Can genetics help predict efficacy of bariatric surgery? An analysis of microRNA profiles
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Can genetics help predict efficacy of bariatric surgery? An analysis of microRNA profiles
Background: There is a significant variability in weight loss after bariatric surgery. We hypothesize that part of this variability can be predetermined by the genetic differences associated with metabolic homeostasis. MicroRNA (miRNA) are short pieces of RNA that regulate gene expression and easily detectable in the serum. They are involved in many metabolic processes, including weight homeostasis. In this pilot study, we briefly review the role of miRNA, and assess the feasibility of using them in a clinical setting treatment of obesity.
Objective: To evaluate the feasibility of using miRNA to predict weight loss after bariatric surgery.
Setting: Academic medical center.
Methods: Serum collected from patients at the initial bariatric surgery consultation. Weight loss data were collected 6 and 12 months postoperatively. Individuals experiencing a bit and the largest number of percentage of excess weight lost at 6 months were analyzed to assess genetic differences in miRNA expression.
Results: The median percentage of excess weight lost was 51% (range, 34% -63%) for those who lose the least and 87% (range, 82% -111%) for those who lost the most weight. Groups were similar in age, gender, diabetes status, and type of operation. In total, of 119 miRNA is detected in the serum of patients, 6 showed potential to differentiate between weight loss group high and low. Mirna has previously been involved in the regulation of fatty acid biosynthesis, adipocytes proliferation, type 2 diabetes, and obesity.
Conclusions: In this pilot study, we demonstrate the feasibility of identifying genetic differences between groups of weight loss by identifying high and low serum miRNA different. In the near future, these biomarkers could facilitate decisions about surgery. In addition, this miRNA could open up new genetic pathways that describe the pathophysiology of obesity, and provide targets for future treatment.
Can genetics help predict efficacy of bariatric surgery? An analysis of microRNA profiles
The platelet microRNA Profile Kawasaki Disease: Identification of Novel Diagnostic Biomarkers
Challenging the unknown diagnosis and etiology of Kawasaki disease (KD) increases the incidence of coronary artery lesions. microRNAs (miRNAs) are the most promising biomarker for their stability in peripheral blood and noninvasive measurement procedures, which have proven potential utility in cancer. To explore the utility expressed differently (DE) miRNAs early diagnostic markers, 44 patients (25 KD 19, KD incomplete and complete) and 31 controls were recruited fever for small RNA sequencing.
Of all the states in 1922 Mirna, DE 210 miRNAs were found between KD and control groups fever. Although platelet miRNA profile of a complete full KD KD similar through cluster analysis, DE miRNAs are not identical. DE eight miRNAs validated by quantitative real-time PCR (qRT-PCR) in a group of complete or incomplete KD using a normalizer, miR-126-3p, identified by geNorm and NormFinder tools.
Rat Complete SeraMir Exosome RNA Amplification and Profiling Kit for Media and Urine (contains cat# RA800TC-1 with 50ml ExoQuick-TC, RA805A-1 and RA812A-1 components)
Human Complete SeraMir Exosome RNA Amplification and Profiling Kit for Media and Urine (contains cat# RA800A-1, RA805A-1, RA810A-1 and EXOTC50A-1 components)
Mouse Complete SeraMir Exosome RNA Amplification and Profiling Kit for Media and Urine (contains cat# RA800A-1, RA805A-1, RA810A-1 and EXOTC50A-1 components)
Description: This product is a useful tool for the isolation and efficient total RNA (miRNA and mRNAs) extraction from the total exosome population from human biofluids or cell culture media.
The expression levels of miRNAs are continually changing over time was observed and analysis of miRNAs function suggests a potential role as a therapeutic biomarker. In addition, a prediction model for KD showed 78.8% sensitivity and 71.4% specificity, respectively. This study uses small RNA sequencing to identify miRNA biomarkers KD diagnosis is based on a large sample size. Our findings illuminate understanding of the molecular pathogenesis of KD and can improve the accuracy of diagnosis and prognosis in clinical KD.
