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- Title
Serum microRNA panels predict bariatric surgery outcomes.
- Authors
Yeh, Jih‐Kai; Chen, Chia‐Chun; Liu, Keng‐Hau; Peng, Chen‐Ching; Lin, Tien‐An; Chang, Yu‐Sun; Wen, Ming‐Shien; Yeh, Ta‐Sen; Wang, Chao‐Yung; Yeh, Jih-Kai; Chen, Chia-Chun; Liu, Keng-Hau; Peng, Chen-Ching; Lin, Tien-An; Chang, Yu-Sun; Wen, Ming-Shien; Yeh, Ta-Sen; Wang, Chao-Yung
- Abstract
<bold>Objective: </bold>The weight losses after bariatric surgery are modulated by multiple factors in people with obesity. MicroRNAs (miRNAs) have been reported to show significant regulatory roles in adipose tissue. However, a serum miRNA signature to serve as a biomarker of sustained weight losses following bariatric surgery has not yet been established.<bold>Methods: </bold>MiRNA microarray was used to identify differentially expressed miRNAs in the serum of patients with an effective response after bariatric surgery compared with those without. Excess weight loss > 55% at 6 months after surgery was defined as an effective response.<bold>Results: </bold>Three miRNAs were shown to have a significantly differential expression between patients with or without an effective response following bariatric surgery. The miR-31-5p was downregulated, whereas miR-328-3p and miR-181a-5p were upregulated in the patients with effective responses compared with those without effective responses. Panels of the serum ratios of miR-328-3p/miR-31-5p or miR-181a-5p/miR-31-5p and individual BMI value exhibited good performance in preoperative prediction of treatment effectiveness. Bioinformatic analysis depicted that predicted targets of these miRNAs were involved in the regulation of the AMP-activated protein kinase signaling pathway.<bold>Conclusions: </bold>A circulating miRNA signature with clinical variables (BMI) can be a clinical biomarker to predict effectiveness following bariatric surgery.
- Subjects
BARIATRIC surgery; TREATMENT effectiveness; GASTRIC bypass; MICRORNA; WEIGHT loss; PROTEIN kinases; RNA metabolism; RESEARCH; RESEARCH methodology; EVALUATION research; BIOINFORMATICS; COMPARATIVE studies; GENE expression profiling
- Publication
Obesity (19307381), 2022, Vol 30, Issue 2, p389
- ISSN
1930-7381
- Publication type
journal article
- DOI
10.1002/oby.23330