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      Genetic correlates of longevity and selected age-related phenotypes: a genome-wide association study in the Framingham Study

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          Abstract

          Background

          Family studies and heritability estimates provide evidence for a genetic contribution to variation in the human life span.

          Methods

          We conducted a genome wide association study (Affymetrix 100K SNP GeneChip) for longevity-related traits in a community-based sample. We report on 5 longevity and aging traits in up to 1345 Framingham Study participants from 330 families. Multivariable-adjusted residuals were computed using appropriate models (Cox proportional hazards, logistic, or linear regression) and the residuals from these models were used to test for association with qualifying SNPs (70, 987 autosomal SNPs with genotypic call rate ≥80%, minor allele frequency ≥10%, Hardy-Weinberg test p ≥ 0.001).

          Results

          In family-based association test (FBAT) models, 8 SNPs in two regions approximately 500 kb apart on chromosome 1 (physical positions 73,091,610 and 73, 527,652) were associated with age at death (p-value < 10 -5). The two sets of SNPs were in high linkage disequilibrium (minimum r 2 = 0.58). The top 30 SNPs for generalized estimating equation (GEE) tests of association with age at death included rs10507486 (p = 0.0001) and rs4943794 (p = 0.0002), SNPs intronic to FOXO1A, a gene implicated in lifespan extension in animal models. FBAT models identified 7 SNPs and GEE models identified 9 SNPs associated with both age at death and morbidity-free survival at age 65 including rs2374983 near PON1. In the analysis of selected candidate genes, SNP associations (FBAT or GEE p-value < 0.01) were identified for age at death in or near the following genes: FOXO1A, GAPDH, KL, LEPR, PON1, PSEN1, SOD2, and WRN. Top ranked SNP associations in the GEE model for age at natural menopause included rs6910534 (p = 0.00003) near FOXO3a and rs3751591 (p = 0.00006) in CYP19A1. Results of all longevity phenotype-genotype associations for all autosomal SNPs are web posted at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007.

          Conclusion

          Longevity and aging traits are associated with SNPs on the Affymetrix 100K GeneChip. None of the associations achieved genome-wide significance. These data generate hypotheses and serve as a resource for replication as more genes and biologic pathways are proposed as contributing to longevity and healthy aging.

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          Most cited references40

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          FoxO proteins in insulin action and metabolism.

          There is increasing evidence that Forkhead box 'Other' (FoxO) proteins, a subgroup of the Forkhead transcription factor family, have an important role in mediating the effects of insulin and growth factors on diverse physiological functions, including cell proliferation, apoptosis and metabolism. Genetic studies in Caenorhabditis (Caenorhabditis elegans) and Drosophila demonstrate that FoxO proteins are ancient targets of insulin-like signaling involved in the regulation of metabolism and longevity. Studies in mammalian cells reveal that FoxO proteins regulate cell cycle progression and promote resistance to oxidative stress; both in vivo and cell culture studies support the concept that FoxO proteins have an important role in mediating the effects of insulin on metabolism, including its effects on hepatic glucose production. Phosphorylation and acetylation modulate FoxO function and control nuclear-cytoplasmic shuttling, DNA binding and protein-protein interactions. FoxO transcription factors exert positive and negative effects on gene expression, through direct binding to DNA target sites and protein-protein interactions with other transcription factors and coactivators. This paper provides an overview of studies leading to the identification of FoxO proteins as targets of insulin action and the mechanisms mediating the effects of insulin-like signaling on FoxO function, emphasizing the role of FoxO proteins in mediating the effects of insulin on metabolism.
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            A comprehensive review of genetic association studies.

            Most common diseases are complex genetic traits, with multiple genetic and environmental components contributing to susceptibility. It has been proposed that common genetic variants, including single nucleotide polymorphisms (SNPs), influence susceptibility to common disease. This proposal has begun to be tested in numerous studies of association between genetic variation at these common DNA polymorphisms and variation in disease susceptibility. We have performed an extensive review of such association studies. We find that over 600 positive associations between common gene variants and disease have been reported; these associations, if correct, would have tremendous importance for the prevention, prediction, and treatment of most common diseases. However, most reported associations are not robust: of the 166 putative associations which have been studied three or more times, only 6 have been consistently replicated. Interestingly, of the remaining 160 associations, well over half were observed again one or more times. We discuss the possible reasons for this irreproducibility and suggest guidelines for performing and interpreting genetic association studies. In particular, we emphasize the need for caution in drawing conclusions from a single report of an association between a genetic variant and disease susceptibility.
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              Genetic influence on human lifespan and longevity.

              There is an intense search for longevity genes in both animal models and humans. Human family studies have indicated that a modest amount of the overall variation in adult lifespan (approximately 20-30%) is accounted for by genetic factors. But it is not known if genetic factors become increasingly important for survival at the oldest ages. We study the genetic influence on human lifespan and how it varies with age using the almost extinct cohorts of Danish, Finnish and Swedish twins born between 1870 and 1910 comprising 20,502 individuals followed until 2003-2004. We first estimate mean lifespan of twins by lifespan of co-twin and then turn to the relative recurrence risk of surviving to a given age. Mean lifespan for male monozygotic (MZ) twins increases 0.39 [95% CI (0.28, 0.50)] years for every year his co-twin survives past age 60 years. This rate is significantly greater than the rate of 0.21 (0.11, 0.30) for dizygotic (DZ) males. Females and males have similar rates and these are negligible before age 60 for both MZ and DZ pairs. We moreover find that having a co-twin surviving to old ages substantially and significantly increases the chance of reaching the same old age and this chance is higher for MZ than for DZ twins. The relative recurrence risk of reaching age 92 is 4.8 (2.2, 7.5) for MZ males, which is significantly greater than the 1.8 (0.10, 3.4) for DZ males. The patterns for females and males are very similar, but with a shift of the female pattern with age that corresponds to the better female survival. Similar results arise when considering only those Nordic twins that survived past 75 years of age. The present large population based study shows genetic influence on human lifespan. While the estimated overall strength of genetic influence is compatible with previous studies, we find that genetic influences on lifespan are minimal prior to age 60 but increase thereafter. These findings provide a support for the search for genes affecting longevity in humans, especially at advanced ages.
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                Author and article information

                Journal
                BMC Med Genet
                BMC Medical Genetics
                BioMed Central (London )
                1471-2350
                2007
                19 September 2007
                : 8
                : Suppl 1
                : S13
                Affiliations
                [1 ]The National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA
                [2 ]Section of General Internal Medicine and the Departments of Neurology, Cardiology, and Preventive Medicine, Boston University School of Medicine, Boston, MA, USA
                [3 ]Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
                [4 ]Hebrew Senior Life Institute for Aging Research and Harvard Medical School, Boston, MA, USA
                [5 ]Statistics and Consulting Unit, Department of Mathematics, Boston University, Boston, MA, USA
                Article
                1471-2350-8-S1-S13
                10.1186/1471-2350-8-S1-S13
                1995604
                17903295
                232d7143-6106-4da6-b98d-cca31b56c699
                Copyright © 2007 Lunetta et al; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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                Research

                Genetics
                Genetics

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