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COVID-19 relevant genetic variants confirmed in an admixed population

Texis, T.; Cruz-Jaramilllo, J. L.; Garcia-Munoz, W.; Anzures-Cortes, L.; Hadadd-Talancon, L.; Sanchez-Garcia, S.; Jimenez-Martinez, M. d. C.; Perez-Barragan, E.; Nieto-Patlan, A.; Martinez-Ezquerro, J. D.; Rubio-Carrasco, K.; Rodriguez-Dorantes, M.; Cortes-Ramirez, S.; Mellado-Sanchez, G.; Perez-Tapia, S. M.; Gonzalez-Covarrubias, V.

2022-04-16 genetic and genomic medicine
10.1101/2022.04.15.22273925 medRxiv
Show abstract

The dissection of factors that contribute to COVID-19 infection and severity has overwhelmed the scientific community for almost 2 years. Current reports highlight the role of in disease incidence, progression, and severity. Here, we aimed to confirm the presence of previously reported genetic variants in an admixed population. Allele frequencies were assessed and compared between the general population (N=3079) for which at least 30% have not been infected with SARS-CoV2 as per July 2021 versus COVID-19 patients (N=106). Genotyping data from the Illumina GSA array was used to impute genetic variation for 14 COVID-relevant genes, using the 1000G phase 3 as reference based on the human genome assembly hg19, following current standard protocols and recommendations for genetic imputation. Bioinformatic and statistical analyses were performed using MACH v1.0, R, and PLINK. A total of 7953 variants were imputed on, ABO, CCR2, CCR9, CXCR6, DPP9, FYCO1, IL10RB/IFNAR2, LZTFL1, OAS1, OAS2, OAS3, SLC6A20, TYK2, and XCR1. Statistically significant allele differences were reported for 10 and 7 previously identified and confirmed variants, ABO rs657152, DPP9 rs2109069, LZTFL1 rs11385942, OAS1 rs10774671, OAS1 rs2660, OAS2 rs1293767, and OAS3 rs1859330 p<0.03. In addition, we identified 842 variants in these COVID-related genes with significant allele frequency differences between COVID patients and the general population (p-value <E-2 - E-179). Our observations confirm the presence of genetic differences in COVID-19 patients in an admixed population and prompts for the investigation of the statistical relevance of additional variants on these and other genes that could identify local and geographical patterns of COVID-19.

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