Dataset Information

A meta-analysis of four genome-wide association studies of survival to age 90 years or older: the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium.

ABSTRACT: Genome-wide association studies (GWAS) may yield insights into longevity.We performed a meta-analysis of GWAS in Caucasians from four prospective cohort studies: the Age, Gene/Environment Susceptibility-Reykjavik Study, the Cardiovascular Health Study, the Framingham Heart Study, and the Rotterdam Study participating in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Longevity was defined as survival to age 90 years or older (n = 1,836); the comparison group comprised cohort members who died between the ages of 55 and 80 years (n = 1,955). In a second discovery stage, additional genotyping was conducted in the Leiden Longevity Study cohort and the Danish 1905 cohort.There were 273 single-nucleotide polymorphism (SNP) associations with p < .0001, but none reached the prespecified significance level of 5 x 10(-8). Of the most significant SNPs, 24 were independent signals, and 16 of these SNPs were successfully genotyped in the second discovery stage, with one association for rs9664222, reaching 6.77 x 10(-7) for the combined meta-analysis of CHARGE and the stage 2 cohorts. The SNP lies in a region near MINPP1 (chromosome 10), a well-conserved gene involved in regulation of cellular proliferation. The minor allele was associated with lower odds of survival past age 90 (odds ratio = 0.82). Associations of interest in a homologue of the longevity assurance gene (LASS3) and PAPPA2 were not strengthened in the second stage.Survival studies of larger size or more extreme or specific phenotypes may support or refine these initial findings.

SUBMITTER: Newman AB

PROVIDER: S-EPMC2854887 | biostudies-literature | 2010 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A meta-analysis of four genome-wide association studies of survival to age 90 years or older: the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium.

Newman Anne B AB Walter Stefan S Lunetta Kathryn L KL Garcia Melissa E ME Slagboom P Eline PE Christensen Kaare K Arnold Alice M AM Aspelund Thor T Aulchenko Yurii S YS Benjamin Emelia J EJ Christiansen Lene L D'Agostino Ralph B RB Fitzpatrick Annette L AL Franceschini Nora N Glazer Nicole L NL Gudnason Vilmundur V Hofman Albert A Kaplan Robert R Karasik David D Kelly-Hayes Margaret M Kiel Douglas P DP Launer Lenore J LJ Marciante Kristin D KD Massaro Joseph M JM Miljkovic Iva I Nalls Michael A MA Hernandez Dena D Psaty Bruce M BM Rivadeneira Fernando F Rotter Jerome J Seshadri Sudha S Smith Albert V AV Taylor Kent D KD Tiemeier Henning H Uh Hae-Won HW Uitterlinden André G AG Vaupel James W JW Walston Jeremy J Westendorp Rudi G J RG Harris Tamara B TB Lumley Thomas T van Duijn Cornelia M CM Murabito Joanne M JM

The journals of gerontology. Series A, Biological sciences and medical sciences 20100318 5

<h4>Background</h4>Genome-wide association studies (GWAS) may yield insights into longevity.<h4>Methods</h4>We performed a meta-analysis of GWAS in Caucasians from four prospective cohort studies: the Age, Gene/Environment Susceptibility-Reykjavik Study, the Cardiovascular Health Study, the Framingham Heart Study, and the Rotterdam Study participating in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Longevity was defined as survival to age 90 years or olde ...[more]

PMID: 20304771

Similar Datasets

Project description:BackgroundGenome-wide association studies have identified multiple genomic loci associated with coronary artery disease, but most are common variants in non-coding regions that provide limited information on causal genes and etiology of the disease. To overcome the limited scope that common variants provide, we focused our investigation on low-frequency and rare sequence variations primarily residing in coding regions of the genome.Methods and resultsUsing samples of individuals of European ancestry from ten cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, both cross-sectional and prospective analyses were conducted to examine associations between genetic variants and myocardial infarction (MI), coronary heart disease (CHD), and all-cause mortality following these events. For prevalent events, a total of 27,349 participants of European ancestry, including 1831 prevalent MI cases and 2518 prevalent CHD cases were used. For incident cases, a total of 55,736 participants of European ancestry were included (3,031 incident MI cases and 5,425 incident CHD cases). There were 1,860 all-cause deaths among the 3,751 MI and CHD cases from six cohorts that contributed to the analysis of all-cause mortality. Single variant and gene-based analyses were performed separately in each cohort and then meta-analyzed for each outcome. A low-frequency intronic variant (rs988583) in PLCL1 was significantly associated with prevalent MI (OR = 1.80, 95% confidence interval: 1.43, 2.27; P = 7.12 × 10-7). We conducted gene-based burden tests for genes with a cumulative minor allele count (cMAC) ≥ 5 and variants with minor allele frequency (MAF) < 5%. TMPRSS5 and LDLRAD1 were significantly associated with prevalent MI and CHD, respectively, and RC3H2 and ANGPTL4 were significantly associated with incident MI and CHD, respectively. No loci were significantly associated with all-cause mortality following a MI or CHD event.ConclusionThis study identified one known locus (ANGPTL4) and four new loci (PLCL1, RC3H2, TMPRSS5, and LDLRAD1) associated with cardiovascular disease risk that warrant further investigation.

Dataset Information

A meta-analysis of four genome-wide association studies of survival to age 90 years or older: the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium.

Publications

A meta-analysis of four genome-wide association studies of survival to age 90 years or older: the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets