Multiple sclerosis (MS) is an autoimmune neuro-inflammatory disease arising from complex interactions of genetic, epigenetic, and environmental factors. Variations in genes of some microRNAs—key post-transcriptional regulators of many genes—can influence microRNAs expression/function and contribute to MS via expression changes of protein-coding target mRNA genes. We performed an association study of polymorphous variants of MIR146A rs2910164, MIR196A2 rs11614913, MIR499A rs3746444 MIR223 rs1044165 and their combinations with MS risk and severity. 561 unrelated patients with bout-onset MS and 441 healthy volunteers were enrolled in the study. We observed associations of MS risk with allele MIR223*T and combination (MIR223*T + MIR146A*G/G) carriage in the entire groups and in women at Bonferroni-corrected significance level (p_corr < 0.05). Besides, MIR146A*G/G association with MS was observed in women with nominal significance (p_f = 0.025). No MS associations were found in men. A more severe MS course (MSSS value > 3.5) was associated with the carriage of MIR499A*C/T and, less reliably, of MIR499A*C (p_corr = 0.006 and p_corr = 0.024, respectively) and with the carriage of combinations (MIR499A*C/T + MIR196A2*C) and (MIR499A*C + MIR196A2*C) (p_corr = 0.00078 and p_corr = 0.0059, respectively). These associations also showed gender specificity, as they were not significant in men and substantially reinforced in women. The strongest association with MS severity was observed in women for combination (MIR499A*C/T + MIR196A2*C): p_corr = 4.43 × 10⁻⁶ and OR = 3.23 (CI: 1.99–5.26).

Aim: Association analysis of genome-wide association studies (GWAS) identified multiple sclerosis (MS) risk genetic variants with glatiramer acetate (GA) treatment efficacy. Patients & methods: SNPs in 17 GWAS-identified immune response loci were analyzed in 296 Russian MS patients as possible markers of optimal GA treatment response for at least 2 years. Results: Alleles/genotypes of EOMES, CLEC16A, IL22RA2, PVT1 and HLA-DRB1 were associated by themselves with event-free phenotype during GA treatment for at least 2 years (p f = 0.032 - 0.00092). The biallelic combinations including EOMES, CLEC16A, IL22RA2, PVT1, TYK2, CD6, IL7RA and IRF8 genes were associated with response to GA with increased significance level (p f = 0.0060 - 1.1 × 10– 5). The epistasic interactions or additive effects were observed between the components of the identified biallelic combinations. Conclusion: We pinpointed the involvement of several GWAS-identified MS risk loci in GA therapy efficacy. These findings may be aggregated ...

Background: Substance use disorders (SUDs), including alcohol and drug dependence, and smoking, pose a public health threat with their high prevalence and comorbidity with other diseases, and contribution to mortality. SUDs are highly correlated, and their genetic background is shared to some degree. Objectives: We aimed to investigate the genetic associations of previously reported loci for a wide range of SUDs in an unstudied Ukrainian population. Methods: We collected data from 595 individuals (339 women, 253 men), including 321 participants from two rehab centres. Based on clinical review and questionnaire data we defined drug dependence, alcohol dependence, alcohol abuse, binge drinking, smoking, opiate, amphetamine, cannabis, and hallucinogen use, along with several intermediary alcohol use and smoking variables considering the amount of use and the level of dependence. We genotyped COMT -rs4680, ADH1B-ADH1C -rs1789891, and HTR2A -rs6313, and applied logistic and ordered logistic regression assuming an additive inheritance model, controlling for the recruitment group, other substance uses, age, and sex, in the association analyses. Results: We replicate ( P <0.05) the associations at COMT -rs4680 with smoking status (OR[95% CI]=1.56[1.01-2.41], P =0.047) and heaviness (1.37[1.04-1.80], P =0.026), and at ADH1B-ADH1C -rs1789891 and HTR2A -rs6313 with alcohol dependence (1.69[1.03-2.76], P =0.038 and 0.66[0.47-0.92, P =0.016], respectively). Furthermore, we provide evidence for an association at HTR2A -rs6313 with hallucinogen use (0.58[0.35-0.98], P =0.040). Conclusion: In this study on multiple SUDs we shed light on the genetic background of SUDs in Ukrainians and provide further evidence that variation at COMT is mainly associated with smoking, at ADH1B-ADH1C with alcohol-related variables, whereas HTR2A is a more general SUD-associated locus. Highlights: We present the first genetic study of substance use disorders in Ukrainians We replicate the associations at COMT -rs4680 with smoking status and heaviness, and ADH1B-ADH1C -rs1789891 and HTR2A -rs6313 with alcohol dependence We provide evidence for an association at HTR2A -rs6313 with hallucinogen use