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Abstract: TH-OR12

Extracellular miRNAs as Predictors of CKD Progression

Session Information

Category: CKD (Non-Dialysis)

  • 2303 CKD (Non-Dialysis): Mechanisms


  • Srivastava, Anvesha, The George Washington University, Washington, District of Columbia, United States
  • Amdur, Richard L., Northwell Health, New Hyde Park, New York, United States
  • Pabalan, Ana, The George Washington University, Washington, District of Columbia, United States
  • Raj, Dominic S., The George Washington University, Washington, District of Columbia, United States

Kidney fibrosis is final common pathway downstream of most renal injuries that contributes to progressive chronic kidney disease (CKD). Noncoding RNAs regulate kidney fibrosis through direct repression and/or expression of matrix genes and TGF-β signaling. We hypothesized that specific circulating microRNAs (miRNAs) are indicators of underlying kidney fibrosis and can serve as early biomarkers for CKD progression.


The study was performed using patient samples/clinical data from the Chronic Renal Insufficiency Cohort (CRIC) cohort (n= 3,471). The slowest and fastest progressors of CKD were defined based on the largest and smallest negative slope of eGFR change over time, using within-subject ordinary least-squares regression of follow-up eGFR readings.
Next Generation Sequencing (NGS) was performed to identify miRNAs associated with CKD progression. Circulating RNAs from plasma samples were isolated and sequencing was performed on NovaSeq platform (Illumina, Inc). The raw counts, mapping, and differential expression analysis was done using R Bioconductor packages. Total of 500 genes with highest variance were used for principal component analysis and 35 genes with highest variance across samples were selected for hierarchical clustering. The biological effects, mechanisms and functions of identified miRNAs were analyzed using Ingenuity Pathway analysis.


Global extracellular miRNA expression analysis showed presence of 1,888 miRNAs in plasma. Differential analysis using generalized linear models (GLMs) in edgeR was performed to identify the miRNA associated with rapid progression adjusting for sex, ethnicity, diabetes status, UAC Ratio and EGFR levels. Expression of 8 miRNAs (miR-887-5p, miR-1197, miR-6729-3p, miR-6774-3p, miR-6795-5p, miR-548f-3p, miR-3135a, miR-1469) varied significantly between fast and slow progressor groups. This differential expression of miRNAs between the two groups was significantly modulated by ethnicity and diabetic status of patient. Bioinformatic analysis showed pivotal role of these miRNAs in variety of important cell activities such as apoptosis, organ fibrosis, autophagy, metastasis etc.


This study identifies extracellular miRNAs that can serve as indicator of CKD progression. Identification of specific miRNA pathways for CKD progression will enhance diagnosis, enable risk stratification and lead to targeted interventions.


  • NIDDK Support