Evidence map›Paper›PMID 41432724›Full record

ArticlemSystems2026

Microbial metabolites associated with healthy lifestyles in relation to metabolic syndrome and vascular health: a cross-sectional study.

Zhuoyu Zhang, Bingqi Ye, Jialin He, Li Xiang, Siqi Li, Jiaqi Zhao, Wanlan Chen, Qi Zhang, Wanying Zhao, Jialu Yang and 4 more

Abstract read
In one paragraph

Article in mSystems, 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

14 authors.

Zhuoyu ZhangGuangdong Provincial Key Laboratory of Food, Nutrition and Health, and Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China.ORCID 0009-0006-5288-9325
Bingqi YeGuangdong Provincial Key Laboratory of Food, Nutrition and Health, and Department of Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Jialin HeGuangdong Provincial Key Laboratory of Food, Nutrition and Health, and Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Li XiangGuangdong Provincial Key Laboratory of Food, Nutrition and Health, and Department of Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Siqi LiGuangdong Provincial Key Laboratory of Food, Nutrition and Health, and Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Jiaqi ZhaoGuangdong Provincial Key Laboratory of Food, Nutrition and Health, and Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Wanlan ChenGuangdong Provincial Key Laboratory of Food, Nutrition and Health, and Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Qi ZhangGuangdong Provincial Key Laboratory of Food, Nutrition and Health, and Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Wanying ZhaoGuangdong Provincial Key Laboratory of Food, Nutrition and Health, and Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Jialu YangGuangdong Provincial Key Laboratory of Food, Nutrition and Health, and Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Yi LiGuangdong Provincial Key Laboratory of Food, Nutrition and Health, and Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Jingmeng JuGuangdong Provincial Key Laboratory of Food, Nutrition and Health, and Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Yan LiuGuangdong Provincial Key Laboratory of Food, Nutrition and Health, and Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China.ORCID 0000-0001-6358-4056
Min XiaGuangdong Provincial Key Laboratory of Food, Nutrition and Health, and Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China.ORCID 0000-0001-5330-6466

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lifestyle behaviors influence the risk of metabolic syndrome (MetS) and affect vascular health. However, the interactions between gut microbiota and lifestyle behaviors in relation to MetS, as well as the specific microbial taxa and metabolites involved, remain unclear. Here, we aimed to investigate the associations among healthy lifestyle behaviors, gut microbiota, and MetS and to explore the potential mediating roles of microbially derived metabolites in these associations. A total of 1,342 participants with complete assessments of the Healthy Lifestyle Score (HLS), MetS, and vascular health were enrolled. Fecal samples were collected and subjected to metagenomic sequencing. Host genetic data were obtained using a high-density genotyping array, and plasma metabolites were quantified by liquid chromatography-mass spectrometry. Using generalized linear models, we found that increased abundances of IMPORTANCE: Metabolic syndrome raises the risk of heart disease and diabetes, yet practical levers to prevent it remain limited. We show that everyday healthy habits align with a gut microbial "signature" linked to better vascular health and lower metabolic risk. Using metagenomics, metabolomics, and genetic causal analyses, we identify specific bacteria (

Indexed as

Gastrointestinal MicrobiomeHealthy LifestyleMetabolic SyndromeAdultAgedBacteriaCross-Sectional StudiesFecesFemaleHumansMaleMetabolomeMiddle Agedbetainecinnamoylglycinegut microbiotahealthy lifestyleMendelian randomizationmetabolic syndromevascular health

Identifiers

PMID41432724
PMCPMC12911354

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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.