Copyright © 1999 The American Society of Human Genetics. All rights reserved.
The American Journal of Human Genetics, Volume 65, Issue 4, 1178-1193, 1 October 1999
doi:10.1086/302572
Genes, Demography, and Life Span: The Contribution of Demographic Data in Genetic Studies on Aging and Longevity
A.I. Yashin1, 2, 
, 
, G. De Benedictis4, J.W. Vaupel1, 3, Q. Tan1, K.F. Andreev1, I.A. Iachine8, M. Bonafe6, M. DeLuca4, S. Valensin7, L. Carotenuto5 and C. Franceschi6, 7
1 Max Planck Institute for Demographic Research, Rostock, Germany
2 Center for Demographic Studies, Durham, NC
3 Sanford Institute, Duke University, Durham, NC
4 Cell Biology Department, Calabria, Italy
5 System Science Department, University of Calabria, Calabria, Italy
6 Istituto Nazionale Riposo e Cura Anziani, Ancona, Italy
7 Biomedical Science Department, University of Bologna, Bologna, Italy
8 Department of Statistics and Demography, Odense University, Odense, Denmark
Address for correspondence and reprints: Dr. A. I. Yashin, Max Planck Institute for Demographic Research, Doberaner Strasse 114 18057, Rostock, GermanyAbstract
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.
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