Evidence map›Paper›PMID 40671045›Full record

ArticleJournal of translational medicine2025

Integrated analysis of blood microbiome and metabolites reveals key biomarkers and functional pathways in myocardial infarction.

Ikram Khan, Stefan Panaiotov, Kotb A Attia, Arif Ahmed Mohammed, Muhammad Uzair, Imran Khan, Zhiqiang Li, Xiaodong Xie

Abstract read
In one paragraph

Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. The Gut-Liver Axis in Metabolic Dysfunction-Associated Steatotic Liver Disease: From Mechanistic Insights to Precision Therapeutics.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026
    Review
  3. 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

8 authors.

Ikram KhanDepartment of Genetics, School of Basic Medical Sciences, Lanzhou University, Lanzhou, Gansu, 730000, China.
Stefan PanaiotovMicrobiology Department, National Center of Infectious and Parasitic Diseases, Yanko Sakazov 26 Blvd., Sofia, 1504, Bulgaria.
Kotb A AttiaDepartment of Biochemistry, College of Science, King Saud University, Riyadh, 11451, Saudi Arabia.
Arif Ahmed MohammedDepartment of Biochemistry, College of Science, King Saud University, Riyadh, 11451, Saudi Arabia.
Muhammad UzairNational Institute for Genomics and Advanced Biotechnology, Park Road, Islamabad, 45500, Pakistan.
Imran KhanDepartment of Microecology, School of Basic Medical Sciences, Dalian Medical University, Dalian, Liaoning, China.
Zhiqiang LiSchool of Stomatology, Key Laboratory of Oral Disease, Northwest Minzu University, Lanzhou, Gansu, China. lizhiqiang6767@163.com.
Xiaodong XieDepartment of Genetics, School of Basic Medical Sciences, Lanzhou University, Lanzhou, Gansu, 730000, China. xdxie@lzu.edu.cn.

Funding

Gansu Provincial Science and Technology Program 22JR5RA19Science and Technology Program gansu province 24ZDCA004
6 · The paper itself

Abstract

backgroundMyocardial infarction (MI) has been linked to changes in the blood microbiome, yet the interplay between microbiome and metabolome remains poorly understood. This study integrates blood microbiome profiling and metabolomic analysis to uncover biomarkers and pathways associated with MI.

methodsUsing 16 S rRNA sequencing and LC-MS metabolomics, blood samples from 24 MI patients and 24 healthy controls were analyzed. Microbial diversity, key taxa, metabolites, and their functional implications were evaluated.

resultsWhile alpha and beta diversity of the microbiome showed no significant differences, three bacterial taxa (Proteobacteria, Gammaproteobacteria, and Bacilli) and twenty metabolites (e.g., UPD-L-Ara4O, Urotensin-related peptide, and 9-hydroxy octadecanoic acid) were identified as potential biomarkers, achieving an AUC of 0.99-1. Functional pathway analysis revealed upregulation in glycerolipid metabolism and mTOR signaling pathways, which were significantly correlated with clinical markers of MI.

conclusionThis integrative approach highlights the diagnostic potential of blood microbiome-metabolome dynamics in MI and suggests mechanistic pathways that could guide future interventions.

Indexed as

BiomarkersMetabolomicsMicrobiotaMyocardial InfarctionAgedBacteriaCase-Control StudiesFemaleHumansMaleMetabolomeMiddle AgedRNA, Ribosomal, 16SSignal TransductionBiomarkersRNA, Ribosomal, 16SBlood microbiomeGlycerolipid metabolismMetabolomicsmTOR pathwayMyocardial infarctionPredictive biomarkers

Identifiers

PMID40671045
PMCPMC12269162

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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 OpenQuestion graph.