Evidence map›Paper›PMID 40182922›Full record

ArticleFrontiers in genetics2025

Causal relationships between serum metabolites and coronary heart disease risk: a mendelian randomization study.

Xiao-Yan Meng, Yong-Qing Zhu, Ying-Jie Zhang, Wei Sun, Shu-Ang Li

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Article in Frontiers in genetics, 2025. 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

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5 · Who and what money

Authors and funding

5 authors.

Xiao-Yan Meng *Clinical Systems Biology Laboratories, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Yong-Qing Zhu *Clinical Systems Biology Laboratories, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Ying-Jie ZhangClinical Systems Biology Laboratories, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Wei SunDepartment of Burn and Repair Reconstruction, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Shu-Ang LiClinical Systems Biology Laboratories, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Coronary heart disease (CHD) represents a substantial global burden in terms of morbidity and mortality. Understanding the causal relationships between serum metabolites and CHD can provide a crucial understanding of disease mechanisms and potential therapeutic targets. Methods: We conducted a Mendelian randomization (MR) approach to explore the potential causal associations between serum metabolites and CHD risk. The primary analysis employed the inverse variance weighted (IVW) method, supplemented by additional analyses, including MR-Egger, weighted median, weighted mode, and sample mode. To bolster the robustness and reliability of our findings, we performed sensitivity analyses, which included evaluating, horizontal pleiotropy and leave-one-out analysis. Additionally, pathway enrichment analysis was conducted. Results: We identified 15 known and 11 unknown metabolites with potential associations to CHD. Among the known, six displayed protective effects, while nine were identified as risk factors. Notably, many of these metabolites are closely related to mitochondrial function, which was further supported by pathways and enrichment analysis. Using multiple statistical models to ensure robust results, we unveiled a significant association between hexadecanedioate, a palmitoyl lipid metabolized in mitochondria, and a ∼18% reduced risk of CHD (OR = 0.82, 95%CI: 0.72-0.93). Conclusion: MR analysis revealed 6 protective molecules, 9 hazardous metabolites associated with CHD. Many of these known metabolites are closely link to mitochondrial function, suggesting a critical role of mitochondria in CHD development. In particular, hexadecanedioate, an essential component for mitochondrial energy production, was inversely associated with CHD risk. This suggests that mitochondrial function, and specifically the role of hexadecanedioate, may be pivotal in the development and progression of CHD.

Indexed as

causal relationshipcoronary heart diseasehexadecanedioatemendelian randomizationrisk factorsserum metabolites

Identifiers

PMID40182922
PMCPMC11965349

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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.