Plasma transcriptome profile associated with CKD progression

Introduction: Understanding the molecular signals associated with the progression of kidney disease is vital for risk stratification and targeted treatment. Recent advances in RNA-sequencing technique has enabled us to characterize extracellular transcriptome profiles for precision diagnostics. Method: We evaluated the plasma mRNA profile of participants exhibiting slow (n=119) and fast (n=119) decline in estimated glomerular filtration rate (eGFR) among the Chronic Renal Insufficiency Cohort (CRIC) in a nested case control study. The two groups were matched for age, sex, race, baseline eGFR, proteinuria and diabetes status. The next generation sequencing data was analyzed using edgeR to identify differentially expressed genes (DEGs) and Ingenuity Pathway Analysis (IPA) was done to identify the associated pathways. We also compared the top plasma DEGs with gene expression in microdissected human CKD kidney. Results: We identified fragments from ~28,000 annotated genes, of which 783 transcripts exhibited differential expression between slow and fast CKD progressors. Among 629 protein coding genes, 469 were overexpressed in slow progressors, while 157 showed increased expression in fast progressors. Expression of GLI2, CUX1, NOTCH1 and LRP1 transcripts were amplified in slow progressors. Pathway analysis linked these differentially expressed genes to WNT/β-catenin signaling, IL-12 signaling and production in macrophages, Netrin-1 Signaling and Epithelial-Mesenchymal Transition pathways. Many of the plasma differentially expressed genes were also upregulated in microdissected human CKD kidney. Conclusion: Warranting further validation, circulating levels of aberrantly expressed transcripts hold potential to be used as biomarkers for fast CKD progression.