Dahm, C. C. | bioRxiv Science

bioRxiv2021

Within-sibship GWAS improve estimates of direct genetic effects

Estimates from genome-wide association studies (GWAS) represent a combination of the effect of inherited genetic variation (direct effects), demography (population stratification, assortative mating) and genetic nurture from relatives (indirect genetic effects). GWAS using family-based designs can control for demography and indirect genetic effects, but large-scale family datasets have been lacking. We combined data on 159,701 siblings from 17 cohorts to generate population (between-family) and within-sibship (within-family) estimates of genome-wide genetic associations for 25 phenotypes. We demonstrate that existing GWAS associations for height, educational attainment, smoking, depressive symptoms, age at first birth and cognitive ability overestimate direct effects. We show that estimates of SNP-heritability, genetic correlations and Mendelian randomization involving these phenotypes substantially differ when calculated using within-sibship estimates. For example, genetic correlations between educational attainment and height largely disappear. In contrast, analyses of most clinical phenotypes (e.g. LDL-cholesterol) were generally consistent between population and within-sibship models. We also report compelling evidence of polygenic adaptation on taller human height using within-sibship data. Large-scale family datasets provide new opportunities to quantify direct effects of genetic variation on human traits and diseases.

genetics↗

bioRxiv2018

Body mass index trajectories preceding first report of poor self-rated health: a longitudinal case-control analysis of the English Longitudinal Study of Ageing

BackgroundStudies have consistently found that obesity is associated with poor self-rated health, but how body mass index (BMI) developed in the lead up to poor self-rated health is unknown.\n\nMethodsWe nested a longitudinal case-control study in the English Longitudinal Study of Ageing (1998-2015) to investigate BMI trajectories in the years preceding a first self-report of poor health. Participants rated their health at each data collection; every other collection included a BMI assessment by a nurse. Case status was defined as a first report of poor health during follow-up. Three age- and sex-matched controls were identified per case using density sampling. BMI trajectories were fitted to time backwards prior to first report of poor health using mixed-effects models. Age and sex were potential modifiers. We conducted subgroup analyses of those not reporting certain chronic diseases or smoking.\n\nResultsWe identified 732 cases and 2195 controls. Age, but not sex, modified the association between BMI and self-rated health. Participants reporting poor health at age 60 had a 1.5 kg/m2 (95%CI: 0.8 to 2.1) higher BMI at the time of reporting than controls, and their BMI had previously increased sharply. After age 75, cases no longer had higher BMI than controls, and their BMI had decreased sharply prior to reporting poor health. Age was also an effect modifier among those without diabetes, however BMI trajectories were more similar among the middle-aged.\n\nConclusionDevelopment of BMI was associated with poor self-rated health; however, the nature of the association depended markedly on age.\n\nO_TEXTBOXWhat is already known on this subjectO_LIStudies based on a single body mass index measurement have consistently found that being underweight or obese was associated with poor self-rated health.\nC_LIO_LIHow body mass index developed in the lead up to poor self-rated health was unknown.\nC_LI\n\nC_TEXTBOX\n\nO_TEXTBOXWhat this study addsO_LIIn the present study, body mass index trajectories leading up to poor self-rated health were strongly dependent on age at first report of poor health. Middle-aged participants with poor self-rated health had higher body mass index than controls; both groups had increasing body mass index over time.\nC_LIO_LIIn contrast, a report of poor health at age 75 or later was preceded by a decrease in body mass index; controls were 10 years older than cases before they started to lose body mass index.\nC_LIO_LIOur results suggest that future prospective studies and clinical decision making should take into account the age-dependent association between development of body mass index preceding poor self-rated health.\nC_LI\n\nC_TEXTBOX

epidemiology↗