Causal links of 233 metabolic markers to benign prostatic hyperplasia: Mendelian randomization and RNA-sequencing insights.

IF 2.4
Pengfei Zhou, Zaisheng Zhu
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Abstract

Background: Benign prostatic hyperplasia (BPH) is a common urological condition affecting middle-aged and elderly men, and it significantly impairs their quality of life. Although metabolic disorders are suspected to contribute to BPH, the causal relationship between metabolic markers and BPH remains unclear due to the limitations of traditional observational studies.

Methods: In this study, Mendelian randomization (MR) analysis was performed by integrating genome-wide association study (GWAS) data from European populations, integrating metabolites from the GWAS Catalog, BPH-related GWAS data from OpenGWAS, and gene expression data from GEO. Five regression models were used for two-sample MR analysis, with reverse MR analysis also performed. Sensitivity analyses were carried out through stringent instrumental variable selection criteria, including heterogeneity tests, horizontal pleiotropy tests, and leave-one-out analysis. Additionally, differential gene expression analysis, consensus clustering of BPH subtypes, characteristic gene screening, diagnostic model construction, immune infiltration analysis, and single-gene Gene Set Enrichment Analysis (GSEA) were performed.

Results: MR analysis identified several metabolic markers, including total cholesterol, valine, and alanine in HDL, that were significantly associated with BPH, all acting as risk factors. Reverse MR analysis revealed no evidence of reverse causal effects of BPH on most metabolic markers. Additionally, distinct BPH subtypes were identified, along with three key genes (GRAMD2B, HEBP2, and STRADB). A highly accurate diagnostic model was constructed based on these genes.

Conclusion: This study elucidates the causal relationship between metabolic markers and BPH, offering new insights into the etiology, diagnosis, and treatment of the disease. However, limitations include the lack of in vitro experimental validation. Future research should address these limitations, further explore the pathogenesis of BPH, and facilitate the development of more effective prevention and treatment strategies.

233个代谢标记与良性前列腺增生的因果关系:孟德尔随机化和RNA测序的见解。
背景:良性前列腺增生(BPH)是影响中老年男性的一种常见泌尿系统疾病,严重影响其生活质量。尽管代谢紊乱被怀疑与BPH有关,但由于传统观察性研究的局限性,代谢标志物与BPH之间的因果关系尚不清楚。方法:在本研究中,通过整合来自欧洲人群的全基因组关联研究(GWAS)数据、来自GWAS目录的代谢物、来自OpenGWAS的bph相关GWAS数据和来自GEO的基因表达数据,进行孟德尔随机化(MR)分析。采用五种回归模型进行双样本MR分析,并进行反向MR分析。通过严格的工具变量选择标准进行敏感性分析,包括异质性检验、水平多效性检验和遗漏分析。此外,还进行了差异基因表达分析、BPH亚型共识聚类、特征基因筛选、诊断模型构建、免疫浸润分析和单基因基因集富集分析(GSEA)。结果:MR分析确定了几种代谢标志物,包括HDL中的总胆固醇、缬氨酸和丙氨酸,它们与BPH显著相关,都是风险因素。反向MR分析显示,没有证据表明BPH对大多数代谢标志物有反向因果效应。此外,还鉴定出不同的BPH亚型,以及三个关键基因(GRAMD2B、HEBP2和STRADB)。基于这些基因构建了一个高精度的诊断模型。结论:本研究阐明了代谢标志物与BPH之间的因果关系,为该病的病因、诊断和治疗提供了新的见解。然而,局限性包括缺乏体外实验验证。未来的研究应解决这些局限性,进一步探索前列腺增生的发病机制,并促进制定更有效的预防和治疗策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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