Polygenic risk scores have shown great promise in predicting complex disease risk and will
become more accurate as training sample sizes increase. The standard approach for …

Population structure causes genome-wide linkage disequilibrium between unlinked loci,
leading to statistical confounding in genome-wide association studies. Mixed models have …

Regulatory and coding variants are known to be enriched with associations identified by
genome-wide association studies (GWASs) of complex disease, but their contributions to trait …

Sequence variants in the parental genomes that are not transmitted to a child (the proband)
are often ignored in genetic studies. Here we show that nontransmitted alleles can affect a …

Importance Schizophrenia has a complex etiology influenced both by genetic and nongenetic
factors but disentangling these factors is difficult. Objective To estimate (1) how strongly …

The authors argue that population structure per se is not a problem in genome-wide association
studies — the true sources are the environment and the genetic background, and the …

Recent work has shown that much of the missing heritability of complex traits can be
resolved by estimates of heritability explained by all genotyped SNPs. However, it is currently …

Although pioneered by human geneticists as a potential solution to the challenging problem
of finding the genetic basis of common human diseases 1 , 2 , genome-wide association (…

A well-functioning placenta is essential for fetal and maternal health throughout pregnancy.
Using placental weight as a proxy for placental growth, we report genome-wide association …

Linear mixed models are a powerful statistical tool for identifying genetic associations and
avoiding confounding. However, existing methods are computationally intractable in large …