Análisis metabolómico y transcriptómico diferencial de pacientes prediabéticos, diabéticos y con nefropatía diabética para identificar potenciales biomarcadores de daño renal

Abstract

Background. The early diagnosis of diabetic nephropathy (DN) is essential to improve the prognosis and manage patients affected by this disease. Standard biomarkers, including albuminuria and glomerular filtration rate, are limited to give a precise result. New molecular biomarkers are needed to identify better and predict DN disease evolution. Characteristic DN biomarkers can be identified using transcriptomic analysis. Aim of the study. To evaluate the transcriptomic profile of controls (CTRLs, n = 15), prediabetes (PREDM, n = 15),, type-2 diabetes mellitus (DM-2, n = 15), and DN (n = 15) patients by microarray analysis to find new biomarkers, RT-PCR was used to confirm gene biomarkers specific for DN. Materials and methods. Blood samples were used to isolate RNA for microarray expression microarrays evaluating 26,803 unique gene sequences and 30,606 LncRNA sequences, selected gene biomarkers for DN were validated using qPCR assays. Sensitivity, specificity, and area under the curve (AUC) were calculated as measures of diagnostic accuracy. Results. The DN transcriptome, founding here, were composed by 300 induced genes, compared to CTRLs, PREDM, and DM-2 groups. RT-qPCR assays validated that METLL22, PFKL , CCNB1 and CASP2 genes were induced in the DN group compared to CTRLs, PREDM, and DM-2 groups. The ROC analysis for these four genes showed 0.9719, 0.8853, 0.8533 and 0.7748 AUC values respectively. Conclusion. Among induced genes in the DN group, we found that CASP2, PFKL and CCNB1 can be used as potential biomarkers to diagnose DN, where, METLL22 represents the best with an AUC=0.9719.