Polygenic effects of common single-nucleotide polymorphisms on life span: when association meets causality.
Ontology highlight
ABSTRACT: Recently we have shown that the human life span is influenced jointly by many common single-nucleotide polymorphisms (SNPs), each with a small individual effect. Here we investigate further the polygenic influence on life span and discuss its possible biological mechanisms. First we identified six sets of prolongevity SNP alleles in the Framingham Heart Study 550K SNPs data, using six different statistical procedures (normal linear, Cox, and logistic regressions; generalized estimation equation; mixed model; gene frequency method). We then estimated joint effects of these SNPs on human survival. We found that alleles in each set show significant additive influence on life span. Twenty-seven SNPs comprised the overlapping set of SNPs that influenced life span, regardless of the statistical procedure. The majority of these SNPs (74%) were within genes, compared to 40% of SNPs in the original 550K set. We then performed a review of current literature on functions of genes closest to these 27 SNPs. The review showed that the respective genes are largely involved in aging, cancer, and brain disorders. We concluded that polygenic effects can explain a substantial portion of genetic influence on life span. Composition of the set of prolongevity alleles depends on the statistical procedure used for the allele selection. At the same time, there is a core set of longevity alleles that are selected with all statistical procedures. Functional relevance of respective genes to aging and major diseases supports causal relationships between the identified SNPs and life span. The fact that genes found in our and other genetic association studies of aging/longevity have similar functions indicates high chances of true positive associations for corresponding genetic variants.
SUBMITTER: Yashin AI
PROVIDER: S-EPMC3419841 | biostudies-literature | 2012 Aug
REPOSITORIES: biostudies-literature
ACCESS DATA