We evaluated the associations between single nucleotide polymorphisms and different clinical parameters related to type 2 diabetes mellitus (T2DM), obesity risk, and metabolic syndrome (MS) in a Kazakh cohort. A total of 1336 subjects, including 408 T2DM patients and 928 control subjects, were recruited from an outpatient clinic and genotyped for 32 polymorphisms previously associated with T2DM and obesity-related phenotypes in other ethnic groups. For association studies, the chi-squared test or Fisher’s exact test for binomial variables were used. Logistic regression was conducted to explore associations between the studied SNPs and the risk of developing T2DM, obesity, and MS, after adjustments for age and sex. After excluding four SNPs due to Hardy-Weinberg disequilibrium, significant associations in age-matched cohorts were found betweenT2DM and the following SNPs: rs9939609 (FTO), rs13266634 (SLC30A8), rs7961581 (TSPAN8/LGR5), and rs1799883 (FABP2). In addition, examination of general unmatched T2DM and control cohorts revealed significant associations between T2DM and SNPsrs1799883 (FABP2) and rs9939609 (FTO). Furthermore, polymorphisms in the FTO gene were associated with increased obesity risk, whereas polymorphisms in the FTO and FABP2 genes were also associated with the risk of developing MS in general unmatched cohorts. We confirmed associations between polymorphisms within the SLC30A8, TSPAN8/LGR5, FABP2, and FTO genes and susceptibility to T2DM in a Kazakh cohort, and revealed significant associations with anthropometric and metabolic traits. In particular, FTO and FABP2 gene polymorphisms were significantly associated with susceptibility to MS and obesity in this cohort.

Kazakhstan has been inhabited by different populations, such as the Kazakh, Kyrgyz, Uzbek and others. Here we investigate allelic and haplotypic polymorphisms of human leukocyte antigen (HLA) genes at DRB1, DQA1 and DQB1 loci in the Kazakh ethnic group, and their genetic relationship between world populations. A total of 157 unrelated Kazakh ethnic individuals from Astana were genotyped using sequence based typing (SBT-Method) for HLA-DRB1, -DQA1 and -DQB1 loci. Allele frequencies, neighbor-joining method, and multidimensional scaling analysis have been obtained for comparison with other world populations. Statistical analyses were performed using Arlequin v3.11. Applying the software PAST v. 2.17 the resulting genetic distance matrix was used for a multidimensional scaling analysis (MDS). Respectively 37, 17 and 19 alleles were observed at HLA-DRB1, -DQA1 and -DQB1 loci. The most frequent alleles were HLA-DRB1*07:01 (13.1%), HLA-DQA1*03:01 (13.1%) and HLA-DQB1*03:01 (17.6%). In the observed group of Kazakhs DRB1*07:01-DQA1*02:01-DQB1*02:01 (8.0%) was the most common three loci haplotype. DRB1*10:01-DQB1*05:01 showed the strongest linkage disequilibrium. The Kazakh population shows genetic kinship with the Kazakhs from China, Uyghurs, Mongolians, Todzhinians, Tuvinians and as well as with other Siberians and Asians. The HLA-DRB1, -DQA1and -DQB1 loci are highly polymorphic in the Kazakh population, and this population has the closest relationship with other Asian and Siberian populations.

Background: Ethnic differences exist in the frequencies of genetic variations that contribute to the risk of common disease. This study aimed to analyse the distribution of several genes, previously associated with susceptibility to type 2 diabetes and obesity-related phenotypes, in a Kazakh population. Methods: A total of 966 individuals belonging to the Kazakh ethnicity were recruited from an outpatient clinic. We genotyped 41 common single nucleotide polymorphisms (SNPs) previously associated with type 2 diabetes in other ethnic groups and 31 of these were in Hardy–Weinberg equilibrium. The obtained allele frequencies were further compared to publicly available data from other ethnic populations. Allele frequencies for other (compared) populations were pooled from the haplotype map (HapMap) database. Principal component analysis (PCA), cluster analysis, and multidimensional scaling (MDS) were used for the analysis of genetic relationship between the populations. Results: Comparative analysis of allele frequencies of the studied SNPs showed significant differentiation among the studied populations. The Kazakh population was grouped with Asian populations according to the cluster analysis and with the Caucasian populations according to PCA. According to MDS, results of the current study show that the Kazakh population holds an intermediate position between Caucasian and Asian populations. Conclusion: A high percentage of population differentiation was observed between Kazakh and world populations. The Kazakh population was clustered with Caucasian populations, and this result may indicate a significant Caucasian component in the Kazakh gene pool.

Studies of genes involved in the absorption, distribution, metabolism, and excretion (ADME) of drugs are crucial to the development of therapeutics in clinical medicine. Such data provide information that may improve our understanding of individual differences in sensitivity or resistance to certain drugs, thereby helping to avoid adverse drug reactions (ADRs) in patients and improve the quality of therapies. Here, we aimed to analyse single nucleotide polymorphisms (SNPs) involved in the ADME of multiple drugs in Kazakhs from Kazakhstan. A total of 158 SNPs involved in the ADME of various drugs were studied. We analysed 320 Kazakh DNA samples using OpenArray genotyping. Of the 158 SNPs, 75 were not found in heterozygous or homozygous variants. Comparative analysis among Kazakhs and world populations showed a fairly high percentage of population differentiation. These results provide further information for pharmacogenetic databases and may contribute to the development of personalized approaches and safer therapies for the Kazakh population. Moreover, these data provide insights into the different racial groups that may have contributed to the Kazakh population.

Adulteration of meat products, including illegal substitution and addition of ingredients, tampering, and the misrepresentation and labelling of food or food ingredients, is becoming a more serious problem globally. The consequences of such manipulations can pose various health risks for consumers, including food allergies and poisoning. This study investigates the problem of meat product adulteration, and detection of the same using real-time polymerase chain reaction (qPCR).