Genes and (common) pathways underlying drug addiction

Drug addiction is a serious worldwide problem with strong genetic and environmental influences. Different technologies have revealed a variety of genes and pathways underlying addiction; however, each individual technology can be biased and incomplete. We integrated 2,343 items of evidence from peer-reviewed publications between 1976 and 2006 linking genes and chromosome regions to addiction by single-gene strategies, microrray, proteomics, or genetic studies. We identified 1,500 human addiction-related genes and developed KARG (http://karg.cbi.pku.edu.cn), the first molecular database for addiction-related genes with extensive annotations and a friendly Web interface. We then performed a meta-analysis of 396 genes that were supported by two or more independent items of evidence to identify 18 molecular pathways that were statistically significantly enriched, covering both upstream signaling events and downstream effects. Five molecular pathways significantly enriched for all four different types of addictive drugs were identified as common pathways which may underlie shared rewarding and addictive actions, including two new ones, GnRH signaling pathway and gap junction. We connected the common pathways into a hypothetical common molecular network for addiction. We observed that fast and slow positive feedback loops were interlinked through CAMKII, which may provide clues to explain some of the irreversible features of addiction.     

Analyzing the pathways enriched in genes associated with nicotine dependence in the context of human protein–protein interaction network

Nicotine dependence is the primary addictive stage of cigarette smoking. Although a lot of studies have been performed to explore the molecular mechanism underlying nicotine dependence, our understanding on this disorder is still far from complete. Over the past decades, an increasing number of candidate genes involved in nicotine dependence have been identified by different technical approaches, including the genetic association analysis. In this study, we performed a comprehensive collection of candidate genes reported to be genetically associated with nicotine dependence. Then, the biochemical pathways enriched in these genes were identified by considering the gene’s propensity to be related to nicotine dependence. One of the most widely used pathway enrichment analysis approach, over-representation analysis, ignores the function non-equivalence of genes in candidate gene set and may have low discriminative power in identifying some dysfunctional pathways. To overcome such drawbacks, we constructed a comprehensive human protein–protein interaction network, and then assigned a function weighting score to each candidate gene based on their network topological features. Evaluation indicated the function weighting score scheme was consistent with available evidence. Finally, the function weighting scores of the candidate genes were incorporated into pathway analysis to identify the dysfunctional pathways involved in nicotine dependence, and the interactions between pathways was detected by pathway crosstalk analysis. Compared to conventional over-representation-based pathway analysis tool, the modified method exhibited improved discriminative power and detected some novel pathways potentially underlying nicotine dependence. In summary, we conducted a comprehensive collection of genes associated with nicotine dependence and then detected the biochemical pathways enriched in these genes using a modified pathway enrichment analysis approach with function weighting score of candidate genes integrated. Our results may provide insight into the molecular mechanism underlying nicotine dependence.     

Genes and Pathways Co-associated with the Exposure to Multiple Drugs of Abuse,Including Alcohol,Amphetamine/Methamphetamine,Cocaine, Marijuana,Morphine, and/or Nicotine: a Review of Proteomics Analyses

Drug addiction is a chronic neuronal disease. In recent years, proteomics technology has been widely used to assess the protein expression in the brain tissues of both animals and humans exposed to addictive drugs. Through this approach, a large number of proteins potentially involved in the etiology of drug addictions have been identified, which provide a valuable resource to study protein function, biochemical pathways, and networks related to the molecular mechanisms underlying drug dependence. In this article, we summarize the recent application of proteomics to profiling protein expression patterns in animal or human brain tissues after the administration of alcohol, amphetamine/methamphetamine, cocaine, marijuana, morphine/heroin/butorphanol, or nicotine. From available reports, we compiled a list of 497 proteins associated with exposure to one or more addictive drugs, with 160 being related to exposure to at least two abused drugs. A number of biochemical pathways and biological processes appear to be enriched among these proteins, including synaptic transmission and signaling pathways related to neuronal functions. The data included in this work provide a summary and extension of the proteomics studies on drug addiction. Furthermore, the proteins and biological processes highlighted here may provide valuable insight into the cellular activities and biological processes in neurons in the development of drug addiction.     

Nicotine and hippocampus-dependent learning

Addiction is a complex disorder because many factors contribute to the development and maintenance of addiction. One factor is learning. For example, drug-context associations that develop during drug use could facilitate drug craving upon re-exposure to contexts previously associated with drugs. Additionally, deficits in cognitive processes associated with withdrawal could precipitate relapse in attempts to ameliorate those deficits. Because addiction and learning involve common neural areas and cell signaling cascades, addiction-related changes in processes underlying plasticity may contribute to addiction. This article examines similarities between addiction and learning at the behavioral, neural, and cellular levels, with emphasis on the neural substrates underlying the effects of acute nicotine, chronic nicotine, and withdrawal from chronic nicotine on hippocampus-dependent contextual, learning.     

Development and validation of hub genes for lymph node metastasis in patients with prostate cancer

Lymph node metastasis is one of the most important independent risk factors that can negatively affect the prognosis of prostate cancer (PCa); however, the exact mechanisms have not been well studied. This study aims to better understand the underlying mechanism of lymph node metastasis in PCa by bioinformatics analysis. We analysed a total of 367 PCa cases from the cancer genome atlas database and performed weighted gene co‐expression network analysis to explore some modules related to lymph node metastasis. Gene Ontology analysis and pathway enrichment analysis were conducted for functional annotation, and a protein‐protein interaction network was built. Samples from the International Cancer Genomics Consortium database were used as a validation set. The turquoise module showed the most relevance with lymph node metastasis. Functional annotation showed that biological processes and pathways were mainly related to activation of the processes of cell cycle and mitosis. Four hub genes were selected: CKAP2L, CDCA8, ERCC6L and ARPC1A. Further validation showed that the four hub genes well‐distinguished tumour and normal tissues, and they were good biomarkers for lymph node metastasis of PCa. In conclusion, the identified hub genes facilitate our knowledge of the underlying molecular mechanism for lymph node metastasis of PCa.     

Pathway Analysis of Smoking Quantity in Multiple GWAS Identifies Cholinergic and Sensory Pathways

Cigarette smoking is a common addiction that increases the risk for many diseases, including lung cancer and chronic obstructive pulmonary disease. Genome-wide association studies (GWAS) have successfully identified and validated several susceptibility loci for nicotine consumption and dependence. However, the trait variance explained by these genes is only a small fraction of the estimated genetic risk. Pathway analysis complements single marker methods by including biological knowledge into the evaluation of GWAS, under the assumption that causal variants lie in functionally related genes, enabling the evaluation of a broad range of signals. Our approach to the identification of pathways enriched for multiple genes associated with smoking quantity includes the analysis of two studies and the replication of common findings in a third dataset. This study identified pathways for the cholinergic receptors, which included SNPs known to be genome-wide significant; as well as novel pathways, such as genes involved in the sensory perception of smell, that do not contain any single SNP that achieves that stringent threshold.     

Convergence and divergence of genetic and modular networks between diabetes and breast cancer

Diabetes mellitus (DM) and breast cancer (BC) can simultaneously occur in the same patient populations, but the molecular relationship between them remains unknown. In this study, we constructed genetic networks and used modularized analysis approaches to investigate the multi‐dimensional characteristics of two diseases and one disease subtype. A text search engine (Agilent Literature Search 2.71) and MCODE software were applied to validate potential subnetworks and to divide the modules, respectively. A total of 793 DM‐related genes, 386 type 2 diabetes (T2DM) genes and 873 BC‐related genes were identified from the Online Mendelian Inheritance in Man database. For DM and BC, a total of 99 overlapping genes, 9 modules, 29 biological processes and 7 pathways were identified. Meanwhile, for T2DM and BC, 56 overlapping genes, 5 modules, 20 biological processes and 12 pathways were identified. Based on the Gene Ontology functional enrichment analysis of the top 10 non‐overlapping modules of the two diseases, 10 biological functions and 5 pathways overlapped between them. The glycosphingolipid and lysosome pathways verified molecular mechanisms of cell death related to both DM and BC. We also identified new biological functions of dopamine receptors and four signalling pathways (Parkinson's disease, Alzheimer's disease, Huntington's disease and long‐term depression) related to both diseases; these warrant further investigation. Our results illustrate the landscape of the novel molecular substructures between DM and BC, which may support a new model for complex disease classification and rational therapies for multiple diseases.     

Integrative gene network analysis provides novel regulatory relationships, genetic contributions and susceptible targets in autism spectrum disorders

Autism spectrum disorders (ASDs) are a group of diseases exhibiting impairment in social drive, communication/language skills and stereotyped behaviors. Though an increased number of candidate genes and molecular interactions have been identified by various approaches, the pathogenesis remains elusive. Based on clinical observations, data from accessible GWAS and expression datasets we identified ASDs gene candidates. Integrative gene network and a novel CNV-centric Node Network (CNN) analysis method highlighted ASDs-associated key elements and biological processes. Functional analysis identified neurological functions including synaptic cholinergic receptor (CHRNA) families, dopamine receptor (DRD2), and correlations between social behavior and oxytocin related pathways. CNN analysis of genome-wide genetic and expression data identified inheritance-related clusters related to PTEN/TSC1/FMR1 and mTor/PI3K regulation. Integrative analysis identified potential regulators of networks, specifically TNF and beta-estradiol, suggesting a potential central role in ASDs. Our data provide information on potential disease mechanisms, and key regulators that may generate novel postulations, and diagnostic molecular biomarkers.     

Computational identification of protein-protein interactions in rice based on the predicted rice interactome network

Plant protein-protein interaction networks have not been identified by large-scale experiments. In order to better understand the protein interactions in rice, the Predicted Rice Interactome Network (PRIN; http://bis.zju.edu.cn/prin/) presented 76,585 predicted interactions involving 5,049 rice proteins. After mapping genomic features of rice (GO annotation, subcellular localization prediction, and gene expression), we found that a well-annotated and biologically significant network is rich enough to capture many significant functional linkages within higher-order biological systems, such as pathways and biological processes. Furthermore, we took MADS-box domain-containing proteins and circadian rhythm signaling pathways as examples to demonstrate that functional protein complexes and biological pathways could be effectively expanded in our predicted network. The expanded molecular network in PRIN has considerably improved the capability of these analyses to integrate existing knowledge and provide novel insights into the function and coordination of genes and gene networks.     

Cellular and synaptic mechanisms of nicotine addiction

The tragic health effects of nicotine addiction highlight the importance of investigating the cellular mechanisms of this complex behavioral phenomenon. The chain of cause and effect of nicotine addiction starts with the interaction of this tobacco alkaloid with nicotinic acetylcholine receptors (nAChRs). This interaction leads to activation of reward centers in the CNS, including the mesoaccumbens DA system, which ultimately leads to behavioral reinforcement and addiction. Recent findings from a number of laboratories have provided new insights into the biologic processes that contribute to nicotine self-administration. Examination of the nAChR subtypes expressed within the reward centers has identified potential roles for these receptors in normal physiology, as well as the effects of nicotine exposure. The high nicotine sensitivity of some nAChR subtypes leads to rapid activation followed in many cases by rapid desensitization. Assessing the relative importance of these molecular phenomena in the behavioral effects of nicotine presents an exciting challenge for future research efforts.     

Identification of Differentially Expressed Genes and Pathways for Myofiber Characteristics in Soleus Muscles between Chicken Breeds Differing in Meat Quality

In the modern chicken industry, fast-growing broilers have undergone strong artificial selection for muscle growth, which has led to remarkable phenotypic variations compared with slow-growing chickens. However, the molecular mechanism underlying these phenotypes differences remains unknown. In this study, a systematic identification of candidate genes and new pathways related to myofiber development and composition in chicken Soleus muscle (SOL) has been made using gene expression profiles of two distinct breeds: Qingyuan partridge (QY), a slow-growing Chinese breed possessing high meat quality and Cobb 500 (CB), a commercial fast-growing broiler line. Agilent cDNA microarray analyses were conducted to determine gene expression profiles of soleus muscle sampled at sexual maturity age of QY (112 d) and CB (42 d). The 1318 genes with at least 2-fold differences were identified (P?相似文献   

Pathway Network Analyses for Autism Reveal Multisystem Involvement,Major Overlaps with Other Diseases and Convergence upon MAPK and Calcium Signaling

We used established databases in standard ways to systematically characterize gene ontologies, pathways and functional linkages in the large set of genes now associated with autism spectrum disorders (ASDs). These conditions are particularly challenging—they lack clear pathognomonic biological markers, they involve great heterogeneity across multiple levels (genes, systemic biological and brain characteristics, and nuances of behavioral manifestations)—and yet everyone with this diagnosis meets the same defining behavioral criteria. Using the human gene list from Simons Foundation Autism Research Initiative (SFARI) we performed gene set enrichment analysis with the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Database, and then derived a pathway network from pathway-pathway functional interactions again in reference to KEGG. Through identifying the GO (Gene Ontology) groups in which SFARI genes were enriched, mapping the coherence between pathways and GO groups, and ranking the relative strengths of representation of pathway network components, we 1) identified 10 disease-associated and 30 function-associated pathways 2) revealed calcium signaling pathway and neuroactive ligand-receptor interaction as the most enriched, statistically significant pathways from the enrichment analysis, 3) showed calcium signaling pathways and MAPK signaling pathway to be interactive hubs with other pathways and also to be involved with pervasively present biological processes, 4) found convergent indications that the process “calcium-PRC (protein kinase C)-Ras-Raf-MAPK/ERK” is likely a major contributor to ASD pathophysiology, and 5) noted that perturbations associated with KEGG’s category of environmental information processing were common. These findings support the idea that ASD-associated genes may contribute not only to core features of ASD themselves but also to vulnerability to other chronic and systemic problems potentially including cancer, metabolic conditions and heart diseases. ASDs may thus arise, or emerge, from underlying vulnerabilities related to pleiotropic genes associated with pervasively important molecular mechanisms, vulnerability to environmental input and multiple systemic co-morbidities.     

Identification of Key Genes and Pathways Involved in the Heterogeneity of Intrinsic Growth Ability Between Neurons After Spinal Cord Injury in Adult Zebrafish

In the adult central nervous system (CNS), axon regeneration is a major hurdle for functional recovery after trauma. The intrinsic growth potential of an injured axon varies widely between neurons. The underlying molecular mechanisms of such heterogeneity are largely unclear. In the present study, the adult zebrafish dataset GSE56842 were downloaded. Differentially expressed genes (DEGs) were sorted and deeply analyzed by bioinformatics methods. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were performed with the DAVID. A DEGs-associated protein–protein interaction network was constructed from the STRING database and visualized with Cytoscape software. In total, 621 DEGs were identified. GO analysis showed that the biological processes of DEGs focused mainly on the Notch signaling pathway, cell differentiation and positive regulation of neuron differentiation. The molecular functions mainly included calcium-transporting ATPase activity and calcium ion binding and structural constituents of the cytoskeleton. The cellular components included the plasma membrane, spectrin, and cytoplasmic and membrane-bound vesicles. KEGG pathway analysis showed that these DEGs were mainly involved in the metabolic pathway and Notch signaling pathway, and subnetworks revealed that genes within modules were involved in the metabolic pathway, Wnt signaling pathway, and calcium signaling pathway. This study identified DEG candidate genes and pathways involved in the heterogeneity of the intrinsic growth ability between neurons after spinal cord injury in adult zebrafish, which could facilitate our understanding of the molecular mechanisms underlying axon regeneration, and these candidate genes and pathways could be therapeutic targets for the treatment of CNS injury.

     

多效生长因子相关基因的生物信息学分析

目的:用生物信息学方法分析多效生长因子(PTN)潜在的分子功能。方法:利用由美国亚利桑那癌中心提供的生物信息学数据库,对前期用小鼠全基因组表达谱芯片检测到的Ptn相关基因进行生物信息学分析,通过GO Terms分析这些基因所属的功能群体,用Pathway Miner分析这些基因参与调控的信号通路。结果:370个由芯片检测得到的Ptn相关基因中,在GO Terms数据库中找到231个基因,其中参与细胞成分构成的基因占31.83%,具有分子功能的基因占35.34%,而参与生物学过程的基因占32.83%;在Pathway Miner数据库中找到105个基因。这些基因相关的信号通路有230条,分别属于细胞和调控过程通路以及代谢通路。结论:PTN是一个重要的细胞因子,可能参与机体的免疫与防御反应、炎症反应,以及细胞的增殖、凋亡调控等。