Multitrait GWAS to connect disease variants and biological mechanisms

Genome-wide association studies (GWASs) have uncovered a wealth of associations between common variants and human phenotypes. Here, we present an integrative analysis of GWAS summary statistics from 36 phenotypes to decipher multitrait genetic architecture and its link with biological mechanisms. Ou...

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Detalles Bibliográficos
Autores principales: Julienne, Hanna, Laville, Vincent, McCaw, Zachary R., He, Zihuai, Guillemot, Vincent, Lasry, Carla, Ziyatdinov, Andrey, Nerin, Cyril, Vaysse, Amaury, Lechat, Pierre, Ménager, Hervé, Le Goff, Wilfried, Dube, Marie-Pierre, Kraft, Peter, Ionita-Laza, Iuliana, Vilhjálmsson, Bjarni J., Aschard, Hugues
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8437297/
https://www.ncbi.nlm.nih.gov/pubmed/34460823
http://dx.doi.org/10.1371/journal.pgen.1009713
Descripción
Sumario:Genome-wide association studies (GWASs) have uncovered a wealth of associations between common variants and human phenotypes. Here, we present an integrative analysis of GWAS summary statistics from 36 phenotypes to decipher multitrait genetic architecture and its link with biological mechanisms. Our framework incorporates multitrait association mapping along with an investigation of the breakdown of genetic associations into clusters of variants harboring similar multitrait association profiles. Focusing on two subsets of immunity and metabolism phenotypes, we then demonstrate how genetic variants within clusters can be mapped to biological pathways and disease mechanisms. Finally, for the metabolism set, we investigate the link between gene cluster assignment and the success of drug targets in randomized controlled trials.

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