The article presents the results of observation of 213 patients with PD, including 90 (42.25%) women, 123 (57.75%) men, whose mean age was 46.17±0.63 years. Patients with PD were selected in accordance with the international criteria of the British brain bank "Parkinson's Disease Society Brain Bank". Patients underwent CT or MRI of the brain. Olfactory disturbances were studied using the Sniffin Stix Test (SST) by Burchard (Hamburg, Germany). All patients underwent examination of the ENT organs. The results obtained indicate that the presence of hyposmia in patients with early onset of PD is an important biomarker of the latent neurodegenerative process of the “Parkinsonian” type and, therefore, the risk of future development of PD.

Около 91% населения планеты проживает в регионах с уровнем загрязнения воздуха, превышающим нормы Всемирной организации здравоохранения. Воздействие загрязнённого воздуха признано значимым фактором риска бронхиальной астмы. В Казахстане уровень заболеваемости БА продолжает расти, и ухудшение экологической обстановки вносит значительный вклад в эту тенденцию. Исследования на близнецах показали, что наследуемость БА достигает 70%. Наряду с этим важную роль играют и внешние факторы, включая качество воздуха. Однонуклеотидные полиморфизмы (SNPs), выявляемые методом GWAS, помогают установить генетическую предрасположенность к БА и оценить влияние факторов окружающей среды, таких загрязнителей воздуха как PM2.5, CO и SO2. Целью настоящего исследования является анализ однонуклеотидных полиморфизмов, связанных с бронхиальной астмой, и их взаимодействия с загрязнителями атмосферного воздуха у жителей города Алматы. В исследование включены пациенты с БА и здоровые добровольцы; проведено микрочиповое генотипирование и сбор данных о загрязнении воздуха в течение семи месяцев. Наиболее выраженные защитные ассоциации были выявлены для rs3117098 (TSBP-AS1, OШ=0.39, p=0.000), тогда как rs2844510 (LINC01149, OШ=2.00, p=0.047) и два полиморфизма в HLA-DRA/TSBP1-AS1 (rs9268516, rs3763309) ассоциировались с повышенным риском, причём воздействие CO значительно усиливало генетический эффект для rs3763309 (OШ=2.96, p=0.002) и rs9268516 (OШ=2.10, p=0.004), тогда как взаимодействия с PM2.5 и SO₂ оказались статистически значимыми, но слабыми. Это первое исследование, направленное на выявление ассоциации между генетическими вариациями, связанными с БА и концентрацией загрязнителей воздуха в Алматы с акцентом на казахское население. Полученные данные позволят углубить понимание механизмов развития БА и способствовать развитию персонализированных подходов к диагностике и профилактике. Ключевые слова: Бронхиальная астма; загрязнение среды; однонуклеотидный полиморфизм; генотипирование.

The Volume 13 published for IJEPR Journal.

Background Bronchial asthma (BA) is a complex respiratory disease resulting from interactions between genetic susceptibility and environmental exposures [1]. Air pollutants contribute to BA via oxidative stress and inflammation, especially in genetically susceptible individuals [2]. This study aimed to investigate genetic susceptibility to BA in an urban Kazakh population by integrating genome-wide SNP genotyping with environmental exposure data to enhance personalized risk prediction. Methods A case-control study was conducted in Almaty involving 288 participants: 144 asthma patients and 144 matched controls. Genome-wide genotyping was performed using the Infinium Global Screening Array-24 v3.0 on an iScan platform. SNP associations were analyzed using PLINK and annotated via ClinVar, dbSNP, and 1000 Genomes. Environmental exposure metrics (PM₂.₅, PM₁₀, SO₂) were monitored digitally over 7 months. Gene-environment interactions were evaluated to determine pollutant-modulated SNP effects. Results Several SNPs demonstrated significant associations with BA risk and specific pollutant exposures. Protective variants included rs12413578 in GSDMB (OR = 0.24, 95% CI: 0.09- 0.67), rs907092 in IKZF3 (OR = 0.59, 95% CI: 0.40-0.86), and rs17293632 in SMAD3 (OR = 0.26, 95% CI: 0.09-0.75) under elevated PM10 exposure. Increased risk was observed for rs1837253 in TSLP (OR = 1.67, 95% CI: 1.03-2.69) in relation to PM2.5, and rs1295686 in IL13 (OR = 0.22, 95% CI: 0.06-0.85) showed a protective effect under SO2 exposure. Conclusions This study identified several SNPs significantly associated with asthma risk in Almaty population, including GSDMB rs12413578 and IKZF3 rs907092 as protective variants, and TSLP rs1837253 as a PM2.5 dependent risk marker for patients with BA. Additionally, SMAD3 and IL13 variants showed pollutant-specific associations with PM10 and SO2, respectively. The proposed integration of gene-environment interactions into risk models may enhance asthma prediction and inform more targeted strategies in precision medicine. Acknowledgement This study was funded by the Committee of Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan under Grant No. AP23488865 Key words: bronchial asthma, gene–environment interaction, SNP genotyping, air pollutants. References: Meyers D.A., Bleecker E.R., Holloway J.W., Holgate S.T. Asthma genetics and personalised medicine. Lancet Respir Med. 2(5):405-15 (2014). Guarnieri M., Balmes J.R. Outdoor air pollution and asthma. Lancet. 383(9928):1581- 92 (2014).

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.