Within-sibship GWAS of 25 phenotypes improve estimates of direct genetic effects

Estimates from genome-wide association studies of unrelated individuals (GWAS) capture effects 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 demographic and indirect genetic effects, but large-scale family datasets have been lacking. We combined data from 178,086 siblings from 19 cohorts to generate population (between-family) and within-sibship (within-family) estimates of genome-wide genetic associations for 25 phenotypes. Consistent with previous studies, within-sibship GWAS estimates were smaller than corresponding population estimates for height, educational attainment, age at first birth, number of children, cognitive ability, depressive symptoms and smoking. We also observed some differences between population and within-sibship model estimates in downstream SNP-heritability, genetic correlations and Mendelian randomization analyses. For example, the genetic correlation between educational attainment and BMI attenuated towards zero. In contrast, analyses of most molecular 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 understand the relationships between genetic variation and phenotypes influenced by demographic and indirect genetic effects