Association of SARS-CoV-2 infection with Age and Gender deduced by RT PCR amplification of ORF1ab, E and N Genes Cycle Threshold (Ct)

Abstract

Abstract Introduction/Objective COVID-19 pandemic caused by SARS-CoV-2 has significantly impacted public health globally. Accurate and rapid detection of the infectious agent is essential for disease control and management. RT-PCR amplifies the specific targets in viral genome. The amplification signals and the cycle threshold (Ct) value gives the idea of presence of the virus and their loads. Understanding the association between Ct values, age, and gender could provide insights into the viral load and could also shed light on the potential alterations in disease transmission, severity, clinical outcomes, and dynamics among different populations and age groups. The current study aims to elaborate the correlation between Ct values of (ORF1ab, E, and N) with age and gender. Methods/Case Report 11,108 samples were tested for COVID-19 RT-PCR assay in the current study at PureLab Pure Health, Abu Dhabi, UAE. Results (if a Case Study enter NA) 1009/11,108 (9.08 %) positivity was observed in the studied population. COVID- 19 was more prevalent in females (53.51%) as compared to males (46.48%). Significantly higher positivity was observed in age group (31-40 years) in both males (24.09%, 113/469) and females (24.44%, 132/540). The Ct values for all the three (03) targets were ranged from 11.37 to 39.39. Longitudinal analysis showed significant increased during the study period from starting to end as were hypothesized. Interestingly, all the three (03) targets (ORF1ab, E, and N) were present in all age groups. This may indicate the existing clade can infect all the age groups even children less than 01 years old. Conclusion In conclusion, between age groups, there was no significant difference in viral loads. In general, females had a larger viral burden than males. Studying the association between Ct values of SARS-CoV-2 genes age and gender is essential for understanding the viral load dynamics and potential variations in disease characteristics among different population groups. Such investigations could contribute to disease prognosis, risk stratification and the development of targeted interventions based on demographic characteristics. However, further research is essential to establish reliable patterns and unravel the complex interplay between viral load, gender, age, and clinical outcomes in COVID-19 patients.