Obesity

Circulating miRNAs Detect High vs Low Visceral Adipose Tissue Inflammation in Patients Living With Obesity

J Clin Endocrinol MetabPublished Diagnostic accuracy study

Authors' conclusion

Circ-miRs that identify patients with low- vs high-VAT inflammation constitute a putative tool to improve personalized care of patients with obesity.

Study context

Population
Patients living with obesity undergoing bariatric surgery; Visceral adipose tissue (VAT) inflammation classified low/high by an expression score from TNFA, IL6 and CCL2 mRNA levels
Participants
35 vs 51
Comparison
Circulating miRNAs combined with homeostatic model assessment of insulin resistance (HOMA-IR) to discriminate high vs low VAT inflammation
  • Discoveryn = 35
  • Validationn = 51
Outcome
Discriminative power of differentially expressed circ-miRs to detect low/high VAT inflammation (ROC-AUC)
Methodological detailsdiscovery and validation cohorts
  • Discovery and validation cohorts

Performance

As reported in the abstract

ROC-AUC of circ-miRs 181b-5p, 1306-3p and 3138 combined with HOMA-IR for high vs low VAT inflammation
Test or modelAUC
Discovery0.951 (95% CI, 0.865-1)
Validation0.808 (95% CI, 0.654-0.963)

AUC

Discovery0.951 (95% CI, 0.865-1)
Validation0.808 (95% CI, 0.654-0.963)

Further findings

circ-miR screening in discovery cohort

circ-miRs associated with high-VAT inflammation (Mann-Whitney)
53 out of 263 (20%)
Differentially expressed by Deseq2
12 (12/53 = 23%)
Discriminated high vs low VAT inflammation with receiver operating characteristic-area under the curve (ROC-AUC) >0.8
6
Differentially abundant in all 3 approaches
5
Unaffected by hemolysis and validated in independent cohort
3

Predicted target genes

Enriched in pathways of insulin and inflammatory signaling, circadian entrainment and cellular senescence

Original publication

Circulating miRNAs Detect High vs Low Visceral Adipose Tissue Inflammation in Patients Living With Obesity. J Clin Endocrinol Metab. Published 15 September 2023. doi:10.1210/clinem/dgad550

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