Genetic signatures of exceptional longevity in humans.
ABSTRACT Healthy aging is thought to reflect the combined influence of environmental factors (lifestyle choices) and genetic factors. To explore the genetic contribution, we undertook a genome-wide association study of exceptional longevity (EL) in 1055 centenarians and 1267 controls. Using these data, we built a genetic model that includes 150 single-nucleotide polymorphisms (SNPs) and found that it could predict EL with 77% accuracy in an independent set of centenarians and controls. Further in silico analysis revealed that 90% of centenarians can be grouped into 19 clusters characterized by different combinations of SNP genotypes-or genetic signatures-of varying predictive value. The different signatures, which attest to the genetic complexity of EL, correlated with differences in the prevalence and age of onset of age-associated diseases (e.g., dementia, hypertension, and cardiovascular disease) and may help dissect this complex phenotype into subphenotypes of healthy aging.
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ABSTRACT: Case control studies of nonagenarians and centenarians provide evidence that long-lived individuals do not differ in the rate of disease associated variants compared to population controls. These results suggest that an enrichment of novel protective variants, rather than a lack of disease associated variants, determine the genetic predisposition to exceptionally long lives. Using data from the Long Life Family Study (LLFS), we sought to replicate these findings and extend them to include a larger number of disease-specific risk alleles. To accomplish this goal, we built a genetic risk score for each of four age-related disease groups: Alzheimer's disease, cardiovascular disease and stroke, type 2 diabetes, and various cancers and compared the distribution of these scores between older participants of the LLFS, their offspring and their spouses. The analyses showed no significant differences in distribution of the genetic risk scores for cardiovascular disease and stroke, type 2 diabetes, or cancer between the groups, while participants of the LLFS appeared to carry an average 1% fewer risk alleles for Alzheimer's disease compared to spousal controls and, while the difference may not be clinically relevant, it was statistically significant. However, the statistical significance between familial longevity and the Alzheimer's disease genetic risk score was lost when a more stringent linkage disequilibrium threshold was imposed to select independent genetic variants.Aging 02/2015; · 4.89 Impact Factor
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ABSTRACT: A recent paper by Deelen et al. (2014) in Human Molecular Genetics reports the largest genome-wide association study of human longevity to date. While impressive, there is a remarkable lack of association of genes known to considerably extend lifespan in rodents with human longevity, both in this latest study and in genetic association studies in general. Here, I discuss several possible explanations, such as intrinsic limitations in longevity association studies and the complex genetic architecture of longevity. Yet one hypothesis is that the lack of correlation between longevity-associated genes in model organisms and genes associated with human longevity is, at least partly, due to intrinsic limitations and biases in animal studies. In particular, most studies in model organisms are conducted in strains of limited genetic diversity which are then not applicable to human populations. This has important implications and, together with other recent results demonstrating strain-specific longevity effects in rodents due to caloric restriction, it questions our capacity to translate the exciting findings from the genetics of aging to human therapies.Cell cycle (Georgetown, Tex.) 09/2014; 13(17):2671-2673. DOI:10.4161/15384101.2014.950151 · 5.01 Impact Factor
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ABSTRACT: Objective: We have previously reported the combined effect of SNPs perturbing insulin signaling (ENPP1 K121Q, rs1044498; IRS1 G972R, rs1801278; TRIB3 Q84R, rs2295490) on insulin resistance (IR), type 2 diabetes (T2D) and cardiovascular events. We here investigated whether such a combined effect affects also all-cause mortality in a sample of 1851 Whites of European ancestry. Methods: We investigated a first sample of 721 patients, 232 deaths, 3389 person-years (py). Replication was assessed in two samples of patients with T2D: the Gargano Mortality Study (GMS) of 714 patients, 127 deaths, 5426 py and the Joslin Kidney Study (JKS) comprising 416 patients, 214 deaths, 5325 py. Results: In the first sample, individuals carrying 1 or ≥2 risk alleles had 33% (p = 0.06) and 51% (p = 0.02) increased risk of mortality, as compared with individuals with no risk alleles. A similar, though not significant, trend was obtained in the two replication samples only for subject carrying ≥ 2 risk alleles. In a pooled analysis, individuals carrying ≥2 risk alleles had higher mortality rate as compared to those carrying 0 risk alleles (HR = 1.34, 95%CI = 1.08-1.67; p = 0.008), and as compared to those carrying only one risk allele (HR = 1.41, 95%CI = 1.13-1.75; p = 0.002). This association was independent from several possible confounders including sex, age, BMI, hypertension and diabetes status. Conclusion: Our data suggest that variants affecting insulin signaling exert a joint effect on all-cause mortality and is consistent with a role of abnormal insulin signaling on mortality risk. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.Atherosclerosis 10/2014; 237(2):639-644. DOI:10.1016/j.atherosclerosis.2014.10.005 · 3.97 Impact Factor