Common and unique biological pathways associated with smoking initiation/progression, nicotine dependence, and smoking cessation

An epidemiological introduction to human metabolomic investigations

Metabolomics holds great promise for uncovering insights around biological processes impacting disease in human epidemiological studies. Metabolites can be measured across biological samples, including plasma, serum, saliva, urine, stool, and whole organs and tissues, offering a means to characterize metabolic processes relevant to disease etiology and traits of interest. Metabolomic epidemiology studies face unique challenges, such as identifying metabolites from targeted and untargeted assays, defining standards for quality control, harmonizing results across platforms that often capture different metabolites, and developing statistical methods for high-dimensional and correlated metabolomic data. In this review, we introduce metabolomic epidemiology to the broader scientific community, discuss opportunities and challenges presented by these studies, and highlight emerging innovations that hold promise to uncover new biological insights.

A Case-Only Genome-Wide Interaction Study of Smoking and Bladder Cancer Risk: Results from the COBLAnCE Cohort

Bladder cancer (BC) is the 6th most common cancer worldwide, with tobacco smoking considered as its main risk factor. Accumulating evidence has found associations between genetic variants and the risk of BC. Candidate gene-environment interaction studies have suggested interactions between cigarette smoking and NAT2/GSTM1 gene variants. Our objective was to perform a genome-wide association case-only study using the French national prospective COBLAnCE cohort (COhort to study BLAdder CancEr), focusing on smoking behavior. The COBLAnCE cohort comprises 1800 BC patients enrolled between 2012 and 2018. Peripheral blood samples collected at enrolment were genotyped using the Illumina Global Screening Array with a Multi-Disease drop-in panel. Genotyping data (9,719,614 single nucleotide polymorphisms (SNP)) of 1674, 1283, and 1342 patients were analyzed for smoking status, average tobacco consumption, and age at smoking initiation, respectively. A genome-wide association study (GWAS) was conducted adjusting for gender, age, and genetic principal components. The results suggest new candidate loci (4q22.1, 12p13.1, 16p13.3) interacting with smoking behavior for the risk of BC. Our results need to be validated in other case-control or cohort studies.

Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program

Smoking behaviors and alcohol use disorder (AUD), both moderately heritable traits, commonly co-occur in the general population. Single-trait genome-wide association studies (GWAS) have identified multiple loci for smoking and AUD. However, GWASs that have aimed to identify loci contributing to co-occurring smoking and AUD have used small samples and thus have not been highly informative. Applying multi-trait analysis of GWASs (MTAG), we conducted a joint GWAS of smoking and AUD with data from the Million Veteran Program (N = 318,694). By leveraging GWAS summary statistics for AUD, MTAG identified 21 genome-wide significant (GWS) loci associated with smoking initiation and 17 loci associated with smoking cessation compared to 16 and 8 loci, respectively, identified by single-trait GWAS. The novel loci for smoking behaviors identified by MTAG included those previously associated with psychiatric or substance use traits. Colocalization analysis identified 10 loci shared by AUD and smoking status traits, all of which achieved GWS in MTAG, including variants on SIX3, NCAM1, and near DRD2. Functional annotation of the MTAG variants highlighted biologically important regions on ZBTB20, DRD2, PPP6C, and GCKR that contribute to smoking behaviors. In contrast, MTAG of smoking behaviors and alcohol consumption (AC) did not enhance discovery compared with single-trait GWAS for smoking behaviors. We conclude that using MTAG to augment the power of GWAS enables the identification of novel genetic variants for commonly co-occuring phenotypes, providing new insights into their pleiotropic effects on smoking behavior and AUD.

Brain Structure and Function Show Distinct Relations With Genetic Predispositions to Mental Health and Cognition

BACKGROUND

Mental health and cognitive achievement are partly heritable, highly polygenic, and associated with brain variations in structure and function. However, the underlying neural mechanisms remain unclear.

METHODS

We investigated the association between genetic predispositions to various mental health and cognitive traits and a large set of structural and functional brain measures from the UK Biobank (N = 36,799). We also applied linkage disequilibrium score regression to estimate the genetic correlations between various traits and brain measures based on genome-wide data. To decompose the complex association patterns, we performed a multivariate partial least squares model of the genetic and imaging modalities.

RESULTS

The univariate analyses showed that certain traits were related to brain structure (significant genetic correlations with total cortical surface area from r_g = -0.101 for smoking initiation to r_g = 0.230 for cognitive ability), while other traits were related to brain function (significant genetic correlations with functional connectivity from r_g = -0.161 for educational attainment to r_g = 0.318 for schizophrenia). The multivariate analysis showed that genetic predispositions to attention-deficit/hyperactivity disorder, smoking initiation, and cognitive traits had stronger associations with brain structure than with brain function, whereas genetic predispositions to most other psychiatric disorders had stronger associations with brain function than with brain structure.

CONCLUSIONS

These results reveal that genetic predispositions to mental health and cognitive traits have distinct brain profiles.

Genetic Risk for Smoking: Disentangling Interplay Between Genes and Socioeconomic Status

This study aims to disentangle the contribution of genetic liability, educational attainment (EA), and their overlap and interaction in lifetime smoking. We conducted genome-wide association studies (GWASs) in UK Biobank (N = 394,718) to (i) capture variants for lifetime smoking, (ii) variants for EA, and (iii) variants that contribute to lifetime smoking independently from EA ('smoking-without-EA'). Based on the GWASs, three polygenic scores (PGSs) were created for individuals from the Netherlands Twin Register (NTR, N = 17,805) and the Netherlands Mental Health Survey and Incidence Study-2 (NEMESIS-2, N = 3090). We tested gene-environment (G × E) interactions between each PGS, neighborhood socioeconomic status (SES) and EA on lifetime smoking. To assess if the PGS effects were specific to smoking or had broader implications, we repeated the analyses with measures of mental health. After subtracting EA effects from the smoking GWAS, the SNP-based heritability decreased from 9.2 to 7.2%. The genetic correlation between smoking and SES characteristics was reduced, whereas overlap with smoking traits was less affected by subtracting EA. The PGSs for smoking, EA, and smoking-without-EA all predicted smoking. For mental health, only the PGS for EA was a reliable predictor. There were suggestions for G × E for some relationships, but there were no clear patterns per PGS type. This study showed that the genetic architecture of smoking has an EA component in addition to other, possibly more direct components. PGSs based on EA and smoking-without-EA had distinct predictive profiles. This study shows how disentangling different models of genetic liability and interplay can contribute to our understanding of the etiology of smoking.

Nicotine Effects, Body Weight Concerns and Smoking: A Literature Review

How people become addicted to cigarette smoking and remain addicted despite repeated attempts to quit requires piecing together a rather complex puzzle. The present review contextualizes the role of nicotine and smoking sensory stimulation on maintaining smoking, describes nicotine's effects on feeding behavior and body weight, and explores the impact of smoking outcome expectancies, including the belief that nicotine suppresses appetite and body weight, on the decision to smoke or vape (use of e-cigarettes). The analysis concludes with a review of rat models of human nicotine intake that attempt to isolate the effects of nicotine on appetite and weight gain. Animal research replicates with relative closeness phenomena observed in smokers, but the rat model falls short of replicating the long-term weight gain observed post-smoking cessation.

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.

Determining population stratification and subgroup effects in association studies of rare genetic variants for nicotine dependence

Supplemental Digital Content is available in the text.

Background

Rare variants (minor allele frequency < 1% or 5 %) can help researchers to deal with the confounding issue of ‘missing heritability’ and have a proven role in dissecting the etiology for human diseases and complex traits.

Methods

We extended the combined multivariate and collapsing (CMC) and weighted sum statistic (WSS) methods and accounted for the effects of population stratification and subgroup effects using stratified analyses by the principal component analysis, named here as ‘str-CMC’ and ‘str-WSS’. To evaluate the validity of the extended methods, we analyzed the Genetic Architecture of Smoking and Smoking Cessation database, which includes African Americans and European Americans genotyped on Illumina Human Omni2.5, and we compared the results with those obtained with the sequence kernel association test (SKAT) and its modification, SKAT-O that included population stratification and subgroup effect as covariates. We utilized the Cochran–Mantel–Haenszel test to check for possible differences in single nucleotide polymorphism allele frequency between subgroups within a gene. We aimed to detect rare variants and considered population stratification and subgroup effects in the genomic region containing 39 acetylcholine receptor-related genes.

Results

The Cochran–Mantel–Haenszel test as applied to GABRG2 (P = 0.001) was significant. However, GABRG2 was detected both by str-CMC (P= 8.04E-06) and str-WSS (P= 0.046) in African Americans but not by SKAT or SKAT-O.

Conclusions

Our results imply that if associated rare variants are only specific to a subgroup, a stratified analysis might be a better approach than a combined analysis.

Identification of 34 genes conferring genetic and pharmacological risk for the comorbidity of schizophrenia and smoking behaviors

The prevalence of smoking is significantly higher in persons with schizophrenia (SCZ) than in the general population. However, the biological mechanisms of the comorbidity of smoking and SCZ are largely unknown. This study aimed to reveal shared biological pathways for the two diseases by analyzing data from two genome-wide association studies with a total sample size of 153,898. With pathway-based analysis, we first discovered 18 significantly enriched pathways shared by SCZ and smoking, which were classified into five groups: postsynaptic density, cadherin binding, dendritic spine, long-term depression, and axon guidance. Then, by using an integrative analysis of genetic, epigenetic, and expression data, we found not only 34 critical genes (e.g., PRKCZ, ARHGEF3, and CDKN1A) but also various risk-associated SNPs in these genes, which convey susceptibility to the comorbidity of the two disorders. Finally, using both in vivo and in vitro data, we demonstrated that the expression profiles of the 34 genes were significantly altered by multiple psychotropic drugs. Together, this multi-omics study not only reveals target genes for new drugs to treat SCZ but also reveals new insights into the shared genetic vulnerabilities of SCZ and smoking behaviors.

Network and pathway-based analyses of genes associated with osteoporosis

Osteoporosis (OP) is a disease characterized by bone mass loss, bone microstructure damage, increased bone fragility, and easy fracture. The molecular mechanism underlying OP remains unclear.In this study, we identified 217 genes associated with OP, and formed a gene set [OP-related genes gene set (OPgset)].The highly enriched GOs and pathways showed OPgset genes were significantly involved in multiple biological processes (skeletal system development, ossification, and osteoblast differentiation), and several OP-related pathways (Wnt signaling pathway, osteoclast differentiation, steroid hormone biosynthesis, and adipocytokine signaling pathway). Besides, pathway crosstalk analysis indicated three major modules, with first module consisted of pathways mainly involved in bone development-related signaling pathways, second module in Wnt-related signaling pathway and third module in metabolic pathways. Further, we calculated degree centrality of a node and selected ten key genes/proteins, including TGFB1, IL6, WNT3A, TNF, PTH, TP53, WNT1, IGF1, IL10, and SERPINE1. We analyze the K-core and construct three k-core sub-networks of OPgset genes.In summary, we for the first time explored the molecular mechanism underlying OP via network- and pathway-based methods, results from our study will improve our understanding of the pathogenesis of OP. In addition, these methods performed in this study can be used to explore pathogenesis and genes related to a specific disease.

Analyzing the genes and pathways related to major depressive disorder via a systems biology approach

INTRODUCTION

Major depressive disorder (MDD) is a mental disorder caused by the combination of genetic, environmental, and psychological factors. Over the years, a number of genes potentially associated with MDD have been identified. However, in many cases, the role of these genes and their relationship in the etiology and development of MDD remains unclear. Under such situation, a systems biology approach focusing on the function correlation and interaction of the candidate genes in the context of MDD will provide useful information on exploring the molecular mechanisms underlying the disease.

METHODS

We collected genes potentially related to MDD by screening the human genetic studies deposited in PubMed (https://www.ncbi.nlm.nih.gov/pubmed). The main biological themes within the genes were explored by function and pathway enrichment analysis. Then, the interaction of genes was analyzed in the context of protein-protein interaction network and a MDD-specific network was built by Steiner minimal tree algorithm.

RESULTS

We collected 255 candidate genes reported to be associated with MDD from available publications. Functional analysis revealed that biological processes and biochemical pathways related to neuronal development, endocrine, cell growth and/or survivals, and immunology were enriched in these genes. The pathways could be largely grouped into three modules involved in biological procedures related to nervous system, the immune system, and the endocrine system, respectively. From the MDD-specific network, 35 novel genes potentially associated with the disease were identified.

CONCLUSION

By means of network- and pathway-based methods, we explored the molecular mechanism underlying the pathogenesis of MDD at a systems biology level. Results from our work could provide valuable clues for understanding the molecular features of MDD.

Differential gene expression analysis of HNSCC tumors deciphered tobacco dependent and independent molecular signatures

Head and neck cancer is the sixth most common cancer worldwide, with tobacco as the leading cause. However, it is increasing in non-tobacco users also, hence limiting our understanding of its underlying molecular mechanisms. RNA-seq analysis of cancers has proven as effective tool in understanding disease etiology. In the present study, RNA-Seq of 86 matched Tumor/Normal pairs, of tobacco smoking (TOB) and non-smokers (N-TOB) HNSCC samples analyzed, followed by validation on 375 similar datasets. Total 2194 and 2073 differentially expressed genes were identified in TOB and N-TOB tumors, respectively. GO analysis found muscle contraction as the most enriched biological process in both TOB and N-TOB tumors. Pathway analysis identified muscle contraction and salivary secretion pathways enriched in both categories, whereas calcium signaling and neuroactive ligand-receptor pathway was more enriched in TOB and N-TOB tumors respectively. Network analysis identified muscle development related genes as hub node i. e. ACTN2, MYL2 and TTN in both TOB and N-TOB tumors, whereas EGFR and MYH6, depicts specific role in TOB and N-TOB tumors. Additionally, we found enriched gene networks possibly be regulated by tumor suppressor miRNAs such as hsa-miR-29/a/b/c, hsa-miR-26b-5p etc., suggestive to be key riboswitches in regulatory cascade of HNSCC. Interestingly, three genes PKLR, CST1 and C17orf77 found to show opposite regulation in each category, hence suggested to be key genes in separating TOB from N-TOB tumors. Our investigation identified key genes involved in important pathways implicated in tobacco dependent and independent carcinogenesis hence may help in designing precise HNSCC diagnostics and therapeutics strategies.

Epigenome-wide association of father's smoking with offspring DNA methylation: a hypothesis-generating study

Epidemiological studies suggest that father's smoking might influence their future children's health, but few studies have addressed whether paternal line effects might be related to altered DNA methylation patterns in the offspring. To investigate a potential association between fathers' smoking exposures and offspring DNA methylation using epigenome-wide association studies. We used data from 195 males and females (11-54 years) participating in two population-based cohorts. DNA methylation was quantified in whole blood using Illumina Infinium MethylationEPIC Beadchip. Comb-p was used to analyse differentially methylated regions (DMRs). Robust multivariate linear models, adjusted for personal/maternal smoking and cell-type proportion, were used to analyse offspring differentially associated probes (DMPs) related to paternal smoking. In sensitivity analyses, we adjusted for socio-economic position and clustering by family. Adjustment for inflation was based on estimation of the empirical null distribution in BACON. Enrichment and pathway analyses were performed on genes annotated to cytosine-phosphate-guanine (CpG) sites using the gometh function in missMethyl. We identified six significant DMRs (Sidak-corrected P values: 0.0006-0.0173), associated with paternal smoking, annotated to genes involved in innate and adaptive immunity, fatty acid synthesis, development and function of neuronal systems and cellular processes. DMP analysis identified 33 CpGs [false discovery rate (FDR)  < 0.05]. Following adjustment for genomic control (λ = 1.462), no DMPs remained epigenome-wide significant (FDR < 0.05). This hypothesis-generating study found that fathers' smoking was associated with differential methylation in their adolescent and adult offspring. Future studies are needed to explore the intriguing hypothesis that fathers' exposures might persistently modify their future offspring's epigenome.

Examining sex differences in pleiotropic effects for depression and smoking using polygenic and gene-region aggregation techniques

Sex differences in rates of depression are thought to contribute to sex differences in smoking initiation (SI) and number of cigarettes smoked per day (CPD). One hypothesis is that women smoke as a strategy to cope with anxiety and depression, and have difficulty quitting because of concomitant changes in hypothalamic-pituitary-adrenocortical (HPA) axis function during nicotine withdrawal states. Despite evidence of biological ties, research has not examined whether genetic factors that contribute to depression-smoking comorbidity differ by sex. We utilized two statistical aggregation techniques-polygenic scores (PGSs) and sequence kernel association testing-to assess the degree of pleiotropy between these behaviors and moderation by sex in the Health and Retirement Study (N = 8,086). At the genome-wide level, we observed associations between PGSs for depressive symptoms and SI, and measured SI and depressive symptoms (all p < .01). At the gene level, we found evidence of pleiotropy in FKBP5 for SI (p = .028), and sex-specific pleiotropy in females in NR3C2 (p = .030) and CHRNA5 (p = .025) for SI and CPD, respectively. Results suggest bidirectional associations between depression and smoking may be partially accounted for by shared genetic factors, and genetic variation in genes related to HPA-axis functioning and nicotine dependence may contribute to sex differences in SI and CPD.

A Review on the Receptor-ligand Molecular Interactions in the Nicotinic Receptor Signaling Systems

Nicotine is regarded as the main active addictive ingredient in tobacco products driving continued tobacco abuse behavior (smoking) to the addiction behavior, whereas nicotinic acetylcholine receptors (nAChR) is the crucial effective apparatus or molecular effector of nicotine and acetylcholine and other similar ligands. Many nAChR subunits have been revealed to bind to either neurotransmitters or exogenous ligands, such as nicotine and acetylcholine, being involved in the nicotinic receptor signal transduction. Therefore, the nicotinic receptor signalling molecules and the receptor-ligand molecular interactions between nAChRs and their ligands are universally regarded as crucial mediators of cellular functions and drug targets in medical treatment and clinical diagnosis. Given numerous endeavours have been made in defining the roles of nAChRs in response to nicotine and other addictive drugs, this review focuses on studies and reports in recent years on the receptor-ligand interactions between nAChR receptors and ligands, including lipid-nAChR and protein-nAChR molecular interactions, relevant signal transduction pathways and their molecular mechanisms in the nicotinic receptor signalling systems. All the references were carefully retrieved from the PubMed database by searching key words "nicotine", "acetylcholine", "nicotinic acetylcholine receptor(s)", "nAChR*", "protein and nAChR", "lipid and nAChR", "smok*" and "tobacco". All the relevant referred papers and reports retrieved were fully reviewed for manual inspection. This effort intend to get a quick insight and understanding of the nicotinic receptor signalling and their molecular interactions mechanisms. Understanding the cellular receptor-ligand interactions and molecular mechanisms between nAChRs and ligands will lead to a better translational and therapeutic operations and outcomes for the prevention and treatment of nicotine addiction and other chronic drug addictions in the brain's reward circuitry.

Genome-wide association study in Finnish twins highlights the connection between nicotine addiction and neurotrophin signaling pathway

The heritability of nicotine dependence based on family studies is substantial. Nevertheless, knowledge of the underlying genetic architecture remains meager. Our aim was to identify novel genetic variants responsible for interindividual differences in smoking behavior. We performed a genome-wide association study on 1715 ever smokers ascertained from the population-based Finnish Twin Cohort enriched for heavy smoking. Data imputation used the 1000 Genomes Phase I reference panel together with a whole genome sequence-based Finnish reference panel. We analyzed three measures of nicotine addiction-smoking quantity, nicotine dependence and nicotine withdrawal. We annotated all genome-wide significant SNPs for their functional potential. First, we detected genome-wide significant association on 16p12 with smoking quantity (P = 8.5 × 10^-9 ), near CLEC19A. The lead-SNP stands 22 kb from a binding site for NF-κB transcription factors, which play a role in the neurotrophin signaling pathway. However, the signal was not replicated in an independent Finnish population-based sample, FINRISK (n = 6763). Second, nicotine withdrawal showed association on 2q21 in an intron of TMEM163 (P = 2.1 × 10^-9 ), and on 11p15 (P = 6.6 × 10^-8 ) in an intron of AP2A2, and P = 4.2 × 10^-7 for a missense variant in MUC6, both involved in the neurotrophin signaling pathway). Third, association was detected on 3p22.3 for maximum number of cigarettes smoked per day (P = 3.1 × 10^-8 ) near STAC. Associating CLEC19A and TMEM163 SNPs were annotated to influence gene expression or methylation. The neurotrophin signaling pathway has previously been associated with smoking behavior. Our findings further support the role in nicotine addiction.

From genes to treatments: a systematic review of the pharmacogenetics in smoking cessation

Smoking cessation treatment outcomes may be heavily influenced by genetic variations among smokers. Therefore, identifying specific variants that affect response to different pharmacotherapies is of major interest to the field. In the current study, we systematically review all studies published in or after the year 1990 which examined one or more gene-drug interactions for smoking cessation treatment. Out of 644 citations, 46 articles met the inclusion criteria for the systematic review. We summarize evidence on several genetic polymorphisms (CHRNA5-A3-B4, CYP2A6, DBH, CHRNA4, COMT, DRD2, DRD4 and CYP2B6) and their potential moderating pharamacotherarpy effects on patient cessation efficacy rates. These findings are promising and call for further research to demonstrate the effectiveness of genetic testing in personalizing treatment decision-making and improving outcome.

Testing associations between cannabis use and subcortical volumes in two large population-based samples

BACKGROUND AND AIMS

Disentangling the putative impact of cannabis on brain morphology from other comorbid substance use is critical. After controlling for the effects of nicotine, alcohol and multi-substance use, this study aimed to determine whether frequent cannabis use is associated with significantly smaller subcortical grey matter volumes.

DESIGN

Exploratory analyses using mixed linear models, one per region of interest (ROI), were performed whereby individual differences in volume (outcome) at seven subcortical ROIs were regressed onto cannabis and comorbid substance use (predictors).

SETTING

Two large population-based twin samples from the United States and Australia.

PARTICIPANTS

A total of 622 young Australian adults [66% female; μage  = 25.9, standard deviation SD) = 3.6] and 474 middle-aged US males (μage  = 56.1SD = 2.6 ) of predominately Anglo-Saxon ancestry with complete substance use and imaging data. Subjects with a history of stroke or traumatic brain injury were excluded.

MEASUREMENTS

Magnetic resonance imaging (MRI) and volumetric segmentation methods were used to estimate volume in seven subcortical ROIs: thalamus, caudate nucleus, putamen, pallidum, hippocampus, amygdala and nucleus accumbens. Substance use measurements included maximum nicotine and alcohol use, total life-time multi-substance use, maximum cannabis use in the young adults and regular cannabis use in the middle-aged males.

FINDINGS

After correcting for multiple testing (P = 0.007), cannabis use was unrelated to any subcortical ROI. However, maximum nicotine use was associated with significantly smaller thalamus volumes in middle-aged males.

CONCLUSIONS

In exploratory analyses based on young adult and middle-aged samples, normal variation in cannabis use is unrelated statistically to individual differences in brain morphology as measured by subcortical volume.

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/

Antidepressant Mechanism Research of Acupuncture: Insights from a Genome-Wide Transcriptome Analysis of Frontal Cortex in Rats with Chronic Restraint Stress

Major depressive disorder (MDD) is a chronic disease that adversely affects mood and cognition. In this study, we randomly divided the rats into control group (C), model group (M), fluoxetine group (F), and acupuncture group (A), used open-field test to ascertain whether acupuncture affects chronic restraint stress (CRS) induced depression-like behaviors of rats, and explored the antidepressant mechanism of acupuncture at the molecular level of transcriptome in the frontal cortex of CRS rats by RNA-sequencing (RNA-seq). According to differentially expressed genes (DEG) analysis, we identified 134, 46, and 89 response genes differentially expressed in C versus M, F versus M, and A versus M, respectively. Through Gene Ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, we identified the gene sets involved in extracellular space, inflammatory response, Toll-like receptor signaling pathway, chemokine signaling pathway, and TNF signaling pathway. In this study, RNA-seq technology was used to investigate the frontal cortex genome-wide transcriptomes in depression rats under CRS, which suggested that the antidepressant effect of acupuncture is effective and has a multitarget characteristic, which may be related to amino acid metabolism and inflammatory pathways, especially the Toll-like receptor signaling pathway, TNF signaling pathway, and NF-kappa B signaling pathway.

Pharmacotherapy for smoking cessation: effects by subgroup defined by genetically informed biomarkers

BACKGROUND

Smoking cessation therapies are not effective for all smokers, and researchers are interested in identifying those subgroups of individuals (e.g. based on genotype) who respond best to specific treatments.

OBJECTIVES

To assess whether quit rates vary by genetically informed biomarkers within pharmacotherapy treatment arms and as compared with placebo. To assess the effects of pharmacotherapies for smoking cessation in subgroups of smokers defined by genotype for identified genome-wide significant polymorphisms.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group specialised register, clinical trial registries, and genetics databases for trials of pharmacotherapies for smoking cessation from inception until 16 August 2016.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) that recruited adult smokers and reported pharmacogenomic analyses from trials of smoking cessation pharmacotherapies versus controls. Eligible trials included those with data on a priori genome-wide significant (P < 5 × 10-8) single-nucleotide polymorphisms (SNPs), replicated non-SNPs, and/or the nicotine metabolite ratio (NMR), hereafter collectively described as biomarkers.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures expected by Cochrane. The primary outcome was smoking abstinence at six months after treatment. The secondary outcome was abstinence at end of treatment (EOT). We conducted two types of meta-analyses- one in which we assessed smoking cessation of active treatment versus placebo within genotype groups, and another in which we compared smoking cessation across genotype groups within treatment arms. We carried out analyses separately in non-Hispanic whites (NHWs) and non-Hispanic blacks (NHBs). We assessed heterogeneity between genotype groups using T², I², and Cochrane Q statistics.

MAIN RESULTS

Analyses included 18 trials including 9017 participants, of whom 6924 were NHW and 2093 NHB participants. Data were available for the following biomarkers: nine SNPs (rs1051730 (CHRNA3); rs16969968, rs588765, and rs2036527 (CHRNA5); rs3733829 and rs7937 (in EGLN2, near CYP2A6); rs1329650 and rs1028936 (LOC100188947); and rs215605 (PDE1C)), two variable number tandem repeats (VNTRs; DRD4 and SLC6A4), and the NMR. Included data produced a total of 40 active versus placebo comparisons, 16 active versus active comparisons, and 64 between-genotype comparisons within treatment arms.For those meta-analyses showing statistically significant heterogeneity between genotype groups, we found the quality of evidence (GRADE) to be generally moderate. We downgraded quality most often because of imprecision or risk of bias due to potential selection bias in genotyping trial participants. Comparisons of relative treatment effects by genotypeFor six-month abstinence, we found statistically significant heterogeneity between genotypes (rs16969968) for nicotine replacement therapy (NRT) versus placebo at six months for NHB participants (P = 0.03; n = 2 trials), but not for other biomarkers or treatment comparisons. Six-month abstinence was increased in the active NRT group as compared to placebo among participants with a GG genotype (risk ratio (RR) 1.47, 95% confidence interval (CI) 1.07 to 2.03), but not in the combined group of participants with a GA or AA genotype (RR 0.43, 95% CI 0.15 to 1.26; ratio of risk ratios (RRR) GG vs GA or AA of 3.51, 95% CI 1.19 to 10.3). Comparisons of treatment effects between genotype groups within pharmacotherapy randomisation armsFor those receiving active NRT, treatment was more effective in achieving six-month abstinence among individuals with a slow NMR than among those with a normal NMR among NHW and NHB combined participants (normal NMR vs slow NMR: RR 0.54, 95% CI 0.37 to 0.78; n = 2 trials). We found no such differences in treatment effects between genotypes at six months for any of the other biomarkers among individuals who received pharmacotherapy or placebo.

AUTHORS' CONCLUSIONS

We did not identify widespread differential treatment effects of pharmacotherapy based on genotype. Some genotype groups within certain ethnic groups may benefit more from NRT or may benefit less from the combination of bupropion with NRT. The reader should interpret these results with caution because none of the statistically significant meta-analyses included more than two trials per genotype comparison, many confidence intervals were wide, and the quality of this evidence (GRADE) was generally moderate. Although we found evidence of superior NRT efficacy for NMR slow versus normal metabolisers, because of the lack of heterogeneity between NMR groups, we cannot conclude that NRT is more effective for slow metabolisers. Access to additional data from multiple trials is needed, particularly for comparisons of different pharmacotherapies.

Significant association of the CHRNB3-CHRNA6 gene cluster with nicotine dependence in the Chinese Han population

Although numerous studies have revealed significant associations between variants in the nicotinic acetylcholine receptors (nAChR) subunits and nicotine dependence (ND), only few studies were performed in Chinese subjects. Here, we performed association and interaction analysis for 20 single nucleotide polymorphisms (SNPs) in the CHRNB3-CHRNA6 gene cluster with ND in a Chinese Han population (N = 5,055). We found nominally significant associations for all tested SNPs with ND measured by the Fagerström Test for Nicotine Dependence score; of these, 11 SNPs remained significant after Bonferroni correction for multiple tests (p = 9 × 10⁻⁴~2 × 10⁻³). Further conditional analysis indicated that no other SNP was significantly associated with ND independent of the most-highly significant SNP, rs6474414. Also, our haplotype-based association analysis indicated that each haplotype block was significantly associated with ND (p < 0.01). Further, we provide the first evidence of the genetic interaction of these two genes in affecting ND in this sample with an empirical p-value of 0.0015. Finally, our meta-analysis of samples with Asian and European origins for five SNPs in CHRNB3 showed significant associations with ND, with p-values ranging from 6.86 × 10⁻¹⁴ for rs13280604 to 6.50 × 10⁻⁸ for rs4950^. This represents the first study showing that CHRNB3/A6 are highly associated with ND in a large Chinese Han sample.

snoRNA and piRNA expression levels modified by tobacco use in women with lung adenocarcinoma

Lung cancer is one of the most frequent types of cancer worldwide. Most patients are diagnosed at advanced stage and thus have poor prognosis. Smoking is a risk factor for lung cancer, however most smokers do not develop lung cancer while 20% of women with lung adenocarcinoma are non-smokers. Therefore, it is possible that these two groups present differences besides the smoking status, including differences in their gene expression signature. The altered expression patterns of non-coding RNAs in complex diseases make them potential biomarkers for diagnosis and treatment. We analyzed data from differentially and constitutively expressed PIWI-interacting RNAs and small nucleolar RNAs from publicly available small RNA high-throughput sequencing data in search of an expression pattern of non-coding RNA that could differentiate these two groups. Here, we report two sets of differentially expressed small non-coding RNAs identified in normal and tumoral tissues of women with lung adenocarcinoma, that discriminate between smokers and non-smokers. Our findings may offer new insights on metabolic alterations caused by tobacco and may be used for early diagnosis of lung cancer.

Pathways to smoking behaviours: biological insights from the Tobacco and Genetics Consortium meta-analysis

By running gene and pathway analyses for several smoking behaviours in the Tobacco and Genetics Consortium (TAG) sample of 74 053 individuals, 21 genes and several chains of biological pathways were implicated. Analyses were carried out using the HYbrid Set-based Test (HYST) as implemented in the Knowledge-based mining system for Genome-wide Genetic studies software. Fifteen genes are novel and were not detected with the single nucleotide polymorphism-based approach in the original TAG analysis. For quantity smoked, 14 genes passed the false discovery rate of 0.05 (corrected for multiple testing), with the top association signal located at the IREB2 gene (P=1.57E-37). Three genomic loci were significantly associated with ever smoked. The top signal is located at the noncoding antisense RNA transcript BDNF-AS (P=6.25E-07) on 11p14. The SLC25A21 gene (P=2.09E-08) yielded the top association signal in the analysis of smoking cessation. The 19q13 noncoding RNA locus exceeded the genome-wide significance in the analysis of age at initiation (P=1.33E-06). Pathways belonging to the Neuronal system pathways, harbouring the nicotinic acetylcholine receptor genes expressing the α (CHRNA 1-9), β (CHRNB 1-4), γ, δ and ɛ subunits, yielded the smallest P-values in the pathway analysis of the quantity smoked (lowest P=4.90E-42). Additionally, pathways belonging to 'a subway map of cancer pathways' regulating the cell cycle, mitotic DNA replication, axon growth and synaptic plasticity were found significantly enriched for genetic variants in ever smokers relative to never smokers (lowest P=1.61E-07). In addition, these pathways were also significantly associated with the quantity smoked (lowest P=4.28E-17). Our results shed light on one of the world's leading causes of preventable death and open a path to potential therapeutic targets. These results are informative in decoding the biological bases of other disease traits, such as depression and cancers, with which smoking shares genetic vulnerabilities.

Pharmacogenetic Optimization of Smoking Cessation Treatment

Worldwide, approximately one billion people smoke cigarettes. Cigarette smoking persists in part because long-term smoking cessation rates are modest on existing treatments. Smoking cessation outcomes are influenced by genetic factors, including genetic variation in enzymes that metabolize nicotine and smoking cessation medications, as well as in receptor targets for nicotine and treatment medications. For example, smokers with genetically slow nicotine metabolism have higher cessation success on behavioural counseling and nicotine patches compared with smokers with genetically fast nicotine metabolism. In this review, we highlight new progress in our understanding of how genetic variation in the pharmacological targets of nicotine and smoking cessation medications could be used to tailor smoking cessation therapy, increase quit rates, and reduce tobacco-related harm.

The association of dopamine pathway gene score, nicotine dependence and smoking cessation in a rural male population of Shandong, China

BACKGROUND AND OBJECTIVES

Smoking and smoking cessation are both psychological and physiological traits. We aimed to investigate the interaction between dopamine pathway gene scores and nicotine dependence on smoking cessation in a rural Chinese male population.

METHODS

Participants were recruited from 17 villages in Shandong, China. DNA was extracted from blood sample of 819 participants. 25 single nucleotide polymorphisms (SNPs) in 8 dopamine (DA) pathway genes were genotyped. Weighted gene score of each gene is used to analyze the whole gene effect. Logistic regression was used to calculate odds ratios (OR) and multivariate-adjusted OR of each gene score for smoking cessation. Multiplicative model interaction was assessed through a cross-product interaction term of gene score by nicotine dependence in a multivariate logistic regression model.

RESULTS

After adjusting for age, occupation, education, marital status, self-rating anxiety score, and disease status, we observed significant negative associations of catechol-O-methyltransferase (COMT), dopamine receptor D2 (DRD2) gene score and smoking cessation, as well as significant positive associations between ankyrin repeat and kinase domain containing 1 (ANKK1), dopamine transporter (SLC6A3), dopamine receptor D4 (DRD4) gene score and smoking cessation. A significant multiplicative model interaction between nicotine dependence and the SLC6A3 gene score on smoking cessation was also observed (p = .03).

CONCLUSIONS AND SCIENTIFIC SIGNIFICANCE

There is a significant multiplicative model interaction of SLC6A3 gene score and nicotine dependence on smoking cessation. This finding could help to identify smokers who may be at high risk of relapse, and thus to develop more professional and personalized smoking cessation treatment. (Am J Addict 2016;25:493-498).

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.

Genetic Relationship between Schizophrenia and Nicotine Dependence

It is well known that most schizophrenia patients smoke cigarettes. There are different hypotheses postulating the underlying mechanisms of this comorbidity. We used summary statistics from large meta-analyses of plasma cotinine concentration (COT), Fagerström test for nicotine dependence (FTND) and schizophrenia to examine the genetic relationship between these traits. We found that schizophrenia risk scores calculated at P-value thresholds of 5 × 10⁻³ and larger predicted FTND and cigarettes smoked per day (CPD), suggesting that genes most significantly associated with schizophrenia were not associated with FTND/CPD, consistent with the self-medication hypothesis. The COT risk scores predicted schizophrenia diagnosis at P-values of 5 × 10⁻³ and smaller, implying that genes most significantly associated with COT were associated with schizophrenia. These results implicated that schizophrenia and FTND/CPD/COT shared some genetic liability. Based on this shared liability, we identified multiple long non-coding RNAs and RNA binding protein genes (DA376252, BX089737, LOC101927273, LINC01029, LOC101928622, HY157071, DA902558, RBFOX1 and TINCR), protein modification genes (MANBA, UBE2D3, and RANGAP1) and energy production genes (XYLB, MTRF1 and ENOX1) that were associated with both conditions. Further analyses revealed that these shared genes were enriched in calcium signaling, long-term potentiation and neuroactive ligand-receptor interaction pathways that played a critical role in cognitive functions and neuronal plasticity.

Cardiovascular diseases among patients with schizophrenia

The presence of comorbid physical illnesses especially, cardiovascular diseases (CVD) in schizophrenia is a growing area of concern in recent years. In order to reduce disease burden, to improve quality of life and to provide holistic care, it is important to know about the relationship between schizophrenia and CVD. The objective of this review is to explore the extent of CVD problems, relevant risk factors and potential measures for early diagnosis and prevention of CVD among patients with schizophrenia. Worldwide studies show that patients with schizophrenia have a higher mortality and lower life expectancy than the general population. CVD is the leading cause of increased mortality in schizophrenia. Common CVD risk factors in schizophrenia include metabolic syndrome, sedentary behaviour, tobacco smoking, effects of antipsychotics, long chain omega-3 fatty acid deficiency and shared genetics between CVD and schizophrenia. The potential methods for early detection and prevention of CVD in schizophrenia are also discussed. Though the patients with schizophrenia form a high risk group for CVD, consensus guidelines for early detection and prevention of CVD in schizophrenia are lacking. Comorbidity of CVD in schizophrenia needs more serious attention by clinicians and researchers.

Integrated miRNA-mRNA analysis in the habenula nuclei of mice intravenously self-administering nicotine

A considerable amount of evidence suggests that microRNAs (miRNAs) play crucial roles in the neuroadaptation of drug addiction. Habenula (Hb), one of the critical brain regions involved in reward and addiction, can be divided into two anatomically and transcriptionally distinct regions: medial habenula (MHb) and lateral habenula (LHb) nuclei. However, very few studies have compared the functional roles of these regions. Here, by using mirConnX integrator and KEGG pathway mapping, we simultaneously analysed the differential expression patterns of miRNAs and messenger RNA (mRNA) within MHb and LHb under nicotine addiction. Significantly altered miRNAs and mRNAs were found in the Hb of mice intravenously self-administering nicotine. Interestingly, some miRNAs were oppositely regulated between the MHb and the LHb, and their potential targets included various genes of cell signalling pathways related to the degeneration of fasciculus retroflexus (FR). This study provides an improved insight into the differential regulation of habenular transcripts in nicotine addiction, as well as the potential functions of miRNAs in several biological pathways involved in the nicotine addiction.

Meta-analysis reveals significant association of 3'-UTR VNTR in SLC6A3 with smoking cessation in Caucasian populations

Many studies have examined the association between SLC6A3 3′-UTR VNTR polymorphism and smoking cessation; however, the results are inconclusive, primarily because of the small to moderate-size samples. The primary goal of this study was to determine whether this polymorphism has any effect on smoking cessation by a meta-analysis of all reported studies. We adopted a 9-repeat dominant model that considers 9-repeat and non 9-repeat as two genotypes and compared their frequencies in former vs. current smokers. Eleven studies with 5,480 participants were included. Considering the presence of study heterogeneity and differences in the availability of information from each study, three separate meta-analyses were performed with the Comprehensive Meta-Analysis statistical software (v. 2.0). The first meta-analysis provided evidence of association between the 9-repeat genotype and smoking cessation under the fixed-effects model (pooled odds ratio [OR] 1.13; 95% confidence interval [CI] 1.01, 1.27; P = 0.037) but not in the random-effects model (pooled OR 1.11; 95% CI 0.96, 1.29; P = 0.159). Given the marginal evidence of heterogeneity among studies (P = 0.10; I2 = 35.9%), which likely was caused by inclusion of an Asian-population treatment study with an opposite effect of the polymorphism on smoking cessation, we excluded these data, revealing a significant association between the 9-repeat genotype and smoking cessation under both the fixed- and random-effects models (pooled OR 1.15; 95% CI 1.02, 1.29; P = 0.02 for both models). By analyzing adjusted and unadjusted results, we performed the third meta-analysis, which showed consistently that the 9-repeat genotype was significantly associated with smoking cessation under both the fixed- and random-effects models (pooled OR 1.17; 95% CI 1.04, 1.31; P = 0.009 for both models). We conclude that the 3′-UTR VNTR polymorphism is significantly associated with smoking cessation, and smokers with one or more 9-repeat alleles have a 17% higher probability of smoking cessation than smokers carrying no such allele.

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.

Gene-based and pathway-based genome-wide association study of alcohol dependence

BACKGROUND

The organization of risk genes within signaling pathways may provide clues about the converging neurobiological effects of risk genes for alcohol dependence.

AIM

Identify risk genes and risk gene pathways for alcohol dependence.

METHODS

We conducted a pathway-based genome-wide association study (GWAS) of alcohol dependence using a gene-set-rich analytic approach. Approximately one million genetic markers were tested in the discovery sample which included 1409 European-American (EA) alcohol dependent individuals and 1518 EA healthy comparison subjects. An additional 681 African-American (AA) cases and 508 AA healthy subjects served as the replication sample.

RESULTS

We identified several genome-wide replicable risk genes and risk pathways that were significantly associated with alcohol dependence. After applying the Bonferroni correction for multiple testing, the 'cellextracellular matrix interactions' pathway (p<2.0E-4 in EAs) and the PXN gene (which encodes paxillin) (p=3.9E-7 in EAs) within this pathway were the most promising risk factors for alcohol dependence. There were also two nominally replicable pathways enriched in alcohol dependence-related genes in both EAs (0.015≤p≤0.035) and AAs (0.025≤p≤0.050): the 'Na+/Cl- dependent neurotransmitter transporters' pathway and the 'other glycan degradation' pathway.

CONCLUSION

These findings provide new evidence highlighting several genes and biological signaling processes that may be related to the risk for alcohol dependence.

Molecular phenotyping of a UK population: defining the human serum metabolome

Phenotyping of 1,200 'healthy' adults from the UK has been performed through the investigation of diverse classes of hydrophilic and lipophilic metabolites present in serum by applying a series of chromatography-mass spectrometry platforms. These data were made robust to instrumental drift by numerical correction; this was prerequisite to allow detection of subtle metabolic differences. The variation in observed metabolite relative concentrations between the 1,200 subjects ranged from less than 5 % to more than 200 %. Variations in metabolites could be related to differences in gender, age, BMI, blood pressure, and smoking. Investigations suggest that a sample size of 600 subjects is both necessary and sufficient for robust analysis of these data. Overall, this is a large scale and non-targeted chromatographic MS-based metabolomics study, using samples from over 1,000 individuals, to provide a comprehensive measurement of their serum metabolomes. This work provides an important baseline or reference dataset for understanding the 'normal' relative concentrations and variation in the human serum metabolome. These may be related to our increasing knowledge of the human metabolic network map. Information on the Husermet study is available at http://www.husermet.org/. Importantly, all of the data are made freely available at MetaboLights (http://www.ebi.ac.uk/metabolights/).

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

Nicotine 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 unknown. Under such situation, prioritizing the candidate genes for further investigation is becoming increasingly important. In this study, we presented a multi-source-based gene prioritization approach for nicotine addiction by utilizing the vast amounts of information generated from for nicotine addiction study during the past years. In this approach, we first collected and curated genes from studies in four categories, i.e., genetic association analysis, genetic linkage analysis, high-throughput gene/protein expression analysis, and literature search of single gene/protein-based studies. Based on these resources, the genes were scored and a weight value was determined for each category. Finally, the genes were ranked by their combined scores, and 220 genes were selected as the prioritized nicotine addiction-related genes. Evaluation suggested the prioritized genes were promising targets for further analysis and replication study.

Genetics and smoking

Regular smoking is the major risk factor for cardiovascular disease and cancers, and thus is one of the most preventable causes of morbidity and mortality worldwide. Intake of nicotine, its central nervous system effects, and its metabolism are regulated by biological pathways; some of these are well known, but others are not. Genetic studies offer a method for developing insights into the genes contributing to those pathways. In recent years, large genome-wide association study (GWAS) meta-analyses have consistently revealed that the strongest genetic contribution to smoking-related traits comes from variation in the nicotinic receptor subunit genes. Many other genes, including those coding for enzymes involved in nicotine metabolism, also have been implicated. However, the proportion of phenotypic variance explained by the identified genetic variants is very modest. This review intends to cover progress made in genetics and genetic epidemiology of smoking behavior in recent years, and focuses on studies revealing the nicotinic receptor gene cluster on chromosome 15q25. Evidence supporting the involvement of a novel pathway in the shared pathophysiology of nicotine dependence and schizophrenia is also briefly reviewed. A summary of the current knowledge on gene-environment interactions involved in smoking behavior is included.

Increased mortality in schizophrenia due to cardiovascular disease - a non-systematic review of epidemiology, possible causes, and interventions

BACKGROUND

Schizophrenia is among the major causes of disability worldwide and the mortality from cardiovascular disease (CVD) is significantly elevated. There is a growing concern that this health challenge is not fully understood and efficiently addressed.

METHODS

Non-systematic review using searches in PubMed on relevant topics as well as selection of references based on the authors' experience from clinical work and research in the field.

RESULTS

In most countries, the standardized mortality rate in schizophrenia is about 2.5, leading to a reduction in life expectancy between 15 and 20 years. A major contributor of the increased mortality is due to CVD, with CVD mortality ranging from 40 to 50% in most studies. Important causal factors are related to lifestyle, including poor diet, lack of physical activity, smoking, and substance abuse. Recent findings suggest that there are overlapping pathophysiology and genetics between schizophrenia and CVD-risk factors, further increasing the liability to CVD in schizophrenia. Many pharmacological agents used for treating psychotic disorders have side effects augmenting CVD risk. Although several CVD-risk factors can be effectively prevented and treated, the provision of somatic health services to people with schizophrenia seems inadequate. Further, there is a sparseness of studies investigating the effects of lifestyle interventions in schizophrenia, and there is little knowledge about effective programs targeting physical health in this population.

DISCUSSION

The risk for CVD and CVD-related deaths in people with schizophrenia is increased, but the underlying mechanisms are not fully known. Coordinated interventions in different health care settings could probably reduce the risk. There is an urgent need to develop and implement effective programs to increase life expectancy in schizophrenia, and we argue that mental health workers should be more involved in this important task.

The association between CHRN genetic variants and dizziness at first inhalation of cigarette smoke

Numerous single nucleotide polymorphisms (SNPs) in multiple nicotinic receptor genes (CHRN) are associated with smoking. However few studies have examined the association between CHRN SNPs and subjective responses to smoking in adolescents which may relate to sustained smoking, such as dizziness at first inhalation. The objective of this study was to investigate the association between 61 SNPs in eight CHRN genes (CHRNA3, CHRNA4, CHRNA5, CHRNA6, CHRNA7, CHRNB2, CHRNB3, CHRNB4) and dizziness at first inhalation. Data were available from a longitudinal cohort investigation of 1293 students 12-13year-old at baseline. Students completed self-report questionnaires at school every 3months for 5years during secondary school, and a mailed questionnaire three years later. DNA extracted from blood or saliva was genotyped for 61 CHRN SNPs selected using a gene tagging approach. Associations were modeled using logistic regression controlling for sex, race and age at first cigarette. Complete data were available for 356 of 475 participants (75%) who initiated smoking. The minor alleles of three SNPs in CHRNA6 (rs7812298, rs2304297, rs7828365) were associated with a decreased probability of dizziness (OR(95% CI)=0.54 (0.36, 0.81), 0.59 (0.40, 0.86) and 0.58 (0.36, 0.95), respectively), while one SNP in each of three other genes (rs3743077 (CHRNA3), rs755204 (CHRNA4), rs7178176 (CHRNA7)) was associated with an increased probability of dizziness (OR(95% CI)=1.40 (1.02, 1.90), 1.85 (1.05, 3.27) and 1.51 (1.06, 2.15), respectively). Thus, several SNPs located in CHRN genes are associated with dizziness at first inhalation, a smoking initiation phenotype that may relate to sustained smoking.

Influence of a dopamine pathway additive genetic efficacy score on smoking cessation: results from two randomized clinical trials of bupropion

AIMS

To evaluate the associations of treatment and an additive genetic efficacy score (AGES) based on dopamine functional polymorphisms with time to first smoking lapse and point prevalence abstinence at end of treatment among participants enrolled into two randomized clinical trials of smoking cessation therapies.

DESIGN

Double-blind pharmacogenetic efficacy trials randomizing participants to active or placebo bupropion. Study 1 also randomized participants to cognitive-behavioral smoking cessation treatment (CBT) or this treatment with CBT for depression. Study 2 provided standardized behavioural support.

SETTING

Two hospital-affiliated clinics (study 1), and two university-affiliated clinics (study 2).

PARTICIPANTS

A total of 792 self-identified white treatment-seeking smokers aged ≥18 years smoking ≥10 cigarettes per day over the last year.

MEASUREMENTS

Age, gender, Fagerström Test for Nicotine Dependence, dopamine pathway genotypes (rs1800497 [ANKK1 E713K], rs4680 [COMT V158M], DRD4 exon 3 variable number of tandem repeats polymorphism [DRD4 VNTR], SLC6A3,3' VNTR) analyzed both separately and as part of an AGES, time to first lapse and point prevalence abstinence at end of treatment.

FINDINGS

Significant associations of the AGES (hazard ratio [HR] = 1.10, 95% confidence interval [CI] = 1.06-1.14, P = 0.009) and of the DRD4 VNTR (HR = 1.29, 95% CI = 1.17-1.41, P = 0.0073) were observed with time to first lapse. A significant AGES by pharmacotherapy interaction was observed (β standard error = -0.18 [0.07], P = 0.016), such that AGES predicted risk for time to first lapse only for individuals randomized to placebo.

CONCLUSIONS

A score based on functional polymorphisms relating to dopamine pathways appears to predict lapse to smoking following a quit attempt, and the association is mitigated in smokers using bupropion.

Implications of genome wide association studies for addiction: are our a priori assumptions all wrong?

Substantial genetic contributions to addiction vulnerability are supported by data from twin studies, linkage studies, candidate gene association studies and, more recently, Genome Wide Association Studies (GWAS). Parallel to this work, animal studies have attempted to identify the genes that may contribute to responses to addictive drugs and addiction liability, initially focusing upon genes for the targets of the major drugs of abuse. These studies identified genes/proteins that affect responses to drugs of abuse; however, this does not necessarily mean that variation in these genes contributes to the genetic component of addiction liability. One of the major problems with initial linkage and candidate gene studies was an a priori focus on the genes thought to be involved in addiction based upon the known contributions of those proteins to drug actions, making the identification of novel genes unlikely. The GWAS approach is systematic and agnostic to such a priori assumptions. From the numerous GWAS now completed several conclusions may be drawn: (1) addiction is highly polygenic; each allelic variant contributing in a small, additive fashion to addiction vulnerability; (2) unexpected, compared to our a priori assumptions, classes of genes are most important in explaining addiction vulnerability; (3) although substantial genetic heterogeneity exists, there is substantial convergence of GWAS signals on particular genes. This review traces the history of this research; from initial transgenic mouse models based upon candidate gene and linkage studies, through the progression of GWAS for addiction and nicotine cessation, to the current human and transgenic mouse studies post-GWAS.

Nicotine-induced impairments of spatial cognition and long-term potentiation in adolescent male rats

The aim of the present study was to investigate whether cognitive behavioral impairment, induced by nicotine in offspring rats, was associated with the alteration of hippocampal short-term potentiation (STP) and long-term potentiation (LTP) and to discuss the potential underlying mechanism. Young adult offspring rats were randomly divided into three groups. The groups include: control group (CC), nicotine group 1 (NC), in which their mothers received nicotine from gestational day 3 (GD3) to GD18, and nicotine group 2 (CN), in which young adult offspring rats received nicotine from postnatal day 42 (PD42) to PD56. Morris water maze (MWM) test was performed and then field excitatory postsynaptic potentials elicited by the stimulation of perforant pathway were recorded in the hippocampal dentate gyrus region. The results of the MWM test showed that learning and memory were impaired by either prenatal or postnatal nicotine exposure. In addition, it was found that there was no statistical difference of the MWM data between both nicotine treatments. In the electrophysiological test, LTP and STP were significantly inhibited in both NC and CN groups in comparison with the CC group. Notably, STP in CN group was also lower than that in the NC group. These findings suggested that both prenatal and postnatal exposure to nicotine induced learning and memory deficits, while the potential mechanism might be different from each other due to their dissimilar impairments of synaptic plasticity.

Serotonin transporter and receptor genes significantly impact nicotine dependence through genetic interactions in both European American and African American smokers

BACKGROUND

Pharmacologic studies implicate a significant role of genes encoding the serotonin transporter (SLC6A4) and the 5-HT3AB subunits HTR3A and HTR3B in nicotine dependence (ND). However, whether they are involved in ND remains largely unknown.

METHODS

Here, we examined the impact of variations in the three genes on ND in 1366 individuals from 402 African American (AA) and 671 individuals from 200 European American (EA) families. The ND of each smoker was assessed with smoking quantity (SQ), heaviness of smoking index (HSI), and Fagerström test for nicotine dependence (FTND).

RESULTS

Association analysis revealed marginal association of rs10160548 in HTR3A with SQ and HSI in AA, 5-HTTLPR in SLC6A4 with FTND in EA, and rs11606194 in HTR3B with SQ and FTND in the pooled sample. Haplotype-based association analysis revealed a few major haplotypes in HTR3A that were significantly associated with ND in the AA, EA, and pooled samples. However, none of these associations remained significant after correcting for multiple testing except for a haplotype G-C-C-T-A-T formed by SNPs rs1150226, rs1062613, rs33940208, rs1985242, rs2276302, and rs10160548 in HTR3A for the AA sample. Considering biological functions of the three genes, we examined interactive effects of variants in the three genes, which revealed significant interactions among rs1062613 and rs10160548 in HTR3A, rs1176744 in HTR3B, and 5-HTTLPR and rs1042173 in SLC6A4 in affecting ND in the three samples.

CONCLUSIONS

We conclude that SLC6A4, HTR3A and HTR3B play a significant role in ND through genetic interactions.

Depressive symptoms among heavy cigarette smokers: the influence of daily rate, gender, and race

INTRODUCTION

Cigarette smokers experience higher levels of depressive symptoms and are more likely to be diagnosed with depressive disorders than nonsmokers. To date, the nature of the smoking-depression relationship has not been adequately studied among heavy smokers, a group at elevated risk for poor health outcomes. In this study, we examined depressive symptom expression among heavy smokers while considering the moderating roles of smoking status, gender, and race. We also explored whether amount of tobacco usually consumed had an impact.

METHODS

We extracted data from a large, highly nicotine-dependent, nontreatment cigarette smoking study sample (N = 6,158). Participants who consented were screened for major exclusions, and they completed questionnaires.

RESULTS

Smokers reported a higher, clinically meaningful level of depressive symptoms relative to nonsmokers (27.3% of smokers vs. 12.5% of nonsmokers) scored above the clinical cutoff on the Center for Epidemiological Studies Depression (CES-D) scale (p < .001), which differed among race × gender subgroups. Further, amount of daily intake was inversely associated with self-report of depressive symptoms. For every 10-cigarette increment, the likelihood of scoring above the CES-D clinical cutoff decreased by 62% (p < .0001).

CONCLUSIONS

These findings improve our understanding of tobacco's influence on depressive symptom expression among heavy smokers, with implications for tailoring evidence-based tobacco treatments.

A framework to prevent and control tobacco among adolescents and children: introducing the IMPACT model

The objective of this paper is to provide a comprehensive evidence based model aimed at addressing multi-level risk factors influencing tobacco use among children and adolescents with multi-level policy and programmatic approaches in India. Evidences around effectiveness of policy and program interventions from developed and developing countries were reviewed using Pubmed, Scopus, Google Scholar and Ovid databases. This evidence was then categorized under three broad approaches: Policy level approaches (increased taxation on tobacco products, smoke-free laws in public places and work places, effective health warnings, prohibiting tobacco advertising, promotions and sponsorships, and restricting access to minors); Community level approaches (school health programs, mass media campaigns, community based interventions, promoting tobacco free norms) and Individual level approaches (promoting cessation in various settings). This review of literature around determinants and interventions was organized into developing the IMPACT framework. The paper further presents a comparative analysis of tobacco control interventions in India vis a vis the proposed approaches. Mixed results were found for prevention and control efforts targeting youth. However, this article suggests a number of intervention strategies that have shown to be effective. Implementing these interventions in a coordinated way will provide potential synergies across interventions. Pediatricians have prominent role in advocating and implementing the IMPACT framework in countries aiming to prevent and control tobacco use among adolescents and children.

Genetics of GABAergic signaling in nicotine and alcohol dependence

Both nicotine and alcohol addictions are common chronic brain disorders that are of great concern to individuals and society. Although genetics contributes significantly to these disorders, the susceptibility genes and variants underlying them remain largely unknown. Many years of genome-wide linkage and association studies have implicated a number of genes and pathways in the etiology of nicotine and alcohol addictions. In this communication, we focus on current evidence, primarily from human genetic studies, supporting the involvement of genes and variants in the GABAergic signaling system in the etiology of nicotine dependence and alcoholism based on linkage, association, and gene-by-gene interaction studies. Current efforts aim not only to replicate these findings in independent samples, but also to identify which variant contributes to the detected associations and through what molecular mechanisms.