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Colocalization analysis of polycystic ovary syndrome to identify potential disease-mediating genes and proteins

Polycystic ovary syndrome (PCOS) is a common complex disease in women with a strong genetic component and downstream consequences for reproductive, metabolic and psychological health. There are currently 19 known PCOS risk loci, primarily identified in women of Han Chinese or European ancestry, and...

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Autores principales: Censin, Jenny C., Bovijn, Jonas, Holmes, Michael V., Lindgren, Cecilia M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8440598/
https://www.ncbi.nlm.nih.gov/pubmed/33664499
http://dx.doi.org/10.1038/s41431-021-00835-8
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author Censin, Jenny C.
Bovijn, Jonas
Holmes, Michael V.
Lindgren, Cecilia M.
author_facet Censin, Jenny C.
Bovijn, Jonas
Holmes, Michael V.
Lindgren, Cecilia M.
author_sort Censin, Jenny C.
collection PubMed
description Polycystic ovary syndrome (PCOS) is a common complex disease in women with a strong genetic component and downstream consequences for reproductive, metabolic and psychological health. There are currently 19 known PCOS risk loci, primarily identified in women of Han Chinese or European ancestry, and 14 of these risk loci were identified or replicated in a genome-wide association study of PCOS performed in up to 10,074 cases and 103,164 controls of European descent. However, for most of these loci the gene responsible for the association is unknown. We therefore use a Bayesian colocalization approach (Coloc) to highlight genes in PCOS-associated regions that may have a role in mediating the disease risk. We evaluated the posterior probabilities of evidence consistent with shared causal variants between 14 PCOS genetic risk loci and intermediate cellular phenotypes in one protein (N = 3301) and two expression quantitative trait locus datasets (N = 31,684 and N = 80–491). Through these analyses, we identified seven proteins or genes with evidence of a possibly shared causal variant for almost 30% of known PCOS signals, including follicle stimulating hormone and ERBB3, IKZF4, RPS26, SUOX, ZFP36L2, and C8orf49. Several of these potential effector proteins and genes have been implicated in the hypothalamic–pituitary–gonadal signalling pathway and provide an avenue for functional follow-up in order to demonstrate a causal role in PCOS pathophysiology.
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spelling pubmed-84405982021-10-04 Colocalization analysis of polycystic ovary syndrome to identify potential disease-mediating genes and proteins Censin, Jenny C. Bovijn, Jonas Holmes, Michael V. Lindgren, Cecilia M. Eur J Hum Genet Article Polycystic ovary syndrome (PCOS) is a common complex disease in women with a strong genetic component and downstream consequences for reproductive, metabolic and psychological health. There are currently 19 known PCOS risk loci, primarily identified in women of Han Chinese or European ancestry, and 14 of these risk loci were identified or replicated in a genome-wide association study of PCOS performed in up to 10,074 cases and 103,164 controls of European descent. However, for most of these loci the gene responsible for the association is unknown. We therefore use a Bayesian colocalization approach (Coloc) to highlight genes in PCOS-associated regions that may have a role in mediating the disease risk. We evaluated the posterior probabilities of evidence consistent with shared causal variants between 14 PCOS genetic risk loci and intermediate cellular phenotypes in one protein (N = 3301) and two expression quantitative trait locus datasets (N = 31,684 and N = 80–491). Through these analyses, we identified seven proteins or genes with evidence of a possibly shared causal variant for almost 30% of known PCOS signals, including follicle stimulating hormone and ERBB3, IKZF4, RPS26, SUOX, ZFP36L2, and C8orf49. Several of these potential effector proteins and genes have been implicated in the hypothalamic–pituitary–gonadal signalling pathway and provide an avenue for functional follow-up in order to demonstrate a causal role in PCOS pathophysiology. Springer International Publishing 2021-03-04 2021-09 /pmc/articles/PMC8440598/ /pubmed/33664499 http://dx.doi.org/10.1038/s41431-021-00835-8 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Censin, Jenny C.
Bovijn, Jonas
Holmes, Michael V.
Lindgren, Cecilia M.
Colocalization analysis of polycystic ovary syndrome to identify potential disease-mediating genes and proteins
title Colocalization analysis of polycystic ovary syndrome to identify potential disease-mediating genes and proteins
title_full Colocalization analysis of polycystic ovary syndrome to identify potential disease-mediating genes and proteins
title_fullStr Colocalization analysis of polycystic ovary syndrome to identify potential disease-mediating genes and proteins
title_full_unstemmed Colocalization analysis of polycystic ovary syndrome to identify potential disease-mediating genes and proteins
title_short Colocalization analysis of polycystic ovary syndrome to identify potential disease-mediating genes and proteins
title_sort colocalization analysis of polycystic ovary syndrome to identify potential disease-mediating genes and proteins
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8440598/
https://www.ncbi.nlm.nih.gov/pubmed/33664499
http://dx.doi.org/10.1038/s41431-021-00835-8
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