Monogenic Contributions to Familial Endometriosis: A Scoping Review

The population (P), concept (C), context (C) framework, following Joanna Briggs Institute (JBI) guidance [ 8 ], was utilized to develop the strict eligibility criteria for inclusion and exclusion of studies. Studies focusing on patients with familial endometriosis, where a family history of the disorder has been observed, were included. Studies with a patient population consisting of sporadic cases of endometriosis were excluded. Studies identifying genes/genetic variants and the pathways associated with them in familial cases of endometriosis, and studies focusing on monogenic causes of familial endometriosis were included. Meanwhile, studies that focused on only familial aggregation of endometriosis and not genetic findings, and studies focusing on polygenic causes of endometriosis disease were excluded. English language articles, including case reports, original articles, clinical studies, clinical trials, controlled clinical trials, comparative studies, evaluation studies, multicentre studies, observational studies, randomized controlled trials, and twin studies were included. Studies conducted in all geographical regions were included. No time filter was applied. Review articles that focused on primary research and direct evidence, studies that were not accessible in full text, and articles that were not peer reviewed were excluded. Studies were also manually searched apart from database searches on Google Scholar/other relevant databases to ensure that no studies were omitted during the search. The guidelines used for the review were the JBI [ 8 ] methodology for scoping reviews and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews (PRISMA-ScR) [ 9 ] (online suppl. Table S1; for all online suppl. material, see https://doi.org/10.1159/000549442 ). The study was registered with the Open Science Framework (OSF) ( https://osf.io/k5dep/ ) on December 11, 2024. A protocol was not published. Databases such as PubMed, Scopus, Embase, and Web of Science were searched using a well-formulated search strategy to identify all relevant articles. All searches were run through the databases’ own platforms: PubMed via NCBI, Scopus via the Elsevier web interface, Embase via the Elsevier web interface, and Web of Science via the Clarivate Analytics web interface. The main keywords included “endometriosis,” “familial,” “genetics,” “variants,” and “inheritance,” along with appropriate Boolean operators. For the PubMed database, the Medical Subject Headings (MeSH) term “Endometriosis” and the main keywords were applied. The search keywords were tested by a trial run on the databases initially on October 11, 2024, to ensure that relevant articles were retrieved. The final search for articles was performed on November 5, 2024, with no time filter, to ensure that all the relevant literature published till November 5, 2024, was covered by this review. The search strategies for the databases are given in the online supplementary material (online suppl. Table S2). Following a comprehensive literature search as detailed in the earlier section, the screening process was performed by two independent reviewers. Studies identified through the four literature databases were then exported to the Rayyan QCRI software ( https://www.rayyan.ai/ ) [ 10 ], and duplicates were removed. Title and abstract screening using pre-specified inclusion and exclusion criteria was initially performed by the reviewers. The removed articles were cited with reasons for exclusion, such as incorrect disease, outcome, population, context, or concept. All the eligible studies were then subjected to full-text screening according to the inclusion criteria. Discrepancies between the two reviewers after full-text screening were resolved by discussion. The reasons for the removal of articles at both the title/abstract and full-text screening stages were noted and mentioned in the PRISMA flow diagram [ 9 ] ( Fig. 1 ). PRISMA flowchart for scoping review. Data extraction was performed using Google Spreadsheet. Potential full-text studies selected underwent data extraction procedures to retrieve significant parameters such as title, author, publication year, country in which the study was conducted, study design, techniques used, genes/genetic variants identified, pathways/mechanisms these genes are involved in, and any other major features of the study. These parameters were first piloted in three studies to ensure that no data were omitted during the process. Any necessary modifications were incorporated into the sheet, and data charting was performed for all studies. The primary data from the selected studies were extracted by one reviewer, while the second reviewer cross-checked the extracted data for quality assurance, and any discrepancies were resolved through discussion. Following data extraction, the data were collated, summarized, and analyzed using tables and figures. Functional enrichment analysis of the identified variants was performed using the EnrichR bioinformatics tool ( https://maayanlab.cloud/Enrichr/ ) [ 11 – 13 ], and the enriched pathways were visualized using the Appyters tool ( https://appyters.maayanlab.cloud/#/ ). Bar graphs were used to represent the enriched pathways ( p < 0.05). A protein-protein interaction (PPI) network was constructed for the identified genes in the STRING version 12.0 database ( https://string-db.org/ ) [ 14 ]. The PPI network created was subsequently exported to Cytoscape v3.10.3 software [ 15 ] for further analysis. Biological pathways associated with the genes were analyzed using the CyTargetLinker plugin ( https://cytargetlinker.github.io/ ), with the link set for this plugin (obtained from the GitHub repository, https://cytargetlinker.github.io/pages/linksets/wikipathways ) that incorporates pathway annotations from the WikiPathways database ( https://www.wikipathways.org/ ) [ 16 ]. A gene-pathway interaction network was then generated based on the associations. Of the 18 genes identified, 15 genes were successfully mapped to their pathways, while three genes could not be included in the gene-pathway network due to their absence in the WikiPathways database.

The initial database search yielded 5,005 studies, of which 3,068 were selected for title and abstract screening after deduplication. Only eight studies aligned with the review’s inclusion criteria were selected for full-text screening. The study selection process is summarized in the PRISMA flowchart ( Fig. 1 ). Among the eight studies, 54 patients with familial endometriosis were included for this review. The phenotypic manifestations of endometriosis varied among the affected family members, with the type of endometriosis specified for 27 patients and endometriosis stages specified for 35 out of a total of 54 patients. The details are given in the online supplementary material (online suppl. Table S3). In this scoping review, we identified 18 genes and their variants associated with familial endometriosis across multiple studies spanning different populations. Genes associated with familial endometriosis were CYP1A1 , GSTM1 , GSTT1 , CDKN2BAS , FN1 , WNT4 , UGT2B28 , USP17L2 , NPSR1 , CIITA , TNFRSF1B , GEN1 , CRABP1 , ADGRG7 , TFG , FGFR4 , NALCN , and NAV2 [ 17 – 24 ]. Reported variants comprised both coding and non-coding variants spanning exonic, intronic, and untranslated regions (3′ UTR and 5′ UTR), detailed in Table 1 . Genetic findings from the eight studies on familial endometriosis VUS, variants of uncertain significance; WES, whole exome sequencing. The identified variants have been reported to affect the pathways that cause the etiopathogenesis of endometriosis, such as steroidogenesis (estrogen and dioxin metabolism), embryonic development, detoxification, cell cycle regulation, and immune modulation. The functional roles and key pathways of the identified genes are outlined in Table 2 . Familial endometriosis genes identified with their functions and pathways One study identified the CIITA c.1949C>G;p.Ala650Gly variant, which followed an autosomal dominant inheritance pattern, with all affected members and their mother being heterozygous for the variant [ 21 ]. Similarly, another study identified FGFR4 c.1238C>T;p.Pro413Leu and NALCN c.5065C>T;p.Arg1689Trp [ 24 ] variants, which were predicted to follow an autosomal dominant inheritance pattern based on the DOMINO in silico prediction tool. The inheritance pattern of other identified genetic variants, such as UGT2B2 and USP17L2 (hemizygous deletions) [ 19 ], TNFRSF1B c.1072G>A;p.Ala358Thr, GEN1 c.1574C>T;p.Ser525Leu, CRABP1 c.54G>C;p.Glu18Asp [ 22 ], NAV2 c.2086G>A;p.Val696Met [ 24 ], and NPSR1 (c.124G>T;p.Gly42Cys; c.590G>T;p.Cys197Phe; c.1073G>A; p.Gly358Asp) [ 20 ], was not explicitly mentioned in the publications but could be inferred as autosomal dominant from the reported pedigree analyses. Other studies included in this review did not specify the mode of inheritance for the identified variants. Among the identified variants, TNFRSF1B , GEN1 , and CRABP1 [ 22 ] were classified as variants of uncertain significance according to the American College of Medical Genetics and Genomics (ACMG) guidelines [ 25 ], which indicates that their pathogenic role remains elusive and requires further investigation. FGFR4 [ 24 ] variant was classified as “likely pathogenic” by two in silico prediction tools, Combined Annotation-Dependent Depletion (CADD) PHRED score [ 26 ] and Rare Exome Variant Ensemble Learner (REVEL) [ 27 ], but not as per ACMG guidelines criteria. The other variants had no definitive ACMG classification. The role of hormonal dysregulation in endometriosis is already well-established. A study on familial endometriosis [ 17 ] from Greece reported the association of the genes CYP1A1 , GSTM1 , and GSTT1 , which have roles in estrogen and dioxin metabolism. The role of CYP1A1 in estrogen metabolism suggests that gene alterations may lead to hormonal imbalance, increasing estrogen activity, promoting ectopic endometrial growth that eventually influences disease progression. GSTM1 and GSTT1 gene variants may disrupt detoxification and oxidative stress regulation, contributing to endometriosis. A novel hemizygous deletion in the UDP glucuronosyltransferase family 2, member B28 ( UGT2B28 ) gene, spanning 14 kb, was identified in the grandmother and four of her descendants in a three-generation Greek family [ 19 ]. This gene is known to regulate the steroid hormone metabolism [ 28 ], and variations in UGT2B28 may affect the sex hormone balance, contributing to the pathogenesis of endometriosis. Inflammatory and immune-related genes have been known to play key roles in endometriosis. A novel missense variant, TNFRSF1B p.Ala358Thr, was identified in a Turkish family with four affected members using whole exome sequencing [ 22 ]. TNFRSF1B , encoding the tumor necrosis factor receptor 2 (TNFR2), mediates the TNF-TNFR signaling pathway involved in inflammation, apoptosis, angiogenesis, and cell proliferation. Elevated TNFR2 levels have been identified in endometriosis patients’ serum and peritoneal fluid, leading to dysregulated inflammatory responses [ 29 ]. Given the established role of TNFRSF1B in inflammation and apoptosis, the variant identified may contribute to endometriosis pathogenesis. One study [ 21 ] identified a novel missense variant c.1949C>G;p.Ala650Gly in the CIITA gene, which encodes a class II MHC transactivator and regulates the immune response [ 30 ]. Although CIITA is implicated in several autoimmune disorders [ 31 ], it is possible that the same mechanistic action is followed in endometriosis pathogenesis also. Functional assays, such as scratch wound and transwell assays, demonstrated that this variant significantly enhanced the migration and invasive abilities of endometrial cells. These findings suggested that the variant may contribute to endometriosis pathogenesis by impairing the immune surveillance and promoting cell migration and invasion in the ectopic endometrium. Another study [ 18 ] reported homozygosity for the risk allele of an SNP rs1333049 within the CDKN2BAS gene in four members of an Italian family affected with severe rectovaginal and ovarian endometriosis. CDKN2BAS encodes an antisense long non-coding RNA in the CDKN2B-CDKN2A gene cluster that regulates the expression of CDKN2A and CDKN2B , influencing cell processes like proliferation, apoptosis, and senescence. This gene was also identified as a susceptibility locus for endometriosis in a Japanese population [ 32 ]. This study identified another SNP rs7521902, within WNT4 , a gene known to be involved in cell growth, differentiation, immune response, and the urogenital development of organisms [ 33 ]. Another study [ 23 ] identified a copy number gain of 113 kb at chromosomal region 3q12.2 using array CGH in dizygotic twin sisters with endometriosis. The CNV region encompassed two candidate genes, Adhesion G Protein-Coupled Receptor ( ADGRG7 ) and TRK-fused gene ( TFG ), both of which are involved in the NF-κβ pathway that plays a significant role in chronic inflammation and cell proliferation and are highly relevant to endometriosis pathogenesis [ 34 ]. Notably, this CNV was absent in controls and was not reported in the Database of Genomic Variants. A study identified two missense variants, GEN1 p.Ser525Leu and CRABP1 p.Glu18Asp [ 22 ]. GEN1 plays a crucial role in DNA repair and homologous recombination, and defects in this gene may contribute to genomic instability, potentially increasing cancer susceptibility [ 35 ]. CRABP1 is known to be involved in retinoic acid-mediated differentiation in cancer [ 36 ]. Since endometriosis and cancer, especially endometrial cancer, have a strong correlation [ 37 ], the study stated that a long-term follow-up of the patients carrying the variants for the development of any malignancy would be undertaken. In another study [ 24 ], whole exome sequencing identified a heterozygous missense variant c.1238C>T;p.Pro413Leu in the fibroblast growth factor receptor 4 ( FGFR4 ) gene in a three-generation Finnish family with three affected members (three ovarian endometriosis and one with endometrial serous carcinoma). FGFR4 plays crucial roles in cell proliferation and tumorigenesis, the involvement of which depicts the interplay between endometriosis and oncogenicity [ 38 ]. In the same study, the NAV2 gene was found to harbor a missense variation c.2086G>A;p.Val696Met in a heterozygous condition among the three affected individuals. This gene has already been proposed as a predictive marker for uterine leiomyosarcoma, and it appeared that two family members who had endometriosis also had uterine leiomyosarcoma. A SNP rs1250248 within the FN1 gene was found in a heterozygous condition in the affected mother and twins, but homozygous in the affected singleton sister of a two-generation Italian family. This gene has been implicated in cell adhesion and extracellular matrix remodeling [ 18 ]. Another novel hemizygous deletion was found in the Ubiquitin Specific Peptidase 17 Like Family Member 2 ( USP17L2 ) gene in a Greek family [ 19 ], where the grandmother and her five descendants carried the variant. This gene regulates cellular processes, such as cell growth and survival, with ubiquitinating activity. This gene is known to regulate and stabilize transcription factors such as Slug, Snail, and Twist, which are key players in the epithelial-to-mesenchymal transition (EMT) [ 39 ]. Activation of the EMT repair mechanism can result in the loss of mesothelial barrier integrity and increase the risk of endometriosis development. The hemizygous deletion of USP17L2 can affect mesothelial integrity, leading to the risk of endometriosis as reported by the study [ 19 ]. A study [ 20 ] conducted on 32 families from the UK and Australia, each with three or more members affected by endometriosis, identified significant overrepresentation of three low-frequency (MAF T;p.Gly42Cys, (ii) c.590G>T;p.Cys197Phe (rs34705969), and (iii) c.1073G>A;p.Gly358Asp (rs116825950). These variants were found to be significantly enriched in familial endometriosis cases compared to controls ( p value = 7.8 × 10 −4 ). About 72% (18/25) of the familial cases had stage III/IV endometriosis as per ASRM classification [ 40 ], which suggested that NPSR1 variants were strongly associated with severe stages of endometriosis. An endometriosis mouse model created by the same study [ 20 ] exhibited decreased inflammation and pain when an inhibitor of NPSR1 , SHA68R, which blocked receptor signaling, was administered. This study states that NPSR1 can also be used as a non-hormonal target option in endometriosis treatment. Neuropeptide S receptor 1 ( NPSR1 ) encodes a G protein-coupled receptor involved in neuropeptide signaling, which plays a major role in pain-related pathways, inflammatory pathways, and immune mechanisms in endometriosis [ 41 ]. Endometriosis is primarily associated with chronic pelvic pain, largely driven by neurogenic pathways that contribute significantly to the pain sensitivity and persistent inflammation of the condition [ 42 ]. These findings reinforce the role of NPSR1 in pain perception and suggest that these missense variants may contribute to the chronic pain associated with endometriosis. Another study [ 24 ] identified a missense variant c.5065C>T;p.Arg1689Trp in the NALCN gene, which encodes a sodium leak channel involved in regulating the resting membrane potential and excitation of neurons, playing a crucial role in pain sensation, which further supports that inherited neurogenic factors can contribute to the pain phenotype in familial endometriosis. The functions and pathways of all the genes identified are detailed in Table 2 . Phenotypic associations of identified genes are listed in online supplementary Table S4. Pathway enrichment analysis of the 18 identified genes using the Enrichr tool revealed significant associations. Kyoto Encyclopedia of Genes and Genomes (KEGG) [ 43 ], Reactome [ 44 ], and WikiPathways [ 16 ] revealed the association of pathways such as the xenobiotic metabolism by cytochrome P450, cancer, biological oxidation, drug metabolism, estrogen metabolism, inflammatory response, etc., as depicted in Figure 2 . Bar plots representing pathway enrichment analysis using the Enrichr web tool for familial endometriosis: WikiPathways ( a ), Kyoto Encyclopedia of Genes and Genomes (KEGG) ( b ), and Reactome ( c ). Gene Ontology was performed to characterize genes according to their biological attributes, using functional categories such as biological processes, molecular function, and cellular components. The functional categories with a p value <0.05 were considered statistically significant. The regulation of the steroid, collagen, and long-chain fatty acid biosynthetic processes were the most enriched biological processes, glutathione transferase activity and tumor necrosis factor activity were the most significant molecular functions, and the cellular components analysis revealed enrichment in the nuclear outer membrane and the endoplasmic reticulum lumen. The gene ontology of 18 genes is depicted in Figure 3 . Bar plots representing Gene Ontology (GO) enrichment analysis using the Enrichr web tool for Familial Endometriosis: biological processes (BP; a ), molecular functions (MF; b ), and cellular components (CC; c ). The PPI network of the 18 genes constructed using STRING was exported to Cytoscape software for visualization. The gene-pathway network generated using the CyTargetLinker plug-in identified six genes, UGT2B28 , CYP1A1 , GSTM1 , WNT4 , FN1 , and TNFRS1B, which were directly involved in certain pathways related to endometriosis. UGT2B28 , CYP1A1 , and GSTM1 belonged to shared pathways such as estrogen metabolism, the meta-pathway biotransformation phase I and II, and the nuclear receptor meta-pathway, all of which play a major role in endometriosis pathogenesis, whereas WNT4 , FN1 , and TNFRS1B were involved in inflammatory response pathways and EMT pathways, further reinforcing their role in endometriosis pathogenesis. The gene-pathway network has been depicted in Figure 4 , and the genes’ functions are summarized in Table 2 . Gene-pathway network of the genes associated with familial endometriosis. Pink circles represent genes, and blue circles represent the pathways in which these genes are involved. Yellow triangles represent common pathways shared among the genes associated with endometriosis (created by Cytoscape v 9.0 and CyTargetLinker plug-in).

This scoping review underscores the genetic complexity in familial endometriosis, as well as highlights key genes along with pathways implicated in its inheritance. While significant progress has been achieved in the identification of many candidate genes, additional research is required to validate those findings. Further research is needed to explore extra genetic contributors in addition to clarifying disease inheritance patterns. Advancing the knowledge of the genetic origins of familial endometriosis will be very important to improve targeted treatments and improve disease control and management for those affected and their families.

This scoping review is the first to comprehensively summarize the genomic landscape of familial endometriosis. The investigation focused on the genes and their variants that contribute to the inheritance of endometriosis in families. It highlights 18 genes and their variants with potential roles in estrogen metabolism, immune response, oxidative stress, neurogenic pain, and cell adhesion based on eight research studies, comprising 16 families with multiple affected members from various geographical locations. The bioinformatic analysis of the identified genes further provided insights into the functional analysis of endometriosis. Enrichment analysis revealed that the genes identified in familial endometriosis cases were involved in pathways such as estrogen metabolism, inflammation, EMT, and neurogenic signaling, all of which are already known contributors to endometriosis pathophysiology. In addition, a phenome-wide association analysis performed using publicly available resources, Genopedia of Public Health Genomics and Precision Health Knowledge Base (PHGKB v10.0) ( https://phgkb.cdc.gov/PHGKB/startPagePedia.action ) and the Open Targets platform ( https://platform.opentargets.org/ ), revealed that the genes implicated in familial endometriosis are pleiotropic, showing associations with multiple traits and conditions beyond endometriosis (online suppl. Table S4). These associations reflect that familial endometriosis genes may contribute to a broader genetic architecture that overlaps with pathways such as hormone signaling, oxidative stress, inflammation, and extracellular matrix remodeling, thereby reinforcing the enrichment analysis findings. While this review focuses on the role of rare monogenic variants in familial endometriosis, it is also important to consider that these findings exist within a broader genetic landscape of the disease. A significant number of low-effect common variants have been uncovered over the past few decades through large-scale GWAS. More than 40 robust loci are found to be associated with endometriosis risk, including genes such as WNT4 , FN1 , CDKN2BAS , GREB1 , VEZT , etc., which are involved in sex steroid hormone signaling, immune function, and cell adhesion [ 1 ]. It is speculated that these common variants may interact with the rare, high-penetrance variants found in the families, potentially influencing the penetrance and disease severity. Many studies report that somatic mutations within endometriotic lesions ( ARID1A, PIK3CA, KRAS ) [ 45 ], epigenetic dysregulations involving histone modifications and DNA methylation [ 46 ], and gene-to-environment interactions [ 47 ] are also contributing factors toward endometriosis pathophysiology. Thus, the genetic landscape of endometriosis could be viewed as a combination of rare monogenic variants, common variants, and non-genetic modifiers that converge on shared biological pathways. It is also important to consider that familial aggregation does not always imply a strong genetic etiology, as clustering within families may also arise due to shared environmental or lifestyle factors [ 48 ]. Among the genes reported in familial endometriosis, mentioned in our review, some have strong evidence for involvement in the disease biology, such as WNT4 and CDKN2BAS. Although the association of these genes is well-established with endometriosis, their precise function remains elusive and is often indirect. By contrast, other genes, such as GSTT1 , even though explored in many studies, show no direct association with endometriosis. Given the high frequency of GSTT1 polymorphisms in the general population, it is unlikely to act as a sole genetic predisposition factor to endometriosis. However, in combination with other polymorphisms in the GSTM1 gene, it might increase the susceptibility to the disorder [ 49 ]. While these genes may be predicted to be an integral part of the disease susceptibility, their effects are also modulated by additional genetic, environmental, and lifestyle factors. Familial endometriosis studies can highlight high-penetrance variants, but the overall strength of the evidence relies on context-specific entities where these genes can be only partial contributors to endometriosis. While this scoping review provides valuable findings regarding the genetic landscape of familial endometriosis, several critical knowledge gaps remain. First is the dearth of the number of studies available on familial endometriosis. The available studies have very few sample sizes, restricting the generalizability of the findings. Second is that, although our bioinformatic analyses revealed the functional roles for the identified genes, experimental validation of the genetic variants remains scarce. The only study included in this review that discussed the functional effect of the genetic variant was the study conducted by Zhu et al. [ 21 ]. Third, there is a lack of ethnic diversity in the familial endometriosis research. The majority of studies included in this review are from European and East Asian populations, raising concerns about the applicability of findings to other regions. In India, even after being a nation with such a high prevalence of familial history of endometriosis, there is not even a study on this aspect. A risk of bias assessment conducted using the JBI critical appraisal checklist for case reports (online suppl. Table S5) did not reveal any limitations that were severe enough to exclude any of the studies. However, even with all studies meeting the minimum quality criteria, many of them presented with lacunae in the evidence. Most of the studies included in the review comprise no more than two families, with limited functional validation for the identified variants. Additionally, the reporting of identified genetic variants was often incomplete, with some studies failing to mention the inheritance patterns of the variants, rs identifiers, or the ACMG classification criteria. This is the first scoping review that provides a systematic synthesis of genes implicated in familial endometriosis, highlighting the key pathways and mechanisms involved in disease pathogenesis. By using stringent inclusion criteria and multiple databases, we ensured a comprehensive overview of the current literature regarding the genetics of familial endometriosis. Also, the integration of bioinformatic analysis further strengthened the findings by linking the genetic variants to their specific biological pathways relevant to endometriosis. Nevertheless, the study has several limitations. The included studies have heterogeneity in their methodologies, such as techniques used, variant interpretation criteria, and sample selection, which creates a barrier to directly comparing the results across the studies. Additionally, the review only included peer-reviewed studies in English, which may have led to the exclusion of relevant research studies published in other languages. Also, a significant limitation was the inability to access the full text of seven relevant studies, even after contacting the authors. The exclusion of these studies might have led to the omission of additional genetic variants potentially affecting the findings of the review.

Endometriosis is a debilitating chronic condition that is characterized by the presence of endometrial-like tissue outside the uterus, mostly on the pelvic peritoneum, ovaries, and fallopian tubes [ 1 ], causing chronic and severe pelvic pain, dyspareunia, dysmenorrhea, dyschezia, menorrhagia, and in some cases, even infertility. It affects 5–10% of women of reproductive age globally [ 2 ], significantly impacting physical health as well as mental well-being. Endometriosis is considered a complex, multifactorial disorder influenced by various genetic and environmental factors, many of which remain unknown. The clinical heterogeneity of the disease due to diverse symptoms further complicates timely diagnosis, treatment, and management. Endometriosis has a diagnostic delay of 5–12 years from the onset of symptoms to a confirmed diagnosis [ 3 ]. This delay stems from symptom overlap with other gynecological or gastrointestinal conditions and the reliance on the invasive laparoscopic procedure [ 3 ]. Familial clustering underscores the significant role of genetic predisposition in endometriosis pathogenesis. As first reported by Simpson et al. [ 4 ], the first-degree relatives of endometriosis-affected women have a sevenfold higher risk of the disease than the normal population. Twin studies [ 5 , 6 ] have further suggested a strong genetic contribution. In a study conducted in India, 65 of 500 patients (13%) with endometriosis had a family history of endometriosis, with a mother, sister, or even grandmother being affected [ 7 ]. A genome-wide association study (GWAS) meta-analysis identified 42 genome-wide significant loci, comprising 49 distinct association signals. These common variants account for approximately 5% of the population-level heritability for the disorder, suggesting that rare genetic variants and other unidentified genetic and environmental factors may be responsible for the “missing heritability” [ 1 ]. While existing studies have investigated the genetics of sporadic endometriosis extensively, familial cases have been largely understudied. Familial studies on endometriosis will identify rare, monogenic variants that may provide critical insights into disease mechanisms and potentially pave the way for personalised treatment strategies. The gap in research on the familial genetics of endometriosis limits our understanding of the monogenic landscape of this disorder. To bridge this gap, this review aims to systematically collate the available literature and identify genes, variants, pathways, and mechanisms associated with familial endometriosis. Thus, our “review question” is What is the genetic landscape known so far for familial endometriosis?

The authors have no conflicts of interest to declare.

The authors acknowledge Intramural funding to AG from Manipal Academy of Higher Education, Manipal, Karnataka, India (MAHE); and Dr. TMA Pai fellowship to LEJ from Manipal Academy of Higher Education, Manipal, Karnataka, India (MAHE). The funder had no role in the design, data collection, data analysis, and reporting of this study.

A statement of ethics is not applicable as this is a scoping review and does not require ethical approval, as no direct participation of subjects is involved and no identifying information is included. However, all studies included in this review were conducted in accordance with ethical standards as stated in their respective publications.

All authors have contributed to the work reported. Individual author contributions are as follows: conceptualization, manuscript review and editing, and supervision: A.G.; literature screening, data extraction, analysis, and synthesis: L.E.J. and A.G.; manuscript preparation: L.E.J.; intellectual inputs: A.G., S.U., V.S.D., R.R.D., A.M., P.A., and S.G.