Unraveling molecular heterogeneity: a systematic review of susceptibility gene profiles in ovarian, deep infiltrating, and superficial peritoneal endometriosis

Background Endometriosis is a heterogeneous gynecological disease manifesting in three distinct phenotypes: superficial peritoneal endometriosis (SUP), ovarian endometrioma (OMA), and deep infiltrating endometriosis (DIE). While Genome-Wide Association Studies (GWAS) have identified numerous susceptibility loci—such as WNT4 , FN1 , and VEZT —the functional translation of these genetic risks into phenotype-specific pathophysiology remains unclear. Objectives This systematic review aims to analyze the differential activation and expression patterns of known endometriosis-susceptibility genes across SUP, OMA, and DIE to determine if distinct genetic signatures define each phenotype. Methods A systematic search was conducted in PubMed, Scopus, and Embase up to September 2025. We included observational case-control and cohort studies comparing the mRNA or protein expression of GWAS-identified susceptibility genes in ectopic endometrial tissue, stratified by phenotype. Quality assessment was performed using the Newcastle-Ottawa Scale (NOS). Results A total of 15 studies involving 1,240 tissue samples were included in the final synthesis. The analysis revealed significant heterogeneity in gene activation. Genes associated with cell adhesion and invasion (e.g., FN1 , MMP2 ) were predominantly upregulated in DIE lesions (Fold Change > 2.5 vs. eutopic), correlating with the fibrotic nature of the disease. Conversely, OMA lesions exhibited a distinct upregulation of oxidative stress-related genes and iron metabolism regulators (e.g., HMOX1 ), likely driven by the hemoglobin-rich environment of the ovary. SUP lesions showed variable expression profiles, often characterized by acute inflammatory markers (e.g., IL-6 , COX-2 ). Conclusion Endometriosis phenotypes are not merely anatomical variations but represent biologically distinct entities driven by unique gene activation profiles. These findings support a move toward phenotype-specific molecular diagnostics and targeted therapies.