Proteomic Characterization of Acute Kidney Injury in Patients Hospitalized with SARS-CoV2 Infection

Background: Acute kidney injury (AKI) is a known complication of COVID-19 and is associated with an increased risk of in-hospital mortality. Unbiased proteomics using biological specimens can lead to improved risk stratification and discover pathophysiological mechanisms. Methods: Using measurements of ~4000 plasma proteins in two cohorts of patients hospitalized with COVID-19, we discovered and validated markers of COVID-associated AKI (stage 2 or 3) and long-term kidney dysfunction. In the discovery cohort (N= 437), we identified 413 higher plasma abundances of protein targets and 40 lower plasma abundances of protein targets associated with COVID-AKI (adjusted p <0.05). Of these, 62 proteins were validated in an external cohort (p <0.05, N =261). Results: We demonstrate that COVID-AKI is associated with increased markers of tubular injury (NGAL) and myocardial injury. Using estimated glomerular filtration (eGFR) measurements taken after discharge, we also find that 25 of the 62 AKI-associated proteins are significantly associated with decreased post-discharge eGFR (adjusted p <0.05). Proteins most strongly associated with decreased post-discharge eGFR included desmocollin-2, trefoil factor 3, transmembrane emp24 domain-containing protein 10, and cystatin-C indicating tubular dysfunction and injury. Conclusions: Using clinical and proteomic data, our results suggest that while both acute and long-term COVID-associated kidney dysfunction are associated with markers of tubular dysfunction, AKI is driven by a largely multifactorial process involving hemodynamic instability and myocardial damage. We used serum protein measurements from patients hospitalized with COVID-19. We defined an AKI cohort using proteomic data acquired at the last available timepoint during the hospital course for all individuals. Controls were defined as individuals who developed AKI stage 1 or did not develop AKI during their hospital course. We used the SomaScan discovery platform to quantify levels of protein expression. See https://www.synapse.org/#!Synapse:syn35874390/ for full clinical data and associated metadata including detailed description for process workflow. Submitter states: The raw data files are .adat files and contain identifiable sample IDs that cannot be deidentified in the adat file. Therefore the raw data files will not be provided.