Population Analysis of the HLA-a* and -B* Allele Frequency in Bone Marrow Donors, Republic of Tatarstan, Russia
Authors: Davidyuk Yuri , Kabwe Emmanuel , Kletenkov Konstantin , Khaiboullina Svetlana , Rizvanov Albert 
Published: October 2019

Introduction

HLA genotyping is a critical stage in finding the best matched bone marrow donor for transplantation. Kazan Federal University (KFU) is involved in the «Rusfond» Charity «Rusfond. Register» program to generate the regional register of the bone marrow donors in the Republic of Tatarstan (RT). Russians and Tatars represent the majority of the RT population. Calculation of the HLA allelic group and haplotype profile of donors in RT could be useful to identify the closely related populations, which could contain the best-matched donors. This will facilitate selection of donors which could be located in far distances. The goal of this study is to characterize the potential bone marrow donors in the RT based on HLA-A* and -B* allelic group frequencies and to identify related populations in Russia and neighboring countries, as well as in European and non-European countries.

Materials and methods

HLA-A* and -B* allelic group frequencies in a group of 483 potential bone marrow donors from RT reported in our previous study (Davidyuk et al, 2017) were used to calculate the genetic distances between RT and 50 other populations. Data on HLA-allele frequencies in Caucasians, Mongoloid and Negroid populations were obtained from The Allele Frequency Net Database - website http://www.allelefrequencies.net (Gonzalez-Galarza et al, 2015). Analysis was conducted using R language for statistical computing and Rstudio (R Core Team, 2018). Packages ade4 and adegenet were used to calculate Reynolds' distances for HLA-A and HLA-B allelic group frequencies, perform clusterization with Ward's method and construct a dendrogram.

Results and discussion

The HLA-allele and haplotype frequencies in RT donors were reported in our previous study (Davidyuk et al, 2017). The comparative analysis of HLA-A* and -B* allelic group frequencies showed that the RT population and other populations from Russia as well as Slovakian and Polish populations are belong to one cluster on the dendrogram (Fig. 1). This cluster also contained the Caucasian populations from Western and Northern Europe.

We also found that the RT population is more related to the populations from Samara region and Moscow. Two populations from north-western region of Russia and two Tatar populations were also closely related to the RT population. All populations listed above had low genetic distances from the RT population, while the genetic distance between the RT population and Russians from Chelyabinsk region was high (Fig. 2). Interestingly, Russians from Chelyabinsk region were more distantly related to the populations of European part of Russia as compared to RT population.

Collected data suggest that the RT population could be used as potential bone marrow donors for recipients from closely related populations in the neighboring regions. However, in future, as the number of donors in the RT regional register will increase, the genetic relationship between RT population and other populations in Russia could be changed.

Conclusion

Our data revealed that potential bone marrow donors studied in the RT are closely related to the Russians and Tatars populations from European part of Russia. This observation could be important for selection of the hematopoietic stem cell transplant recipients from these populations to find a phenotypically matched donor within the register of RT.

The Russian Government Program of Competitive Growth of KFU and «Rusfond» supported this study. Albert Rizvanov was supported by state assignment 20.5175.2017/6.7 of the Ministry of Education and Science of Russian Federation.

ReferencesDavidyuk et al (2017). HLA Alleles and Haplotypes Frequency in the Population of the Republic of Tatarstan, Russia. Blood. 130:4942.Gonzalez-Galarza et al (2015). Allele frequency net 2015 update: new features for HLA epitopes, KIR and disease and HLA adverse drug reaction associations. Nucleic Acid Research 39, 28, D784-8.R Core Team (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.

Disclosures

No relevant conflicts of interest to declare.