Epigenetic mechanisms in drug addiction

Changes in gene expression in brain reward regions are thought to contribute to the pathogenesis and persistence of drug addiction. Recent studies have begun to focus on the molecular mechanisms by which drugs of abuse and related environmental stimuli, such as drug-associated cues or stress, converge on the genome to alter specific gene programs. Increasing evidence suggests that these stable gene expression changes in neurons are mediated in part by epigenetic mechanisms that alter chromatin structure on specific gene promoters. This review discusses recent findings from behavioral, molecular and bioinformatic approaches being used to understand the complex epigenetic regulation of gene expression by drugs of abuse. This novel mechanistic insight might open new avenues for improved treatments of drug addiction.     

Gene expression‐based drug repurposing to target aging

Aging is the largest risk factor for a variety of noncommunicable diseases. Model organism studies have shown that genetic and chemical perturbations can extend both lifespan and healthspan. Aging is a complex process, with parallel and interacting mechanisms contributing to its aetiology, posing a challenge for the discovery of new pharmacological candidates to ameliorate its effects. In this study, instead of a target‐centric approach, we adopt a systems level drug repurposing methodology to discover drugs that could combat aging in human brain. Using multiple gene expression data sets from brain tissue, taken from patients of different ages, we first identified the expression changes that characterize aging. Then, we compared these changes in gene expression with drug‐perturbed expression profiles in the Connectivity Map. We thus identified 24 drugs with significantly associated changes. Some of these drugs may function as antiaging drugs by reversing the detrimental changes that occur during aging, others by mimicking the cellular defence mechanisms. The drugs that we identified included significant number of already identified prolongevity drugs, indicating that the method can discover de novo drugs that meliorate aging. The approach has the advantages that using data from human brain aging data, it focuses on processes relevant in human aging and that it is unbiased, making it possible to discover new targets for aging studies.     

甲基苯丙胺成瘾的表观遗传学机制

苯丙胺类兴奋剂是全世界第二大滥用程度的药物,甲基苯丙胺作为苯胺类兴奋剂中的主要药物,是中国滥用的“头号毒品”。而现有的研究对甲基苯丙胺成瘾机制尚不清晰,且临床上对药物成瘾的治疗依然存在无药可医的局面。因此,发现新的成瘾机制和治疗策略尤为迫切。甲基苯丙胺成瘾与额前叶皮质（mPFC）、中脑腹侧被盖区（VTA）和伏隔核（NAc）中的多巴胺（DA）、谷氨酸（Glu）、去甲肾上腺素（NE）和血清素（SNRIS）等神经递质的异常释放有关。研究表明,这些神经递质受到表观遗传机制中组蛋白乙酰化、甲基化、泛素化和非编码RNA等调节,某些基因的表达在甲基苯丙胺的诱导过程中增强或被抑制,导致甲基苯丙胺依赖性产生。本文将针对表观遗传学对甲基苯丙胺成瘾机制的影响进行着重论述,以期推进临床开发甲基苯丙胺戒断药物的研究。     

Resistance of human fungal pathogens to antifungal drugs

Resistance mechanisms can be engaged in clinically relevant fungal pathogens under different conditions when exposed to antifungal drugs. Over past years, active research was undertaken in the understanding of the molecular basis of antifungal drug resistance in these pathogens, and especially against the class of azole antifungals. The isolation of various alleles of the gene encoding the target of azoles has enabled correlation of the appearance of resistance with distinct mutations. Resistance mechanisms to azoles also converge to the upregulation of multidrug transporter genes, whose products have the capacity to extrude from cells several chemically unrelated antifungal agents and toxic compounds. Genome-wide studies of azole-resistant isolates are now permitting a more comprehensive analysis of the impact of resistance on gene expression, and may deliver new clues to their mechanisms. Several laboratories are also exploring, as well as possible alternative resistance pathways, the role of biofilm formation by several fungal species in the development of resistance to various antifungals, including azoles.     

Up-regulation of calcineurin Abeta mRNA in the Alzheimer's disease brain: assessment by cDNA microarray

Recent advances in cDNA microarray technology have made it possible to analyze expression of more than 8000 genes. Using this technology, gene expression in the hippocampus containing neurofibrillary tangle-associated lesions from an Alzheimer's disease (AD) patient was compared with expression in the parietal cortex from the same patient that lacked these lesions. We also compared gene expression using a control brain. The top 20 named genes significantly up-regulated or down-regulated only in the AD brain were determined. The most up-regulated gene proved to be calcineurin Abeta mRNA (CAbeta). In situ hybridization histochemistry revealed that CAbeta was significantly up-regulated in pyramidal neurons of the hippocampus in the AD brain. RT-PCR analysis revealed that CAbeta was up-regulated in the hippocampus from two out of three AD brains while there were no changes in three control brains. Our study suggests that CAbeta may play a crucial role in the pathophysiological mechanisms in AD.     

A gene co-expression network in whole blood of schizophrenia patients is independent of antipsychotic-use and enriched for brain-expressed genes

Despite large-scale genome-wide association studies (GWAS), the underlying genes for schizophrenia are largely unknown. Additional approaches are therefore required to identify the genetic background of this disorder. Here we report findings from a large gene expression study in peripheral blood of schizophrenia patients and controls. We applied a systems biology approach to genome-wide expression data from whole blood of 92 medicated and 29 antipsychotic-free schizophrenia patients and 118 healthy controls. We show that gene expression profiling in whole blood can identify twelve large gene co-expression modules associated with schizophrenia. Several of these disease related modules are likely to reflect expression changes due to antipsychotic medication. However, two of the disease modules could be replicated in an independent second data set involving antipsychotic-free patients and controls. One of these robustly defined disease modules is significantly enriched with brain-expressed genes and with genetic variants that were implicated in a GWAS study, which could imply a causal role in schizophrenia etiology. The most highly connected intramodular hub gene in this module (ABCF1), is located in, and regulated by the major histocompatibility (MHC) complex, which is intriguing in light of the fact that common allelic variants from the MHC region have been implicated in schizophrenia. This suggests that the MHC increases schizophrenia susceptibility via altered gene expression of regulatory genes in this network.     

Neurodevelopment and mood stabilizers

Mood disorders and schizophrenia share a number of common properties, including: genetic susceptibility; differences in brain structure and drug based therapy. Some genetic loci may even confer susceptibility for bipolar mood disorder and schizophrenia, and some atypical antipsychotic drugs are used as mood stabilizers. As schizophrenia is associated with aberrant neurodevelopment, could this also be true for mood disorders? Such changes could arise pre- or post-natal, however the recent interest in neurogenesis in the adult brain has suggested involvement of these later processes in the origins of mood disorders. Interestingly, the common mood stabilizing drugs, lithium, valproic acid (VPA) and carbamazepine, are teratogens, affecting a number of aspects of animal development. Recent work has shown that lithium and VPA interfere with normal cell development, and all three drugs affect neuronal morphology. The molecular basis for mood stabilizer action in the treatment of mood is unknown, however these studies have suggested both targets and potential mechanisms. Lithium directly inhibits two evolutionarily conserved signal transduction pathways: the protein kinase Glycogen Synthase Kinase-3 (GSK-3) and inositol signaling. VPA can up-regulate gene expression through inhibition of histone deacetylase (HDAC) and indirectly reduce GSK-3 activity. VPA effects are not conserved between cell types, and carbamazepine has no effect on the GSK-3 pathway. All three mood stabilizers suppress inositol signaling, results further supported by studies on the enzyme prolyl oligopeptidase (PO) and the sodium myo-inositol transporter (SMIT). Despite these intriguing observations, it remains unclear whether GSK-3, inositol signaling or both underlie the origins of bipolar disorder.     

Expression profiling of autism candidate genes during human brain development implicates central immune signaling pathways

The Autism Spectrum Disorders (ASD) represent a clinically heterogeneous set of conditions with strong hereditary components. Despite substantial efforts to uncover the genetic basis of ASD, the genomic etiology appears complex and a clear understanding of the molecular mechanisms underlying Autism remains elusive. We hypothesized that focusing gene interaction networks on ASD-implicated genes that are highly expressed in the developing brain may reveal core mechanisms that are otherwise obscured by the genomic heterogeneity of the disorder. Here we report an in silico study of the gene expression profile from ASD-implicated genes in the unaffected developing human brain. By implementing a biologically relevant approach, we identified a subset of highly expressed ASD-candidate genes from which interactome networks were derived. Strikingly, immune signaling through NFκB, Tnf, and Jnk was central to ASD networks at multiple levels of our analysis, and cell-type specific expression suggested glia--in addition to neurons--deserve consideration. This work provides integrated genomic evidence that ASD-implicated genes may converge on central cytokine signaling pathways.     

Network-assisted investigation of antipsychotic drugs and their targets

Antipsychotic drugs are tranquilizing psychiatric medications primarily used in the treatment of schizophrenia and similar severe mental disorders. So far, most of these drugs have been discovered without knowing much on the molecular mechanisms of their actions. The available large amount of pharmacogenetics, pharmacometabolomics, and pharmacoproteomics data for many drugs makes it possible to systematically explore the molecular mechanisms underlying drug actions. In this study, we applied a unique network-based approach to investigate antipsychotic drugs and their targets. We first retrieved 43 antipsychotic drugs, 42 unique target genes, and 46 adverse drug interactions from the DrugBank database and then generated a drug-gene network and a drug-drug interaction network. Through drug-gene network analysis, we found that seven atypical antipsychotic drugs tended to form two clusters that could be defined by drugs with different target receptor profiles. In the drug-drug interaction network, we found that three drugs (zuclopenthixol, ziprasidone, and thiothixene) tended to have more adverse drug interactions than others, while clozapine had fewer adverse drug interactions. This investigation indicated that these antipsychotics might have different molecular mechanisms underlying the drug actions. This pilot network-assisted investigation of antipsychotics demonstrates that network-based analysis is useful for uncovering the molecular actions of antipsychotics.     

Glutamate and Brain Glutaminases in Drug Addiction

Glutamate is the principal excitatory neurotransmitter in the central nervous system and its actions are related to the behavioral effects of psychostimulant drugs. In the last two decades, basic neuroscience research and preclinical studies with animal models are suggesting a critical role for glutamate transmission in drug reward, reinforcement, and relapse. Although most of the interest has been centered in post-synaptic glutamate receptors, the presynaptic synthesis of glutamate through brain glutaminases may also contribute to imbalances in glutamate homeostasis, a key feature of the glutamatergic hypothesis of addiction. Glutaminases are the main glutamate-producing enzymes in brain and dysregulation of their function have been associated with neurodegenerative diseases and neurological disorders; however, the possible implication of these enzymes in drug addiction remains largely unknown. This mini-review focuses on brain glutaminase isozymes and their alterations by in vivo exposure to drugs of abuse, which are discussed in the context of the glutamate homeostasis theory of addiction. Recent findings from mouse models have shown that drugs induce changes in the expression profiles of key glutamatergic transmission genes, although the molecular mechanisms that regulate drug-induced neuronal sensitization and behavioral plasticity are not clear.     

Reviewing once more the c-myc and Ras collaboration

The c-myc is a proto-oncogene that manifests aberrant expression at high frequencies in most types of human cancer. C-myc gene amplifications are often observed in various cancers as well. Ample studies have also proved that c-myc has a potent oncogenicity, which can be further enhanced by collaborations with other oncogenes such as Bcl-2 and activated Ras. Studies on the collaborations of c-myc with Ras or other genes in oncogenicity have established several basic concepts and have disclosed their underlying mechanisms of tumor biology, including “immortalization” and “transformation”. In many cases, these collaborations may converge at the cyclin D1-CDK4 complex. In the meantime, however, many results from studies on the c-myc, Ras and cyclin D1-CDK4 also challenge these basic concepts of tumor biology and suggest to us that the immortalized status of cells should be emphasized. Stricter criteria and definitions for a malignantly transformed status and a benign status of cells in culture also need to be established to facilitate our study of the mechanisms for tumor formation and to better link up in vitro data with animal results and eventually with human cancer pathology.     

Dynamic Stabilization in the PU1-GATA1 Circuit Using a Model with Time-Dependent Kinetic Change

The PU.1 and GATA1 genes play an important role in the differentiation of blood stem cells. The protein levels expressed by these genes are thought to be regulated by a self-excitatory feedback loop for each gene and a cross-inhibitory feedback loop between the two genes. A mathematical model that captures the dynamical interaction between these two genes reveals that constant levels of self-excitation and cross-inhibition allow the most self-exciting or cross-inhibiting gene to dominate the system. However, since biological systems rarely exist in an unchanging equilibrium, we modeled this gene circuit using discrete time-dependent changes in the parameters in lieu of steady state parameters. These time-dependent parameters lead to new phenomena, including the development of new limit cycles and basins of attraction. These phenomena are not present in models using constant parameter values. Our findings suggest that even small perturbations in the PU.1 and GATA1 feedback loops may substantially alter the gene expression and therefore the cell phenotype. These time-dependent parameter models may also have implications for other gene systems and provide new ways to understand the mechanisms of cellular differentiation.