Evidence map›Paper›PMID 39789419›Full record

ArticleJournal of cellular and molecular medicine2025

Genetic Commonalities Between Metabolic Syndrome and Rheumatic Diseases Through Disease Interactome Modules.

Yinli Shi, Shuang Guan, Xi Liu, Hongjun Zhai, Yingying Zhang, Jun Liu, Weibin Yang, Zhong Wang

Abstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. 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

8 authors.

Yinli ShiInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Shuang GuanInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Xi LiuInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Hongjun ZhaiChengdu University of Traditional Chinese Medicine Key Laboratory of Systematic Research of Distinctive Chinese Medicine Resources in Southwest China, Chengdu, China.
Yingying ZhangDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Jun LiuInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Weibin YangGraduate School of China Academy of Chinese Medical Sciences, Beijing, China.
Zhong WangInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.ORCID 0000-0003-0975-9251

Funding

China Academy of Chinese Medical SciencesScientific and Technological Innovation Project of China Academy of Chinese Medical Sciences CI2023C063YLLthe National Natural Science Foundation of China 82474682
6 · The paper itself

Abstract

This study aims to elucidate the potential genetic commonalities between metabolic syndrome (MetS) and rheumatic diseases through a disease interactome network, according to publicly available large-scale genome-wide association studies (GWAS). The analysis included linkage disequilibrium score regression analysis, cross trait meta-analysis and colocalisation analysis to identify common genetic overlap. Using modular partitioning, the network-based association between the two disease proteins in the protein-protein interaction set was divided and quantified. Clinical samples from public databases were used to confirm the mapped genes. Mendelian randomisation analyses were conducted using genetic instrumental variables for causal inference. MetS and rheumatoid arthritis (RA), ankylosing spondylitis (AS), systemic lupus erythematosus (SLE), Sjogren's syndrome (SS) and their primary module networks shared topological overlap and genetic correlation. Functional analysis highlighted the significance of these shared targets in processes such as a diverse array of metabolic pathways involving glucose, lipids, energy, protein transport, inflammatory response, autophagy and cytokine regulation, elucidating the pathways through which MetS intersects with rheumatic diseases. Causal associations were determined between MetS phenotypes and rheumatic diseases. The persistence of MetS effects on rheumatic diseases remained evident even after adjusting for alcohol consumption and smoking. We have highlighted specific genetic associations between MetS and rheumatic diseases. Several genes (e.g., PRRC2A, PSMB8, BAG6, GPSM3, PBX2, etc.) have been identified with molecular commonalities in MetS and RA, AS, SLE and SS, which may serve as potential targets for shared treatments.

Indexed as

Genetic Predisposition to DiseaseGenome-Wide Association StudyMetabolic SyndromeRheumatic DiseasesGene Regulatory NetworksHumansLinkage DisequilibriumMendelian Randomization AnalysisPolymorphism, Single NucleotideProtein Interaction MapsSpondylitis, Ankylosingbioinformaticsdisease interactomedisease moduleMendelian randomisation studymetabolic syndromerheumatic diseasestranslational informatics

Identifiers

PMID39789419
PMCPMC11717667

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.