BackgroundCoronavirus disease 2019 (COVID-19) is thought to cause kidney injury by a variety of mechanisms. To date, pathologic analyses have been limited to patient reports and autopsy series.MethodsWe evaluated biopsy samples of native and allograft kidneys from patients with COVID-19 at a single center in New York City between March and June of 2020. We also used immunohistochemistry, in situ hybridization, and electron microscopy to examine this tissue for presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).ResultsThe study group included 17 patients with COVID-19 (12 men, 12 black; median age of 54 years). Sixteen patients had comorbidities, including hypertension, obesity, diabetes, malignancy, or a kidney or heart allograft. Nine patients developed COVID-19 pneumonia. Fifteen patients (88%) presented with AKI; nine had nephrotic-range proteinuria. Among 14 patients with a native kidney biopsy, 5 were diagnosed with collapsing glomerulopathy, 1 was diagnosed with minimal change disease, 2 were diagnosed with membranous glomerulopathy, 1 was diagnosed with crescentic transformation of lupus nephritis, 1 was diagnosed with anti-GBM nephritis, and 4 were diagnosed with isolated acute tubular injury. The three allograft specimens showed grade 2A acute T cell–mediated rejection, cortical infarction, or acute tubular injury. Genotyping of three patients with collapsing glomerulopathy and the patient with minimal change disease revealed that all four patients had APOL1 high-risk gene variants. We found no definitive evidence of SARS-CoV-2 in kidney cells. Biopsy diagnosis informed treatment and prognosis in all patients.ConclusionsPatients with COVID-19 develop a wide spectrum of glomerular and tubular diseases. Our findings provide evidence against direct viral infection of the kidneys as the major pathomechanism for COVID-19–related kidney injury and implicate cytokine-mediated effects and heightened adaptive immune responses.

The novel coronavirus SARS-CoV-2 (coronavirus disease 19, or COVID-19) primarily causes pulmonary injury, but has been implicated to cause hepatic injury, both by serum markers and histologic evaluation. The histologic pattern of injury has not been completely described. Studies quantifying viral load in the liver are lacking. Here we report the clinical and histologic findings related to the liver in 40 patients who died of complications of COVID-19. A subset of liver tissue blocks were subjected to polymerase chain reaction (PCR) for viral ribonucleic acid (RNA). Peak levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were elevated; median ALT peak 68 U/l (normal up to 46 U/l) and median AST peak 102 U/l (normal up to 37 U/l). Macrovesicular steatosis was the most common finding, involving 30 patients (75%). Mild lobular necroinflammation and portal inflammation were present in 20 cases each (50%). Vascular pathology, including sinusoidal microthrombi, was infrequent, seen in six cases (15%). PCR of liver tissue was positive in 11 of 20 patients tested (55%). In conclusion, we found patients dying of COVID-19 had biochemical evidence of hepatitis (of variable severity) and demonstrated histologic findings of macrovesicular steatosis and mild acute hepatitis (lobular necroinflammation) and mild portal inflammation. We also identified viral RNA in a sizeable subset of liver tissue samples.

BackgroundAKI is common among hospitalized patients with coronavirus disease 2019 (COVID-19) and is an independent risk factor for mortality. Although there are numerous potential mechanisms underlying COVID-19–associated AKI, our current knowledge of kidney pathologic findings in COVID-19 is limited.MethodsWe examined the postmortem kidneys from 42 patients who died of COVID-19. We reviewed light microscopy findings in all autopsies and performed immunofluorescence, electron microscopy, and in situ hybridization studies for SARS-CoV-2 on a subset of samples.ResultsThe cohort had a median age of 71.5 years (range, 38–97 years); 69% were men, 57% were Hispanic, and 73% had a history of hypertension. Among patients with available data, AKI developed in 31 of 33 patients (94%), including 6 with AKI stage 1, 9 with stage 2, and 16 with stage 3. The predominant finding correlating with AKI was acute tubular injury. However, the degree of acute tubular injury was often less severe than predicted for the degree of AKI, suggesting a role for hemodynamic factors, such as aggressive fluid management. Background changes of hypertensive arterionephrosclerosis and diabetic glomerulosclerosis were frequent but typically mild. We identified focal kidney fibrin thrombi in 6 of 42 (14%) autopsies. A single Black patient had collapsing FSGS. Immunofluorescence and electron microscopy were largely unrevealing, and in situ hybridization for SARS-CoV-2 showed no definitive positivity.ConclusionsAmong a cohort of 42 patients dying with COVID-19, autopsy histologic evaluation revealed acute tubular injury, which was typically mild relative to the degree of creatinine elevation. These findings suggest potential for reversibility upon resolution of SARS-CoV-2 infection.

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Transplantable kidneys are in very limited supply. Accurate viability assessment prior to transplantation could minimize organ discard. Rapid and accurate evaluation of intra-operative donor kidney biopsies is essential for determining which kidneys are eligible for transplantation. The criterion for accepting or rejecting donor kidneys relies heavily on pathologist determination of the percent of glomeruli (determined from a frozen section) that are normal and sclerotic. This percentage is a critical measurement that correlates with transplant outcome. Inter- and intra-observer variability in donor biopsy evaluation is, however, significant. An automated method for determination of percent global glomerulosclerosis could prove useful in decreasing evaluation variability, increasing throughput, and easing the burden on pathologists. Here, we describe the development of a deep learning model that identifies and classifies non-sclerosed and sclerosed glomeruli in whole-slide images of donor kidney frozen section biopsies. This model extends a convolutional neural network (CNN) pre-trained on a large database of digital images. The extended model, when trained on just 48 whole slide images, exhibits slide-level evaluation performance on par with expert renal pathologists. Encouragingly, the model's performance is robust to slide preparation artifacts associated with frozen section preparation. The model substantially outperforms a model trained on image patches of isolated glomeruli, in terms of both accuracy and speed. The methodology overcomes the technical challenge of applying a pretrained CNN bottleneck model to whole-slide image classification. The traditional patch-based approach, while exhibiting deceptively good performance classifying isolated patches, does not translate successfully to whole-slide image segmentation in this setting. As the first model reported that identifies and classifies normal and sclerotic glomeruli in frozen kidney sections, and thus the first model reported in the literature relevant to kidney transplantation, it may become an essential part of donor kidney biopsy evaluation in the clinical setting.