C allele of rs479200 of the host EGLN1 gene - a risk factor for severe COVID-19 (pilot study)
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Abstract
Background
Coronavirus disease-2019 (COVID-19) symptoms can range from asymptomatic, moderate to severe manifestations that result in an overall global case fatality rate of 2-7 %. While each variant has had it challenges, and some variants are more severe than others, risk factors of severe COVID-19 are still under investigation. In this context, the host genetic predisposition is also a crucial factor to investigate. In the present study, we investigated host genotypes of the SNP rs479200 of the host EGLN1 gene, previously implicated in high altitude pulmonary edema (HAPE), some of whose symptoms such as hypoxia profoundly overlap with severe COVID-19.
Methods
After informed consent, 158 RT-PCR confirmed COVID-19 patients (March 2020 to June 2021) were enrolled in the study. Based on their clinical manifestations, disease severity was categorized by the clinical team. Blood samples were drawn and DNA was extracted from the clot to infer different genotypes of the SNP rs479200 of the host EGLN1 gene. PCR-RFLP analysis of the SNP rs479200 (C > T) was performed with an amplicon size of 367 bp. Various genotypes (TT, TC and CC) were assigned based on the presence/absence of a restriction site (T/GTACA) for restriction enzyme BsrGI . Allele frequencies, Hardy-Weinberg Equilibrium (HWE) and multinomial logistic regression were performed using statistical tool SPSS version 23 (IBM).
Findings
We observed that the severe COVID-19 category was composed of comparatively younger patients with mean age (34.9±15.6), compared to asymptomatic and moderate categories whose mean age was 49.7±17.9 and 54.3±15.7, respectively. Preponderance of males and high heterozygosity (TC) was observed across the clinical categories. Notably, the frequency of C allele (0.664) was 2-fold higher than the T allele (0.336) in severe COVID-19 patients, whereas the allele frequencies were similar in asymptomatic and moderate category of COVID-19 patients. Multinomial logistic regression showed an association of genotypes with increasing clinical severity; odds ratio (adjusted OR-11.414 (2.564-50.812)) and (unadjusted OR-6.214 (1.84-20.99)) for the genotype CC in severe category of COVID-19. Interestingly, the TC genotype was also found to be positively associated with severe outcome (unadjusted OR-5.816 (1.489-22.709)), indicating association of C allele in imparting the risk of severe outcome.
Interpretation
The study provides strong evidence that the presence of C allele of SNP (rs479200) of the EGLN1 gene associates with severity in COVID-19 patients. Thus, the presence of C allele may be a risk factor for COVID-19 severity. This study opens new avenues towards risk assessment that include EGLN1 (rs479200) genotype testing and identifying patients with C allele who might be prioritized for critical care.
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SciScore for 10.1101/2022.03.11.22272214: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IACUC: The study was approved by the Institutional Ethics Committees (IECs), AIIMS, Raipur [1379/IEC-AIIMSRPR/2020] & ICMR-NIMR, Delhi [PHB/NIMR/EC/2020/145]. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources Statistical analysis: The study data was fed in Microsoft Excel 365 and cross checked by two independent researchers. Microsoft Excelsuggested: (Microsoft Excel, RRID:SCR_016137)The statistical and association analysis was performed using the SPSS version 23 (IBM). SPSSsuggested: (SPSS, RRID:SCR_002865)Results from OddPub: We did not detect open data. We also did …
SciScore for 10.1101/2022.03.11.22272214: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IACUC: The study was approved by the Institutional Ethics Committees (IECs), AIIMS, Raipur [1379/IEC-AIIMSRPR/2020] & ICMR-NIMR, Delhi [PHB/NIMR/EC/2020/145]. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources Statistical analysis: The study data was fed in Microsoft Excel 365 and cross checked by two independent researchers. Microsoft Excelsuggested: (Microsoft Excel, RRID:SCR_016137)The statistical and association analysis was performed using the SPSS version 23 (IBM). SPSSsuggested: (SPSS, RRID:SCR_002865)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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