Evidence map›Paper›PMID 40507148›Full record

ArticleNutrients2025

Integrating Metabolomics and Gut Microbiota to Identify Key Biomarkers and Regulatory Pathways Underlying Metabolic Heterogeneity in Childhood Obesity.

Zhiwei Xia, Yan Li, Jiyong Yin, Zhaolong Gong, Jing Sun, Shi Shen, Yi Yang, Tingting Liu, Liyuan Wang, Junsheng Huo

Abstract read
In one paragraph

Article in Nutrients, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
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  5. Review
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

10 authors.

Zhiwei XiaNHC Key Laboratory of Public Nutrition and Health, National Institute of Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China.ORCID 0000-0001-6909-8323
Yan LiNHC Key Laboratory of Public Nutrition and Health, National Institute of Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
Jiyong YinNHC Key Laboratory of Public Nutrition and Health, National Institute of Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
Zhaolong GongNHC Key Laboratory of Public Nutrition and Health, National Institute of Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
Jing SunNHC Key Laboratory of Public Nutrition and Health, National Institute of Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
Shi ShenNHC Key Laboratory of Public Nutrition and Health, National Institute of Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China.ORCID 0000-0002-9130-3984
Yi YangKey Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing Center for Disease Control and Prevention, Beijing 100013, China.ORCID 0000-0003-1160-3627
Tingting LiuNHC Key Laboratory of Public Nutrition and Health, National Institute of Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
Liyuan WangNHC Key Laboratory of Public Nutrition and Health, National Institute of Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
Junsheng HuoNHC Key Laboratory of Public Nutrition and Health, National Institute of Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China.ORCID 0000-0002-9643-1897

Funding

the Public Health Emergency Project Nutrition Health and Healthy Diet Campaign Grant No. 102393220020070000012
6 · The paper itself

Abstract

BACKGROUND/

objectivesIndividuals with childhood obesity exhibit significant metabolic heterogeneity, necessitating precise biomarkers for risk stratification and assessment. This multi-omics investigation characterizes metabolic and microbial signatures underlying divergent metabolic phenotypes in the context of pediatric obesity.

methodsWe analyzed 285 Chinese children (5-7 years) stratified into five groups: wasting (WAS,

resultsAnalysis identified 225 differential metabolites and 12 bacterial genera. The proportion of steroids and their derivatives among differential metabolites in the MUO/MHO group was significantly lower than that in the OVOB/NOR and OVOB/WAS groups (2.12% vs. 7.9-14.1%). MUO displayed elevated C17 sphinganine and LysoPC (O-18:0) levels but reduced PI (16:0/14:1) levels. In contrast, OVOB showed upregulated glycerol phospholipids (LPCs and PSs) and downregulated PE species (e.g., PE(16:0/16:0)) as well as gut microbiota dysbiosis characterized by a higher Firmicutes/Bacteroidetes (F/B) ratio (2.07 vs. 1.24 in controls,

conclusionsWe identified distinct lipid disruptions characterizing obesity subtypes, including steroid/terpene deficits and sphingolipid/ether lipid dysregulation in the MUO/MHO groups as well as phospholipid imbalance (↑LPC/PS↓PE) in the OVOB/NOR groups. The gut microbiota exhibited a profile characterized by low diversity, an increased F/B ratio, and a reduced abundance of SCFA-producing genera. These findings suggest potential biomarkers for childhood obesity stratification, though further validation is warranted.

Indexed as

Gastrointestinal MicrobiomeMetabolomicsPediatric ObesityBiomarkersChildChild, PreschoolChinaFemaleHumansMaleRNA, Ribosomal, 16SBiomarkersRNA, Ribosomal, 16Schildhood obesitygut microbiotametabolic heterogeneitymetabolomicsmulti-omics

Identifiers

PMID40507148
PMCPMC12158115

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.