JOURNAL ARTICLE
Genetic polymorphisms of ACE insertion/deletion, TNF-α (-308G>A), and IL-6 (-572G/C) in among recurrent COVID-19 subjects.
Published In: Minerva Biotechnology & Biomolecular Research, 2026, v. 38, n. 1. P. 4 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: KOYOU, Haily L.; RAMACHANDRAN, Vasudevan; SALLEH, Mohd N.; MOHAMAD, Nur A.; MOHD NAZIRUL FIKRI, Maizatul A.; HASHIM, Noramira A.; SAMSUL ANUAR, Nurfarahana; AYOB, Azizi 3 of 3
Abstract
This article investigates the association of genetic polymorphisms in the angiotensin-converting enzyme (ACE) insertion/deletion (I/D), tumor necrosis factor-alpha (TNF-α) -308G>A, and interleukin-6 (IL-6) -572G/C genes with susceptibility to recurrent COVID-19 infections in a Malaysian population. In a case-control study of 120 participants (60 with recurrent COVID-19 confirmed by RT-PCR at least 90 days apart and 60 SARS-CoV-2-negative controls), significant associations were found for the ACE D allele and IL-6 C allele, both more frequent in recurrent cases, suggesting these variants contribute to increased risk of reinfection. A modest association was observed for the TNF-α A allele at the allelic level but not at the genotype level. The findings highlight the potential role of pro-inflammatory genetic variants in predisposing individuals to repeated SARS-CoV-2 infections and support the utility of host genetic profiling in understanding and managing COVID-19 recurrence.
Additional Information
- Source:Minerva Biotechnology & Biomolecular Research. 2026/03, Vol. 38, Issue 1, p4
- Document Type:Article
- Subject Area:History
- Publication Date:2026
- ISSN:2724-542X
- DOI:10.23736/S2724-542X.25.03308-5
- Accession Number:193536225
- Copyright Statement:Copyright of Minerva Biotechnology & Biomolecular Research is the property of Edizioni Minerva Medica and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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