BackgroundAlcohol abuse has deleterious effects on human health by disrupting the functions of many organs and systems. Gut microbiota has been implicated in the pathogenesis of alcohol-related liver diseases, with its composition manifesting expressed dysbiosis in patients suffering from alcoholic dependence. Due to its inherent plasticity, gut microbiota is an important target for prevention and treatment of these diseases. Identification of the impact of alcohol abuse with associated psychiatric symptoms on the gut community structure is confounded by the liver dysfunction. In order to differentiate the effects of these two factors, we conducted a comparative “shotgun” metagenomic survey of 99 patients with the alcohol dependence syndrome represented by two cohorts—with and without liver cirrhosis. The taxonomic and functional composition of the gut microbiota was subjected to a multifactor analysis including comparison with the external control group.ResultsAlcoholic dependence and liver cirrhosis were associated with profound shifts in gut community structures and metabolic potential across the patients. The specific effects on species-level community composition were remarkably different between cohorts with and without liver cirrhosis. In both cases, the commensal microbiota was found to be depleted. Alcoholic dependence was inversely associated with the levels of butyrate-producing species from the Clostridiales order, while the cirrhosis—with multiple members of the Bacteroidales order. The opportunist pathogens linked to alcoholic dependence included pro-inflammatory Enterobacteriaceae, while the hallmarks of cirrhosis included an increase of oral microbes in the gut and more frequent occurrence of abnormal community structures. Interestingly, each of the two factors was associated with the expressed enrichment in many Bifidobacterium and Lactobacillus—but the exact set of the species was different between alcoholic dependence and liver cirrhosis. At the level of functional potential, the patients showed different patterns of increase in functions related to alcohol metabolism and virulence factors, as well as pathways related to inflammation.ConclusionsMultiple shifts in the community structure and metabolic potential suggest strong negative influence of alcohol dependence and associated liver dysfunction on gut microbiota. The identified differences in patterns of impact between these two factors are important for planning of personalized treatment and prevention of these pathologies via microbiota modulation. Particularly, the expansion of Bifidobacterium and Lactobacillus suggests that probiotic interventions for patients with alcohol-related disorders using representatives of the same taxa should be considered with caution. Taxonomic and functional analysis shows an increased propensity of the gut microbiota to synthesis of the toxic acetaldehyde, suggesting higher risk of colorectal cancer and other pathologies in alcoholics.Electronic supplementary materialThe online version of this article (10.1...
There is growing interest in non-invasive brain stimulation (NIBS) as a novel treatment option for substance-use disorders (SUDs). Recent momentum stems from a foundation of preclinical neuroscience demonstrating links between neural circuits and drug consuming behavior, as well as recent FDA-approval of NIBS treatments for mental health disorders that share overlapping pathology with SUDs. As with any emerging field, enthusiasm must be tempered by reason; lessons learned from the past should be prudently applied to future therapies. Here, an international ensemble of experts provides an overview of the state of transcranial-electrical (tES) and transcranial-magnetic (TMS) stimulation applied in SUDs. This consensus paper provides a systematic literature review on published data-emphasizing the heterogeneity of methods and outcome measures while suggesting strategies to help bridge knowledge gaps. The goal of this effort is to provide the community with guidelines for best practices in tES/TMS SUD research. We hope this will accelerate the speed at which the community translates basic neuroscience into advanced neuromodulation tools for clinical practice in addiction medicine.
We examined 13 single nucleotide polymorphisms (SNPs) spanning the coding region of the mu-opioid receptor gene (OPRM1), among 382 European Americans (EAs) affected with substance dependence [alcohol dependence (AD) and/or drug dependence (DD)] and 338 EA healthy controls. These SNPs delineated two haplotype blocks. Genotype distributions for all SNPs were in Hardy-Weinberg equilibrium (HWE) in controls, but in cases, four SNPs in Block I and three SNPs in Block II showed deviation from HWE. Significant differences were found between cases and controls in allele and/or genotype frequencies for six SNPs in Block I and two SNPs in Block II. Association of SNP4 in Block I with DD (allele: P=0.004), SNP5 in Block I with AD and DD (allele: P< or =0.005 for both) and two SNPs in Block II with AD (SNP11 genotype: P=0.002; SNP12 genotype: P=0.001) were significant after correction for multiple testing. Frequency distributions of haplotypes (constructed by five tag SNPs) differed significantly for cases and controls (P<0.001 for both AD and DD). Logistic regression analyses confirmed the association between OPRM1 variants and substance dependence, when sex and age of subjects and alleles, genotypes, haplotypes or diplotypes of five tag SNPs were considered. Population structure analyses excluded population stratification artifact. Additional supporting evidence for association between OPRM1 and AD was obtained in a smaller Russian sample (247 cases and 100 controls). These findings suggest that OPRM1 intronic variants play a role in susceptibility to AD and DD in populations of European ancestry.
These findings suggest that genetic variants of GABRA2 increase risk for AD in the Russian population and provide additional support to the hypothesis that polymorphic variation at the GABRA2 locus plays an important role in predisposing to AD at least in European-ancestry populations.
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