Level C· Early human research exploring benefitsProspective StudyEurope PMC

In silico and functional analysis identifies key gene networks and novel gene candidates in obesity-linked human visceral fat

Wang L., Seshachalam PV., Chua R., Zhou H., Lei S., Ghosh S.

Prospective Study on Type 2 Diabetes, published in Obesity (Silver Spring) (2024) — summary generated from the PubMed abstract.

Open my reading list
Level C· Early human research exploring benefitsEvidence level of this study

Early human evidence such as case series or small samples is exploring possible benefits.

  • Level A · Stronger Clinical Evidence
  • Level B · Emerging clinical evidence with positive signals
  • Level C · Early human research exploring benefits
  • Level D · Scientific groundwork from lab and animal studies
  • Emerging · Emerging topic under active research
Read the A–D evidence level guide

This page is generated from the PubMed record. The Thai description is an automated summary of bibliographic fields and the abstract, not a full translation, and is not medical advice.

Study type
Prospective Study
Journal
Obesity (Silver Spring) (2024)
Reported sample size
—
Source database
Europe PMC
PMID
39497634
PMCID
PMC11548800
DOI
10.1002/oby.24161
Citations
2

Abstract (original English)

Objective Visceral adiposity is associated with increased proinflammatory activity, insulin resistance, diabetes risk, and mortality rate. Numerous individual genes have been associated with obesity, but studies investigating gene regulatory networks in human visceral obesity have been lacking. Methods We analyzed gene regulatory networks in human visceral adipose tissue (VAT) from 48 and 11 Chinese patients with and without obesity, respectively, using gene coexpression and gene regulatory network construction from RNA-sequencing data. We also conducted RNA interference-based functional tests on selected genes for effects on adipocyte differentiation. Results A scale-free gene coexpression network was constructed from 360 differentially expressed genes between VAT samples from patients with and without obesity (absolute log fold change > 1, false discovery rate [FDR] 0.8. Gene regulatory network analysis identified candidate transcription factors associated with differentially expressed genes. A total of 15 subnetworks (communities) displayed altered connectivity patterns between obesity and nonobesity networks. Genes in proinflammatory pathways showed increased network connectivity in VAT samples with obesity, whereas the oxidative phosphorylation pathway displayed reduced connectivity (enrichment FDR Conclusions This approach highlights the network architecture in human obes

What this study does not prove

  • • This study does not prove SVF is an approved treatment or a replacement for standard care.

Evidence level

Early human evidence such as case series or small samples is exploring possible benefits.

How we grade evidence
AdipocytesHumansObesityTranscription FactorsRNA InterferenceComputer SimulationAdultMiddle AgedFemaleMale

Browse all related research

Filter the research library by this study's title keywords, author, or publication year.

Related research