Precision Medicine Discovers Underlying Risk Factors for Severe COVID Infection in Latinx Population

Winter 2021


American Association for the Advancement of Science
American Association for the Advancement of Science

Tim Chang, MD, PhD
Assistant Professor of Neurology

Drs. Timothy Chang and Daniel Geschwind are neurology faculty focused on understanding the causes of dementia, autism and Parkinson’s Disease. They are experts in precision health (a field of science that targets treatment based on patients’ genes, lifestyle and environment). When the pandemic hit, Chang and Geschwind and their colleagues began using electronic health record (EHR) data at UCLA to understand pre-existing conditions that were risk factors for COVID-19. Soon after, other states that were initially hardest hit by COVID-19 began to publish studies about severe outcomes among hospitalized patients, but without considering race or ethnicity. As reports of worse COVID-19 outcomes for minority groups surfaced, the UCLA researchers recognized it would be critical to understand pre-existing conditions that were risk factors for COVID-19 in Hispanics/Latinx patients (HL). Twenty percent of UCLA Health’s patient population identifies as HL, so there were ample data for this analysis.

Drs. Chang and Geschwind and colleagues are the first group at UCLA to utilize UCLA Health’s de-identified data (data uncoupled from all personal patient information). This dataset includes EHR information from 1.5 million patients seen at UCLA Health since 2013. The study included 58,901 individuals that were tested for COVID-19 and 1,994 that tested positive from March 2020 to August 2020. The study showed significant evidence in a number of areas:

  • Disease severity: HL patients constituted an increasing percentage of all COVID-19 positive individuals as disease severity escalated, a disparity that remained after correcting for pre-existing diseases.
  • Renal disease: Multiple risk factors identified in Non-Hispanic/Latinx whites (non-HL-W), like renal disease, also conveyed risk in HL patients.
  • Cardiac disorder: Pre-existing nonrheumatic mitral valve disorder was a risk factor to HL patient hospitalization but not for non-HL-W COVID-19 patients or a comparable group of HL patients with influenza hospitalization, suggesting that this cardiac condition may unexpectedly be a specific HL patient risk for severe COVID-19 disease.
  • Inflammation: Admission laboratory values also suggested that HL patients presented with a greater inflammatory response.

These results show that while some pre-existing conditions are shared risk factors for COVID-19 hospitalization among all individuals, there are risk factors that are specific to minority groups. Future work will be necessary to validate HL-patient-specific risk factors such as mitral valve disorders and determine the mechanism of association. The researchers are also studying what genetic risk factors may predispose individuals to have worse COVID-19 outcomes.
These findings are an important first step. Now it’s essential to address these risk factors and ultimately reduce health disparities.

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