Evidence map›Paper›PMID 40413611›Full record

ArticleClinical and translational medicine2025

Microbial metabolism mediates the deteriorative effects of sedentary behaviour on insulin resistance.

Jingmeng Ju, Jialin He, Bingqi Ye, Siqi Li, Jiaqi Zhao, Wanlan Chen, Qi Zhang, Wanying Zhao, Jialu Yang, Ludi Liu and 3 more

Abstract read
In one paragraph

Article in Clinical and 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
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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

13 authors.

Jingmeng JuGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Jialin HeGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Bingqi YeGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Siqi LiGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Jiaqi ZhaoGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Wanlan ChenGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Qi ZhangGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Wanying ZhaoGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Jialu YangGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Ludi LiuGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Yi LiGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Min XiaGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.
Yan LiuGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, P.R. China.ORCID 0000-0001-6358-4056

Funding

Distinguished Young Scholars of the National Natural Science Foundation of China 21HAA01094Distinguished Young Scholars of the National Natural Science Foundation of China OverseasGuangzhou Science and Technology Project 2024A04J6477Key Project of National Natural Science Foundation of China 82330105National Key Research and Development Program of China 2023YFC3606300
6 · The paper itself

Abstract

backgroundProlonged sedentary time is a strong risk factor for insulin resistance. Recent evidence indicates that gut microbiota may influence the regulation of insulin sensitivity and demonstrates a distinct profile between sedentary and physically active individuals. However, whether and how microbial metabolism mediates the progression of insulin resistance induced by prolonged sedentary time remains unclear.

methods560 male participants without hypoglycaemic therapy were included, and insulin resistance was evaluated using the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR). The gut microbiota was identified through metagenomics, host genetic data were obtained using a genotyping array, and plasma metabolites were quantified by liquid chromatography mass spectrometry.

resultsA panel of 15 sedentary-related species and 38 sedentary-associated metabolic capacities accounted for 31.68% and 21.48% of the sedentary time-related variation in HOMA-IR, respectively. Specifically, decreased Roseburia sp. CAG:471, Intestinibacter bartlettii, and Firmicutes bacterium CAG:83, but increased Bacteroides xylanisolvens related to longer sedentary time, were causally linked to the development of insulin resistance. Furthermore, integrative analysis with metabolomics identified reduced L-citrulline and L-serine, resulting from a suppression of arginine biosynthesis as key microbial effectors linking longer sedentary time to enhanced insulin resistance.

conclusionsIn summary, our findings provide insights into the mediating role of gut microbiota on the progression of insulin resistance induced by excessive sedentary time, and highlight the possibility of counteracting the detrimental effect of prolonged sedentary time on insulin resistance by microbiota-modifying interventions. KEY POINTS: Prolonged sedentary time leads to a depletion of Roseburia sp. CAG:471 and Firmicutes bacterium CAG:83, and suppresses arginine biosynthesis. Decreased L-citrulline and L-serine function as key microbial effectors mediating the adverse effect of sedentary time on insulin sensitivity. Targeting gut microbiota holds promise to combat insulin resistance induced by excessive sedentary time.

Indexed as

Gastrointestinal MicrobiomeInsulin ResistanceSedentary BehaviorAdultHumansMalegut microbiotainsulin resistanceMendelian randomisationsedentary behaviour

Identifiers

PMID40413611
PMCPMC12103651

What Socratic 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 Socratic graph.