Genes, Demography, and Life Span: The Contribution of Demographic Data in Genetic Studies on Aging and Longevity

• Published in: American journal of human genetics Vol. 65; no. 4; pp. 1178 - 1193
• Main Authors: Yashin, A.I., De Benedictis, G., Vaupel, J.W., Tan, Q., Andreev, K.F., Iachine, I.A., Bonafe, M., DeLuca, M., Valensin, S., Carotenuto, L., Franceschi, C.
• Format: Journal Article
• Language: English
• Published: Chicago, IL Elsevier Inc 01.10.1999; University of Chicago Press; The American Society of Human Genetics
• Subjects: Aging - genetics; Biological and medical sciences; Candidate genes; Centenarian studies; Computer Simulation; Cross-Sectional Studies; Demography; DNA, Mitochondrial - genetics; Gene frequencies; Gene Frequency - genetics; General aspects. Genetic counseling; Genotype; Haplotypes - genetics; Haplotypes of mtDNA; Heterogeneity; Humans; Italy - epidemiology; Likelihood Functions; Longevity - genetics; Longitudinal Studies; Medical genetics; Medical sciences; Models, Genetic; Relative risk; Sensitivity and Specificity; Survival Rate; Italy; Gene frequencies; Heterogeneity; Haplotypes of mtDNA; Centenarian studies; Candidate genes; Relative risk; Human; Demography; Analysis method; Gene; Ageing; Genetics; Genotype; Longevity; Statistics; Genetic determinism; Survival
• ISSN: 0002-9297; 1537-6605
• DOI: 10.1086/302572

In population studies on aging, the data on genetic markers are often collected for individuals from different age groups. The purpose of such studies is to identify, by comparison of the frequencies of selected genotypes, “longevity” or “frailty” genes in the oldest and in younger groups of individuals. To address questions about more-complicated aspects of genetic influence on longevity, additional information must be used. In this article, we show that the use of demographic information, together with data on genetic markers, allows us to calculate hazard rates, relative risks, and survival functions for respective genes or genotypes. New methods of combining genetic and demographic information are discussed. These methods are tested on simulated data and then are applied to the analysis of data on genetic markers for two haplogroups of human mtDNA. The approaches suggested in this article provide a powerful tool for analyzing the influence of candidate genes on longevity and survival. We also show how factors such as changes in the initial frequencies of candidate genes in subsequent cohorts, or secular trends in cohort mortality, may influence the results of an analysis.