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Multitrait GWAS to connect disease variants and biological mechanisms.
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.
Afiliación
  • Julienne H; Department of Computational Biology, Institut Pasteur, Paris, France.
  • Laville V; Department of Computational Biology, Institut Pasteur, Paris, France.
  • McCaw ZR; Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, Massachusetts, United States of America.
  • He Z; Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, United States of America.
  • Guillemot V; Department of Computational Biology, Institut Pasteur, Paris, France.
  • Lasry C; Department of Computational Biology, Institut Pasteur, Paris, France.
  • Ziyatdinov A; Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, Massachusetts, United States of America.
  • Nerin C; Department of Computational Biology, Institut Pasteur, Paris, France.
  • Vaysse A; Department of Computational Biology, Institut Pasteur, Paris, France.
  • Lechat P; Department of Computational Biology, Institut Pasteur, Paris, France.
  • Ménager H; Department of Computational Biology, Institut Pasteur, Paris, France.
  • Le Goff W; Sorbonne Université, INSERM, Institute of Cardiometabolism and Nutrition (ICAN), UMR_S 1166, Paris, France.
  • Dube MP; Université de Montréal Beaulieu-Saucier Pharmacogenomics Centre, Montreal Heart Institute, Montreal, Canada.
  • Kraft P; Université de Montréal, Faculty of Medicine, Department of medicine, Université de Montréal, Montreal, Canada.
  • Ionita-Laza I; Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, Massachusetts, United States of America.
  • Vilhjálmsson BJ; Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, Massachusetts, United States of America.
  • Aschard H; Department of Biostatistics, Columbia University, New York, New York, United States of America.
PLoS Genet ; 17(8): e1009713, 2021 08.
Article en En | MEDLINE | ID: mdl-34460823
ABSTRACT
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.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Biología Computacional / Polimorfismo de Nucleótido Simple / Sitios de Carácter Cuantitativo Tipo de estudio: Clinical_trials Límite: Humans Idioma: En Revista: PLoS Genet Asunto de la revista: GENETICA Año: 2021 Tipo del documento: Article País de afiliación: Francia

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Biología Computacional / Polimorfismo de Nucleótido Simple / Sitios de Carácter Cuantitativo Tipo de estudio: Clinical_trials Límite: Humans Idioma: En Revista: PLoS Genet Asunto de la revista: GENETICA Año: 2021 Tipo del documento: Article País de afiliación: Francia