Evidence map›Paper›PMID 40822952›Full record

ArticleFrontiers in endocrinology2025

Integrated proteomic and metabolomic profiling identifies distinct molecular signatures and metabolic pathways associated with obesity and potential targets for anti-obesity therapies.

Yi Li, Huawu Yang, Xinpeng Zhang, Xingyu He, Anke Liuli, Rui Li, Xingyu Han, Yongmei Li, Pan Gao

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 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.

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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

9 authors.

Yi Li *Department of Radiology, The Third People's Hospital of Chengdu, Chengdu, Sichuan, China.
Huawu Yang *The Center of Obesity and Metabolic Diseases, Department of General Surgery, The Third People's Hospital of Chengdu, Chengdu, Sichuan, China.
Xinpeng Zhang *General Surgery Day Ward, Department of General Surgery, The Third People's Hospital of Chengdu, Chengdu, Sichuan, China.
Xingyu HeCollege of Life Science and Engineering, Southwest Jiaotong University, Chengdu, Sichuan, China.
Anke LiuliCollege of Life Science and Engineering, Southwest Jiaotong University, Chengdu, Sichuan, China.
Rui LiSchool of Basic Medical Sciences, Southwest Medical University, Luzhou, Sichuan, China.
Xingyu HanCollege of Life Science and Engineering, Southwest Jiaotong University, Chengdu, Sichuan, China.
Yongmei LiDepartment of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Pan GaoObesity and Metabolism Medicine-Engineering Integration Laboratory, Department of General Surgery, The Third People's Hospital of Chengdu, Chengdu, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Adipose tissue remodeling induced by bariatric surgery plays a pivotal role in promoting weight loss and metabolic improvement. However, the underlying molecular mechanisms, particularly protein-metabolite regulatory networks, remain poorly understood. This integrative proteomic and metabolomic study identifies key pathway alterations and molecular signatures associated with metabolic phenotypes, offering novel mechanistic insights into the therapeutic efficacy of bariatric surgery. Methods: Visceral adipose tissue samples were analyzed using label-free DIA quantitative proteomics and LC-MS/MS metabolomics. Proteomic and metabolomic data were processed with MaxQuant software and XCMS R package, respectively. Results: Proteomic and metabolomic analyses were performed on visceral adipose tissue from 10 obese patients undergoing sleeve gastrectomy and 10 controls. Proteomic profiling quantified identified 135 differentially expressed proteins (57 upregulated, 78 downregulated), with PHACTR2 and PLIN2 upregulated in obesity and ADAR down-regulated in obesity. Enrichment analyses indicated disruptions in lipid droplet formation, muscle processes, and protein autophosphorylation, with KRT1/MYH9 and NF1/ATR identified as hub proteins. Metabolomics revealed 191 differential metabolites (110 upregulated, 81 downregulated), with 4-Vinylcyclohexene positively correlated with BMI and asparagine-betaxanthin negatively correlated. KEGG analysis showed disturbances in purine/pyrimidine metabolism, AMPK signaling, and cortisol biosynthesis. Integrated protein-metabolite network analysis identified OSBPL10, CUL2, and PRTN3 as potential regulators of lipid metabolism and insulin resistance, offering insights into obesity-associated metabolic dysfunction. Conclusions: This study integrated proteomic and metabolomic data from visceral adipose tissue obtained through sleeve gastrectomy, identifying obesity-related functional pathways and molecular signatures linked to metabolic phenotypes, highlighting the value of multi-omics in understanding adipose tissue remodeling and postoperative metabolic improvement.

Indexed as

Intra-Abdominal FatMetabolic Networks and PathwaysMetabolomicsObesityProteomicsAdultBariatric SurgeryFemaleHumansMaleMiddle Agedadipose tissuemetabolomicobesityproteomicsignature

Identifiers

PMID40822952
PMCPMC12350109

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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 OpenQuestion graph.