Biogerontology

, Volume 17, Issue 1, pp 89–107 | Cite as

How the effects of aging and stresses of life are integrated in mortality rates: insights for genetic studies of human health and longevity

  • Anatoliy I. Yashin
  • Konstantin G. Arbeev
  • Liubov S. Arbeeva
  • Deqing Wu
  • Igor Akushevich
  • Mikhail Kovtun
  • Arseniy Yashkin
  • Alexander Kulminski
  • Irina Culminskaya
  • Eric Stallard
  • Miaozhu Li
  • Svetlana V. Ukraintseva
Review Article

Abstract

Increasing proportions of elderly individuals in developed countries combined with substantial increases in related medical expenditures make the improvement of the health of the elderly a high priority today. If the process of aging by individuals is a major cause of age related health declines then postponing aging could be an efficient strategy for improving the health of the elderly. Implementing this strategy requires a better understanding of genetic and non-genetic connections among aging, health, and longevity. We review progress and problems in research areas whose development may contribute to analyses of such connections. These include genetic studies of human aging and longevity, the heterogeneity of populations with respect to their susceptibility to disease and death, forces that shape age patterns of human mortality, secular trends in mortality decline, and integrative mortality modeling using longitudinal data. The dynamic involvement of genetic factors in (i) morbidity/mortality risks, (ii) responses to stresses of life, (iii) multi-morbidities of many elderly individuals, (iv) trade-offs for diseases, (v) genetic heterogeneity, and (vi) other relevant aging-related health declines, underscores the need for a comprehensive, integrated approach to analyze the genetic connections for all of the above aspects of aging-related changes. The dynamic relationships among aging, health, and longevity traits would be better understood if one linked several research fields within one conceptual framework that allowed for efficient analyses of available longitudinal data using the wealth of available knowledge about aging, health, and longevity already accumulated in the research field.

Keywords

Longitudinal data Genetic heterogeneity Pleiotropy Population aging Quadratic hazard Health of the elderly 

Notes

Acknowledgments

Research reported in this publication was supported by the National Institute on Aging of the National Institutes of Health under Award Numbers R01AG046860, P01AG043352, and P30AG034424. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The Framingham Heart Study is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with Boston University (Contract No. N01-HC-25195). This manuscript was not prepared in collaboration with investigators of the Framingham Heart Study and does not necessarily reflect the opinions or views of the Framingham Heart Study, Boston University, or NHLBI. Funding for SHARe Affymetrix genotyping was provided by NHLBI Contract N02-HL-64278. SHARe Illumina genotyping was provided under an agreement between Illumina and Boston University. The authors thank Debra Fincham for help in preparing this paper for publication.

References

  1. Aalen OO (1994) Effects of frailty in survival analysis. Stat Methods Med Res 3:227–243PubMedCrossRefGoogle Scholar
  2. Aalen OO, Valberg M, Grotmol T, Tretli S (2014) Understanding variation in disease risk: the elusive concept of frailty. Int J Epidemiol. doi: 10.1093/ije/dyu192 PubMedCentralPubMedGoogle Scholar
  3. Abbring JH, Van den Berg GJ (2007) The unobserved heterogeneity distribution in duration analysis. Biometrika 94:87–99. doi: 10.1093/biomet/asm013 CrossRefGoogle Scholar
  4. Abelson PH (1993) Improvements in health care. Science 260:11PubMedCrossRefGoogle Scholar
  5. Akushevich I, Kravchenko J, Ukraintseva S, Arbeev K, Kulminski A, Yashin AI (2013) Morbidity risks among older adults with pre-existing age-related diseases. Exp Gerontol 48:1395–1401. doi: 10.1016/j.exger.2013.09.005 PubMedCentralPubMedCrossRefGoogle Scholar
  6. Alfin-Slater RB (1979) Nutrition and aging: introduction Federation proceedings 38:1993Google Scholar
  7. Allison DB, Faith MS, Heo M, Kotler DP (1997) Hypothesis concerning the U-shaped relation between body mass index and mortality. Am J Epidemiol 146:339–349PubMedCrossRefGoogle Scholar
  8. Arbeev KG et al (2009) Genetic model for longitudinal studies of aging, health, and longevity and its potential application to incomplete data. J Theor Biol 258:103–111. doi: 10.1016/j.jtbi.2009.01.023 PubMedCentralPubMedCrossRefGoogle Scholar
  9. Arbeev KG, Ukraintseva SV, Arbeeva LS, Akushevich I, Kulminski AM, Yashin AI (2011) Evaluation of genotype-specific survival using joint analysis of genetic and non-genetic subsamples of longitudinal data. Biogerontology 12:157–166. doi: 10.1007/s10522-010-9316-1 PubMedCentralPubMedCrossRefGoogle Scholar
  10. Asimit J, Zeggini E (2010) Rare variant association analysis methods for complex traits. Annu Rev Genet 44:293–308. doi: 10.1146/annurev-genet-102209-163421 PubMedCrossRefGoogle Scholar
  11. Atkins JL, Whincup PH, Morris RW, Lennon LT, Papacosta O, Wannamethee SG (2014) Sarcopenic obesity and risk of cardiovascular disease and mortality: a population-based cohort study of older men. J Am Geriatr Soc 62:253–260. doi: 10.1111/jgs.12652 PubMedCrossRefGoogle Scholar
  12. Atzmon G, Rincon M, Schechter CB, Shuldiner AR, Lipton RB, Bergman A, Barzilai N (2006) Lipoprotein genotype and conserved pathway for exceptional longevity in humans. PLoS Biol 4:e113. doi: 10.1371/journal.pbio.0040113 PubMedCentralPubMedCrossRefGoogle Scholar
  13. Aubin-Horth N, Renn SC (2009) Genomic reaction norms: using integrative biology to understand molecular mechanisms of phenotypic plasticity. Mol Ecol 18:3763–3780. doi: 10.1111/j.1365-294X.2009.04313.x PubMedCrossRefGoogle Scholar
  14. Baird RD, Caldas C (2013) Genetic heterogeneity in breast cancer: the road to personalized medicine? BMC Med 11:151. doi: 10.1186/1741-7015-11-151 PubMedCentralPubMedCrossRefGoogle Scholar
  15. Barzilai N, Rennert G (2012) The rationale for delaying aging and the prevention of age-related diseases. Rambam Maimonides Med J 3:e0020. doi: 10.5041/rmmj.10087 PubMedCentralPubMedCrossRefGoogle Scholar
  16. Barzilai N, Huffman DM, Muzumdar RH, Bartke A (2012) The critical role of metabolic pathways in aging. Diabetes 61:1315–1322. doi: 10.2337/db11-1300 PubMedCentralPubMedCrossRefGoogle Scholar
  17. Basu S, Pan W (2011) Comparison of statistical tests for disease association with rare variants. Genet Epidemiol 35:606–619. doi: 10.1002/gepi.20609 PubMedCentralPubMedCrossRefGoogle Scholar
  18. Beekman M et al (2010) Genome-wide association study (GWAS)-identified disease risk alleles do not compromise human longevity. Proc Natl Acad Sci USA 107:18046–18049. doi: 10.1073/pnas.1003540107 PubMedCentralPubMedCrossRefGoogle Scholar
  19. Beltran-Sanchez H, Crimmins EM, Finch CE (2012) Early cohort mortality predicts the rate of aging in the cohort: a historical analysis. J Dev Orig Health Dis 3:380–386. doi: 10.1017/s2040174412000281 PubMedCentralCrossRefGoogle Scholar
  20. Bergman A, Atzmon G, Ye K, MacCarthy T, Barzilai N (2007) Buffering mechanisms in aging: a systems approach toward uncovering the genetic component of aging. PLoS Comput Biol 3:e170. doi: 10.1371/journal.pcbi.0030170 PubMedCentralPubMedCrossRefGoogle Scholar
  21. Bolormaa S et al (2014) A multi-trait, meta-analysis for detecting pleiotropic polymorphisms for stature, fatness and reproduction in beef cattle. PLoS Genet 10:e1004198. doi: 10.1371/journal.pgen.1004198 PubMedCentralPubMedCrossRefGoogle Scholar
  22. Bosma-den Boer MM, van Wetten ML, Pruimboom L (2012) Chronic inflammatory diseases are stimulated by current lifestyle: how diet, stress levels and medication prevent our body from recovering. Nutr Metab. doi: 10.1186/1743-7075-9-32 Google Scholar
  23. Boutitie F, Gueyffier F, Pocock S, Fagard R, Boissel JP (2002) J-shaped relationship between blood pressure and mortality in hypertensive patients: new insights from a meta-analysis of individual-patient data. Ann Intern Med 136:438–448PubMedCrossRefGoogle Scholar
  24. Broer L et al (2015) GWAS of longevity in CHARGE consortium confirms APOE and FOXO3 candidacy. J Gerontol A Biol Sci Med Sci 70:110–118. doi: 10.1093/gerona/glu166 PubMedCentralPubMedCrossRefGoogle Scholar
  25. Bunker JP (2001) The role of medical care in contributing to health improvements within societies. Int J Epidemiol 30:1260–1263PubMedCrossRefGoogle Scholar
  26. Butler RN et al (2008) New model of health promotion and disease prevention for the 21st century. BMJ 337:a399PubMedCrossRefGoogle Scholar
  27. Cai D et al (2015) A correlation between diet and longevity characterization by means of element profiles in healthy people over 80 years from a chinese longevous region. Biol Trace Elem Res 165(1):18–29. doi: 10.1007/s12011-015-0233-7 PubMedCrossRefGoogle Scholar
  28. Calabrese V, Cornelius C, Cuzzocrea S, Iavicoli I, Rizzarelli E, Calabrese EJ (2011) Hormesis, cellular stress response and vitagenes as critical determinants in aging and longevity. Mol Aspects Med 32:279–304. doi: 10.1016/j.mam.2011.10.007 PubMedCrossRefGoogle Scholar
  29. Carey JR, Liedo P, Orozco D, Vaupel JW (1992) Slowing of mortality rates at older ages in large medfly cohorts. Science 258:457–461PubMedCrossRefGoogle Scholar
  30. Carnes BA, Olshansky SJ (2001) Heterogeneity and its biodemographic implications for longevity and mortality. Exp Gerontol 36:419–430PubMedCrossRefGoogle Scholar
  31. Chavali S, Barrenas F, Kanduri K, Benson M (2010) Network properties of human disease genes with pleiotropic effects. BMC Syst Biol 4:78. doi: 10.1186/1752-0509-4-78 PubMedCentralPubMedCrossRefGoogle Scholar
  32. Chedraui P, Perez-Lopez FR (2013) Nutrition and health during mid-life: searching for solutions and meeting challenges for the aging population. Climacteric 16(Suppl 1):85–95. doi: 10.3109/13697137.2013.802884 PubMedCrossRefGoogle Scholar
  33. Colgrove J (2002) The McKeown thesis: a historical controversy and its enduring influence. Am J Public Health 92:725–729PubMedCentralPubMedCrossRefGoogle Scholar
  34. Crous-Bou M et al (2014) Mediterranean diet and telomere length in Nurses’ Health Study: population based cohort study. BMJ 349:g6674. doi: 10.1136/bmj.g6674 PubMedCentralPubMedCrossRefGoogle Scholar
  35. Cypser JR, Johnson TE (2002) Multiple stressors in Caenorhabditis elegans induce stress hormesis and extended longevity. J Gerontol A Biol Sci Med Sci 57:B109–B114PubMedCrossRefGoogle Scholar
  36. de Benedictis G et al (1998) Age-related changes of the 3′APOB-VNTR genotype pool in ageing cohorts. Ann Hum Genet 62:115–122. doi: 10.1046/j.1469-1809.1998.6220115.x PubMedCrossRefGoogle Scholar
  37. de Magalhaes JP (2014) Why genes extending lifespan in model organisms have not been consistently associated with human longevity and what it means to translation research. Cell Cycle 13:2671–2673. doi: 10.4161/15384101.2014.950151 PubMedCentralPubMedCrossRefGoogle Scholar
  38. Deelen J et al (2014) Genome-wide association meta-analysis of human longevity identifies a novel locus conferring survival beyond 90 years of age. Hum Mol Genet 23:4420–4432. doi: 10.1093/hmg/ddu139 PubMedCentralPubMedCrossRefGoogle Scholar
  39. Doubal S, Klemera P (1990) Influence of aging rate change on mortality curves. Mech Ageing Dev 54:75–85PubMedCrossRefGoogle Scholar
  40. Economos AC (1982) Rate of aging, rate of dying and the mechanism of mortality. Arch Gerontol Geriatr 1:3–27PubMedCrossRefGoogle Scholar
  41. Eichler EE, Flint J, Gibson G, Kong A, Leal SM, Moore JH, Nadeau JH (2010) Missing heritability and strategies for finding the underlying causes of complex disease. Nat Rev Genet 11:446–450. doi: 10.1038/nrg2809 PubMedCentralPubMedCrossRefGoogle Scholar
  42. Epel ES, Lithgow GJ (2014) Stress biology and aging mechanisms: toward understanding the deep connection between adaptation to stress and longevity. J Gerontol A Biol Sci Med Sci 69(Suppl 1):S10–S16. doi: 10.1093/gerona/glu055 PubMedCentralPubMedCrossRefGoogle Scholar
  43. Evert J, Lawler E, Bogan H, Perls T (2003) Morbidity profiles of centenarians: survivors, delayers, and escapers. J Gerontol A Biol Sci Med Sci 58:232–237PubMedCrossRefGoogle Scholar
  44. Feng T, Zhu X (2012) Detecting rare variants. Methods Mol Biol 850:453–464. doi: 10.1007/978-1-61779-555-8_24 PubMedCrossRefGoogle Scholar
  45. Feng S et al (2015) Methods for Association Analysis and Meta-Analysis of Rare Variants in Families. Genet Epidemiol. doi: 10.1002/gepi.21892 PubMedCentralGoogle Scholar
  46. Flatt T (2014) Plasticity of lifespan: a reaction norm perspective. Proc Nutr Soc 73:532–542. doi: 10.1017/s0029665114001141 PubMedCrossRefGoogle Scholar
  47. Goh KI, Cusick ME, Valle D, Childs B, Vidal M, Barabasi AL (2007) The human disease network. Proc Natl Acad Sci USA 104:8685–8690. doi: 10.1073/pnas.0701361104 PubMedCentralPubMedCrossRefGoogle Scholar
  48. Goldman DP, Cutler D, Rowe JW, Michaud PC, Sullivan J, Peneva D, Olshansky SJ (2013) Substantial health and economic returns from delayed aging may warrant a new focus for medical research. Health Aff 32:1698–1705. doi: 10.1377/hlthaff.2013.0052 CrossRefGoogle Scholar
  49. Hamerman D (2010) Can biogerontologists and geriatricians unite to apply aging science to health care in the decade ahead? J Gerontol A Biol Sci Med Sci 65:1193–1197. doi: 10.1093/gerona/glq117 PubMedCrossRefGoogle Scholar
  50. Heller DA, Ahern FM, Stout JT, McClearn GE (1998) Mortality and biomarkers of aging in heterogeneous stock (HS) mice. J Gerontol A Biol Sci Med Sci 53:B217–B230PubMedCrossRefGoogle Scholar
  51. Hougaard P (1995) Frailty models for survival data. Lifetime Data Anal 1:255–273PubMedCrossRefGoogle Scholar
  52. Hougaard P (1999) Multi-state models: a review. Lifetime Data Anal 5:239–264PubMedCrossRefGoogle Scholar
  53. Hougaard P, Myglegaard P, Borch-Johnsen K (1994) Heterogeneity models of disease susceptibility, with application to diabetic nephropathy. Biometrics 50:1178–1188PubMedCrossRefGoogle Scholar
  54. Jain KK (2002) Personalized medicine Curr Opin Mol Ther 4:548–558PubMedGoogle Scholar
  55. Jazwinski SM (2002) Biological aging research today: potential, peeves, and problems. Exp Gerontol 37:1141–1146PubMedCrossRefGoogle Scholar
  56. Jazwinski SM (2005) The retrograde response links metabolism with stress responses, chromatin-dependent gene activation, and genome stability in yeast aging. Gene 354:22–27. doi: 10.1016/j.gene.2005.03.040 PubMedCrossRefGoogle Scholar
  57. Karlamangla AS, Singer BH, Seeman TE (2006) Reduction in allostatic load in older adults is associated with lower all-cause mortality risk: MacArthur studies of successful aging. Psychosom Med 68:500–507. doi: 10.1097/01.psy.0000221270.93985.82 PubMedCrossRefGoogle Scholar
  58. Kesteloot H (1993) Nutrition and life expectancy of populations. Acta Cardiol 48:441–442PubMedGoogle Scholar
  59. Kiefte-de Jong H, Mathers JC, Franco OH (2014) Nutrition and healthy ageing: the key ingredients. Proc Nutr Soc 73:249–259. doi: 10.1017/s0029665113003881 PubMedCrossRefGoogle Scholar
  60. Kirkwood TB (2015) Deciphering death: a commentary on Gompertz (1825) ‘On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies’. Philos Trans R Soc Lond B Biol Sci. doi: 10.1098/rstb.2014.0379 PubMedCentralPubMedGoogle Scholar
  61. Kirkwood TL, Kapahi P, Shanley DP (2000) Evolution, stress, and longevity. J Anat 197(4):587–590PubMedCentralPubMedCrossRefGoogle Scholar
  62. Kulminski AM, Arbeev KG, Kulminskaya IV, Ukraintseva SV, Land K, Akushevich I, Yashin AI (2008) Body mass index and nine-year mortality in disabled and nondisabled older U.S. Individuals. J Am Geriatr Soc 56:105–110. doi: 10.1111/j.1532-5415.2007.01494.x PubMedCrossRefGoogle Scholar
  63. Kulminski AM et al (2011) Trade-off in the effects of the apolipoprotein E polymorphism on the ages at onset of CVD and cancer influences human lifespan. Aging Cell 10:533–541. doi: 10.1111/j.1474-9726.2011.00689.x PubMedCentralPubMedCrossRefGoogle Scholar
  64. Kuzuya M, Enoki H, Iwata M, Hasegawa J, Hirakawa Y (2008) J-shaped relationship between resting pulse rate and all-cause mortality in community-dwelling older people with disabilities. J Am Geriatr Soc 56:367–368PubMedCrossRefGoogle Scholar
  65. Le Bourg E (2009) Hormesis, aging and longevity. Biochim Biophys Acta 1790:1030–1039. doi: 10.1016/j.bbagen.2009.01.004 PubMedCrossRefGoogle Scholar
  66. Lee M, Ha ID, Lee Y (2014a) Frailty modeling for clustered competing risks data with missing cause of failure. Stat Methods Med Res. doi: 10.1177/0962280214545639 PubMedCentralGoogle Scholar
  67. Lee S, Abecasis GR, Boehnke M, Lin X (2014b) Rare-variant association analysis: study designs and statistical tests. Am J Hum Genet 95:5–23. doi: 10.1016/j.ajhg.2014.06.009 PubMedCentralPubMedCrossRefGoogle Scholar
  68. Lewington S, Clarke R, Qizilbash N, Peto R, Collins R (2002) Age-specific relevance of usual blood pressure to vascular mortality: a meta-analysis of individual data for one million adults in 61 prospective studies. Lancet 360:1903–1913PubMedCrossRefGoogle Scholar
  69. Li T, Anderson JJ (2015) The Strehler–Mildvan correlation from the perspective of a two-process vitality model. Popul Stud 69:91–104. doi: 10.1080/00324728.2014.992358 CrossRefGoogle Scholar
  70. Li T, Yang YC, Anderson JJ (2013) Mortality increase in late-middle and early-old age: heterogeneity in death processes as a new explanation. Demography 50:1563–1591. doi: 10.1007/s13524-013-0222-4 PubMedCentralPubMedCrossRefGoogle Scholar
  71. Link BG, Phelan JC (2002) McKeown and the idea that social conditions are fundamental causes of disease. Am J Public Health 92:730–732PubMedCentralPubMedCrossRefGoogle Scholar
  72. Lithgow GJ, Walker GA (2002) Stress resistance as a determinate of C. elegans lifespan. Mech Ageing Dev 123:765–771PubMedCrossRefGoogle Scholar
  73. Lund J, Tedesco P, Duke K, Wang J, Kim SK, Johnson TE (2002) Transcriptional profile of aging in C-elegans. Curr Biol 12:1566–1573PubMedCrossRefGoogle Scholar
  74. Lunetta KL et al (2007) Genetic correlates of longevity and selected age-related phenotypes: a genome-wide association study in the Framingham Study. BMC Med Genet 8(Suppl 1):S13PubMedCentralPubMedCrossRefGoogle Scholar
  75. Mackenbach JP (1996) The contribution of medical care to mortality decline: McKeown revisited. J Clin Epidemiol 49:1207–1213PubMedCrossRefGoogle Scholar
  76. MacRae CA, Vasan RS (2011) Next-generation genome-wide association studies: time to focus on phenotype? Circ Cardiovasc Genet 4:334–336. doi: 10.1161/CIRCGENETICS.111.960765 PubMedCentralPubMedCrossRefGoogle Scholar
  77. Maijo M, Clements SJ, Ivory K, Nicoletti C, Carding SR (2014) Nutrition, diet and immunosenescence. Mech Ageing Dev 136–137:116–128. doi: 10.1016/j.mad.2013.12.003 PubMedCrossRefGoogle Scholar
  78. Manton KG, Yashin AI (2000) Mechanisms of aging and mortality: a search for new paradigms. Odense Monograph on Population Aging No. 7. Odense University Press, OdenseGoogle Scholar
  79. Martin GM, Bergman A, Barzilai N (2007) Genetic determinants of human health span and life span: progress and new opportunities. PLoS Genet 3:e125PubMedCentralPubMedCrossRefGoogle Scholar
  80. Mazza A, Zamboni S, Rizzato E, Pessina AC, Tikhonoff V, Schiavon L, Casiglia E (2007) Serum uric acid shows a J-shaped trend with coronary mortality in non-insulin-dependent diabetic elderly people. The CArdiovascular STudy in the ELderly (CASTEL). Acta Diabetol 44:99–105. doi: 10.1007/s00592-007-0249-3 PubMedCrossRefGoogle Scholar
  81. McKeown T, Record RG, Turner RD (1975) An interpretation of the decline of mortality in England and Wales during the twentieth century. Popul Stud 29:391–422CrossRefGoogle Scholar
  82. Miller RA (2009) “Dividends” from research on aging–can biogerontologists, at long last, find something useful to do? J Gerontol A Biol Sci Med Sci 64:157–160. doi: 10.1093/gerona/gln062 PubMedCrossRefGoogle Scholar
  83. Mills MG, Greenwood AK, Peichel CL (2014) Pleiotropic effects of a single gene on skeletal development and sensory system patterning in sticklebacks. EvoDevo 5:5. doi: 10.1186/2041-9139-5-5 PubMedCentralPubMedCrossRefGoogle Scholar
  84. Morris BJ et al (2014) Genetic analysis of TOR complex gene variation with human longevity: a nested case–control study of American men of Japanese ancestry. J Gerontol A Biol Sci Med Sci. doi: 10.1093/gerona/glu021 PubMedCentralGoogle Scholar
  85. Newman AB et al (2010) 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 65:478–487. doi: 10.1093/gerona/glq028 PubMedCrossRefGoogle Scholar
  86. Niculescu MD, Lupu DS (2011) Nutritional influence on epigenetics and effects on longevity. Curr Opin Clin Nutr Metab Care 14:35–40. doi: 10.1097/MCO.0b013e328340ff7c PubMedCrossRefGoogle Scholar
  87. Nussey DH, Wilson AJ, Brommer JE (2007) The evolutionary ecology of individual phenotypic plasticity in wild populations. J Evol Biol 20:831–844. doi: 10.1111/j.1420-9101.2007.01300.x PubMedCrossRefGoogle Scholar
  88. Okumiya K et al (1999) A U-shaped association between home systolic blood pressure and four-year mortality in community-dwelling older men. J Am Geriatr Soc 47:1415–1421PubMedCrossRefGoogle Scholar
  89. Olshansky SJ, Perry D, Miller RA, Butler RN (2007) Pursuing the longevity dividend: scientific goals for an aging world. Ann N Y Acad Sci 1114:11–13. doi: 10.1196/annals.1396.050 PubMedCrossRefGoogle Scholar
  90. Palatini P (1999) Need for a revision of the normal limits of resting heart rate. Hypertension 33:622–625PubMedCrossRefGoogle Scholar
  91. Parsons PA (1996) The limit to human longevity: an approach through a stress theory of ageing. Mech Ageing Dev 87:211–218PubMedCrossRefGoogle Scholar
  92. Parsons PA (2002) Life span: does the limit to survival depend upon metabolic efficiency under stress? Biogerontology 3:233–241PubMedCrossRefGoogle Scholar
  93. Parsons PA (2007) The ecological stress theory of aging and hormesis: an energetic evolutionary model. Biogerontology 8:233–242. doi: 10.1007/s10522-007-9080-z PubMedCrossRefGoogle Scholar
  94. Protogerou AD et al (2007) Diastolic blood pressure and mortality in the elderly with cardiovascular disease. Hypertension 50:172–180PubMedCrossRefGoogle Scholar
  95. Riggs JE (1992) Aging and mortality: manifestations of natural ‘non-selection’. Mech Ageing Dev 62:127–135PubMedCrossRefGoogle Scholar
  96. Rose G et al (2001) Paradoxes in longevity: sequence analysis of mtDNA haplogroup J in centenarians. Eur J Hum Genet 9:701–707. doi: 10.1038/sj.ejhg.5200703 PubMedCrossRefGoogle Scholar
  97. Savory FR, Benton TG, Varma V, Hope IA, Sait SM (2014) Stressful environments can indirectly select for increased longevity. Ecol Evol 4:1176–1185. doi: 10.1002/ece3.1013 PubMedCentralPubMedCrossRefGoogle Scholar
  98. Scheiner SM, Holt RD (2012) The genetics of phenotypic plasticity. X. Variation versus uncertainty. Ecol Evol 2:751–767. doi: 10.1002/ece3.217 PubMedCentralPubMedCrossRefGoogle Scholar
  99. Seeman TE, McEwen BS, Rowe JW, Singer BH (2001) Allostatic load as a marker of cumulative biological risk: MacArthur studies of successful aging. Proc Natl Acad Sci USA 98:4770–4775PubMedCentralPubMedCrossRefGoogle Scholar
  100. Semenchenko GV, Khazaeli AA, Curtsinger JW, Yashin AI (2004) Stress resistance declines with age: analysis of data from a survival experiment with Drosophila melanogaster. Biogerontology 5:17–30PubMedCrossRefGoogle Scholar
  101. Shega JW, Dale W, Andrew M, Paice J, Rockwood K, Weiner DK (2012) Persistent pain and frailty: a case for homeostenosis. J Am Geriatr Soc 60:113–117. doi: 10.1111/j.1532-5415.2011.03769.x PubMedCentralPubMedCrossRefGoogle Scholar
  102. Sisodia S, Singh BN (2012) Experimental evidence for nutrition regulated stress resistance in Drosophila ananassae. PLoS One 7:e46131. doi: 10.1371/journal.pone.0046131 PubMedCentralPubMedCrossRefGoogle Scholar
  103. Solovieff N, Cotsapas C, Lee PH, Purcell SM, Smoller JW (2013) Pleiotropy in complex traits: challenges and strategies. Nat Rev Genet 14:483–495. doi: 10.1038/nrg3461 PubMedCentralPubMedCrossRefGoogle Scholar
  104. Strehler BL, Mildvan AS (1960) General theory of mortality and aging Science 132:14–21PubMedGoogle Scholar
  105. Thinnes FP (2012) Why cancer survivors have a lower risk of Alzheimer disease. MGM 107:630–631. doi: 10.1016/j.ymgme.2012.06.016 CrossRefGoogle Scholar
  106. Tremolizzo L, Rodriguez-Menendez V, Brighina L, Ferrarese C (2006) Is the inverse association between Alzheimer’s disease and cancer the result of a different propensity to methylate DNA? Med Hypotheses 66:1251–1252. doi: 10.1016/j.mehy.2005.12.022 PubMedCrossRefGoogle Scholar
  107. Troiano RP, Frongillo EA, Sobal J, Levitsky DA (1996) The relationship between body weight and mortality: a quantitative analysis of combined information from existing studies. Int J Obesity 20:63–75Google Scholar
  108. Troncale JA (1996) The aging process: physiologic changes and pharmacologic implications. Postgrad Med 99(111–114):120–122Google Scholar
  109. Ukraintseva SV et al (2010) Trade-offs between cancer and other diseases: do they exist and influence longevity? Rejuvenation Res 13:387–396. doi: 10.1089/rej.2009.0941 PubMedCentralPubMedCrossRefGoogle Scholar
  110. Ukraintseva S, Arbeev K, Kulminski A, Akushevich I, Wu D, Yashin A (2012) Genetic trade-offs may explain some paradoxes of genetics of human longevity. Paper presented at the ASHG 2012 annual meeting, San Francisco, November 6–10, 2012Google Scholar
  111. van Vliet-Ostaptchouk JV et al (2013) Pleiotropic effects of obesity-susceptibility loci on metabolic traits: a meta-analysis of up to 37,874 individuals. Diabetologia 56:2134–2146. doi: 10.1007/s00125-013-2985-y PubMedCrossRefGoogle Scholar
  112. Vaupel JW, Yashin AI (1985) Heterogeneity’s ruses: some surprising effects of selection on population dynamics. Am Stat 39:176–185PubMedGoogle Scholar
  113. Vaupel JW, Yashin AI (1987) Repeated resuscitation: how lifesaving alters life tables. Demography 24:123–135PubMedCrossRefGoogle Scholar
  114. Vaupel JW, Manton KG, Stallard E (1979) The impact of heterogeneity in individual frailty on the dynamics of mortality. Demography 16:439–454PubMedCrossRefGoogle Scholar
  115. Vaupel JW et al (1998) Biodemographic trajectories of longevity. Science 280:855–860PubMedCrossRefGoogle Scholar
  116. Vermeulen CJ, Loeschcke V (2007) Longevity and the stress response in Drosophila. Exp Gerontol 42:153–159. doi: 10.1016/j.exger.2006.09.014 PubMedCrossRefGoogle Scholar
  117. Walter S et al (2011) A genome-wide association study of aging. Neurobiol Aging. doi: 10.1016/j.neurobiolaging.2011.05.026 PubMedCentralGoogle Scholar
  118. Warner H et al (2005) Science fact and the SENS agenda. What can we reasonably expect from ageing research? EMBO Rep 6:1006–1008. doi: 10.1038/sj.embor.7400555 PubMedCentralPubMedCrossRefGoogle Scholar
  119. Westin S, Heath I (2005) Thresholds for normal blood pressure and serum cholesterol. Br Med J 330:1461–1462CrossRefGoogle Scholar
  120. Wienke A (2010) Frailty models in survival analysis. Chapman & Hall/CRC, Boca RatonCrossRefGoogle Scholar
  121. Witteman JCM, Grobbee DE, Valkenburg HA, Vanhemert AM, Stijnen T, Burger H, Hofman A (1994) J-shaped relation between change in diastolic blood pressure and progression of aortic atherosclerosis. Lancet 343:504–507PubMedCrossRefGoogle Scholar
  122. Woodbury MA, Manton KG (1977) A random-walk model of human mortality and aging. Theor Popul Biol 11:37–48PubMedCrossRefGoogle Scholar
  123. Wu D, Cypser JR, Yashin AI, Johnson TE (2008) The U-shaped response of initial mortality in Caenorhabditis elegans to mild heat shock: does it explain recent trends in human mortality? J GerontologySer A 63:660–668CrossRefGoogle Scholar
  124. Yashin AI, Iachine IA (1995) Survival of related individuals: an extension of some fundamental results of heterogeneity analysis. Math Popul Stud 5:321–377PubMedCrossRefGoogle Scholar
  125. Yashin AI, Iachine IA (1999a) Dependent hazards in multivariate survival problems. J Multivar Anal 71:241–261. doi: 10.1006/jmva.1999.1848 CrossRefGoogle Scholar
  126. Yashin AI, Iachine IA (1999b) What difference does the dependence between durations make? Insights for population studies of aging. Lifetime Data Anal 5:5–22PubMedCrossRefGoogle Scholar
  127. Yashin AI, Jazwinski SM (2014) Aging and health: a systems biology perspective. Cytogenet Genome Res 144:77–154CrossRefGoogle Scholar
  128. Yashin AI, Manton KG, Stallard E (1986) Evaluating the effects of observed and unobserved diffusion processes in survival analysis of longitudinal data. Math Model 7:1353–1363. doi: 10.1016/0270-0255(86)90085-0 CrossRefGoogle Scholar
  129. Yashin AI, Vaupel JW, Iachine IA (1994) A duality in aging: the equivalence of mortality models based on radically different concepts. Mech Ageing Dev 74:1–14PubMedCrossRefGoogle Scholar
  130. Yashin AI, Vaupel JW, Iachine IA (1995) Correlated individual frailty: an advantageous approach to survival analysis of bivariate data. Math Popul Stud 5(145–159):183. doi: 10.1080/08898489509525394 Google Scholar
  131. Yashin AI et al (1999) Genes, demography, and life span: the contribution of demographic data in genetic studies on aging and longevity. Am J Hum Genet 65:1178–1193. doi: 10.1086/302572 PubMedCentralPubMedCrossRefGoogle Scholar
  132. Yashin AI et al (2000) Genes and longevity: lessons from studies of centenarians. J Gerontol A Biol Sci Med Sci 55:B319–B328PubMedCrossRefGoogle Scholar
  133. Yashin AI, Begun AS, Boiko SI, Ukraintseva SV, Oeppen J (2001a) The new trends in survival improvement require a revision of traditional gerontological concepts. Exp Gerontol 37:157–167PubMedCrossRefGoogle Scholar
  134. Yashin AI et al (2001b) Have the oldest old adults ever been frail in the past? A hypothesis that explains modern trends in survival. J Gerontol A Biol Sci Med Sci 56:B432–B442PubMedCrossRefGoogle Scholar
  135. Yashin AI, Begun AS, Boiko SI, Ukraintseva SV, Oeppen J (2002a) New age patterns of survival improvement in Sweden: do they characterize changes in individual aging? Mech Ageing Dev 123:637–647PubMedCrossRefGoogle Scholar
  136. Yashin AI, Ukraintseva SV, Boiko SI, Arbeev KG (2002b) Individual aging and mortality rate: how are they related? Soc Biol 49:206–217PubMedGoogle Scholar
  137. Yashin AI, Arbeev KG, Ukraintseva SV (2007) The accuracy of statistical estimates in genetic studies of aging can be significantly improved. Biogerontology 8:243–255. doi: 10.1007/s10522-006-9072-4 PubMedCentralPubMedCrossRefGoogle Scholar
  138. Yashin AI, Ukraintseva SV, Akushevich IV, Arbeev KG, Kulminski A, Akushevich L (2009) Trade-off between cancer and aging: what role do other diseases play? Evidence from experimental and human population studies. Mech Ageing Dev 130:98–104. doi: 10.1016/j.mad.2008.03.006 PubMedCentralPubMedCrossRefGoogle Scholar
  139. Yashin AI, Akushevich I, Arbeev KG, Kulminski A, Ukraintseva S (2011) Joint analysis of health histories, physiological states, and survival. Math Popul Stud 18:207–233CrossRefGoogle Scholar
  140. Yashin AI, Arbeev KG, Akushevich I, Kulminski A, Ukraintseva SV, Stallard E, Land KC (2012a) The quadratic hazard model for analyzing longitudinal data on aging, health, and the life span. Phys Life Rev 9:177–188. doi: 10.1016/j.plrev.2012.05.002 PubMedCentralPubMedCrossRefGoogle Scholar
  141. Yashin AI, Wu D, Arbeev KG, Stallard E, Land KC, Ukraintseva SV (2012b) How genes influence life span: the biodemography of human survival. Rejuvenation Res 15:374–380. doi: 10.1089/rej.2011.1290 PubMedCentralPubMedCrossRefGoogle Scholar
  142. Yashin AI et al (2013a) How lifespan associated genes modulate aging changes: lessons from analysis of longitudinal data. Front Genet 4:3. doi: 10.3389/fgene.2013.00003 PubMedCentralPubMedGoogle Scholar
  143. Yashin AI et al (2013b) How the quality of GWAS of human lifespan and health span can be improved. Front Genet. doi: 10.3389/fgene.2013.00125 Google Scholar
  144. Yashin AI et al (2014) Genetic structures of population cohorts change with increasing age: Implications for genetic analyses of human aging and life span. Ann Gerontol Geriatr Res 1:1020PubMedCentralPubMedGoogle Scholar
  145. Zajacova A, Goldman N, Rodriguez G (2009) Unobserved heterogeneity can confound the effect of education on mortality. Math Popul Stud 16:153–173. doi: 10.1080/08898480902790528 PubMedCentralPubMedCrossRefGoogle Scholar
  146. Zheng H, Yang Y, Land KC (2011) Heterogeneity in the Strehler-Mildvan general theory of mortality and aging. Demography 48:267–290. doi: 10.1007/s13524-011-0013-8 PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Anatoliy I. Yashin
    • 1
    • 3
  • Konstantin G. Arbeev
    • 1
  • Liubov S. Arbeeva
    • 1
  • Deqing Wu
    • 1
  • Igor Akushevich
    • 1
  • Mikhail Kovtun
    • 1
  • Arseniy Yashkin
    • 1
  • Alexander Kulminski
    • 1
  • Irina Culminskaya
    • 1
  • Eric Stallard
    • 1
  • Miaozhu Li
    • 1
  • Svetlana V. Ukraintseva
    • 1
    • 2
  1. 1.The Biodemography of Aging Research Unit, Social Science Research InstituteDuke UniversityDurhamUSA
  2. 2.The Biodemography of Aging Research Unit, Social Science Research InstituteDuke UniversityDurhamUSA
  3. 3.The Biodemography of Aging Research Unit, Social Science Research InstituteDuke UniversityDurhamUSA

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