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Biology subjects

Irwin, J. C.

Publications and source records attributed to Irwin, J. C..

5 recordsLinked to original sources

Simvastatin and Primaquine Identified as Potential Endometriosis Therapeutics via a Novel Epithelial-Stromal Assembloid Drug Screening Assay

Background: Endometriosis is an estrogen-driven, inflammatory disorder affecting ~10% of menstruators, causing severe pain. Current treatments that reduce estrogen or inflammation have inconsistent efficacy and poor tolerability. Therapies identified via drug-repositioning methods, which target patient-specific pathways, offer a promising alternative. Simvastatin and primaquine were identified as potential treatments, strongly reversing endometriosis-associated gene expression pathways, and behavioral testing in an animal model showed that these drugs diminish endometriosis-associated pain. This paper examines their effects in human assembloids to provide proof-of-concept validation and insights into their mechanisms of action relevant to endometriosis. Methods: We established human endometrial assembloids using immortalized epithelial (12Z) and stromal fibroblast (iEc) cell lines, as well as primary tissue from patients. Assembloids were generated in 96-well agarose molds with both cell types. We tested ibuprofen, fenoprofen, primaquine, and simvastatin. Following a 24-hour exposure, assembloids and monolayer cultures were harvested and stranded mRNA-seq libraries were sequenced on an Illumina NovaSeqX Plus System. Results: Gene set enrichment analysis showed key pathway reversals: Primaquine reversed the chemical carcinogenesis ROS pathway in assembloids. Simvastatin reversed cytokine-cytokine receptor interaction in both epithelial and stromal cell lines, and the cytoskeleton in muscle cells pathway in stromal cell lines. Fenoprofen reversed the calcium signaling pathway in stromal cell lines. Conclusion: Simvastatin induced the most significant gene expression changes, notably reversing cytokine-cytokine receptor interactions in both cell lines, mirroring findings from our rat model. Despite the small sample size limitation, these experiments highlight the promise of assembloid models to test therapeutic candidates for endometriosis.

molecular biology↗

A Transcriptomics-Based Computational Drug Repositioning Pipeline Identifies Simvastatin And Primaquine As Novel Therapeutics For Endometriosis Pain

Endometriosis has limited treatment options, prompting the search for novel therapeutics. We previously used a transcriptomics-based computational drug repositioning pipeline to analyze public bulk transcriptomic data of eutopic endometrium from cases and controls and identified several drug candidates. Fenoprofen, our top in silico candidate, was validated in a rat model of endometriosis-associated pain. Building on this, we evaluated herein two additional candidates, simvastatin (a cholesterol-lowering drug) and primaquine (an antimalarial), based on strong endometrial gene expression reversal scores and favorable safety profiles. Using the rat model, we conducted behavioral testing, bulk RNA sequencing, and differential expression analysis to assess their therapeutic potential. We also assessed endometriosis diagnosis among patients prescribed simvastatin in electronic medical records (EMR) across six University of California (UC) healthcare institutions. In vivo validation using a rat model of endometriosis demonstrated that both simvastatin and primaquine significantly reduced vaginal hyperalgesia, a surrogate marker of endometriosis-related pain. RNA-seq of uteri and lesions confirmed reversal of disease-associated gene expression signatures following treatment. Analysis of UC-wide EMR data found lower relative risk of endometriosis among those prescribed simvastatin compared to a matched control group. Overall, simvastatin and primaquine attenuated pain-associated behaviors and reversed endometriosis-related gene expression changes in an animal model. Moreover, simvastatin prescription was associated with a lower relative risk of endometriosis in our retrospective multi-center cohort study. These findings highlight their potential as repurposed therapeutics for endometriosis and support the effectiveness of computational drug repositioning in identifying new treatment strategies. One Sentence SummarySimvastatin and primaquine reduced endometriosis pain and reversed gene signatures, with simvastatin also linked to lower disease risk.

bioinformatics↗

Anticlustering for Sample Allocation To Minimize Batch Effects

High throughput sequencing is a powerful tool for processing large amounts of DNA and RNA samples in batches. Proper experimental design and statistical methods are required to mitigate systematic technical factors due to differences in batches ("batch effects"), as data variation due to these non-biological factors can mask actual biological differences. We propose using anticlustering as an automated method to assign samples to balanced batches. Anticlustering effectively negates differences in (numeric and/or categorical) covariates among batches, and implements user-defined restrictions on the number of batches, the number of samples per batch, and whether to assign certain samples to the same batch ("must-link constraints"). A simulation study shows that anticlustering is better at achieving balance among batches than previous approaches. An application from the UCSF-Stanford Endometriosis Center for Discovery, Innovation, Training and Community Engagement ("ENACT", https://enactcenter.org/) is presented as a real-life example. In the application, multiple samples provided by an individual had to be processed on the same batch, so that comparisons among different samples of the same patient were not diluted by batch effects. The novel Two Phase Must Link (2PML) anticlustering algorithm realized the must-link restrictions while simultaneously obtaining balance among batches regarding disease stage, menstrual cycle phase, case versus control sample, and clinical site. All methods presented here are accessible via the free and open source R package anticlust (https://cran.r-project.org/package=anticlust). An interactive visualization and web-based batch assignment tool are made available in the Rshiny app "anticlust" (https://anticlust.org/).

bioinformatics↗

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↗

Deep Immunophenotyping Reveals Endometriosis is Marked by Dysregulation of the Mononuclear Phagocytic System in Endometrium and Peripheral Blood

BackgroundEndometriosis is a chronic, estrogen-dependent disorder where inflammation contributes to disease-associated symptoms of pelvic pain and infertility. Immune dysfunction includes insufficient immune lesion clearance, a pro-inflammatory endometrial environment, and systemic inflammation. Comprehensive understanding of endometriosis immune pathophysiology in different hormonal milieu and disease severity has been hampered by limited direct characterization of immune populations in endometrium, blood, and lesions. Simultaneous deep phenotyping at single cell resolution of complex tissues has transformed our understanding of the immune system and its role in many diseases. Herein, we report mass cytometry and high dimensional analyses to study immune cell phenotypes, abundance, activation states, and functions in endometrium and blood of women with and without endometriosis in different cycle phases and disease stages. MethodsA case-control study was designed. Endometrial biopsies and blood (n=60 total) were obtained from women with (n=20, n=17, respectively) and without (n=14, n=9) endometriosis in the proliferative and secretory cycle phases of the menstrual cycle. Two mass cytometry panels were designed; one broad panel and one specific for mononuclear phagocytic cells (MPC), and all samples were multiplexed to characterize both endometrium and blood immune composition at unprecedented resolution. We combined supervised and unsupervised analyses to finely define the immune cell subsets with an emphasis on MPC. Then, association between cell types, protein expression, disease status, and cycle phase were performed. ResultsThe broad panel highlighted a significant modification of MPC in endometriosis; thus, they were studied in detail with an MPC-focused panel. Endometrial CD91+ macrophages overexpressed SIRP (phagocytosis inhibitor) and CD64 (associated with inflammation) in endometriosis, and they were more abundant in mild versus severe disease. In blood, classical and intermediate monocytes were less abundant in endometriosis, whereas plasmacytoid dendritic cells and non-classical monocytes were more abundant. Non-classical monocytes were higher in severe versus mild disease. ConclusionsA greater inflammatory phenotype and decreased phagocytic capacity of endometrial macrophages in endometriosis are consistent with defective clearance of endometrial cells shed during menses and in tissue homeostasis, with implications in endometriosis pathogenesis and pathophysiology. Different proportions of monocytes and plasmacytoid dendritic cells in blood from endometriosis suggest systemically aberrant functionality of the myeloid system opening new venues for the study of biomarkers and therapies for endometriosis.

immunology↗