Gulnara Svyatova

Neonatal screening using Dried Blood Spot (DBS) cards is an important and successful public health facility in Europe, enabling early detection of congenital disorders for early treatment and prevention of overt disease. Biobanks of stored DBS cards offer significant potential for biomedical research. Biobanking and secondary use of DBS cards also raise ethical and legal issues, particularly concerning the rights of parents and children. This study provides a comprehensive overview of legislation and legal practices governing DBS biobanking across 29 European countries, based on a survey conducted in collaboration with the International Society for Neonatal Screening. Findings reveal a highly heterogeneous landscape: 15 countries have national legislation, five have regional guidelines, and nine lack formal regulations. Only four countries require explicit parental consent for DBS storage, with considerable variation in approval processes for research use. A harmonization of practices, with the European General Data Protection Regulation (GDPR) as a basis for future regulation, supplemented by clearer guidance on ‘public interest’ and robust safeguards for individual rights may lead to more transparent and consistent governance, which is essential to balance scientific progress with the protection of parental and children’s rights in DBS-based research across Europe.

Background and Objectives: Psoriasis is a chronic immune-mediated inflammatory disease frequently accompanied by obesity and cardiometabolic disturbances. This study evaluated metabolic, inflammatory, and genetic correlates of overweight/obesity in ethnic Kazakh patients with psoriasis and explored potential multilocus genetic interactions. Materials and Methods: This study included 150 patients with clinically confirmed psoriasis, comprising 75 patients with overweight/obesity and 75 non-overweight/obese individuals frequency-matched by age and sex; because group sizes were fixed by design rather than sampled in proportion to prevalence, the reported odds ratios reflect within-sample associations rather than population-level risk estimates. Clinical, anthropometric, biochemical, inflammatory, and genetic data were collected using standardized protocols. Multivariable logistic regression was used to assess clinical, metabolic, and inflammatory correlates of overweight/obesity. Associations between three candidate polymorphisms, rs1558902 in FTO, rs696574 in CALCRL, and rs10968110 in ZTV, were evaluated. Results: In the multivariable model adjusted for age and sex, higher triglyceride levels (adjusted OR 4.73, 95% CI 1.36–18.57), higher HbA1c (adjusted OR 1.71, 95% CI 1.09–2.91), and lower HDL-C levels (adjusted OR 0.36, 95% CI 0.18–0.66) were independently associated with overweight/obesity. In genetic analyses, rs10968110 in ZTV showed significant associations with overweight/obesity in genotype, additive trend, allelic, and dominant models, while the recessive model was not significant. The FTO rs1558902 variant was also significantly associated with overweight/obesity, with the strongest support observed under additive, allelic, and dominant assumptions. In contrast, rs696574 in CALCRL was not significantly associated with overweight/obesity. Exploratory MDR analysis identified rs10968110 as the most stable single-locus model, whereas higher-order models showed only limited additional discriminatory value and lower cross-validation consistency. Conclusions: Among ethnic Kazakh patients with psoriasis, overweight/obesity was associated with an adverse cardiometabolic profile characterized by elevated triglycerides, higher HbA1c, and reduced HDL-C. Candidate genetic findings suggest that ZTV rs10968110 and FTO rs1558902 may be associated with overweight/obesity susceptibility, although these results should be considered exploratory pending validation in larger independent cohorts. These findings support integrated cardiometabolic assessment in psoriasis care and further investigation of genetic susceptibility to obesity in this population.

Background: Alport syndrome is a hereditary disorder caused by defects in the type IV collagen network. Although exon variants are primarily associated with Alport syndrome, the clinical significance of intronic variants remains incompletely characterized. The aim of this study was to characterize the clinical and molecular features of a familial case of Alport syndrome associated with the intronic variant c.1588-2A>G and to assess its impact using in silico tools. Case description: Two affected siblings presented with hematuria, proteinuria, and renal biopsy demonstrated focal global and segmental glomerulosclerosis, findings consistent with Alport syndrome. Whole-exome sequencing was subsequently performed in patients. The variant (NM_033380.2, c.1588-2A>G) in intron 23 of the COL4A5 gene was identified in both probands. SpliceAI analysis demonstrated a complete loss of the canonical acceptor site and a high probability of cryptic site activation. Conclusion: The evidence suggests a likely pathogenic role of the COL4A5 c.1588-2A>G variant in Alport syndrome.

Background: Gestational diabetes mellitus (GDM) poses a growing public health challenge worldwide due to its increasing prevalence, associated pregnancy complications, and long-term metabolic risks for both mothers and offspring. Genetic factors are known to contribute to GDM susceptibility, yet little is known about their relevance in ethnic Kazakh population. The primary objective of this study was to evaluate associations between selected candidate SNPs involved in β-cell function and the risk of GDM in a Kazakh cohort. Secondary objectives included the assessment of potential gene–gene interactions. Methods: We conducted a case–control study among 365 pregnant Kazakh women. Of these, 217 were diagnosed with GDM, and 148 had normal glucose tolerance. Clinical and genealogical data were collected. Eight candidate SNPs that were previously associated with GDM or glucose metabolism were genotyped. Logistic regression was used to assess associations between SNPs and GDM risk. Gene–gene interactions were evaluated using multifactor dimensionality reduction (MDR). Results: In univariate analysis, MTNR1B rs10830963 demonstrated a statistically significant association under the additive model (OR 0.61, 95% CI 0.42–0.89), indicating a potential protective effect of the C allele. However, this association was not statistically significant after multivariable adjustment (adjusted OR 0.58, 95% CI 0.32–1.03) and correction for multiple testing. In the adjusted analysis, TCF7L2 rs7903146 showed a significant association under the dominant model (adjusted OR 2.29, 95% CI 1.01–5.46); however, this finding did not remain significant following FDR correction. MDR analysis showed that the best two-locus model included IGF2BP2 rs4402960 and CDKAL1 rs7754840 (CVC = 6/10; testing accuracy = 0.558; permutation p < 0.001). The most stable interaction was observed for the three-locus model comprising IGF2BP2 rs4402960, MTNR1B rs10830963, and PPARG rs1801282 (CVC = 9/10; testing accuracy = 0.576; permutation p < 0.001). Conclusions: The findings suggest that common variants in IGF2BP2, CDKAL1, MTNR1B, TCF7L2, PPARG, and GCK do not exert strong individual effects on GDM susceptibility in this cohort of ethnic Kazakh women. Instead, the results are more consistent with a modest polygenic architecture characterized by small effect sizes and possible weak gene–gene interactions. MDR analysis identified statistically significant interaction models; however, their limited predictive accuracy indicates that these findings should be interpreted as exploratory.

Background: This study aims to investigate the genetic contribution of polymorphic variants of the TCF7L2 (rs7903146) and PPARG (rs1801282) genes to the risk of developing prediabetes in individuals of Kazakh ethnicity. Materials and Methods: This was a case-control study involving 200 cases with prediabetes and 200 prediabetes-free controls, aged 16–60 years (n = 400). Real-time polymerase chain reaction on a StepOnePlus instrument (Applied Biosystems, USA), employing the TaqMan method for site-specific amplification and genotyping of the TCF7L2 (rs7903146) and PPARG (rs1801282) genes was used. Results: Patients with prediabetes had a higher birth weight, increased BMI, larger waist and hip circumferences, and a higher waist-to-hip ratio compared to healthy patients in the control group. There was a significant increase in the risk of developing prediabetes for both the rs1801282 polymorphism of the PPARG gene and the rs7903146 polymorphism of the TCF7L2 gene. The risk was 9.8 times higher in carriers of the GG genotype of PPARG (rs1801282) (OR = 9.769, 95% CI: 2.124–44.922, p = 0.003) and 10.7 times higher for carriers of the TT genotype of TCF7L2 (rs7903146) (OR = 10.731, 95% CI: 1.309–87.939, p < 0.001). Conclusions: These findings highlight the need for tailored early screening and preventive strategies for prediabetes in the Kazakh population, focusing on individuals with high-risk genotypes. Such efforts could improve targeted interventions and reduce the burden of prediabetes. Future research should adopt a longitudinal design, include diverse ethnic groups, and investigate additional genetic markers to provide a more comprehensive understanding of the genetic underpinnings of prediabetes.

The aim of this study was to conduct a comparative analysis of the population frequencies of the minor allele of polymorphic variants in the genes TCF7L2 (rs7903146) and PPARG (rs1801282), based on the genome-wide association studies analysis data associated with the risk of developing prediabetes, in an ethnically homogeneous Kazakh population compared to previously studied populations worldwide. This study utilized a genomic database consisting of 1800 ethnically Kazakh individuals who were considered in healthy condition. Whole-genome genotyping was performed using Illumina OmniChip 2.5–8 arrays, which interrogated approximately 2.5 million single nucleotide polymorphisms. The distribution of genotypes for the TCF7L2 (rs7903146) and PPARG (rs1801282) polymorphisms in the Kazakh sample was found to be in Hardy–Weinberg equilibrium (p > 0.05). The minor G allele of the “Asian” protective polymorphism rs1801282 in the PPARG gene was observed at a frequency of 13.8% in the Kazakh population. This suggests a potentially more significant protective effect of this polymorphism in reducing the risk of prediabetes among Kazakhs. The frequency of the unfavorable T allele of the insulin secretion-disrupting gene TCF7L2 (rs7903146) in Kazakhs was 15.2%. Studying the associations of genetic markers for prediabetes enables the timely identification of “high-risk groups” and facilitates the implementation of effective preventive measures. Further results from replicative genomic research will help identify significant polymorphic variants of genes underlying the alteration of prediabetes status.