Evidence mapPaperPMID 40371613Full record

ArticleJournal of the American Heart Association2025

Potential Modulatory Roles of Gut Microbiota and Metabolites in the Associations of Macronutrient-to-Physical Activity Ratios With Dyslipidemia.

Menghan Wang, Guoqing Ma, Yunfeng Li, Junqi Li, Jiawen Xie, Juan He, Chen He, Yifei He, Kaizhen Jia, Xinran Feng and 4 more

Abstract read
In one paragraph

Article in Journal of the American Heart Association, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

14 authors.

Menghan WangKey Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute Xi'an Jiaotong University Health Science Center Xi'an Shaanxi China.ORCID 0009-0005-5578-6690
Guoqing MaKey Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute Xi'an Jiaotong University Health Science Center Xi'an Shaanxi China.
Yunfeng LiKey Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute Xi'an Jiaotong University Health Science Center Xi'an Shaanxi China.
Junqi LiKey Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute Xi'an Jiaotong University Health Science Center Xi'an Shaanxi China.ORCID 0009-0003-1916-1832
Jiawen XieKey Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute Xi'an Jiaotong University Health Science Center Xi'an Shaanxi China.
Juan HeKey Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute Xi'an Jiaotong University Health Science Center Xi'an Shaanxi China.
Chen HeKey Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute Xi'an Jiaotong University Health Science Center Xi'an Shaanxi China.
Yifei HeKey Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute Xi'an Jiaotong University Health Science Center Xi'an Shaanxi China.ORCID 0009-0004-3522-2137
Kaizhen JiaKey Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute Xi'an Jiaotong University Health Science Center Xi'an Shaanxi China.ORCID 0009-0000-7614-4738
Xinran FengKey Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute Xi'an Jiaotong University Health Science Center Xi'an Shaanxi China.
Tian TianKey Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute Xi'an Jiaotong University Health Science Center Xi'an Shaanxi China.
Hongbao LiDepartment of Physiology and Pathophysiology Xi'an Jiaotong University School of Basic Medical Sciences Xi'an China.ORCID 0000-0002-1600-9590
Xia LiaoDepartment of Nutrition, the First Affiliated Hospital Xi'an Jiaotong University Xi'an China.ORCID 0000-0002-2684-8232
Xin LiuKey Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute Xi'an Jiaotong University Health Science Center Xi'an Shaanxi China.ORCID 0000-0001-5105-0532

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLifestyle factors toward diet and physical activity (PA) may directly influence the pathophysiology of dyslipidemia. However, the associations of the specific macronutrient-to-PA ratio with dyslipidemia, and the underlying mechanisms regarding gut microbiota and metabolites, remain largely unexplored.

methodsDietary and PA information from 273 participants with or at risk of metabolic syndrome was collected via a food frequency questionnaire and the International Physical Activity Questionnaire. Gut microbial genera and fecal metabolites were profiled through 16S rRNA sequencing and untargeted LC-MS metabolomics, respectively. Machine-learning algorithms were applied to identify gut microbiome features of macronutrient-to-PA ratios and to construct microbiome risk score.

resultsHigher macronutrient-to-PA ratios, especially for high saturated fatty acid intake, were associated with increased risks of dyslipidemia, with adjusted odds ratio (95% CIs) of 2.87 (1.41-5.99) for hypercholesteremia, 2.21 (1.11-4.48) for hypertriglyceridemia, and 2.52 (1.26-5.16) for high low-density lipoprotein cholesterol. Microbiome risk scores were significantly associated with elevated levels of total cholesterol, triglycerides, and low-density lipoprotein cholesterol. Additionally, for each macronutrient-to-PA ratio, a core group of gut microbial genera were identified (eg,

conclusionsThis study identified varied associations between macronutrient-to-PA ratios and dyslipidemia and depicted the potential modulatory roles of gut microbiota and fecal metabolites.

Indexed as

DyslipidemiasExerciseGastrointestinal MicrobiomeNutrientsAdultAgedDietFecesFemaleHumansMaleMetabolomicsMiddle AgedRisk FactorsNutrientsdietary macronutrientdyslipidemiagut microbiotametabolomephysical activity

Identifiers

PMID40371613
PMCPMC12184610

What Socratic holds

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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.