MD/PhD student Louisiana State University Health, New Orleans Metairie, Louisiana, United States
Disclosure(s):
Grace Kim: No financial relationships to disclose
Introduction/Rationale: We investigated the relationship between imputed human leukocyte antigen (HLA) alleles to COVID-19 clinical severity within the NIH funded All of Us dataset, which integrates electronic health records and genomic sequences of enrolled participants.
Methods: The base population was defined as any participant who had been administered a SARS-CoV-2 test and provided genomic sequencing data (n=113,015). Cohorts were refined by COVID-19 conditions: (1) a positive COVID-19 test (n=20,872), (2) a negative COVID-19 test (n= 88,680), (3) both a positive test and an ICD-10 diagnosis code for pneumonia due to COVID-19 or lower respiratory infection caused by SARS-CoV-2 (n= 1,079), (4) a positive test and a diagnosis code for Long COVID (n= 509), and (5) ONLY and at least 3 positive COVID-19 tests (n= 1,298), and (6) ONLY and at least 3 negative COVID-19 tests (n=4,884). HLA Class I and Class II allele imputation utilized a global diversity reference panel utilizing the HIBAG “R” package with a median posterior probability rate greater than 92.7% for the 6 HLA alleles.
Results: Through this approach, we found several alleles significantly associated with protection from and increased risk of severe COVID-19 infection.
Conclusion: Our findings expand the limited clinical research on the role of HLA haplotypes in the response to SARS-CoV-2, underscoring the usefulness of large, multi-ancestral clinical and molecular datasets in generating testable hypotheses that have potentially significant clinical applications
