Please use this identifier to cite or link to this item: https://ptsldigital.ukm.my/jspui/handle/123456789/389992
Title: Urinary Long Non-Coding RNAS as Potential Early Biomarkers for Diabetic Nephropathy
Authors: Tamil Selvi Loganathan
Supervisor: Siti Aishah Sulaiman, Dr.
Noraidatulakma Abdullah., Dr.
Nor Azian Abdul Murad, Prof. Dr.
A. Rahman A. Jamal, Prof. Datuk. Dr.
Keywords: Diabetic Nephropathies
Academic Dissertations as Topic
Issue Date: 2021
Abstract: Diabetic Nephropathy (DN) is a common complication in Type 2 Diabetes Mellitus (T2DM) individuals. T2DM individuals have to undergo a routine clinical screening using the Urinary albumin estimation (UAE) level to detect DN presence. However, in some patients, early kidney damage is reported before any indication of an increase in the UAE level (microalbuminuria). Previous studies have proposed that long non- coding RNAs (lncRNAs) can be used as potential early biomarkers to identify microalbuminuria in urine samples. Here, we aimed to determine the potential of urinary lncRNAs as early biomarkers in T2DM individuals before the presence of microalbuminuria. In this study, we used T2DM participants from The Malaysian Cohort (TMC) without any disease complications at the baseline phase. Those T2DM individuals who developed microalbuminuria after a 5-years follow-up were considered the cases (T2DN), while those who did not were considered the controls (T2D). For the discovery part, T2DN (n=6) and T2D (n=6) groups with their clean whole urine samples for phase 1 (baseline) and phase 2 (5-year-follow-up) were retrieved from the TMC bio- bank. Total RNA was extracted from the urine samples, and the urinary lncRNAs expressions were measured using microarray technology. Data were analyzed using the Genespring software, and lncRNAs with log2 fold-change (FC)>1.5 and adjusted p- value<0.05 were considered differentially expressed. For selecting which lncRNAs as early biomarkers to detect microalbuminuria, integrative in silico functional analysis was performed. The potential lncRNAs candidates were then validated in a validation cohort of T2DM TMC participants of T2D (n=43) and T2DN (n=42) in their phase 1 urine samples by the Real-Time qPCR method. The diagnostic potential of these lncRNAs to predict microalbuminuria was determined using the receiver operating characteristic (ROC) curve analysis in another cohort of 225 T2DM TMC participants with a randomized status of microalbuminuria. Urinary lncRNA profiling showed that four lncRNAs were reduced (LNC-SLC25A13, LINC00113, LNC-CPPED1, and ZNF252P-AS1, p-value<0.05) in the T2DN group in phase 1. Three of these lncRNAs were significantly reduced (LINC00113: p-value<0.0001), LNC-CPPED1: p- value=0.012), and ZNF252P-AS1: p-value=0.0069) in the validation cohort. The baseline two urinary ZNF252P-AS1 and LINC00113 expressions significantly predicted the microalbuminuria with the area under the ROC (AUROC) curve, 0.855 and 0.783, respectively. A combination of three baseline urinary lncRNAs (ZNF252P-AS1, LINC00113, and LNC-CPPED1-5) expressions improved microalbuminuria prediction with an AUROC curve of 0.905 (95% CI, 0.858-0.953, the sensitivity of 0.808, and specificity of 0.816). In conclusion, urinary lncRNAs expressions significantly differ due to microalbuminuria presence and may be used to predict microalbuminuria's future incidence in T2DM individuals.
Pages: 167
Publisher: UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia,Kuala Lumpur
Appears in Collections:UKM Medical Molecular Biology Institute / Institut Perubatan Molekul (UMBI)

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