Mendelian Randomization Analysis Identifies Inverse Causal Relationship between External Eating and Metabolic Phenotypes.

Disordered eating contributes to weight gain, obesity, and type 2 diabetes (T2D), but the precise mechanisms underlying the development of different eating patterns and connecting them to specific metabolic phenotypes remain unclear. We aimed to identify genetic variants linked to eating behaviour and investigate its causal relationships with metabolic traits using Mendelian randomization (MR). We tested associations between 30 genetic variants and eating patterns in individuals with T2D from the Volga-Ural region and investigated causal relationships between variants associated with eating patterns and various metabolic and anthropometric traits using data from the Volga-Ural population and large international consortia. We detected associations between HTR1D and CDKAL1 and external eating; between HTR2A and emotional eating; between HTR2A, NPY2R, HTR1F, HTR3A, HTR2C, CXCR2, and T2D. Further analyses in a separate group revealed significant associations between metabolic syndrome (MetS) and the loci in CRP, ADCY3, GHRL, CDKAL1, BDNF, CHRM4, CHRM1, HTR3A, and AKT1 genes. MR results demonstrated an inverse causal relationship between external eating and glycated haemoglobin levels in the Volga-Ural sample. External eating influenced anthropometric traits such as body mass index, height, hip circumference, waist circumference, and weight in GWAS cohorts. Our findings suggest that eating patterns impact both anthropometric and metabolic traits.

Polygenic markers of survival and longevity in the antioxidant genes PON1, PON2, MTHFR, MSRA, SOD1, NQO1, and CAT in a 20-year follow-up study in the population from the Volga-Ural region.

BACKGROUND: Genetic background of healthy or pathological styles of aging and human lifespan is determined by joint gene interactions. Lucky combinations of antioxidant gene polymorphisms can result in a highly adaptive phenotype, providing a successful way to interact with external triggers. Our purpose was to identify the polygenic markers of survival and longevity in the antioxidant genes among elderly people with physiological and pathological aging. METHODS: In a 20-year follow-up study of 2350 individuals aged 18-114 years residing in the Volga-Ural region of Russia, sex-adjusted association analyses of MTHFR rs1801133, MSRA rs10098474, PON1 rs662, PON2 rs7493, SOD1 rs2070424, NQO1 rs1131341 and CAT rs1001179 polymorphic loci with longevity were carried out. Survival analysis was subsequently performed using the established single genes and gene-gene combinations as cofactors. RESULTS: The PON1 rs662*G allele was defined as the main longevity marker in women (OR = 1.44, p = 3E-04 in the log-additive model; HR = 0.77, p = 1.9E-04 in the Cox-survival model). The polymorphisms in the MTHFR, MSRA, PON2, SOD1, and CAT genes had an additive effect on longevity. A strong protective effect of combined MTHFR rs1801133*C, MSRA rs10098474*T, PON1 rs662*G, and PON2 rs7493*C alleles against mortality was obtained in women (HR = 0.81, p = 5E-03). The PON1 rs662*A allele had a meaningful impact on mortality for both long-lived men with cerebrovascular accidents (HR = 1.76, p = 0.027 for the PON1 rs662*AG genotype) and women with cardiovascular diseases (HR = 1.43, p = 0.002 for PON1 rs662*AA genotype). The MTHFR rs1801133*TT (HR = 1.91, p = 0.036), CAT rs1001179*TT (HR = 2.83, p = 0.031) and SOD1 rs2070424*AG (HR = 1.58, p = 0.018) genotypes were associated with the cancer mortality. CONCLUSION: In our longitudinal 20-year study, we found the combinations of functional polymorphisms in antioxidant genes involved in longevity and survival in certain clinical phenotypes in the advanced age.

COVID-19: Mechanisms, risk factors, genetics, non-coding RNAs and neurologic impairments.

The novel coronavirus infection (COVID-19) causes a severe acute illness with the development of respiratory distress syndrome in some cases. COVID-19 is a global problem of mankind to this day. Among its most important aspects that require in-depth study are pathogenesis and molecular changes in severe forms of the disease. A lot of literature data is devoted to the pathogenetic mechanisms of COVID-19. Without dwelling in detail on some paths of pathogenesis discussed, we note that at present there are many factors of development and progression. Among them, this is the direct role of both viral non-coding RNAs (ncRNAs) and host ncRNAs. One such class of ncRNAs that has been extensively studied in COVID-19 is microRNAs (miRNAs) and long non-coding RNAs (lncRNAs). Moreover, Initially, it was believed that this COVID-19 was limited to damage to the respiratory system. It has now become clear that COVID-19 affects not only the liver and kidneys, but also the nervous system. In this review, we summarized the current knowledge of mechanisms, risk factors, genetics and neurologic impairments in COVID-19. In addition, we discuss and evaluate evidence demonstrating the involvement of miRNAs and lnRNAs in COVID-19 and use this information to propose hypotheses for future research directions.

Integrating Common Risk Factors with Polygenic Scores Improves the Prediction of Type 2 Diabetes.

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.

Alu Deletions in LAMA2 and CDH4 Genes Are Key Components of Polygenic Predictors of Longevity.

Longevity is a unique human phenomenon and a highly stable trait, characterized by polygenicity. The longevity phenotype occurs due to the ability to successfully withstand the age-related genomic instability triggered by Alu elements. The purpose of our cross-sectional study was to evaluate the combined contribution of ACE*Ya5ACE, CDH4*Yb8NBC516, COL13A1*Ya5ac1986, HECW1*Ya5NBC182, LAMA2*Ya5-MLS19, PLAT*TPA25, PKHD1L1*Yb8AC702, SEMA6A*Yb8NBC597, STK38L*Ya5ac2145 and TEAD1*Ya5ac2013 Alu elements to longevity. The study group included 2054 unrelated individuals aged from 18 to 113 years who are ethnic Tatars from Russia. We analyzed the dynamics of the allele and genotype frequencies of the studied Alu polymorphic loci in the age groups of young (18-44 years old), middle-aged (45-59 years old), elderly (60-74 years old), old seniors (75-89 years old) and long-livers (90-113 years old). Most significant changes in allele and genotype frequencies were observed between the long-livers and other groups. The search for polygenic predictors of longevity was performed using the APSampler program. Attaining longevity was associated with the combinations LAMA2*ID + CDH4*D (OR = 2.23, PBonf = 1.90 × 10-2) and CDH4*DD + LAMA2*ID + HECW1*D (OR = 4.58, PBonf = 9.00 × 10-3) among persons aged between 18 and 89 years, LAMA2*ID + CDH4*D + SEMA6A*I for individuals below 75 years of age (OR = 3.13, PBonf = 2.00 × 10-2), LAMA2*ID + HECW1*I for elderly people aged 60 and older (OR = 3.13, PBonf = 2.00 × 10-2) and CDH4*DD + LAMA2*D + HECW1*D (OR = 4.21, PBonf = 2.60 × 10-2) and CDH4*DD + LAMA2*D + ACE*I (OR = 3.68, PBonf = 1.90 × 10-2) among old seniors (75-89 years old). The key elements of combinations associated with longevity were the deletion alleles of CDH4 and LAMA2 genes. Our results point to the significance for human longevity of the Alu polymorphic loci in CDH4, LAMA2, HECW1, SEMA6A and ACE genes, involved in the integration systems.

Multilocus evaluation of genetic predictors of multiple sclerosis.

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.

Genetic predictors of sick sinus syndrome.

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.

Multilocus associations of inflammatory genes with the risk of type 1 diabetes.

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.

CXCL13 polymorphism is associated with essential hypertension in Tatars from Russia.

Essential arterial hypertension is a disease with distinct yet unexplored inflammatory component. Our aim was to assess the role of chemokine genes and their interaction in its development. Genotyping of polymorphic markers in six chemokine genes (CXCL13, CCL8, CCL16, CCL17, CCL18, and CCL23) was performed in the group of 522 men of Tatar ethnic origin from the Republic of Bashkortostan, Russia (213 patients with essential hypertension and 309 healthy individuals without history of cardiovascular disease). We found a strong association of CXCL13 rs355689*C allele with essential hypertension under additive (OR 0.56, PFDR = 0.008) and dominant (OR 0.41, PFDR 4.38 × 10- 4) genetic model. The analysis of gene-gene interactions revealed 12 allele/genotype combinations that remained significantly associated with essential hypertension after correction for multiple testing was applied, and each of these combinations included CXCL13 rs355689 polymorphism. Our results indicate that CXCL13 rs355689 polymorphism is strongly associated with essential hypertension in the ethnic group of Tatars, alone and in combination with polymorphic markers in other chemokine genes.

Genetic determinants of essential hypertension in the population of Tatars from Russia.

OBJECTIVE: Systemic inflammation and impaired function of endothelium play an important role in the development of hypertension. Our study aimed to analyze an association between essential hypertension and polymorphic markers in candidate genes in the group of 530 Tatars from the Republic of Bashkortostan, Russia. METHODS: The study group consisted of 216 male patients with essential hypertension (mean age 48.92 ±â€Š8.8 years) and 314 healthy individuals of corresponding sex and age without history of cardiovascular disease. Association between studied polymorphisms and essential hypertension was analyzed using PLINK. RESULTS: We detected an association between EDNRB rs5351, VEGFA -2549(18)I/D, and ADRB2 rs1042713 polymorphisms and essential hypertension in men of Tatar ethnic origin. EDNRB, VEGFA, and VCAM1 single-nucleotide polymorphisms were associated with SBP and DBP. However, only EDNRB rs5351 remained associated with hypertension after Bonferroni correction for multiple testing. A Markov chain Monte Carlo-based approach implemented in the APSampler program was used to analyze association of genotype and/or allele combinations with disease. The most influential in conferring risk of hypertension was EDNRBG/G+ADRB2A+VCAM1A combination (odds ratio = 4.15, PBonf = 5.43 × 10). CONCLUSION: Our results suggest that rs5351 single-nucleotide polymorphism is a strong independent predictor of essential hypertension in men of Tatar ethnic origin.

Genotype/allelic combinations as potential predictors of myocardial infarction.

In order to find new informative predictors of myocardial infarction, we performed an analysis of genotype frequencies of polymorphic markers of SELE (rs2076059, 3832T > C), SELP (rs6131, S290 N), SELL (rs1131498, F206L), ICAM1 (rs5498, K469E), VCAM1 (rs3917010, c.928 + 420A > C), PECAM1 (rs668, V125L), VEGFA (rs35569394, -2549(18)I/D), CCL2 (rs1024611, -2518A > G), NOS3 (rs1799983, E298D), and DDAH1 (rs669173, c.303 + 30998A > G) genes in the group of Russian men with myocardial infarction (N = 315) and the control group of corresponding ethnicity, gender, and age (N = 286). Using Markov chain Monte-Carlo method (APSampler), we found genotype combinations associated with increased and decreased risk of myocardial infarction. The most significant associations were detected for PECAM1*V/V + DDAH1*C (OR = 4.17 CI 1.56-11.15 Pperm = 0.005) SELE*C + VEGFA*I + CCL2*G + VCAM1*A + NOS3*D (OR = 2.74 CI 1.66-4.52 Pperm = 2.09 × 10(-5)), and VEGFA*D/D + CCL2*A + DDAH1*C (OR = 0.44 CI 0.28-0.7 Pperm = 7.89 × 10(-5)) genotype combinations.

The CXCR2 Gene Polymorphism Is Associated with Stroke in Patients with Essential Hypertension.

Hypertension is the major risk factor for stroke, and genetic factors contribute to its development. Inflammation has been hypothesized to be the key link between blood pressure elevation and stroke. We performed an analysis of the association between inflammatory mediator gene polymorphisms and the incidence of stroke in patients with essential hypertension (EH). The study group consisted of 625 individuals (296 patients with noncomplicated EH, 71 hypertensive patients with ischemic stroke, and 258 control subjects). Both patients and controls were ethnic Tatars originating from the Republic of Bashkortostan (Russian Federation). The analysis has shown that the risk of ischemic stroke was associated with the CXCR2 rs1126579 polymorphism. Our results indicate that among patients with EH, the heterozygous genotype carriers had a higher risk of stroke (OR = 1.72, 95% CI 1.01-2.92), whereas the CXCR2*C/C genotype was protective against stroke (OR = 0.32, 95% CI 0.12-0.83). As shown by the gene-gene interaction analysis, the CXCR2 rs1126579 polymorphism was also present in all genotype/allele combinations associated with the risk of stroke. Genetic patterns associated with stroke also included polymorphisms in the CCL2, CCL18, CX3CR1, CCR5, and CXCL8 (IL8) genes, although no association between these loci and stroke was detected by individual analysis.

Polymorphisms of inflammatory markers and risk of essential hypertension in Tatars from Russia.

Essential hypertension (EH) is a common disease with a clear genetic component. Inflammation and endothelial dysfunction play a prominent role in the development of persistent blood pressure elevation. The aim of the current study was to detect an association between EH and polymorphic markers in genes encoding for molecules involved in the control of intercellular interactions during the inflammation process. We analysed SNPs in SELE, SELP, SELL, ICAM1, VEGFA, IL1B, IL6, IL10 and IL12B genes in a group of 534 men of Tatar ethnicity (217 patients with EH and 317 controls). Using a Markov chain Monte-Carlo-based approach (APSampler), we found genotype and allelic combinations associated with EH. The most significant associations were observed for SELE rs2076059*C-SELP rs6131*A-VEGFA -2549*I-IL1B rs16944*C (p = 3.42 × 10(-5), FDR q = 0.035) and SELE rs2076059*C-SELP rs6131*A-IL12B rs3212227*C-IL1B rs16944*C (p = 323 × 10(-4), FDR q = 0.035).