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

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 employed for two-sample MR analysis, with reverse MR analysis also performed. Sensitivity analysis was 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.

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Publication Details

Journal
Journal of the Chinese Medical Association
Published
2026-04-13
DOI
https://doi.org/10.1097/jcma.0000000000001377
Primary Topic
Urinary Bladder and Prostate Research
Type
article
Field-Weighted Citation Impact
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article

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

Zaisheng Zhu
Journal of the Chinese Medical Association
Urinary Bladder and Prostate Research
article

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

Zaisheng Zhu
article en

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 employed for two-sample MR analysis, with reverse MR analysis also performed. Sensitivity analysis was 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.

Journal of the Chinese Medical Association
Jinhua Central Hospital (CN)
Openalex Percentile: Top 22%
Urinary Bladder and Prostate Research
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