The mendelian randomized study revealed the association of prostatitis with prostate cancer risk

• Published in: Scientific reports Vol. 14; no. 1; p. 24643
• Main Authors: Chen, Jun, Ye, Fan, Shang, Kun, Li, Ning, Li, Changjiu, He, Huadong
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 20.10.2024; Nature Publishing Group
• Subjects: 631/67/2195; 692/4025/1752; Bioinformatics; Causality; Genetic diversity; Genetic Predisposition to Disease; Genome-wide association studies; Genome-Wide Association Study; Health risks; Heterogeneity; Humanities and Social Sciences; Humans; Male; Mendelian Randomization Analysis - methods; Middle Aged; multidisciplinary; Observational studies; Polymorphism, Single Nucleotide; Prostate cancer; Prostatic Neoplasms - genetics; Prostatitis; Prostatitis - epidemiology; Prostatitis - genetics; Risk Factors; Science; Science (multidisciplinary); Prostate cancer; Prostatitis; Mendelian randomization
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-024-76355-4

In recent observational studies, a potential link between prostatitis and prostate cancer (PCa) has been hinted at, yet the causality remains ambiguous. In our endeavor to scrutinize the conceivable causal nexus between prostatitis and PCa, we embarked upon a Mendelian randomization (MR) study. MR circumvents arbitrary groupings by employing genetic variations that have a strong association with the exposure as instrumental variables to infer causal relationships between exposures and outcomes. The etiology of PCa remains elusive. Given that prostatitis and prostate cancer occupy the same anatomical region, MR can more effectively delineate their relationship by mitigating confounding variables. This method can indirectly elucidate disease correlations, thereby contributing to cancer prevention strategies. FinnGen Consortium data were used for the prostatitis genome-wide association study (GWAS), including 74,658 participants. UK biobank baseline data (ncase = 3436, ncontrol = 459574), European Bioinformatics Institute Database (ncase = 79148, ncontrol = 61106), and IEU openGWAS database (ncase = 79148, ncontrol = 61106) were used for PCa outcomes, mostly for European population samples. Data from the GWSAs for prostatitis were compared with data from the three GWASs for PCa, respectively, in an analysis of an MR. Utilizing the inverse variance weighting (IVW) methodology as our primary analytical framework, we delved into a meticulous exploration of the conceivable causal association between prostatitis and PCa. Furthermore, we deployed supplementary methodologies, including Maximum Likelihood, MR-Egger, weighted median, and MR-PRESSO, to thoroughly assess and scrutinize the causality aspect comprehensively. Cochran’s Q statistic is employed as a metric to quantify the heterogeneity inherent in instrumental variables. The inverse variance weighted analysis revealed no discernible effect of prostatitis on PCa in the three PCa GWAS databases (odds ratio [OR]: 1.001, 95% Confidence Interval [CI]: 0.999–1.002, p =  0.28), (OR: 1.015, 95% CI: 0.981–1.050, p =  0.40), (OR: 1.015, 95% CI: 0.981–1.050, p =  0.40). Similarly, employing MR-Egger did not yield substantial evidence (OR: 0.999, 95% CI: 0.999–1.002, p =  0.89), (OR: 1.103, 95% CI: 1.006–1.209, p =  0.07), (OR: 1.103, 95% CI: 1.006–1.209, p =  0.07). The weighted median analysis also failed to provide convincing support for the impact of prostatitis on the incidence of PCa (OR: 1.001, 95% CI: 1.000-1.002, p =  0.064), (OR: 0.989, 95% CI: 0.946–1.034, p =  0.64), (OR: 0.989, 95% CI: 0.945–1.036, p =  0.65). The results of the MR showed no causality from prostatitis to PCa.