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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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Beta2-adrenergic receptor gene polymorphisms as systemic determinants of healthy aging in an evolutionary context.

https://arctichealth.org/en/permalink/ahliterature97315
Source
Mech Ageing Dev. 2010 May;131(5):338-45
Publication Type
Article
Date
May-2010
Author
Alexander M Kulminski
Irina Culminskaya
Svetlana V Ukraintseva
Konstantin G Arbeev
Kenneth C Land
Anatoli I Yashin
Author Affiliation
Center for Population Health and Aging, Duke University Population Research Institute, Durham, NC 27708, USA. ander.Kulminski@duke.edu
Source
Mech Ageing Dev. 2010 May;131(5):338-45
Date
May-2010
Language
English
Publication Type
Article
Abstract
The Gln(27)Glu polymorphism but not the Arg(16)Gly polymorphism of the beta2-adrenergic receptor (ADRB2) gene appears to be associated with a broad range of aging-associated phenotypes, including cancers at different sites, myocardial infarction (MI), intermittent claudication (IC), and overall/healthy longevity in the Framingham Heart Study Offspring cohort. The Gln(27)Gln genotype increases risks of cancer, MI and IC, whereas the Glu(27) allele or, equivalently, the Gly(16)Glu(27) haplotype tends to be protective against these diseases. Genetic associations with longevity are of opposite nature at young-old and oldest-old ages highlighting the phenomenon of antagonistic pleiotropy. The mechanism of antagonistic pleiotropy is associated with an evolutionary-driven advantage of carriers of a derived Gln(27) allele at younger ages and their survival disadvantage at older ages as a result of increased risks of cancer, MI and IC. The ADRB2 gene can play an important systemic role in healthy aging in evolutionary context that warrants exploration in other populations.
PubMed ID
20399803 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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Trade-offs in the effects of the apolipoprotein E polymorphism on risks of diseases of the heart, cancer, and neurodegenerative disorders: insights on mechanisms from the Long Life Family Study.

https://arctichealth.org/en/permalink/ahliterature269622
Source
Rejuvenation Res. 2015 Apr;18(2):128-35
Publication Type
Article
Date
Apr-2015
Author
Alexander M Kulminski
Konstantin G Arbeev
Irina Culminskaya
Svetlana V Ukraintseva
Eric Stallard
Michael A Province
Anatoli I Yashin
Source
Rejuvenation Res. 2015 Apr;18(2):128-35
Date
Apr-2015
Language
English
Publication Type
Article
Keywords
Adult
Age Factors
Aged
Aged, 80 and over
Aging - genetics
Apolipoprotein E4 - genetics
Denmark - epidemiology
Female
Genetic Predisposition to Disease
Heart Diseases - diagnosis - epidemiology - genetics
Heredity
Humans
Kaplan-Meier Estimate
Life expectancy
Longitudinal Studies
Male
Middle Aged
Neoplasms - diagnosis - epidemiology - genetics
Neurodegenerative Diseases - diagnosis - epidemiology - genetics
Odds Ratio
Pedigree
Polymorphism, Genetic
Proportional Hazards Models
Protective factors
Risk assessment
Risk factors
Sex Factors
United States - epidemiology
Abstract
The lack of evolutionary established mechanisms linking genes to age-related traits makes the problem of genetic susceptibility to health span inherently complex. One complicating factor is genetic trade-off. Here we focused on long-living participants of the Long Life Family Study (LLFS), their offspring, and spouses to: (1) Elucidate whether trade-offs in the effect of the apolipoprotein E e4 allele documented in the Framingham Heart Study (FHS) are a more general phenomenon, and (2) explore potential mechanisms generating age- and gender-specific trade-offs in the effect of the e4 allele on cancer, diseases of the heart, and neurodegenerative disorders assessed retrospectively in the LLFS populations. The e4 allele can diminish risks of cancer and diseases of the heart and confer risks of diseases of the heart in a sex-, age-, and LLFS-population-specific manner. A protective effect against cancer is seen in older long-living men and, potentially, their sons (>75 years, relative risk [RR]>75=0.48, p=0.086), which resembles our findings in the FHS. The protective effect against diseases of the heart is limited to long-living older men (RR>76=0.50, p=0.016), as well. A detrimental effect against diseases of the heart is characteristic for a normal LLFS population of male spouses and is specific for myocardial infarction (RR=3.07, p=2.1×10(-3)). These trade-offs are likely associated with two inherently different mechanisms, including disease-specific (detrimental; characteristic for a normal male population) and systemic, aging-related (protective; characteristic for older long-living men) mechanisms. The e4 allele confers risks of neurological disorders in men and women (RR=1.98, p=0.046). The results highlight the complex role of the e4 allele in genetic susceptibility to health span.
Notes
Cites: J Am Geriatr Soc. 2008 Mar;56(3):478-8318179501
Cites: Am J Hum Genet. 2008 Apr;82(4):849-5818387595
Cites: Nat Rev Genet. 2009 Apr;10(4):241-5119293820
Cites: Ann Clin Lab Sci. 2009 Spring;39(2):120-3319429797
Cites: Maturitas. 2009 May 20;63(1):13-919282116
Cites: Annu Rev Med. 2009;60:457-6918817460
Cites: Am J Epidemiol. 2009 Dec 15;170(12):1555-6219910380
Cites: Rejuvenation Res. 2010 Feb;13(1):13-2120230274
Cites: Mech Ageing Dev. 2010 Mar;131(3):215-2220184914
Cites: Cell. 2010 Apr 16;141(2):210-720403315
Cites: Hum Mol Genet. 2010 May 15;19(10):2059-6720176734
Cites: Nat Rev Genet. 2010 Jun;11(6):446-5020479774
Cites: Mech Ageing Dev. 2010 May;131(5):338-4520399803
Cites: Mol Ecol. 2010 Aug;19(15):3022-420687246
Cites: Eur J Hum Genet. 2010 Sep;18(9):1045-5320442747
Cites: Ann N Y Acad Sci. 2010 Sep;1206:80-10920860684
Cites: Osteoporos Int. 2011 Feb;22(2):599-60520567806
Cites: Eur J Clin Invest. 2011 May;41(5):561-721155765
Cites: Aging Cell. 2011 Jun;10(3):533-4121332925
Cites: J Gerontol A Biol Sci Med Sci. 2001 Oct;56(10):B432-4211584028
Cites: Ageing Res Rev. 2014 Nov;18:53-7325159268
Cites: Exp Gerontol. 2002 Oct-Nov;37(10-11):1141-612470824
Cites: Evolution. 2003 Jul;57(7):1478-8812940353
Cites: Ann Intern Med. 2004 Jul 20;141(2):137-4715262670
Cites: Am J Hum Genet. 2004 Sep;75(3):353-6215272419
Cites: J Chronic Dis. 1982 Feb;35(2):101-147056835
Cites: Arterioscler Thromb Vasc Biol. 1996 Oct;16(10):1250-58857921
Cites: Am J Hum Genet. 1997 Jul;61(1):171-819245998
Cites: Science. 1997 Oct 17;278(5337):407-119334291
Cites: Ann Hum Genet. 1998 Mar;62(Pt 2):115-229759473
Cites: Circulation. 1999 Aug 10;100(6):608-1310441097
Cites: Diabetes Metab. 2005 Dec;31 Spec No 2:5S27-5S3416415763
Cites: Nat Rev Genet. 2006 Jun;7(6):436-4816708071
Cites: Dan Med Bull. 2006 Nov;53(4):441-917150149
Cites: Ann N Y Acad Sci. 2007 Apr;1100:14-2017460162
Cites: Proc Natl Acad Sci U S A. 2007 May 22;104(21):8685-9017502601
Cites: Biol Psychol. 2007 Jul;75(3):229-3817433528
Cites: PLoS Genet. 2007 Jul;3(7):e12517677003
Cites: PLoS Comput Biol. 2007 Aug;3(8):e17017784782
Cites: Ann N Y Acad Sci. 2007 Oct;1114:11-317986572
Cites: Am J Hum Genet. 2011 Nov 11;89(5):607-1822077970
Cites: Nat Rev Genet. 2011 Feb;13(2):135-4522251874
Cites: J Am Geriatr Soc. 2012 Feb;60(2):323-722283485
Cites: Rejuvenation Res. 2012 Aug;15(4):381-9422533364
Cites: Neurobiol Aging. 2013 Apr;34(4):1287-9123040522
Cites: Rejuvenation Res. 2013 Feb;16(1):28-3423094790
Cites: Aging Cell. 2013 Apr;12(2):237-4623320904
Cites: Nat Rev Neurosci. 2013 Apr;14(4):293-30423511909
Cites: Rejuvenation Res. 2013 Aug;16(4):304-1223768105
Cites: Cell Stress Chaperones. 2001 Oct;6(4):316-2511795468
PubMed ID
25482294 View in PubMed
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