{Reference Type}: Journal Article
{Title}: Construction of m6A-Related Gene Prediction Model and Subtype Analysis in Non-Obstructive Azoospermia Based on Bioinformatics.
{Author}: Li G;Che K;Wu J;Yang B;
{Journal}: Am J Reprod Immunol
{Volume}: 92
{Issue}: 1
{Year}: 2024 Jul
{Factor}: 3.777
{DOI}: 10.1111/aji.13892
{Abstract}: <B>OBJECTIVE: </B>Non-obstructive azoospermia (NOA) is a severe and common cause of male infertility. Currently, the most reliable predictor of sperm retrieval success in NOA is histopathology, but preoperative testicular biopsy often increases the difficulty of sperm retrieval surgery. This study aims to explore the characteristics of N6-methyladenosine (m6A) modification in NOA patients and investigate the potential biomarkers and molecular mechanisms for pathological diagnosis and treatment of NOA using m6A-related genes.<BR><B>METHODS: </B>NOA-related datasets were downloaded from the GEO database. Based on the results of LASSO regression analysis, a prediction model was established from differentially expressed m6A-related genes, and the predictive performance of the model was evaluated using ROC curves. Cluster analysis was performed based on differentially expressed m6A-related genes to evaluate the differences in different m6A modification patterns in terms of differentially expressed genes (DEGs), biological features, and immune features.<BR><B>RESULTS: </B>There were significant differences in eight m6A-related genes between NOA samples and healthy controls. The ROC curves showed excellent predictive performance for the diagnostic models constructed with ALKBH5 and FTO. DEGs of two m6A modification subtypes indicated the influence of m6A-related genes in the biological processes of mitosis and meiosis in NOA patients, and there were significant immune differences between the two subtypes.<BR><B>CONCLUSIONS: </B>The NOA pathological diagnostic models constructed with FTO and ALKBH5 have good predictive ability. We have identified two different m6A modification subtypes, which may help predict sperm retrieval success rate and treatment selection in NOA patients.