Age at natural menopause rs10496265 2 81,580,466 1.1 x 10^-8 0.001 
rs10496262*2*81,662,782*3.3*10^-7*0.005 
rs958672 2 154,896,075 1.9 x 10^-6 0.087 GALNT13 
rs291353 1 232,046,939 5.5 x 10^-6 0.035 GNG4 
rs726336 5 163,911,906 1.1 x 10^-5 0.125 

Walking speed exam 7 rs7137869*12*118,452,366*6.3*10^-7*0.009 CCDC60 
rs7662116 4 154,375,569 1.9 x10^-5 0.016 
rs7972859*12*118,452,765*2.5*10^-5*0.005 CCDC60 
rs9318312 13 74,489,506 5.8 x10^-5*0.266 
rs1994854 4 78,124,824 9.4 x10^-5*0.280 
rs7718104 5 122,183,258 1.2 x10^-4*0.011 SNX2 

Biologic age by osseographic scoring system rs1463605*12*30,005,150*7.0 x10^-8*5.3 x10^-4 
rs7176093 15 84,170,4347.4 x10^-6 *0.005 KLHL25 
rs3772255 *3 *157,585,436 *8.2 x10^-6*0.085 KCNAB1 
rs726846 5 136,099,953 1.1 x10^-5 *0.003 
rs646983 13 29,413,553 1.2 x10^-5 *0.003 

2b. FBAT, Top 5 p-values by Phenotype* 

Trait SNP Chromosome Physical location GEE p-value FBAT p-value Gene Region (within 60 kb) 

Age at death rs10493513 1 73,091,610 0.640 1.5 x10^-6 
rs10493514*1*73,092,533*0.623*2.8 x10^-6 
rs6689491*1*73,064,050*0.205*2.0 x10^-5 
rs10493515 1 73,527,652 0.225 2.3 x10^-5 
rs10493518*1*73,572,652*0.191*3.6 x10^-5 
rs10493517*"rs4764600" and it has a FBAT p-value of 0.833 and a GEE p-value of 0.005. The SNP is located in the locus or intron near KL.detect novel susceptibility genes and examine the relevance of promising candidate gene associations reported in animal models to human aging. The most strongly associated SNP near WRN is actually closer to PURG related phenotypes, and 100K SNP genotyping results are available on the web. Several strategies are described to prioritize SNP associations in this unique resource to enhance the discovery of various genes and pathways that contribute to the control of human longevity. Furthermore, FHS investigators are part of the NIA-sponsored Longevity Consortium http://www.longevityconsortium.org, which offers the opportunity for collaboration with other investigators to replicate important findings in additional cohorts.

Forkhead box group O (FOXO) transcription factors are targets of insulin-like signaling and are involved in a diverse set of physiological functions, including DNA repair and resistance to oxidative stress [33,34]. Further, FOXO plays a role in lifespan extension in C. elegans and Drosophila [35]. Studies of this gene in humans are limited; two case-control studies have not identified an association between FOXO1a and longevity [36,37]. However, the prospective population-based Leiden 85-plus Study found that FOXO1a was associated with increased mortality attributable to diabetes-related deaths in participants aged 85 years and older [38]. The Leiden 85-plus Study also reported that genetic variation causing a reduction in insulin/IGF-1 signaling resulted in improved old age survival among women [20]. However, that report examined other genes in the insulin/insulin-like signaling pathway and did not specifically examine FOXO1a.

Finally, the untargeted approach to SNP selection also identified a SNP near FOXO3a associated with age at natural menopause. This gene has been implicated in oocyte death, depletion of functioning ovarian follicles, and infertility in mice [39,40] and thus represents a plausible candidate gene for menopause. Most positive common gene variant-disease association studies have failed replication [41], including reports on exceptional longevity. Haplotype-based fine mapping of the region on chromosome 4 linked to human longevity initially suggested the MTP gene, a gene important in lipoprotein synthesis, was associated with longevity [21]. However, this association failed replication in a French cohort of long-lived individuals and subsequent case-control studies of nonagenarians [22,42]. Beekman et al [43] found neither linkage to chromosome 4 nor association with the MTP gene and longevity among nonagenarians in the Leiden Longevity Study. Meta-analyses implicated admixture of the control sample in the original report as an explanation for the presumed false-positive association. Thus, our findings are hypothesis-generating, and their importance cannot be determined without evidence of consistent replication in other populations.

Several important limitations merit comment. First, we acknowledge that there may be a survival bias as participants in this sample had to survive to provide DNA (first systematic DNA collection began 1995) and hence are likely healthier than the full FHS sample. To ameliorate this issue, we adjusted for covariates using the full Framingham sample and used the residual traits for the subset of individuals genotyped using the 100K Affymetrix GeneChip to test for association with the SNPs using linear regression models. Residual traits from Cox and logistic models typically are not ideally distributed for linear regression models, but our adjustment method using the full sample precludes testing SNP associations with age at death and morbidity-free survival using Cox and logistic models. Second, the 100K Affymetrix GeneChip provides limited coverage of the genome; many of our a priori candidate genes did not have any SNP coverage on the chip. For example, several genes that have been studied in model organisms or even in humans such as ACE, Lamin A, SIRT2, and SIRT3 had no SNPs within 60 kb of the gene on the 100K Affymetrix GeneChip. However, genotyping is near-complete for the NHLBI funded 550 K genome-wide scan on all FHS participants. This will enable deeper exploration of our initial 100K SNP associations in a larger sample with denser coverage of the genome. Third, in this analysis, we did not examine epistasis or gene-environment interactions, which may modify the associations in this study. Importantly, this study is hypothesis-generating. Our findings need to be replicated in other samples.