Temporal Transcriptomics in Hospitalized COVID-19 Patients from Disparately Impacted Ancestral Groups for Therapeutic Discovery

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PROJECT SUMMARY SARS-CoV-2 is a novel coronavirus which causes COVID-19, a disease that has infected >46M people resulting in >1.2M deaths by 31 October 2020. The US has the highest global case count (>9.2M) and mortality (>230K) with recent record-setting daily cases and hospitalization rates across the country. This has been particularly true for New Mexico (NM) where cases and hospitalizations are surging again. It is now recognized that certain minority groups, i.e., African Americans, Hispanics, and American Indians/Alaska Natives (AI/AN), suffer disproportionally from COVID-19. NM has the highest proportion of Hispanic ancestry, and one of the largest AI/AN populations, with these two groups representing 47% and 26% of the cumulative cases, respectively. After adjusting for population size, the AI/AN group has 3.3-fold higher cumulative case rates, 7.9-fold higher hospitalizations, and 10.6-fold higher age-adjusted mortality rates. As the only academic medical center and Level 1 Trauma Center in the state, the University of New Mexico Hospital (UNMH) has played a principal role in caring for patients with COVID-19. UNMH is the primary tertiary care referral center for NM and surrounding regions, including the Navajo Nation and other tribal lands. As such, we are uniquely positioned to address important gaps-in-knowledge about the molecular basis of increased COVID-19 disease severity and mortality in disproportionally affected ancestral groups. In mid-February, the UNM Center for Global Health assembled a multidisciplinary group of investigators to address the challenges of COVID-19. As of 31 October, we have recruited and followed 167 hospitalized patients with COVID-19, offering an opportunity for rapid translational impact within the planned three-year study. The experimental strategy parallels our ongoing R01 studies in African children utilizing mRNA-Seq to identify novel therapeutic targets (PI: Perkins). State-of-the-art methodologies and modeling efforts in place in our laboratories will be applied to create solutions for improving outcomes in COVID-19 patients. This will be achieved by following non-severe and severe COVID-19 patients across hospitalization from different ancestral groups to successfully complete three specific aims: 1) determine the impact of SARS-CoV-2 viral load dynamics on disease severity, 2) identify gene expression networks that mediate disease severity, and 3) identify prioritized FDA-approved compounds that modulate gene networks associated with enhanced disease severity for use in future clinical trials. In a short time, we have generated extensive data on viral load dynamics and identified novel gene networks with target-compound matches. We present data showing that individuals of AI/AN descent have significantly higher and protracted viral loads in peripheral blood and more severe disease, despite comparable co-morbid factors with other groups. The proposed investigations have direct translational impact, particularly in disproportionately affected ancestral groups by defining the host immune response to SARS-CoV-2, identifying biomarkers for risk assessment, prognosis, and disease progression, and fostering drug repurposing to reduce disease severity and mortality.