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

Sulayman, Hikmat
2025 · doi:10.5281/zenodo.17100919 · W7081321456
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This paper describes a curated dataset that accompanies a systematic literature review and meta-analysis assessing how hereditary genetic factors contribute to endometriosis. It uses MeSH-based searches in multiple databases (through March 20, 2025), includes reproductive-aged women with surgically confirmed endometriosis, and extracts study design, population characteristics, genetic factors, outcomes, and risk of bias (with Newcastle–Ottawa Scale scoring), while excluding animal/cell studies, adenomyosis and ovarian cancer studies, drug-related work, and studies without genetic or inheritance components or adequate sample size. Where feasible, the underlying meta-analysis pools effect sizes using a random-effects model, and a major limitation implied by the methods is that only English-language, full-text-available human studies with at least 10 participants are included. This paper is centrally about endometriosis — it provides the dataset for a review and meta-analysis of genetic factors and heritability in endometriosis.

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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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