Geographic and Temporal Trends in COVID-Associated Acute Kidney Injury in the National COVID Cohort Collaborative.

BACKGROUND: AKI is associated with mortality in patients hospitalized with coronavirus disease 2019 (COVID-19); however, its incidence, geographic distribution, and temporal trends since the start of the pandemic are understudied. METHODS: Electronic health record data were obtained from 53 health systems in the United States in the National COVID Cohort Collaborative. We selected hospitalized adults diagnosed with COVID-19 between March 6, 2020, and January 6, 2022. AKI was determined with serum creatinine and diagnosis codes. Time was divided into 16-week periods (P1-6) and geographical regions into Northeast, Midwest, South, and West. Multivariable models were used to analyze the risk factors for AKI or mortality. RESULTS: Of a total cohort of 336,473, 129,176 (38%) patients had AKI. Fifty-six thousand three hundred and twenty-two (17%) lacked a diagnosis code but had AKI based on the change in serum creatinine. Similar to patients coded for AKI, these patients had higher mortality compared with those without AKI. The incidence of AKI was highest in P1 (47%; 23,097/48,947), lower in P2 (37%; 12,102/32,513), and relatively stable thereafter. Compared with the Midwest, the Northeast, South, and West had higher adjusted odds of AKI in P1. Subsequently, the South and West regions continued to have the highest relative AKI odds. In multivariable models, AKI defined by either serum creatinine or diagnostic code and the severity of AKI was associated with mortality. CONCLUSIONS: The incidence and distribution of COVID-19-associated AKI changed since the first wave of the pandemic in the United States.

Cross-validation of SARS-CoV-2 responses in kidney organoids and clinical populations.

Kidneys are critical target organs of COVID-19, but susceptibility and responses to infection remain poorly understood. Here, we combine SARS-CoV-2 variants with genome-edited kidney organoids and clinical data to investigate tropism, mechanism, and therapeutics. SARS-CoV-2 specifically infects organoid proximal tubules among diverse cell types. Infections produce replicating virus, apoptosis, and disrupted cell morphology, features of which are revealed in the context of polycystic kidney disease. Cross-validation of gene expression patterns in organoids reflects proteomic signatures of COVID-19 in the urine of critically ill patients indicating interferon pathway upregulation. SARS-CoV-2 viral variants alpha, beta, gamma, kappa, and delta exhibit comparable levels of infection in organoids. Infection is ameliorated in ACE2-/- organoids and blocked via treatment with de novo-designed spike binder peptides. Collectively, these studies clarify the impact of kidney infection in COVID-19 as reflected in organoids and clinical populations, enabling assessment of viral fitness and emerging therapies.

Repurposing Didanosine as a Potential Treatment for COVID-19 Using Single-Cell RNA Sequencing Data.

As of today (7 April 2020), more than 81,000 people around the world have died from the coronavirus disease 19 (COVID-19) pandemic. There is no approved drug or vaccine for COVID-19, although more than 10 clinical trials have been launched to test potential drugs. In an urgent response to this pandemic, I developed a bioinformatics pipeline to identify compounds and drug candidates to potentially treat COVID-19. This pipeline is based on publicly available single-cell RNA sequencing (scRNA-seq) data and the drug perturbation database "Library of Integrated Network-Based Cellular Signatures" (LINCS). I developed a ranking score system that prioritizes these drugs or small molecules. The four drugs with the highest total score are didanosine, benzyl-quinazolin-4-yl-amine, camptothecin, and RO-90-7501. In conclusion, I have demonstrated the utility of bioinformatics for identifying drugs than can be repurposed for potentially treating COVID-19 patients.