Introduction:Arterial hypertension is one of the leading contributors to cardiovascular morbidity and mortality worldwide. This study aimed to evaluate the performance of polygenic risk scores (PRS) for hypertension in Russia and to develop predictive models integrating PRS and questionnaire-based risk factors for disease risk assessment. Methods:We analyzed a cohort of 175,704 individuals from multiethnic inner Eurasian populations. Published PRS for systolic blood pressure, diastolic blood pressure, and pulse pressure were evaluated for association with hypertension across different ancestry groups. Predictive models integrating PRS and questionnaire-derived risk factors were developed using multiple machine learning tools, including neural networks. Results:PRSs for systolic and diastolic blood pressure showed marked differences between the top and bottom deciles of the PRS distribution, with odds ratios of 6.20 (95% CI: 5.22-7.36) and 6.71 (95% CI: 5.58-8.06), respectively. The PRS for pulse pressure was also strongly associated with hypertension, with an odds ratio of 3.71 (95% CI: 3.16-4.35). All evaluated PRSs were consistently associated with hypertension across several ancestry groups represented in Russia and neighboring regions, including East Slavic populations (Russians, Belarusians, and Ukrainians), populations of the Volga-Ural region, such as Tatars, and West Asian-related groups represented by Armenians and Hemshins. A neural network model integrating PRSs with questionnaire-based risk factors achieved a test ROC-AUC of 0.8245 (95% CI: 0.8114-0.8362), demonstrating robust discriminatory performance for arterial hypertension. Conclusion:Our study demonstrates that previously published PRSs for systolic blood pressure, diastolic blood pressure, and pulse pressure retain substantial predictive value across diverse inner Eurasian populations and provide complementary information beyond conventional questionnaire-based risk factors. Among the evaluated scores, the systolic blood pressure PRS showed the most robust and consistent transferability, remaining informative even in several genetically diverse and underpowered cohorts.

BACKGROUND:Alcohol use disorder (AUD) significantly affects over 200 health conditions, causing about 3 million deaths annually worldwide and is approximately 50 % heritable. METHODS:We conducted a genome-wide association study (GWAS) on self-reported alcohol consumption and alcohol-related challenges (AUDIT score) in a large East Slavs cohort (N = 41,575). Genetic correlations with diverse phenotypes were assessed, and a polygenic risk score (PRS) for alcohol use disorder (AUD) was built and tested in an independent clinical cohort. GWAS and PRS associations were validated across various genetic ancestries. RESULTS:The East Slavs GWAS identified a highly significant association (p = 2.5 ×10-18) between the rs1229984 SNP and AUD. Transancestral modeling revealed significant associations in Ashkenazi Jews, Tatars, Siberian, and other populations. Additional subthreshold associations (p < 10-6) were found in SNPs within KIF26, OCA2, DLGAP2, and miRNA AL161421 gene regions. SNP-based heritability was estimated at hg = 6.4 % (SE = 1.1 %). Genetic correlation analysis revealed the strongest positive associations with psychiatric traits. We trained the PRS using external summary statistics and individual-level genomic data from our cohort (R2 = 0.013). It outperformed other external PRSs included in the analysis. Validation in the independent clinical cohort showed an AUC of 0.6 (95 % CI = 0.56-0.64), and integrating PRS with non-genetic models increased the AUC by 1.33 %, resulting in 0.762 (p = 8 × 10⁻⁵). CONCLUSIONS:Our findings suggest a genetic basis for AUD involving genes related to alcohol metabolism and the reward system. The applicability of the PRS across diverse genetic ancestries supports its integration into non-genetic prediction models, enhancing AUD prediction accuracy in diverse populations.

BackgroundPolygenic risk score (PRS) prediction is widely used to assess the risk of diagnosis and progression of many diseases. Routinely, the weights of individual SNPs are estimated by the linear regression model that assumes independent and linear contribution of each SNP to the phenotype. However, for complex multifactorial diseases such as Alzheimer’s disease, diabetes, cardiovascular disease, cancer, and others, association between individual SNPs and disease could be non-linear due to epistatic interactions. The aim of the presented study is to explore the power of non-linear machine learning algorithms and deep learning models to predict the risk of multifactorial diseases with epistasis.MethodsSimulated data with 2- and 3-loci interactions and tested three different models of epistasis: additive, multiplicative and threshold, were generated using the GAMETES. Penetrance tables were generated using PyTOXO package. For machine learning methods we used multilayer perceptron (MLP), convolutional neural network (CNN) and recurrent neural network (RNN), Lasso regression, random forest and gradient boosting models. Performance of machine learning models were assessed using accuracy, AUC-ROC, AUC-PR, recall, precision, and F1 score.ResultsFirst, we tested ensemble tree methods and deep learning neural networks against LASSO linear regression model on simulated data with different types and strength of epistasis. The results showed that with the increase of strength of epistasis effect, non-linear models significantly outperform linear. Then the higher performance of non-linear models over linear was confirmed on real genetic data for multifactorial phenotypes such as obesity, type 1 diabetes, and psoriasis. From non-linear models, gradient boosting appeared to be the best model in obesity and psoriasis while deep learning methods significantly outperform linear approaches in type 1 diabetes.ConclusionOverall, our study underscores the efficacy of non-linear models and deep learning approaches in more accurately accounting for the effects of epistasis in simulations with specific configurations and in the context of certain diseases.

BackgroundCOVID-19 disease has infected more than 772 million people, leading to 7 million deaths. Although the severe course of COVID-19 can be prevented using appropriate treatments, effective interventions require a thorough research of the genetic factors involved in its pathogenesis.MethodsWe conducted a genome-wide association study (GWAS) on 7,124 individuals (comprising 6,400 controls who had mild to moderate COVID-19 and 724 cases with severe COVID-19). The inclusion criteria were acute respiratory distress syndrome (ARDS), acute respiratory failure (ARF) requiring respiratory support, or CT scans indicative of severe COVID-19 infection without any competing diseases. We also developed a polygenic risk score (PRS) model to identify individuals at high risk.ResultsWe identified two genome-wide significant loci (P-value <5 × 10−8) and one locus with approximately genome-wide significance (P-value = 5.92 × 10−8-6.15 × 10−8). The most genome-wide significant variants were located in the leucine zipper transcription factor like 1 (LZTFL1) gene, which has been highlighted in several previous GWAS studies. Our PRS model results indicated that individuals in the top 10% group of the PRS had twice the risk of severe course of the disease compared to those at median risk [odds ratio = 2.18 (1.66, 2.86), P-value = 8.9 × 10−9].ConclusionWe conducted one of the largest studies to date on the genetics of severe COVID-19 in an Eastern European cohort. Our results are consistent with previous research and will guide further epidemiologic studies on host genetics, as well as for the development of targeted treatments.

BACKGROUND: Anhedonia is characterized by a reduced ability to anticipate, experience, and/or learn about pleasure. This phenomenon has a transdiagnostic nature and is one of the key symptoms of mood disorders, schizophrenia, addictions, and somatic conditions. AIM: To evaluate the genetic architecture of anhedonia and its overlap with other mental disorders and somatic conditions. METHODS: We performed a genome-wide association study of anhedonia on a sample of 4,520 individuals from a Russian non-clinical population. Using the available summary statistics, we calculated polygenic risk scores (PRS) to investigate the genetic relationship between anhedonia and other psychiatric or somatic phenotypes. RESULTS: No variants with a genome-wide significant association were identified. PRS for major depression, bipolar disorder, and schizophrenia were significantly associated with anhedonia. Conversely, no significant associations were found between PRS for anxiety and anhedonia, which aligns well with existing clinical evidence. None of the PRS for somatic phenotypes attained a significance level after correction for multiple comparisons. A nominal significance for the anhedonia association was determined for omega-3 fatty acids, type 2 diabetes mellitus, and Crohn’s disease. CONCLUSION: Anhedonia has a complex polygenic architecture, and its presence in somatic diseases or normal conditions may be due to a genetic predisposition to mood disorders or schizophrenia.

We present the results of the depression Genome-wide association studies study performed on a cohort of Russian-descent individuals, which identified a novel association at chromosome 7q21 locus. Gene prioritization analysis based on already known depression risk genes indicated MAGI2 (S-SCAM) as the most probable gene from the locus and potential susceptibility gene for the disease. Brain and gut expression patterns were the main features highlighting functional relatedness of MAGI2 to the previously known depression risk genes. Local genetic covariance analysis, analysis of gene expression, provided initial suggestive evidence of hospital anxiety and depression scale and diagnostic and statistical manual of mental disorders scales having a different relationship with gut-brain axis disturbance. It should be noted, that while several independent methods successfully in silico validate the role of MAGI2, we were unable to replicate genetic association for the leading variant in the MAGI2 locus, therefore the role of rs521851 in depression should be interpreted with caution.

Background Overweight is the scourge of modern society and a major risk factor for many diseases. For this reason, understanding the genetic component predisposing to high body mass index (BMI) seems to be an important task along with preventive measures aimed at improving eating behavior and increasing physical activity. Methods We analyzed genetic data of a European cohort ( n = 21,080, 47.25% women, East Slavs ancestry >80%) for 5 frequently found genes in the context of association with obesity: IPX3 (rs3751723), MC4R (rs17782313), TMEM18 (rs6548238), PPARG (rs1801282) and FTO (rs9939609). Results Our study revealed significant associations of FTO (rs9939609) (β = 0.37 (kg/m 2 )/allele, p = <2 × 10 −16 ), MC4R (rs17782313) (β = 0.28 (kg/m 2 )/allele, p = 5.79 × 10 −9 ), TMEM18 (rs6548238) (β = 0.29 (kg/m 2 )/allele, p = 2.43 × 10 −8 ) with BMI and risk of obesity. Conclusions The results confirm the contribution of FTO, M4CR, and TMEM18 genes to the mechanism of body weight regulation and control.

Joubert syndrome (JS) is a recessive disorder that is characterized by midbrain-hindbrain malformation and shows the “molar tooth sign” on magnetic resonance imaging. Mutations in 40 genes, including Abelson helper integration site 1 ( AHI1 ), inositol polyphosphate-5-phosphatase ( INPP5E ), coiled-coil and c2 domain-containing protein 2A ( CC2D2A ), and ARL2-like protein 1 ( ARL13B ), can cause JS. Classic JS is a part of a group of diseases associated with JS, and its manifestations include various neurological signs such as skeletal abnormalities, ocular coloboma, renal disease, and hepatic fibrosis. Here, we present a proband with the molar tooth sign, ataxia, and developmental and psychomotor delays in a Dagestan family from Russia. Molecular genetic testing revealed two novel heterozygous variants, c.2924G>A (p.Arg975His) in exon 28 and c.1241C>G (p.Pro414Arg) in exon 12 of the transmembrane protein 67 ( TMEM67 ) gene. These TMEM67 gene variants significantly affected the development of JS type 6. This case highlights the importance of whole exome sequencing for a proper clinical diagnosis of children with complex motor and psycho-language delays. This case also expands the clinical phenotype and genotype of TMEM67 -associated diseases.

BackgroundLactase persistence-the ability to digest lactose through adulthood-is closely related to evolutionary adaptations and has affected many populations since the beginning of cattle breeding. Nevertheless, the contrast initial phenotype, lactase non-persistence or adult lactase deficiency, is still observed in large numbers of people worldwide.MethodsWe performed a multiethnic genetic study of lactase deficiency on 24,439 people, the largest in Russia to date. The percent of each population group was estimated according to the local ancestry inference results. Additionally, we calculated frequencies of rs4988235 GG genotype in Russian regions using the information of current location and birthplace data from the client's questionnaire.ResultsThe attained results show that among all studied population groups, the frequency of GG genotype in rs4988235 is higher than the average in the European populations. In particular, the prevalence of lactase deficiency genotype in the East Slavs group was 42.8% (95% CI: 42.1-43.4%). We also investigated the regional prevalence of lactase deficiency based on the current place of residence.ConclusionsOur study emphasizes the significance of genetic testing for diagnostics, i.e., specifically for lactose intolerance parameter, as well as the scale of the problem of lactase deficiency in Russia which needs to be addressed by the healthcare and food sectors.

Charcot–Marie–Tooth disease (CMT) is a genetically heterogeneous group of peripheral neuropathies most of which are associated with mutations in four genes including peripheral myelin protein-22 ( PMP22) , myelin protein zero ( MPZ ), gap junction protein beta1 ( GJB1 ) and mitofusin2 ( MFN2 ). This current case report describes the clinical and genetic characteristics of a 6-year-old male proband. A physical examination revealed muscular hypotonia. He started walking on his own at 18 months. A nerve conduction study with needle electromyography revealed conduction block. A novel MPZ mutation (c.398C > T, p.Pro133Leu) was revealed in the proband. This mutation was also found in the 32-year-old father of the proband. The father had had deformity of the feet and distal muscle weakness since childhood. The novel p.Pro133Leu pathogenic mutation was responsible for early onset but slowly progressive CMT1B. We assume that this site is an intolerant to change region in the MPZ gene. This variant in the MPZ gene is an important contributor to hereditary neuropathy with reduced nerve conduction velocity in the Russian population. This case highlights the importance of whole exome sequencing for a proper clinical diagnosis of CMT associated with a mutation in the MPZ gene. Keywords Charcot-Marie-Tooth disease , MPZ gene , neuropathy

Abstract The Minusinsk Basin in Southern Siberia had unique conditions for the development of ancient societies, thanks to its geographical location, favorable climatic conditions, and relative isolation. Located at the northern periphery of the eastern Eurasian steppe, surrounded by the Altai-Sayan Mountains this area witnessed numerous ancient human migrations with specific types of interaction between outside and local archaeological cultures. The genomic history of the human population of Southern Siberia from the Chalcolithic to the middle Bronze Age has been relatively well described in the recent genome-wide studies, while the genetic ancestry of populations, represented by diverse archaeological cultures of the Late Bronze and Early Iron Ages, remains a blank spot for modern paleogenomics. Here, for the first time, we present two ancient nuclear genomes of the individuals buried in the Oglakhty cemetery (early Tashtyk culture, 2nd to 4th centuries AD). Our pilot study is undertaken within a multidisciplinary project on this noteworthy site with well-preserved organic remains and provides fresh paleogenomic data on the ancient societies of Southern Siberia.

Charcot-Marie-Tooth disease (CMT) is a genetically heterogeneous group of peripheral neuropathies most of which are associated with mutations in four genes including peripheral myelin protein-22 (PMP22), myelin protein zero (MPZ), gap junction protein beta1 (GJB1) and mitofusin2 (MFN2). This current case report describes the clinical and genetic characteristics of a 6-year-old male proband. A physical examination revealed muscular hypotonia. He started walking on his own at 18 months. A nerve conduction study with needle electromyography revealed conduction block. A novel MPZ mutation (c.398C > T, p.Pro133Leu) was revealed in the proband. This mutation was also found in the 32-year-old father of the proband. The father had had deformity of the feet and distal muscle weakness since childhood. The novel p.Pro133Leu pathogenic mutation was responsible for early onset but slowly progressive CMT1B. We assume that this site is an intolerant to change region in the MPZ gene. This variant in the MPZ gene is an important contributor to hereditary neuropathy with reduced nerve conduction velocity in the Russian population. This case highlights the importance of whole exome sequencing for a proper clinical diagnosis of CMT associated with a mutation in the MPZ gene.