Abstract
Diabetic kidney disease (DKD) is a serious disease that presents a major health problem worldwide. There is a desperate need to explore novel biomarkers to further facilitate the early diagnosis and effective treatment in DKD patients, thus preventing them from developing end-stage renal disease (ESRD). However, most regulation mechanisms at the genetic level in DKD still remain unclear. In this paper, we describe our innovative methodologies that integrate biological, computational, and statistical approaches to investigate important roles performed by regulations among microRNAs (miRs), long non-coding RNAs (lncRNAs), and messenger RNAs (mRNAs) in DKD. We conducted fully transparent, rigorously designed experiments. Our robust and reproducible results identified hsa-miR-223-3p as a candidate novel biomarker performing important roles in DKD disease process.