Sex-Specific Polygenic Risk Scores and Replication in a Model-Free Analysis of Schizophrenia Data

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BACKGROUND/OBJECTIVES: While single variants may have only small effects on common heritable traits like schizophrenia, methods for combining such effects over multiple variants have been proposed for more than 30 years. The currently favored approaches are polygenic risk scores. Their main aim is the genetic prediction of phenotypes. METHODS: To accommodate the inherent genetic heterogeneity between males and females, we separated them into two independent datasets and in each developed allelic polygenic risk scores. We focused on variants with high predictability rather than high statistical significance and derived a statistical test to assess the significance of results obtained in one sex and replicated in the other sex. RESULTS: As few as 5000 highly predictive variants achieved accuracy exceeding 95% in each of males and females, and only 2.8% and 3.3% of cases and controls were misclassified in females and males, respectively. CONCLUSIONS: Our allelic polygenic risk scores are based on individual genotypes rather than summary statistics and produce highly accurate, cross-validated phenotype predictions. Although variants were originally selected as being highly predictive rather than statistically significant, 544 disease-associated variants were shown to be significantly shared between males and females, which represents a replication in an independent dataset.

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