Dataset from a Systematic Literature Review and Meta-Analysis of Genetic Factors in Endometriosis

Sulayman, Hikmat
2025 · doi:10.5281/zenodo.17100918 · W7081273196
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This dataset from a systematic literature review and meta-analysis compiles extracted study information, risk of bias assessments, and pooled genetic factor results for endometriosis.

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This dataset accompanies a systematic literature review and meta-analysis that investigates the hereditary nature of endometriosis by examining genetic factors in reproductive-aged women. The authors conducted comprehensive searches across multiple databases to identify studies reporting on gene mutations, expression, or inheritance patterns in surgically confirmed cases. The resulting structured data includes risk of bias assessments and pooled effect sizes to support transparency and secondary analysis within the field. This paper is centrally about endometriosis — specifically focusing on the genetic associations and hereditary components of the disease.

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Abstract

Description This dataset accompanies a systematic literature review (SLR) and meta-analysis examining the role of genetic factors in endometriosis. The central research question was: “To what degree is endometriosis a hereditary disease?” Systematic searches were conducted using the Medical Subject Headings (MeSH) terms: (“endometriosis”) AND (gene OR associated gene OR genetics OR hereditary OR inheritance). The dataset contains extracted study-level information, risk of bias assessments, and pooled results from included studies. It has been structured to promote transparency, reproducibility, and secondary analyses within the field of endometriosis genetics. Objective The dataset provides a curated and structured collection of studies examining genetic associations with endometriosis. By making this data openly available, it supports replication, data reuse, and further investigations into the genetic basis of endometriosis. Methods Search strategy: Searches were conducted in PubMed, Cochrane Library, Scopus, Medline, and CINAHL Ultimate up to March 20, 2025. Inclusion criteria: Studies involving reproductive-aged women (15–49 years) with surgically confirmed endometriosis and reporting genetic traits, gene mutations, gene expression, or inheritance patterns. Exclusion criteria: Non-human studies (animal or cell line); studies on adenomyosis or ovarian cancer; drug-related studies; those lacking genetic or inheritance components; case studies, reviews, or meta-analyses; articles without full-text access; publications in languages other than English; or studies with <10 participants or unreported sample size. Data extraction: Study design, population characteristics, genetic factors, and outcomes were extracted. Analysis: Where feasible, meta-analyses pooled effect sizes using a random-effects model. Supplementary Data Supplementary Data I: Protocol Supplementary Data II: Systematic Literature Review (one page per step of the process) Supplementary Data III: Newcastle-Ottawa Scale (NOS) assessment scoring Supplementary Data IV: Data Extraction and Analysis Citation If you use this dataset, please cite as: Sulayman, H. (2025) ‘Dataset from a Systematic Literature Review and Meta-Analysis of Genetic Factors in Endometriosis’. Zenodo. doi:10.5281/zenodo.17100919
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Objective

The dataset provides a curated and structured collection of studies examining genetic associations with endometriosis. By making this data openly available, it supports replication, data reuse, and further investigations into the genetic basis of endometriosis.

Methods

- Search strategy: Searches were conducted in PubMed, Cochrane Library, Scopus, Medline, and CINAHL Ultimate up to March 20, 2025. - Inclusion criteria: Studies involving reproductive-aged women (15–49 years) with surgically confirmed endometriosis and reporting genetic traits, gene mutations, gene expression, or inheritance patterns. - Exclusion criteria: Non-human studies (animal or cell line); studies on adenomyosis or ovarian cancer; drug-related studies; those lacking genetic or inheritance components; case studies, reviews, or meta-analyses; articles without full-text access; publications in languages other than English; or studies with <10 participants or unreported sample size. - Data extraction: Study design, population characteristics, genetic factors, and outcomes were extracted. - Analysis: Where feasible, meta-analyses pooled effect sizes using a random-effects model. Supplementary Data - Supplementary Data I: Protocol - Supplementary Data II: Systematic Literature Review (one page per step of the process) - Supplementary Data III: Newcastle-Ottawa Scale (NOS) assessment scoring - Supplementary Data IV: Data Extraction and Analysis Citation If you use this dataset, please cite as: Sulayman, H. (2025) ‘Dataset from a Systematic Literature Review and Meta-Analysis of Genetic Factors in Endometriosis’. Zenodo. doi:10.5281/zenodo.17100919 Files Files (7.1 MB) | Name | Size | Download all | |---|---|---| | md5:f036661d99b8c9d98ea61aeb8c1878fb | 390.6 kB | Download | | md5:26802d2bc27c0914c8824ec800ad71a8 | 318.5 kB | Download | | md5:229f2ee9926f7ca7719c327692938ace | 32.6 kB | Download | | md5:a3d04c424714bbc6a838c123f7a92092 | 6.3 MB | Download |

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Condition tags

endometriosisadenomyosis

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last seen: 2026-05-10T10:52:01.003817+00:00
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