Evidence mapPaperPMID 38544498Full record

ArticleJournal of geriatric cardiology : JGC2024

Plasma metabolites and risk of myocardial infarction: a bidirectional Mendelian randomization study.

Dong-Hua Li, Qiang Wu, Jing-Sheng Lan, Shuo Chen, You-Yi Huang, Lan-Jin Wu, Zhi-Qing Qin, Ying Huang, Wan-Zhong Huang, Ting Zeng and 3 more

Open access · greenAbstract read
In one paragraph

Article in Journal of geriatric cardiology : JGC, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
5.0field-weighted citation impact, top 5% of its field
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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Trial
  2. Article
  3. Research Progress of Regulatory Cell Death in Coronary Microembolization.International journal of medical sciences · 2025
    Review
  4. Article
  5. 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

13 authors at 1 institution in 1 country.

Dong-Hua LiDepartment of Cardiovascular Medicine, Minzu Hospital of Guangxi Zhuang Autonomous Region, Guangxi, China.
Qiang WuSenior Department of Cardiology, the Sixth Medical Center, Chinese PLA General Hospital, Beijing, China.
Jing-Sheng LanDepartment of Cardiovascular Medicine, Minzu Hospital of Guangxi Zhuang Autonomous Region, Guangxi, China.
Shuo ChenLibrary of Graduate School, Chinese PLA General Hospital, Beijing, China.
You-Yi HuangDepartment of Cardiovascular Medicine, Minzu Hospital of Guangxi Zhuang Autonomous Region, Guangxi, China.
Lan-Jin WuDepartment of Cardiovascular Medicine, Minzu Hospital of Guangxi Zhuang Autonomous Region, Guangxi, China.
Zhi-Qing QinDepartment of Cardiovascular Medicine, Minzu Hospital of Guangxi Zhuang Autonomous Region, Guangxi, China.
Ying HuangDepartment of Cardiovascular Medicine, Minzu Hospital of Guangxi Zhuang Autonomous Region, Guangxi, China.
Wan-Zhong HuangDepartment of Cardiology, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, Guangxi, China.
Ting ZengDepartment of Cardiology, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, Guangxi, China.
Xin HaoHealth Management Institute, the Second Medical Center, Chinese PLA General Hospital, Beijing, China.
Hua-Bin SuDepartment of Cardiology, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, Guangxi, China.
Qiang SuDepartment of Cardiology, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, Guangxi, China.
Chinese PLA General Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMyocardial infarction (MI) is a critical cardiovascular event with multifaceted etiology, involving several genetic and environmental factors. It is essential to understand the function of plasma metabolites in the development of MI and unravel its complex pathogenesis.

methodsThis study employed a bidirectional Mendelian randomization (MR) approach to investigate the causal relationships between plasma metabolites and MI risk. We used genetic instruments as proxies for plasma metabolites and MI and conducted MR analyses in both directions to assess the impact of metabolites on MI risk and vice versa. In addition, the large-scale genome-wide association studies datasets was used to identify genetic variants associated with plasma metabolite (1400 metabolites) and MI (20,917 individuals with MI and 440,906 individuals without MI) susceptibility. Inverse variance weighted was the primary method for estimating causal effects. MR estimates are expressed as beta coefficients or odds ratio (OR) with 95% CI.

resultsWe identified 14 plasma metabolites associated with the occurrence of MI (

conclusionsOur bidirectional MR study identified 14 plasma metabolites associated with the occurrence of MI, among which 13 plasma metabolites have not been reported previously. These findings provide valuable insights for the early diagnosis of MI and potential therapeutic targets.

Identifiers

PMID38544498
PMCPMC10964012
OpenAlexW4393444252

What Socratic holds

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Registered trials

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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.