Integrated multiomics implicates dysregulation of ECM and cell adhesion pathways as drivers of severe COVID-associated kidney injury.

COVID-19 has been a significant public health concern for the last four years; however, little is known about the mechanisms that lead to severe COVID-associated kidney injury. In this multicenter study, we combined quantitative deep urinary proteomics and machine learning to predict severe acute outcomes in hospitalized COVID-19 patients. Using a 10-fold cross-validated random forest algorithm, we identified a set of urinary proteins that demonstrated predictive power for both discovery and validation set with 87% and 79% accuracy, respectively. These predictive urinary biomarkers were recapitulated in non-COVID acute kidney injury revealing overlapping injury mechanisms. We further combined orthogonal multiomics datasets to understand the mechanisms that drive severe COVID-associated kidney injury. Functional overlap and network analysis of urinary proteomics, plasma proteomics and urine sediment single-cell RNA sequencing showed that extracellular matrix and autophagy-associated pathways were uniquely impacted in severe COVID-19. Differentially abundant proteins associated with these pathways exhibited high expression in cells in the juxtamedullary nephron, endothelial cells, and podocytes, indicating that these kidney cell types could be potential targets. Further, single-cell transcriptomic analysis of kidney organoids infected with SARS-CoV-2 revealed dysregulation of extracellular matrix organization in multiple nephron segments, recapitulating the clinically observed fibrotic response across multiomics datasets. Ligand-receptor interaction analysis of the podocyte and tubule organoid clusters showed significant reduction and loss of interaction between integrins and basement membrane receptors in the infected kidney organoids. Collectively, these data suggest that extracellular matrix degradation and adhesion-associated mechanisms could be a main driver of COVID-associated kidney injury and severe outcomes.

Combination therapy for kidney disease in people with diabetes mellitus.

Diabetic kidney disease (DKD), defined as co-existing diabetes and chronic kidney disease in the absence of other clear causes of kidney injury, occurs in approximately 20-40% of patients with diabetes mellitus. As the global prevalence of diabetes has increased, DKD has become highly prevalent and a leading cause of kidney failure, accelerated cardiovascular disease, premature mortality and global health care expenditure. Multiple pathophysiological mechanisms contribute to DKD, and single lifestyle or pharmacological interventions have shown limited efficacy at preserving kidney function. For nearly two decades, renin-angiotensin system inhibitors were the only available kidney-protective drugs. However, several new drug classes, including sodium glucose cotransporter-2 inhibitors, a non-steroidal mineralocorticoid antagonist and a selective endothelin receptor antagonist, have now been demonstrated to improve kidney outcomes in people with type 2 diabetes mellitus. In addition, emerging preclinical and clinical evidence of the kidney-protective effects of glucagon-like-peptide-1 receptor agonists has led to the prospective testing of these agents for DKD. Research and clinical efforts are geared towards using therapies with potentially complementary efficacy in combination to safely halt kidney disease progression. As more kidney-protective drugs become available, the outlook for people living with DKD should improve in the next few decades.

Ontology-based modeling, integration, and analysis of heterogeneous clinical, pathological, and molecular kidney data for precision medicine.

Many data resources generate, process, store, or provide kidney related molecular, pathological, and clinical data. Reference ontologies offer an opportunity to support knowledge and data integration. The Kidney Precision Medicine Project (KPMP) team contributed to the representation and addition of 329 kidney phenotype terms to the Human Phenotype Ontology (HPO), and identified many subcategories of acute kidney injury (AKI) or chronic kidney disease (CKD). The Kidney Tissue Atlas Ontology (KTAO) imports and integrates kidney-related terms from existing ontologies (e.g., HPO, CL, and Uberon) and represents 259 kidney-related biomarkers. We also developed a precision medicine metadata ontology (PMMO) to integrate 50 variables from KPMP and CZ CellxGene data resources and applied PMMO for integrative kidney data analysis. The gene expression profiles of kidney gene biomarkers were specifically analyzed under healthy control or AKI/CKD disease statuses. This work demonstrates how ontology-based approaches support multi-domain data and knowledge integration in precision medicine.

Endogenous adenine mediates kidney injury in diabetic models and predicts diabetic kidney disease in patients.

Diabetic kidney disease (DKD) can lead to end-stage kidney disease (ESKD) and mortality; however, few mechanistic biomarkers are available for high-risk patients, especially those without macroalbuminuria. Urine from participants with diabetes from the Chronic Renal Insufficiency Cohort (CRIC) study, the Singapore Study of Macro-angiopathy and Micro-vascular Reactivity in Type 2 Diabetes (SMART2D), and the American Indian Study determined whether urine adenine/creatinine ratio (UAdCR) could be a mechanistic biomarker for ESKD. ESKD and mortality were associated with the highest UAdCR tertile in the CRIC study and SMART2D. ESKD was associated with the highest UAdCR tertile in patients without macroalbuminuria in the CRIC study, SMART2D, and the American Indian study. Empagliflozin lowered UAdCR in nonmacroalbuminuric participants. Spatial metabolomics localized adenine to kidney pathology, and single-cell transcriptomics identified ribonucleoprotein biogenesis as a top pathway in proximal tubules of patients without macroalbuminuria, implicating mTOR. Adenine stimulated matrix in tubular cells via mTOR and stimulated mTOR in mouse kidneys. A specific inhibitor of adenine production was found to reduce kidney hypertrophy and kidney injury in diabetic mice. We propose that endogenous adenine may be a causative factor in DKD.

Role of endogenous adenine in kidney failure and mortality with diabetes.

Diabetic kidney disease (DKD) can lead to end-stage kidney disease (ESKD) and mortality, however, few mechanistic biomarkers are available for high risk patients, especially those without macroalbuminuria. Urine from participants with diabetes from Chronic Renal Insufficiency Cohort (CRIC), Singapore Study of Macro-Angiopathy and Reactivity in Type 2 Diabetes (SMART2D), and the Pima Indian Study determined if urine adenine/creatinine ratio (UAdCR) could be a mechanistic biomarker for ESKD. ESKD and mortality were associated with the highest UAdCR tertile in CRIC (HR 1.57, 1.18, 2.10) and SMART2D (HR 1.77, 1.00, 3.12). ESKD was associated with the highest UAdCR tertile in patients without macroalbuminuria in CRIC (HR 2.36, 1.26, 4.39), SMART2D (HR 2.39, 1.08, 5.29), and Pima Indian study (HR 4.57, CI 1.37-13.34). Empagliflozin lowered UAdCR in non-macroalbuminuric participants. Spatial metabolomics localized adenine to kidney pathology and transcriptomics identified ribonucleoprotein biogenesis as a top pathway in proximal tubules of patients without macroalbuminuria, implicating mammalian target of rapamycin (mTOR). Adenine stimulated matrix in tubular cells via mTOR and stimulated mTOR in mouse kidneys. A specific inhibitor of adenine production was found to reduce kidney hypertrophy and kidney injury in diabetic mice. We propose that endogenous adenine may be a causative factor in DKD.

SGLT2 inhibitors mitigate kidney tubular metabolic and mTORC1 perturbations in youth-onset type 2 diabetes.

The molecular mechanisms of sodium-glucose cotransporter-2 (SGLT2) inhibitors (SGLT2i) remain incompletely understood. Single-cell RNA sequencing and morphometric data were collected from research kidney biopsies donated by young persons with type 2 diabetes (T2D), aged 12 to 21 years, and healthy controls (HCs). Participants with T2D were obese and had higher estimated glomerular filtration rates and mesangial and glomerular volumes than HCs. Ten T2D participants had been prescribed SGLT2i (T2Di[+]) and 6 not (T2Di[-]). Transcriptional profiles showed SGLT2 expression exclusively in the proximal tubular (PT) cluster with highest expression in T2Di(-) patients. However, transcriptional alterations with SGLT2i treatment were seen across nephron segments, particularly in the distal nephron. SGLT2i treatment was associated with suppression of transcripts in the glycolysis, gluconeogenesis, and tricarboxylic acid cycle pathways in PT, but had the opposite effect in thick ascending limb. Transcripts in the energy-sensitive mTORC1-signaling pathway returned toward HC levels in all tubular segments in T2Di(+), consistent with a diabetes mouse model treated with SGLT2i. Decreased levels of phosphorylated S6 protein in proximal and distal tubules in T2Di(+) patients confirmed changes in mTORC1 pathway activity. We propose that SGLT2i treatment benefits the kidneys by mitigating diabetes-induced metabolic perturbations via suppression of mTORC1 signaling in kidney tubules.

Quantitative morphometrics reveals glomerular changes in patients with infrequent segmentally sclerosed glomeruli.

AIMS: Detection of one segmentally sclerosed glomerulus (SSG) identifies patients with focal segmental glomerulosclerosis (FSGS) but rare SSGs may be missed in kidney biopsies. It is unknown whether alterations of unaffected glomeruli in patients with infrequent SSG can be detected by quantitative morphometrics. METHODS: We determined SSG frequency and obtained quantitative morphometrics in glomeruli without a pathologic phenotype in large kidney sections of non-involved kidney tissue from 137 patients undergoing total nephrectomy. We used multivariate modelling to identify morphometrics independently associated with increasing frequency of SSG and Receiver Operator Curve (ROC) analysis to determine the ability of quantitative morphometrics to identify patients with FSGS. We used the geometric distribution to estimate the sensitivity and specificity of a needle biopsy to identify patients with FSGS. RESULTS: In seventy-one patients (51.8%), at least one SSG was observed, and of those, 39 (54.9%) had an SSG lesion in less than 2% of all glomeruli (mean of 249 glomeruli per specimen). Increasing percent of SSG was independently associated with decreasing podocyte density and increasing mesangial index in multivariate modelling. For infrequent SSG lesions (<1% of glomeruli), kidney biopsy could miss FSGS diagnosis more than 74% of the time, and podocyte density had an area under the curve (AUC) of 0.77, and mesangial index, an AUC of 0.79 to identify patients with FSGS. CONCLUSIONS: More than half of patients had FSGS, although 30% had infrequent SSG. Quantitative morphometrics in glomeruli without pathology, such as podocyte density and mesangial index, identified patients with infrequent SSG and may serve as clinical markers to identify patients with FSGS.

Rationale and design of the Kidney Precision Medicine Project.

Chronic kidney disease (CKD) and acute kidney injury (AKI) are common, heterogeneous, and morbid diseases. Mechanistic characterization of CKD and AKI in patients may facilitate a precision-medicine approach to prevention, diagnosis, and treatment. The Kidney Precision Medicine Project aims to ethically and safely obtain kidney biopsies from participants with CKD or AKI, create a reference kidney atlas, and characterize disease subgroups to stratify patients based on molecular features of disease, clinical characteristics, and associated outcomes. An additional aim is to identify critical cells, pathways, and targets for novel therapies and preventive strategies. This project is a multicenter prospective cohort study of adults with CKD or AKI who undergo a protocol kidney biopsy for research purposes. This investigation focuses on kidney diseases that are most prevalent and therefore substantially burden the public health, including CKD attributed to diabetes or hypertension and AKI attributed to ischemic and toxic injuries. Reference kidney tissues (for example, living-donor kidney biopsies) will also be evaluated. Traditional and digital pathology will be combined with transcriptomic, proteomic, and metabolomic analysis of the kidney tissue as well as deep clinical phenotyping for supervised and unsupervised subgroup analysis and systems biology analysis. Participants will be followed prospectively for 10 years to ascertain clinical outcomes. Cell types, locations, and functions will be characterized in health and disease in an open, searchable, online kidney tissue atlas. All data from the Kidney Precision Medicine Project will be made readily available for broad use by scientists, clinicians, and patients.

Proximal Tubular Oxidative Metabolism in Acute Kidney Injury and the Transition to CKD.

The proximal tubule relies on oxidative mitochondrial metabolism to meet its energy needs and has limited capacity for glycolysis, which makes it uniquely susceptible to damage during AKI, especially after ischemia and anoxia. Under these conditions, mitochondrial ATP production is initially decreased by several mechanisms, including fatty acid-induced uncoupling and inhibition of respiration related to changes in the shape and volume of mitochondria. Glycolysis is initially insufficient as a source of ATP to protect the cells and mitochondrial function, but supplementation of tricarboxylic acid cycle intermediates augments anaerobic ATP production, and improves recovery of mitochondrial oxidative metabolism. Incomplete recovery is characterized by defects of respiratory enzymes and lipid metabolism. During the transition to CKD, tubular cells atrophy but maintain high expression of glycolytic enzymes, and there is decreased fatty acid oxidation. These metabolic changes may be amenable to a number of therapeutic interventions.

SARS-CoV-2 receptor networks in diabetic and COVID-19-associated kidney disease.

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.

Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project.

An important need exists to better understand and stratify kidney disease according to its underlying pathophysiology in order to develop more precise and effective therapeutic agents. National collaborative efforts such as the Kidney Precision Medicine Project are working towards this goal through the collection and integration of large, disparate clinical, biological and imaging data from patients with kidney disease. Ontologies are powerful tools that facilitate these efforts by enabling researchers to organize and make sense of different data elements and the relationships between them. Ontologies are critical to support the types of big data analysis necessary for kidney precision medicine, where heterogeneous clinical, imaging and biopsy data from diverse sources must be combined to define a patient's phenotype. The development of two new ontologies - the Kidney Tissue Atlas Ontology and the Ontology of Precision Medicine and Investigation - will support the creation of the Kidney Tissue Atlas, which aims to provide a comprehensive molecular, cellular and anatomical map of the kidney. These ontologies will improve the annotation of kidney-relevant data, and eventually lead to new definitions of kidney disease in support of precision medicine.

The role of renal hypoxia in the pathogenesis of diabetic kidney disease: a promising target for newer renoprotective agents including SGLT2 inhibitors?

Diabetic kidney disease is the most common cause of end-stage kidney disease and poses a major global health problem. Finding new, safe, and effective strategies to halt this disease has proven to be challenging. In part that is because the underlying mechanisms are complex and not fully understood. However, in recent years, evidence has accumulated suggesting that chronic hypoxia may be the primary pathophysiological pathway driving diabetic kidney disease and chronic kidney disease of other etiologies and was called the chronic hypoxia hypothesis. Hypoxia is the result of a mismatch between oxygen delivery and oxygen demand. The primary determinant of oxygen delivery is renal perfusion (blood flow per tissue mass), whereas the main driver of oxygen demand is active sodium reabsorption. Diabetes mellitus is thought to compromise the oxygen balance by impairing oxygen delivery owing to hyperglycemia-associated microvascular damage and exacerbate oxygen demand owing to increased sodium reabsorption as a result of sodium-glucose cotransporter upregulation and glomerular hyperfiltration. The resultant hypoxic injury creates a vicious cycle of capillary damage, inflammation, deposition of the extracellular matrix, and, ultimately, fibrosis and nephron loss. This review will frame the role of chronic hypoxia in the pathogenesis of diabetic kidney disease and its prospect as a promising therapeutic target. We will outline the cellular mechanisms of hypoxia and evidence for renal hypoxia in animal and human studies. In addition, we will highlight the promise of newer imaging modalities including blood oxygenation level-dependent magnetic resonance imaging and discuss salutary interventions such as sodium-glucose cotransporter 2 inhibition that (may) protect the kidney through amelioration of renal hypoxia.

SARS-CoV-2 receptor networks in diabetic and COVID-19 associated kidney disease.

COVID-19 morbidity and mortality is increased in patients with diabetes and kidney disease via unknown mechanisms. SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2) for entry into host cells. Since ACE2 is a susceptibility factor for infection, we investigated how diabetic kidney disease (DKD) and medications alter ACE2 receptor expression in kidneys. Single cell RNA profiling of healthy living donor (LD) and DKD kidney biopsies revealed ACE2 expression primarily in proximal tubular epithelial cells (PTEC). This cell specific localization was confirmed by in situ hybridization. ACE2 expression levels were unaltered by exposures to renin angiotensin aldosterone system inhibitors in DKD. Bayesian integrative analysis of a large compendium of public -omics datasets identified molecular network modules induced in ACE2-expressing PTEC in DKD (searchable at hb.flatironinstitute.org/covid-kidney) that were linked to viral entry, immune activation, endomembrane reorganization, and RNA processing. The DKD ACE2-positive PTEC module overlapped with expression patterns seen in SARS-CoV-2 infected cells. Similar cellular programs were seen in ACE2-positive PTEC obtained from urine samples of 13 COVID-19 patients who were hospitalized, suggesting a consistent ACE2-coregulated PTEC 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.

Systems Biology and Kidney Disease.

The kidney is a complex organ responsible for maintaining multiple aspects of homeostasis in the human body. The combination of distinct, yet interrelated, molecular functions across different cell types make the delineation of factors associated with loss or decline in kidney function challenging. Consequently, there has been a paucity of new diagnostic markers and treatment options becoming available to clinicians and patients in managing kidney diseases. A systems biology approach to understanding the kidney leverages recent advances in computational technology and methods to integrate diverse sets of data. It has the potential to unravel the interplay of multiple genes, proteins, and molecular mechanisms that drive key functions in kidney health and disease. The emergence of large, detailed, multilevel biologic and clinical data from national databases, cohort studies, and trials now provide the critical pieces needed for meaningful application of systems biology approaches in nephrology. The purpose of this review is to provide an overview of the current state in the evolution of the field. Recent successes of systems biology to identify targeted therapies linked to mechanistic biomarkers in the kidney are described to emphasize the relevance to clinical care and the outlook for improving outcomes for patients with kidney diseases.

Atypical Presentation of Pregnancy-Related Hemolytic Uremic Syndrome.

The cause of acute kidney injury during pregnancy and in the postpartum period can be particularly challenging to diagnose, especially when it is necessary to differentiate among preeclampsia; eclampsia; hemolysis, elevated liver enzymes and low platelets (HELLP) syndrome; and thrombotic microangiopathies (TMAs). All these disease entities can present with kidney failure, microangiopathic hemolytic anemia, and thrombocytopenia. We present a teaching case of atypical hemolytic uremic syndrome in the postpartum period in a young woman who was found to have mutations of uncertain clinical significance in the complement cascade, including in C3, CFH, and CFI. We use this as an opportunity to review the clinical presentation and pathophysiology of preeclampsia, eclampsia, and the TMAs. We focus on diagnostic challenges, especially because many patients with TMA do not present with thrombocytopenia, which can delay diagnosis. We additionally review the clinical settings in which administration of eculizumab, a C5 membrane attack complex inhibitor, is appropriate.

A Genome-Wide Association Study to Identify Single-Nucleotide Polymorphisms for Acute Kidney Injury.

RATIONALE: Acute kidney injury is a common and severe complication of critical illness and cardiac surgery. Despite significant attempts at developing treatments, therapeutic advances to attenuate acute kidney injury and expedite recovery have largely failed. OBJECTIVES: Identifying genetic loci associated with increased risk of acute kidney injury may reveal novel pathways for therapeutic development. METHODS: We conducted an exploratory genome-wide association study to identify single-nucleotide polymorphisms associated with genetic susceptibility to in-hospital acute kidney injury. MEASUREMENTS AND MAIN RESULTS: We genotyped 609,508 single-nucleotide polymorphisms and performed genotype imputation in 760 acute kidney injury cases and 669 controls. We then evaluated polymorphisms that showed the strongest association with acute kidney injury in a replication patient population containing 206 cases with 1,406 controls. We observed an association between acute kidney injury and four single-nucleotide polymorphisms at two independent loci on metaanalysis of discovery and replication populations. These include rs62341639 (metaanalysis P = 2.48 × 10-7; odds ratio [OR], 0.64; 95% confidence interval [CI], 0.55-0.76) and rs62341657 (P = 3.26 × 10-7; OR, 0.65; 95% CI, 0.55-0.76) on chromosome 4 near APOL1-regulator IRF2, and rs9617814 (metaanalysis P = 3.81 × 10-6; OR, 0.70; 95% CI, 0.60-0.81) and rs10854554 (P = 6.53 × 10-7; OR, 0.67; 95% CI, 0.57-0.79) on chromosome 22 near acute kidney injury-related gene TBX1. CONCLUSIONS: Our findings reveal two genetic loci that are associated with acute kidney injury. Additional studies should be conducted to functionally evaluate these loci and to identify other common genetic variants contributing to acute kidney injury.

Biomarkers of acute kidney injury and associations with short- and long-term outcomes.

Acute kidney injury is strongly associated with increased mortality and other adverse outcomes. Medical researchers have intensively investigated novel biomarkers to predict short- and long-term outcomes of acute kidney injury in many patient care settings, such as cardiac surgery, intensive care units, heart failure, and transplant. Future research should focus on leveraging this relationship to improve enrollment for clinical trials of acute kidney injury.