• Record: found
  • Abstract: found
  • Article: not found

The relationship between fertility and lifespan in humans

Read this article at

      There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.


      Evolutionary theories of aging predict a trade-off between fertility and lifespan, where increased lifespan comes at the cost of reduced fertility. Support for this prediction has been obtained from various sources. However, which genes underlie this relationship is unknown. To assess it, we first analyzed the association of fertility with age at menarche and menopause, and with mortality in 3,575 married female participants of the Rotterdam Study. In addition, we conducted a candidate gene study where 1,664 single nucleotide polymorphisms (SNPs) in 25 candidate genes were analyzed in relation to number of children as a measure of fertility. SNPs that associated with fertility were analyzed for association with mortality. We observed no associations between fertility and age at menarche (p = 0.38) and menopause (p = 0.07). In contrast, fertility was associated with mortality. Women with two to three children had significantly lower mortality (hazard ratio (HR), 0.82; 95% confidence interval (95% CI), 0.69–0.97) compared to women with no children. No such benefit was observed for women with four or more children, who had a similar mortality risk (HR, 0.93; 95% CI, 0.76–1.13) as women with no children. The analysis of candidate genes revealed four genes that influence fertility after correction for multiple testing: CGB/LHB gene cluster (p = 0.0036), FSHR (p = 0.023), FST (p = 0.023), and INHBA (p = 0.021). However, none of the independent SNPs in these genes predicted mortality. In conclusion, women who bear two to three children live longer than those who bear none or many children, but this relationship was not mediated by the candidate genes analyzed in this study.Electronic supplementary materialThe online version of this article (doi:10.1007/s11357-010-9202-4) contains supplementary material, which is available to authorized users.

      Related collections

      Most cited references 37

      • Record: found
      • Abstract: found
      • Article: not found

      PLINK: a tool set for whole-genome association and population-based linkage analyses.

      Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.
        • Record: found
        • Abstract: not found
        • Article: not found

        Pleiotropy, Natural Selection, and the Evolution of Senescence

          • Record: found
          • Abstract: found
          • Article: not found

          Evolution of ageing.

          An evolutionary view of ageing suggests that mortality may be due to an energy-saving strategy of reduced error regulation in somatic cells. This supports Orgel's 'error catastrophe' hypothesis and offers a new basis for the study of normal and abnormal ageing syndromes and of apparently immortal transformed cell lines.

            Author and article information

            [1 ]Department of Epidemiology, Erasmus University Medical Center, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands
            [2 ]Department of Clinical Science, Intervention and Technology, Division of Obstetrics and Gynaecology, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden
            [3 ]Competence Centre on Reproductive Medicine and Biology, Tartu, Estonia
            [4 ]Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
            [5 ]Department of Child and Adolescent Psychiatry, Erasmus Medical Center–Sophia Children’s Hospital, Rotterdam, The Netherlands
            +31-10-7043488 , +31-10-7044657 ,
            Age (Dordr)
            Springer Netherlands (Dordrecht )
            11 January 2011
            11 January 2011
            December 2011
            : 33
            : 4
            : 615-622
            © The Author(s) 2011
            Custom metadata
            © American Aging Association 2011

            Geriatric medicine

            snp, fertility, trade-off, lifespan, gene


            Comment on this article