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Natural selection acts ubiquitously on complex human traits, predominantly constraining the occurrence of extreme phenotypes (stabilizing selection). These constrains propagate to DNA sequence variants associated with traits under selection. The genetic imprints of such evolutionary events can thus be detected via combining effect size estimates from genetic association studies and the corresponding allele frequencies. While this approach has been successfully applied to high-level traits, the prevalence and mode of selection acting on molecular traits remains poorly understood. Here, we estimate the action of natural selection on genetic variants associated with metabolite levels, an important layer of molecular traits. By leveraging summary statistics of published genome-wide association studies with large sample sizes, we find strong evidence of stabilizing selection for 15 out of 97 plasma metabolites, with an overrepresentation of amino acids among such cases. Mendelian randomization analysis revealed that metabolites under stronger stabilizing selection display larger effects on key cardiometabolic traits, suggesting that maintaining a healthy cardiometabolic profile may be an important source of selective constraints on the metabolome. Metabolites under strong stabilizing selection in humans are also more conserved in their concentrations among diverse mammalian species, suggesting shared selective forces across micro and macroevolutionary time scales. Finally, we also found evidence for both disruptive and directional selection on specific lipid metabolites, potentially indicating ongoing evolutionary adaptation in humans. Overall, this study demonstrates that variation in metabolite levels among humans is frequently shaped by natural selection and this may be acting indirectly through maintaining cardiometabolic fitness.

Sick sinus syndrome (SSS) encompasses a group of conduction disorders characterized by the inability of sinoatrial node to perform its pacemaker function. Our aim was to identify genetic predictors of SSS in a prospective cohort of patients admitted to the clinic for pacemaker implantation using single-locus and multilocus approaches. We performed genotyping for polymorphic markers of CLCNKA (rs10927887), SCN10A (rs6795970), FNDC3B (rs9647379), MIR146A (rs2910164), SYT10 (rs7980799), MYH6 (rs365990), and KCNE1 (rs1805127) genes in the group of 284 patients with SSS and 243 healthy individuals. Associations between the studied loci and SSS were tested using logistic regression under recessive genetic model using sex and age as covariates. Multilocus analysis was performed using Markov chain Monte Carlo method implemented in the APSampler program. Correction for multiple testing was performed using Benjamini–Hochberg procedure. We detected an individual association between KCNE1 rs1805127*A allele and SSS in the total study group (OR 0.43, PFDR = 0.028) and in the subgroup of patients with 2nd or 3rd degree sinoatrial block (OR 0.17, PFDR = 0.033), and identified seven allelic patterns associated with the disease. SCN10A rs6795970*T and MIR146A rs2910164*C alleles were present in all seven combinations associated with SSS. The highest risk of SSS was conferred by the combination SCN10A rs6795970*T+FNDC3B rs9647379*C+MIR146A rs2910164*C+SYT10 rs7980799*C+KCNE1 rs1805127*G (OR 2.98, CI 1.77–5.00, P = 1.27 × 10–5, PFDR = 0.022). Our findings suggest that KCNE1 rs1805127 polymorphism may play a role in susceptibility to sinoatrial node dysfunction, particularly presenting as 2nd or 3rd degree sinoatrial block, and the risk-modifying effect of other studied loci is better detected using multilocus approach.

We tested associations between 13 established genetic variants and type 2 diabetes (T2D) in 1371 study participants from the Volga-Ural region of the Eurasian continent, and evaluated the predictive ability of the model containing polygenic scores for the variants associated with T2D in our dataset, alone and in combination with other risk factors such as age and sex. Using logistic regression analysis, we found associations with T2D for the CCL20 rs6749704 (OR = 1.68, PFDR = 3.40 × 10−5), CCR5 rs333 (OR = 1.99, PFDR = 0.033), ADIPOQ rs17366743 (OR = 3.17, PFDR = 2.64 × 10−4), TCF7L2 rs114758349 (OR = 1.77, PFDR = 9.37 × 10−5), and CCL2 rs1024611 (OR = 1.38, PFDR = 0.033) polymorphisms. We showed that the most informative prognostic model included weighted polygenic scores for these five loci, and non-genetic factors such as age and sex (AUC 85.8%, 95%CI 83.7–87.8%). Compared to the model containing only non-genetic parameters, adding the polygenic score for the five T2D-associated loci showed improved net reclassification (NRI = 37.62%, 1.39 × 10−6). Inclusion of all 13 tested SNPs to the model with age and sex did not improve the predictive ability compared to the model containing five T2D-associated variants (NRI = −17.86, p = 0.093). The five variants associated with T2D in people from the Volga-Ural region are linked to inflammation (CCR5, CCL2, CCL20) and glucose metabolism regulation (TCF7L, ADIPOQ2). Further studies in independent groups of T2D patients should validate the prognostic value of the model and elucidate the molecular mechanisms of the disease development.

Background Genome-wide association studies have captured a large proportion of genetic variation related to type 1 diabetes mellitus (T1D). However, most of these studies are performed in populations of European ancestry and therefore the disease risk estimations can be inaccurate when extrapolated to other world populations. Methods We conducted a case-control study in 1866 individuals from the three major populations of the Republic of Bashkortostan (Russians, Tatars, and Bashkirs) in Russian Federation, using single-locus and multilocus approach to identify genetic predictors of T1D. Results We found that LTA rs909253 and TNF rs1800629 polymorphisms were associated with T1D in the group of Tatars. Meta-analysis of the association study results in the three ethnic groups has confirmed the association between the T1D risk and LTA rs909253 genetic variant. LTA rs909253 and TNF rs1800629 loci were also featured in combinations most significantly associated with T1D. Conclusion Our findings suggest that LTA rs909253 and TNF rs1800629 polymorphisms are associated with the risk of T1D both independently and in combination with polymorphic markers in other inflammatory genes, and the analysis of multi-allelic combinations provides valuable insight in the study of polygenic traits.

Background Genome-wide association studies identified numerous susceptibility loci for multiple sclerosis in populations of European ancestry, but the associations are not always reproducible in other populations due to admixture and different linkage disequilibrium patterns obscuring true association signals. Objective Our aim was to identify genetic predictors of multiple sclerosis in three ethnically homogenous populations from the Volga-Ural region of Russian Federation. Methods In the largest to date study of multiple sclerosis in Russian population, involving 2048 participants from the Republic of Bashkortostan, Russian Federation (641 patients with multiple sclerosis and 1407 unaffected individuals), we performed replication analysis of previously identified genome-wide signals for multiple sclerosis. Associations were tested using logistic regression analysis under additive genetic model adjusted for sex. Meta-analysis of the study results in three populations was performed under fixed effects and random effects models. Results We demonstrate the association with multiple sclerosis of the five variants (INAVA rs7522462, EOMES rs11129295, C6orf10 rs3129934, CD86 rs9282641, and GPR65 rs2119704). The strongest association (OR = 2.16, CI:1.85–2.74, P = 2.53x10−13) was detected for rs3129934 polymorphism in the major histocompatibility region. Multilocus analysis has revealed 322 and 27 allelic patterns associated with multiple sclerosis in women and men, respectively. In women, the highest risk of MS was conferred by C6orf10 rs3129934*T/T + STAT3 rs744166*T combination (OR = 11.87), in men – by C6orf10 rs3129934*T + EOMES rs11129295*C + RPS6KB1 rs180515*C combination (OR = 3.25). Conclusion We confirm five associations with multiple sclerosis previously reported in genome-wide scans in Europeans in three ethnic groups from the Volga-Ural region of Russia.

Sick sinus syndrome (SSS) encompasses a group of conduction disorders characterized by the inability of sinoatrial node to perform its pacemaker function. Our aim was to identify genetic predictors of SSS in a prospective cohort of patients admitted to the clinic for pacemaker implantation using single-locus and multilocus approaches. We performed genotyping for polymorphic markers of CLCNKA (rs10927887), SCN10A (rs6795970), FNDC3B (rs9647379), MIR146A (rs2910164), SYT10 (rs7980799), MYH6 (rs365990), and KCNE1 (rs1805127) genes in the group of 284 patients with SSS and 243 healthy individuals. Associations between the studied loci and SSS were tested using logistic regression under recessive genetic model using sex and age as covariates. Multilocus analysis was performed using Markov chain Monte Carlo method implemented in the APSampler program. Correction for multiple testing was performed using Benjamini-Hochberg procedure. We detected an individual association between KCNE1 rs1805127*A allele and SSS in the total study group (OR 0.43, P

Aim. To analyze the association between tumor necrosis factor-alpha gene –308 G/A polymorphism and essential arterial hypertension (EAH). Material and methods. The study included 354 EAH patients and 295 age-matched healthy subjects. DNA was extracted from venous blood. Genotyping was performed using polymerase chain reaction followed by restriction amplicon analysis. Results. TNFA -308*G/*G genotype frequency was significantly lower among EAH patients with stroke than in control group (60,98% vs 78,98%; p=0,015). EAH patients with TNFA -308 *G/*G genotype had lower stroke risk (OR=0,38; 95% CI: 0,21-0,83). Conclusion. The results obtained suggest that TNFA gene -308G/A polymorphism is involved in stroke pathogenesis among EAH patients.