Evidence map›Paper›PMID 41659099›Full record

ArticleReviews in cardiovascular medicine2026

Causal Associations Between Gut Microbes and Heart Failure Across Multiple Etiologies: A Mendelian Randomization Study.

Xinming Xu, Safraz Anwar, Yunpeng Shang, Xiaogang Guo, Xiao Cui

Abstract read
In one paragraph

Article in Reviews in cardiovascular medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Xinming XuDepartment of Cardiology, The First Affiliated Hospital, Zhejiang University School of Medicine, 311121 Hangzhou, Zhejiang, China.
Safraz AnwarDepartment of Cardiology, The First Affiliated Hospital, Zhejiang University School of Medicine, 311121 Hangzhou, Zhejiang, China.
Yunpeng ShangDepartment of Cardiology, The First Affiliated Hospital, Zhejiang University School of Medicine, 311121 Hangzhou, Zhejiang, China.
Xiaogang GuoDepartment of Cardiology, The First Affiliated Hospital, Zhejiang University School of Medicine, 311121 Hangzhou, Zhejiang, China.ORCID https://orcid.org/0000-0001-6754-1432
Xiao CuiDepartment of Cardiology, The First Affiliated Hospital, Zhejiang University School of Medicine, 311121 Hangzhou, Zhejiang, China.ORCID https://orcid.org/0009-0000-9302-9774

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Gut microbiota are associated with heart failure (HF); however, the causal relationship between gut microbial communities and HF of varying etiologies remains incompletely established. Methods: This study leveraged two-sample Mendelian randomization (MR) to investigate whether genetically determined gut microbiota features causally influence HF and its related subtypes. Instrumental variables (IVs) for gut microbiota were derived from a large-scale, genome-wide association study (GWAS) of microbial traits conducted by the MiBioGen consortium, which included 18,340 individuals. Summary statistics for HF and its subtypes were extracted from the FinnGen Release 7, encompassing 19,350 all-cause HF cases and 288,996 controls. The Wald ratio and inverse-variance weighted analyses were applied to calculate the causal estimates. Results: A total of 19 single-nucleotide polymorphisms (SNPs) corresponding to 18 gut microbial taxa were selected as IVs. A significant inverse causal association was identified between the family Conclusions: Genetically predicted enrichment of

Indexed as

gut microbesheart failurehypertensive heart diseasesPeptostreptococcaceae

Identifiers

PMID41659099
PMCPMC12873699

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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.