ABSTRACT
Introduction: Coronavirus disease 2019 (COVID-19) has brought countless infections and deaths worldwide. COVID-19 patients demonstrated a great diversity in clinical manifestation and disease severity, but factors for these diversions are yet to be determined. Genetic variations such as the single nucleotide polymorphisms (SNPs) might be responsible for COVID-19 severity. Methods: Genomic DNA was extracted from the peripheral blood of 215 recovered COVID-19 patients with different disease severities (asymptomatic, mild, and severe). Their personal information such as gender, age, BMI, and comorbidities was recorded. Global Screening Array (GSA) was performed to search for SNPs linked with the COVID-19 severity. Potential SNPs were further genotyped using real-time PCR for validation, and their risk association was assessed. Results: Hypertension and obesity were the most prevalent comorbidities in severe COVID-19 patients. The GSA showed three potential SNPs (rs923147, rs409017, and rs17062791) that were significantly associated with COVID-19 severity. Further analyses on these SNPs revealed that male, older (>60 years), and overweight subjects who carried an A allele in the rs923147 were protective against severe COVID-19. In contrast, male patients who inherited a G allele had an increased risk of severe COVID-19. For the rs409017 SNP, the presence of an A allele significantly increased the risk of subjects developing severe COVID-19. Besides, obese patients who carried a T allele in the rs17062791 SNP had a significantly lower risk of developing mild symptoms. Conclusion: This study suggests SNPs' potential role that is linked with the COVID-19 severity. These data are useful in predicting the disease severity of COVID-19 patients.
ABSTRACT
More than 1.75 million COVID-19 infections and 16 thousand associated deaths have been reported in Malaysia. A meta-analysis on the prevalence of COVID-19 in different clinical stages before the National COVID-19 Vaccination Program in Malaysia is still lacking. To address this, the disease severity of a total of 215 admitted COVID-19 patients was initially recorded in the early phase of this study, and the data were later pooled into a meta-analysis with the aim of providing insight into the prevalence of COVID-19 in 5 different clinical stages during the outset of the COVID-19 pandemic in Malaysia. We have conducted a systematic literature search using PubMed, Web of Science, Scopus, ScienceDirect, and two preprint databases (bioRxiv and medRxiv) for relevant studies with specified inclusion and exclusion criteria. The quality assessment for the included studies was performed using the Newcastle-Ottawa Scale. The heterogeneity was examined with an I2 index and a Q-test. Funnel plots and Egger's tests were performed to determine publication bias in this meta-analysis. Overall, 5 studies with 6375 patients were included, and the pooled prevalence rates in this meta-analysis were calculated using a random-effect model. The highest prevalence of COVID-19 in Malaysia was observed in Stage 2 cases (32.0%), followed by Stage 1 (27.8%), Stage 3 (17.1%), Stage 4 (7.6%), and Stage 5 (3.4%). About two-thirds of the number of cases have at least one morbidity, with the highest percentage of hypertension (66.7%), obesity (55.5%), or diabetes mellitus (33.3%) in Stage 5 patients. In conclusion, this meta-analysis suggested a high prevalence of COVID-19 occurred in Stage 2. The prevalence rate in Stage 5 appeared to be the lowest among COVID-19 patients before implementing the vaccination program in Malaysia. These meta-analysis data are critically useful for designing screening and vaccination programs and improving disease management in the country.