Noncoding RNA profiling in omentum adipose tissue from obese patients and the identification of novel metabolic biomarkers
Zhang Y., Chen A., Lu S., Liu D., Xuan X., Lei X.
Prospective Study, published in Front Genet (2025) — summary generated from the PubMed abstract.
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
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
- Front Genet (2025)
- Reported sample size
- —
- Source database
- Europe PMC
- PMID
- 39981261
- PMCID
- PMC11839770
- DOI
- 10.3389/fgene.2025.1533637
- Citations
- 2
Abstract (original English)
Background Obesity, a prevalent metabolic disorder, is linked to perturbations in the balance of gene expression regulation. Noncoding RNAs (ncRNAs), including long noncoding RNAs (lncRNAs), circular RNAs (circRNAs), and microRNAs (miRNAs), play pivotal roles in regulating gene expression. The aim of this study was to identify additional ncRNA candidates that are implicated in obesity, elucidating their potential as key regulators of the pathogenesis of obesity. Methods We identified distinct ncRNA expression profiles in omental adipose tissue in obese and healthy subjects through comprehensive whole-transcriptome sequencing. Subsequent analyses included functional annotation with GO and KEGG pathway mapping, validation via real-time quantitative polymerase chain reaction (qRT‒PCR), the exploration of protein‒protein interactions (PPIs), and the identification of key regulatory genes through network analysis. Results The results indicated that, compared with those in healthy individuals, various lncRNAs, circRNAs, and miRNAs were significantly differentially expressed in obese subjects. Further verifications of top changed gene expressions proved the most genes' consistence with RNA-sequencing including 11 lncRNAs and 4 circRNAs. Gene network analysis highlighted the most significant features associated with metabolic pathways, specifically ENST00000605862, ENST00000558885, and
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.
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