Intrapartum Obstetric Violence and Associated Factors Among Women Attending Delivery Care at Public Health Facilities of Gondar City: A Cross-Sectional Study.

Male genital lichen sclerosus (MGLSc) is a chronic lichenoid inflammatory fibrosing disorder primarily diagnosed based on clinical symptoms, which include male sexual dysfunction, pruritus, and cutaneous lesions (, ). The etiology of MGLSc remains uncertain, with several hypotheses suggesting autoimmune mechanisms, immune dysregulation, and infectious factors (, , ). Previous studies have highlighted the important role of the foreskin in the development of MGLSc, as the condition is exceedingly rare in men who have undergone circumcision at birth (, ). Another hypothesis posits that MGLSc may result from susceptible epithelial cells being exposed to urine, however, the specific components or characteristics of urine responsible, as well as the relevant susceptibility factors, remain unidentified (, ). As a rare disease, current researches on MGLSc primarily focus on clinical studies and case reports. Unfortunately, our understanding of the underlying basic research on MGLSc remains nearly blank, especially regarding the exploration of its genetic and biological mechanisms. To address the current lack of precise measurement of MGLSc mechanisms, we designed a genome-wide association study (GWAS) targeting potentially unmeasured MGLSc. In this study, we employed Genomic Structural Equation Modeling (Genomic-SEM), a method that leverages publicly available GWAS summary statistics from MGLSc-associated diseases and biomarkers. Using these statistics, we estimated associations between single-nucleotide polymorphisms (SNPs) and the phenotype of MGLSc, thereby constructing a novel GWAS for unmeasured MGLSc and developing a unique Genomic-SEM framework for MGLSc. Additionally, drawing on integrative analysis methods from systems biology, we defined the portion of MGLSc genetic variation unexplained by known biomarkers as “potential relevant genetic markers” and conducted multiple GWAS-related investigations on these markers. This analytical framework has been validated in prior studies, including investigations of allergic diseases () and inflammatory bowel disease (, ). Although this method does not perfectly capture the true relationships between MGLSc-related pathways and multi-factorial interactions—given that MGLSc is inherently a complex process driven by genetic, environmental, and stochastic factors—our study simulates MGLSc construction using Genomic-SEM to bypass these limitations. Importantly, this approach excludes known confounding effects on MGLSc-related biomarkers, enabling the analysis of previously challenging data. Collectively, our study seeks to establish a straightforward bridge between genomic statistics, basic research, and clinical practice.