We propose an extended Gaussian mixture model for the distribution of causal effects of common single nucleotide polymorphisms (SNPs) for human complex phenotypes, taking into account linkage disequilibrium (LD) and heterozygosity (H), while also allowing for independent components for small and large effects. Using a precise methodology showing how genome-wide association studies (GWAS) summary statistics (z-scores) arise through LD with underlying causal SNPs, we applied the model to multiple GWAS. Our findings indicated that causal effects are distributed with dependence on a SNP's total LD and H, whereby SNPs with lower total LD are more likely to be causal, and causal SNPs with lower H tend to have larger effects, consistent with the influence of negative pressure from natural selection. The degree of dependence, however, varies markedly across phenotypes. ### Competing Interest Statement The authors have declared no competing interest.
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