Biology subjects

Mortlock, S.

Publications and source records attributed to Mortlock, S..

7 recordsLinked to original sources

bioRxiv2026

Predicting Endometriosis Status and Menstrual Cycle Phase Using DNA Methylation

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.

bioinformatics↗

bioRxiv2025

Molecular signature of human endometrial stem/progenitor cells at the single cell level

Human endometrium sheds and regenerates each month during the menstrual cycle. N-cadherin+ (CDH2) glandular epithelial progenitors and SUSD2+ MSC and their niches have been identified but their signaling interactions remain unknown. SSEA1+ epithelial cells resurface the endometrium generating a new luminal epithelium each cycle. Based on these markers, we characterised the gene expression of human endometrial stem/progenitor cell-enriched populations derived from FACSorted hysterectomy endometrium by scRNAseq. Two of 10 epithelial clusters contained CDH2+SOX9+ cells with high TRH and IHH expression. N-cadherin and IHH, and SSEA1 and Hedgehog coreceptor BOC immunocolocalised in the basal layer of endometrial glands from which the new functional layer glands regenerate each menstrual cycle. Two of six mesenchymal clusters contained SUSD2+ MSC, one with high MUSTN1 expression. Epithelial progenitors and endometrial MSC transitioned to their respective progeny. We provide new insights into human endometrial stem/progenitor cell signaling pathways and niche interactions regulating their function. HighlightsO_LIEnriching cell suspensions of human endometrial cells from hysterectomy tissues with CDH2+ epithelial progenitors, SSEA-1+ basalis epithelial cells and SUSD2+ perivascular MSC enabled their gene profiling at the single cell level. C_LIO_LIMultiple cell fate trajectory analyses showed that CDH2+SOX9+ epithelial cells and SUSD2+MYH11+MCAM+MUSTN1+ MSC are the progenitors for human endometrial glandular and luminal epithelial cells, and stromal vascular cells, respectively. C_LIO_LIEnriched TRH expression in human endometrial epithelial progenitors suggests a role in their progenitor function. C_LIO_LIInteraction between IHH of SOX9+ human endometrial epithelial progenitors with basalis fibroblasts and decidualized stroma and co-receptor BOC suggests IHH signalling may have a role in basalis epithelial migration to repair the luminal epithelium during menses. C_LI eTOC blurbGargett and colleagues provide a molecular signature of human endometrial stem/progenitor cells by enriching 4 stem/progenitor populations from hysterectomies using known markers for scRNAseq analysis. The two epithelial and two MSC progenitor states identified transitioned to their differentiated progeny. IHH was validated as a key signalling molecule of epithelial progenitors in basal glands that interacted with BOC co-receptors.

molecular biology↗

bioRxiv2024

M2 Macrophages are Major Mediators of Germline Risk of Endometriosis and Explain Pleiotropy with Comorbid Traits

Endometriosis is a common gynecologic condition that causes chronic life-altering symptoms including pain, infertility, and elevated cancer risk. There is an urgent need for new non-hormonal targeted therapeutics to treat endometriosis, but until very recently, the cellular and molecular signatures of endometriotic lesions were undefined, severely hindering the development of clinical advances. Integrating inherited risk data from analyses of >450,000 individuals with [~]350,000 single cell transcriptomes from 21 patients, we uncover M2-macrophages as candidate drivers of disease susceptibility, and nominate IL1 signaling as a central hub impacted by germline genetic variation associated with endometriosis. Extensive functional follow-up confirmed these associations and revealed a pleiotropic role for this pathway in endometriosis. Population-scale expression quantitative trail locus analysis demonstrated that genetic variation controlling IL1A expression is also associated with endometriosis risk variants. Manipulation of IL1 signaling in state-of-the-art in vitro decidualized assembloids impacted epithelial differentiation, and in an in vivo endometriosis model, treatment with anakinra (an interleukin-1 receptor antagonist) resulted in a significant, dose-dependent reduction in both spontaneous pain and evoked pain. Together these studies highlight non-diagnostic cell types as central to endometriosis susceptibility and support IL1 signaling as an important actionable pathway for this disease.

immunology↗

bioRxiv2022

Global Endometrial DNA Multi-omics Analysis Reveals Insights into mQTL Regulation and Associated Endometriosis Disease Risk

Endometriosis is a leading cause of pain and infertility affecting millions of women globally. Identifying biologic and genetic effects on DNA methylation (DNAm) in endometrium increases understanding of mechanisms that influence gene regulation predisposing to endometriosis and offers an opportunity for novel therapeutic target discovery. Herein, we characterize variation in endometrial DNAm and its association with menstrual cycle phase, endometriosis, and genetic variants through analysis of genome-wide genotype data and methylation at 759,345 DNAm sites in endometrial samples from 984 deeply-phenotyped participants. We identify significant differences in DNAm profiles between menstrual cycle phases and at four DNAm sites between stage III/IV endometriosis and controls. We estimate that 15.4% of the variation in endometriosis is captured by DNAm, and identify DNAm networks associated with endometriosis. DNAm quantitative trait locus (mQTL) analysis identified 118,185 independent cis-mQTL including some tissue-specific effects. We find significant differences in DNAm profiles between endometriosis sub- phenotypes and a significant association between genetic regulation of methylation in endometrium and disease risk, providing functional evidence for genomic targets contributing to endometriosis risk and pathogenesis.

systems biology↗

bioRxiv2021

An extremes of phenotype approach confirms significant genetic heterogeneity in patients with ulcerative colitis.

Ulcerative colitis (UC) is a major form of inflammatory bowel disease with increasing global incidence. There is significant phenotypic heterogeneity defined by a range of clinical variables including age of onset and disease extent. Clinical outcomes range from long-term remission on minimal therapy to surgical resection. Close to 70% of UC risk can be attributed to genetics and understanding the genetic mechanisms contributing to this risk and disease heterogeneity is vital for understanding disease pathogenesis and improving patient outcomes through targeted screening and therapies. This study aims to characterise the genetic heterogeneity of UC by identifying genomic risk variants specific to mild and/or severe forms of UC, exploring variations in the effect size of known risk variants and assessing the clinical value of a genetic risk score (GRS). We conducted genome-wide association (GWA) analyses in 287 patients with mild UC, 311 patients with severe UC and 583 age- and gender-matched controls. Odds ratios (OR) for mild vs control, severe vs control and combined mild and severe UC vs control were calculated. Using the combined UC data, two independent loci in the HLA region reached genome-wide significance. An additional genome-wide significant signal on chromosome 1 was identified in severe cases only. OR for known risk loci varied between mild and severe patients and were similar to previously published results. Effect estimates from the most recent UC GWA meta-analysis were used to calculate a GRS for each individual. A higher mean GRS was observed in both mild and severe UC cases compared to controls however, there was no difference between the mean GRS for mild and severe UC. Heterogeneity in effect sizes of UC associated variants between mild and severe disease burden suggests the presence of genetically distinct signatures. While large consortium data are needed to identify genome-wide significant variants, additional risk loci may be identified by targeted recruitment of individuals with a history of severe disease. Author SummaryUlcerative colitis (UC) is a chronic and often debilitating form of inflammatory bowel disease affecting approximately 0.3% of the population in industrialized economies. The disease displays significant clinical heterogeneity including age at presentation, disease severity, and the propensity to develop disease-related complications. Several previous studies have demonstrated the heritability of UC, identifying over 30 loci specific to the disease. The majority of these loci have small to modest effect sizes other than those within the Human Leucocyte Antigen (HLA) region on chromosome 6. Using stringent clinical criteria for defining mild and severe forms of UC in an extremes of phenotype approach, we undertook a genome wide association study in a dataset of 1222 participants to investigate genetic heterogeneity in this disease. We demonstrated substantial differences in genetic associations in severe UC as compared to mild UC. While over 2,000 SNPs achieved genome-wide significance in the severe UC analysis, none reached significance for mild UC. These results were reflected in significant differences in odds ratios. We identified Complement Factor B (CFB) as a potential susceptibility gene for severe UC in the Caucasian population with additional tissue gene expression demonstrating a positive correlation with disease severity.

genetics↗

bioRxiv2021

Dominant Effect Of Host Genetics On Skin Microbiota Composition In Homeostasis And Wound Healing

Animal microbiota have complex interactions with hosts and environment that determines its composition. Yet the ability of hosts to determine their microbiota composition is less well studied. In this study, to investigate the role host genetics in determining skin microbiota, we used 30 different mouse strains from the recombinant inbred panel, the Collaborative Cross. Murine skin microbiota composition was strongly dependent on murine strain with > 50% of the variation explained by murine strain. In particular, a quantitative trait locus on chromosome 4 associates both with Staphylococcus abundance and principal-component multi-trait analyses. Additionally, excisional wound associated changes in microbiota composition were not uniform across mouse strains and were host-specific, the genetic background accounting for about 40% of the variation in microbiota. Genetic background also had the highest effect on the healing speed of wounds accounting for over 50% of the variation while mouse age and microbiota composition change accounted only for 20% and 5% of the healing speed despite reaching statistical significance. In conclusion, host genetics has a significant impact on the skin microbiota composition during both homeostasis and wound healing. These findings have long reaching implications in our understanding of associations between microbiota dysbiosis and disease.

systems biology↗

bioRxiv2018

Large-scale genome-wide association meta-analysis of endometriosis reveals 13 novel loci and genetically-associated comorbidity with other pain conditions

Endometriosis is a common complex inflammatory condition characterised by the presence of endometrium-like tissue outside the uterus, mainly in the pelvic area. It is associated with chronic pelvic pain and infertility, and its pathogenesis remains poorly understood. The disease is typically classified according to the revised American Fertility Society (rAFS) 4-stage surgical assessment system, although stage does not correlate well with symptomatology or prognosis. Previously identified genetic variants mainly are associated with stage III/IV disease, highlighting the need for further phenotype-stratified analysis that requires larger datasets. We conducted a meta-analysis of 15 genome-wide association studies (GWAS) and a replication analysis, including 58,115 cases and 733,480 controls in total, and sub-phenotype analyses of stage I/II, stage III/IV and infertility-associated endometriosis cases. This revealed 27 genetic loci associated with endometriosis at the genome-wide p-value threshold (P<5x10-8), 13 of which are novel and an additional 8 novel genes identified from gene-based association analyses. Of the 27 loci, 21 (78%) had greater effect sizes in stage III/IV disease compared to stage I/II, 1 (4%) had greater effect size in stage I/II compared to stage III/IV and 17 (63%) had greater effect sizes when restricted to infertility-associated endometriosis cases compared to overall endometriosis. These results suggest that specific variants may confer risk for different sub-types of endometriosis through distinct pathways. Analyses of genetic variants underlying different pain symptoms reported in the UK Biobank showed that 7/9 had positive significant (p<1.28x103) positive genetic correlations with endometriosis, suggesting a genetic basis for sensitivity to pain in general. Additional conditions with significant positive genetic correlations with endometriosis included uterine fibroids, excessive and irregular menstrual bleeding, osteoarthritis, diabetes as well as menstrual cycle length and age at menarche. These results provide a basis for fine-mapping of the causal variants at these 27 loci, and for functional follow-up to understand their contribution to endometriosis and its potential subtypes.

genomics↗