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Candidate early predictors for diabetic nephropathy
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posted on 08.02.2017, 04:48by Yap, Christina Gertrude
Since diabetic nephropathy (DN) is the most common cause of end-stage renal disease (ESRD), the search for an early predictor for DN is important because interventions may be tailored to prevent the onset of pathogenesis leading to DN instead of reversing an already altered physiological condition. Microalbuminuria is presently the preferred marker of nephropathy, but by the time the detection of microalbuminuria is initiated, advanced renal structural changes have already occurred as evidenced from renal biopsies. Recent reports have showed that the expression and levels of CYP2E1 protein is elevated in the peripheral blood lymphocytes among patients with prolonged diabetes and in those with chronic renal failure. However, there are no published reports on the correlation between elevated CYP2E1 and progression of nephropathy.
Therefore, the aims of this study were to evaluate lymphocyte CYP2E1 as a candidate early predictor for diabetic nephropathy using high performance liquid chromatography (HPLC), validate the HPLC observations using real-time PCR, to construct a candidate DN gene signature using the microarray technology, as well as to determine other biomarkers besides CYP2E1 which may be suitable candidate early predictors for DN.
A cross-sectional cohort study was carried out among Malaysians,
consisting of control (n=28), diabetes (n=50), diabetic nephropathy (n=34) and non diabetic nephropathy (n=15) cohorts. Whole blood samples were collected, lymphocytes were isolated and aliquots were made. Microsomes were prepared for CYP2E1 analysis using HPLC. Total RNA was extracted from the lymphocytes for real time PCR and microarray studies. Microarray analysis was done using Illumina Human Ref-8 Sentrix bead chips and the raw data were analyzed using GeneSpring GX 11.0 software. A gene expression signature consisting of 59 differentially expressed genes (P<0.001) has been constructed and validated using real time PCR. Statistical significance tests were done by employing the one-way ANOVA test at P value cut-off of 0.001 using the Sigma Plot software, version 11.0.
The prototype candidate gene expression pattern displayed properties of possible early predictors for DN. Genes involved in glucose metabolism and associated pathways (PGK1, ENO1, TpI1, ANGPTL4, AKR1B1, and SORD) were good observational entities for early prediction of DN. Products of these candidate signature genes may be easily measured in clinical laboratories from plasma samples. The results also showed lymphocyte CYP2E1 was detected in 38.7% of the diabetes cohort population (n=50) with normal serum creatinine, urine microalbumin, glomerular filtration rate and HbA1c levels. Lymphocyte CYP2E1 was not detectable in the control and pre-diabetic cohorts. In conclusion, this study lends early evidence that lymphocyte CYP2E1 is a more specific candidate predictor for diabetic nephropathy compared to microalbuminuria and a prototype candidate molecular signature may be tested as a possible early predictor for DN.