Evidence map›Paper›PMID 38433226›Full record

ArticleBMC medicine2024

Plasma metabolites and risk of seven cancers: a two-sample Mendelian randomization study among European descendants.

Yaxin Chen, Yufang Xie, Hang Ci, Zhengpei Cheng, Yongjie Kuang, Shuqing Li, Gang Wang, Yawen Qi, Jun Tang, Dan Liu and 2 more

Abstract read
In one paragraph

Article in BMC medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed.

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  11. Causal Links Between Antibody-Mediated Immune Responses and Pancreatic Cancer Risk.Endocrine, metabolic & immune disorders drug targets · 2026
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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

12 authors.

Yaxin ChenInstitute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Guoxue Alley 37, Chengdu, Sichuan, China.
Yufang XieDepartment of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Hang CiInstitute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Guoxue Alley 37, Chengdu, Sichuan, China.
Zhengpei ChengCenter for Public Health Genomics, Department of Public Health Sciences, UVA Comprehensive Cancer Center, School of Medicine, University of Virginia, 560 Ray C. Hunt Dr., Rm 4408, Charlottesville, VA, USA.
Yongjie KuangDepartment of Public Health Sciences, UVA Comprehensive Cancer Center, School of Medicine, University of Virginia, Charlottesville, VA, USA.
Shuqing LiInstitute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Guoxue Alley 37, Chengdu, Sichuan, China.
Gang WangInnovation Laboratory for Precision Diagnostics, Precision Medicine Research Center, Precision Medicine Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Yawen QiInstitute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Guoxue Alley 37, Chengdu, Sichuan, China.
Jun TangInstitute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Guoxue Alley 37, Chengdu, Sichuan, China.
Dan LiuDepartment of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Weimin LiInstitute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Guoxue Alley 37, Chengdu, Sichuan, China. weimi003@scu.edu.cn.
Yaohua YangCenter for Public Health Genomics, Department of Public Health Sciences, UVA Comprehensive Cancer Center, School of Medicine, University of Virginia, 560 Ray C. Hunt Dr., Rm 4408, Charlottesville, VA, USA. vta8we@virginia.edu.ORCID 0000-0002-3815-7172

Funding

Dissecting roles of microbiome-host interactions in colorectal neoplasia etiology using multi-omics dataR00CA248822 · NCI · UNIVERSITY OF VIRGINIA · PI YANG, YAOHUA · 2023 to 2025
$724k
NCI NIH HHS R00 CA248822NCI NIH HHS R00CA248822
6 · The paper itself

Abstract

backgroundWhile circulating metabolites have been increasingly linked to cancer risk, the causality underlying these associations remains largely uninterrogated.

methodsWe conducted a comprehensive 2-sample Mendelian randomization (MR) study to evaluate the potential causal relationship between 913 plasma metabolites and the risk of seven cancers among European-ancestry individuals. Data on variant-metabolite associations were obtained from a genome-wide association study (GWAS) of plasma metabolites among 14,296 subjects. Data on variant-cancer associations were gathered from large-scale GWAS consortia for breast (N = 266,081), colorectal (N = 185,616), lung (N = 85,716), ovarian (N = 63,347), prostate (N = 140,306), renal cell (N = 31,190), and testicular germ cell (N = 28,135) cancers. MR analyses were performed with the inverse variance-weighted (IVW) method as the primary strategy to identify significant associations at Bonferroni-corrected P < 0.05 for each cancer type separately. Significant associations were subjected to additional scrutiny via weighted median MR, Egger regression, MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO), and reverse MR analyses. Replication analyses were performed using an independent dataset from a plasma metabolite GWAS including 8,129 participants of European ancestry.

resultsWe identified 94 significant associations, suggesting putative causal associations between 66 distinct plasma metabolites and the risk of seven cancers. Remarkably, 68.2% (45) of these metabolites were each associated with the risk of a specific cancer. Among the 66 metabolites, O-methylcatechol sulfate and 4-vinylphenol sulfate demonstrated the most pronounced positive and negative associations with cancer risk, respectively. Genetically proxied plasma levels of these two metabolites were significantly associated with the risk of lung cancer and renal cell cancer, with an odds ratio and 95% confidence interval of 2.81 (2.33-3.37) and 0.49 (0.40-0.61), respectively. None of these 94 associations was biased by weak instruments, horizontal pleiotropy, or reverse causation. Further, 64 of these 94 were eligible for replication analyses, and 54 (84.4%) showed P < 0.05 with association patterns consistent with those shown in primary analyses.

conclusionsOur study unveils plausible causal relationships between 66 plasma metabolites and cancer risk, expanding our understanding of the role of circulating metabolites in cancer genetics and etiology. These findings hold promise for enhancing cancer risk assessment and prevention strategies, meriting further exploration.

Indexed as

Carcinoma, Renal CellKidney NeoplasmsLung NeoplasmsGenome-Wide Association StudyHumansMaleMendelian Randomization AnalysisCancer riskMendelian randomizationPlasma metabolites

Identifiers

PMID38433226
PMCPMC10910673

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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 OpenQuestion graph.