Variation of Genomic Sites Associated with Severe Covid-19 Across Populations: Global and National Patterns

Oleg Balanovsky; Valeria Petrushenko; Karin Mirzaev; Sherzod Abdullaev; Igor Gorin; Denis Chernevskiy; Anastasiya Agdzhoyan; Elena Balanovska; Alexander Kryukov; Ilyas Temirbulatov; Dmitriy Sychev

doi:10.2147/PGPM.S320609

Variation of Genomic Sites Associated with Severe Covid-19 Across Populations: Global and National Patterns

Pharmgenomics Pers Med. 2021 Nov 4:14:1391-1402. doi: 10.2147/PGPM.S320609. eCollection 2021.

Authors

Oleg Balanovsky^{1

2

3}, Valeria Petrushenko^{1

4}, Karin Mirzaev^{2

5}, Sherzod Abdullaev⁵, Igor Gorin^{1

4}, Denis Chernevskiy², Anastasiya Agdzhoyan^{1

2}, Elena Balanovska^{2

3}, Alexander Kryukov⁵, Ilyas Temirbulatov^{2

5}, Dmitriy Sychev⁵

Affiliations

¹ Laboratory of Genome Geography, Vavilov Institute of General Genetics, Moscow, Russia.
² Laboratory of Human Population Genetics, Research Centre for Medical Genetics, Moscow, Russia.
³ Biobank of North Eurasia, Moscow, Russia.
⁴ Department of Bioinformatics Moscow Institute of Physics and Technology, Moscow, Russia.
⁵ Department of Clinical Pharmacology and Therapeutics, Russian Medical Academy of Continuous Professional Education, Moscow, Russia.

Abstract

Background: Information about the distribution of clinically significant genetic markers in different populations may be helpful in elaborating personalized approaches to the clinical management of COVID-19 in the absence of consensus guidelines.

Aim: Analyze frequencies and distribution patterns of two markers associated with severe COVID-19 (rs11385942 and rs657152) and look for potential correlations between these markers and deaths from COVID-19 among populations in Russia and across the world.

Methods: We genotyped 1883 samples from 91 ethnic groups pooled into 28 populations representing Russia and its neighbor states. We also compiled a dataset on 32 populations from other regions using genotypes extracted or imputed from the available databases. Geographic maps showing the frequency distribution of the analyzed markers were constructed using the obtained data.

Results: The cartographic analysis revealed that rs11385942 distribution follows the West Eurasian pattern: the marker is frequent among the populations of Europe, West Asia and South Asia but rare or absent in all other parts of the globe. Notably, the transition from high to low rs11385942 frequencies across Eurasia is not abrupt but follows the clinal variation pattern instead. The distribution of rs657152 is more homogeneous. The analysis of correlations between the frequencies of the studied markers and the epidemiological characteristics of COVID-19 in a population revealed that higher frequencies of both risk alleles correlated positively with mortality from this disease. For rs657152, the correlation was especially strong (r = 0.59, p = 0.02). These reasonable correlations were observed for the "Russian" dataset only: no such correlations were established for the "world" dataset. This could be attributed to the differences in methodology used to collect COVID-19 statistics in different countries.

Conclusion: Our findings suggest that genetic differences between populations make a small yet tangible contribution to the heterogeneity of the pandemic worldwide.

Keywords: AB0; gene geography; genetic markers; rs11385942; rs657152; severe COVID-19.