Sahar Houshdaran

Endometriosis is a chronic inflammatory disease associated with pelvic pain, infertility, and delayed diagnosis. Growing evidence suggests that altered DNA methylation contributes to disease development and could serve as a biomarker for disease. We developed a leakage-safe machine learning pipeline to classify endometriosis case-control status and menstrual cycle phase using genome-wide DNA methylation data from eutopic endometrial tissue. The dataset consisted of 984 samples profiled using the Illumina Infinium MethylationEPIC array, with measurements across approximately 759,000 CpG sites. Technical variation was corrected using SmartSVA batch correction. Ridge logistic regression models were trained using stratified 80/20 train-test splits, with regularization strength selected via stratified cross-validation. Feature selection approaches included ridge coefficient ranking, per-CpG t-tests, and univariate logistic regression with FDR correction. Model validity was evaluated using label-shuffling analyses. Menstrual cycle phase classification showed strong performance (mean cross-validation AUROC: 0.971, held-out test AUROC: 0.989), reflecting genome-wide hormonally driven methylation. Ridge regression produced lower but meaningful performance for endometriosis classification (mean cross-validation AUROC: 0.854, held-out test AUROC: 0.875). Ridge coefficient-based feature selection identified compact predictive CpG sets, supporting the hypothesis that endometriosis-associated methylation signal is distributed across many loci rather than a few highly predictive CpGs. Pathway enrichment analyses identified substantial enrichment for menstrual cycle phase but limited enrichment for disease status following FDR correction, consistent with a diffuse endometriosis-associated signal. These findings demonstrate that ridge regression can detect methylation patterns associated with both endometriosis and menstrual cycle phase, highlighting the importance of accounting for cycle-related epigenetic variation in endometrial DNA methylation studies. Graphical

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.

Endometriosis is a common condition associated with debilitating pelvic pain and infertility. A genome-wide association study meta-analysis, including 60,674 cases and 701,926 controls of European and East Asian descent, identified 42 genome-wide significant loci comprising 49 distinct association signals. Effect sizes were largest for stage 3/4 disease, driven by ovarian endometriosis. Identified signals explained up to 5.01% of disease variance and regulated expression or methylation of genes in endometrium and blood, many of which were associated with pain perception/maintenance (SRP14/BMF, GDAP1, MLLT10, BSN and NGF). We observed significant genetic correlations between endometriosis and 11 pain conditions, including migraine, back and multisite chronic pain (MCP), as well as inflammatory conditions, including asthma and osteoarthritis. Multitrait genetic analyses identified substantial sharing of variants associated with endometriosis and MCP/migraine. Targeted investigations of genetically regulated mechanisms shared between endometriosis and other pain conditions are needed to aid the development of new treatments and facilitate early symptomatic intervention.

In patients with high serum E₂ embryo transfer is often postponed, as high E₂ levels adversely affect embryo transfer outcome. We aimed to determine if stratified serum oestradiol (E₂) and progesterone (P₄) levels differentially affect endometrial histology and endometrial oestrogen and progesterone receptor protein levels. Endometrial biopsies were collected from oocyte donors. Samples were divided based on peak serum E₂ levels into three groups: (i) low-E₂ (n = 33) E₂≤2999pg/mL; (ii) mid-E₂ (n = 40) E₂ 3000–4999 pg/mL; and (iii) high-E₂ (n = 15) E₂≥5000 pg/mL. Oestrogen receptor alpha (ERα) and progesterone receptors A and B (PR) protein levels in endometrial stroma (S), glandular (GE) and luminal (LE) epithelia were assessed by immunohistochemistry. Samples in high-E₂ group demonstrated strongest association with accelerated endometrial maturation (2 (1–2); 2 (1–3); and 3 (2.8–3) median days of advancement of endometrial maturation respectively in low, mid, high-E₂ groups, p = 0.046). There were significant differences in ERα and PR immunoexpression in S, GE and LE among the groups (p < 0.05). Higher E₂ levels were associated with decreased ERα expression (p < 0.017) in GE and LE, and increased PR expression in S and GE (p < 0.011 and p < 0.0001, respectively). Higher serum E₂ levels were associated with impaired endometrial steroid hormone receptor expression, higher serum P₄ and more advancement of endometrial maturation.

The placenta releases large quantities of extracellular vesicles (EVs) that likely facilitate communication between the embryo/fetus and the mother. We isolated EVs from second trimester human cytotrophoblasts (CTBs) by differential ultracentrifugation and characterized them by transmission electron microscopy, immunoblotting, and mass spectrometry. The 100,000 xg pellet was enriched for vesicles with a cup-like morphology typical of exosomes. They expressed markers specific to this vesicle type, CD9 and HRS, and the trophoblast proteins placental alkaline phosphatase and HLA-G. Global profiling by mass spectrometry showed that placental EVs were enriched for proteins that function in transport and viral processes. A cytokine array revealed that the CTB 100,000 xg pellet contained a significant amount of TNF-α. CTB EVs increased decidual stromal cell (dESF) transcription and secretion of NF-κB targets, including IL-8, as measured by qRT-PCR and cytokine array. A soluble form of the TNF-α receptor inhibited the ability of CTB 100,000 xg EVs to increase dESF secretion of IL-8. Overall, the data suggest that CTB EVs enhance decidual cell release of inflammatory cytokines, which we theorize is an important component of successful pregnancy.

Programmed cellular responses to cycling ovarian-derived steroid hormones are central to normal endometrial function. Abnormalities therein, as in the estrogen-dependent, progesterone-“resistant” disorder, endometriosis, predispose to infertility and poor pregnancy outcomes. The endometrial stromal fibroblast (eSF) is a master regulator of pregnancy success. However, the complex hormone-epigenome-transcriptome interplay in eSF by each individual steroid hormone, estradiol (E₂) and/or progesterone (P₄), under physiologic and pathophysiologic conditions, is poorly understood and was investigated herein. Genome-wide analysis in normal, early and late stage eutopic eSF revealed: i) In contrast to P₄, E₂ extensively affected the eSF DNA methylome and transcriptome. Importantly, E₂ resulted in a more open versus closed chromatin, confirmed by histone modification analysis. Combined E₂ with P₄ affected a totally different landscape than E₂ or P₄ alone. ii) P₄ responses were aberrant in early and late stage endometriosis, and mapping differentially methylated CpG sites with progesterone receptor targets from the literature revealed different but not decreased P₄-targets, leading to question the P₄-“resistant” phenotype in endometriosis. Interestingly, an aberrant E₂-response was noted in eSF from endometriosis women; iii) Steroid hormones affected specific genomic contexts and locations, significantly enriching enhancers and intergenic regions and minimally involving proximal promoters and CpG islands, regardless of hormone type and eSF disease state. iv) In eSF from women with endometriosis, aberrant hormone-induced methylation signatures were mainly due to existing DNA methylation marks prior to hormone treatments and involved known endometriosis genes and pathways. v) Distinct DNA methylation and transcriptomic signatures revealed early and late stage endometriosis comprise unique disease subtypes. Taken together, the data herein, for the first time, provide significant insight into the hormone-epigenome-transcriptome interplay of each steroid hormone in normal eSF, and aberrant E₂ response, distinct disease subtypes, and pre-existing epigenetic aberrancies in the setting of endometriosis, provide mechanistic insights into how endometriosis affects endometrial function/dysfunction. Steroid hormones regulate genes in select tissues, including the lining of the uterus (“endometrium”). If the hormone response in the endometrium is abnormal, infertility and poor pregnancy outcomes can result. Interaction of steroid hormones with the second genome (“epigenome”) to regulate gene expression is poorly understood. Thus, we studied the response to estrogen (E₂), progesterone (P₄) and their combination of the endometrial stromal fibroblast (eSF), a cell that is pivotal in pregnancy. The cells were derived from normal woman and those with endometriosis, an E₂-responsive, P₄-resistant, inflammatory disorder with implantation-based infertility and poor pregnancy outcomes. Hormone-regulated genome-wide DNA methylation (a key epigenetic mechanism) and gene expression patterns and profiles were distinct for each hormone and in normal versus disease. Advanced stage disease had the most blunted response, and novel, not previously reported E₂ responses were observed in eSF from women with endometriosis. Intergenic regions and enhancers were significantly enriched, with minimal involvement of gene proximal promoters, indicating a broad, genome-wide hormone effect. Unexpectedly, pre-existing aberrant DNA methylation signatures in eSF from women with endometriosis were found and revealed distinct disease sub-types. These data advance our understanding of genome-wide hormone-epigenome dynamics critical in hormone-responsive tissues with downstream impact on physiologic processes.

Progestins are widely used for the treatment of gynecologic disorders and alone, or combined with an estrogen, are used as contraceptives. While their potencies, efficacies and side effects vary due to differences in structures, doses and routes of administration, little is known about their effects on the endometrial transcriptome in the presence or absence of estrogen. Herein, we assessed the transcriptome and pathways induced by progesterone (P₄) and the three most commonly used synthetic progestins, medroxyprogesterone acetate (MPA), levonorgestrel (LNG), and norethindrone acetate (NETA), on human endometrial stromal fibroblasts (eSF), key players in endometrial physiology and reproductive success. While there were similar transcriptional responses, each progestin induced unique genes and biofunctions, consistent with their structural similarities to progesterone (P₄ and MPA) or testosterone (LNG and NETA), involving cellular proliferation, migration and invasion. Addition of estradiol (E₂) to each progestin influenced the number of differentially expressed genes and biofunctions in P₄ and MPA, while LNG and NETA signatures were more independent of E₂. Together, these data suggest different mechanisms of action for different progestins, with progestin-specific altered signatures when combined with E₂. Further investigation is warranted for a personalized approach in different gynecologic disorders, for contraception, and minimizing side effects associated with their use.

BACKGROUND: Endometriosis, a common oestrogen-dependent inflammatory disorder in women of reproductive age, is characterized by endometrial-like tissue outside its normal location in the uterus, which causes pelvic scarring, pain and infertility. While its pathogenesis is poorly understood, the immune system (systemically and locally in endometrium, pelvic endometriotic lesions and peritoneal fluid) is believed to play a central role in its aetiology, pathophysiology and associated morbidities of pain, infertility and poor pregnancy outcomes. However, immune cell populations within the endometrium of women with the disease have had incomplete phenotyping, thereby limiting insight into their roles in this disorder.OBJECTIVE AND RATIONALE: The objective herein was to determine reproducible and consistent findings regarding specific immune cell populations and their abundance, steroid hormone responsiveness, functionality, activation states, and markers, locally and systemically in women with and without endometriosis.SEARCH METHODS: A comprehensive English language PubMed, Medline and Google Scholar search was conducted with key search terms that included endometriosis, inflammation, human eutopic/ectopic endometrium, immune cells, immune population, immune system, macrophages, dendritic cells (DC), natural killer cells, mast cells, eosinophils, neutrophils, B cells and T cells.OUTCOMES: In women with endometriosis compared to those without endometriosis, some endometrial immune cells display similar cycle-phase variation, whereas macrophages (Mø), immature DC and regulatory T cells behave differently. A pro-inflammatory Mø1 phenotype versus anti-inflammatory Mø2 phenotype predominates and natural killer cells display abnormal activity in endometrium of women with the disease. Conflicting data largely derive from small studies, variably defined hormonal milieu and different experimental approaches and technologies.WIDER IMPLICATIONS: Phenotyping immune cell subtypes is essential to determine the role of the endometrial immune niche in pregnancy and endometrial homeostasis normally and in women with poor reproductive history and can facilitate development of innovative diagnostics and therapeutics for associated symptoms and compromised reproductive outcomes.