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Updated: May 28, 2026

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
Multi-Layered Genomic and Clinical Analysis Identifies Novel Variants, Co-Occurring Single Nucleotide Polymorphism
Doris Repušić1, Marina Korolija2,3, Ana Livun2
1Bioinformatics Group, Division of Molecular Biology, Department of Biology, Faculty of Science, University of Zagreb, Zagreb, Croatia.
Abstract:
Host genetic factors may contribute to COVID-19 severity. To identify genetic variants influencing COVID-19 severity progression, whole-exome sequencing was performed, followed by an exome-wide association study on 191 hospitalized patients categorized into three severity groups. The analysis identified nine loci surpassing the suggestive significance threshold (p ≤ 3 × 10-4): rs2180196 (β = 2.09, TGM1-RABGGTA), rs2236232 (β = -1.37, PLEKHH1), rs7886938 (β = 1.66, FMO6P), rs2929047 (β = -1.16, XKR4), rs9841237 (β = 1.21, SI), rs34357454 (β = 1.92, NID2), rs1005887 (β = 1.28, DUSP18), rs2281880 (β = -1.11, SUFU), and rs73061693 (β = 1.66, TULP2). Furthermore, binomial exact test identified 218 SNPs in COVID-19-related genes with significant allele frequency differences between severity groups, including 61 novel variants. Of those 218, co-occurring SNP pairs were identified within specific severity groups, including pairs in JAK1-PIK3R2 in critical patients and eight pairs in genes IL6, SERPINE1, COL5A1, MAPK14, FREM1, C7, GLS, ATP5PO, and RPL7 in severe patients. Clinical data analysis confirmed known risk factors like older age in men and specific comorbidities and revealed distinct therapeutic and biochemical profiles across severity groups. This study confirms known genetic risks and reveals novel variants, providing a more detailed basis for understanding COVID-19 pathogenesis and for developing genetic diagnostic and prognostic biomarkers.
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