ABSTRACT
Background: Renal (acute kidney injury, AKI) involvement in COVID-19 patients is associated with high mortality and morbidity. Critically ill COVID-19 patients are at twice the risk of in hospital mortality compared to nonCOVID AKI patients. The cell types that succumb to direct or indirect damage and the associated abnormal biological responses are unclear. New generation single cell technologies have the potential to provide insights into physiological states and molecular mechanisms in COVID-AKI. One of the key limitations is that biopsies are not routinely performed and the risks of procuring an additional research core is indeterminate making it difficult to get direct insights into the landscape of COVID-AKI disease in the kidney at genome wide and cellular scale. Method(s): We developed an innovative method that used remnant kidney biopsy tissue from OCT-embedded frozen diagnostic pathology biopsy core and generated single nucleus transcriptome (snRNAseq) of COVID-AKI from as little as 1 mm3 of tissue. Comparative analysis of snRNAseq of 4 COVID-AKI and 4 control cortical biopsies was done in conjunction with urine transcriptomics to find overlapping genes in these two datasets representing COVID-AKI-enriched genes and the corresponding cell types in the kidney. Result(s): snRNAseq of COVID-AKI remnant or control frozen kidney biopsies (15659 and 15604 nuclei passing QC, respectively) identified all major and minor cell types. Differential expression analysis of COVID-AKI biopsies showed pathways enriched in viral response, kidney regeneration, WNT signaling, cancer, kidney development and cytokines in several nephron epithelial cells including kidney injury markers and fibrosis indicating robust remodelling in various cell types. Ten genes were also detected in urine cells of COVID-AKI patients as potential biomarkers. Two of these genes, LRP1B and PDE3A, have been recently implicated in driving fibrosis in COVID-AKI model systems. Conclusion(s): snRNAseq is feasible on leftover kidney biopsy tissue using minimum amount of sample and enabled identification of altered kidney cell types and states with several novel genes associated with tissue injury, remodelling and fibrosis.