Literature DB >> 25916590

Models to explore genetics of human aging.

David Karasik1, Anne Newman.   

Abstract

Genetic studies have bestowed insight into the biological mechanisms underlying inter-individual differences in susceptibility to (or resistance to) organisms’ aging. Recent advances in molecular and genetic epidemiology provide tools to explore the genetic sources of the variability in biological aging in humans. To be successful, the genetic study of a complex condition such as aging requires the clear definition of essential traits that can characterize the aging process phenotypically. Phenotypes of human aging have long relied on mortality rate or exceptional longevity. Genome-wide association studies (GWAS) have been shown to present an unbiased approach to the identification of new candidate genes for human diseases. The GWAS approach can also be used for positive health phenotypes such as longevity or a delay in age-related chronic disease, as well as for other age related changes such as loss of telomere length or lens transparency. Sequencing, either in targeted regions or across the whole genome can further identify rare variation that may contribute to the biological aging mechanisms. To date, the results of the GWAS for longevity are rather disappointing, possibly in part due to the small number of individuals with GWAS data who have reached advanced old age.Human aging phenotypes are needed that can be assessed prior to death, and should be both heritable and validated as predictors of longevity. Potentially, phenotypes that focus on “successful” or “healthy” aging will be more powerful as they can be measured in large numbers of people and also are clinically relevant.We postulate that construction of an integrated phenotype of aging can be achieved capitalizing on multiple traits that may have weak correlations, but a shared underlying genetic architecture. This is based on a hypothesis that convergent results from multiple individual aging-related traits will point out the pleiotropic signals responsible for the overall rate of aging of the organism. An approach would be to investigate traits that are linked to the state of many vital functions, disability, and ultimately survival rates, to identify common biological pathways that govern aging processes in humans. New composite aging phenotypes must be validated by predicting all-cause mortality, major chronic disease and disability late in life.

Entities:  

Mesh:

Year:  2015        PMID: 25916590     DOI: 10.1007/978-1-4939-2404-2_7

Source DB:  PubMed          Journal:  Adv Exp Med Biol        ISSN: 0065-2598            Impact factor:   2.622


  3 in total

1.  NOS3 Polymorphisms Can Influence the Effect of Multicomponent Training on Blood Pressure, Nitrite Concentration and Physical Fitness in Prehypertensive and Hypertensive Older Adult Women.

Authors:  Átila Alexandre Trapé; Jhennyfer Aline Lima Rodrigues; Letícia Perticarrara Ferezin; Gustavo Duarte Ferrari; Elisangela Aparecida da Silva Lizzi; Vitor Nolasco de Moraes; Roberta Fernanda da Silva; Anderson Saranz Zago; Javier Brazo-Sayavera; Carlos Roberto Bueno Júnior
Journal:  Front Physiol       Date:  2021-03-10       Impact factor: 4.566

2.  Effect of Multicomponent Training on Blood Pressure, Nitric Oxide, Redox Status, and Physical Fitness in Older Adult Women: Influence of Endothelial Nitric Oxide Synthase (NOS3) Haplotypes.

Authors:  Atila Alexandre Trapé; Elisangela Aparecida da Silva Lizzi; Thiago Correa Porto Gonçalves; Jhennyfer Aline Lima Rodrigues; Simone Sakagute Tavares; Riccardo Lacchini; Lucas Cezar Pinheiro; Graziele Cristina Ferreira; José Eduardo Tanus-Santos; Paula Payão Ovídio; Alceu Afonso Jordão; André Mourão Jacomini; Anderson Saranz Zago; Carlos Roberto Bueno Júnior
Journal:  Oxid Med Cell Longev       Date:  2017-09-14       Impact factor: 6.543

3.  Genetic variants associated with physical performance and anthropometry in old age: a genome-wide association study in the ilSIRENTE cohort.

Authors:  David Heckerman; Bryan J Traynor; Anna Picca; Riccardo Calvani; Emanuele Marzetti; Dena Hernandez; Michael Nalls; Sampath Arepali; Luigi Ferrucci; Francesco Landi
Journal:  Sci Rep       Date:  2017-11-20       Impact factor: 4.379

  3 in total

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