Endometriosis - on the intersection of modern environmental pollutants and ancient genetic regulatory variants

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Despite increasing genomic insights into advanced-stage disease, the genetic underpinnings of early-stage endometriosis remain poorly understood, limiting opportunities for timely diagnosis and intervention. This study explores the contribution of regulatory variants, including those derived from ancient hominin introgression, and their interaction with modern environmental exposures in shaping endometriosis susceptibility. We conducted a dual-phase literature review to identify genes implicated in endometriosis pathophysiology and endocrine-disrupting chemical (EDC) sensitivity. Five genes ( IL-6, CNR1, IDO1, TACR3, and KISS1R ) were selected based on tissue expression, pathway involvement, and EDC reactivity. Whole-genome sequencing data from the Genomics England 100,000 Genomes Project were analysed in nineteen females with clinically confirmed endometriosis. Variant enrichment, co-localisation, and linkage disequilibrium analyses were conducted, and functional impact was evaluated using public regulatory databases. Six regulatory variants were significantly enriched in the endometriosis cohort compared to matched controls and the general Genomics England population. Notably, co-localised IL-6 variants rs2069840 and rs34880821—located at a Neanderthal-derived methylation site—demonstrated strong linkage disequilibrium and potential immune dysregulation. Variants in CNR1 and IDO1 , some of Denisovan origin, also showed significant associations. Several of these variants overlapped EDC-responsive regulatory regions, suggesting gene-environment interactions may exacerbate risk. These findings propose a novel model of endometriosis susceptibility, in which ancient regulatory variants and contemporary environmental exposures converge to modulate immune and inflammatory responses. This integrative approach identified new potential biomarkers for early-stage detection of endometriosis. Biological sciences/Genetics/Gene expression Biological sciences/Genetics/Evolutionary biology Health sciences/Endocrinology/Endocrine system and metabolic diseases/Endocrine reproductive disorders Figures Figure 1 Figure 2 Figure 3 1 Introduction Globally, ten percent of reproductive-aged women have endometriosis, a heterogeneous gynaecological disease driven by estrogen signalling ( 1 ). Endometriosis can be difficult to diagnose due to limited diagnostic tools, contributing to misdiagnosis and delays. Diagnosis can take up to eleven years between symptom onset and diagnosis ( 2 ). Fifty percent of diagnosed women medically reported severe pelvic pain during adolescence that went untreated ( 3 ). Endometriosis is potentially a multifactorial disease and may involve a complex system of immunological, environmental, hormonal, and genetic factors. Studies have suggested a dampened immune response in endometriosis patients due to estrogen dominance, triggering pro-inflammatory factors and altering immune cell functions. This fuels chronic inflammation and prevents cell death, promoting endometrial lesion growth ( 4 ). Furthermore, studies using twins found a heritability component, with genome-wide association studies suggesting a genetic (47%) and environmental (53%) contribution to endometriosis predisposition ( 5 ). Environmental predisposition from modern industrial pollutants and chemicals such as endocrine-disrupting chemicals (EDCs) may play a role in endometriosis development. EDCs imitate hormones and block naturally occurring hormones from binding to receptors. This can interfere with physiological processes, including the reproductive system ( 6 ). Current genome-wide studies have collectively identified forty-two single nucleotide polymorphisms (SNPs) linked to endometriosis, some of which are associated with pain perception and maintenance and advanced endometriosis ( 7 – 9 ), however, none of these SNPs predict early endometriosis stages, hindering increased risk assessment accuracy and early diagnosis preventing complications like infertility. Despite advancements in identifying endometriosis genes, research largely focuses on advanced stages and comorbidities, rather than disease onset, leading to a diagnosis of earlier stages and prevention of endometriosis to remain elusive. Understanding genetic risk and gene-environment interaction in early endometriosis is key to improving endometriosis management and preventing complications like infertility and gynaecologic cancers. This study aims to bridge the gap between genetics and environmental risk factors, providing a more comprehensive model of endometriosis susceptibility and identifying potential biomarkers for early-stage detection. 2 Materials and Methods 2.1 Ethical Approval This study received ethical approval from Bournemouth University’s Institutional Research Ethics Panel (ID: 45978). Genomic data were obtained under Project ID 645 through the Genomics England 100,000 Genomes Project. All participants provided informed consent for the use of their data in secondary research. 2.2 Literature Searches A two-phase systematic literature review was conducted using PubMed and Web of Science to identify genes and genomic markers implicated in endometriosis pathophysiology and their interaction with environmental exposures, particularly EDCs. 2.2.1 Literature Selection Criteria Inclusion Criteria: Original studies focusing on genomic/genetic analysis, or genome-wide association design., Only human participants (no other species)., Patients with a diagnosis of endometriosis for at least a year., Patients aged between eighteen and forty-three years at the time of recruitment. Exclusion Criteria: Review studies., Studies including participants with other types of female infertility., Participants without an endometriosis diagnosis., Participants with additional illnesses and diseases which could affect result outcomes. A literature search investigating environmental risk factors for endometriosis and a review of their impact on signalling pathways and related genes was conducted. The key words used were; “endometriosis” and “exposure to endocrine disrupting chemicals”, “endocrine disrupting chemicals”, “exposure to pesticides”, “pesticides”, “personal care products”, “cosmetics”, “exposure to heavy metals”, “heavy metals”, “exposure to radiation”, “radiation”, “exposure to toxins”, “toxins”, “chemicals”, “plastics”, “exposure to pollution”, “pollution”, “exposure to air pollution”, “air pollution”, “exposure to water pollution”, “water pollution”. This yielded sixty-four papers and excluded 236 papers. Figure one shows the screening process of the primary literature search as a PRISMA flow chart. EDCs were identified as the most significant environmental factor to endometriosis. Leading this study to focus on their association with genetic susceptibility to endometriosis. A secondary literature search was conducted to identify genomic areas/ markers of interest involved in endometriosis. The keywords used in this search were; “endometriosis” and “polymorphism”, “SNP”, “genetic polymorphism”, “variants”, “locus”, “GWA”, “Genome-wide”, “Genome wide”, “Genetic association study”. This yielded 166 papers and excluded 2476 papers. Figure two shows the screening process of the secondary literature search as a PRISMA flow chart. This literature search identified fifty-seven genes of interest relating to endometriosis risk susceptibility; from this, five genes were chosen to investigate further. These were chosen through identifying the main function of the gene and where it is expressed using the National Library of Medicine (NIH). The pathways of the gene’s pathways were identified using Reactome. The criteria for this selection were: literature has shown EDCs are associated with the gene, and their effects are within the signalling pathways in which the selected genes are involved. Pathways associated with the gene are associated or involved in endometriosis onset or progression., Selected genes are expressed within associated tissues of endometriosis implant locations., The main function of the gene, when disrupted, potentially leads to endometriosis development. 2.3 100,000 Genomics England Database The Genomics England (GE) 100,000 genome database was used as a part of an ongoing larger project “Genomic and chromosomal instability sequence markers in relation to fertility, early pregnancy, and cancers of the reproductive tissues” and included domains of Ovarian Cancer GE Research Network (GERN) and Endocrine and Metabolism GERN to obtain participants and analyse genomic data. Participants from the GE Rare Disease Programs GRCh38 Participant Explorer were chosen by searching for a clinical diagnosis of endometriosis. Inclusion Criteria: Female participants aged eighteen to forty-three years at the time of recruitment., Diagnosis of endometriosis recorded in medical history., Availability of whole-genome sequencing (WGS) data., Inclusion of participants with endometriosis-related infertility and/or ovarian chocolate cysts. Exclusion Criteria: Individuals not assigned female sex at birth., Participants over 43 years (to minimize cofounding by menopause-related genetic changes)., Presence of additional ovarian pathology, chromosomal abnormalities, haematological disorders or other reproductive tract malignancies., Diagnosis of diabetes., Immunological disorders, or hormonal conditions that could confound genetic associations., Body mass index outside the range of 18.5-30 kg/m2 to minimize metabolic confounders' impact. The final study cohort included nineteen individuals meeting these criteria. Endometriosis stages were estimated using American Society of Reproductive Medicine criteria and additional clinical information, such as location of endometrial implants and/or lesions and procedures or investigations carried out in relation to endometriosis in the patient’s profile, as the participant Explorer database did not specify stage. Table one depicts the study criteria to estimate endometriosis stage. Each of the five selected genes were searched in GE per participant and single nucleotide variations (SNV), and insertion-deletion mutations (INDELs) were collected. This study focused on regulatory regions, introns, upstream, and downstream sequences, instead of coding regions, as environmental pollutants are more likely to affect gene expression than protein structure (10). Targeting these regions enabled a more efficient and detailed investigation of relevant genomic variants. 2.4 Statistical analysis and linkage disequilibrium Heatmaps were created using GraphPad Prism v10 to visualise variants across stages. Variant frequencies were compared between the general GE population and the endometriosis cohort using R v4.2.2 a X2 goodness of fit test for individual variants with Fisher’s combined probability and small sample corrections relevant to data discovery. A Benjamini-Hochberg (BH) false discovery rate correction was applied to p-values, to account for multiple hypothesis testing controlling for false positives while maintaining statistical power. To confirm that variant enrichment was specific to the endometriosis cohort, nineteen randomly selected individuals without endometriosis from the GE database were screened using the same method. A Fisher's combined probability test compared variant frequencies across the endometriosis cohort, random group, and total GE population. Statistically significant variants were assessed for co-localisation to determine non-random clustering within the endometriosis cohort. Linkage disequilibrium analysis was conducted to assess the correlation between regulatory variants associated with endometriosis. Pairwise LD values Pairwise LD values (D’ and r²) were calculated for rs34880821 and rs2069840 in IL-6 and rs806372 in CNR1 , using data from the 1000 Genomes Project across multiple populations. LDpair and LDpop from LDlink were used to determine linkage strength, with comparisons across African, East Asian, European, South Asian, and Admixed American populations. Results were analysed to evaluate population-specific evolutionary pressures and potential functional implications for immune regulation and pain sensitivity. 2.5 Regulatory Sequence Analysis To identify statistically significant variant effects a search of the variants rsID was undertaken using ClinVar, dbSNP, ensemble, UCSC, and String. An extensive analysis was conducted using UCSC and previous literature on other hominoids and the conservation of the statistically significant variants. All results are reported with adjusted p-values, and statistically significant associations are discussed in the context of biological plausibility and environmental interactions. 3 Results 3.1 Genomic findings of five selected genes and Significant variant findings Through using the literature search and consulting the criteria, the five genes chosen to be investigated further were IDO1 (Indoleamine two, three-dioxygenase one), IL-6 (Interleukin six), CNR1 (cannabinoid receptor one), TACR3 (tachykinin receptor three), and KISS1R ( KISS1 receptor). Ten genetic variants were identified as potential contributors to endometriosis when compared to both the study population and the GE general population. Of these, 40% had a frequency of 0% in the Ensembl general population but were present in the GE general population. This is potentially due to GE participants having a higher percentage of genetic mutations and variants through recruiting participants with known rare genetic conditions or specific diseases. After conducting an X2 goodness of fit test for each of the ten variants found using the study cohort population frequency and GE total population frequency, variants, rs806372, rs76129761, rs2069840, rs34880821, rs933717388, and rs72643906 were found to be statistically significant. A BH test was conducted on the X2 goodness of fit test, which shows the variants are significant in the endometriosis cohort. When observing co-occurrence with other significant variants, rs2069840 and rs34880821 showed the strongest co-occurrence within eight individuals in the endometriosis cohort. Whereas rs806372 and rs933717388 show moderate co-occurrence in three individuals. However, rs76129761 and rs72643906 rarely occur with other variants. When conducting a co-localisation analysis, rs2069840 and rs34880832 show a strong co-localisation effect. The expected frequency for co-localisation for the variants is two participants in the cohort of nineteen (10.5%), based on P(co-localise) = 0.316x0.263=0.083. In the endometriosis group, eight individuals had both variants (47.4%), which is significantly higher than expected at p=0.0001, showing a strong co-localisation effect. However, in the random group, this was seen in six individuals (31.6%), which was also higher than expected at p=0.0110 but is less pronounced than the endometriosis group. This shows the co-localisation of rs2069840 and rs34880821 occurs much more frequently than would be expected by chance in both groups. Furthermore, both variants individually and together show significant enrichment in the endometriosis group. This suggests a potential biological interaction between these variants that may be particularly relevant to endometriosis. When comparing the six significant variants in the endometriosis cohort compared to the random sample cohort and total GE populations, each of the variants is shown to be significantly higher in the endometriosis group, except rs76129761, which is shown to be higher in the random sample cohort. From the Fisher’s combined probability test between the endometriosis cohort and the random sample compared to the GE total population a combined X2 statistic; 44.37, with a p-value of 0.000013 (p<0.001), showed strong evidence in overall frequency difference between the endometriosis cohort and the GE total population across all endometriosis variants. This suggests that the genetic profile of the endometriosis cohort significantly deviates from the general population, potentially indicating a unique genetic signature associated with endometriosis. Furthermore, the combined X2 statistic for the random sample cohort, 12.23, with a p-value of 0.427, showed no significant difference between the random sample cohort and the GE total population across all endometriosis variants. This lack of significant deviation suggests that the random sample’s variant frequencies are representative of the GE total population, serving as a control group. Table two shows the variant profiles for the significant variants found within the endometriosis cohort. 3.2 LD analysis LD analysis revealed a strong linkage between Neanderthal-derived IL-6 variants (rs34880821 and rs2069840) (depicted in Figure three), in East Asians (D’ = 1.0, r2 = 0.9662), suggesting selective retention and potential immune regulation effects. Europeans showed moderate LD (D’ = 0.9234, r2 = 0.5794), while Africans had weak linkage (D’ = 0.8752, r2 = 0.4823), likely due to the absence of Neanderthal introgression. The Denisovan-influenced CNR1 variant (rs806372) exhibited moderate LD in East Asians (D’ = 0.8004) but weak LD in Europeans (D’ = 0.4607) and South Asians (D’ = 0.1459), suggesting population-specific evolutionary pressures. African populations had negligible LD for both variant pairs, supporting the hypothesis that these associations arose post-migration due to archaic human introgression. These findings highlight six regulatory variants significantly enriched in the endometriosis cohort. Notably, the IL-6 variants rs2069840 and rs34880821 not only co-occurred at a rate well above chance but also exhibit population-specific LD consistent with archaic hominin ancestry and potential immunoregulatory roles. Other significant variants in CNR1 , IDO1 , and KISS1R were associated with transcription factor binding sites and are located in genomic regions shown to be responsive to endocrine-disrupting chemicals. 4 Discussion Many sufferers of endometriosis are subject to misdiagnosis and delays due to limited understanding of early-stage risk factors. To obtain a better understanding of genetic factors predisposing to endometriosis development, two literature searches and interrogation of the GE 100,000 genome database were conducted. Using a highly targeted multilevel approach, five genes have been characterised as potential targets in the developing endometriosis pathway, containing variants or having altered expression levels, with five variants found as highly significant and one as moderately significant in our cohort population when compared to GE. This builds on the work conducted by Sapkota, Zondervan, and Rahmioglu (7–9), who collectively found forty-two SNPs linked to endometriosis. 4.1 IDO1 The downstream variant of IDO1 rs72643906 is found to be rare in the general population, is significantly higher in the study cohort, indicating the variant may influence endometriosis development through altering IDO1 expression levels. Specifically, Brooks (11) found that immune system activation increases IDO1 expression. Furthermore, the UCSC database showed an association with an elevated risk of COVID-19, and therefore, is potentially disadvantageous to the immune system, which is seen to be associated with endometriosis patients (4). The UCSC database showed rs72643906 to alter the motif of the transcription factor Zic family member two ( ZIC2 ), which regulates tissue expression (12), this potentially modifies the ZIC2 motif to prevent the transcription factor from binding, therefore hypothetically increasing the expression levels of IDO1 and ZIC2 . Furthermore, elevated IDO1 expression has been found in endometriosis patients (13), showing a potential link between rs72643906 and endometriosis. However, when Bisphenol A (BPA) is introduced through the environment, IDO1 and ZIC2 expression levels are decreased (14,15), potentially reversing the rs72643906 effect. 4.2 CNR1 The CNR1 variants rs76129761 and rs806372 were found to be significant within the study cohort; rs76129761 is deleterious, and rs806372 has a potential splicing site implicating three alternative transcripts within intron 1 (6q15) of CNR1 . Therefore, it is possible these variants potentially increase CNR1 expression levels, leading to endometriosis development, with Allam (16) finding increased CNR1 levels in endometriosis patients when compared to controls. The UCSC database shows rs806372 to be a Denisovan variant, which may be well established in populations where Denisovans and sapiens interact, being randomly selected until the onset of EDCs in our modern society (17). The consequence of this may have been exposure to Di-(2-ethylhexyl) phthalate (DEHP) and BPA, which has been found to increase CNR1 expression (18). The UCSC database also shows rs806372 to lie on the binding site of SRY-box transcription factor ( SOX ) twelve. This may alter the motif, disrupting its binding and leading to increased CNR1 and decreased SOX12 expression levels. However, environmental DEHP exposure has been shown to elevate both SOX12 and CNR1 levels, as supported by expression studies (18,19). Whereas rs76129761 lies on the binding site of five transcription factors; Zinc finger protein 701 ( ZNF701 ), SOX4 , S0X6 , Forkhead box D3 ( FOXD3 ) and SOX11 , which may cause increased expression levels of the these and CNR1 . Furthermore, environmental BPA exposure increases SOX4 , SOX6 , and SOX11 (20,21) and decreases FOXD3 expression levels (22). 4.3 KISS1R The KISS1R intronic variant rs933717388 is a potentially novel variant (no literature or records referencing this variant) and was found to be significantly higher in the study population. The UCSC database found rs933717388 to lie on the binding sites of Zinc finger protein 707 ( ZNF707 ) and Zinc finger and BTB domain-containing protein 11 ( ZTB11 ). The variant rs933717388 may bind to the sites of transcription factors ZNF707 and ZTB11 , altering their motifs and potentially hindering their binding. Since ZBTB11 is a silencing transcription factor, reduced binding could increase KISS1R expression. This upregulation may disrupt reproductive function and promote endometriotic cell metastasis (23). Blasco (24) supports this, reporting elevated KISS1R levels in granulosa cells of endometriosis patients. Both KISS1R and transcription factor levels are potentially increased in the presence of rs933717388, and DEHP exposure further raises KISS1R expression (25), though its effect on ZNF707 or ZBTB11 remains unstudied. 4.4 IL-6 Intronic variants rs2069850 and rs34880821 of the IL-6 gene were found to be significant within the study cohort. These variants have been found to colocalise in the endometriosis cohort, which suggests a potential biological interaction between these variants that are potentially relevant to endometriosis. The UCSC showed rs34880821 to be a Neandertal methylation site. Therefore, the reference allele was methylated in Neandertals and Denisovans, but this variant abolishes the methylation site, so rs34880821 may exacerbate endometriosis development due to the disease being associated with dysregulation of the immune and inflammatory system by aberrant silencing of the area and continuous expression. This probability of heightened IL-6 expression in endometriosis patients is further validated in research by Li (26), finding an increase in IL-6 expression levels when compared to controls. 4.5 The Intersection of Ancient Genetic Variants, Epigenetic Regulation, and Modern Environmental Pollutants in Endometriosis Susceptibility Our findings highlight how ancient genetic variants inherited from Neanderthals and Denisovans, epigenetic regulation, and modern industrial pollutants may potentially converge to shape population-specific risks for endometriosis. The linkage disequilibrium (LD) analysis of IL-6 and CNR1 regulatory variants suggests that evolutionary pressures involving immune regulation and inflammatory responses, when combined with modern environmental exposures, may amplify disease susceptibility (27,28) Neanderthal introgression has significantly influenced IL-6 regulation, particularly in East Asian populations. The IL-6 variant rs34880821, located at a Neanderthal-derived methylation site, exhibits strong LD in East Asians (r² = 0.9662, D’ = 1.0), while showing weaker LD in Europeans (r² = 0.5794) and South Asians (r² = 0.8104) (27). This suggests that Neanderthal introgression may have played a role in shaping IL-6 regulatory pathways, particularly in East Asians, where it remains strongly linked. Given that East Asian populations also have the highest reported prevalence of endometriosis (~15.4%), it is likely that these genetic variants contribute to heightened inflammatory responses, immune dysregulation, and fibrotic lesion formation (29,30). The functionality for the Neanderthal-derived methylation at rs34880821 may indicate another subtle contributor to endometriosis risk. Methylation usually functions as a gene-silencing mechanism, regulating cytokine levels to prevent excessive inflammation (31). If methylation is lost, IL-6 expression could become hyperactive, leading to chronic immune activation, sustaining peritoneal inflammation, fibrosis, and deep-infiltrating endometriosis, as IL-6 is known to drive fibrotic remodelling in reproductive tissues (30). It also may account for heightened neuroinflammation, potentially explaining increased pain sensitivity in East Asian endometriosis patients (32). Similarly, the Denisovan-derived rs806372 variant in CNR1 , which is involved in immune modulation and pain perception, exhibits moderate LD in East Asians (D’ = 0.8004) but weak LD in Europeans (D’ = 0.4607) and South Asians (D’ = 0.1459) (27). Since CNR1 plays a key role in pain signalling and inflammatory responses, this Denisovan-influenced variant may enhance pain sensitivity in individuals with endometriosis, particularly in East Asian populations (28). While these ancestral variants may have once provided immune advantages in prehistoric environments, modern environmental factors may be reversing these evolutionary benefits, transforming once-adaptive immune responses into drivers of chronic disease (30). Exposure to EDCs, such as BPA, phthalates, and dioxins, has been shown to demethylate immune regulatory genes, including IL-6 , leading to excessive cytokine production (29). If Neanderthal-derived IL-6 regulatory variants are already prone to overactivation, additional EDC-induced demethylation could further escalate inflammatory signalling, worsening lesion development. This suggests a gene-environment interaction, where modern industrial chemicals exacerbate genetic predispositions inherited from archaic human ancestors. In contrast to East Asian and European populations, African populations exhibit significantly lower LD for these IL-6 and CNR1 variants (D’ < 0.02, r² < 0.001), suggesting these genetic associations arose post-migration due to Neanderthal and Denisovan introgression (27). There is limited available data on the prevalence of endometriosis in African populations, and estimates may vary due to underdiagnosis. This study supports a novel model for endometriosis susceptibility, in which ancestral genetic variants interact with modern environmental pollutants to modulate immune regulation, chronic inflammation, and pain perception across populations. 4.6 Limitations and future directions While this study provides novel insights into the genetic and environmental factors influencing endometriosis susceptibility, several limitations must be acknowledged. The sample size was limited, particularly in younger individuals under twenty-nine years old. Additionally, family-based cascade genetic testing was not included, preventing the evaluation of heritability and potential familial aggregation of risk variants. Another limitation is the reliance on medical records to infer endometriosis staging, which introduces the potential for misclassification bias. Furthermore, while this study identified significant associations between regulatory variants and endometriosis risk, functional validation through in vitro and vivo models is required to confirm their biological relevance. Further research should focus on expanding the study cohort to include a larger and more diverse population to improve the statistical power of genetic associations and assess whether these findings are consistent across different ethnic backgrounds. Family-based studies incorporating cascade genetic testing could help clarify inheritance patterns and the potential contribution of additional rare variants to endometriosis risk. Further functional studies are necessary to evaluate how the identified regulatory variants influence gene expression and immune signalling pathways, particularly in response to EDCs. Integrating environmental exposure data with genomic analysis would provide a more comprehensive understanding of how genetic and environmental factors interact in the development and progression of endometriosis. These future directions will be critical for translating genetic discoveries into practical applications for early diagnosis and personalised treatment strategies. 5 Conclusion This study provides a novel perspective on the genetic and environmental interplay driving endometriosis susceptibility, highlighting the influence of ancient regulatory variants and modern industrial pollutants. This research identified statistically significant regulatory variants in IL-6 , CNR1 , IDO1 , and KISS1R that may contribute to endometriosis risk through interactions with EDCs. These findings aim to bridge the gap between genetic predisposition, evolutionary selection, and environmental exposures, shedding light on how Neanderthal and Denisovan introgressed variants in immune and pain-regulatory genes may influence disease susceptibility in modern populations. This is the first study to systematically explore how ancient genetic signatures, epigenetic regulation, and contemporary environmental pollutants intersect in the pathophysiology of endometriosis. These results lay the first steps for future precision medicine approaches, where genetic screening combined with environmental risk assessment may improve early detection and personalised intervention strategies. Moving forward, functional validation of these regulatory variants and their interaction with endocrine disruptors will be crucial in understanding their mechanistic role in endometriosis onset and progression. These findings enhance our understanding of endometriosis as a multifactorial disease but also provide a framework for future research integrating evolutionary genetics, environmental health, and reproductive medicine. Declarations Acknowledgements Posthumous acknowledgement. This work is dedicated to our beloved colleague Dr Elpida Fragkouli for her consistent support, supervision and contribution to the study design and data interpretation. This research was made possible through access to data in the National Genomic Research Library, which is managed by Genomics England Limited (a wholly owned company of the Department of Health and Social Care). The National Genomic Research Library holds data provided by patients and collected by the NHS as part of their care and data collected as part of their participation in research. The National Genomic Research Library is funded by the National Institute for Health Research and NHS England. The Welcome Trust, Cancer Research UK and the Medical Research Council have also funded research infrastructure. Author contributions A.W. contributed to the study design, collected the data and analysed the data and drafted the manuscript. D.A. contributed to the study design, provided supervision of the study and contributed to the article drafting and editing. D.W. contributed to the study design, analysed the data and editing. J.W. contributed to data gathering. A.M. leads the GE project that this study is a part of, designed the study, data analysis and interpretation, provided supervision of the study and manuscript drafting and editing. Funding Bournemouth University funded the writing of this manuscript granted to the first author of this manuscript. Competing interests The authors declare no competing of interest. Data availability statement Research on the de-identified patient data used in this publication can be carried out in the Genomics England Research Environment subject to a collaborative agreement that adheres to patient led governance. All interested readers will be able to access the data in the same manner that the authors accessed the data. For more information about accessing the data, interested readers may contact [email protected] or access the relevant information on the Genomics England website: https://www.genomicsengland.co.uk/research. References Kanellopoulos D, Karagianni D, Pergialiotis V, Patsouras G, Patsouras K, Nikiteas N, et al. The interplay between endometriosis and fertility in rats: a systematic review. Vol. 15, Journal of Medicine and Life. 2022. Agarwal SK, Chapron C, Giudice LC, Laufer MR, Leyland N, Missmer SA, et al. Clinical diagnosis of endometriosis: a call to action. Am J Obstet Gynecol. 2019;220(4). 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Female infertility is associated with an altered expression of the neurokinin B/neurokinin B receptor and kisspeptin/kisspeptin receptor systems in ovarian granulosa and cumulus cells. Fertil Steril. 2020;114(4). Graceli JB, Dettogni RS, Merlo E, Niño O, da Costa CS, Zanol JF, et al. The impact of endocrine-disrupting chemical exposure in the mammalian hypothalamic-pituitary axis. Vol. 518, Molecular and Cellular Endocrinology. 2020. Li C, Zhao HL, Li YJ, Zhang YY, Liu HY, Feng FZ, et al. The expression and significance of leukemia inhibitory factor, interleukin-6 and vascular endothelial growth factor in Chinese patients with endometriosis. Arch Gynecol Obstet [Internet]. 2021 Jul 1 [cited 2024 Jul 17];304(1):163–70. Available from: https://link.springer.com/article/10.1007/s00404-021-05980-5 Sankararaman S, Mallick S, Dannemann M, Prüfer K, Kelso J, Pääbo S, et al. The genomic landscape of Neanderthal ancestry in present-day humans. Nature [Internet]. 2014 Jan 29 [cited 2025 May 10];507(7492):354–7. Available from: https://www.nature.com/articles/nature12961 Harris K, Nielsen R. The Genetic Cost of Neanderthal Introgression. Genetics [Internet]. 2016 Jun 1 [cited 2025 May 10];203(2):881–91. Available from: https://dx.doi.org/10.1534/genetics.116.186890 Yen CF, Kim MR, Lee CL. Epidemiologic Factors Associated with Endometriosis in East Asia. Gynecol Minim Invasive Ther [Internet]. 2019 Jan 1 [cited 2025 May 10];8(1):4. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC6367920/ Velarde MC, Bucu MEM, Habana MAE. Endometriosis as a highly relevant yet neglected gynecologic condition in Asian women. Endocr Connect [Internet]. 2023 Nov 1 [cited 2025 May 10];12(11). Available from: https://ec.bioscientifica.com/view/journals/ec/12/11/EC-23-0169.xml Zeberg H, Pääbo S. The major genetic risk factor for severe COVID-19 is inherited from Neanderthals. Nature 2020 587:7835 [Internet]. 2020 Sep 30 [cited 2025 May 10];587(7835):610–2. Available from: https://www.nature.com/articles/s41586-020-2818-3 ‘c.1018delG’ - ClinVar - NCBI [Internet]. [cited 2024 Jul 17]. Available from: https://www.ncbi.nlm.nih.gov/clinvar/?term=c.1018delG 672[geneid] - ClinVar - NCBI [Internet]. [cited 2024 Jul 17]. Available from: https://www.ncbi.nlm.nih.gov/clinvar/?term=672[geneid] 17[chr] AND 43000000:44000000[chrpos37] - ClinVar - NCBI [Internet]. [cited 2024 Jul 17]. Available from: https://www.ncbi.nlm.nih.gov/clinvar/?term=17[chr]+AND+43000000:44000000[chrpos37] 100,000 Genomes Project | Genomics England [Internet]. [cited 2024 Jul 17]. Available from: https://www.genomicsengland.co.uk/initiatives/100000-genomes-project Ensembl genome browser 112 [Internet]. [cited 2024 Jul 17]. Available from: https://www.ensembl.org/index.html Home - GraphPad [Internet]. [cited 2024 Jul 17]. Available from: https://www.graphpad.com/ National Library of Medicine - National Institutes of Health. SNPedia [Internet]. [cited 2024 Jul 17]. Available from: https://www.snpedia.com/ Gillespie M, Jassal B, Stephan R, Milacic M, Rothfels K, Senff-Ribeiro A, et al. The reactome pathway knowledgebase 2022. Nucleic Acids Res. 2022;50(D1). Szklarczyk D, Kirsch R, Koutrouli M, Nastou K, Mehryary F, Hachilif R, et al. The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest. Database issue Published online [Internet]. 2023 [cited 2025 May 10];51. Available from: https://doi.org/10.1093/nar/gkac1000 Sherry ST, Ward M, Sirotkin K. dbSNP—Database for Single Nucleotide Polymorphisms and Other Classes of Minor Genetic Variation. Genome Res [Internet]. 1999 Aug 1 [cited 2025 May 10];9(8):677–9. Available from: http://genome.cshlp.org/content/9/8/677.full Myers TA, Chanock SJ, Machiela MJ. LDlinkR: An R Package for Rapidly Calculating Linkage Disequilibrium Statistics in Diverse Populations. Front Genet [Internet]. 2020 Feb 28 [cited 2025 May 10];11:513535. Available from: www.frontiersin.org Machiela MJ, Chanock SJ. LDassoc: an online tool for interactively exploring genome-wide association study results and prioritizing variants for functional investigation. Bioinformatics [Internet]. 2018 Mar 1 [cited 2025 May 10];34(5):887–9. Available from: https://dx.doi.org/10.1093/bioinformatics/btx561 Machiela MJ, Chanock SJ. LDlink: a web-based application for exploring population-specific haplotype structure and linking correlated alleles of possible functional variants. Bioinformatics [Internet]. 2015 Nov 1 [cited 2025 May 10];31(21):3555–7. Available from: https://dx.doi.org/10.1093/bioinformatics/btv402 The National Genomic Research Library v5.1. 2020 [cited 2025 May 10]; Available from: www.genomicsengland.co.uk Tables Table 1: Criteria used in this study to estimate the patient’s endometriosis stage according to the American Sociated of Reproductive medicine (10). Stage Clinical information to diagnose endometriosis stage Stage 1 Minimal surgeries such as examination of uterus and laparoscopic approach to abdomen, with one or two locations of endometriosis within the ovary, pelvic peritoneum, uterus or rectovaginal septum and vagina. Stage 2 Had two or more locations of endometriosis within the ovary, pelvic peritoneum, uterus or rectovaginal septum and vagina and minimal surgeries such as examination of uterus and laparoscopic approach to abdomen, including removal of lesions. Stage 3 Multiple locations of endometriosis, chocolate cysts and multiple surgeries including cauterisation of organs, endoscopic freeing of adhesions and extirpation of ovaries. Stage 4 All locations of endometriosis including possible endometriosis located in the intestine in some cases, chocolate cysts and procedures of endoscopic resection, endoscopic destructions, repair of obstetric lacerations, drainage of ovarian cysts and endoscopic extirpation. Table 2: Variant profiles for the significant variants found within this cohort (created using UCSC (12)). Variant Associated gene. Variant type/ consequence. Chromosome location. Potential transcription factor (TF) binding site affected (if applicable. Number of publications. Other significant features. Pollutant interference. P-value from χ 2 goodness of fit BH-corrected p-value rs72643906 IDO1 A > G Downstream variant Chr8:39779157-399779157 ZIC2 ( Zic family member 2) None Highly conserved in mammals and vertebrates BPA and TBBPA (Tetrabromobisphenol A) can decrease methylation of IDO1 ’s mRNA and DNA (13), and TCDD can increase IDO1 expression levels (14). Exposure to BPA has been shown to decrease ZIC2 expression (15). 0.00175665990877229 0.006 rs933717388 KISS1R C > G Intron variant Chr19:912365-912365 ZNF707 ( Zinc finger protein 707 ) and ZBTB11 ( Zinc finger and BTB domain-containing protein 11 ) None Conserved in humans DEHP exposure influences regulators of HPGA by regulating GnRH (Gonadotropin hormone-releasing hormone) release altering KISS1R expression (16). 0.017530950708949900 0.036 rs34880821 IL-6 G > A Intergenic Chr7:22775450-22775450 None 3 Conserved in humans Methylation site. Neandertal variant. Exposure to TCDD can increase the expression of IL-6 (14). 0.006042586245540780 0.024 rs2069840 IL-6 C > G Intronic Chr7:22768572-22768572 None 12 Conserved in rhesus, mouse, and dogs. Exposure to TCDD can increase the expression of IL-6 (14). 0.020059606754631400 0.040 rs76129761 CNR1 CTCT > CT Intron Chr6:88860156-88860156 ZNF701 ( Zinc finger protein 701 ), SOX4 (SRY-box transcription factor 4), SOX6 (SRY-box transcription factor 6), FOXD3 ( Forkhead box D3 ) and SOX11 (SRY-box transcription factor 11). None Conserved in human, rhesus, mouse, and dogs. Exposure to DiNP and BPA significantly increased the expression of CNR1 (17). Exposure to BPA can upregulate SOX4 expression (18), SOX6 and SOX11 (19). Exposure to BPA has been shown to decrease FOXD3 levels (20). 0.023331593081759400 0.046 rs806372 CNR1 C > G Intron Chr6:88846563-88866563 SOX12 (SRY-box transcription factor 12). 3 Conserved in humans and rhesus. Splicing site; SIB locus ID: NC-000006-1470. 3 alternative transcripts within intron 1 (6q15) of CNR1 . Denisovan variant Exposure to DiNP and BPA significantly increased the expression of CNR1 (13). DEHP can increase SOX12 expression levels (21). 0.003312817523356740 0.018 Additional Declarations There is no duality of interest Supplementary Files SupplementarydataLD.xlsx Supplementary data LD Cite Share Download PDF Status: Published Journal Publication published 20 Nov, 2025 Read the published version in European Journal of Human Genetics → Version 1 posted Editorial decision: revise 29 Jul, 2025 Review # 3 received at journal 25 Jul, 2025 Review # 2 received at journal 11 Jul, 2025 Review # 1 received at journal 08 Jul, 2025 Reviewer # 3 agreed at journal 29 Jun, 2025 Reviewer # 2 agreed at journal 27 Jun, 2025 Reviewer # 1 agreed at journal 25 Jun, 2025 Reviewers invited by journal 06 Jun, 2025 Submission checks completed at journal 12 May, 2025 First submitted to journal 11 May, 2025 Editor assigned by journal 11 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6639771","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":467550974,"identity":"231722ce-42dd-4260-a8ff-424cf7ef3bce","order_by":0,"name":"Anna 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University","correspondingAuthor":false,"prefix":"","firstName":"Amelia","middleName":"","lastName":"Warren","suffix":""},{"id":467550976,"identity":"e7649d9a-fefe-4a70-9570-cd16ae87787e","order_by":2,"name":"Demetra Andreou","email":"","orcid":"","institution":"Bournemouth University","correspondingAuthor":false,"prefix":"","firstName":"Demetra","middleName":"","lastName":"Andreou","suffix":""},{"id":467550977,"identity":"eecec24b-8e85-486b-93f8-8477606f6655","order_by":3,"name":"Dean Warren","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Dean","middleName":"","lastName":"Warren","suffix":""},{"id":467550978,"identity":"6f0548df-e01c-41a2-b412-f3988c6b2fdf","order_by":4,"name":"Jack Wieland","email":"","orcid":"https://orcid.org/0000-0002-4806-1780","institution":"Bournemouth University","correspondingAuthor":false,"prefix":"","firstName":"Jack","middleName":"","lastName":"Wieland","suffix":""}],"badges":[],"createdAt":"2025-05-11 13:15:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6639771/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6639771/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41431-025-01977-9","type":"published","date":"2025-11-20T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":84250025,"identity":"82c35208-6df7-4faf-b146-97016f74fff9","added_by":"auto","created_at":"2025-06-09 18:05:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":543346,"visible":true,"origin":"","legend":"\u003cp\u003eThe PRISMA flow chart used to select literature for the impact of the environment on endometriosis risk.\u003c/p\u003e","description":"","filename":"PRISMAflowchartusedtoselectliteraturefortheimpactoftheenvrionmentonendometriosisriskfigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6639771/v1/d3b267cd16eed35a47e997ca.png"},{"id":84250024,"identity":"7e5d442b-1082-4bd7-a12f-884339330f3a","added_by":"auto","created_at":"2025-06-09 18:05:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":557049,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA flow chart created for the screening process to select literature on genomic areas of interest in relation to endometriosis development\u003c/p\u003e","description":"","filename":"PRISMAflowchartusedtoselectliteratureongenomicareasofinterestinrelationtoendometriosisdevelopmentfigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6639771/v1/d0d3e3ffd682c94fee41e8a7.png"},{"id":84250492,"identity":"60b6a8dc-eb01-41c3-8973-da369b59acb5","added_by":"auto","created_at":"2025-06-09 18:13:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1033362,"visible":true,"origin":"","legend":"\u003cp\u003eWorkflow of methods followed for finding the impact and regulatory sequences of statistically significant variants\u003c/p\u003e","description":"","filename":"Workflowofmethodsfollowedfigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6639771/v1/b88beb01673141061aaf3d97.png"},{"id":96446707,"identity":"5c3bd51c-91e0-44fd-b3fd-1acb01f4e7e8","added_by":"auto","created_at":"2025-11-21 08:10:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2765151,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6639771/v1/975bcc42-8c23-4f61-a54a-fa4afb59ad53.pdf"},{"id":84250034,"identity":"094f6746-fc6c-4395-aac6-df91e513f783","added_by":"auto","created_at":"2025-06-09 18:05:02","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":838287,"visible":true,"origin":"","legend":"Supplementary data LD","description":"","filename":"SupplementarydataLD.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6639771/v1/207e98b47ec0e5629ff8e249.xlsx"}],"financialInterests":"There is no duality of interest","formattedTitle":"\u003cp\u003eEndometriosis - on the intersection of modern environmental pollutants and ancient genetic regulatory variants\u003c/p\u003e","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eGlobally, ten percent of reproductive-aged women have endometriosis, a heterogeneous gynaecological disease driven by estrogen signalling (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Endometriosis can be difficult to diagnose due to limited diagnostic tools, contributing to misdiagnosis and delays. Diagnosis can take up to eleven years between symptom onset and diagnosis (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Fifty percent of diagnosed women medically reported severe pelvic pain during adolescence that went untreated (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEndometriosis is potentially a multifactorial disease and may involve a complex system of immunological, environmental, hormonal, and genetic factors. Studies have suggested a dampened immune response in endometriosis patients due to estrogen dominance, triggering pro-inflammatory factors and altering immune cell functions. This fuels chronic inflammation and prevents cell death, promoting endometrial lesion growth (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Furthermore, studies using twins found a heritability component, with genome-wide association studies suggesting a genetic (47%) and environmental (53%) contribution to endometriosis predisposition (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Environmental predisposition from modern industrial pollutants and chemicals such as endocrine-disrupting chemicals (EDCs) may play a role in endometriosis development. EDCs imitate hormones and block naturally occurring hormones from binding to receptors. This can interfere with physiological processes, including the reproductive system (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Current genome-wide studies have collectively identified forty-two single nucleotide polymorphisms (SNPs) linked to endometriosis, some of which are associated with pain perception and maintenance and advanced endometriosis (\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), however, none of these SNPs predict early endometriosis stages, hindering increased risk assessment accuracy and early diagnosis preventing complications like infertility.\u003c/p\u003e \u003cp\u003eDespite advancements in identifying endometriosis genes, research largely focuses on advanced stages and comorbidities, rather than disease onset, leading to a diagnosis of earlier stages and prevention of endometriosis to remain elusive. Understanding genetic risk and gene-environment interaction in early endometriosis is key to improving endometriosis management and preventing complications like infertility and gynaecologic cancers. This study aims to bridge the gap between genetics and environmental risk factors, providing a more comprehensive model of endometriosis susceptibility and identifying potential biomarkers for early-stage detection.\u003c/p\u003e"},{"header":"2 Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Ethical Approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study received ethical approval from Bournemouth University’s Institutional Research Ethics Panel (ID: 45978). Genomic data were obtained under Project ID 645 through the Genomics England 100,000 Genomes Project. All participants provided informed consent for the use of their data in secondary research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Literature Searches\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA two-phase systematic literature review was conducted using PubMed and Web of Science to identify genes and genomic markers implicated in endometriosis pathophysiology and their interaction with environmental exposures, particularly EDCs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.1 Literature Selection Criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInclusion Criteria: Original studies focusing on genomic/genetic analysis, or genome-wide association design., Only human participants (no other species)., Patients with a diagnosis of endometriosis for at least a year., Patients aged between eighteen and forty-three years at the time of recruitment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eExclusion Criteria: Review studies., Studies including participants with other types of female infertility., Participants without an endometriosis diagnosis., Participants with additional illnesses and diseases which could affect result outcomes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA literature search investigating environmental risk factors for endometriosis and a review of their impact on signalling pathways and related genes was conducted. The key words used were; “endometriosis” and “exposure to endocrine disrupting chemicals”, “endocrine disrupting chemicals”, “exposure to pesticides”, “pesticides”, “personal care products”, “cosmetics”, “exposure to heavy metals”, “heavy metals”, “exposure to radiation”, “radiation”, “exposure to toxins”, “toxins”, “chemicals”, “plastics”, “exposure to pollution”, “pollution”, “exposure to air pollution”, “air pollution”, “exposure to water pollution”, “water pollution”. This yielded sixty-four papers and excluded 236 papers. Figure one shows the screening process of the primary literature search as a PRISMA flow chart.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEDCs were identified as the most significant environmental factor to endometriosis. Leading this study to focus on their association with genetic susceptibility to endometriosis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA secondary literature search was conducted to identify genomic areas/ markers of interest involved in endometriosis. The keywords used in this search were; “endometriosis” and “polymorphism”, “SNP”, “genetic polymorphism”, “variants”, “locus”, “GWA”, “Genome-wide”, “Genome wide”, “Genetic association study”. This yielded 166 papers and excluded 2476 papers. Figure two shows the screening process of the secondary literature search as a PRISMA flow chart.\u003c/p\u003e\n\u003cp\u003eThis literature search identified fifty-seven genes of interest relating to endometriosis risk susceptibility; from this, five genes were chosen to investigate further. These were chosen through identifying the main function of the gene and where it is expressed using the National Library of Medicine (NIH). The pathways of the gene’s pathways were identified using Reactome. The criteria for this selection were: literature has shown EDCs are associated with the gene, and their effects are within the signalling pathways in which the selected genes are involved. Pathways associated with the gene are associated or involved in endometriosis onset or progression., Selected genes are expressed within associated tissues of endometriosis implant locations., The main function of the gene, when disrupted, potentially leads to endometriosis development.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 100,000 Genomics England Database\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Genomics England (GE) 100,000 genome database was used as a part of an ongoing larger project “Genomic and chromosomal instability sequence markers in relation to fertility, early pregnancy, and cancers of the reproductive tissues” and included domains of Ovarian Cancer GE Research Network (GERN) and Endocrine and Metabolism GERN to obtain participants and analyse genomic data.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eParticipants from the GE Rare Disease Programs GRCh38 Participant Explorer were chosen by searching for a clinical diagnosis of endometriosis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInclusion Criteria: Female participants aged eighteen to forty-three years at the time of recruitment., Diagnosis of endometriosis recorded in medical history., Availability of whole-genome sequencing (WGS) data., Inclusion of participants with endometriosis-related infertility and/or ovarian chocolate cysts.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eExclusion Criteria: Individuals not assigned female sex at birth., Participants over 43 years (to minimize cofounding by menopause-related genetic changes)., Presence of additional ovarian pathology, chromosomal abnormalities, haematological disorders or other reproductive tract malignancies., Diagnosis of diabetes., Immunological disorders, or hormonal conditions that could confound genetic associations., Body mass index outside the range of 18.5-30 kg/m2 to minimize metabolic confounders' impact. The final study cohort included nineteen individuals meeting these criteria.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEndometriosis stages were estimated using American Society of Reproductive Medicine criteria and additional clinical information, such as location of endometrial implants and/or lesions and procedures or investigations carried out in relation to endometriosis in the patient’s profile, as the participant Explorer database did not specify stage. Table one depicts the study criteria to estimate endometriosis stage.\u003c/p\u003e\n\u003cp\u003eEach of the five selected genes were searched in GE per participant and single nucleotide variations (SNV), and insertion-deletion mutations (INDELs) were collected.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study focused on regulatory regions, introns, upstream, and downstream sequences, instead of coding regions, as environmental pollutants are more likely to affect gene expression than protein structure (10). Targeting these regions enabled a more efficient and detailed investigation of relevant genomic variants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Statistical analysis and linkage disequilibrium\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHeatmaps were created using GraphPad Prism v10 to visualise variants across stages. Variant frequencies were compared between the general GE population and the endometriosis cohort using R v4.2.2 a X2 goodness of fit test for individual variants with Fisher’s combined probability and small sample corrections relevant to data discovery. A Benjamini-Hochberg (BH) false discovery rate correction was applied to p-values, to account for multiple hypothesis testing controlling for false positives while maintaining statistical power.\u003c/p\u003e\n\u003cp\u003eTo confirm that variant enrichment was specific to the endometriosis cohort, nineteen randomly selected individuals without endometriosis from the GE database were screened using the same method. \u0026nbsp;A Fisher's combined probability test compared variant frequencies across the endometriosis cohort, random group, and total GE population. Statistically significant variants were assessed for co-localisation to determine non-random clustering within the endometriosis cohort. Linkage disequilibrium analysis was conducted to assess the correlation between regulatory variants associated with endometriosis. Pairwise LD values Pairwise LD values (D’ and r²) were calculated for rs34880821 and rs2069840 in \u003cem\u003eIL-6\u003c/em\u003e and rs806372 in \u003cem\u003eCNR1\u003c/em\u003e, using data from the 1000 Genomes Project across multiple populations. LDpair and LDpop from LDlink were used to determine linkage strength, with comparisons across African, East Asian, European, South Asian, and Admixed American populations. Results were analysed to evaluate population-specific evolutionary pressures and potential functional implications for immune regulation and pain sensitivity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Regulatory Sequence Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo identify statistically significant variant effects a search of the variants rsID was undertaken using ClinVar, dbSNP, ensemble, UCSC, and String. An extensive analysis was conducted using UCSC and previous literature on other hominoids and the conservation of the statistically significant variants. All results are reported with adjusted p-values, and statistically significant associations are discussed in the context of biological plausibility and environmental interactions.\u003c/p\u003e"},{"header":"3 Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Genomic findings of five selected genes and Significant variant findings\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThrough using the literature search and consulting the criteria, the five genes chosen to be investigated further were \u003cem\u003eIDO1\u003c/em\u003e (Indoleamine two, three-dioxygenase one), \u003cem\u003eIL-6\u003c/em\u003e (Interleukin six), \u003cem\u003eCNR1\u003c/em\u003e (cannabinoid receptor one), \u003cem\u003eTACR3\u003c/em\u003e (tachykinin receptor three), and \u003cem\u003eKISS1R\u003c/em\u003e (\u003cem\u003eKISS1\u0026nbsp;\u003c/em\u003ereceptor).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTen genetic variants were identified as potential contributors to endometriosis when compared to both the study population and the GE general population. Of these, 40% had a frequency of 0% in the Ensembl general population but were present in the GE general population. This is potentially due to GE participants having a higher percentage of genetic mutations and variants through recruiting participants with known rare genetic conditions or specific diseases.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAfter conducting an X2 goodness of fit test for each of the ten variants found using the study cohort population frequency and GE total population frequency, variants, rs806372, rs76129761, rs2069840, rs34880821, rs933717388, and rs72643906 were found to be statistically significant.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA BH test was conducted on the X2 goodness of fit test, which shows the variants are significant in the endometriosis cohort. When observing co-occurrence with other significant variants, rs2069840 and rs34880821 showed the strongest co-occurrence within eight individuals in the endometriosis cohort. Whereas rs806372 and rs933717388 show moderate co-occurrence in three individuals. However, rs76129761 and rs72643906 rarely occur with other variants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhen conducting a co-localisation analysis, rs2069840 and rs34880832 show a strong co-localisation effect. The expected frequency for co-localisation for the variants is two participants in the cohort of nineteen (10.5%), based on P(co-localise) = 0.316x0.263=0.083. In the endometriosis group, eight individuals had both variants (47.4%), which is significantly higher than expected at p=0.0001, showing a strong co-localisation effect. However, in the random group, this was seen in six individuals (31.6%), which was also higher than expected at p=0.0110 but is less pronounced than the endometriosis group. This shows the co-localisation of rs2069840 and rs34880821 occurs much more frequently than would be expected by chance in both groups. Furthermore, both variants individually and together show significant enrichment in the endometriosis group. This suggests a potential biological interaction between these variants that may be particularly relevant to endometriosis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhen comparing the six significant variants in the endometriosis cohort compared to the random sample cohort and total GE populations, each of the variants is shown to be significantly higher in the endometriosis group, except rs76129761, which is shown to be higher in the random sample cohort. From the Fisher’s combined probability test between the endometriosis cohort and the random sample compared to the GE total population a combined X2 statistic; 44.37, with a p-value of 0.000013 (p\u0026lt;0.001), showed strong evidence in overall frequency difference between the endometriosis cohort and the GE total population across all endometriosis variants. This suggests that the genetic profile of the endometriosis cohort significantly deviates from the general population, potentially indicating a unique genetic signature associated with endometriosis. Furthermore, the combined X2 statistic for the random sample cohort, 12.23, with a p-value of 0.427, showed no significant difference between the random sample cohort and the GE total population across all endometriosis variants. This lack of significant deviation suggests that the random sample’s variant frequencies are representative of the GE total population, serving as a control group. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable two shows the variant profiles for the significant variants found within the endometriosis cohort.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 LD analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLD analysis revealed a strong linkage between Neanderthal-derived \u003cem\u003eIL-6\u003c/em\u003e variants (rs34880821 and rs2069840) (depicted in Figure three), in East Asians (D’ = 1.0, r2 = 0.9662), suggesting selective retention and potential immune regulation effects. Europeans showed moderate LD (D’ = 0.9234, r2 = 0.5794), while Africans had weak linkage (D’ = 0.8752, r2 = 0.4823), likely due to the absence of Neanderthal introgression.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe Denisovan-influenced \u003cem\u003eCNR1\u003c/em\u003e variant (rs806372) exhibited moderate LD in East Asians (D’ = 0.8004) but weak LD in Europeans (D’ = 0.4607) and South Asians (D’ = 0.1459), suggesting population-specific evolutionary pressures. African populations had negligible LD for both variant pairs, supporting the hypothesis that these associations arose post-migration due to archaic human introgression.\u003c/p\u003e\n\u003cp\u003eThese findings highlight six regulatory variants significantly enriched in the endometriosis cohort. Notably, the \u003cem\u003eIL-6\u003c/em\u003e variants rs2069840 and rs34880821 not only co-occurred at a rate well above chance but also exhibit population-specific LD consistent with archaic hominin ancestry and potential immunoregulatory roles. Other significant variants in \u003cem\u003eCNR1\u003c/em\u003e, \u003cem\u003eIDO1\u003c/em\u003e, and \u003cem\u003eKISS1R\u003c/em\u003e were associated with transcription factor binding sites and are located in genomic regions shown to be responsive to endocrine-disrupting chemicals.\u003c/p\u003e"},{"header":"4 Discussion ","content":"\u003cp\u003eMany sufferers of endometriosis are subject to misdiagnosis and delays due to limited understanding of early-stage risk factors. To obtain a better understanding of genetic factors predisposing to endometriosis development, two literature searches and interrogation of the GE 100,000 genome database were conducted.\u003c/p\u003e\n\u003cp\u003eUsing a highly targeted multilevel approach, five genes have been characterised as potential targets in the developing endometriosis pathway, containing variants or having altered expression levels, with five variants found as highly significant and one as moderately significant in our cohort population when compared to GE. This builds on the work conducted by Sapkota, Zondervan, and Rahmioglu (7–9), who collectively found forty-two SNPs linked to endometriosis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e4.1 IDO1\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe downstream variant of \u003cem\u003eIDO1\u003c/em\u003e rs72643906 is found to be rare in the general population, is significantly higher in the study cohort, indicating the variant may influence endometriosis development through altering \u003cem\u003eIDO1\u003c/em\u003e expression levels. Specifically, Brooks (11) found that immune system activation increases \u003cem\u003eIDO1\u003c/em\u003e expression. Furthermore, the UCSC database showed an association with an elevated risk of COVID-19, and therefore, is potentially disadvantageous to the immune system, which is seen to be associated with endometriosis patients (4). The UCSC database showed rs72643906 to alter the motif of the transcription factor Zic family member two (\u003cem\u003eZIC2\u003c/em\u003e), which regulates tissue expression (12), this potentially modifies the \u003cem\u003eZIC2\u003c/em\u003e motif to prevent the transcription factor from binding, therefore hypothetically increasing the expression levels of \u003cem\u003eIDO1\u003c/em\u003e and \u003cem\u003eZIC2\u003c/em\u003e. Furthermore, elevated \u003cem\u003eIDO1\u003c/em\u003e expression has been found in endometriosis patients (13), showing a potential link between rs72643906 and endometriosis. However, when Bisphenol A (BPA) is introduced through the environment, \u003cem\u003eIDO1\u003c/em\u003e and \u003cem\u003eZIC2\u003c/em\u003e expression levels are decreased (14,15), potentially reversing the rs72643906 effect.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.2 \u003cem\u003eCNR1\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe \u003cem\u003eCNR1\u003c/em\u003e variants rs76129761 and rs806372 were found to be significant within the study cohort; rs76129761 is deleterious, and rs806372 has a potential splicing site implicating three alternative transcripts within intron 1 (6q15) of \u003cem\u003eCNR1\u003c/em\u003e. Therefore, it is possible these variants potentially increase\u003cem\u003e\u0026nbsp;CNR1\u003c/em\u003e expression levels, leading to endometriosis development, with Allam (16) finding increased \u003cem\u003eCNR1\u003c/em\u003e levels in endometriosis patients when compared to controls.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe UCSC database shows rs806372 to be a Denisovan variant, which may be well established in populations where Denisovans and sapiens interact, being randomly selected until the onset of EDCs in our modern society (17). The consequence of this may have been exposure to Di-(2-ethylhexyl) phthalate (DEHP) and BPA, which has been found to increase \u003cem\u003eCNR1\u003c/em\u003e expression (18).\u003c/p\u003e\n\u003cp\u003eThe UCSC database also shows rs806372 to lie on the binding site of SRY-box transcription factor (\u003cem\u003eSOX\u003c/em\u003e) twelve. This may alter the motif, disrupting its binding and leading to increased \u003cem\u003eCNR1\u003c/em\u003e and decreased \u003cem\u003eSOX12\u003c/em\u003e expression levels. However, environmental DEHP exposure has been shown to elevate both \u003cem\u003eSOX12\u003c/em\u003e and \u003cem\u003eCNR1\u003c/em\u003e levels, as supported by expression studies (18,19).\u003c/p\u003e\n\u003cp\u003eWhereas rs76129761 lies on the binding site of five transcription factors; Zinc finger protein 701 (\u003cem\u003eZNF701\u003c/em\u003e), \u003cem\u003eSOX4\u003c/em\u003e, \u003cem\u003eS0X6\u003c/em\u003e, Forkhead box D3 (\u003cem\u003eFOXD3\u003c/em\u003e) and \u003cem\u003eSOX11\u003c/em\u003e, which may cause increased expression levels of the these and \u003cem\u003eCNR1\u003c/em\u003e. Furthermore, environmental BPA exposure increases \u003cem\u003eSOX4\u003c/em\u003e, \u003cem\u003eSOX6\u003c/em\u003e, and \u003cem\u003eSOX11\u003c/em\u003e (20,21) and decreases \u003cem\u003eFOXD3\u003c/em\u003e expression levels (22).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.3\u003cem\u003e\u0026nbsp;KISS1R\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe \u003cem\u003eKISS1R\u003c/em\u003e intronic variant rs933717388 is a potentially novel variant (no literature or records referencing this variant) and was found to be significantly higher in the study population. The UCSC database found rs933717388 to lie on the binding sites of Zinc finger protein 707 (\u003cem\u003eZNF707\u003c/em\u003e) and Zinc finger and BTB domain-containing protein 11 (\u003cem\u003eZTB11\u003c/em\u003e). The variant rs933717388 may bind to the sites of transcription factors \u003cem\u003eZNF707\u003c/em\u003e and\u003cem\u003e\u0026nbsp;ZTB11\u003c/em\u003e, altering their motifs and potentially hindering their binding. Since \u003cem\u003eZBTB11\u003c/em\u003e is a silencing transcription factor, reduced binding could increase \u003cem\u003eKISS1R\u003c/em\u003e expression. This upregulation may disrupt reproductive function and promote endometriotic cell metastasis (23). Blasco (24) supports this, reporting elevated \u003cem\u003eKISS1R\u003c/em\u003e levels in granulosa cells of endometriosis patients. Both \u003cem\u003eKISS1R\u003c/em\u003e and transcription factor levels are potentially increased in the presence of rs933717388, and DEHP exposure further raises \u003cem\u003eKISS1R\u003c/em\u003e expression (25), though its effect on \u003cem\u003eZNF707\u003c/em\u003e or \u003cem\u003eZBTB11\u003c/em\u003e remains unstudied.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.4\u003cem\u003e\u0026nbsp;IL-6\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIntronic variants rs2069850 and rs34880821 of the \u003cem\u003eIL-6\u003c/em\u003e gene were found to be significant within the study cohort. These variants have been found to colocalise in the endometriosis cohort, which suggests a potential biological interaction between these variants that are potentially relevant to endometriosis. The UCSC showed rs34880821 to be a Neandertal methylation site. Therefore, the reference allele was methylated in Neandertals and Denisovans, but this variant abolishes the methylation site, so rs34880821 may exacerbate endometriosis development due to the disease being associated with dysregulation of the immune and inflammatory system by aberrant silencing of the area and continuous expression. This probability of heightened \u003cem\u003eIL-6\u003c/em\u003e expression in endometriosis patients is further validated in research by Li (26), finding an increase in \u003cem\u003eIL-6\u003c/em\u003e expression levels when compared to controls.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.5 The Intersection of Ancient Genetic Variants, Epigenetic Regulation, and Modern Environmental Pollutants in Endometriosis Susceptibility\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur findings highlight how ancient genetic variants inherited from Neanderthals and Denisovans, epigenetic regulation, and modern industrial pollutants may potentially converge to shape population-specific risks for endometriosis. The linkage disequilibrium (LD) analysis of \u003cem\u003eIL-6\u003c/em\u003e and \u003cem\u003eCNR1\u003c/em\u003e regulatory variants suggests that evolutionary pressures involving immune regulation and inflammatory responses, when combined with modern environmental exposures, may amplify disease susceptibility (27,28)\u003c/p\u003e\n\u003cp\u003eNeanderthal introgression has significantly influenced \u003cem\u003eIL-6\u003c/em\u003e regulation, particularly in East Asian populations. The \u003cem\u003eIL-6\u003c/em\u003e variant rs34880821, located at a Neanderthal-derived methylation site, exhibits strong LD in East Asians (r² = 0.9662, D’ = 1.0), while showing weaker LD in Europeans (r² = 0.5794) and South Asians (r² = 0.8104) (27). This suggests that Neanderthal introgression may have played a role in shaping \u003cem\u003eIL-6\u003c/em\u003e regulatory pathways, particularly in East Asians, where it remains strongly linked. Given that East Asian populations also have the highest reported prevalence of endometriosis (~15.4%), it is likely that these genetic variants contribute to heightened inflammatory responses, immune dysregulation, and fibrotic lesion formation (29,30).\u003c/p\u003e\n\u003cp\u003eThe functionality for the Neanderthal-derived methylation at rs34880821 may indicate another subtle contributor to endometriosis risk. \u0026nbsp;Methylation usually functions as a gene-silencing mechanism, regulating cytokine levels to prevent excessive inflammation (31). If methylation is lost, \u003cem\u003eIL-6\u003c/em\u003e expression could become hyperactive, leading to chronic immune activation, sustaining peritoneal inflammation, fibrosis, and deep-infiltrating endometriosis, as \u003cem\u003eIL-6\u003c/em\u003e is known to drive fibrotic remodelling in reproductive tissues (30). It also may account for heightened neuroinflammation, potentially explaining increased pain sensitivity in East Asian endometriosis patients (32).\u003c/p\u003e\n\u003cp\u003eSimilarly, the Denisovan-derived rs806372 variant in \u003cem\u003eCNR1\u003c/em\u003e, which is involved in immune modulation and pain perception, exhibits moderate LD in East Asians (D’ = 0.8004) but weak LD in Europeans (D’ = 0.4607) and South Asians (D’ = 0.1459) (27). Since \u003cem\u003eCNR1\u003c/em\u003e plays a key role in pain signalling and inflammatory responses, this Denisovan-influenced variant may enhance pain sensitivity in individuals with endometriosis, particularly in East Asian populations (28).\u003c/p\u003e\n\u003cp\u003eWhile these ancestral variants may have once provided immune advantages in prehistoric environments, modern environmental factors may be reversing these evolutionary benefits, transforming once-adaptive immune responses into drivers of chronic disease (30).\u003c/p\u003e\n\u003cp\u003eExposure to EDCs, such as BPA, phthalates, and dioxins, has been shown to demethylate immune regulatory genes, including \u003cem\u003eIL-6\u003c/em\u003e, leading to excessive cytokine production (29). If Neanderthal-derived \u003cem\u003eIL-6\u0026nbsp;\u003c/em\u003eregulatory variants are already prone to overactivation, additional EDC-induced demethylation could further escalate inflammatory signalling, worsening lesion development. This suggests a gene-environment interaction, where modern industrial chemicals exacerbate genetic predispositions inherited from archaic human ancestors.\u003c/p\u003e\n\u003cp\u003eIn contrast to East Asian and European populations, African populations exhibit significantly lower LD for these \u003cem\u003eIL-6\u003c/em\u003e and \u003cem\u003eCNR1\u003c/em\u003e variants (D’ \u0026lt; 0.02, r² \u0026lt; 0.001), suggesting these genetic associations arose post-migration due to Neanderthal and Denisovan introgression (27). There is limited available data on the prevalence of endometriosis in African populations, and estimates may vary due to underdiagnosis.\u003c/p\u003e\n\u003cp\u003eThis study supports a novel model for endometriosis susceptibility, in which ancestral genetic variants interact with modern environmental pollutants to modulate immune regulation, chronic inflammation, and pain perception across populations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.6 Limitations and future directions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhile this study provides novel insights into the genetic and environmental factors influencing endometriosis susceptibility, several limitations must be acknowledged. The sample size was limited, particularly in younger individuals under twenty-nine years old. Additionally, family-based cascade genetic testing was not included, preventing the evaluation of heritability and potential familial aggregation of risk variants. Another limitation is the reliance on medical records to infer endometriosis staging, which introduces the potential for misclassification bias. Furthermore, while this study identified significant associations between regulatory variants and endometriosis risk, functional validation through in vitro and vivo models is required to confirm their biological relevance.\u003c/p\u003e\n\u003cp\u003eFurther research should focus on expanding the study cohort to include a larger and more diverse population to improve the statistical power of genetic associations and assess whether these findings are consistent across different ethnic backgrounds. Family-based studies incorporating cascade genetic testing could help clarify inheritance patterns and the potential contribution of additional rare variants to endometriosis risk. Further functional studies are necessary to evaluate how the identified regulatory variants influence gene expression and immune signalling pathways, particularly in response to EDCs. Integrating environmental exposure data with genomic analysis would provide a more comprehensive understanding of how genetic and environmental factors interact in the development and progression of endometriosis. These future directions will be critical for translating genetic discoveries into practical applications for early diagnosis and personalised treatment strategies.\u0026nbsp;\u003c/p\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eThis study provides a novel perspective on the genetic and environmental interplay driving endometriosis susceptibility, highlighting the influence of ancient regulatory variants and modern industrial pollutants. This research identified statistically significant regulatory variants in \u003cem\u003eIL-6\u003c/em\u003e, \u003cem\u003eCNR1\u003c/em\u003e, \u003cem\u003eIDO1\u003c/em\u003e, and \u003cem\u003eKISS1R\u003c/em\u003e that may contribute to endometriosis risk through interactions with EDCs. These findings aim to bridge the gap between genetic predisposition, evolutionary selection, and environmental exposures, shedding light on how Neanderthal and Denisovan introgressed variants in immune and pain-regulatory genes may influence disease susceptibility in modern populations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis is the first study to systematically explore how ancient genetic signatures, epigenetic regulation, and contemporary environmental pollutants intersect in the pathophysiology of endometriosis. These results lay the first steps for future precision medicine approaches, where genetic screening combined with environmental risk assessment may improve early detection and personalised intervention strategies. Moving forward, functional validation of these regulatory variants and their interaction with endocrine disruptors will be crucial in understanding their mechanistic role in endometriosis onset and progression. These findings enhance our understanding of endometriosis as a multifactorial disease but also provide a framework for future research integrating evolutionary genetics, environmental health, and reproductive medicine.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePosthumous acknowledgement. This work is dedicated to our beloved colleague Dr Elpida Fragkouli for her consistent support, supervision and contribution to the study design and data interpretation.\u003c/p\u003e\n\u003cp\u003eThis research was made possible through access to data in the National Genomic Research Library, which is managed by Genomics England Limited (a wholly owned company of the Department of Health and Social Care). The National Genomic Research Library holds data provided by patients and collected by the NHS as part of their care and data collected as part of their participation in research. The National Genomic Research Library is funded by the National Institute for Health Research and NHS England. The Welcome Trust, Cancer Research UK and the Medical Research Council have also funded research infrastructure.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA.W. contributed to the study design, collected the data and analysed the data and drafted the manuscript. D.A. contributed to the study design, provided supervision of the study and contributed to the article drafting and editing. D.W. contributed to the study design, analysed the data and editing. J.W. contributed to data gathering. A.M. leads the GE project that this study is a part of, designed the study, data analysis and interpretation, provided supervision of the study and manuscript drafting and editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBournemouth University funded the writing of this manuscript granted to the first author of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing of interest.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eData availability statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResearch on the de-identified patient data used in this publication can be carried out in the Genomics England Research Environment subject to a collaborative agreement that adheres to patient led governance. All interested readers will be able to access the data in the same manner that the authors accessed the data. For more information about accessing the data, interested readers may contact [email protected] or access the relevant information on the Genomics England website: https://www.genomicsengland.co.uk/research.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKanellopoulos D, Karagianni D, Pergialiotis V, Patsouras G, Patsouras K, Nikiteas N, et al. The interplay between endometriosis and fertility in rats: a systematic review. Vol. 15, Journal of Medicine and Life. 2022. \u003c/li\u003e\n\u003cli\u003eAgarwal SK, Chapron C, Giudice LC, Laufer MR, Leyland N, Missmer SA, et al. Clinical diagnosis of endometriosis: a call to action. Am J Obstet Gynecol. 2019;220(4). \u003c/li\u003e\n\u003cli\u003eNnoaham KE, Hummelshoj L, Webster P, D\u0026rsquo;Hooghe T, De Cicco Nardone F, De Cicco Nardone C, et al. 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Mol Cell Endocrinol. 2023;577. \u003c/li\u003e\n\u003cli\u003eMatta K, Koual M, Ploteau S, Coumoul X, Audouze K, Bizec B Le, et al. Associations between exposure to organochlorine chemicals and endometriosis: A systematic review of experimental studies and integration of epidemiological evidence. Vol. 129, Environmental Health Perspectives. 2021. \u003c/li\u003e\n\u003cli\u003eBrown JS. Effects of bisphenol-A and other endocrine disruptors compared with abnormalities of schizophrenia: An endocrine-disruption theory of schizophrenia. Vol. 35, Schizophrenia Bulletin. 2009. \u003c/li\u003e\n\u003cli\u003eXie Q, Kang Y, Zhang C, Xie Y, Wang C, Liu J, et al. The Role of Kisspeptin in the Control of the Hypothalamic-Pituitary-Gonadal Axis and Reproduction. Vol. 13, Frontiers in Endocrinology. 2022. \u003c/li\u003e\n\u003cli\u003eKang SY, Song JY, Cho HH. Gene expression analysis of uterine smooth muscle cells exposed to bisphenol A. 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Interactions between inflammatory mediators and corticosteroids regulate transcription of genes within the Kynurenine Pathway in the mouse hippocampus. J Neuroinflammation. 2016;13(1). \u003c/li\u003e\n\u003cli\u003eLuo Z, Gao X, Lin C, Smith ER, Marshall SA, Swanson SK, et al. Zic2 is an enhancer-binding factor required for embryonic stem cell specification. Mol Cell. 2015;57(4). \u003c/li\u003e\n\u003cli\u003eMei J, Li MQ, Ding D, Li DJ, Jin LP, Hu WG, et al. Indoleamine 2,3-dioxygenase-1 (IDO1) enhances survival and invasiveness of endometrial stromal cells via the activation of JNK signaling pathway. Int J Clin Exp Pathol [Internet]. 2013 [cited 2024 Jul 17];6(3):431. Available from: /pmc/articles/PMC3563200/\u003c/li\u003e\n\u003cli\u003eAllam S, Paris E, Lazcano I, Bitterman P, Basu S, O\u0026rsquo;Donnell J, et al. Detection of Cannabinoid Receptor Expression by Endometriotic Lesions in Women with Endometriosis as an Alternative to Opioid-Based Pain Medication. J Immunol Res. 2022;2022. \u003c/li\u003e\n\u003cli\u003eZhang X, Witt KE, Ba\u0026ntilde;uelos MM, Ko A, Yuan K, Xu S, et al. The history and evolution of the Denisovan-EPAS1 haplotype in Tibetans. Proc Natl Acad Sci U S A. 2021;118(22). \u003c/li\u003e\n\u003cli\u003eZhang J, Jin L, Kong L, Nie L, Yuan D. Developments in reproductive biology and medicine Physiological and pathological roles of locally expressed kisspeptin and KISS1R in the endometrium Mini-Review. Human Reproduction [Internet]. 2023 [cited 2025 May 10];38(7):1253\u0026ndash;60. Available from: https://doi.org/10.1093/humrep/dead080\u003c/li\u003e\n\u003cli\u003eBlasco V, Pinto FM, Fern\u0026aacute;ndez-Atucha A, Gonz\u0026aacute;lez-Ravina C, Fern\u0026aacute;ndez-S\u0026aacute;nchez M, Candenas L. Female infertility is associated with an altered expression of the neurokinin B/neurokinin B receptor and kisspeptin/kisspeptin receptor systems in ovarian granulosa and cumulus cells. 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Available from: https://www.nature.com/articles/nature12961\u003c/li\u003e\n\u003cli\u003eHarris K, Nielsen R. The Genetic Cost of Neanderthal Introgression. Genetics [Internet]. 2016 Jun 1 [cited 2025 May 10];203(2):881\u0026ndash;91. Available from: https://dx.doi.org/10.1534/genetics.116.186890\u003c/li\u003e\n\u003cli\u003eYen CF, Kim MR, Lee CL. Epidemiologic Factors Associated with Endometriosis in East Asia. Gynecol Minim Invasive Ther [Internet]. 2019 Jan 1 [cited 2025 May 10];8(1):4. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC6367920/\u003c/li\u003e\n\u003cli\u003eVelarde MC, Bucu MEM, Habana MAE. Endometriosis as a highly relevant yet neglected gynecologic condition in Asian women. Endocr Connect [Internet]. 2023 Nov 1 [cited 2025 May 10];12(11). Available from: https://ec.bioscientifica.com/view/journals/ec/12/11/EC-23-0169.xml\u003c/li\u003e\n\u003cli\u003eZeberg H, P\u0026auml;\u0026auml;bo S. 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Available from: https://www.genomicsengland.co.uk/initiatives/100000-genomes-project\u003c/li\u003e\n\u003cli\u003eEnsembl genome browser 112 [Internet]. [cited 2024 Jul 17]. Available from: https://www.ensembl.org/index.html\u003c/li\u003e\n\u003cli\u003eHome - GraphPad [Internet]. [cited 2024 Jul 17]. Available from: https://www.graphpad.com/\u003c/li\u003e\n\u003cli\u003eNational Library of Medicine - National Institutes of Health. \u003c/li\u003e\n\u003cli\u003eSNPedia [Internet]. [cited 2024 Jul 17]. Available from: https://www.snpedia.com/\u003c/li\u003e\n\u003cli\u003eGillespie M, Jassal B, Stephan R, Milacic M, Rothfels K, Senff-Ribeiro A, et al. The reactome pathway knowledgebase 2022. Nucleic Acids Res. 2022;50(D1). \u003c/li\u003e\n\u003cli\u003eSzklarczyk D, Kirsch R, Koutrouli M, Nastou K, Mehryary F, Hachilif R, et al. The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest. Database issue Published online [Internet]. 2023 [cited 2025 May 10];51. Available from: https://doi.org/10.1093/nar/gkac1000\u003c/li\u003e\n\u003cli\u003eSherry ST, Ward M, Sirotkin K. dbSNP\u0026mdash;Database for Single Nucleotide Polymorphisms and Other Classes of Minor Genetic Variation. Genome Res [Internet]. 1999 Aug 1 [cited 2025 May 10];9(8):677\u0026ndash;9. Available from: http://genome.cshlp.org/content/9/8/677.full\u003c/li\u003e\n\u003cli\u003eMyers TA, Chanock SJ, Machiela MJ. LDlinkR: An R Package for Rapidly Calculating Linkage Disequilibrium Statistics in Diverse Populations. Front Genet [Internet]. 2020 Feb 28 [cited 2025 May 10];11:513535. Available from: www.frontiersin.org\u003c/li\u003e\n\u003cli\u003eMachiela MJ, Chanock SJ. LDassoc: an online tool for interactively exploring genome-wide association study results and prioritizing variants for functional investigation. Bioinformatics [Internet]. 2018 Mar 1 [cited 2025 May 10];34(5):887\u0026ndash;9. Available from: https://dx.doi.org/10.1093/bioinformatics/btx561\u003c/li\u003e\n\u003cli\u003eMachiela MJ, Chanock SJ. LDlink: a web-based application for exploring population-specific haplotype structure and linking correlated alleles of possible functional variants. Bioinformatics [Internet]. 2015 Nov 1 [cited 2025 May 10];31(21):3555\u0026ndash;7. Available from: https://dx.doi.org/10.1093/bioinformatics/btv402\u003c/li\u003e\n\u003cli\u003eThe National Genomic Research Library v5.1. 2020 [cited 2025 May 10]; Available from: www.genomicsengland.co.uk\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1:\u003c/strong\u003e Criteria used in this study to estimate the patient\u0026rsquo;s endometriosis stage according to the American Sociated of Reproductive medicine (10).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical information to diagnose endometriosis stage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStage 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMinimal surgeries such as examination of uterus and laparoscopic approach to abdomen, with one or two locations of endometriosis within the ovary, pelvic peritoneum, uterus or rectovaginal septum and vagina.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStage 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHad two or more locations of endometriosis within the ovary, pelvic peritoneum, uterus or rectovaginal septum and vagina and minimal surgeries such as examination of uterus and laparoscopic approach to abdomen, including removal of lesions.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStage 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMultiple locations of endometriosis, chocolate cysts and multiple surgeries including cauterisation of organs, endoscopic freeing of adhesions and extirpation of ovaries.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStage 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAll locations of endometriosis including possible endometriosis located in the intestine in some cases, chocolate cysts and procedures of endoscopic resection, endoscopic destructions, repair of obstetric lacerations, drainage of ovarian cysts and endoscopic extirpation.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u003c/strong\u003e Variant profiles for the significant variants found within this cohort (created using UCSC (12)).\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"992\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariant\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAssociated gene.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariant type/ consequence.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChromosome location.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePotential transcription factor (TF) binding site affected (if applicable.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of publications.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther significant features.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePollutant interference.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eP-value from \u0026chi;\u003csup\u003e2\u0026nbsp;\u003c/sup\u003egoodness of fit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eBH-corrected p-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003ers72643906\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cem\u003eIDO1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eA \u0026gt; G Downstream variant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eChr8:39779157-399779157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e\u003cem\u003eZIC2 (\u003c/em\u003eZic family member 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eHighly conserved in mammals and vertebrates\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eBPA and TBBPA (Tetrabromobisphenol A) can decrease methylation of \u003cem\u003eIDO1\u003c/em\u003e\u0026rsquo;s mRNA and DNA\u0026nbsp;\u0026nbsp;(13), and TCDD can increase IDO1 expression levels (14).\u003c/p\u003e\n \u003cp\u003eExposure to BPA has been shown to decrease \u003cem\u003eZIC2\u003c/em\u003e expression (15).\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e0.00175665990877229\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003ers933717388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cem\u003eKISS1R\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eC \u0026gt; G Intron variant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eChr19:912365-912365\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e\u003cem\u003eZNF707 (\u003c/em\u003eZinc finger protein 707\u003cem\u003e)\u003c/em\u003e and \u003cem\u003eZBTB11 (\u003c/em\u003eZinc finger and BTB domain-containing protein 11\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eConserved in humans\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eDEHP exposure influences regulators of HPGA by regulating GnRH (Gonadotropin hormone-releasing hormone) release altering \u003cem\u003eKISS1R\u003c/em\u003e expression\u0026nbsp;(16).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e0.017530950708949900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003ers34880821\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cem\u003eIL-6\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eG \u0026gt; A Intergenic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eChr7:22775450-22775450\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eConserved in humans\u003c/p\u003e\n \u003cp\u003eMethylation site.\u003c/p\u003e\n \u003cp\u003eNeandertal variant.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eExposure to TCDD can increase the expression of \u003cem\u003eIL-6\u0026nbsp;\u003c/em\u003e(14).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e0.006042586245540780\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003ers2069840\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cem\u003eIL-6\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eC \u0026gt; G Intronic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eChr7:22768572-22768572\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eConserved in rhesus, mouse, and dogs.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eExposure to TCDD can increase the expression of \u003cem\u003eIL-6\u0026nbsp;\u003c/em\u003e(14).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e0.020059606754631400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003ers76129761\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cem\u003eCNR1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eCTCT \u0026gt; CT Intron\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eChr6:88860156-88860156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e\u003cem\u003eZNF701 (\u003c/em\u003eZinc finger protein 701\u003cem\u003e),\u003c/em\u003e \u003cem\u003eSOX4 (SRY-box transcription factor 4), SOX6 (SRY-box transcription factor 6), FOXD3 (\u003c/em\u003eForkhead box D3\u003cem\u003e)\u003c/em\u003e and \u003cem\u003eSOX11 (SRY-box transcription factor 11).\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eConserved in human, rhesus, mouse, and dogs.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eExposure to DiNP and BPA significantly increased the expression of \u003cem\u003eCNR1\u003c/em\u003e (17).\u003c/p\u003e\n \u003cp\u003eExposure to BPA can upregulate \u003cem\u003eSOX4\u003c/em\u003e expression (18), \u003cem\u003eSOX6\u003c/em\u003e and \u003cem\u003eSOX11\u003c/em\u003e (19).\u003c/p\u003e\n \u003cp\u003eExposure to BPA has been shown to decrease \u003cem\u003eFOXD3\u003c/em\u003e levels (20).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e0.023331593081759400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003ers806372\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cem\u003eCNR1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;C \u0026gt; G Intron\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eChr6:88846563-88866563\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 152px;\"\u003e\n \u003cp\u003e\u003cem\u003eSOX12 (SRY-box transcription factor 12).\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eConserved in humans and rhesus.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSplicing site; SIB locus ID: NC-000006-1470. 3 alternative transcripts within intron 1 (6q15) of \u003cem\u003eCNR1\u003c/em\u003e.\u003c/p\u003e\n \u003cp\u003eDenisovan variant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eExposure to DiNP and BPA significantly increased the expression of \u003cem\u003eCNR1\u003c/em\u003e (13).\u003c/p\u003e\n \u003cp\u003eDEHP can increase \u003cem\u003eSOX12\u003c/em\u003e expression levels (21).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e0.003312817523356740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-human-genetics","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"ejhg","sideBox":"Learn more about [European Journal of Human Genetics](http://www.nature.com/ejhg/)","snPcode":"41431","submissionUrl":"https://mts-ejhg.nature.com/cgi-bin/main.plex","title":"European Journal of Human Genetics","twitterHandle":"@ejhg_journal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6639771/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6639771/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEndometriosis is a chronic, estrogen-driven inflammatory disorder affecting approximately 10% of reproductive-aged women globally. Despite increasing genomic insights into advanced-stage disease, the genetic underpinnings of early-stage endometriosis remain poorly understood, limiting opportunities for timely diagnosis and intervention.\u003c/p\u003e\n\u003cp\u003eThis study explores the contribution of regulatory variants, including those derived from ancient hominin introgression, and their interaction with modern environmental exposures in shaping endometriosis susceptibility.\u003c/p\u003e\n\u003cp\u003eWe conducted a dual-phase literature review to identify genes implicated in endometriosis pathophysiology and endocrine-disrupting chemical (EDC) sensitivity. Five genes (\u003cem\u003eIL-6, CNR1, IDO1, TACR3,\u003c/em\u003e and \u003cem\u003eKISS1R\u003c/em\u003e) were selected based on tissue expression, pathway involvement, and EDC reactivity. Whole-genome sequencing data from the Genomics England 100,000 Genomes Project were analysed in nineteen females with clinically confirmed endometriosis. Variant enrichment, co-localisation, and linkage disequilibrium analyses were conducted, and functional impact was evaluated using public regulatory databases. Six regulatory variants were significantly enriched in the endometriosis cohort compared to matched controls and the general Genomics England population. Notably, co-localised \u003cem\u003eIL-6\u003c/em\u003evariants rs2069840 and rs34880821—located at a Neanderthal-derived methylation site—demonstrated strong linkage disequilibrium and potential immune dysregulation. Variants in \u003cem\u003eCNR1\u003c/em\u003e and \u003cem\u003eIDO1\u003c/em\u003e, some of Denisovan origin, also showed significant associations. Several of these variants overlapped EDC-responsive regulatory regions, suggesting gene-environment interactions may exacerbate risk. These findings propose a novel model of endometriosis susceptibility, in which ancient regulatory variants and contemporary environmental exposures converge to modulate immune and inflammatory responses. This integrative approach identified new potential biomarkers for early-stage detection of endometriosis.\u003c/p\u003e","manuscriptTitle":"Endometriosis - on the intersection of modern environmental pollutants and ancient genetic regulatory variants","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-09 18:04:57","doi":"10.21203/rs.3.rs-6639771/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2025-07-29T10:36:14+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-07-25T22:06:48+00:00","index":3,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-07-11T18:15:28+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-07-08T15:35:43+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-06-29T04:33:14+00:00","index":3,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-06-27T15:00:45+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-06-25T17:19:06+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-06-06T12:23:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-12T16:00:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Human Genetics","date":"2025-05-11T13:10:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-11T13:10:47+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-human-genetics","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"ejhg","sideBox":"Learn more about [European Journal of Human Genetics](http://www.nature.com/ejhg/)","snPcode":"41431","submissionUrl":"https://mts-ejhg.nature.com/cgi-bin/main.plex","title":"European Journal of Human Genetics","twitterHandle":"@ejhg_journal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"ce75433a-0455-4546-aabb-7be6524de2c7","owner":[],"postedDate":"June 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":49770293,"name":"Biological sciences/Genetics/Gene expression"},{"id":49770294,"name":"Biological sciences/Genetics/Evolutionary biology"},{"id":49770295,"name":"Health sciences/Endocrinology/Endocrine system and metabolic diseases/Endocrine reproductive disorders"}],"tags":[],"updatedAt":"2025-11-21T08:10:09+00:00","versionOfRecord":{"articleIdentity":"rs-6639771","link":"https://doi.org/10.1038/s41431-025-01977-9","journal":{"identity":"european-journal-of-human-genetics","isVorOnly":false,"title":"European Journal of Human Genetics"},"publishedOn":"2025-11-20 05:00:00","publishedOnDateReadable":"November 20th, 2025"},"versionCreatedAt":"2025-06-09 18:04:57","video":"","vorDoi":"10.1038/s41431-025-01977-9","vorDoiUrl":"https://doi.org/10.1038/s41431-025-01977-9","workflowStages":[]},"version":"v1","identity":"rs-6639771","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6639771","identity":"rs-6639771","version":["v1"]},"buildId":"WvIrzKhiLBfengagbw6Ux","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}