes} 10(-5) ; female effect = -0.007 and p = 3.3 {\texttimes} 10(-2) ), and 11 suggestive loci associated with either FN- or LS-BMD in discovery cohorts. However, there was no evidence for genome-wide significant (p < 5 {\texttimes} 10(-8) ) gene-by-sex interaction in the joint analysis of discovery and replication cohorts. Despite the large collaborative effort, no genome-wide significant evidence for gene-by-sex interaction was found to influence BMD variation in this screen of autosomal markers. If they exist, gene-by-sex interactions for BMD probably have weak effects, accounting for less than 0.08\% of the variation in these traits per implicated SNP. {\textcopyright} 2012 American Society for Bone and Mineral Research.

}, keywords = {Bone Density, Cohort Studies, Female, Genes, Genome-Wide Association Study, Humans, Male, Meta-Analysis as Topic, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Reproducibility of Results, Sex Characteristics}, issn = {1523-4681}, doi = {10.1002/jbmr.1679}, author = {Liu, Ching-Ti and Estrada, Karol and Yerges-Armstrong, Laura M and Amin, Najaf and Evangelou, Evangelos and Li, Guo and Minster, Ryan L and Carless, Melanie A and Kammerer, Candace M and Oei, Ling and Zhou, Yanhua and Alonso, Nerea and Dailiana, Zoe and Eriksson, Joel and Garc{\'\i}a-Giralt, Natalia and Giroux, Sylvie and Husted, Lise Bjerre and Khusainova, Rita I and Koromila, Theodora and Kung, Annie Waichee and Lewis, Joshua R and Masi, Laura and Mencej-Bedrac, Simona and Nogues, Xavier and Patel, Millan S and Prezelj, Janez and Richards, J Brent and Sham, Pak Chung and Spector, Timothy and Vandenput, Liesbeth and Xiao, Su-Mei and Zheng, Hou-Feng and Zhu, Kun and Balcells, Susana and Brandi, Maria Luisa and Frost, Morten and Goltzman, David and Gonz{\'a}lez-Mac{\'\i}as, Jes{\'u}s and Karlsson, Magnus and Khusnutdinova, Elza K and Kollia, Panagoula and Langdahl, Bente Lomholt and Ljunggren, Osten and Lorentzon, Mattias and Marc, Janja and Mellstr{\"o}m, Dan and Ohlsson, Claes and Olmos, Jos{\'e} M and Ralston, Stuart H and Riancho, Jos{\'e} A and Rousseau, Fran{\c c}ois and Urreizti, Roser and Van Hul, Wim and Zarrabeitia, Mar{\'\i}a T and Castano-Betancourt, Martha and Demissie, Serkalem and Grundberg, Elin and Herrera, Lizbeth and Kwan, Tony and Medina-G{\'o}mez, Carolina and Pastinen, Tomi and Sigurdsson, Gunnar and Thorleifsson, Gudmar and Vanmeurs, Joyce Bj and Blangero, John and Hofman, Albert and Liu, Yongmei and Mitchell, Braxton D and O{\textquoteright}Connell, Jeffrey R and Oostra, Ben A and Rotter, Jerome I and Stefansson, Kari and Streeten, Elizabeth A and Styrkarsdottir, Unnur and Thorsteinsdottir, Unnur and Tylavsky, Frances A and Uitterlinden, Andre and Cauley, Jane A and Harris, Tamara B and Ioannidis, John Pa and Psaty, Bruce M and Robbins, John A and Zillikens, M Carola and Vanduijn, Cornelia M and Prince, Richard L and Karasik, David and Rivadeneira, Fernando and Kiel, Douglas P and Cupples, L Adrienne and Hsu, Yi-Hsiang} } @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 {6067, title = {Best practices and joint calling of the HumanExome BeadChip: the CHARGE Consortium.}, journal = {PLoS One}, volume = {8}, year = {2013}, month = {2013}, pages = {e68095}, abstract = {

Genotyping arrays are a cost effective approach when typing previously-identified genetic polymorphisms in large numbers of samples. One limitation of genotyping arrays with rare variants (e.g., minor allele frequency [MAF] <0.01) is the difficulty that automated clustering algorithms have to accurately detect and assign genotype calls. Combining intensity data from large numbers of samples may increase the ability to accurately call the genotypes of rare variants. Approximately 62,000 ethnically diverse samples from eleven Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium cohorts were genotyped with the Illumina HumanExome BeadChip across seven genotyping centers. The raw data files for the samples were assembled into a single project for joint calling. To assess the quality of the joint calling, concordance of genotypes in a subset of individuals having both exome chip and exome sequence data was analyzed. After exclusion of low performing SNPs on the exome chip and non-overlap of SNPs derived from sequence data, genotypes of 185,119 variants (11,356 were monomorphic) were compared in 530 individuals that had whole exome sequence data. A total of 98,113,070 pairs of genotypes were tested and 99.77\% were concordant, 0.14\% had missing data, and 0.09\% were discordant. We report that joint calling allows the ability to accurately genotype rare variation using array technology when large sample sizes are available and best practices are followed. The cluster file from this experiment is available at www.chargeconsortium.com/main/exomechip.

}, keywords = {Aging, Alleles, Cluster Analysis, Cohort Studies, Continental Population Groups, Exome, Female, Gene Frequency, Genomics, Genotype, Heart, Humans, Male, Oligonucleotide Array Sequence Analysis, Polymorphism, Single Nucleotide, Sample Size, Self Report, Sequence Analysis, DNA}, issn = {1932-6203}, doi = {10.1371/journal.pone.0068095}, author = {Grove, Megan L and Yu, Bing and Cochran, Barbara J and Haritunians, Talin and Bis, Joshua C and Taylor, Kent D and Hansen, Mark and Borecki, Ingrid B and Cupples, L Adrienne and Fornage, Myriam and Gudnason, Vilmundur and Harris, Tamara B and Kathiresan, Sekar and Kraaij, Robert and Launer, Lenore J and Levy, Daniel and Liu, Yongmei and Mosley, Thomas and Peloso, Gina M and Psaty, Bruce M and Rich, Stephen S and Rivadeneira, Fernando and Siscovick, David S and Smith, Albert V and Uitterlinden, Andre and van Duijn, Cornelia M and Wilson, James G and O{\textquoteright}Donnell, Christopher J and Rotter, Jerome I and Boerwinkle, Eric} } @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 {6579, title = {Sequence variation in TMEM18 in association with body mass index: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study.}, journal = {Circ Cardiovasc Genet}, volume = {7}, year = {2014}, month = {2014 Jun}, pages = {344-9}, abstract = {

BACKGROUND: Genome-wide association studies for body mass index (BMI) previously identified a locus near TMEM18. We conducted targeted sequencing of this region to investigate the role of common, low-frequency, and rare variants influencing BMI.

METHODS AND RESULTS: We sequenced TMEM18 and regions downstream of TMEM18 on chromosome 2 in 3976 individuals of European ancestry from 3 community-based cohorts (Atherosclerosis Risk in Communities, Cardiovascular Health Study, and Framingham Heart Study), including 200 adults selected for high BMI. We examined the association between BMI and variants identified in the region from nucleotide position 586 432 to 677 539 (hg18). Rare variants (minor allele frequency, <1\%) were analyzed using a burden test and the sequence kernel association test. Results from the 3 cohort studies were meta-analyzed. We estimate that mean BMI is 0.43 kg/m(2) higher for each copy of the G allele of single-nucleotide polymorphism rs7596758 (minor allele frequency, 29\%; P=3.46{\texttimes}10(-4)) using a Bonferroni threshold of P<4.6{\texttimes}10(-4). Analyses conditional on previous genome-wide association study single-nucleotide polymorphisms associated with BMI in the region led to attenuation of this signal and uncovered another independent (r(2)<0.2), statistically significant association, rs186019316 (P=2.11{\texttimes}10(-4)). Both rs186019316 and rs7596758 or proxies are located in transcription factor binding regions. No significant association with rare variants was found in either the exons of TMEM18 or the 3{\textquoteright} genome-wide association study region.

CONCLUSIONS: Targeted sequencing around TMEM18 identified 2 novel BMI variants with possible regulatory function.

}, keywords = {Adult, Aged, Aging, Body Mass Index, Cohort Studies, Female, Genetic Association Studies, Genetic Variation, Genome-Wide Association Study, Genomics, Heart Diseases, Humans, Male, Membrane Proteins, Middle Aged, Polymorphism, Single Nucleotide, Sequence Analysis, DNA, Young Adult}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.13.000067}, author = {Liu, Ching-Ti and Young, Kristin L and Brody, Jennifer A and Olden, Matthias and Wojczynski, Mary K and Heard-Costa, Nancy and Li, Guo and Morrison, Alanna C and Muzny, Donna and Gibbs, Richard A and Reid, Jeffrey G and Shao, Yaming and Zhou, Yanhua and Boerwinkle, Eric and Heiss, Gerardo and Wagenknecht, Lynne and McKnight, Barbara and Borecki, Ingrid B and Fox, Caroline S and North, Kari E and Cupples, L Adrienne} } @article {6547, title = {Sequencing of 2 subclinical atherosclerosis candidate regions in 3669 individuals: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study.}, journal = {Circ Cardiovasc Genet}, volume = {7}, year = {2014}, month = {2014 Jun}, pages = {359-64}, abstract = {

BACKGROUND: Atherosclerosis, the precursor to coronary heart disease and stroke, is characterized by an accumulation of fatty cells in the arterial intimal-medial layers. Common carotid intima media thickness (cIMT) and plaque are subclinical atherosclerosis measures that predict cardiovascular disease events. Previously, genome-wide association studies demonstrated evidence for association with cIMT (SLC17A4) and plaque (PIK3CG).

METHODS AND RESULTS: We sequenced 120 kb around SLC17A4 (6p22.2) and 251 kb around PIK3CG (7q22.3) among 3669 European ancestry participants from the Atherosclerosis Risk in Communities (ARIC) study, Cardiovascular Health Study (CHS), and Framingham Heart Study (FHS) in Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Primary analyses focused on 438 common variants (minor allele frequency >=1\%), which were independently meta-analyzed. A 3{\textquoteright} untranslated region CCDC71L variant (rs2286149), upstream from PIK3CG, was the most significant finding in cIMT (P=0.00033) and plaque (P=0.0004) analyses. A SLC17A4 intronic variant was also associated with cIMT (P=0.008). Both were in low linkage disequilibrium with the genome-wide association study single nucleotide polymorphisms. Gene-based tests including T1 count and sequence kernel association test for rare variants (minor allele frequency <1\%) did not yield statistically significant associations. However, we observed nominal associations for rare variants in CCDC71L and SLC17A3 with cIMT and of the entire 7q22 region with plaque (P=0.05).

CONCLUSIONS: Common and rare variants in PIK3CG and SLC17A4 regions demonstrated modest association with subclinical atherosclerosis traits. Although not conclusive, these findings may help to understand the genetic architecture of regions previously implicated by genome-wide association studies and identify variants within these regions for further investigation in larger samples.

}, keywords = {Aged, Aged, 80 and over, Aging, Atherosclerosis, Class Ib Phosphatidylinositol 3-Kinase, Cohort Studies, European Continental Ancestry Group, Female, Genetic Variation, Genome-Wide Association Study, Genomics, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Sequence Analysis, DNA, Sodium-Phosphate Cotransporter Proteins, Type I}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.113.000116}, author = {Bis, Joshua C and White, Charles C and Franceschini, Nora and Brody, Jennifer and Zhang, Xiaoling and Muzny, Donna and Santibanez, Jireh and Gibbs, Richard and Liu, Xiaoming and Lin, Honghuang and Boerwinkle, Eric and Psaty, Bruce M and North, Kari E and Cupples, L Adrienne and O{\textquoteright}Donnell, Christopher J} } @article {6583, title = {Sequencing of SCN5A identifies rare and common variants associated with cardiac conduction: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium.}, journal = {Circ Cardiovasc Genet}, volume = {7}, year = {2014}, month = {2014 Jun}, pages = {365-73}, abstract = {

BACKGROUND: The cardiac sodium channel SCN5A regulates atrioventricular and ventricular conduction. Genetic variants in this gene are associated with PR and QRS intervals. We sought to characterize further the contribution of rare and common coding variation in SCN5A to cardiac conduction.

METHODS AND RESULTS: In Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study, we performed targeted exonic sequencing of SCN5A (n=3699, European ancestry individuals) and identified 4 common (minor allele frequency >1\%) and 157 rare variants. Common and rare SCN5A coding variants were examined for association with PR and QRS intervals through meta-analysis of European ancestry participants from CHARGE, National Heart, Lung, and Blood Institute{\textquoteright}s Exome Sequencing Project (n=607), and the UK10K (n=1275) and by examining Exome Sequencing Project African ancestry participants (n=972). Rare coding SCN5A variants in aggregate were associated with PR interval in European and African ancestry participants (P=1.3{\texttimes}10(-3)). Three common variants were associated with PR and QRS interval duration among European ancestry participants and one among African ancestry participants. These included 2 well-known missense variants: rs1805124 (H558R) was associated with PR and QRS shortening in European ancestry participants (P=6.25{\texttimes}10(-4) and P=5.2{\texttimes}10(-3), respectively) and rs7626962 (S1102Y) was associated with PR shortening in those of African ancestry (P=2.82{\texttimes}10(-3)). Among European ancestry participants, 2 novel synonymous variants, rs1805126 and rs6599230, were associated with cardiac conduction. Our top signal, rs1805126 was associated with PR and QRS lengthening (P=3.35{\texttimes}10(-7) and P=2.69{\texttimes}10(-4), respectively) and rs6599230 was associated with PR shortening (P=2.67{\texttimes}10(-5)).

CONCLUSIONS: By sequencing SCN5A, we identified novel common and rare coding variants associated with cardiac conduction.

}, keywords = {Adult, Aged, Aged, 80 and over, Aging, Cohort Studies, Female, Genetic Variation, Genome-Wide Association Study, Genomics, Heart Conduction System, Heart Diseases, Humans, Male, Middle Aged, NAV1.5 Voltage-Gated Sodium Channel, Polymorphism, Single Nucleotide, Sequence Analysis, DNA}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.113.000098}, author = {Magnani, Jared W and Brody, Jennifer A and Prins, Bram P and Arking, Dan E and Lin, Honghuang and Yin, Xiaoyan and Liu, Ching-Ti and Morrison, Alanna C and Zhang, Feng and Spector, Tim D and Alonso, Alvaro and Bis, Joshua C and Heckbert, Susan R and Lumley, Thomas and Sitlani, Colleen M and Cupples, L Adrienne and Lubitz, Steven A and Soliman, Elsayed Z and Pulit, Sara L and Newton-Cheh, Christopher and O{\textquoteright}Donnell, Christopher J and Ellinor, Patrick T and Benjamin, Emelia J and Muzny, Donna M and Gibbs, Richard A and Santibanez, Jireh and Taylor, Herman A and Rotter, Jerome I and Lange, Leslie A and Psaty, Bruce M and Jackson, Rebecca and Rich, Stephen S and Boerwinkle, Eric and Jamshidi, Yalda and Sotoodehnia, Nona} } @article {6578, title = {Strategies to design and analyze targeted sequencing data: cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study.}, journal = {Circ Cardiovasc Genet}, volume = {7}, year = {2014}, month = {2014 Jun}, pages = {335-43}, abstract = {

BACKGROUND: Genome-wide association studies have identified thousands of genetic variants that influence a variety of diseases and health-related quantitative traits. However, the causal variants underlying the majority of genetic associations remain unknown. Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study aims to follow up genome-wide association study signals and identify novel associations of the allelic spectrum of identified variants with cardiovascular-related traits.

METHODS AND RESULTS: The study included 4231 participants from 3 CHARGE cohorts: the Atherosclerosis Risk in Communities Study, the Cardiovascular Health Study, and the Framingham Heart Study. We used a case-cohort design in which we selected both a random sample of participants and participants with extreme phenotypes for each of 14 traits. We sequenced and analyzed 77 genomic loci, which had previously been associated with >=1 of 14 phenotypes. A total of 52 736 variants were characterized by sequencing and passed our stringent quality control criteria. For common variants (minor allele frequency >=1\%), we performed unweighted regression analyses to obtain P values for associations and weighted regression analyses to obtain effect estimates that accounted for the sampling design. For rare variants, we applied 2 approaches: collapsed aggregate statistics and joint analysis of variants using the sequence kernel association test.

CONCLUSIONS: We sequenced 77 genomic loci in participants from 3 cohorts. We established a set of filters to identify high-quality variants and implemented statistical and bioinformatics strategies to analyze the sequence data and identify potentially functional variants within genome-wide association study loci.

}, keywords = {Adult, Aged, Aged, 80 and over, Aging, Cohort Studies, Female, Genetic Variation, Genome-Wide Association Study, Genomics, Heart Diseases, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Research Design, Sequence Analysis, DNA}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.113.000350}, author = {Lin, Honghuang and Wang, Min and Brody, Jennifer A and Bis, Joshua C and Dupuis, Jos{\'e}e and Lumley, Thomas and McKnight, Barbara and Rice, Kenneth M and Sitlani, Colleen M and Reid, Jeffrey G and Bressler, Jan and Liu, Xiaoming and Davis, Brian C and Johnson, Andrew D and O{\textquoteright}Donnell, Christopher J and Kovar, Christie L and Dinh, Huyen and Wu, Yuanqing and Newsham, Irene and Chen, Han and Broka, Andi and DeStefano, Anita L and Gupta, Mayetri and Lunetta, Kathryn L and Liu, Ching-Ti and White, Charles C and Xing, Chuanhua and Zhou, Yanhua and Benjamin, Emelia J and Schnabel, Renate B and Heckbert, Susan R and Psaty, Bruce M and Muzny, Donna M and Cupples, L Adrienne and Morrison, Alanna C and Boerwinkle, Eric} } @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 {6844, title = {Consumption of meat is associated with higher fasting glucose and insulin concentrations regardless of glucose and insulin genetic risk scores: a meta-analysis of 50,345 Caucasians.}, journal = {Am J Clin Nutr}, volume = {102}, year = {2015}, month = {2015 Nov}, pages = {1266-78}, abstract = {

BACKGROUND: Recent studies suggest that meat intake is associated with diabetes-related phenotypes. However, whether the associations of meat intake and glucose and insulin homeostasis are modified by genes related to glucose and insulin is unknown.

OBJECTIVE: We investigated the associations of meat intake and the interaction of meat with genotype on fasting glucose and insulin concentrations in Caucasians free of diabetes mellitus.

DESIGN: Fourteen studies that are part of the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium participated in the analysis. Data were provided for up to 50,345 participants. Using linear regression within studies and a fixed-effects meta-analysis across studies, we examined 1) the associations of processed meat and unprocessed red meat intake with fasting glucose and insulin concentrations; and 2) the interactions of processed meat and unprocessed red meat with genetic risk score related to fasting glucose or insulin resistance on fasting glucose and insulin concentrations.

RESULTS: Processed meat was associated with higher fasting glucose, and unprocessed red meat was associated with both higher fasting glucose and fasting insulin concentrations after adjustment for potential confounders [not including body mass index (BMI)]. For every additional 50-g serving of processed meat per day, fasting glucose was 0.021 mmol/L (95\% CI: 0.011, 0.030 mmol/L) higher. Every additional 100-g serving of unprocessed red meat per day was associated with a 0.037-mmol/L (95\% CI: 0.023, 0.051-mmol/L) higher fasting glucose concentration and a 0.049-ln-pmol/L (95\% CI: 0.035, 0.063-ln-pmol/L) higher fasting insulin concentration. After additional adjustment for BMI, observed associations were attenuated and no longer statistically significant. The association of processed meat and fasting insulin did not reach statistical significance after correction for multiple comparisons. Observed associations were not modified by genetic loci known to influence fasting glucose or insulin resistance.

CONCLUSION: The association of higher fasting glucose and insulin concentrations with meat consumption was not modified by an index of glucose- and insulin-related single-nucleotide polymorphisms. Six of the participating studies are registered at clinicaltrials.gov as NCT0000513 (Atherosclerosis Risk in Communities), NCT00149435 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetics of Lipid Lowering Drugs and Diet Network), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).

}, keywords = {Blood Glucose, Cohort Studies, Genetic Association Studies, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Hyperglycemia, Hyperinsulinism, Insulin, Insulin Resistance, Insulin-Secreting Cells, Meat, Meat Products, Middle Aged, Polymorphism, Single Nucleotide, Risk Factors}, issn = {1938-3207}, doi = {10.3945/ajcn.114.101238}, author = {Fretts, Amanda M and Follis, Jack L and Nettleton, Jennifer A and Lemaitre, Rozenn N and Ngwa, Julius S and Wojczynski, Mary K and Kalafati, Ioanna Panagiota and Varga, Tibor V and Frazier-Wood, Alexis C and Houston, Denise K and Lahti, Jari and Ericson, Ulrika and van den Hooven, Edith H and Mikkil{\"a}, Vera and Kiefte-de Jong, Jessica C and Mozaffarian, Dariush and Rice, Kenneth and Renstrom, Frida and North, Kari E and McKeown, Nicola M and Feitosa, Mary F and Kanoni, Stavroula and Smith, Caren E and Garcia, Melissa E and Tiainen, Anna-Maija and Sonestedt, Emily and Manichaikul, Ani and van Rooij, Frank J A and Dimitriou, Maria and Raitakari, Olli and Pankow, James S and Djouss{\'e}, Luc and Province, Michael A and Hu, Frank B and Lai, Chao-Qiang and Keller, Margaux F and Per{\"a}l{\"a}, Mia-Maria and Rotter, Jerome I and Hofman, Albert and Graff, Misa and K{\"a}h{\"o}nen, Mika and Mukamal, Kenneth and Johansson, Ingegerd and Ordovas, Jose M and Liu, Yongmei and M{\"a}nnist{\"o}, Satu and Uitterlinden, Andr{\'e} G and Deloukas, Panos and Sepp{\"a}l{\"a}, Ilkka and Psaty, Bruce M and Cupples, L Adrienne and Borecki, Ingrid B and Franks, Paul W and Arnett, Donna K and Nalls, Mike A and Eriksson, Johan G and Orho-Melander, Marju and Franco, Oscar H and Lehtim{\"a}ki, Terho and Dedoussis, George V and Meigs, James B and Siscovick, David S} } @article {6602, title = {Generalized estimating equations for genome-wide association studies using longitudinal phenotype data.}, journal = {Stat Med}, volume = {34}, year = {2015}, month = {2015 Jan 15}, pages = {118-30}, abstract = {

Many longitudinal cohort studies have both genome-wide measures of genetic variation and repeated measures of phenotypes and environmental exposures. Genome-wide association study analyses have typically used only cross-sectional data to evaluate quantitative phenotypes and binary traits. Incorporation of repeated measures may increase power to detect associations, but also requires specialized analysis methods. Here, we discuss one such method-generalized estimating equations (GEE)-in the contexts of analysis of main effects of rare genetic variants and analysis of gene-environment interactions. We illustrate the potential for increased power using GEE analyses instead of cross-sectional analyses. We also address challenges that arise, such as the need for small-sample corrections when the minor allele frequency of a genetic variant and/or the prevalence of an environmental exposure is low. To illustrate methods for detection of gene-drug interactions on a genome-wide scale, using repeated measures data, we conduct single-study analyses and meta-analyses across studies in three large cohort studies participating in the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium-the Atherosclerosis Risk in Communities study, the Cardiovascular Health Study, and the Rotterdam Study.

}, keywords = {Aged, Aging, Cardiovascular Diseases, Cohort Studies, Computer Simulation, Cross-Sectional Studies, Epidemiologic Research Design, Gene-Environment Interaction, Genetic Variation, Genome, Human, Genome-Wide Association Study, Humans, Longitudinal Studies, Meta-Analysis as Topic, Models, Genetic, Pharmacogenetics, Risk Assessment, United States}, issn = {1097-0258}, doi = {10.1002/sim.6323}, author = {Sitlani, Colleen M and Rice, Kenneth M and Lumley, Thomas and McKnight, Barbara and Cupples, L Adrienne and Avery, Christy L and Noordam, Raymond and Stricker, Bruno H C and Whitsel, Eric A and Psaty, Bruce M} } @article {7004, title = {Genome-Wide Association Study for Incident Myocardial Infarction and Coronary Heart Disease in Prospective Cohort Studies: The CHARGE Consortium.}, journal = {PLoS One}, volume = {11}, year = {2016}, month = {2016}, pages = {e0144997}, abstract = {

BACKGROUND: Data are limited on genome-wide association studies (GWAS) for incident coronary heart disease (CHD). Moreover, it is not known whether genetic variants identified to date also associate with risk of CHD in a prospective setting.

METHODS: We performed a two-stage GWAS analysis of incident myocardial infarction (MI) and CHD in a total of 64,297 individuals (including 3898 MI cases, 5465 CHD cases). SNPs that passed an arbitrary threshold of 5{\texttimes}10-6 in Stage I were taken to Stage II for further discovery. Furthermore, in an analysis of prognosis, we studied whether known SNPs from former GWAS were associated with total mortality in individuals who experienced MI during follow-up.

RESULTS: In Stage I 15 loci passed the threshold of 5{\texttimes}10-6; 8 loci for MI and 8 loci for CHD, for which one locus overlapped and none were reported in previous GWAS meta-analyses. We took 60 SNPs representing these 15 loci to Stage II of discovery. Four SNPs near QKI showed nominally significant association with MI (p-value<8.8{\texttimes}10-3) and three exceeded the genome-wide significance threshold when Stage I and Stage II results were combined (top SNP rs6941513: p = 6.2{\texttimes}10-9). Despite excellent power, the 9p21 locus SNP (rs1333049) was only modestly associated with MI (HR = 1.09, p-value = 0.02) and marginally with CHD (HR = 1.06, p-value = 0.08). Among an inception cohort of those who experienced MI during follow-up, the risk allele of rs1333049 was associated with a decreased risk of subsequent mortality (HR = 0.90, p-value = 3.2{\texttimes}10-3).

CONCLUSIONS: QKI represents a novel locus that may serve as a predictor of incident CHD in prospective studies. The association of the 9p21 locus both with increased risk of first myocardial infarction and longer survival after MI highlights the importance of study design in investigating genetic determinants of complex disorders.

}, keywords = {Aged, Cohort Studies, Cooperative Behavior, Coronary Artery Disease, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Middle Aged, Myocardial Infarction, Polymorphism, Single Nucleotide, Prospective Studies}, issn = {1932-6203}, doi = {10.1371/journal.pone.0144997}, author = {Dehghan, Abbas and Bis, Joshua C and White, Charles C and Smith, Albert Vernon and Morrison, Alanna C and Cupples, L Adrienne and Trompet, Stella and Chasman, Daniel I and Lumley, Thomas and V{\"o}lker, Uwe and Buckley, Brendan M and Ding, Jingzhong and Jensen, Majken K and Folsom, Aaron R and Kritchevsky, Stephen B and Girman, Cynthia J and Ford, Ian and D{\"o}rr, Marcus and Salomaa, Veikko and Uitterlinden, Andr{\'e} G and Eiriksdottir, Gudny and Vasan, Ramachandran S and Franceschini, Nora and Carty, Cara L and Virtamo, Jarmo and Demissie, Serkalem and Amouyel, Philippe and Arveiler, Dominique and Heckbert, Susan R and Ferrieres, Jean and Ducimetiere, Pierre and Smith, Nicholas L and Wang, Ying A and Siscovick, David S and Rice, Kenneth M and Wiklund, Per-Gunnar and Taylor, Kent D and Evans, Alun and Kee, Frank and Rotter, Jerome I and Karvanen, Juha and Kuulasmaa, Kari and Heiss, Gerardo and Kraft, Peter and Launer, Lenore J and Hofman, Albert and Markus, Marcello R P and Rose, Lynda M and Silander, Kaisa and Wagner, Peter and Benjamin, Emelia J and Lohman, Kurt and Stott, David J and Rivadeneira, Fernando and Harris, Tamara B and Levy, Daniel and Liu, Yongmei and Rimm, Eric B and Jukema, J Wouter and V{\"o}lzke, Henry and Ridker, Paul M and Blankenberg, Stefan and Franco, Oscar H and Gudnason, Vilmundur and Psaty, Bruce M and Boerwinkle, Eric and O{\textquoteright}Donnell, Christopher J} } @article {7578, title = {Genome-wide association meta-analysis of fish and EPA+DHA consumption in 17 US and European cohorts.}, journal = {PLoS One}, volume = {12}, year = {2017}, month = {2017}, pages = {e0186456}, abstract = {

BACKGROUND: Regular fish and omega-3 consumption may have several health benefits and are recommended by major dietary guidelines. Yet, their intakes remain remarkably variable both within and across populations, which could partly owe to genetic influences.

OBJECTIVE: To identify common genetic variants that influence fish and dietary eicosapentaenoic acid plus docosahexaenoic acid (EPA+DHA) consumption.

DESIGN: We conducted genome-wide association (GWA) meta-analysis of fish (n = 86,467) and EPA+DHA (n = 62,265) consumption in 17 cohorts of European descent from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Nutrition Working Group. Results from cohort-specific GWA analyses (additive model) for fish and EPA+DHA consumption were adjusted for age, sex, energy intake, and population stratification, and meta-analyzed separately using fixed-effect meta-analysis with inverse variance weights (METAL software). Additionally, heritability was estimated in 2 cohorts.

RESULTS: Heritability estimates for fish and EPA+DHA consumption ranged from 0.13-0.24 and 0.12-0.22, respectively. A significant GWA for fish intake was observed for rs9502823 on chromosome 6: each copy of the minor allele (FreqA = 0.015) was associated with 0.029 servings/day (~1 serving/month) lower fish consumption (P = 1.96x10-8). No significant association was observed for EPA+DHA, although rs7206790 in the obesity-associated FTO gene was among top hits (P = 8.18x10-7). Post-hoc calculations demonstrated 95\% statistical power to detect a genetic variant associated with effect size of 0.05\% for fish and 0.08\% for EPA+DHA.

CONCLUSIONS: These novel findings suggest that non-genetic personal and environmental factors are principal determinants of the remarkable variation in fish consumption, representing modifiable targets for increasing intakes among all individuals. Genes underlying the signal at rs72838923 and mechanisms for the association warrant further investigation.

}, keywords = {Adult, Aged, Cohort Studies, Docosahexaenoic Acids, Eicosapentaenoic Acid, Europe, European Continental Ancestry Group, Female, Genome-Wide Association Study, Humans, Male, Middle Aged, Seafood, United States}, issn = {1932-6203}, doi = {10.1371/journal.pone.0186456}, author = {Mozaffarian, Dariush and Dashti, Hassan S and Wojczynski, Mary K and Chu, Audrey Y and Nettleton, Jennifer A and M{\"a}nnist{\"o}, Satu and Kristiansson, Kati and Reedik, M{\"a}gi and Lahti, Jari and Houston, Denise K and Cornelis, Marilyn C and van Rooij, Frank J A and Dimitriou, Maria and Kanoni, Stavroula and Mikkil{\"a}, Vera and Steffen, Lyn M and de Oliveira Otto, Marcia C and Qi, Lu and Psaty, Bruce and Djouss{\'e}, Luc and Rotter, Jerome I and Harald, Kennet and Perola, Markus and Rissanen, Harri and Jula, Antti and Krista, Fischer and Mihailov, Evelin and Feitosa, Mary F and Ngwa, Julius S and Xue, Luting and Jacques, Paul F and Per{\"a}l{\"a}, Mia-Maria and Palotie, Aarno and Liu, Yongmei and Nalls, Nike A and Ferrucci, Luigi and Hernandez, Dena and Manichaikul, Ani and Tsai, Michael Y and Kiefte-de Jong, Jessica C and Hofman, Albert and Uitterlinden, Andr{\'e} G and Rallidis, Loukianos and Ridker, Paul M and Rose, Lynda M and Buring, Julie E and Lehtim{\"a}ki, Terho and K{\"a}h{\"o}nen, Mika and Viikari, Jorma and Lemaitre, Rozenn and Salomaa, Veikko and Knekt, Paul and Metspalu, Andres and Borecki, Ingrid B and Cupples, L Adrienne and Eriksson, Johan G and Kritchevsky, Stephen B and Bandinelli, Stefania and Siscovick, David and Franco, Oscar H and Deloukas, Panos and Dedoussis, George and Chasman, Daniel I and Raitakari, Olli and Tanaka, Toshiko} }