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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.

Central Asia

Beyond enrichment: pharmacogenetic heterogeneity in treatment-resistant depression.

OBJECTIVES: Genetic variation has been proposed as a potential contributor to antidepressant nonresponse, but its role in treatment-resistant depression (TRD) remains unclear. This study used pharmacogenetics (PGx) to characterize genetic variation in TRD and determine whether actionable PGx variation and drug-gene interaction (DGI) mismatch were associated with antidepressant nonresponse and TRD burden. METHODS: This observational study included 158 individuals with TRD recruited from outpatient clinics in Western Australia. Genotype and genotype-predicted phenotypes for CYP2B6, CYP2C19, and CYP2D6 were derived from commercial PGx testing and compared with ethnicity-matched reference populations from ClinPGx. Antidepressant-specific DGIs were classified as actionable or nonactionable according to Clinical Pharmacogenetics Implementation Consortium guidelines, and unsupervised clustering was used to identify clusters based on these actionability profiles. Analyses were performed to determine if actionable PGx variation, cluster membership, or PGx mismatch was associated with TRD burden (number of failed antidepressant trials). RESULTS: PGx variation in the TRD cohort was consistent with population expectations, with no evidence of enrichment for actionable PGx variants. Clustering identified six clusters with distinct and gene-specific patterns of PGx variation independent of demographic and clinical characteristics. However, neither PGx mismatch nor cluster membership were associated with TRD burden. CONCLUSION: These findings suggest that actionable PGx phenotypes are neither enriched in TRD nor associated with greater TRD severity. Rather, the results indicate that TRD does not represent a single, unified PGx-predicted 'poor pharmacological responder' phenotype but instead reflects a biologically heterogeneous collection of distinct PGx profiles.

antidepressants

Toward an integrated resource for pharmacogenomics (PGx): Survey findings from the genomic medicine communities.

PURPOSE: Pharmacogenomics (PGx) is a critical component of precision health care that aims to improve drug efficacy and reduce adverse events. Terminologies and standards have not always aligned between PGx and broader genomic medicine communities, which is a barrier to PGx implementation. An updated assessment of community barriers, needs, and perspectives is critical to enable more standardized terminologies and interpretation frameworks. METHODS: The Clinical Genome Resource's PGx Interpretation Committee (PGxIC, formerly referred to as the PGx Working Group, PGxWG) conducted 2 surveys targeting the PGx and genomic medicine communities (n = 508) to evaluate perspectives on PGx clinical validity and actionability frameworks, as well as other barriers to PGx implementation. Surveys were tailored toward self-reported familiarity with PGx. Data primarily consisted of free text, which were analyzed using qualitative content analysis methods. RESULTS: Survey responses indicated conflation of terminology across disciplines, including confusion around differing definitions of terms in PGx and non-PGx contexts. Data also indicated broad support for leveraging existing PGx guidelines and framework structures alongside the standardization of approaches and centralization of resources. CONCLUSION: These novel survey results demonstrate broad consensus on the importance of integrating PGx into clinical practice, including support for development of gene-drug response clinical validity and actionability frameworks aligned with Clinical Genome Resource's frameworks for gene-disease relationships.

Humans