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The relationship between fertility and lifespan in humans

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      Abstract

      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.

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      The online version of this article (doi:10.1007/s11357-010-9202-4) contains supplementary material, which is available to authorized users.

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      Most cited references 37

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      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.
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        Pleiotropy, Natural Selection, and the Evolution of Senescence

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          Evolution of senescence: late survival sacrificed for reproduction.

          In so far as it is associated with declining fertility and increasing mortality, senescence is directly detrimental to reproductive success. Natural selection should therefore act in the direction of postponing or eliminating senescence from the life history. The widespread occurrence of senescence is explained by observing that (i) the force of natural selection is generally weaker at late ages than at early ages, and (ii) the acquisition of greater longevity usually involves some cost. Two convergent theories are the 'antagonistic pleiotropy' theory, based in population genetics, and the 'disposable soma' theory, based in physiological ecology. The antagonistic pleiotropy theory proposes that certain alleles that are favoured because of beneficial early effects also have deleterious later effects. The disposable soma theory suggests that because of the competing demands of reproduction less effort is invested in the maintenance of somatic tissues than is necessary for indefinite survival.
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            Author and article information

            Affiliations
            [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
            Contributors
            +31-10-7043488 , +31-10-7044657 , M.Kuningas@erasmusmc.nl
            Journal
            Age (Dordr)
            Age
            Springer Netherlands (Dordrecht )
            0161-9152
            1574-4647
            11 January 2011
            11 January 2011
            December 2011
            : 33
            : 4
            : 615-622
            3220400
            21222045
            9202
            10.1007/s11357-010-9202-4
            © The Author(s) 2011
            Categories
            Article
            Custom metadata
            © American Aging Association 2011

            Geriatric medicine

            snp, fertility, trade-off, lifespan, gene

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