Exploring the genetic landscape of COVID-19 susceptibility and severity among patients in Türkiye

Date

2026-12-01

Author

Er, Ahmet Gorkem
Çakır, Yavuzhan
Er, Berrin
Burduroğlu, Hüseyin Cahit
Çakmak, Mehmet
ÖZIŞIK, LALE
DURUSU TANRIÖVER, MİNE
Topeli, Arzu
Aydın Son, Yeşim
Ünal, Serhat

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Background: One of the most challenging factors for clinicians in managing COVID-19 has been differences in the clinical course. To investigate the parameters associated with severe disease in detail, along with examining known risk factors such as advanced age and comorbidities, understanding personal genetic factors is necessary, as the clinical course may change due to differences in the host genome. Methods: Human genetic variants reported to be associated with severe disease were genotyped in 68 patients in COVID-19 medical wards and 52 in COVID-19 intensive care units at Hacettepe University Adult Hospital. Results: The rs17860115 variant was significantly more prevalent in our cohort than in the European (non-Finish) population, whereas the rs2298659, rs2298661, rs4290734, and rs9271609 variants were significantly less common, which may reflect genetic differentiation, selective pressures, or protective factors within this population. While no significant association was found between variants and disease severity, notably, the ACE2 rs1548474 allele frequency was 38.0% in the ICU group and 22.9% in the non-ICU group (OR = 2.06; 95% CI 1.10–3.90; p = 0.02). Conclusion: These findings emphasize the importance of examining genetic differences both within and across populations when developing new strategies for disease control and public health policies, particularly for infectious diseases such as COVID-19. They also point to the necessity for further research involving larger and more varied populations to validate these associations and to investigate the genetic factors that may drive them.

Subject Keywords

COVID-19, Genetics, Human variants, Severe disease

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105029547011&origin=inward
https://hdl.handle.net/11511/118532

Collections

Graduate School of Informatics, Article