A global overview of pleiotropy and genetic architecture in complex traits

By Kyoko Watanabe, S. Stringer, O. Frei, M. Umiċeviċ Mirkov, C. D. de Leeuw, T. Polderman, S. van der Sluis, O. Andreassen, Benjamin M. Neale, Danielle Posthuma. Nature Genetics, 2019

1,107 citations recorded by the source corpus.

After a decade of genome-wide association studies (GWASs), fundamental questions in human genetics, such as the extent of pleiotropy across the genome and variation in genetic architecture across traits, are still unanswered. The current availability of hundreds of GWASs provides a unique opportunity to address these questions. We systematically analyzed 4,155 publicly available GWASs. For a subset of well-powered GWASs on 558 traits, we provide an extensive overview of pleiotropy and genetic architecture. We show that trait-associated loci cover more than half of the genome, and 90% of these overlap with loci from multiple traits. We find that potential causal variants are enriched in coding and flanking regions, as well as in regulatory elements, and show variation in polygenicity and discoverability of traits. Our results provide insights into how genetic variation contributes to trait variation. All GWAS results can be queried and visualized at the GWAS ATLAS resource (https://atlas.ctglab.nl). Systematic analyses of large-scale genome-wide association data provide an overview of pleiotropy and genetic architecture for hundreds of human complex traits and diseases.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/e9043478b1e73568207df52c28095bfb842f642c

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In Genetics

1. Eric J. Topol
2. Pranav Rajpurkar
3. Danielle Posthuma

In Molecular Biology

1. S. van der Sluis
2. Eric J. Topol
3. Pranav Rajpurkar

Citations in the corpus

• An integrated framework for local genetic correlation analysis (2022, background): “The loci with the greatest number of significant r g s tended to be located within the MHC (chr6:26–34Mb), a region where extensive pleiotropy has been noted previously 2,28 .”
• Multimodal biomedical AI (2022, background): “Beyond oncology, there has been a remarkable increase in the last 15 years in the availability and sharing of genetic data, which enabled genome-wide association studies 12 and characterization of the genetic architecture of complex human conditions and traits 13 .”