Large-Scale Data Analysis on Endometriosis from the UK Biobank Reveals Novel Genetic Loci.

Nilüfer Rahmioğlu, Jason P. Cook, Christian V. Becker, A P Morris, Krina T. Zondervan
2018 · vol. 25 · W2898543063
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Researchers utilized UK Biobank data to expand a genome-wide association study of endometriosis, aiming to identify novel genetic loci beyond the 14 previously known significant sites.

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This study presents a large-scale genetic analysis of endometriosis utilizing data from the UK Biobank to identify novel risk loci. By incorporating genotype data and self-reported medical records from 500,000 volunteers, the researchers aimed to substantially increase the sample size beyond previous meta-analyses that identified only 14 significant loci explaining a small fraction of heritability. The paper highlights the potential for these expanded datasets to uncover additional genetic factors contributing to the condition’s estimated 50% heritability. This paper is centrally about endometriosis — specifically the identification of novel genetic loci through large-scale biobank data analysis.

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Abstract

Endometriosis is a common complex condition with an estimated heritability of 50%. The largest meta-analysis of genome-wide association studies (GWAS) for endometriosis to date, including 17K cases, identified 14 genome-wide significant loci (p<5x10-8) together explaining only 5% of the heritability. In ongoing analyses we are substantially increasing sample size by including novel datasets such as the UK Biobank. The UK Biobank involves medical records and self-reported questionnaire data on 500,000 volunteer participants, for which the full genotype data, imputed up to the HRC reference panel, has been recently released.
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Conference item Large-scale data analysis on endometriosis from the UK Biobank reveals novel genetic loci - Abstract: - Endometriosis is a common complex condition with an estimated heritability of 50%. The largest meta-analysis of genome-wide association studies (GWAS) for endometriosis to date, including 17K cases, identified 14 genome-wide significant loci (p<5x10-8) together explaining only 5% of the heritability. In ongoing analyses we are substantially increasing sample size by including novel datasets such as the UK Biobank. The UK Biobank involves medical records and self-reported questionnaire data on 500,000 volunteer participants, for which the full genotype data, imputed up to the HRC reference panel, has been recently released. - Publication status: - Published - Peer review status: - Peer reviewed Actions Access Document - Files: - - (Preview, Accepted manuscript, pdf, 262.7KB, Terms of use) - - Publisher copy: - 10.1177/1933719118759999 Authors - Publisher: - SAGE Publications - Host title: - 65th Annual Meeting of the Society for Reproductive Investigation (SRI 2018) - Journal: - 65th Annual Meeting of the Society for Reproductive Investigation (SRI 2018) More from this journal - Publication date: - 2018-02-28 - Acceptance date: - 2017-12-27 - DOI: - ISSN: - 1933-7191, 1933-7205 - Keywords: - Pubs id: - pubs:846255 - UUID: - uuid:c566a3d6-b0c3-42ae-a16e-0b4705a104fe - Local pid: - pubs:846255 - Source identifiers: - 846255 - Deposit date: - 2018-06-16 - ARK identifier: Terms of use - Copyright holder: - Society for Reproductive Investigation - Copyright date: - 2018 - Notes: - Copyright © 2018 by Society for Reproductive Investigation. This is the accepted manuscript version of the article. The final version is available online from SAGE Publications at: https://doi.org/10.1177/1933719118759999 If you are the owner of this record, you can report an update to it here: Report update to this record

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