MicroRNA expression profiling in peripheral blood mononuclear cells and serum of type 2 diabetic, pre-diabetic and normo-glycaemic individuals
Year: 2016
Type: dissertation
Study design: Observational Study
Abstract: MicroRNAs (miRNAs) are small non-coding RNAs that play a fundamental role in cellular function by regulating messenger RNA gene expression.Alterations in miRNA expression are implicated in metabolic dysregulation, with several studies reporting the involvement of miRNAs in the pathophysiology of Type 2 diabetes (T2D).Recently, circulating miRNAs have attracted considerable interest as biomarkers to identify individuals at risk for T2D, thus we hypothesised that circulating miRNA could be used as markers for T2D progression.The aim of this study was to determine whether miRNA expression profiles differ between diabetic, pre-diabetic and normo-glycaemic individuals.Individuals were recruited from local communities and classified as diabetic, pre-diabetic or normo-glycaemic according to World Health Organization criteria, whereafter miRNAs were extracted from peripheral blood mononuclear cells (PBMCs) and serum of age-, gender-, ethnicity-and BMI-matched diabetic (n=4), pre-diabetic (n=4) and normo-glycaemic (n=4) individuals.MiRNAs extracted from PBMCs were sequenced using the Illumina HiSeq 2500 platform, and validated by quantitative real time PCR (qRT-PCR) in PBMCs and serum of these individuals.Moreover, bioinformatics was conducted using various target prediction programs (TargetScan, DIANA and PITA) and the DAVID functional gene annotation tool to assign biological significance to the differentially expressed miRNAs identified by sequencing.Sequencing showed that 267 (pre-diabetics vs. normo-glycaemics), 277 (diabetics vs. normo-glycaemics) and 267 (pre-diabetics vs. diabetics) miRNAs were differentially expressed between groups.Of these, five differentially expressed miRNAs (miR-27b, miR-379, miR-21, miR-98 and miR-143) were selected for validation by qRT-PCR in PBMCs.Only miR-143 and miR-27b were significantly differentially expressed using qRT-PCR, although the results for miR-143 were different compared to the sequencing data.MiR-143 was upregulated in pre-diabetics compared to normo-glycaemic individuals (1.40-fold, p≤0.01), whereas sequencing showed upregulation of miR-143 in diabetics compared to prediabetics (1.75-fold, p≤0.05).The differential expression of miR-27b was consistent between qRT-PCR (1.55-fold; p=0.07) and sequencing (1.15-fold; p<0.01),where both methods Stellenbosch University https://scholar.sun.ac.za iv showed upregulation in pre-diabetics compared to normo-glycaemic individuals.The expression of miR-27b was similarly upregulated in serum of pre-diabetics compared to normo-glycaemic individuals (2.0-fold; p≤0.05).Furthermore, five novel miRNAs identified by sequencing were successfully validated in PBMCs of diabetic, pre-diabetic and normoglycaemic individual.Sequencing and qRT-PCR showed that miR-27b was upregulated in PBMCs and serum of pre-diabetics compared to normo-glycaemic individuals.Bioinformatics identified peroxisome proliferator-activated receptor gamma (Pparg) as a target for miR-27b.PPARG is an insulin sensitizing agent, thus we speculate that increased miR-27b expression in pre-diabetes suppresses Pparg, thereby inhibiting insulin signaling and subsequently decreasing glucose uptake.The increased insulin and glucose levels observed in the pre-diabetic individuals support this idea, although further work is required to confirm this hypothesis.In conclusion, we showed that miRNA profiles differ during T2D progression, and are able to discriminate between diabetic, pre-diabetic and normo-glycaemic individuals.To our knowledge, this is the first study to report differential expression of miR-27b during T2D, suggesting its potential as a biomarker that could be incorporated into predictive models for the identification of high risk individuals.However, miRNA profiling in a larger sample size and prospective longitudinal studies are required to assess clinical applicability.
Author: Stephanie Dias
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2345779585