Prioritizing Genes Related to Nicotine Addiction Via a Multi-source-Based Approach

A Network and Pathway Analysis of Genes Associated With Atrial Fibrillation

Background: Atrial fibrillation (AF) is affected by both environmental and genetic factors. Previous genetic association studies, especially genome-wide association studies, revealed a large group of AF-associated genes. However, little is known about the functions and interactions of these genes. Moreover, established genetic variants of AF contribute modestly to AF variance, implying that numerous additional AF-associated genetic variations need to be identified. Hence, a systematic network and pathway analysis is needed. Methods: We retrieved all AF-associated genes from genetic association studies in various databases and performed integrative analyses including pathway enrichment analysis, pathway crosstalk analysis, network analysis, and microarray meta-analysis. Results: We collected 254 AF-associated genes from genetic association studies in various databases. Pathway enrichment analysis revealed the top biological pathways that were enriched in the AF-associated genes related to cardiac electromechanical activity. Pathway crosstalk analysis showed that numerous neuro-endocrine-immune pathways connected AF with various diseases including cancers, inflammatory diseases, and cardiovascular diseases. Furthermore, an AF-specific subnetwork was constructed with the prize-collecting Steiner forest algorithm based on the AF-associated genes, and 24 novel genes that were potentially associated with AF were inferred by the subnetwork. In the microarray meta-analysis, six of the 24 novel genes (APLP1, CREB1, CREBBP, PRMT1, IRAK1, and PLXND1) were expressed differentially in patients with AF and sinus rhythm. Conclusions: AF is not only an isolated disease with abnormal electrophysiological activity but might also share a common genetic basis and biological process with tumors and inflammatory diseases as well as cardiovascular diseases. Moreover, the six novel genes inferred from network analysis might help detect the missing AF risk loci.

PheSom: a term frequency-based method for measuring human phenotype similarity on the basis of MeSH vocabulary

Background: Phenotype similarity calculation should be used to help improve drug repurposing. In this study, based on the MeSH terms describing the phenotypes deposited in OMIM, we proposed a method, namely, PheSom (Phenotype Similarity On MeSH), to measure the similarity between phenotypes. PheSom counted the number of overlapping MeSH terms between two phenotypes and then took the weight of every MeSH term within each phenotype into account according to the term frequency-inverse document frequency (FIDC). Phenotype-related genes were used for the evaluation of our method. Results: A 7,739 × 7,739 similarity score matrix was finally obtained and the number of phenotype pairs was dramatically decreased with the increase of similarity score. Besides, the overlapping rates of phenotype-related genes were remarkably increased with the increase of similarity score between phenotypes, which supports the reliability of our method. Conclusion: We anticipate our method can be applied to identifying novel therapeutic methods for complex diseases.

Common genetic substrates of alcohol and substance use disorder severity revealed by pleiotropy detection against GWAS catalog in two populations

Alcohol and other substance use disorders (AUD and SUD) are complex diseases that are postulated to have a polygenic inheritance and are often comorbid with other disorders. The comorbidities may arise partially through genetic pleiotropy. Identification of specific gene variants accounting for large parts of the variance in these disorders has yet to be accomplished. We describe a flexible strategy that takes a variant-trait association database and determines if a subset of disease/straits are potentially pleiotropic with the disorder under study. We demonstrate its usage in a study of use disorders in two independent cohorts: alcohol, stimulants, cannabis (CUD), and multi-substance use disorders (MSUD) in American Indians (AI) and AUD and CUD in Mexican Americans (MA). Using a machine learning method with variants in GWAS catalog, we identified 229 to 246 pleiotropic variants for AI and 153 to 160 for MA for each SUD. Inflammation was the most enriched for MSUD and AUD in AIs. Neurological disorder was the most significantly enriched for CUD in both cohorts, and for AUD and stimulants in AIs. Of the select pleiotropic genes shared among substances-cohorts, multiple biological pathways implicated in SUD and other psychiatric disorders were enriched, including neurotrophic factors, immune responses, extracellular matrix, and circadian regulation. Shared pleiotropic genes were significantly up-regulated in brain regions playing important roles in SUD, down-regulated in esophagus mucosa, and differentially regulated in adrenal gland. This study fills a gap for pleiotropy detection in understudied admixed populations and identifies pleiotropic variants that may be potential targets of interest for SUD.

Integrative systems and functional analyses reveal a role of dopaminergic signaling in myelin pathogenesis

BACKGROUND

Myelin sheaths surrounding axons are critical for electrical signal transmission in the central nervous system (CNS). Diseases with myelin defects such as multiple sclerosis (MS) are devastating neurological conditions for which few effective treatments are available. Dysfunction of the dopaminergic system has been observed in multiple neurological disorders. Its role in myelin pathogenesis, however, is unclear.

METHODS

This work used a combination of literature curation, bioinformatics, pharmacological and genetic manipulation, as well as confocal imaging techniques. Literature search was used to establish a complete set of genes which is associated with MS in humans. Bioinformatics analyses include pathway enrichment and crosstalk analyses with human genetic association studies as well as gene set enrichment and causal relationship analyses with transcriptome data. Pharmacological and CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9) genetic manipulation were applied to inhibit the dopaminergic signaling in zebrafish. Imaging techniques were used to visualize myelin formation in vivo.

RESULTS

Systematic analysis of human genetic association studies revealed that the dopaminergic synapse signaling pathway is enriched in candidate gene sets. Transcriptome analysis confirmed that expression of multiple dopaminergic gene sets was significantly altered in patients with MS. Pathway crosstalk analysis and gene set causal relationship analysis reveal that the dopaminergic synapse signaling pathway interacts with or is associated with other critical pathways involved in MS. We also found that disruption of the dopaminergic system leads to myelin deficiency in zebrafish.

CONCLUSIONS

Dopaminergic signaling may be involved in myelin pathogenesis. This study may offer a novel molecular mechanism of demyelination in the nervous system.

Alcohol and Cocaine Exposure Modulates ABCB1 and ABCG2 Transporters in Male Alcohol-Preferring Rats

Two efflux transporters, ATP-binding cassettes B1 (ABCB1) and G2 (ABCG2), are highly expressed in the endothelial cells of the brain, where they regulate the bioavailability and distribution of several endogenous and xenobiotic compounds. However, whether ABCB1 or ABCG2 has any link with drug dependence, drug withdrawal effects, or the incidence of adverse effects in drug abuser is not known. In this study, we determined the effects of voluntary ethanol consumption following repeated exposure to cocaine or vehicle on the relative mRNA and protein expression of Abcg2/ABCG2 and Abcb1/ABCB1 in the nucleus accumbens (NAc) and medial prefrontal cortex (mPFC) of male alcohol-preferring (P) rats. Male P rats were allowed free choice access to ethanol (15 and 30% v/v) and water for 5 weeks to establish baseline drinking behavior. The following week, rats were either injected with 20 mg/kg i.p. of cocaine or saline, once a day, for 7 days. The relative mRNA and protein expression of Abcb1/ABCB1 and Abcg2/ABCG2 in the NAc and mPFC were significantly decreased in ethanol-saline- and ethanol-cocaine-exposed rats compared to control rats that received neither ethanol nor cocaine. Thus, prolonged exposure to commonly abused drugs, ethanol and cocaine, alters the expression of Abcb1/ABCB1 and Abcg2/ABCG2 mRNA and protein levels in brain areas that play a role in drug dependence.

Comparison between dopaminergic and non-dopaminergic neurons in the VTA following chronic nicotine exposure during pregnancy

Exposure to nicotine during pregnancy through maternal smoking or nicotine replacement therapy is associated with adverse birth outcomes as well as several cognitive and neurobehavioral deficits. Several studies have shown that nicotine produces long-lasting effects on gene expression within many brain regions, including the ventral tegmental area (VTA), which is the origin of dopaminergic neurons and the dopamine reward pathway. Using a well-established rat model for perinatal nicotine exposure, we sought to investigate altered biological pathways using mRNA and miRNA expression profiles of dopaminergic (DA) and non-dopaminergic (non-DA) neurons in this highly-valuable area. Putative miRNA-gene target interactions were assessed as well as miRNA-pathway interactions. Our results indicate that extracellular matrix (ECM) receptor interactions were significantly altered in DA and non-DA neurons due to chronic nicotine exposure during pregnancy. They also show that the PI3K/AKT signaling pathway was enriched in DA neurons with multiple significant miRNA-gene targets, but the same changes were not seen in non-DA neurons. We speculate that nicotine exposure during pregnancy could differentially affect the gene expression of DA and non-DA neurons in the VTA.

Investigating the Effect of Perinatal Nicotine Exposure on Dopaminergic Neurons in the VTA Using miRNA Expression Profiles

Maternal smoking during pregnancy is associated with developmental, cognitive, and behavioral disorders, including low birth weight, attention deficit hyperactivity disorder, learning disabilities, and drug abuse later in life. Nicotine activates the reward-driven behavior characteristic of drug abuse. Dopaminergic (DA) neurons originating from the ventral tegmental area (VTA) of the brain, which are stimulated by nicotine and other stimuli, are widely implicated in the natural reward pathway that is known to contribute to addiction. In recent years, microRNAs have been implicated in disrupting regulatory mechanisms due to their capability of targeting multiple genes and thus inducing downstream effects along many pathways. In order to investigate miRNA expression of dopaminergic neurons from the VTA, we employed patch clamping to identify and harvest both DA and non-DA neurons from rats perinatally exposed to nicotine for use in single-cell RT-qPCR. Our data indicated that miR-140-5p and miR-140-3p were upregulated in DA neurons; while miR-140-3p and miR-212 were differentially expressed in non-DA neurons. A functional enrichment analysis was also performed on our miRNA-gene prediction network and predicted that our miRNAs target genes involved in drug response and neuroplasticity.

Investigating the genetic profile of dopaminergic neurons in the VTA in response to perinatal nicotine exposure using mRNA-miRNA analyses

Maternal smoking during pregnancy is associated with an increased risk of developmental, behavioral, and cognitive deficits. Nicotine, the primary addictive component in tobacco, has been shown to modulate changes in gene expression when exposure occurs during neurodevelopment. The ventral tegmental area (VTA) is believed to be central to the mechanism of addiction because of its involvement in the reward pathway. The purpose of this study was to build a genetic profile for dopamine (DA) neurons in the VTA and investigate the disruptions to the molecular pathways after perinatal nicotine exposure. Initially, we isolated the VTA from rat pups treated perinatally with either nicotine or saline (control) and collected DA neurons using fluorescent-activated cell sorting. Using microarray analysis, we profiled the differential expression of mRNAs and microRNAs from DA neurons in the VTA in order to explore potential points of regulation and enriched pathways following perinatal nicotine exposure. Furthermore, mechanisms of miRNA-mediated post-transcriptional regulation were investigated using predicted and validated miRNA-gene targets in order to demonstrate the role of miRNAs in the mesocorticolimbic DA pathway. This study provides insight into the genetic profile as well as biological pathways of DA neurons in the VTA of rats following perinatal nicotine exposure.

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.

Analyzing the genes related to nicotine addiction or schizophrenia via a pathway and network based approach

The prevalence of tobacco use in people with schizophrenia is much higher than in general population, which indicates a close relationship between nicotine addiction and schizophrenia. However, the molecular mechanism underlying the high comorbidity of tobacco smoking and schizophrenia remains largely unclear. In this study, we conducted a pathway and network analysis on the genes potentially associated with nicotine addiction or schizophrenia to reveal the functional feature of these genes and their interactions. Of the 276 genes associated with nicotine addiction and 331 genes associated with schizophrenia, 52 genes were shared. From these genes, 12 significantly enriched pathways associated with both diseases were identified. These pathways included those related to synapse function and signaling transduction, and drug addiction. Further, we constructed a nicotine addiction-specific and schizophrenia-specific sub-network, identifying 11 novel candidate genes potentially associated with the two diseases. Finally, we built a schematic molecular network for nicotine addiction and schizophrenia based on the results of pathway and network analysis, providing a systematic view to understand the relationship between these two disorders. Our results illustrated that the biological processes underlying the comorbidity of nicotine addiction and schizophrenia was complex, and was likely induced by the dysfunction of multiple molecules and pathways.

GRONS: a comprehensive genetic resource of nicotine and smoking

Nicotine, the primary psychoactive component in tobacco, can exert a broad impact on both the central and peripheral nervous systems. During the past years, a tremendous amount of efforts has been put to exploring the molecular mechanisms underlying tobacco smoking related behaviors and diseases, and many susceptibility genes have been identified via various genomic approaches. For many human complex diseases, there is a trend towards collecting and integrating the data from genetic studies and the biological information related to them into a comprehensive resource for further investigation, but we have not found such an effort for nicotine addiction or smoking-related phenotypes yet. To collect, curate, and integrate cross-platform genetic data so as to make them interpretable and easily accessible, we developed Genetic Resources Of Nicotine and Smoking (GRONS), a comprehensive database for genes related to biological response to nicotine exposure, tobacco smoking related behaviors or diseases. GRONS deposits genes from nicotine addiction studies in the following four categories, i.e. association study, genome-wide linkage scan, expression analysis on genes/proteins via high-throughput technologies, as well as single gene/protein-based experimental studies via literature search. Moreover, GRONS not only provides tools for data browse, search and graphical presentation of gene prioritization, but also presents the results from comprehensive bioinformatics analyses for the prioritized genes associated with nicotine addiction. With more and more genetic data and analysis tools integrated, GRONS will become a useful resource for studies focusing on nicotine addiction or tobacco smoking.

Database URL: http://bioinfo.tmu.edu.cn/GRONS/

Network and Pathway-Based Analyses of Genes Associated with Parkinson's Disease

Parkinson's disease (PD) is a major neurodegenerative disease influenced by both genetic and environmental factors. Although previous studies have provided insights into the significant impacts of genetic factors on PD, the molecular mechanism underlying PD remains largely unclear. Under such situation, a comprehensive analysis focusing on biological function and interactions of PD-related genes will provide us valuable information to understand the pathogenesis of PD. In the current study, by reviewing the literatures deposited in PUBMED, we identified 242 genes genetically associated with PD, referred to as PD-related genes gene set (PDgset). Functional analysis revealed that biological processes and biochemical pathways related to neurodevelopment, metabolism, and immune system were enriched in PDgset. Then, pathway crosstalk analysis indicated that the enriched pathways could be grouped into two modules, with one module consisted of pathways mainly involved in neuronal signaling and another in immune response. Further, based on a global human interactome, we found that PDgset tended to have more moderate degree compared with cancer-related genes. Moreover, PD-specific molecular network was inferred using Steiner minimal tree algorithm and some potential related genes associated with PD were identified. In summary, by using network- and pathway-based methods to explore pathogenetic mechanism underlying PD, results from our work may have important implications for understanding the molecular mechanism underlying PD. Also, the framework proposed in our current work can be used to infer pathological molecular network and genes related to a specific disease.

RNA sequencing of transcriptomes in human brain regions: protein-coding and non-coding RNAs, isoforms and alleles

BACKGROUND

We used RNA sequencing to analyze transcript profiles of ten autopsy brain regions from ten subjects. RNA sequencing techniques were designed to detect both coding and non-coding RNA, splice isoform composition, and allelic expression. Brain regions were selected from five subjects with a documented history of smoking and five non-smokers. Paired-end RNA sequencing was performed on SOLiD instruments to a depth of >40 million reads, using linearly amplified, ribosomally depleted RNA. Sequencing libraries were prepared with both poly-dT and random hexamer primers to detect all RNA classes, including long non-coding (lncRNA), intronic and intergenic transcripts, and transcripts lacking poly-A tails, providing additional data not previously available. The study was designed to generate a database of the complete transcriptomes in brain region for gene network analyses and discovery of regulatory variants.

RESULTS

Of 20,318 protein coding and 18,080 lncRNA genes annotated from GENCODE and lncipedia, 12 thousand protein coding and 2 thousand lncRNA transcripts were detectable at a conservative threshold. Of the aligned reads, 52 % were exonic, 34 % intronic and 14 % intergenic. A majority of protein coding genes (65 %) was expressed in all regions, whereas ncRNAs displayed a more restricted distribution. Profiles of RNA isoforms varied across brain regions and subjects at multiple gene loci, with neurexin 3 (NRXN3) a prominent example. Allelic RNA ratios deviating from unity were identified in > 400 genes, detectable in both protein-coding and non-coding genes, indicating the presence of cis-acting regulatory variants. Mathematical modeling was used to identify RNAs stably expressed in all brain regions (serving as potential markers for normalizing expression levels), linked to basic cellular functions. An initial analysis of differential expression analysis between smokers and nonsmokers implicated a number of genes, several previously associated with nicotine exposure.

CONCLUSIONS

RNA sequencing identifies distinct and consistent differences in gene expression between brain regions, with non-coding RNA displaying greater diversity between brain regions than mRNAs. Numerous RNAs exhibit robust allele selective expression, proving a means for discovery of cis-acting regulatory factors with potential clinical relevance.

A Systematic Analysis of Candidate Genes Associated with Nicotine Addiction

Nicotine, as the major psychoactive component of tobacco, has broad physiological effects within the central nervous system, but our understanding of the molecular mechanism underlying its neuronal effects remains incomplete. In this study, we performed a systematic analysis on a set of nicotine addiction-related genes to explore their characteristics at network levels. We found that NAGenes tended to have a more moderate degree and weaker clustering coefficient and to be less central in the network compared to alcohol addiction-related genes or cancer genes. Further, clustering of these genes resulted in six clusters with themes in synaptic transmission, signal transduction, metabolic process, and apoptosis, which provided an intuitional view on the major molecular functions of the genes. Moreover, functional enrichment analysis revealed that neurodevelopment, neurotransmission activity, and metabolism related biological processes were involved in nicotine addiction. In summary, by analyzing the overall characteristics of the nicotine addiction related genes, this study provided valuable information for understanding the molecular mechanisms underlying nicotine addiction.

Pathways and networks-based analysis of candidate genes associated with nicotine addiction

Nicotine is the addictive substance in tobacco and it has a broad impact on both the central and peripheral nervous systems. Over the past decades, an increasing number of genes potentially involved in nicotine addiction have been identified by different technical approaches. However, the molecular mechanisms underlying nicotine addiction remain largely unclear. Under such situation, a comprehensive analysis focusing on the overall functional characteristics of these genes, as well as how they interact with each other will provide us valuable information to understand nicotine addiction. In this study, we presented a systematic analysis on nicotine addiction-related genes to identify the major underlying biological themes. Functional analysis revealed that biological processes and biochemical pathways related to neurodevelopment, immune system and metabolism were significantly enriched in the nicotine addiction-related genes. By extracting the nicotine addiction-specific subnetwork, a number of novel genes associated with addiction were identified. Moreover, we constructed a schematic molecular network for nicotine addiction via integrating the pathways and network, providing an intuitional view to understand the development of nicotine addiction. Pathway and network analysis indicated that the biological processes related to nicotine addiction were complex. Results from our work may have important implications for understanding the molecular mechanism underlying nicotine addiction.