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Meta-analysis identifies five novel loci associated with endometriosis highlighting key genes involved in hormone metabolism

Meta-analysis identifies five novel loci associated with endometriosis highlighting key genes involved in hormone metabolism


Title: Meta-analysis identifies five novel loci associated with endometriosis highlighting key genes involved in hormone metabolism
Author: Sapkota, Yadav
Steinthorsdottir, Valgerdur   orcid.org/0000-0003-1846-6274
Morris, Andrew P.
Fassbender, Amelie
Rahmioglu, Nilufer
De Vivo, Immaculata
Buring, Julie E.
Zhang, Futao
Edwards, Todd L.
Jones, Sarah
... 33 more authors Show all authors
Date: 2017-05-24
Language: English
Scope: 15539
University/Institute: Háskóli Íslands
University of Iceland
School: Heilbrigðisvísindasvið (HÍ)
School of Health Sciences (UI)
Department: Læknadeild (HÍ)
Faculty of Medicine (UI)
Series: Nature Communications;8
ISSN: 2041-1723
DOI: 10.1038/ncomms15539
Subject: Genetic variation; Genetics research; Genome-wide association studies; Risk factors; Erfðabreytileiki; Erfðafræði; Áhættuþættir; Rannsóknir
URI: https://hdl.handle.net/20.500.11815/342

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Citation:

Sapkota, Y., Steinthorsdottir, V., Morris, A. P., Fassbender, A., Rahmioglu, N., De Vivo, I., . . . Nyholt, D. R. (2017). Meta-analysis identifies five novel loci associated with endometriosis highlighting key genes involved in hormone metabolism. 8, 15539. doi:10.1038/ncomms15539

Abstract:

Endometriosis is a heritable hormone-dependent gynecological disorder, associated with severe pelvic pain and reduced fertility; however, its molecular mechanisms remain largely unknown. Here we perform a meta-analysis of 11 genome-wide association case-control data sets, totalling 17,045 endometriosis cases and 191,596 controls. In addition to replicating previously reported loci, we identify five novel loci significantly associated with endometriosis risk (P<5 × 10−8), implicating genes involved in sex steroid hormone pathways (FN1, CCDC170, ESR1, SYNE1 and FSHB). Conditional analysis identified five secondary association signals, including two at the ESR1 locus, resulting in 19 independent single nucleotide polymorphisms (SNPs) robustly associated with endometriosis, which together explain up to 5.19% of variance in endometriosis. These results highlight novel variants in or near specific genes with important roles in sex steroid hormone signalling and function, and offer unique opportunities for more targeted functional research efforts.

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