| "Predicting" parental longevity from offspring endophenotypes: data from the Long Life Family Study (LLFS). | |
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MedLine Citation:
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PMID: 20184914 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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While there is evidence that longevity runs in families, the study of long-lived families is complicated by the fact that longevity-related information is available only for the oldest old, many of whom may be deceased and unavailable for testing, and information on other living family members, primarily descendents, is censored. This situation requires a creative approach for analyzing determinants of longevity in families. There are likely biomarkers that predict an individual's longevity, suggesting the possibility that those biomarkers which are heritable may constitute valuable endophenotypes for exceptional survival. These endophenotypes could be studied in families to identify human longevity genes and elucidate possible mechanisms of their influence on longevity. In this paper, we analyze data collected in the Long Life Family Study (LLFS) investigating whether indicators of physiological state, cognitive functioning and health/well-being among offspring predict longevity in parents. Good predictors can be used as endophenotypes for exceptional survival. Our analyses revealed significant associations between cumulative indices describing physiological state, as well as a number of offspring phenotypes, and parental lifespan, supporting both their familial basis and relevance to longevity. We conclude that the study of endophenotypes within families is a valid approach to the genetics of human longevity. |
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Authors:
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Anatoli I Yashin; Konstantin G Arbeev; Alexander Kulminski; Ingrid Borecki; Kaare Christensen; Michael Barmada; Evan Hadley; Winifred Rossi; Joseph H Lee; Rong Cheng; Irma T Elo |
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Publication Detail:
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Type: Journal Article; Research Support, N.I.H., Extramural Date: 2010-02-23 |
Journal Detail:
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Title: Mechanisms of ageing and development Volume: 131 ISSN: 1872-6216 ISO Abbreviation: Mech. Ageing Dev. Publication Date: 2010 Mar |
Date Detail:
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Created Date: 2010-03-29 Completed Date: 2010-06-29 Revised Date: 2011-08-01 |
Medline Journal Info:
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Nlm Unique ID: 0347227 Medline TA: Mech Ageing Dev Country: Ireland |
Other Details:
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Languages: eng Pagination: 215-22 Citation Subset: IM |
Copyright Information:
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2010 Elsevier Ireland Ltd. All rights reserved. |
Affiliation:
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Duke University, Center for Population Health and Aging, Durham, NC 27708-0408, USA. aiy@duke.edu |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Family
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psychology* Family Relations Health Services Humans Longevity / genetics* Male Parents* Research Survival |
| Grant Support | |
ID/Acronym/Agency:
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5P01AG008761/AG/NIA NIH HHS; R01 AG028259-05/AG/NIA NIH HHS; R01AG028259/AG/NIA NIH HHS; R24 HD044964-07/HD/NICHD NIH HHS; R24 HD044964-08/HD/NICHD NIH HHS; U01AG023712/AG/NIA NIH HHS |
| Comments/Corrections | |
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