How Genes Influence Life Span: The Biodemography of Human Survival

Yashin, Anatoliy I.; Wu, Deqing; Arbeev, Konstantin G.; Stallard, Eric; Land, Kenneth C.; Ukraintseva, Svetlana V.

doi:10.1089/rej.2011.1290

Cited by 27 publications

(19 citation statements)

References 50 publications

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“…Paradoxically, these seemingly sensible strategies pose translational difficulties. The difficulty with studying aging in old humans is that many of them already have age-related diseases (9)(10)(11). Age-related changes to physiology accumulate from early life, affecting organ systems years before disease diagnosis (12)(13)(14)(15).…”

mentioning

confidence: 99%

Quantification of biological aging in young adults

Belsky

Caspi

Houts

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

729

633

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Antiaging therapies show promise in model organism research. Translation to humans is needed to address the challenges of an aging global population. Interventions to slow human aging will need to be applied to still-young individuals. However, most human aging research examines older adults, many with chronic disease. As a result, little is known about aging in young humans. We studied aging in 954 young humans, the Dunedin Study birth cohort, tracking multiple biomarkers across three time points spanning their third and fourth decades of life. We developed and validated two methods by which aging can be measured in young adults, one cross-sectional and one longitudinal. Our longitudinal measure allows quantification of the pace of coordinated physiological deterioration across multiple organ systems (e.g., pulmonary, periodontal, cardiovascular, renal, hepatic, and immune function). We applied these methods to assess biological aging in young humans who had not yet developed age-related diseases. Young individuals of the same chronological age varied in their "biological aging" (declining integrity of multiple organ systems). Already, before midlife, individuals who were aging more rapidly were less physically able, showed cognitive decline and brain aging, selfreported worse health, and looked older. Measured biological aging in young adults can be used to identify causes of aging and evaluate rejuvenation therapies.biological aging | cognitive aging | aging | healthspan | geroscience B y 2050, the world population aged 80 y and above will more than triple, approaching 400 million individuals (1, 2). As the population ages, the global burden of disease and disability is rising (3). From the fifth decade of life, advancing age is associated with an exponential increase in burden from many different chronic conditions (Fig. 1). The most effective means to reduce disease burden and control costs is to delay this progression by extending healthspan, years of life lived free of disease and disability (4). A key to extending healthspan is addressing the problem of aging itself (5-8).At present, much research on aging is being carried out with animals and older humans. Paradoxically, these seemingly sensible strategies pose translational difficulties. The difficulty with studying aging in old humans is that many of them already have age-related diseases (9-11). Age-related changes to physiology accumulate from early life, affecting organ systems years before disease diagnosis (12-15). Thus, intervention to reverse or delay the march toward age-related diseases must be scheduled while people are still young (16). Early interventions to slow aging can be tested in model organisms (17,18). The difficulty with these nonhuman models is that they do not typically capture the complex multifactorial risks and exposures that shape human aging. Moreover, whereas animals' brief lives make it feasible to study animal aging in the laboratory, humans' lives span many years. A solution is to study human aging in the first half of ...

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mentioning

confidence: 99%

Quantification of biological aging in young adults

Belsky

Caspi

Houts

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

729

633

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“…Some recent studies have shown the promise of this approach by examining how the genetic variants would affect mortality rate and lifespan. Yashin et al (2012), for example, employed the Strehler and Mildvan (SM) theory to explain the shape of mortality trajectories of population subgroups with different numbers of longevity alleles. In this pioneering work, they hypothesized that each longevity allele contributed to an increase in robustness and resistance to stress and thus the number of longevity alleles affected mortality risk through its influence on the initial survival capacity (i.e., vitality) of an individual.…”

Section: Discussionmentioning

confidence: 99%

Mortality Increase in Late-Middle and Early-Old Age: Heterogeneity in Death Processes as a New Explanation

Yang²,

Anderson

2013

Demography

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Deviations from the Gompertz law of exponential mortality increases in late-middle and early-old age are commonly neglected in overall mortality analyses. In this study, we examined mortality increase patterns between ages 40 and 85 in 16 low-mortality countries and demonstrated sex differences in these patterns, which also changed across period and cohort. These results suggest that the interaction between aging and death is more complicated than what is usually assumed from the Gompertz law and also challenge existing biodemographic hypotheses about the origin and mechanisms of sex differences in mortality. We propose a two-mortality model that explains these patterns as the change in the composition of intrinsic and extrinsic death rates with age. We show that the age pattern of overall mortality and the population heterogeneity therein are possibly generated by multiple dynamics specified by a two-mortality model instead of a uniform process throughout most adult ages.

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“…Genetic linkage studies for longevity and several other studies showing an association between human longevity and single nucleotide polymorphisms (SNPs) in a variety of genes in various biological pathways, including heat shock response, mitochondrial functions, immune response, cholesterol metabolism, and others (Singh et al, 2004;Rattan and Singh, 2009;Yashin et al, 2012;Yashin et al, 2013). An analysis of the various functions of the genes associated with aging and longevity shows that these genes cover a wide range of biochemical pathways, such as energy metabolism, kinases, kinase receptors, transcription factors, DNA helicases, membrane glucosidases, GTP-binding protein coupled receptors, chaperones, and cell cycle check point pathways.…”

Section: Genetics Post-genetics and Epigenetics Of Agingmentioning

confidence: 99%

Molecular Gerontology

Rattan¹

2014

Omega-3 Fatty Acids in Brain and Neurological Health

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How Genes Influence Life Span: The Biodemography of Human Survival

Cited by 27 publications

References 50 publications

Quantification of biological aging in young adults

Quantification of biological aging in young adults

Mortality Increase in Late-Middle and Early-Old Age: Heterogeneity in Death Processes as a New Explanation

Molecular Gerontology

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