Clinically Relevant Pharmacogenomic Variant Frequencies in Kazakh, Russian, and Uzbek Population Groups Residing in Kazakhstan

Central Asian populations remain underrepresented in pharmacogenomic research, limiting the availability of population-specific data for genotype-informed prescribing and precision medicine. This study analyzed clinically relevant pharmacogenomic variant frequencies in Kazakh, Russian, and Uzbek population groups residing in Kazakhstan using genome-wide genotype data from 1301 individuals: Kazakh (n = 1111), Russian (n = 156), and Uzbek (n = 34). ClinPGx, a PharmGKB-based clinical annotation framework that prioritizes variant–drug associations according to levels of evidence, was used to select variants with evidence levels 1A, 1B, and 2A. In total, 112 directly genotyped variants were retained for population-specific allele and genotype frequency analysis. All 112 variants were queried against the gnomAD v4.1 genome and exome reference datasets. Of these, matching allele-frequency data for the predefined reported allele were available in at least one of the two gnomAD datasets for 103 variants, whereas for 9 variants the VEP-based query did not return a matching gnomAD frequency for that allele. Frequencies were reported for the same predefined reported allele across all groups, and differences between the study groups were assessed using 95% confidence intervals, Fisher’s exact tests, and false discovery rate correction. Genotype counts and the proportions of individuals carrying at least one copy of the reported allele were also summarized for all selected variants. Several pharmacogenomic variants showed population-specific frequency patterns, including NUDT15 rs116855232, SLCO1B1 rs4149056, VKORC1 rs9934438, and UGT1A1 rs10929302. Comparison with gnomAD showed that the observed frequencies were variant-specific and could not be consistently approximated by a single broad genetic ancestry group. Reference-based population structure analysis provided additional ancestry context and supported separate reporting by population group. The study did not evaluate clinical outcomes or make individual prescribing recommendations, and the small Uzbek sample size limits the precision of frequency estimates for this group, particularly for rare variants. Overall, this study provides a clinically prioritized pharmacogenomic frequency resource for underrepresented population groups in Kazakhstan and supports broader Central Asian representation in pharmacogenomic implementation research.

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Journal
Biology
Published
2026-09-01
DOI
https://doi.org/10.3390/biology15171477
Primary Topic
Pharmacogenetics and Drug Metabolism
Type
article
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article

Clinically Relevant Pharmacogenomic Variant Frequencies in Kazakh, Russian, and Uzbek Population Groups Residing in Kazakhstan

Nazym Altynova, Zhassulan Zhaniyazov, Beimbet Daribayev, S.B. Ryspaeva et al.
Biology
Pharmacogenetics and Drug Metabolism
article

Clinically Relevant Pharmacogenomic Variant Frequencies in Kazakh, Russian, and Uzbek Population Groups Residing in Kazakhstan

Nazym Altynova, Zhassulan Zhaniyazov, Beimbet Daribayev, S.B. Ryspaeva, Rauash Mangazbayeva, Madina Abdullayeva, Gulnur Zhunussova, Leyla Djansugurova, Aikorkem Mustafayeva, Akmaral Kulatayeva, Saltanbek Mukhambetzhanov, Assel Aulbekova
article en

Abstract

Central Asian populations remain underrepresented in pharmacogenomic research, limiting the availability of population-specific data for genotype-informed prescribing and precision medicine. This study analyzed clinically relevant pharmacogenomic variant frequencies in Kazakh, Russian, and Uzbek population groups residing in Kazakhstan using genome-wide genotype data from 1301 individuals: Kazakh (n = 1111), Russian (n = 156), and Uzbek (n = 34). ClinPGx, a PharmGKB-based clinical annotation framework that prioritizes variant–drug associations according to levels of evidence, was used to select variants with evidence levels 1A, 1B, and 2A. In total, 112 directly genotyped variants were retained for population-specific allele and genotype frequency analysis. All 112 variants were queried against the gnomAD v4.1 genome and exome reference datasets. Of these, matching allele-frequency data for the predefined reported allele were available in at least one of the two gnomAD datasets for 103 variants, whereas for 9 variants the VEP-based query did not return a matching gnomAD frequency for that allele. Frequencies were reported for the same predefined reported allele across all groups, and differences between the study groups were assessed using 95% confidence intervals, Fisher’s exact tests, and false discovery rate correction. Genotype counts and the proportions of individuals carrying at least one copy of the reported allele were also summarized for all selected variants. Several pharmacogenomic variants showed population-specific frequency patterns, including NUDT15 rs116855232, SLCO1B1 rs4149056, VKORC1 rs9934438, and UGT1A1 rs10929302. Comparison with gnomAD showed that the observed frequencies were variant-specific and could not be consistently approximated by a single broad genetic ancestry group. Reference-based population structure analysis provided additional ancestry context and supported separate reporting by population group. The study did not evaluate clinical outcomes or make individual prescribing recommendations, and the small Uzbek sample size limits the precision of frequency estimates for this group, particularly for rare variants. Overall, this study provides a clinically prioritized pharmacogenomic frequency resource for underrepresented population groups in Kazakhstan and supports broader Central Asian representation in pharmacogenomic implementation research.

BiologyVol. 15(17)
Al-Farabi Kazakh National University (KZ), Satbayev University (KZ), Ministry of Education and Science of the Republic of Kazakhstan (KZ), Shakarim University (KZ)
Openalex Percentile: Top 9%
Pharmacogenetics and Drug Metabolism
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