Abstract
BackgroundProstatitis is characterized by high prevalence, low cure rates, and frequent recurrences, and remains one of the most clinically challenging problems. Hence, in this article, we first integrated Mendelian randomization (MR) with expression quantitative trait loci (eQTL) and protein quantitative trait loci (pQTL) data to identify novel therapeutic targets and their potential metabolic mechanisms for prostatitis. MethodsProstatitis-related genetic data, eQTLs, pQTLs, and 1,400 metabolites were downloaded from online databases. MR, or summary data-based MR (SMR) analyses were applied to assess the potential causal relationships between exposures and predicted outcomes. Sensitivity analysis was conducted using pleiotropy, heterogeneity, and leave-one-out analysis to evaluate the robustness of our results. ResultsBased on our results, we first identified and validated GNLY as a novel cis-eQTL and cis-pQTL-mediated susceptibility gene for reducing prostatitis risk in five independent datasets (one discovery dataset and four validation datasets) (all p <0.05). Meanwhile, we also found that the GNLY eQTL could increase the metabolite of sphingomyelin level (d18:0/20:0, d16:0/22:0) risks (p <0.05), and the metabolite of sphingomyelin level (d18:0/20:0, d16:0/22:0) could reduce the risk of prostatitis (p <0.05). According to the above-mentioned relationships, we finally revealed the potential metabolic mechanism of GNLY eQTL in suppressing prostatitis via regulating the metabolite of sphingomyelin level (d18:0/20:0, d16:0/22:0). ConclusionsWe successfully identified GNLY as a novel cis-eQTL and cis-pQTL-mediated susceptibility gene in suppressing prostatitis and its potential metabolic mechanism via regulating sphingomyelin (d18:0/20:0, d16:0/22:0) levels, providing a novel therapeutic target and paving the way for future GNLY-related studies in prostatitis.
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