How Genes Influence Life Span: The Biodemography of Human Survival
Abstract
Background: In genome-wide association studies (GWAS) of human life span, none of the genetic variants has reached the level of genome-wide statistical significance. The roles of such variants in life span regulation remain unclear.
Data and Method: A biodemographic analyses was done of genetic regulation of life span using data on low-significance longevity alleles selected in the earlier GWAS of the original Framingham cohort.
Results: Age-specific survival curves considered as functions of the number of longevity alleles exhibit regularities known in demography as “rectangularization” of survival curves. The presence of such pattern confirms observations from experimental studies that regulation of life span involves genes responsible for stress resistance.
Conclusion: Biodemographic analyses could provide important information about the properties of genes affecting phenotypic traits.
Get full access to this article
View all available purchase options and get full access to this article.
References
1.
Hardy JSingleton A. Genomewide association studies and human diseaseN Engl J Med20093601759-1768. 1. Hardy, J, Singleton A. Genomewide association studies and human disease. N Engl J Med 2009;360:1759–1768.
2.
Maher B. Personal genomes: The case of the missing heritabilityNature200845618-21. 2. Maher B. Personal genomes: The case of the missing heritability. Nature 2008;456:18–21.
3.
Manolio TACollins FSCox NJ et al. Finding the missing heritability of complex diseasesNature2009461747-753. 3. Manolio TA, Collins FS, Cox NJ, et al. Finding the missing heritability of complex diseases. Nature 2009;461:747–753.
4.
Slatkin M. Epigenetic inheritance and the missing heritability problemGenetics2009182845-850. 4. Slatkin M. Epigenetic inheritance and the missing heritability problem. Genetics 2009;182:845–850.
5.
Visscher PMHill WGWray NR. Heritability in the genomics era—concepts and misconceptionsNat Rev Genet20089255-266. 5. Visscher PM, Hill WG, Wray NR. Heritability in the genomics era—concepts and misconceptions. Nat Rev Genet 2008;9:255–266.
6.
Anselmi CVMalovini ARoncarati R et al. Association of the FOXO3A locus with extreme longevity in a Southern Italian centenarian studyRejuvenation Res20091295-103. 6. Anselmi CV, Malovini A, Roncarati R, et al. Association of the FOXO3A locus with extreme longevity in a Southern Italian centenarian study. Rejuvenation Res 2009;12:95–103.
7.
Flachsbart FCaliebeb AKleindorp R et al. Association of FOXO3A variation with human longevity confirmed in German centenariansProc Natl Acad Sci USA20091062700-2705. 7. Flachsbart F, Caliebeb A, Kleindorp R, et al. Association of FOXO3A variation with human longevity confirmed in German centenarians. Proc Natl Acad Sci USA 2009;106:2700–2705.
8.
Willcox BJDonlon TAHe Q et al. FOXO3A genotype is strongly associated with human longevityProc Natl Acad Sci USA200810513987-13992. 8. Willcox BJ, Donlon TA, He Q, et al. FOXO3A genotype is strongly associated with human longevity. Proc Natl Acad Sci USA 2008;105:13987–13992.
9.
Zeng YCheng LGChen HSA et al. Effects of FOXO genotypes on longevity: A biodemographic analysisJ Gerontol A Biol Sci Med Sci2010651285-1299. 9. Zeng Y, Cheng LG, Chen HSA, et al. Effects of FOXO genotypes on longevity: A biodemographic analysis. J Gerontol A Biol Sci Med Sci 2010;65:1285–1299.
10.
Lunetta KLD'Agostino RB Sr.Karasik D et al. Genetic correlates of longevity and selected age-related phenotypes: A genome-wide association study in the Framingham StudyBMC Med Genet20078Suppl. 1S13. 10. Lunetta KL, D'Agostino RB, Sr., Karasik D, et al. Genetic correlates of longevity and selected age-related phenotypes: A genome-wide association study in the Framingham Study. BMC Med Genet 2007;8(Suppl. 1):S13.
11.
Newman ABWalter SLunetta KL et al. A meta-analysis of four genome-wide association studies of survival to age 90 years or older: The cohorts for heart and aging research in Genomic Epidemiology ConsortiumJ Gerontol A Biol Sci Med Sci201065478-487. 11. Newman AB, Walter S, Lunetta KL, et al. A meta-analysis of four genome-wide association studies of survival to age 90 years or older: The cohorts for heart and aging research in Genomic Epidemiology Consortium. J Gerontol A Biol Sci Med Sci 2010;65:478–487.
12.
Walter SAtzmon GDemerath EW et al. A genome-wide association study of agingNeurobiol Aging2011322109.e2115-2109.e2128. 12. Walter S, Atzmon G, Demerath EW, et al. A genome-wide association study of aging. Neurobiol Aging 2011;32:2109.e2115–2109.e2128.
13.
Deelen JBeekman MUh H-W et al. Genome-wide association study identifies a single major locus contributing to survival into old age; the APOE locus revisitedAging Cell201110686-698. 13. Deelen J, Beekman M, Uh H-W, et al. Genome-wide association study identifies a single major locus contributing to survival into old age; the APOE locus revisited. Aging Cell 2011;10:686–698.
14.
Nebel AKleindorp RCaliebe A et al. A genome-wide association study confirms APOE as the major gene influencing survival in long-lived individualsMech Ageing Dev2011132324-330. 14. Nebel A, Kleindorp R, Caliebe A, et al. A genome-wide association study confirms APOE as the major gene influencing survival in long-lived individuals. Mech Ageing Dev 2011;132:324–330.
15.
Yashin AIWu DQArbeev KGUkraintseva SV. Joint influence of small-effect genetic variants on human longevityAging20102612-620. 15. Yashin AI, Wu DQ, Arbeev KG, Ukraintseva SV. Joint influence of small-effect genetic variants on human longevity. Aging 2010;2:612–620.
16.
Mitnitski ABMogilner AJRockwood K. Accumulation of deficits as a proxy measure of agingScientific World Journal20011323-336. 16. Mitnitski AB, Mogilner AJ, Rockwood K. Accumulation of deficits as a proxy measure of aging. Scientific World Journal. 2001;1:323–336.
17.
Kulminski AYashin AUkraintseva S et al. Accumulation of health disorders as a systemic measure of aging: Findings from the NLTCS dataMech Ageing Dev2006127840-848. 17. Kulminski A, Yashin A, Ukraintseva S, et al. Accumulation of health disorders as a systemic measure of aging: Findings from the NLTCS data. Mech Ageing Dev 2006;127:840–848.
18.
Yashin AIArbeev KGKulminski A et al. Health decline, aging and mortality: How are they related?Biogerontology20078291-302. 18. Yashin AI, Arbeev KG, Kulminski A, et al. Health decline, aging and mortality: How are they related? Biogerontology 2007;8:291–302.
19.
Strehler BLMildvan AS. General theory of mortality and agingScience196013214-21. 19. Strehler BL, Mildvan AS. General theory of mortality and aging. Science 1960;132:14–21.
20.
Vaupel JWYashin AI. Repeated resuscitation: How lifesaving alters life tablesDemography198724123-135. 20. Vaupel JW, Yashin AI. Repeated resuscitation: How lifesaving alters life tables. Demography 1987;24:123–135.
21.
Oeppen JVaupel JW. Broken limits to life expectancyScience20022961029-1031. 21. Oeppen J, Vaupel JW. Broken limits to life expectancy. Science 2002;296:1029–1031.
22.
Finkelstein MS. Lifesaving explains mortality decline with timeMath Biosci2005196187-197. 22. Finkelstein MS. Lifesaving explains mortality decline with time. Math Biosci 2005;196:187–197.
23.
Gavrilov LAGavrilova NSThe Biology of Life Span: A Quantitative ApproachHarwood Academic PublisherNew York1991. 23. Gavrilov LA, Gavrilova NS. The Biology of Life Span: A Quantitative Approach. Harwood Academic Publisher, New York, 1991.
24.
Zheng HYang YLand KC. Heterogeneity in the Strehler–Mildvan general theory of mortality and agingDemography201148267-290. 24. Zheng H, Yang Y, Land KC. Heterogeneity in the Strehler–Mildvan general theory of mortality and aging. Demography 2011;48:267–290.
25.
Yashin AIBegun ASBoiko SI et al. The new trends in survival improvement require a revision of traditional gerontological conceptsExp Gerontol200137157-167. 25. Yashin AI, Begun AS, Boiko SI, et al. The new trends in survival improvement require a revision of traditional gerontological concepts. Exp Gerontol 2001;37:157–167.
26.
Yashin AIBegun ASBoiko SI et al. New age patterns of survival improvement in Sweden: do they characterize changes in individual aging?Mech Ageing Dev2002123637-647. 26. Yashin AI, Begun AS, Boiko SI, et al. New age patterns of survival improvement in Sweden: do they characterize changes in individual aging? Mech Ageing Dev 2002;123:637–647.
27.
Riggs JEMillecchia RJ. Using the Gompertz-Strehler model of aging and mortality to explain mortality trends in industrialized countriesMech Ageing Dev199265217-228. 27. Riggs JE, Millecchia RJ. Using the Gompertz-Strehler model of aging and mortality to explain mortality trends in industrialized countries. Mech Ageing Dev 1992;65:217–228.
28.
Myers GCManton KG. Compression of mortality: Myth or realityGerontologist198424346-353. 28. Myers GC, Manton KG. Compression of mortality: Myth or reality. Gerontologist 1984;24:346–353.
29.
Yashin AIIachine IABegun AS. Mortality modeling: A reviewMathematical Population Studies20008305-332. 29. Yashin AI, Iachine IA, Begun AS. Mortality modeling: A review. Mathematical Population Studies 2000;8:305–332.
30.
Zeng YShen K. Resilience significantly contributes to exceptional longevityCurr Gerontol Geriatr Res20102010525693. 30. Zeng Y, Shen K. Resilience significantly contributes to exceptional longevity. Curr Gerontol Geriatr Res 2010;2010:525693.
31.
Horiuchi SWilmoth JR. Age patterns of the life table aging rate for major causes of death in Japan, 1951–1990J Gerontol A Biol Sci Med Sci199752B67-B77. 31. Horiuchi S, Wilmoth JR. Age patterns of the life table aging rate for major causes of death in Japan, 1951–1990. J Gerontol A Biol Sci Med Sci 1997;52:B67–B77.
32.
Horiuchi SWilmoth JR. Deceleration in the age pattern of mortality at older agesDemography199835391-412. 32. Horiuchi S, Wilmoth JR. Deceleration in the age pattern of mortality at older ages. Demography 1998;35:391–412.
33.
Wilmoth JRHoriuchi S. Rectangularization revisited: Variability of age at death within human populationsDemography199936475-495. 33. Wilmoth JR, Horiuchi S. Rectangularization revisited: Variability of age at death within human populations. Demography 1999;36:475–495.
34.
Port SCBoyle NGHsueh WA et al. The predictive role of blood glucose for mortality in subjects with cardiovascular diseaseAm J Epidemiol2006163342-351. 34. Port SC, Boyle NG, Hsueh WA, et al. The predictive role of blood glucose for mortality in subjects with cardiovascular disease. Am J Epidemiol 2006;163:342–351.
35.
Yashin AIAkushevich IVArbeev KG et al. Insights on aging and exceptional longevity from longitudinal data: Novel findings from the Framingham Heart StudyAge200628363-374. 35. Yashin AI, Akushevich IV, Arbeev KG, et al. Insights on aging and exceptional longevity from longitudinal data: Novel findings from the Framingham Heart Study. Age 2006;28:363–374.
36.
Benetos AZureik MMorcet J et al. A decrease in diastolic blood pressure combined with an increase in systolic blood pressure is associated with a higher cardiovascular mortality in menJ Am Coll Cardiol200035673-680. 36. Benetos A, Zureik M, Morcet J, et al. A decrease in diastolic blood pressure combined with an increase in systolic blood pressure is associated with a higher cardiovascular mortality in men. J Am Coll Cardiol 2000;35:673–680.
37.
Yashin AIArbeev KGAkushevich I et al. Dynamic determinants of longevity and exceptional healthCurr Gerontol Geriatr Res20102010381637. 37. Yashin AI, Arbeev KG, Akushevich I, et al. Dynamic determinants of longevity and exceptional health. Curr Gerontol Geriatr Res 2010;2010:381637.
38.
Barlow REProschan FMathematical Theory of ReliabilityJohn Wiley and Sons, Inc.New York1996. 38. Barlow RE, Proschan F. Mathematical Theory of Reliability. John Wiley and Sons, Inc., New York, 1996.
39.
Fuellen GAdjaye Jde Grey A et al. Bioinformatics in aging research: A workshop reportRejuvenation Res201013763-767. 39. Fuellen G, Adjaye J, de Grey A, et al. Bioinformatics in aging research: A workshop report. Rejuvenation Res 2010;13:763–767.
40.
McGue MVaupel JWHolm NHarvald B. Longevity is moderately heritable in a sample of Danish twins born 1870–1880J Gerontol199348B237-B244. 40. McGue M, Vaupel JW, Holm N, Harvald B. Longevity is moderately heritable in a sample of Danish twins born 1870–1880. J Gerontol 1993;48:B237–B244.
41.
Herskind AMMcGue MHolm NV et al. The heritability of human longevity: A population-based study of 2872 Danish twin pairs born 1870–1900Hum Genet199697319-323. 41. Herskind AM, McGue M, Holm NV, et al. The heritability of human longevity: A population-based study of 2872 Danish twin pairs born 1870–1900. Hum Genet 1996;97:319–323.
42.
Meigs JBShrader PSullivan LM et al. Genotype score in addition to common risk factors for prediction of type 2 diabetesN Engl J Med20083592208-2219. 42. Meigs JB, Shrader P, Sullivan LM, et al. Genotype score in addition to common risk factors for prediction of type 2 diabetes. N Engl J Med 2008;359:2208–2219.
43.
Paynter NPChasman DIPare G et al. Association between a literature-based genetic risk score and cardiovascular events in womenJAMA2010303631-637. 43. Paynter NP, Chasman DI, Pare G, et al. Association between a literature-based genetic risk score and cardiovascular events in women. JAMA. 2010;303:631–637.
44.
Reeves GKTravis RCGreen J et al. Incidence of breast cancer and its subtypes in relation to individual and multiple low-penetrance genetic susceptibility lociJAMA2010304426-434. 44. Reeves GK, Travis RC, Green J, et al. Incidence of breast cancer and its subtypes in relation to individual and multiple low-penetrance genetic susceptibility loci. JAMA 2010;304:426–434.
45.
Ruiz JRGomez-Gallego FSantiago C et al. Is there an optimum endurance polygenic profile?J Physiol (Lond)20095871527-1534. 45. Ruiz JR, Gomez-Gallego F, Santiago C, et al. Is there an optimum endurance polygenic profile? J Physiol (Lond) 2009;587:1527–1534.
46.
Talmud PJHingorani ADCooper JA et al. Utility of genetic and non-genetic risk factors in prediction of type 2 diabetes: Whitehall II prospective cohort studyBr Med J2010340b4838. 46. Talmud PJ, Hingorani AD, Cooper JA, et al. Utility of genetic and non-genetic risk factors in prediction of type 2 diabetes: Whitehall II prospective cohort study. Br Med J 2010;340:b4838.
47.
Evans DMVisscher PMWray NR. Harnessing the information contained within genome-wide association studies to improve individual prediction of complex disease riskHum Mol Genet2009183525-3531. 47. Evans DM, Visscher PM, Wray NR. Harnessing the information contained within genome-wide association studies to improve individual prediction of complex disease risk. Hum Mol Genet 2009;18:3525–3531.
48.
Purcell SMWray NRStone JL et al. Common polygenic variation contributes to risk of schizophrenia and bipolar disorderNature2009460748-752. 48. Purcell SM, Wray NR, Stone JL, et al. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 2009;460:748–752.
Information & Authors
Information
Published In
Copyright
Copyright 2012, Mary Ann Liebert, Inc.
History
Published online: 9 August 2012
Published in print: August 2012
Published ahead of print: 18 May 2012
Accepted: 15 January 2012
Received: 7 October 2011
Authors
Author Disclosure Statement
No competing financial interests exist.
Metrics & Citations
Metrics
Citations
Export Citation
Export citation
Select the format you want to export the citations of this publication.
View Options
Access content
To read the fulltext, please use one of the options below to sign in or purchase access.⚠ Society Access
If you are a member of a society that has access to this content please log in via your society website and then return to this publication.