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Genetic variants determining survival and fertility in an adverse African environment: a population-based large-scale candidate gene association study.

ABSTRACT: Human survival probability and fertility decline strongly with age. These life history traits have been shaped by evolution. However, research has failed to uncover a consistent genetic determination of variation in survival and fertility. As an explanation, such genetic determinants have been selected in adverse environments, in which humans have lived during most of their history, but are almost exclusively studied in populations in modern affluent environments. Here, we present a large-scale candidate gene association study in a rural African population living in an adverse environment. In 4387 individuals, we studied 4052 SNPs in 148 genes that have previously been identified as possible determinants of survival or fertility in animals or humans. We studied their associations with survival comparing newborns, middle-age adults, and old individuals. In women, we assessed their associations with reported and observed numbers of children. We found no statistically significant associations of these SNPs with survival between the three age groups nor with women's reported and observed fertility. Population stratification was unlikely to explain these results. Apart from a lack of power, we hypothesise that genetic heterogeneity of complex phenotypes and gene-environment interactions prevent the identification of genetic variants explaining variation in survival and fertility in humans.

SUBMITTER: Koopman JJ

PROVIDER: S-EPMC4993336 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

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Genetic variants determining survival and fertility in an adverse African environment: a population-based large-scale candidate gene association study.

Koopman Jacob J E JJ Pijpe Jeroen J Böhringer Stefan S van Bodegom David D Eriksson Ulrika K UK Sanchez-Faddeev Hernando H Ziem Juventus B JB Zwaan Bas B Slagboom P Eline PE de Knijff Peter P Westendorp Rudi G J RG

Aging 20160701 7

Human survival probability and fertility decline strongly with age. These life history traits have been shaped by evolution. However, research has failed to uncover a consistent genetic determination of variation in survival and fertility. As an explanation, such genetic determinants have been selected in adverse environments, in which humans have lived during most of their history, but are almost exclusively studied in populations in modern affluent environments. Here, we present a large-scale ...[more]

PMID: 27356285

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Project description:BackgroundThe apolipoprotein-ε4 allele (APOE-ε4) is strongly associated with detrimental outcomes in affluent populations including atherosclerotic disease, Alzheimer's disease, and reduced lifespan. Despite these detrimental outcomes, population frequencies of APOE-ε4 are high. We hypothesize that the high frequency of APOE-ε4 was maintained because of beneficial effects during evolution when infectious pathogens were more prevalent and a major cause of mortality. We examined a rural Ghanaian population with a high pathogen exposure for selective advantages of APOE-ε4, to survival and or fertility.Methods and findingsThis rural Ghanaian population (n = 4311) has high levels of mortality from widespread infectious diseases which are the main cause of death. We examined whether APOE-ε4 was associated with survival (total follow-up time was 30,262 years) and fertility after stratifying by exposure to high or low pathogen levels. Households drawing water from open wells and rivers were classified as exposed to high pathogen levels while low pathogen exposure was classified as those drawing water from borehole wells. We found a non-significant, but positive survival benefit, i.e. the hazard ratio per APOE-ε4 allele was 0.80 (95% confidence interval: 0.69 to 1.05), adjusted for sex, tribe, and socioeconomic status. Among women aged 40 years and older (n = 842), APOE-ε4 was not associated with the lifetime number of children. However, APOE-ε4 was associated with higher fertility in women exposed to high pathogen levels. Compared with women not carrying an APOE-ε4 allele, those carrying one APOE-ε4 allele had on average one more child and those carrying two APOE-ε4 alleles had 3.5 more children (p = 0.018).ConclusionsContrary to affluent modern-day populations, APOE-ε4 did not carry a survival disadvantage in this rural Ghanaian population. Moreover, APOE-ε4 promotes fertility in highly infectious environments. Our findings suggest that APOE-ε4 may be considered as evolutionarily adaptive. Its adverse associations in affluent modern populations with later onset diseases of aging further characterize APOE-ε4 as an example of antagonistic pleiotropy.

Project description:The absence of comprehensive measured kinetic values and the observed inconsistency in the available in vitro kinetic data has hindered the formulation of network-scale kinetic models of biochemical reaction networks. To meet this challenge we present an approach to construct a convex space, termed the k-cone, which contains all the allowable numerical values of the kinetic constants in large-scale biochemical networks. The definition of the k-cone relies on the incorporation of in vivo concentration data and a simplified approach to represent enzyme kinetics within an established constraint-based modeling approach. The k-cone approach was implemented to define the allowable combination of numerical values for a full kinetic model of human red blood cell metabolism and to study its correlated kinetic parameters. The k-cone approach can be used to determine consistency between in vitro measured kinetic values and in vivo concentration and flux measurements when used in a network-scale kinetic model. k-Cone analysis was successful in determining whether in vitro measured kinetic values used in the reconstruction of a kinetic-based model of Saccharomyces cerevisiae central metabolism could reproduce in vivo measurements. Further, the k-cone can be used to determine which numerical values of in vitro measured parameters are required to be changed in a kinetic model if in vivo measured values are not reproduced. k-Cone analysis could identify what minimum number of in vitro determined kinetic parameters needed to be adjusted in the S. cerevisiae model to be consistent with the in vivo data. Applying the k-cone analysis a priori to kinetic model development may reduce the time and effort involved in model building and parameter adjustment. With the recent developments in high-throughput profiling of metabolite concentrations at a whole-cell scale and advances in metabolomics technologies, the k-cone approach presented here may hold the promise for kinetic characterization of metabolic networks as well as other biological functions at a whole-cell level.

Dataset Information

Genetic variants determining survival and fertility in an adverse African environment: a population-based large-scale candidate gene association study.

Publications

Genetic variants determining survival and fertility in an adverse African environment: a population-based large-scale candidate gene association study.

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