SARS-CoV-2 receptor networks in diabetic and COVID-19–associated kidney disease
Authors: Rajasree Menon, Edgar A. Otto, Rachel Sealfon, Viji Nair, Aaron K. Wong, Chandra L. Theesfeld, Xi Chen, Yuan Wang, Avinash S. Boppana, Jinghui Luo, Yingbao Yang, Peter M. Kasson, Jennifer A. Schaub, Celine C. Berthier, Sean Eddy, Chrysta C. Lienczewski, Bradley Godfrey, Susan L. Dagenais, Ryann Sohaney, John Hartman, Damian Fermin, Lalita Subramanian, Helen C. Looker, Jennifer L. Harder, Laura H. Mariani, Jeffrey B. Hodgin, Jonathan Z. Sexton, Christiane E. Wobus, Abhijit S. Naik, Robert G. Nelson, Olga G. Troyanskaya, Matthias Kretzler
Journal: Kidney International (2020)

COVID-19 morbidity and mortality are increased via unknown mechanisms in patients with diabetes and kidney disease. SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2) for entry into host cells. Because ACE2 is a susceptibility factor for infection, we investigated how diabetic kidney disease and medications alter ACE2 receptor expression in kidneys. Single cell RNA profiling of kidney biopsies from healthy living donors and patients with diabetic kidney disease revealed ACE2 expression primarily in proximal tubular epithelial cells. This cell-specific localization was confirmed by in situ hybridization. ACE2 expression levels were unaltered by exposures to renin-angiotensin-aldosterone system inhibitors in diabetic kidney disease. Bayesian integrative analysis of a large compendium of public -omics datasets identified molecular network modules induced in ACE2-expressing proximal tubular epithelial cells in diabetic kidney disease (searchable at hb.flatironinstitute.org/covid-kidney) that were linked to viral entry, immune activation, endomembrane reorganization, and RNA processing. The diabetic kidney disease ACE2-positive proximal tubular epithelial cell module overlapped with expression patterns seen in SARS-CoV-2–infected cells. Similar cellular programs were seen in ACE2-positive proximal tubular epithelial cells obtained from urine samples of 13 hospitalized patients with COVID-19, suggesting a consistent ACE2-coregulated proximal tubular epithelial cell expression program that may interact with the SARS-CoV-2 infection processes. Thus SARS-CoV-2 receptor networks can seed further research into risk stratification and therapeutic strategies for COVID-19–related kidney damage. COVID-19 morbidity and mortality are increased via unknown mechanisms in patients with diabetes and kidney disease. SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2) for entry into host cells. Because ACE2 is a susceptibility factor for infection, we investigated how diabetic kidney disease and medications alter ACE2 receptor expression in kidneys. Single cell RNA profiling of kidney biopsies from healthy living donors and patients with diabetic kidney disease revealed ACE2 expression primarily in proximal tubular epithelial cells. This cell-specific localization was confirmed by in situ hybridization. ACE2 expression levels were unaltered by exposures to renin-angiotensin-aldosterone system inhibitors in diabetic kidney disease. Bayesian integrative analysis of a large compendium of public -omics datasets identified molecular network modules induced in ACE2-expressing proximal tubular epithelial cells in diabetic kidney disease (searchable at hb.flatironinstitute.org/covid-kidney) that were linked to viral entry, immune activation, endomembrane reorganization, and RNA processing. The diabetic kidney disease ACE2-positive proximal tubular epithelial cell module overlapped with expression patterns seen in SARS-CoV-2–infected cells. Similar cellular programs were seen in ACE2-positive proximal tubular epithelial cells obtained from urine samples of 13 hospitalized patients with COVID-19, suggesting a consistent ACE2-coregulated proximal tubular epithelial cell expression program that may interact with the SARS-CoV-2 infection processes. Thus SARS-CoV-2 receptor networks can seed further research into risk stratification and therapeutic strategies for COVID-19–related kidney damage. Editor's NoteThis is one of several articles we think you will find of interest that are part of our special issue of Kidney International addressing the challenges of dialysis and transplantation during the COVID-19 pandemic. Please also find additional material in our commentaries and letters to the editor sections. We hope these insights will help you in the daily care of your own patients. This is one of several articles we think you will find of interest that are part of our special issue of Kidney International addressing the challenges of dialysis and transplantation during the COVID-19 pandemic. Please also find additional material in our commentaries and letters to the editor sections. We hope these insights will help you in the daily care of your own patients. Translational StatementTo understand the overwhelming burden of kidney disease in coronavirus disease 2019 (COVID-19), we mapped the expression of the severe acute respiratory syndrome coronavirus 2 receptor, ACE2, in healthy kidney, early diabetic kidney diseases (DKDs), and COVID-19–associated kidney diseases. Single-cell RNA sequencing of 111,035 cells identified ACE2 predominantly in proximal tubular epithelial cells. ACE2 upregulation was observed in DKD but was not associated with renin-angiotensin-aldosterone system (RAAS) inhibition, arguing against an increased risk of COVID-19 among patients taking RAAS inhibitors. Molecular network analysis linked ACE2 expression to innate immune response and viral entry machinery, thereby revealing potential therapeutic strategies against COVID-19. To understand the overwhelming burden of kidney disease in coronavirus disease 2019 (COVID-19), we mapped the expression of the severe acute respiratory syndrome coronavirus 2 receptor, ACE2, in healthy kidney, early diabetic kidney diseases (DKDs), and COVID-19–associated kidney diseases. Single-cell RNA sequencing of 111,035 cells identified ACE2 predominantly in proximal tubular epithelial cells. ACE2 upregulation was observed in DKD but was not associated with renin-angiotensin-aldosterone system (RAAS) inhibition, arguing against an increased risk of COVID-19 among patients taking RAAS inhibitors. Molecular network analysis linked ACE2 expression to innate immune response and viral entry machinery, thereby revealing potential therapeutic strategies against COVID-19. Coronavirus disease 2019 (COVID-19) disproportionally affects people with diabetes, hypertension, and kidney disease.1Argenziano M.G. Bruce S.L. 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Zhang S. et al.Single cell RNA sequencing of 13 human tissues identify cell types and receptors of human coronaviruses.Biochem Biophys Res Commun. 2020; 526: 135-140Crossref PubMed Scopus (638) Google Scholar Single-cell RNA sequencing (scRNAseq) of SARS-CoV-2 target tissues provides a way to identify specific cell types with enhanced ACE2 expression and determine whether these cells possess molecular machinery that facilitate viral entry and subsequent virus-induced cytotoxicity. Characterization of these molecular processes could greatly accelerate the identification and development of novel therapeutic options for SARS-CoV-2 infection and noninvasive means for stratifying individuals at risk for COVID-19. Therefore, in the present study, we explored the expression and associated biological processes of ACE2 and other SARS-CoV-2 entry factors in kidney cells from healthy living donors (LDs), patients with diabetic kidney disease (DKD), and COVID-19 patients that required hospitalization (COV). Using in situ hybridization and scRNAseq techniques, we (i) localized the cellular expression of ACE2 in kidneys, (ii) characterized the cellular programs associated with ACE2 expression in DKD and COV, (iii) mapped the ACE2-associated changes to emerging data on SARS-CoV-2–induced cellular responses, and (iv) tested associations with DKD phenotypic characteristics (Figure 1). This study included a DKD cohort because COVID-19 disproportionally affects individuals with diabetes and kidney disease.3Muniyappa R. Gubbi S. COVID-19 pandemic, corona viruses, and diabetes mellitus.Am J Physiol Endocrinol Metab. 2020; 318: E736-E741Crossref PubMed Scopus (554) Google Scholar,5Emami A. Javanmardi F. Pirbonyeh N. et al.Prevalence of underlying diseases in hospitalized patients with COVID-19: a systematic review and meta-analysis.Arch Acad Emerg Med. 2020; 8 (e35–e35)PubMed Google Scholar,8Drucker D.J. Coronavirus infections and type 2 diabetes—shared pathways with therapeutic implications.Endocr Rev. 2020; 41: bnaa011Crossref PubMed Scopus (112) Google Scholar,14Cheng Y. Luo R. Wang K. et al.Kidney impairment is associated with in-hospital death of COVID-19 patients.medRxiv. 2020; 2002: 20023242Google Scholar,31Perico L. Benigni A. Remuzzi G. Should COVID-19 concern nephrologists? Why and to what extent? The emerging impasse of angiotensin blockade.Nephron. 2020; 144: 213-221Crossref PubMed Scopus (243) Google Scholar,32Al Heialy S. Hachim M.Y. Senok A. et al.Regulation of angiotensin converting enzyme 2 (ACE2) in obesity: implications for COVID-19.bioRxiv. 2020; (Accessed April 21, 2020)https://doi.org/10.1101/2020.04.17.046938Crossref Scopus (0) Google Scholar Side-by-side analysis of the DKD and COV cohorts were aimed at identifying ACE2-associated mechanisms in DKD shared with COVID-19 associated kidney disease. Kidney cell expression profiles were obtained from early DKD (n = 44) and LD (n = 18) kidney biopsies and from COV urine samples (n = 13). Clinical characteristics at the time of sample collection are provided for the DKD and COV (Table 1) cohorts. Additional details are provided in the Methods and the Supplementary Methods).Table 1Clinical characteristics of DKD and LD cohorts at time of biopsy and COV cohort at time of urine sample collectionCharacteristicDKD at biopsy (n = 44)COV at sample collection (n = 13)LD at biospy (n = 18)Age, yr41 ± 1150 ± 1745 ± 10Male, %325449Race, % White03888 Black0546 American Indian10000 Other086Diabetes duration, yr12.2 ± 7.5––Body mass index, kg/m236.9 (7.3)34.3–HbA1c, %9.2 ± 2.47.9 (N = 4)–Diastolic blood pressure, mm Hg72 ± 10––ACR, mg/g, median [IQR]18 [9–53]––iGFR, ml/min159 ± 58–101 ± 17Use of antihypertensives, %4354–Use of RASS blockers, %438–Use of angiotensin receptor blockers, %78–Use of ACE inhibitors, %3615–Baseline CKD, %–46–History of kidney transplant, %–23–History of DM, %10054–On immunosuppressant, %–23–Time since first positive COVID-19 test, d [IQR]–11 [5–29]–AKI by KDIGO, %–62– KDIGO stage 1–25– KDIGO stage 2–0– KDIGO stage 3–75–Renal recovery, %–38–COVID-19 treatment features, %–– Need for RRT–23– Indwelling urinary catheter–69– ICU admission–85– Intubation–85– ECMO–23–ACE, angiotensin converting enzyme; ACR, albumin/creatinine ratio; AKI, acute kidney injury; CKD, chronic kidney disease; COV, coronavirus disease 2019 cohort; COVID-19, coronavirus disease 2019; DKD, diabetic kidney disease; DM, diabetes mellitus; ECMO, extracorporeal membrane oxygenation; ICU, intensive care unit; iGFR, iothalamate-measured glomerular filtration rate; KDIGO, Kidney Disease: Improving Global Outcomes; LD, living donor; RAAS, renin-angiotensin-aldosterone system; RRT, renal replacement therapy.Continuous variables are presented as mean (SD). Open table in a new tab ACE, angiotensin converting enzyme; ACR, albumin/creatinine ratio; AKI, acute kidney injury; CKD, chronic kidney disease; COV, coronavirus disease 2019 cohort; COVID-19, coronavirus disease 2019; DKD, diabetic kidney disease; DM, diabetes mellitus; ECMO, extracorporeal membrane oxygenation; ICU, intensive care unit; iGFR, iothalamate-measured glomerular filtration rate; KDIGO, Kidney Disease: Improving Global Outcomes; LD, living donor; RAAS, renin-angiotensin-aldosterone system; RRT, renal replacement therapy. Continuous variables are presented as mean (SD). To define the expression pattern of ACE2, cell populations obtained by scRNAseq analysis of kidney biopsies (44 DKD and 18 LD) were clustered based on the transcription profiles of individual cells. A combined analysis of 111,035 cells from the 2 data sets with a resolution (clustering granularity) of 0.6 defined 21 cell clusters (Figure 2a and b , UMAP plots). Cells from both sample sources populated 18 of these, indicating the presence of cells with similar identity in both sample sources (Supplementary Figure S1). The 18 cell clusters covered the entire spectrum of kidney cell types found along the nephron- and tissue-resident immune cells. Furthermore, we identified 2 DKD-specific clusters (disease-specific and disease-specific thick ascending loop of Henle) and 1 LD-specific cluster (transitional principal cell-intercalated cluster). The violin plots in Figure 2c and d show a restricted cell-type-specific mRNA expression of ACE2 in proximal tubular epithelial cells (PTECs), identified using standard transcript markers including cubilin.33Sahali D. Mulliez N. Chatelet F. et al.Characterization of a 280-kD protein restricted to the coated pits of the renal brush border and the epithelial cells of the yolk sac. Teratogenic effect of the specific monoclonal antibodies.J Exp Med. 1988; 167: 213-218Crossref PubMed Scopus (136) Google Scholar ACE2, in both LD and DKD, was predominantly expressed in cells expressing cubilin, found in 2 clusters: PTEC and a hybrid cluster containing both distal limb of loop of Henle and PTEC. For further analysis, we focused on the cubilin-positive PTEC in these 2 clusters. Cellular localization of ACE2 transcripts via in situ hybridization in the kidney is shown in Figure 3 and is consistent with ACE2 expression only in proximal tubules and focally in parietal cells. Representative images from 2 control kidney biopsies (taken from 2 LD kidneys at time of transplantation) after in situ hybridization with the use of ACE2 specific probes revealed punctate signal of ACE2 expression in PTECs, but not in distal tubular cells, glomeruli, or arterioles (Figure 3a and b). A few parietal cells also showed positive signal (arrowhead in inset of Figure 3a). A clear increase in ACE2 signal in PTEC was evident in representative images from 2 kidney biopsies with mild features of DKD (Figure 3b and c) and 2 with advanced DKD (Figure 3d and e). Focally parietal cells also showed increased signal (Figure 3c inset), while other cell types remained negative. Loss of signal was seen in areas of interstitial fibrosis and tubular atrophy (Figure 3e), concomitant with loss of proximal cells in advanced DKD. To define the functional context of ACE2 expression in PTECs, we first identified genes specifically expressed in PTECs that express ACE2 (ACE2+). To this end, we first compared the expression profiles of ACE2+ with PTECs with no detectable ACE2 (ACE2−) in LD and DKD. The resulting gene expression signatures (ACE2+ signatures) consisted of genes with increased expression in ACE2+ compared with ACE2− in LD (LD ACE2+ signature; Supplementary Table S1) and DKD (DKD ACE2+ signature; Supplementary Table S2). To define the DKD-specific component of the ACE2+ signature, we next identified disease-induced genes, i.e., those upregulated in DKD ACE2+ compared with LD ACE2+ (DKD-induced ACE2+ signature; Supplementary Table S3). Table 2 provides a summary of the key ACE2+ gene signatures defined in this study.Table 2ACE2+ signatures defined from single-cell sequencing dataSignatureDefinitionFigureTableLD ACE2+ signatureGenes with increased expression in ACE2+ vs. ACE2− PTECs in LDNot shownSupplementary Table S1DKD ACE2+ signatureGenes with increased expression in ACE2+ vs. ACE2− PTECs in DKDFigure 4aSupplementary Table S2DKD induced ACE2+ signatureGenes with increased expression in DKD ACE2+ PTECs compared with LD ACE2+ PTECsSupplementary Figure S2Supplementary Table S3COV ACE2+ signatureGenes with increased expression in ACE2+ vs. ACE2− PTECs in COVFigure 7aSupplementary Table S10ACE2+, angiotensin-converting enzyme 2–positive; COV, coronavirus disease 2019–associated disease that required hospitalization; DKD, diabetic kidney disease; LD, living donor; PTEC, proximal tubular epithelial cell. Open table in a new tab ACE2+, angiotensin-converting enzyme 2–positive; COV, coronavirus disease 2019–associated disease that required hospitalization; DKD, diabetic kidney disease; LD, living donor; PTEC, proximal tubular epithelial cell. To functionally characterize the molecular machinery expressed in ACE2 + cells in DKD, we projected the DKD ACE2+ signature genes onto the HumanBase functional network that represents biological processes and pathways active in PTECs. Intuitively, this functional network is constructed by probabilistically integrating a large compendium of thousands of public omics datasets to predict the likelihood of 2 genes acting together in processes in PTECs.34Greene C.S. Krishnan A. Wong A.K. et al.Understanding multicellular function and disease with human tissue-specific networks.Nat Genet. 2015; 47: 569-576Crossref PubMed Scopus (564) Google Scholar,35Wong A.K. Krishnan A. Troyanskaya O.G. GIANT 2.0: genome-scale integrated analysis of gene networks in tissues.Nucleic Acids Res. 2018; 46: W65-W70Crossref PubMed Scopus (48) Google Scholar We clustered the DKD ACE2+ signature genes within this PTEC functional network (Figure 4a36Bojkova D. Westhaus S. Costa R. et al.Sofosbuvir activates EGFR-dependent pathways in hepatoma cells with implications for liver-related pathological processes.Cells. 2020; 9: 1003Crossref Scopus (11) Google Scholar; Supplementary Table S2), and the resulting modules (Figure 4a; Supplementary Table S4) contained key processes of tubular function and failure (M7) as well as disease signals (M3–M5, M7). Importantly, we also identified key processes important to both host response and viral replication, including viral entry and genome replication (M1, M4), viral gene transcription (M1, M3), and endomembrane organization and transport (M2–M4, M7). Immune processes were significantly enriched across multiple modules and encompassed innate immune responses (M1, M4) and both production and response to tumor necrosis factor, interferons, and cytokine and macrophage activation (M4). Thus, this signature contains both key elements of documented DKD pathophysiology and processes generally associated with viral infections.37Becker J.L. Miller F. Nuovo G.J. et al.Epstein-Barr virus infection of renal proximal tubule cells: possible role in chronic interstitial nephritis.J Clin Invest. 1999; 104: 1673-1681Crossref PubMed Scopus (75) Google Scholar,38Yamanaka K. Oka K. Nakazawa S. et al.Immunohistochemical features of BK virus nephropathy in renal transplant recipients.Clin Transplant. 2012; 26: 20-24Crossref PubMed Scopus (14) Google Scholar The signature above describes processes in ACE2+ compared with ACE2− PTECs in DKD. To discover which aspects of DKD could be linked to a more severe COVID-19 disease progression, we identified genes upregulated in ACE2+ DKD compared with LD (Supplementary Table S3). Analysis of these genes demonstrated prominent signals reflecting induction of processes such as inflammation and immune signaling, regulation of kidney size, and morphogenesis of kidney epithelium, which are consistent with reported impacts of diabetic pathology on proximal tubules and PTECs (Supplementary Table S5; Supplementary Figure S2A). Notably, many genes and processes connected to RNA splicing and several aspects related to viral biology were also induced in DKD. We compared the DKD ACE2+ signature genes with published SARS-CoV-2–relevant gene sets20Zhou L. Niu Z. Jiang X. et al.Systemic analysis of tissue cells potentially vulnerable to SARS-CoV-2 infection by the protein-proofed single-cell RNA profiling of ACE2, TMPRSS2 and Furin proteases.bioRxiv. 2020; (Accessed April 16, 2020)https://doi.org/10.1101/2020.04.06.028522Crossref Scopus (0) Google Scholar,36Bojkova D. Westhaus S. Costa R. et al.Sofosbuvir activates EGFR-dependent pathways in hepatoma cells with implications for liver-related pathological processes.Cells. 2020; 9: 1003Crossref Scopus (11) Google Scholar,