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Measuring the genetic influence in modulating the human life span: gene–environment interaction and the sex-specific genetic effect

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Abstract

New approaches are needed to explore the different ways in which genes affect the human life span. One needs to assess the genetic effects themselves, as well as gene–environment interactions and sex dependency. In this paper, we present a new model that combines both genotypic and demographicinformation in the estimation of the geneticinfluence on life spans. Based on Cox'sproportional hazard assumption, the modelmeasures the risks for each gene as well as forgene–environment and gene–sex interactions,while controlling for confounding factors. Atwo-step MLE is introduced to obtain anon-parametric form of the baseline hazardfunction. The model is applied to genotypicdata from Italian centenarian studies toestimate relative risks of candidate genes,risks due to interactions and initialfrequencies of different genes in thepopulation. Results from models that either door do not take into consideration individualheterogeneity are compared. It is shown thatignoring the existence of heterogeneity canlead to a systematic underestimation of geneticeffects and effects due to interactions.

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Authors and Affiliations

  1. Max-Planck Institute for Demographic Research, Doberaner Str. 114, 18057, Rostock, Germany

    Qihua Tan, A.I. Yashin & J.W. Vaupel

  2. Cell Biology Department, University of Calabria, Rende, Italy

    G. De Benedictis & M. DeLuca

  3. Center for Demographic Studies and Sanford Institute, Duke University, Durham, North Carolina, USA (e-mail

    A.I. Yashin

  4. Department of Experimental Pathology, University of Bologna, Italy

    M. Bonafe, S. Valensin & C. Franceschi

Authors
  1. Qihua Tan
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  2. G. De Benedictis
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  3. A.I. Yashin
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  4. M. Bonafe
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  5. M. DeLuca
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  6. S. Valensin
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  7. J.W. Vaupel
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  8. C. Franceschi
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Tan, Q., De Benedictis, G., Yashin, A. et al. Measuring the genetic influence in modulating the human life span: gene–environment interaction and the sex-specific genetic effect. Biogerontology 2, 141–153 (2001). https://doi.org/10.1023/A:1011557022985

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