Recently, genetic association findings for nicotine dependence, smoking behavior, and smoking-related diseases converged to implicate the chromosome 15q25.1 region, which includes the CHRNA5-CHRNA3-CHRNB4 cholinergic nicotinic receptor subunit genes. In particular, association with the nonsynonymous CHRNA5 SNP rs16969968 and correlates has been replicated in several independent studies. Extensive genotyping of this region has suggested additional statistically distinct signals for nicotine dependence, tagged by rs578776 and rs588765. One goal of the Consortium for the Genetic Analysis of Smoking Phenotypes (CGASP) is to elucidate the associations among these markers and dichotomous smoking quantity (heavy versus light smoking), lung cancer, and chronic obstructive pulmonary disease (COPD). We performed a meta-analysis across 34 datasets of European-ancestry subjects, including 38,617 smokers who were assessed for cigarettes-per-day, 7,700 lung cancer cases and 5,914 lung-cancer-free controls (all smokers), and 2,614 COPD cases and 3,568 COPD-free controls (all smokers). We demonstrate statistically independent associations of rs16969968 and rs588765 with smoking (mutually adjusted p-values<10−35 and <10−8 respectively). Because the risk alleles at these loci are negatively correlated, their association with smoking is stronger in the joint model than when each SNP is analyzed alone. Rs578776 also demonstrates association with smoking after adjustment for rs16969968 (p<10−6). In models adjusting for cigarettes-per-day, we confirm the association between rs16969968 and lung cancer (p<10−20) and observe a nominally significant association with COPD (p = 0.01); the other loci are not significantly associated with either lung cancer or COPD after adjusting for rs16969968. This study provides strong evidence that multiple statistically distinct loci in this region affect smoking behavior. This study is also the first report of association between rs588765 (and correlates) and smoking that achieves genome-wide significance; these SNPs have previously been associated with mRNA levels of CHRNA5 in brain and lung tissue.

Supplementary data are available at Bioinformatics online.

Schizophrenia (SCZ) and bipolar disorder (BPD) are severe mental disorders with high heritability. Clinicians have long noticed the similarities of clinic symptoms between these disorders. In recent years, accumulating evidence indicates some shared genetic liabilities. However, what is shared remains elusive. In this study, we conducted whole transcriptome analysis of postmortem brain tissues (cingulate cortex) from SCZ, BPD and control subjects, and identified differentially expressed genes in these disorders. We found 105 and 153 genes differentially expressed in SCZ and BPD, respectively. By comparing the t-test scores, we found that many of the genes differentially expressed in SCZ and BPD are concordant in their expression level (q ≤ 0.01, 53 genes; q ≤ 0.05, 213 genes; q ≤ 0.1, 885 genes). Using genome-wide association data from the Psychiatric Genomics Consortium, we found that these differentially and concordantly expressed genes were enriched in association signals for both SCZ (p < 10−7 ) and BPD (p = 0.029). To our knowledge, this is the first time that a substantially large number of genes shows concordant expression and association for both SCZ and BPD. Pathway analyses of these genes indicated that they are involved in the lysosome, Fc gamma receptor mediated phagocytosis, regulation of actin skeleton pathways, along with several cancer pathways. Functional analyses of these genes revealed an interconnected pathway network centered on lysosomal function and the regulation of actin cytoskeleton. These pathways and their interacting network were principally confirmed by an independent transcriptome sequencing dataset of hippocampus. Dysregulation of lysosomal function and cytoskeleton remodeling has direct impacts on endocytosis, phagocytosis, exocytosis, vesicle trafficking, neuronal maturation and migration, neurite outgrowth, and synaptic density and plasticity, and different aspects of these processes have been implicated in SCZ and BPD.

ATF3 (activating transcription factor 3) gene encodes a member of the ATF/CREB (cAMP-response-element-binding protein) family of transcription factors. Its expression is induced by a wide range of signals, including stress signals and signals that promote cell proliferation and motility. Thus the ATF3 gene can be characterized as an 'adaptive response' gene for the cells to cope with extra- and/or intra-cellular changes. In the present study, we demonstrate that the p38 signalling pathway is involved in the induction of ATF3 by stress signals. Ectopic expression of CA (constitutively active) MKK6 [MAPK (mitogen-activated protein kinase) kinase 6], a kinase upstream of p38, indicated that activation of the p38 pathway is sufficient to induce the expression of the ATF3 gene. Inhibition of the pathway indicated that the p38 pathway is necessary for various signals to induce ATF3, including anisomycin, IL-1beta (interleukin 1beta), TNFalpha (tumour necrosis factor alpha) and H2O2. Analysis of the endogenous ATF3 gene indicates that the regulation is at least in part at the transcription level. Specifically, CREB, a transcription factor known to be phosphorylated by p38, plays a role in this induction. Interestingly, the ERK (extracellular-signal-regulated kinase) and JNK (c-Jun N-terminal kinase)/SAPK (stress-activated protein kinase) signalling pathways are neither necessary nor sufficient to induce ATF3 in the anisomycin stress paradigm. Furthermore, analysis of caspase 3 activation indicated that knocking down ATF3 reduced the ability of MKK6(CA) to exert its pro-apoptotic effect. Taken together, our results indicate that a major signalling pathway, the p38 pathway, plays a critical role in the induction of ATF3 by stress signals, and that ATF3 is functionally important to mediate the pro-apoptotic effects of p38.

Nicotinic acetylcholine receptors bind to nicotine and initiate the physiological and pharmacological responses to tobacco smoking. In this report, we studied the association of α5 and α3 subunits with nicotine dependence and with the symptoms of alcohol and cannabis abuse and dependence in two independent epidemiological samples (n = 815 and 1,121, respectively). In this study, seven single nucleotide polymorphisms were genotyped in the CHRNA5 and CHRNA3 genes. In both samples, we found that the same alleles of rs16969968 (P = 0.0068 and 0.0028) and rs1051730 (P = 0.0237 and 0.0039) were significantly associated with the scores of Fagerström test for nicotine dependence (FTND). In the analyses of the symptoms of abuse/dependence of alcohol and cannabis, we found that rs16969968 and rs1051730 were significantly associated with the symptoms of alcohol abuse or dependence (P = 0.0072 and 0.0057) in the combined sample, but the associated alleles were the opposite of that of FTND. No association with cannabis abuse/ dependence was found. These results suggested that the α5 and α3 subunits play a significant role in both nicotine dependence and alcohol abuse/dependence. However, the opposite effects with nicotine dependence and alcohol abuse/dependence were puzzling and future studies are necessary to resolve this issue.

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Context Recent studies have shown an association between cigarettes per day (CPD) and a nonsynonymous single-nucleotide polymorphism in CHRNA5, rs16969968. Objective To determine whether the association between rs16969968 and smoking is modified by age at onset of regular smoking. Data Sources Primary data. Study Selection Available genetic studies containing measures of CPD and the genotype of rs16969968 or its proxy. Data Extraction Uniform statistical analysis scripts were run locally. Starting with 94 050 ever-smokers from 43 studies, we extracted the heavy smokers (CPD >20) and light smokers (CPD ≤10) with age-at-onset information, reducing the sample size to 33 348. Each study was stratified into early-onset smokers (age at onset ≤16 years) and late-onset smokers (age at onset >16 years), and a logistic regression of heavy vs light smoking with the rs16969968 genotype was computed for each stratum. Meta-analysis was performed within each age-at-onset stratum. Data Synthesis Individuals with 1 risk allele at rs16969968 who were early-onset smokers were significantly more likely to be heavy smokers in adulthood (odds ratio [OR]=1.45; 95% CI, 1.36–1.55; n=13 843) than were carriers of the risk allele who were late-onset smokers (OR = 1.27; 95% CI, 1.21–1.33, n = 19 505) (P = .01). Conclusion These results highlight an increased genetic vulnerability to smoking in early-onset smokers.

The mu1 opioid receptor gene, OPRM1, has long been a high-priority candidate for human genetic studies of addiction. Because of its potential functional significance, the non-synonymous variant rs1799971 (A118G, Asn40Asp) in OPRM1 has been extensively studied, yet its role in addiction has remained unclear, with conflicting association findings. To resolve the question of what effect, if any, rs1799971 has on substance dependence risk, we conducted collaborative meta-analyses of 25 datasets with over 28,000 European-ancestry subjects. We investigated non-specific risk for “general” substance dependence, comparing cases dependent on any substance to controls who were non-dependent on all assessed substances. We also examined five specific substance dependence diagnoses: DSM-IV alcohol, opioid, cannabis, and cocaine dependence, and nicotine dependence defined by the proxy of heavy/light smoking (cigarettes-per-day > 20 versus ≤ 10). The G allele showed a modest protective effect on general substance dependence (OR = 0.90, 95% C.I. [0.83–0.97], p-value = 0.0095, N = 16,908). We observed similar effects for each individual substance, although these were not statistically significant, likely because of reduced sample sizes. We conclude that rs1799971 contributes to mechanisms of addiction liability that are shared across different addictive substances. This project highlights the benefits of examining addictive behaviors collectively and the power of collaborative data sharing and meta-analyses.