Genome-Wide Scan Informed by Age-Related Disease Identifies Loci for Exceptional XXXX Longevity.

@entity1 @entity2204 @entity16 @entity72909 @entity195 @entity44280 @entity453 @entity18414 @entity238
We developed a new statistical framework to find genetic variants associated with extreme longevity. The method, informed GWAS (iGWAS), takes advantage of knowledge from large studies of age-related disease in order to narrow the search for SNPs associated with longevity. To gain support for our approach, we first show there is an overlap between loci involved in disease and loci associated with extreme longevity. These results indicate that several disease variants may be depleted in centenarians versus the general population. Next, we used iGWAS to harness information from 14 meta-analyses of disease and trait GWAS to identify longevity loci in two studies of long-lived @entity1 . In a standard GWAS analysis, only one locus in these studies is significant ( @entity2204 / @entity18414 ) when controlling the false discovery rate (FDR) at 10%. With iGWAS, we identify eight genetic loci to associate significantly with exceptional @entity1 longevity at FDR < 10%. We followed up the eight lead SNPs in independent cohorts, and found replication evidence of four loci and suggestive evidence for one more with exceptional longevity. The loci that replicated (FDR < 5%) included @entity2204 / @entity18414 (associated with @entity195 ), @entity44280 /ANRIL (implicated in the regulation of cellular senescence), @entity72909 (tags the O blood group), and SH2B3/ATXN2 (a signaling gene that extends lifespan in @entity238 and a gene involved in @entity16 ). Our results implicate new loci in longevity and reveal a genetic overlap between longevity and age-related diseases and traits, including @entity453 and @entity195 . iGWAS provides a new analytical strategy for uncovering SNPs that influence extreme longevity, and can be applied more broadly to boost power in other studies of complex phenotypes.
