Genome-wide association analyses of common infections in a large practice-based biobank

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Abstract

Introduction: Infectious diseases are common causes of morbidity and mortality worldwide. Susceptibility to infection is highly heritable; however, little has been done to identify the genetic determinants underlying common infectious diseases. One GWAS was performed using 23andMe information about self-reported infections; we set out to confirm previous loci and identify new ones using medically diagnosed infections. Methods: We used the electronic health record (EHR)-based biobank at Vanderbilt and diagnosis codes to identify cases of 12 infectious diseases in white patients: urinary tract infection, pneumonia, chronic sinus infections, otitis media, candidiasis, streptococcal pharyngitis, herpes zoster, herpes labialis, hepatitis B, infectious mononucleosis, tuberculosis (TB) or a positive TB test, and hepatitis C. We selected controls from patients with no diagnosis code for the candidate disease and matched by year of birth, sex, and calendar year at first and last EHR visits. We conducted GWAS using SAIGE and transcriptome-wide analysis (TWAS) using S-PrediXcan. We also conducted phenome-wide association study to understand associations between identified genetic variants and clinical phenotypes. Results: We replicated three 23andMe loci (p ≤ 0.05): herpes zoster and rs7047299-A (p = 2.6 × 10–3) and rs2808290-C (p = 9.6 × 10–3;); otitis media and rs114947103-C (p = 0.04). We also identified 2 novel regions (p ≤ 5 × 10–8): rs113235453-G for otitis media (p = 3.04 × 10–8), and rs10422015-T for candidiasis (p = 3.11 × 10–8). In TWAS, four gene-disease associations were significant: SLC30A9 for otitis media (p = 8.06 × 10–7); LRP3 and WDR88 for candidiasis (p = 3.91 × 10–7 and p = 1.95 × 10–6); and AAMDC for hepatitis B (p = 1.51 × 10–6). Conclusion: We conducted GWAS and TWAS for 12 infectious diseases and identified novel genetic contributors to the susceptibility of infectious diseases.

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Jiang, L., Kerchberger, V. E., Shaffer, C., Dickson, A. L., Ormseth, M. J., Daniel, L. L., … Feng, Q. P. (2022). Genome-wide association analyses of common infections in a large practice-based biobank. BMC Genomics, 23(1). https://doi.org/10.1186/s12864-022-08888-9

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