Abstract
PURPOSE: To develop a robust quantitative method for assessing testicular spermatogenic capacity in patients with idiopathic non-obstructive azoospermia (iNOA), leveraging single-cell RNA sequencing to enhance diagnostic precision and inform personalized treatment strategies. MATERIALS AND METHODS: This study involved the classification of 18 iNOA patients, encompassing nearly 4000 single cells, into discrete groups based on their gene expression profiles and histological features. We developed a spermatogenesis scoring system that correlates with the expression levels of spermatogenesis-related genes. By applying fuzzy clustering and gene expression trend analyses, we pinpointed key genes correlated with spermatogenic potential, marking them as biomarkers for assessing testicular function. We validated the genes' predictive ability by comparing gene expression in iNOA patients with controls and confirmed their diagnostic potential through RT-qPCR in another 18 patients, ensuring their clinical applicability. RESULTS: We identified five distinct spermatogenic profiles among iNOA patients. Fuzzy clustering and trend analysis showed a strong positive correlation (R = 0.79) between testicular spermatogenic capacity and the expression of Module 2 genes. The top five genes, LDHC, SPINK2, LOC81691, TCP11, and ANKRD7, had a prediction accuracy rate of up to 88% for testicular spermatogenic capacity. This correlation was consistent across various NOA conditions and other spermatogenesis disorders, including Y chromosome microdeletions and Klinefelter syndrome. CONCLUSIONS: These identified gene markers quantify testicular spermatogenic capacity, laying the groundwork for tailored evaluations and therapies in male infertility. This breakthrough deepens our grasp of spermatogenesis and its intricacies.