Genetic control of DNA methylation is largely shared across European and East Asian populations.

DNA methylation is an ideal trait to study the extent of the shared genetic control across ancestries, effectively providing hundreds of thousands of model molecular traits with large QTL effect sizes. We investigate cis DNAm QTLs in three European (n = 3701) and two East Asian (n = 2099) cohorts to quantify the similarities and differences in the genetic architecture across populations. We observe 80,394 associated mQTLs (62.2% of DNAm probes with significant mQTL) to be significant in both ancestries, while 28,925 mQTLs (22.4%) are identified in only a single ancestry. mQTL effect sizes are highly conserved across populations, with differences in mQTL discovery likely due to differences in allele frequency of associated variants and differing linkage disequilibrium between causal variants and assayed SNPs. This study highlights the overall similarity of genetic control across ancestries and the value of ancestral diversity in increasing the power to detect associations and enhancing fine mapping resolution.

Polygenic risk score phenome-wide association study reveals an association between endometriosis and testosterone.

BACKGROUND: Endometriosis affects 1 in 9 women, yet it is poorly understood with long diagnostic delays, invasive diagnoses, and poor treatment outcomes. Characterised by the presence of endometrial-like tissue outside of the uterus, its main symptoms are pain and infertility. Endometriosis often co-occurs with other conditions, which may provide insights into the origins of endometriosis. METHODS: Here a polygenic risk score phenome-wide association study of endometriosis was conducted in the UK Biobank to investigate the pleiotropic effects of a genetic liability to endometriosis. The relationship between the polygenic risk score for endometriosis and health conditions, blood and urine biomarkers and reproductive factors were investigated separately in females, males and females without an endometriosis diagnosis. The relationship between endometriosis and the blood and urine biomarkers was further investigated using genetic correlation and Mendelian randomisation approaches to identify causal relationships. RESULTS: Multiple health conditions, blood and urine biomarkers and reproductive factors were associated with genetic liability to endometriosis in each group, indicating many endometriosis comorbidities are not dependent on the physical manifestation of endometriosis. Differences in the associated traits between males and females highlighted the importance of sex-specific pathways in the overlap of endometriosis with many other traits. Notably, an association of genetic liability to endometriosis with lower testosterone levels was identified. Follow-up analysis utilising Mendelian randomisation approaches suggested lower testosterone may be causal for both endometriosis and clear cell ovarian cancer. CONCLUSIONS: This study highlights the diversity of the pleiotropic effects of genetic risk to endometriosis irrespective of a diagnosis of endometriosis. A key finding was the identification of a causal effect of the genetic liability to lower testosterone on endometriosis using Mendelian randomisation.

Evidence of shared genetic factors in the etiology of gastrointestinal disorders and endometriosis and clinical implications for disease management.

In clinical practice, the co-existence of endometriosis and gastrointestinal symptoms is often observed. Using large-scale datasets, we report a genetic correlation between endometriosis and irritable bowel syndrome (IBS), peptic ulcer disease (PUD), gastro-esophageal reflux disease (GORD), and a combined GORD/PUD medicated (GPM) phenotype. Mendelian randomization analyses support a causal relationship between genetic predisposition to endometriosis and IBS and GPM. Identification of shared risk loci highlights biological pathways that may contribute to the pathogenesis of both diseases, including estrogen regulation and inflammation, and potential therapeutic drug targets (CCKBR; PDE4B). Higher use of IBS, GORD, and PUD medications in women with endometriosis and higher use of hormone therapies in women with IBS, GORD, and PUD, support the co-occurrence of these conditions and highlight the potential for drug repositioning and drug contraindications. Our results provide evidence of shared disease etiology and have important clinical implications for diagnostic and treatment decisions for both diseases.

GWAS of Dizygotic Twinning in an Enlarged Australian Sample of Mothers of DZ Twins.

Female fertility is a complex trait with age-specific changes in spontaneous dizygotic (DZ) twinning and fertility. To elucidate factors regulating female fertility and infertility, we conducted a genome-wide association study (GWAS) on mothers of spontaneous DZ twins (MoDZT) versus controls (3273 cases, 24,009 controls). This is a follow-up study to the Australia/New Zealand (ANZ) component of that previously reported (Mbarek et al., 2016), with a sample size almost twice that of the entire discovery sample meta-analysed in the previous article (and five times the ANZ contribution to that), resulting from newly available additional genotyping and representing a significant increase in power. We compare analyses with and without male controls and show unequivocally that it is better to include male controls who have been screened for recent family history, than to use only female controls. Results from the SNP based GWAS identified four genomewide significant signals, including one novel region, ZFPM1 (Zinc Finger Protein, FOG Family Member 1), on chromosome 16. Previous signals near FSHB (Follicle Stimulating Hormone beta subunit) and SMAD3 (SMAD Family Member 3) were also replicated (Mbarek et al., 2016). We also ran the GWAS with a dominance model that identified a further locus ADRB2 on chr 5. These results have been contributed to the International Twinning Genetics Consortium for inclusion in the next GWAS meta-analysis (Mbarek et al., in press).

Gene expression profiles separate endometriosis lesion subtypes and indicate a sensitivity of endometrioma to estrogen suppressive treatments through elevated ESR2 expression.

BACKGROUND: Endometriosis is a common, gynaecological disease characterised by the presence of endometrial-like cells growing outside the uterus. Lesions appear at multiple locations, present with variation in appearance, size and depth of invasion. Despite hormones being the recommended first-line treatment, their efficacy, success and side effects vary widely amongst study populations. Current, hormonal medication for endometriosis is designed to suppress systemic oestrogen. Whether these hormones can influence the lesions themselves is not yet clear. Evidence of hormone receptor expression in endometriotic lesions and their ability to respond is conflicting. A variation in their expression, activation of transcriptional co-regulators and the potential to respond may contribute to their variation in patient outcomes. Identifying patients who would benefit from hormonal treatments remain an important goal in endometriosis research. METHODS: Using gene expression data from endometriosis lesions including endometrioma (OMA, n = 28), superficial peritoneal lesions (SUP, n = 72) and deeply infiltrating lesions (DIE, n = 78), we performed principal component analysis, differential gene expression and gene correlation analyses to assess the impact of menstrual stage, lesion subtype and hormonal treatment on the gene expression. RESULTS: The gene expression profiles did not vary based on menstrual stage, but could distinguish lesion subtypes with OMA significantly differentiating from both SUP and DIE. Additionally, the effect of oestrogen suppression medication altered the gene expression profile in OMA, while such effect was not observed in SUP or DIE. Analysis of the target receptors for hormonal medication indicated ESR2 was differentially expressed in OMA and that genes that correlated with ESR2 varied significantly between medicated and non-medicated OMA samples. CONCLUSIONS: Our results demonstrate of the different lesion types OMA present with strongest response to hormonal treatment directly through ESR2. The data suggests that there may be the potential to target treatment options to individual patients based on pre-surgical diagnoses.

Global endometrial DNA methylation analysis reveals insights into mQTL regulation and associated endometriosis disease risk and endometrial function.

Endometriosis is a leading cause of pain and infertility affecting millions of women globally. Herein, we characterize variation in DNA methylation (DNAm) and its association with menstrual cycle phase, endometriosis, and genetic variants through analysis of genotype data and methylation in endometrial samples from 984 deeply-phenotyped participants. We estimate that 15.4% of the variation in endometriosis is captured by DNAm and identify significant differences in DNAm profiles associated with stage III/IV endometriosis, endometriosis sub-phenotypes and menstrual cycle phase, including opening of the window for embryo implantation. Menstrual cycle phase was a major source of DNAm variation suggesting cellular and hormonally-driven changes across the cycle can regulate genes and pathways responsible for endometrial physiology and function. DNAm quantitative trait locus (mQTL) analysis identified 118,185 independent cis-mQTLs including 51 associated with risk of endometriosis, highlighting candidate genes contributing to disease risk. Our work provides functional evidence for epigenetic targets contributing to endometriosis risk and pathogenesis. Data generated serve as a valuable resource for understanding tissue-specific effects of methylation on endometrial biology in health and disease.

Genomic characterisation of the overlap of endometriosis with 76 comorbidities identifies pleiotropic and causal mechanisms underlying disease risk.

Comorbid conditions can be driven by underlying pleiotropic and causal mechanisms that can provide insights into shared molecular and biological processes contributing to disease risk. Endometriosis is a chronic condition affecting one in nine women of reproductive age and poses many challenges including lengthy diagnostic delays and limited treatment efficacy owing to poor understanding of disease aetiology. To shed light on the underlying biological mechanisms and to identify potential risk factors, we examine the epidemiological and genomic relationship between endometriosis and its comorbidities. In the UK Biobank 292 ICD10 codes were epidemiologically correlated with endometriosis diagnosis, including gynaecological, immune, infection, pain, psychiatric, cancer, gastrointestinal, urinary, bone and cardiovascular traits. A subset of the identified comorbidities (n = 76) underwent follow-up genetic analysis. Whilst Mendelian randomisation suggested causality was not responsible for most comorbid relationships, 22 traits were genetically correlated with endometriosis, including pain, gynaecological and gastrointestinal traits, suggestive of a shared genetic background. Pleiotropic genetic variants and genes were identified using gene-based and colocalisation analysis. Shared genetic risk factors and potential target genes suggest a diverse collection of biological systems are involved in these comorbid relationships including coagulation factors, development of the female reproductive tract and cell proliferation. These findings highlight the diversity of traits with epidemiological and genomic overlap with endometriosis and implicate a key role for pleiotropy in the comorbid relationships.

Global Analysis of Transcription Start Sites and Enhancers in Endometrial Stromal Cells and Differences Associated with Endometriosis.

Identifying tissue-specific molecular signatures of active regulatory elements is critical to understanding gene regulatory mechanisms. In this study, transcription start sites (TSS) and enhancers were identified using Cap analysis of gene expression (CAGE) across endometrial stromal cell (ESC) samples obtained from women with (n = 4) and without endometriosis (n = 4). ESC TSSs and enhancers were compared to those reported in other tissue and cell types in FANTOM5 and were integrated with RNA-seq and ATAC-seq data from the same samples for regulatory activity and network analyses. CAGE tag count differences between women with and without endometriosis were statistically tested and tags within close proximity to genetic variants associated with endometriosis risk were identified. Over 90% of tag clusters mapping to promoters were observed in cells and tissues in FANTOM5. However, some potential cell-type-specific promoters and enhancers were also observed. Regions of open chromatin identified using ATAC-seq provided further evidence of the active transcriptional regions identified by CAGE. Despite the small sample number, there was evidence of differences associated with endometriosis at 210 consensus clusters, including IGFBP5, CALD1 and OXTR. ESC TSSs were also located within loci associated with endometriosis risk from genome-wide association studies. This study provides novel evidence of transcriptional differences in endometrial stromal cells associated with endometriosis and provides a valuable cell-type specific resource of active TSSs and enhancers in endometrial stromal cells.

Establishing the Australian National Endometriosis Clinical and Scientific Trials (NECST) Registry: A protocol paper.

Endometriosis is a common yet under-recognised chronic inflammatory disease, affecting 176 million women, trans and gender diverse people globally. The National Endometriosis Clinical and Scientific Trials (NECST) Registry is a new clinical registry, collecting and tracking diagnostic and treatment data, and patient-reported outcomes on people with endometriosis. The registry is a research priority action item from the 2018 National Action Plan for Endometriosis and aims to provide, large-scale, national and longitudinal population-based data on endometriosis. Working groups (consisting of patients with endometriosis, clinicians and researchers) developing the NECST Registry data dictionary and data collection platform started in 2019. Our data dictionary was developed based on existing and validated questionnaires, tools, meta-data and data cubes - World Endometriosis Research Foundation (WERF) Endometriosis Phenome and Biobanking Harmonisation Project (EPHect), endometriosis CORE outcomes set, patient-reported outcome measures, the International Statistical Classification of Diseases-10th Revision Australian Modification diagnosis codes, and Australian Government datasets: Australian Institute for Health and Welfare (for sociodemographic data), Medicare Benefits Schedule (MBS; for medical procedures) and the Pharmaceutical Benefits Scheme (PBS; for medical therapies). The resulting NECST Registry is an online, secure cloud-based database; prospectively collecting minimum core clinical and health data across eight patient and clinician modules and longitudinal data tracking disease life course. The NECST Registry has ethics approval (HREC/62508/MonH-2020) and is registered on the Australian New Zealand Clinical Trials Registry (ACTRN12622000987763).

Insights from Mendelian randomization and genetic correlation analyses into the relationship between endometriosis and its comorbidities.

BACKGROUND: Endometriosis remains a poorly understood disease, despite its high prevalence and debilitating symptoms. The overlap in symptoms and the increased risk of multiple other traits in women with endometriosis is becoming increasingly apparent through epidemiological data. Genetic studies offer a method of investigating these comorbid relationships through the assessment of causal relationships with Mendelian randomization (MR), as well as identification of shared genetic variants and genes involved across traits. This has the capacity to identify risk factors for endometriosis as well as provide insight into the aetiology of disease. OBJECTIVE AND RATIONALE: We aim to review the current literature assessing the relationship between endometriosis and other traits using genomic data, primarily through the methods of MR and genetic correlation. We critically examine the limitations of these studies in accordance with the assumptions of the utilized methods. SEARCH METHODS: The PubMed database was used to search for peer-reviewed original research articles using the terms 'Mendelian randomization endometriosis' and '"genetic correlation" endometriosis'. Additionally, a Google Scholar search using the terms '"endometriosis" "mendelian randomization" "genetic correlation"' was performed. All relevant publications (n = 21) published up until 7 October 2022 were included in this review. Upon compilation of all traits with published MR and/or genetic correlation with endometriosis, additional epidemiological and genetic information on their comorbidity with endometriosis was sourced by searching for the trait in conjunction with 'endometriosis' on Google Scholar. OUTCOMES: The association between endometriosis and multiple pain, gynaecological, cancer, inflammatory, gastrointestinal, psychological, and anthropometric traits has been assessed using MR analysis and genetic correlation analysis. Genetic correlation analyses provide evidence that genetic factors contributing to endometriosis are shared with multiple traits: migraine, uterine fibroids, subtypes of ovarian cancer, melanoma, asthma, gastro-oesophageal reflux disease, gastritis/duodenitis, and depression, suggesting the involvement of multiple biological mechanisms in endometriosis. The assessment of causality with MR has revealed several potential causes (e.g. depression) and outcomes (e.g. ovarian cancer and uterine fibroids) of a genetic predisposition to endometriosis; however, interpretation of these results requires consideration of potential violations of the MR assumptions. WIDER IMPLICATIONS: Genomic studies have demonstrated that there is a molecular basis for the co-occurrence of endometriosis with other traits. Dissection of this overlap has identified shared genes and pathways, which provide insight into the biology of endometriosis. Thoughtful MR studies are necessary to ascertain causality of the comorbidities of endometriosis. Given the significant diagnostic delay of endometriosis of 7-11 years, determining risk factors is necessary to aid diagnosis and reduce the disease burden. Identification of traits for which endometriosis is a risk factor is important for holistic treatment and counselling of the patient. The use of genomic data to disentangle the overlap of endometriosis with other traits has provided insights into the aetiology of endometriosis.

New concepts on the etiology of endometriosis.

Endometriosis is a serious, chronic disorder where endometrial tissue grows outside the uterus, causing severe pelvic pain and infertility. It affects 11% of women. Endometriosis is a multifactorial disorder of unclear etiology, although retrograde menstruation plays a major role. It has a genetic component with over 40 genetic risk factors mapped, although their mechanism of action is still emerging. New evidence suggests a role for retrograde menstruation of endometrial stem/progenitor cells, now that identifying markers of these cells are available. Recent lineage tracing and tissue clearing microscopy and 3D reconstruction has provided new understanding of endometrial glandular structure, particularly the horizontal orientation and interconnection of basalis glands. New sequencing technologies, particularly whole genome DNA sequencing are revealing somatic mutations, including in cancer driver genes, in normal and eutopic endometrium of patients with endometriosis, as well as ectopic endometriotic lesions. Methylome sequencing is offering insight into the regulation of genes and the role of the environmental factors. Single cell RNA sequencing reveals the transcriptome of individual endometrial cells, shedding new light on the diversity and range of cellular subpopulations of the major cell types present in the endometrium and in endometriotic lesions. New endometrial epithelial organoid cultures replicating glandular epithelium are providing tractable models for studying endometriosis. Organoids derived from menstrual fluid offer a non-invasive source of endometrial tissue and a new avenue for testing drugs and developing personalized medicine for treating endometriosis. These new approaches are rapidly advancing our understanding of endometriosis etiology.

Rare genetic variants underlie outlying levels of DNA methylation and gene-expression.

Testing the effect of rare variants on phenotypic variation is difficult due to the need for extremely large cohorts to identify associated variants given expected effect sizes. An alternative approach is to investigate the effect of rare genetic variants on DNA methylation (DNAm) as effect sizes are expected to be larger for molecular traits compared with complex traits. Here, we investigate DNAm in healthy ageing populations-the Lothian Birth Cohorts of 1921 and 1936-and identify both transient and stable outlying DNAm levels across the genome. We find an enrichment of rare genetic single nucleotide polymorphisms (SNPs) within 1 kb of DNAm sites in individuals with stable outlying DNAm, implying genetic control of this extreme variation. Using a family-based cohort, the Brisbane Systems Genetics Study, we observed increased sharing of DNAm outliers among more closely related individuals, consistent with these outliers being driven by rare genetic variation. We demonstrated that outlying DNAm levels have a functional consequence on gene expression levels, with extreme levels of DNAm being associated with gene expression levels toward the tails of the population distribution. This study demonstrates the role of rare SNPs in the phenotypic variation of DNAm and the effect of extreme levels of DNAm on gene expression.

Multi-trait genome-wide association study of opioid addiction: OPRM1 and beyond.

Opioid addiction (OA) is moderately heritable, yet only rs1799971, the A118G variant in OPRM1, has been identified as a genome-wide significant association with OA and independently replicated. We applied genomic structural equation modeling to conduct a GWAS of the new Genetics of Opioid Addiction Consortium (GENOA) data together with published studies (Psychiatric Genomics Consortium, Million Veteran Program, and Partners Health), comprising 23,367 cases and effective sample size of 88,114 individuals of European ancestry. Genetic correlations among the various OA phenotypes were uniformly high (rg > 0.9). We observed the strongest evidence to date for OPRM1: lead SNP rs9478500 (p = 2.56 × 10-9). Gene-based analyses identified novel genome-wide significant associations with PPP6C and FURIN. Variants within these loci appear to be pleiotropic for addiction and related traits.

Changing genetic architecture of body mass index from infancy to early adulthood: an individual based pooled analysis of 25 twin cohorts.

BACKGROUND: Body mass index (BMI) shows strong continuity over childhood and adolescence and high childhood BMI is the strongest predictor of adult obesity. Genetic factors strongly contribute to this continuity, but it is still poorly known how their contribution changes over childhood and adolescence. Thus, we used the genetic twin design to estimate the genetic correlations of BMI from infancy to adulthood and compared them to the genetic correlations of height. METHODS: We pooled individual level data from 25 longitudinal twin cohorts including 38,530 complete twin pairs and having 283,766 longitudinal height and weight measures. The data were analyzed using Cholesky decomposition offering genetic and environmental correlations of BMI and height between all age combinations from 1 to 19 years of age. RESULTS: The genetic correlations of BMI and height were stronger than the trait correlations. For BMI, we found that genetic correlations decreased as the age between the assessments increased, a trend that was especially visible from early to middle childhood. In contrast, for height, the genetic correlations were strong between all ages. Age-to-age correlations between environmental factors shared by co-twins were found for BMI in early childhood but disappeared altogether by middle childhood. For height, shared environmental correlations persisted from infancy to adulthood. CONCLUSIONS: Our results suggest that the genes affecting BMI change over childhood and adolescence leading to decreasing age-to-age genetic correlations. This change is especially visible from early to middle childhood indicating that new genetic factors start to affect BMI in middle childhood. Identifying mediating pathways of these genetic factors can open possibilities for interventions, especially for those children with high genetic predisposition to adult obesity.

Co-Inheritance of Variation in All-Cause Mortality and Biochemical Risk Factors.

Biomarkers may be useful endophenotypes for genetic studies if they share genetic sources of variation with the outcome, for example, with all-cause mortality. Australian adult study participants who had reported their parental survival information were included in the study: 14,169 participants had polygenic risk scores (PRS) from genotyping and up to 13,365 had biomarker results. We assessed associations between participants' biomarker results and parental survival, and between biomarker results and eight parental survival PRS at varying p-value cut-offs. Survival in parents was associated with participants' serum bilirubin, C-reactive protein, HDL cholesterol, triglycerides and uric acid, and with LDL cholesterol for participants' fathers but not for their mothers. PRS for all-cause mortality were associated with liver function tests (alkaline phosphatase, butyrylcholinesterase, gamma-glutamyl transferase), metabolic tests (LDL and HDL cholesterol, triglycerides, uric acid), and acute-phase reactants (C-reactive protein, globulins). Association between offspring biomarker results and parental survival demonstrates the existence of familial effects common to both, while associations between biomarker results and PRS for mortality favor at least a partial genetic cause of this covariation. Identification of genetic loci affecting mortality-associated biomarkers offers a route to the identification of additional loci affecting mortality.

Smoking remains associated with education after controlling for social background and genetic factors in a study of 18 twin cohorts.

We tested the causality between education and smoking using the natural experiment of discordant twin pairs allowing to optimally control for background genetic and childhood social factors. Data from 18 cohorts including 10,527 monozygotic (MZ) and same-sex dizygotic (DZ) twin pairs discordant for education and smoking were analyzed by linear fixed effects regression models. Within twin pairs, education levels were lower among the currently smoking than among the never smoking co-twins and this education difference was larger within DZ than MZ pairs. Similarly, education levels were higher among former smoking than among currently smoking co-twins, and this difference was larger within DZ pairs. Our results support the hypothesis of a causal effect of education on both current smoking status and smoking cessation. However, the even greater intra-pair differences within DZ pairs, who share only 50% of their segregating genes, provide evidence that shared genetic factors also contribute to these associations.

Gene expression of the endocannabinoid system in endometrium through menstrual cycle.

Endocannabinoids mediate cellular functions and their activity is controlled by a complex system of enzymes, membrane receptors and transport molecules. Endocannabinoids are present in endometrium, a cyclical regenerative tissue requiring tightly regulated cellular mechanisms for maturation. The objective of this study was to investigate the gene expression of key elements involved in the endocannabinoid system across the menstrual cycle. RNA was isolated from endometrial tissue and genome-wide gene expression datasets were generated using RNA-sequencing. An a priori set of 70 genes associated with endocannabinoid system were selected from published literature. Gene expression across the menstrual cycle was analyzed using a moderated t test, corrected for multiple testing with Bonferroni's method. A total of 40 of the 70 genes were present in > 90% of the samples, and significant differential gene expression identified for 29 genes. We identified 4 distinct regulation patterns for synthesizing enzymes, as well as a distinct regulation pattern for degradations and transporting enzymes. This study charts the expression of endometrial endocannabinoid system genes across the menstrual cycle. Altered expression of genes that control endocannabinoid may allow fine control over endocannabinoid concentrations and their influence on cellular function, maturation and differentiation as the endometrium matures through the menstrual cycle.

Altered differentiation of endometrial mesenchymal stromal fibroblasts is associated with endometriosis susceptibility.

Cellular development is tightly regulated as mature cells with aberrant functions may initiate pathogenic processes. The endometrium is a highly regenerative tissue, shedding and regenerating each month. Endometrial stromal fibroblasts are regenerated each cycle from mesenchymal stem cells and play a pivotal role in endometriosis, a disease characterised by endometrial cells that grow outside the uterus. Why the cells of some women are more capable of developing into endometriosis lesions is not clear. Using isolated, purified and cultured endometrial cells of mesenchymal origin from 19 women with (n = 10) and without (n = 9) endometriosis we analysed the transcriptome of 33,758 individual cells and compared these to clinical characteristics and in vitro growth profiles. We show purified mesenchymal cell cultures include a mix of mesenchymal stem cells and two endometrial stromal fibroblast subtypes with distinct transcriptomic signatures indicative of varied progression through the differentiation processes. The fibroblast subgroup characterised by incomplete differentiation was predominantly (81%) derived from women with endometriosis and exhibited an altered in vitro growth profile. These results uncover an inherent difference in endometrial cells of women with endometriosis and highlight the relevance of cellular differentiation and its potential to contribute to disease susceptibility.

A multi-level investigation of the genetic relationship between endometriosis and ovarian cancer histotypes.

Endometriosis is associated with increased risk of epithelial ovarian cancers (EOCs). Using data from large endometriosis and EOC genome-wide association meta-analyses, we estimate the genetic correlation and evaluate the causal relationship between genetic liability to endometriosis and EOC histotypes, and identify shared susceptibility loci. We estimate a significant genetic correlation (rg) between endometriosis and clear cell (rg = 0.71), endometrioid (rg = 0.48), and high-grade serous (rg = 0.19) ovarian cancer, associations supported by Mendelian randomization analyses. Bivariate meta-analysis identified 28 loci associated with both endometriosis and EOC, including 19 with evidence for a shared underlying association signal. Differences in the shared risk suggest different underlying pathways may contribute to the relationship between endometriosis and the different histotypes. Functional annotation using transcriptomic and epigenomic profiles of relevant tissues/cells highlights several target genes. This comprehensive analysis reveals profound genetic overlap between endometriosis and EOC histotypes with valuable genomic targets for understanding the biological mechanisms linking the diseases.

Body mass index and the diagnosis of endometriosis: Findings from a national data linkage cohort study.

BACKGROUND: Women with lower body mass index (BMI) have a higher risk of surgically confirmed endometriosis but this finding runs counterintuitive to the oestrogen-dependent theory for the disease. Increasingly, endometriosis is diagnosed via non-surgical methods. We examined BMI at age 18-23 years, and changes in BMI, and the risk of endometriosis according to the diagnostic method. METHODS: We analysed data from 11 794 young women, born in 1989-95, who completed six surveys as part of an Australian, longitudinal cohort study between 2013 and 2018. Women's survey responses were linked to administrative health records to identify endometriosis. Cox proportional hazards models modelled associations between BMI at age 18-23 years, and changes in BMI, and endometriosis. Analyses were stratified by the diagnostic method of endometriosis: clinically confirmed endometriosis (based on hospital discharge diagnosis) versus clinically suspected endometriosis (women's reports of physician-diagnosed endometriosis). RESULTS: There were 223 cases of clinically confirmed endometriosis and 396 cases of clinically suspected endometriosis. Women who gained weight after age 18-23 had lower risk of clinically confirmed endometriosis than women without endometriosis whose weight remained stable (HR = 0.64, 95% CI = 0.47-0.88). Women who were overweight (HR = 1.29, 95% CI = 1.01-1.66) at age 18-23 had higher risk of clinically suspected endometriosis than women of normal weight without endometriosis. CONCLUSIONS: The risk of clinically confirmed endometriosis was lower among women who gained weight compared to women with stable weight. The risk of clinically suspected endometriosis was higher among women who were overweight compared to normal weight.