Evidence map›Paper›PMID 31594827›Full record

ArticlemSystems2019

Distinct Gut Microbiota Induced by Different Fat-to-Sugar-Ratio High-Energy Diets Share Similar Pro-obesity Genetic and Metabolite Profiles in Prediabetic Mice.

Kai Shan, Hongyan Qu, Keru Zhou, Liangfang Wang, Congmin Zhu, Haiqin Chen, Zhennan Gu, Jing Cui, Guoling Fu, Jiaqi Li and 5 more

Open access · goldAbstract read
In one paragraph

Article in mSystems, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

21 citing papers in PubMed, 33 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Gut Microbiota-Derived Metabolites Orchestrate Metabolic Reprogramming in Diabetic Cardiomyopathy: Mechanisms and Therapeutic Frontiers.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2025
    Review
  5. Fat-rich diet promotes microbiome-dependent ATP synthesis in sheep model.Journal of animal science and biotechnology · 2025
    Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. 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

15 authors at 2 institutions in 1 country.

Kai ShanWuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu Province, China.
Hongyan QuWuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu Province, China.
Keru ZhouSchool of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu Province, China.
Liangfang WangSchool of Science, Jiangnan University, Wuxi, Jiangsu Province, China.
Congmin ZhuMOE Key Laboratory of Bioinformatics and Bioinformatics Division, Center for Synthetic & Systems Biology, TNLIST/Department of Automation, Tsinghua University, Beijing, China.
Haiqin ChenSchool of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu Province, China.
Zhennan GuSchool of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu Province, China.
Jing CuiWuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu Province, China.
Guoling FuWuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu Province, China.
Jiaqi LiWuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu Province, China.
Heyan ChenWuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu Province, China.
Rong WangWuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu Province, China.
Yumin QiWuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu Province, China.
Wei ChenSchool of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu Province, China.
Yong Q ChenWuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu Province, China yqchen@jiangnan.edu.cn.
Jiangnan University · CNTsinghua University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gut microbiota play important roles in host metabolism, especially in diabetes. However, why different diets lead to similar diabetic states despite being associated with different microbiota is not clear. Mice were fed two high-energy diets (HED) with the same energy density but different fat-to-sugar ratios to determine the associations between the microbiota and early-stage metabolic syndrome. The two diets resulted in different microbiota but similar diabetic states. Interestingly, the microbial gene profiles were not significantly different, and many common metabolites were identified, including l-aspartic acid, cholestan-3-ol (5β, 3α), and campesterol, which have been associated with lipogenesis and inflammation. Our study suggests that different metabolic-syndrome-inducing diets may result in different microbiota but similar microbiomes and metabolomes. This suggests that the metagenome and metabolome are crucial for the prognosis and pathogenesis of obesity and metabolic syndrome.

Indexed as

gut microbiotahigh-energy dietmetabolomemetagenomeprediabetes

Identifiers

PMID31594827
PMCPMC6787563
OpenAlexW2979845605

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.