Human longevity is a complex phenotype with a significant familial component, yet little is known about its genetic antecedents. Increasing evidence from animal models suggests that the insulin/ IGF-1 signaling (IIS) pathway is an important, evolutionarily conserved biological pathway that influences aging and longevity. However, to date human data have been scarce. Studies have been hampered by small sample sizes, lack of precise phenotyping, and population stratification, among other challenges. Therefore, to more precisely assess potential genetic contributions to human longevity from genes linked to IIS signaling, we chose a large, homogeneous, long-lived population of men well-characterized for aging phenotypes, and we performed a nested-case control study of 5 candidate longevity genes. Genetic variation within the FOXO3A gene was strongly associated with human longevity. The OR for homozygous minor vs. homozygous major alleles between the cases and controls was 2.75 (P ‫؍‬ 0.00009; adjusted P ‫؍‬ 0.00135). Long-lived men also presented several additional phenotypes linked to healthy aging, including lower prevalence of cancer and cardiovascular disease, better self-reported health, and high physical and cognitive function, despite significantly older ages than controls. Several of these aging phenotypes were associated with FOXO3A genotype. Long-lived men also exhibited several biological markers indicative of greater insulin sensitivity and this was associated with homozygosity for the FOXO3A GG genotype. Further exploration of the FOXO3A gene, human longevity and other aging phenotypes is warranted in other populations.gene ͉ insulin ͉ healthy aging ͉ disease ͉ disability

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Context-Prediction models to identify healthy individuals at high risk of cardiovascular disease have limited accuracy. A low ankle brachial index is an indicator of atherosclerosis and has the potential to improve prediction.Objective-To determine if the ankle brachial index provides information on the risk of cardiovascular events and mortality independently of the Framingham Risk Score and can improve risk prediction.