GABRA2 rs279858-linked variants are associated with disrupted structural connectome of reward circuits in heroin abusers

Atp1a2 and Kcnj9 Are Candidate Genes Underlying Sensitivity to Oxycodone-Induced Locomotor Activation and Withdrawal-Induced Anxiety-Like Behaviors in C57BL/6 Substrains

Opioid use disorder is heritable, yet its genetic etiology is largely unknown. C57BL/6J and C57BL/6NJ mouse substrains exhibit phenotypic diversity in the context of limited genetic diversity which together can facilitate genetic discovery. Here, we found C57BL/6NJ mice were less sensitive to oxycodone (OXY)-induced locomotor activation versus C57BL/6J mice in a conditioned place preference paradigm. Narrow-sense heritability of OXY-induced locomotor activity traits ranged from 0.22 to 0.31, implicating suitability for genetic analysis. Quantitative trait locus (QTL) mapping in an F2 cross identified a chromosome 1 QTL explaining 7%-12% of the variance in OXY locomotion and anxiety-like withdrawal in the elevated plus maze. A second QTL for EPM withdrawal behavior on chromosome 5 near Gabra2 (alpha-2 subunit of GABA-A receptor) explained 9% of the variance. To narrow the chromosome 1 locus, we generated recombinant lines spanning 163-181 Mb, captured the QTL for OXY locomotor traits and withdrawal, and fine-mapped a 2.45-Mb region (170.16-172.61 Mb). Transcriptome analysis identified five, localized striatal cis-eQTL transcripts and two were confirmed at the protein level (KCNJ9, ATP1A2). Kcnj9 codes for a potassium channel (GIRK3) that is a major effector of mu opioid receptor signaling. Atp1a2 codes for a subunit of a Na+/K+ ATPase enzyme that regulates neuronal excitability and shows functional adaptations following chronic opioid administration. To summarize, we identified two candidate genes underlying the physiological and behavioral properties of opioids, with direct preclinical relevance to investigators employing these widely used substrains and clinical relevance to human genetic studies of opioid use disorder.

Genomic factors associated with substance use disorder relapse: A critical review

Several genetic and epigenetic factors contribute to the elevated substance use disorder (SUD) relapse vulnerability, yet a comprehensive investigation into these factors is lacking. This review aims to delve into current literature to highlight key genomic factors associated with SUD relapse. Focusing on genetic predisposition and epigenetic modifications the review synthesized research findings of several genetic polymorphisms, histone modifications and DNA methylation patterns contributing to the initiation of SUD and the elevated relapse susceptibility. Notably, specific gene polymorphisms, such as Dopamine Receptor D2 gene (DRD2), Gamma-Aminobutyric Acid Receptor Alpha gene (GABRA2), Catechol-O-methyltransferase (COMT) gene, Dopamine Transporter (DAT1) gene and others were identified to be connected to various patterns of SUD relapse. Furthermore, SUD initiation and relapse has been shown to be influenced by epigenetics. Specifically, CpG hypermethylation has been associated with severe alcohol use disorder in the 5' untranslated region of the Bladder Cancer Associated Protein gene (BLCAP) and the upstream region of the Active BCR Related gene (ABR). Co-users of cannabis and tobacco showed notable variations in CpG site methylation, especially at the Aryl Hydrocarbon Receptor Repressor (AHRR), and factor II receptor-like 3 gene sites (F2RL3). In conclusion, there is good evidence of certain associations between genomic factors and relapse to SUD. However, further research is needed to ascertain causality effects of these factors and develop novel interventions for effective treatment and relapse prevention.

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.

Circadian rhythm disruptions associated with opioid use disorder in synaptic proteomes of human dorsolateral prefrontal cortex and nucleus accumbens

Opioid craving and relapse vulnerability is associated with severe and persistent sleep and circadian rhythm disruptions. Understanding the neurobiological underpinnings of circadian rhythms and opioid use disorder (OUD) may prove valuable for developing new treatments for opioid addiction. Previous work indicated molecular rhythm disruptions in the human brain associated with OUD, highlighting synaptic alterations in the dorsolateral prefrontal cortex (DLPFC) and nucleus accumbens (NAc)-key brain regions involved in cognition and reward, and heavily implicated in the pathophysiology of OUD. To provide further insights into the synaptic alterations in OUD, we used mass-spectrometry based proteomics to deeply profile protein expression alterations in bulk tissue and synaptosome preparations from DLPFC and NAc of unaffected and OUD subjects. We identified 55 differentially expressed (DE) proteins in DLPFC homogenates, and 44 DE proteins in NAc homogenates, between unaffected and OUD subjects. In synaptosomes, we identified 161 and 56 DE proteins in DLPFC and NAc, respectively, of OUD subjects. By comparing homogenate and synaptosome protein expression, we identified proteins enriched specifically in synapses that were significantly altered in both DLPFC and NAc of OUD subjects. Across brain regions, synaptic protein alterations in OUD subjects were primarily identified in glutamate, GABA, and circadian rhythm signaling. Using time-of-death (TOD) analyses, where the TOD of each subject is used as a time-point across a 24-h cycle, we were able to map circadian-related changes associated with OUD in synaptic proteomes associated with vesicle-mediated transport and membrane trafficking in the NAc and platelet-derived growth factor receptor beta signaling in DLPFC. Collectively, our findings lend further support for molecular rhythm disruptions in synaptic signaling in the human brain as a key factor in opioid addiction.

The evolution of Big Data in neuroscience and neurology

Neurological diseases are on the rise worldwide, leading to increased healthcare costs and diminished quality of life in patients. In recent years, Big Data has started to transform the fields of Neuroscience and Neurology. Scientists and clinicians are collaborating in global alliances, combining diverse datasets on a massive scale, and solving complex computational problems that demand the utilization of increasingly powerful computational resources. This Big Data revolution is opening new avenues for developing innovative treatments for neurological diseases. Our paper surveys Big Data's impact on neurological patient care, as exemplified through work done in a comprehensive selection of areas, including Connectomics, Alzheimer's Disease, Stroke, Depression, Parkinson's Disease, Pain, and Addiction (e.g., Opioid Use Disorder). We present an overview of research and the methodologies utilizing Big Data in each area, as well as their current limitations and technical challenges. Despite the potential benefits, the full potential of Big Data in these fields currently remains unrealized. We close with recommendations for future research aimed at optimizing the use of Big Data in Neuroscience and Neurology for improved patient outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40537-023-00751-2.

Abnormal resting-state functional connectome in methamphetamine-dependent patients and its application in machine-learning-based classification

Brain resting-state functional connectivity (rsFC) has been widely analyzed in substance use disorders (SUDs), including methamphetamine (MA) dependence. Most of these studies utilized Pearson correlation analysis to assess rsFC, which cannot determine whether two brain regions are connected by direct or indirect pathways. Moreover, few studies have reported the application of rsFC-based graph theory in MA dependence. We evaluated alterations in Tikhonov regularization-based rsFC and rsFC-based topological attributes in 46 MA-dependent patients, as well as the correlations between topological attributes and clinical variables. Moreover, the topological attributes selected by least absolute shrinkage and selection operator (LASSO) were used to construct a support vector machine (SVM)-based classifier for MA dependence. The MA group presented a subnetwork with increased rsFC, indicating overactivation of the reward circuit that makes patients very sensitive to drug-related visual cues, and a subnetwork with decreased rsFC suggesting aberrant synchronized spontaneous activity in subregions within the orbitofrontal cortex (OFC) system. The MA group demonstrated a significantly decreased area under the curve (AUC) for the clustering coefficient (Cp) (Pperm < 0.001), shortest path length (Lp) (Pperm = 0.007), modularity (Pperm = 0.006), and small-worldness (σ, Pperm = 0.004), as well as an increased AUC for global efficiency (E.glob) (Pperm = 0.009), network strength (Sp) (Pperm = 0.009), and small-worldness (ω, Pperm < 0.001), implying a shift toward random networks. MA-related increased nodal efficiency (E.nodal) and altered betweenness centrality were also discovered in several brain regions. The AUC for ω was significantly positively associated with psychiatric symptoms. An SVM classifier trained by 36 features selected by LASSO from all topological attributes achieved excellent performance, cross-validated prediction area under the receiver operating characteristics curve, accuracy, sensitivity, specificity, and kappa of 99.03 ± 1.79, 94.00 ± 5.78, 93.46 ± 8.82, 94.52 ± 8.11, and 87.99 ± 11.57%, respectively (Pperm < 0.001), indicating that rsFC-based topological attributes can provide promising features for constructing a high-efficacy classifier for MA dependence.

Ultrasound combined with glial cell line-derived neurotrophic factor-loaded microbubbles for the targeted treatment of drug addiction

Drug addiction is a serious problem globally, recently exacerbated by the COVID-19 pandemic. Glial cell-derived neurotrophic factor (GDNF) is considered a potentially effective strategy for the treatment of addiction. Previous animal experiments have proven that GDNF has a good therapeutic effect on drug addiction, but its clinical application is limited due to its poor blood-brain barrier (BBB) permeability. Low-frequency focused ultrasound, combined with microbubbles, is a non-invasive and reversible technique for locally-targeted BBB opening. In the present study, magnetic resonance imaging-guided low-frequency focused ultrasound, combined with GDNF microbubbles, was used to target BBB opening in the ventral tegmental area (VTA) region. The effects of GDNF on morphine-induced conditioned place preference (CPP) and acute withdrawal symptoms in rats after a partially opened BBB were evaluated by behavioral observation. Western blot was used to detect changes in tyrosine hydroxylase (TH) expression levels in the VTA region after different treatments, and high performance liquid chromatography was used to detect the changes in monoamine neurotransmitter content. The results showed that ultrasound combined with GDNF microbubbles targeted and opened the BBB in the VTA region, and significantly increased GDNF content, destroyed morphine-induced CPP, and reduced the withdrawal symptoms of morphine addiction in rats. Furthermore, the up-regulation of TH expression and the increase of norepinephrine and dopamine content induced by morphine were significantly reversed, and the increase of 5-hydroxytryptamine content was partially reversed. Therefore, ultrasound combined with GDNF microbubbles to target and open the BBB can effectively increase the content of central GDNF, thus playing a therapeutic role in morphine addiction. Our study provides a new approach to locally open the BBB and target delivery of neurotrophic factors, such as GDNF, to treat brain diseases like addiction.

The Effects of Gene Variations of GABRA2, GABRB1, GABRG2, GAD1 and SLC1A3 on Patients with Propofol During Anesthesia Induction

Purpose

Propofol is one of the most commonly used intravenous sedatives in general anesthesia, while the individual variations of propofol are apparent. The objective of this study was to investigate the influence of genetic variations in GABAergic neurons and glutamatergic neurons on time to loss of consciousness (LOC) and the incidence of hypotension during anesthesia induction.

Patients and Methods

A total of 140 Chinese patients undergoing thyroid surgery or breast surgery were recruited. Genotyping of candidate genes was carried out using the Agena Bioscience MassARRAY system. Anesthesia induction was initiated with a propofol target plasma concentration (Cp) of 4.0 μg mL⁻¹. The LOC latency, systolic blood pressure, diastolic blood pressure, mean arterial pressure were documented.

Results

We found that GABRA2 rs35496835, GABRB1 rs1372496, GABRG2 rs11135176, GABRG2 rs209358, GAD1 rs3791878, SLC1A3 rs1049522 and gender were significant determinants of the patient’s LOC latency following propofol administration. GABRA2 rs11503014 was highly correlated with blood pressure reduction during anesthesia induction. Multiple linear regression analysis revealed that GABRB1 rs1372496, GABRG2 rs11135176, and SLC1A3 rs1049522 accounted for 35.3% variations in LOC latency following propofol administration.

Conclusion

Our findings indicate that genetic variants of GABRA2, GABRB1, GABRG2, GAD1 and SLC1A3 may have influence on propofol susceptibility, which would be an important guidance towards building clinical models that can precisely predict the efficacy of propofol with various populations before surgery.

Unconditioned and learned morphine tolerance influence hippocampal-dependent short-term memory and the subjacent expression of GABA-A receptor alpha subunits

BACKGROUND

ɣ-aminobutyric acid (GABA) facilitator valproic acid may be able to curb memory disruption induced by morphine exposure.

OBJECTIVE

The effects of the GABA facilitator valproic acid on the behavioral tolerance induced by morphine were investigated. Then hippocampal-dependent tasks named spatial-working and short-term memory procedures using the Y-maze apparatus were examined in morphine tolerant rats. Finally, the changes in the expression of hippocampal GABA-A receptors underlying morphine tolerance were also examined.

METHODS

Rats were treated with daily morphine injections, with or without distinct contextual pairing. To examine the effect of valproic acid on morphine tolerance expression, valproic acid was pretreated an hour before morphine. Spatial-working and short-term memory procedures using the Y-maze apparatus were examined in morphine tolerant rats. Afterwards the changes in the expression of hippocampal GABAα receptors using the quantitative real-time PCR and western blot techniques to detect GABArα subunits mRNAs and protein level were studied.

RESULTS

Our results showed that both learned and non-associative morphine tolerance influence short-term memory and the subjacent expression of GABArα mRNAs and protein level. Despite its attenuating effects on the development and expression of both learned and non-associative morphine tolerance, only associative morphine tolerance-induced memory dysfunction was ameliorated by valproic acid pretreatment. We also found that the expression of GABArα1, α2, α5 subunits mRNAs and GABAα protein level were affected heavier in associative morphine tolerant rats.

CONCLUSION

Our data supports the hypothesis that unconditioned and learned morphine tolerance influences short-term memory and the expression of GABArα 1, α2, α5 mRNAs and GABArα protein level differently, and adds to our understanding of the behavioral and molecular aspects of the learned tolerance to morphine effects.

Endogenous opiates and behavior: 2019

This paper is the forty-second consecutive installment of the annual anthological review of research concerning the endogenous opioid system, summarizing articles published during 2019 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides and receptors as well as effects of opioid/opiate agonists and antagonists. The review is subdivided into the following specific topics: molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors (1), the roles of these opioid peptides and receptors in pain and analgesia in animals (2) and humans (3), opioid-sensitive and opioid-insensitive effects of nonopioid analgesics (4), opioid peptide and receptor involvement in tolerance and dependence (5), stress and social status (6), learning and memory (7), eating and drinking (8), drug abuse and alcohol (9), sexual activity and hormones, pregnancy, development and endocrinology (10), mental illness and mood (11), seizures and neurologic disorders (12), electrical-related activity and neurophysiology (13), general activity and locomotion (14), gastrointestinal, renal and hepatic functions (15), cardiovascular responses (16), respiration and thermoregulation (17), and immunological responses (18).

Association study of genetic polymorphisms in GABRD with treatment response and dose in methadone maintenance treatment

Aim: This study determined if gene variants in the GABA receptor delta subunit (GABRD) are associated with treatment response and dose in methadone maintenance treatment (MMT) for heroin addiction. Materials & methods: A total of 286 MMT patients were recruited and divided into response and nonresponse groups based on retention time in therapy. A total of 177 responders were classified into low dose and high dose subgroups according to the stabilized methadone dose. Four (single nucleotide polymorphisms) SNPs (rs13303344, rs4481796, rs2376805 and rs2229110) in GABRD were genotyped using the TaqMan SNP assay. Logistic regression was used to assess the genetic effects of the SNPs in MMT. Results: No significant associations were observed between the SNPs and treatment response or dose, except the frequency of haplotype ACGC at the four SNPs significantly differed between responders and nonresponders. Conclusion: The results indicated that GABRD variants may play a small role in modulating methadone treatment response.

Association between GABA receptor delta subunit gene polymorphisms and heroin addiction

Evidence suggests that γ-aminobutyric acid (GABA) receptors are involved in the development of drug dependence. Considering its exclusively extrasynaptic localization, GABA receptor delta subunit (GABRD) is likely involved in heroin addiction. The purpose of this study was to explore the association between the single nucleotide polymorphisms (SNPs) of GABRD and heroin addiction. Genotyping of five SNPs (rs13303344, rs4481796, rs2376805, rs2229110, and rs41307846) in GABRD gene was performed by using TaqMan SNP assay. The association between heroin addiction and these SNPs was assessed in 446 heroin dependent patients and 400 normal control subjects of male Han Chinese origin. Only the genotype and allele frequencies at rs13303344 differed significantly between the cases and controls (nominal P values were 0.028 and 0.019, respectively). The C allele of rs13303344 was associated with an increased risk of heroin addiction (OR = 1.281, 95 % CI: 1.042-1.575). After Bonferroni correction, the association lost significance. The frequencies of the haplotype C-C-A and A-C-A at GARBD (rs13303344-rs4481796- rs2376805) differed significantly between the cases and controls. The heroin craving score was significantly higher in patients with CC/AC genotypes at rs13303344 than in those with the AA genotype (nominal P = 0.017). The results suggest that GABRD rs13303344 may contribute to the susceptibility to heroin addiction and is associated with the drug cravings of heroin dependent patients.

A Novel Precision Approach to Overcome the "Addiction Pandemic" by Incorporating Genetic Addiction Risk Severity (GARS) and Dopamine Homeostasis Restoration

This article describes a unique therapeutic precision intervention, a formulation of enkephalinase inhibitors, enkephalin, and dopamine-releasing neuronutrients, to induce dopamine homeostasis for detoxification and treatment of individuals genetically predisposed to developing reward deficiency syndrome (RDS). The formulations are based on the results of the addiction risk severity (GARS) test. Based on both neurogenetic and epigenetic evidence, the test evaluates the presence of reward genes and risk alleles. Existing evidence demonstrates that the novel genetic risk testing system can successfully stratify the potential for developing opioid use disorder (OUD) related risks or before initiating opioid analgesic therapy and RDS risk for people in recovery. In the case of opioid use disorders, long-term maintenance agonist treatments like methadone and buprenorphine may create RDS, or RDS may have been in existence, but not recognized. The test will also assess the potential for benefit from medication-assisted treatment with dopamine augmentation. RDS methodology holds a strong promise for reducing the burden of addictive disorders for individuals, their families, and society as a whole by guiding the restoration of dopamine homeostasisthrough anti-reward allostatic neuroadaptations. WC 175.

Prevalence of Some Genetic Risk Factors for Nicotine Dependence in Ukraine

Tobacco smoking is known to be a strong risk factor for developing many diseases. The development and severity of smoking dependence results from interaction of environmental and lifestyle factors, psycho-emotional predispositions, and also from genetic susceptibility. In present study, we investigated polymorphic variants in genes contributed to nicotine dependence, as well as to increased impulsivity, known to be an important risk factor for substance use disorders, in Ukraine population. The genotype frequencies at CYP2A6, DNMT3B, DRD2, HTR2A, COMT, BDNF, GABRA2, CHRNA5, and DAT1 polymorphisms were determined in 171 Ukraine residents, and these data were compared with data for several other European populations and main ethnic groups. It has been found that genotype frequencies for all studied loci are in Hardy-Weinberg equilibrium in the Ukrainian population and correspond to the respective frequencies in European populations. These findings suggest a similar impact of these loci on nicotine dependence in Ukraine. Further studies with larger sample sizes are, however, needed to draw firm conclusions about the effect size of these polymorphisms.