Evidence map›Paper›PMID 38581039›Full record

ArticleCardiovascular diabetology2024

Oral-gut microbial transmission promotes diabetic coronary heart disease.

Yiwen Li, Yanfei Liu, Jing Cui, Mengmeng Zhu, Wenting Wang, Keji Chen, Luqi Huang, Yue Liu

Open access · goldAbstract read
In one paragraph

Article in Cardiovascular diabetology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
7.7field-weighted citation impact, top 2% 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

38 citing papers in PubMed, 34 citations in OpenAlex.

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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

8 authors at 2 institutions in 1 country.

Yiwen LiNational Clinical Research Center for TCM Cardiology, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, 100091, China.
Yanfei LiuNational Clinical Research Center for TCM Cardiology, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, 100091, China.
Jing CuiNational Clinical Research Center for TCM Cardiology, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, 100091, China.
Mengmeng ZhuNational Clinical Research Center for TCM Cardiology, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, 100091, China.
Wenting WangNational Clinical Research Center for TCM Cardiology, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, 100091, China.
Keji ChenNational Clinical Research Center for TCM Cardiology, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, 100091, China.
Luqi HuangChina Academy of Chinese Medical Sciences, Beijing, 100078, China.
Yue LiuNational Clinical Research Center for TCM Cardiology, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, 100091, China. liuyueheart@hotmail.com.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNXiyuan Hospital · CN

Funding

National Outstanding Youth Foundation of China 82022076
6 · The paper itself

Abstract

backgroundDiabetes is a predominant driver of coronary artery disease worldwide. This study aims to unravel the distinct characteristics of oral and gut microbiota in diabetic coronary heart disease (DCHD). Simultaneously, we aim to establish a causal link between the diabetes-driven oral-gut microbiota axis and increased susceptibility to diabetic myocardial ischemia-reperfusion injury (MIRI).

methodsWe comprehensively investigated the microbial landscape in the oral and gut microbiota in DCHD using a discovery cohort (n = 183) and a validation chohort (n = 68). Systematically obtained oral (tongue-coating) and fecal specimens were subjected to metagenomic sequencing and qPCR analysis, respectively, to holistically characterize the microbial consortia. Next, we induced diabetic MIRI by administering streptozotocin to C57BL/6 mice and subsequently investigated the potential mechanisms of the oral-gut microbiota axis through antibiotic pre-treatment followed by gavage with specific bacterial strains (Fusobacterium nucleatum or fecal microbiota from DCHD patients) to C57BL/6 mice.

resultsSpecific microbial signatures such as oral Fusobacterium nucleatum and gut Lactobacillus, Eubacterium, and Roseburia faecis, were identified as potential microbial biomarkers in DCHD. We further validated that oral Fusobacterium nucleatum and gut Lactobacillus are increased in DCHD patients, with a positive correlation between the two. Experimental evidence revealed that in hyperglycemic mice, augmented Fusobacterium nucleatum levels in the oral cavity were accompanied by an imbalance in the oral-gut axis, characterized by an increased coexistence of Fusobacterium nucleatum and Lactobacillus, along with elevated cardiac miRNA-21 and a greater extent of myocardial damage indicated by TTC, HE, TUNEL staining, all of which contributed to exacerbated MIRI.

conclusionOur findings not only uncover dysregulation of the oral-gut microbiota axis in diabetes patients but also highlight the pivotal intermediary role of the increased abundance of oral F. nucleatum and gut Lactobacillus in exacerbating MIRI. Targeting the oral-gut microbiota axis emerges as a potent strategy for preventing and treating DCHD. Oral-gut microbial transmission constitutes an intermediate mechanism by which diabetes influences myocardial injury, offering new insights into preventing acute events in diabetic patients with coronary heart disease.

Indexed as

Coronary Artery DiseaseDiabetes MellitusGastrointestinal MicrobiomeAnimalsFusobacterium nucleatumHumansMiceMice, Inbred C57BLDiabetic coronary heart diseaseFusobacterium nucleatumMyocardial ischemia–reperfusion injuryOral-gut axisOral microbiota

Identifiers

PMID38581039
PMCPMC10998415
OpenAlexW4393999178

What OpenQuestion holds

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LicenceCC BY
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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.