Evidence map›Paper›PMID 41675714›Full record

ArticleiMetaOmics2025

Multi-omics reveals different signatures of obesity-prone and obesity-resistant mice.

Congcong Wang, Jinhua Lin, Meng Duan, Jialing He, Simayi Halizere, Ningxin Chen, Xinyu Chen, Ye Jiao, Wei He, Kenneth A Dyar and 2 more

Abstract read
In one paragraph

Article in iMetaOmics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Cross-Study Meta-Analysis of Blood Transcriptomes in Type 2 Diabetes.International journal of molecular sciences · 2025
    Pooled it
  2. Trial
  3. Article
  4. Article
  5. 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

12 authors.

Congcong WangDepartment of Nutrition and Food Hygiene, Children's Hospital Zhejiang University School of Medicine, National Clinical Research Center for Child Health Hangzhou China.
Jinhua LinDepartment of Nutrition and Food Hygiene, Children's Hospital Zhejiang University School of Medicine, National Clinical Research Center for Child Health Hangzhou China.
Meng DuanDepartment of Nutrition and Food Hygiene, Children's Hospital Zhejiang University School of Medicine, National Clinical Research Center for Child Health Hangzhou China.
Jialing HeDepartment of Nutrition and Food Hygiene, Children's Hospital Zhejiang University School of Medicine, National Clinical Research Center for Child Health Hangzhou China.
Simayi HalizereDepartment of Nutrition and Food Hygiene, Children's Hospital Zhejiang University School of Medicine, National Clinical Research Center for Child Health Hangzhou China.
Ningxin ChenDepartment of Nutrition and Food Hygiene, Children's Hospital Zhejiang University School of Medicine, National Clinical Research Center for Child Health Hangzhou China.
Xinyu ChenDepartment of Nutrition and Food Hygiene, Children's Hospital Zhejiang University School of Medicine, National Clinical Research Center for Child Health Hangzhou China.
Ye JiaoDepartment of Nutrition and Food Hygiene, Children's Hospital Zhejiang University School of Medicine, National Clinical Research Center for Child Health Hangzhou China.
Wei HeDepartment of Nutrition and Food Hygiene, Children's Hospital Zhejiang University School of Medicine, National Clinical Research Center for Child Health Hangzhou China.
Kenneth A DyarMetabolic Physiology, Institute for Diabetes and Cancer, Helmholtz Diabetes Center, Helmholtz Zentrum München, German Research Center for Environmental Health Neuherberg Germany.
Fei YangDepartment of Nutrition and Food Hygiene, Children's Hospital Zhejiang University School of Medicine, National Clinical Research Center for Child Health Hangzhou China.
Shankuan ZhuDepartment of Nutrition and Food Hygiene, Children's Hospital Zhejiang University School of Medicine, National Clinical Research Center for Child Health Hangzhou China.ORCID 0000-0002-9509-7364

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Obesity-prone (OP) and obesity-resistant (OR) individuals demonstrate significant metabolic differences, potentially influenced by variations in the gut microbiome. However, the influence of host-microbiota interactions on obesity susceptibility remains unknown. We performed an integrative multi-omics approach to explore microbial, metabolic, and genetic differences in high-fat diet (HFD)-fed OP and OR mice, with additional analyses of gut microbiota variations in humans. In OP mice, the dynamic gut microbiota was characterized by a stable presence of

Indexed as

high‐fat dietmetabolomicsmicrobiotaobesitytranscriptome

Identifiers

PMID41675714
PMCPMC12806275

What OpenQuestion holds

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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.