Evidence map›Paper›PMID 39834784›Full record

ArticleFrontiers in molecular biosciences2024

Exploring the causal role of plasma metabolites and metabolite ratios in prostate cancer: a two-sample Mendelian randomization study.

Changzhou Feng, Haining Li, Chu Zhang, Ying Zhou, Huanhuan Zhang, Ping Zheng, Shaolin Zhao, Lei Wang, Jin Yang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in molecular biosciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Changzhou Feng *Department of Clinical Laboratory, The First People's Hospital of Lianyungang, The Affiliated Lianyungang Hospital of Xuzhou Medical University, The First Affiliated Hospital of Kangda College of Nanjing Medical University, Lianyungang, Jiangsu, China.
Haining Li *Department of Clinical Laboratory, The First People's Hospital of Lianyungang, The Affiliated Lianyungang Hospital of Xuzhou Medical University, The First Affiliated Hospital of Kangda College of Nanjing Medical University, Lianyungang, Jiangsu, China.
Chu ZhangDepartment of Clinical Laboratory, The First People's Hospital of Lianyungang, The Affiliated Lianyungang Hospital of Xuzhou Medical University, The First Affiliated Hospital of Kangda College of Nanjing Medical University, Lianyungang, Jiangsu, China.
Ying ZhouDepartment of Clinical Laboratory, The First People's Hospital of Lianyungang, The Affiliated Lianyungang Hospital of Xuzhou Medical University, The First Affiliated Hospital of Kangda College of Nanjing Medical University, Lianyungang, Jiangsu, China.
Huanhuan ZhangDepartment of Clinical Laboratory, The First People's Hospital of Lianyungang, The Affiliated Lianyungang Hospital of Xuzhou Medical University, The First Affiliated Hospital of Kangda College of Nanjing Medical University, Lianyungang, Jiangsu, China.
Ping ZhengDepartment of Clinical Laboratory, The First People's Hospital of Lianyungang, The Affiliated Lianyungang Hospital of Xuzhou Medical University, The First Affiliated Hospital of Kangda College of Nanjing Medical University, Lianyungang, Jiangsu, China.
Shaolin ZhaoDepartment of Clinical Laboratory, The First People's Hospital of Lianyungang, The Affiliated Lianyungang Hospital of Xuzhou Medical University, The First Affiliated Hospital of Kangda College of Nanjing Medical University, Lianyungang, Jiangsu, China.
Lei WangDepartment of Clinical Laboratory, The First People's Hospital of Lianyungang, The Affiliated Lianyungang Hospital of Xuzhou Medical University, The First Affiliated Hospital of Kangda College of Nanjing Medical University, Lianyungang, Jiangsu, China.
Jin YangDepartment of Clinical Laboratory, The First People's Hospital of Lianyungang, The Affiliated Lianyungang Hospital of Xuzhou Medical University, The First Affiliated Hospital of Kangda College of Nanjing Medical University, Lianyungang, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Prostate cancer (PCa), the most prevalent malignant neoplasm in males, involves complex biological mechanisms and risk factors, many of which remain unidentified. By employing a novel two-sample Mendelian randomization (MR) approach, this study aims to elucidate the causal relationships between the circulating metabolome and PCa risk, utilizing comprehensive data on genetically determined plasma metabolites and metabolite ratios. Methods: For the MR analysis, we utilized data from the GWAS Catalog database to analyze 1,091 plasma metabolites and 309 ratios in relation to PCa outcomes within two independent GWAS datasets. The inverse variance weighted (IVW) method was the primary approach for determining the existence of the causal relationship, supplemented by additional MR methods for heterogeneity, pleiotropy, and cross-validation. The false discovery rate (FDR) and Bonferroni correction were applied to identify the most significant causative associations. Additionally, reverse MR and Steiger filtering were conducted to ascertain whether PCa influenced the observed metabolite levels. Furthermore, metabolic pathway analysis was conducted with MetaboAnalyst 6.0 software. Results: In the MR analysis, our findings reveal three overlapped metabolite ratios (arginine to glutamate, phosphate to uridine, and glycerol to mannitol/sorbitol) inversely associated with PCa risk. Following FDR correction (FDR < 0.05), cysteinylglycine disulfide was identified as a potential reducer of PCa risk, whereas Uridine and N-acetyl-L-glutamine (NAG) were pinpointed as potential risk factors. Notably, NAG (OR 1.044; 95% CI 1.025-1.063) emerged as a metabolite with significant causal influence, as confirmed by stringent Bonferroni correction ( Conclusion: This study provides novel insights into the potential causal effects of plasma metabolites and metabolite ratios on PCa. The identified metabolites and ratios could serve as candidate biomarkers, contributing to the elucidation of PCa's biological mechanisms.

Indexed as

Mendelian randomization (MR)metabolitesmetabolites ratiosprostate cancer (PCa)risk

Identifiers

PMID39834784
PMCPMC11743260

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.