Pleiotropy in complex traits: challenges and strategies

Key Points Genome-wide association studies have identified many novel loci for hundreds of traits. Interestingly, numerous genetic loci have been associated with multiple seemingly distinct traits. These cross-phenotype (CP) associations highlight the relevance of pleiotropy in human disease. There is substantial evidence for CP associations in contemporary gene-mapping studies. Different types of pleiotropy (biological, mediated and spurious pleiotropy) can underlie a CP association. Various analytical approaches have been devised for detecting CP associations, especially methods that are based on summary statistics as opposed to individual-level data. Different methods have relative advantages and disadvantages and are distinguished by their underlying algorithms and by the types of phenotype data that they handle. Study design considerations are crucial for minimizing the identification of spurious CP associations. CP associations can highlight shared biological pathways and, when associated with different diseases, have clinical implications for diagnosis, counselling and treatment. Modern genomic studies are revealing widespread associations between single genetic variants and multiple distinct traits, including diseases. This Review discusses the biological underpinnings of such pleiotropy and the available bioinformatic tools for the detection and characterization of these effects, as well as the implications for understanding human disease. Genome-wide association studies have identified many variants that each affects multiple traits, particularly across autoimmune diseases, cancers and neuropsychiatric disorders, suggesting that pleiotropic effects on human complex traits may be widespread. However, systematic detection of such effects is challenging and requires new methodologies and frameworks for interpreting cross-phenotype results. In this Review, we discuss the evidence for pleiotropy in contemporary genetic mapping studies, new and established analytical approaches to identifying pleiotropic effects, sources of spurious cross-phenotype effects and study design considerations. We also outline the molecular and clinical implications of such findings and discuss future directions of research.