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Age trajectories of physiological indices in relation to healthy life course.

https://arctichealth.org/en/permalink/ahliterature101888
Source
Mech Ageing Dev. 2011 Mar;132(3):93-102
Publication Type
Article
Date
Mar-2011
Author
Konstantin G Arbeev
Svetlana V Ukraintseva
Igor Akushevich
Alexander M Kulminski
Liubov S Arbeeva
Lucy Akushevich
Irina V Culminskaya
Anatoliy I Yashin
Author Affiliation
Centre for Population Health and Aging, Duke University, Department of Sociology, Durham, NC 27708-0408, USA. konstantin.arbeev@duke.edu
Source
Mech Ageing Dev. 2011 Mar;132(3):93-102
Date
Mar-2011
Language
English
Publication Type
Article
Keywords
Adult
Aging
Blood pressure
Cohort Studies
Female
Hematocrit
Humans
Life Style
Male
Middle Aged
Models, Biological
Sex Factors
Stress, Physiological
Abstract
We analysed relationship between the risk of onset of "unhealthy life" (defined as the onset of cancer, cardiovascular diseases, or diabetes) and longitudinal changes in body mass index, diastolic blood pressure, hematocrit, pulse pressure, pulse rate, and serum cholesterol in the Framingham Heart Study (Original Cohort) using the stochastic process model of human mortality and aging. The analyses demonstrate how decline in resistance to stresses and adaptive capacity accompanying human aging can be evaluated from longitudinal data. We showed how these components of the aging process, as well as deviation of the trajectories of physiological indices from those minimising the risk at respective ages, can lead to an increase in the risk of onset of unhealthy life with age. The results indicate the presence of substantial gender difference in aging related decline in stress resistance and adaptive capacity, which can contribute to differences in the shape of the sex-specific patterns of incidence rates of aging related diseases.
PubMed ID
21262255 View in PubMed
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Evaluation of genotype-specific survival using joint analysis of genetic and non-genetic subsamples of longitudinal data.

https://arctichealth.org/en/permalink/ahliterature99755
Source
Biogerontology. 2010 Dec 31;
Publication Type
Article
Date
Dec-31-2010
Author
Konstantin G Arbeev
Svetlana V Ukraintseva
Liubov S Arbeeva
Igor Akushevich
Alexander M Kulminski
Anatoliy I Yashin
Author Affiliation
Center for Population Health and Aging, Duke University, Trent Hall, Room 002, Box 90408, Durham, NC, 27708-0408, USA, konstantin.arbeev@duke.edu.
Source
Biogerontology. 2010 Dec 31;
Date
Dec-31-2010
Language
English
Publication Type
Article
Abstract
Small sample size of genetic data is often a limiting factor for desirable accuracy of estimated genetic effects on age-specific risks and survival. Longitudinal non-genetic data containing information on survival or disease onsets of study participants for whom the genetic data were not collected may provide an additional "reserve" for increasing the accuracy of respective estimates. We present a novel method for joint analyses of "genetic" (covering individuals for whom both genetic information and mortality/morbidity data are available) and "non-genetic" (covering individuals for whom only mortality/morbidity data were collected) subsamples of longitudinal data. Our simulation studies show substantial increase in the accuracy of estimates in such joint analyses compared to analyses based on genetic subsample alone. Application of this method to analysis of the effect of common apolipoprotein E (APOE) polymorphism on survival using combined genetic and non-genetic subsamples of the Framingham Heart Study original cohort data showed that female, but not male, carriers of the APOE e4 allele have significantly worse survival than non-carriers, whereas empirical analyses did not produce any significant results for either sex.
PubMed ID
21193960 View in PubMed
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Joint influence of small-effect genetic variants on human longevity.

https://arctichealth.org/en/permalink/ahliterature100414
Source
Aging (Albany NY). 2010 Sep;2(9):612-20
Publication Type
Article
Date
Sep-2010
Author
Anatoliy I Yashin
Deqing Wu
Konstantin G Arbeev
Svetlana V Ukraintseva
Author Affiliation
Center for Population Health and Aging, Duke University, Durham, NC 27708-0408, USA. aiy@duke.edu
Source
Aging (Albany NY). 2010 Sep;2(9):612-20
Date
Sep-2010
Language
English
Publication Type
Article
Keywords
Aging - genetics - physiology
Alleles
Genetic Variation - genetics - physiology
Genome, Human - genetics - physiology
Humans
Longevity - genetics - physiology
Polymorphism, Single Nucleotide - genetics - physiology
Abstract
The results of genome-wide association studies of complex traits, such as life span or age at onset of chronic disease, suggest that such traits are typically affected by a large number of small-effect alleles. Individually such alleles have little predictive values, therefore they were usually excluded from further analyses. The results of our study strongly suggest that the alleles with small individual effects on longevity may jointly influence life span so that the resulting influence can be both substantial and significant. We show that this joint influence can be described by a relatively simple "genetic dose - phenotypic response" relationship.
PubMed ID
20834067 View in PubMed
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