Sahar Houshdaran

This study uses DNA methylation data to predict endometriosis status and menstrual cycle phase, finding strong performance for cycle phase and moderate performance for endometriosis.

The paper uses single-cell transcriptomics to analyze endometrial cells from endometriosis patients, revealing altered cellular features and immune communication networks across the menstrual cycle.

The paper analyzes endometrial DNA methylation and genetic variants to identify mQTLs and their association with endometriosis risk and menstrual cycle phases.

Nearly 500,000 cells from 24 human tissues, many from one donor, characterize over 400 cell types and enable within-donor study of T-cell clones, B-cell mutation rates and splicing.

This study identifies 13 novel genetic loci associated with endometriosis through a large GWAS meta-analysis and finds genetic links to other pain-related conditions.