Integrating GWASs and human protein interaction networks identifies a gene subnetwork underlying alcohol dependence

Natural allelic variation modifies acute ethanol response phenotypes in wild strains of C. elegans

BACKGROUND

Genetic variation contributes to the likelihood that an individual will develop an alcohol use disorder (AUD). Traditional laboratory studies in animal models have elucidated the molecular pharmacology of ethanol, but laboratory-derived genetic manipulations rarely model the naturally occurring genetic variation observed in wild populations. Rather, these manipulations are biased toward identifying genes of central importance in the phenotypes. Because changes in such genes can confer selective disadvantages, they are not ideal candidates for carrying AUD risk alleles in humans. We sought to exploit Caenorhabditis elegans to identify allelic variation existing in the wild that modulates ethanol response behaviors.

METHODS

We tested the acute ethanol responses of four strains recently isolated from the wild (JU1511, JU1926, JU1931, and JU1941) and 41 multiparental recombinant inbred lines (mpRILs) derived from them. We assessed locomotion at 10, 30, and 50 min on low and high ethanol concentrations. We performed principal component analyses (PCA) on the different phenotypes, tested for transgressive behavior, calculated heritability, and determined the correlations between behavioral responses.

RESULTS

We observed a range of responses to ethanol across the strains. We detected a low-concentration locomotor activation effect in some of the mpRILs not seen in the laboratory wild-type strain. PCA showed different ethanol response behaviors to be independent. We observed transgressive behavior for many of the measured phenotypes and found that multiple behaviors were uncorrelated. The average broad-sense heritability for all phenotypes was 23.2%.

CONCLUSIONS

Genetic variation significantly affects multiple acute ethanol response behaviors, many of which are independent of one another. This suggests that the genetic variation captured by these strains likely affects multiple biological mechanisms through which ethanol acts. Further study of these strains may allow these distinct mechanisms to be identified.

Structural systems biology approach delineate the functional implications of SNPs in exon junction complex interaction network

In eukaryotes, transcripts that carry premature termination codons (PTC) leading to truncated proteins are degraded by the Nonsense Mediated Decay (NMD) machinery. Missense and nonsense Single Nucleotide Polymorphisms (SNPs) in proteins belonging to Exon junction complex (EJC) and up-frameshift protein (UPF) will compromise NMD leading to the accumulation of truncated proteins in various diseases. The EJC and UPF which are involved in NMD is a good model system to study the effect of SNPs at a system level. Despite the availability of crystal structures, computational tools, and data on mutational and deletion studies, with functional implications, an integrated effort to understand the impact of SNPs at the systems level is lacking. To study the functional consequences of missense SNPs, sequence-based techniques like SIFT and PolyPhen which classify SNPs as deleterious or non-deleterious and structure-based methods like FoldX which calculate the Delta Delta G, (ddGs, ∆∆G) are used. Using FoldX, the ddG for mutations with experimentally validated functional effects is calculated and compared with those calculated for SNPs in the same protein-protein interaction interface. Further, a model is conceived to explain the functional implications of SNPs based on the effects observed for known mutants. The results are visualized in a network format. The effects of nonsense mutations are discerned by comparing with deletion mutation studies and loss of interaction in the crystal structure. The present work not only integrates genomics, proteomics, and classical genetics with 'Structural Biology' but also helps to integrate it into a 'systems-level functional network'.Communicated by Ramaswamy H. Sarma.

A Genome-Wide Association Study Reveals a BDNF-Centered Molecular Network Associated with Alcohol Dependence and Related Clinical Measures

At least 50% of factors predisposing to alcohol dependence (AD) are genetic and women affected with this disorder present with more psychiatric comorbidities, probably indicating different genetic factors involved. We aimed to run a genome-wide association study (GWAS) followed by a bioinformatic functional annotation of associated genomic regions in patients with AD and eight related clinical measures. A genome-wide significant association of rs220677 with AD (p-value = 1.33 × 10^-8 calculated with the Yates-corrected χ² test under the assumption of dominant inheritance) was discovered in female patients. Associations of AD and related clinical measures with seven other single nucleotide polymorphisms listed in previous GWASs of psychiatric and addiction traits were differently replicated in male and female patients. The bioinformatic analysis showed that regulatory elements in the eight associated linkage disequilibrium blocks define the expression of 80 protein-coding genes. Nearly 68% of these and of 120 previously published coding genes associated with alcohol phenotypes directly interact in a single network, where BDNF is the most significant hub gene. This study indicates that several genes behind the pathogenesis of AD are different in male and female patients, but implicated molecular mechanisms are functionally connected. The study also reveals a central role of BDNF in the pathogenesis of AD.

Effect of Prenatal Opioid Exposure on the Human Placental Methylome

Prenatal exposure to addictive drugs can lead to placental epigenetic modifications, but a methylome-wide evaluation of placental DNA methylation changes after prenatal opioid exposure has not yet been performed. Placental tissue samples were collected at delivery from 19 opioid-exposed and 20 unexposed control full-term pregnancies. Placental DNA methylomes were profiled using the Illumina Infinium HumanMethylationEPIC BeadChip. Differentially methylated CpG sites associated with opioid exposure were identified with a linear model using the ‘limma’ R package. To identify differentially methylated regions (DMRs) spanning multiple CpG sites, the ‘DMRcate’ R package was used. The functions of genes mapped by differentially methylated CpG sites and DMRs were further annotated using Enrichr. Differentially methylated CpGs (n = 684, unadjusted p < 0.005 and |∆β| ≥ 0.05) were mapped to 258 genes (including PLD1, MGAM, and ALCS2). Differentially methylated regions (n = 199) were located in 174 genes (including KCNMA1). Enrichment analysis of the top differentially methylated CpG sites and regions indicated disrupted epigenetic regulation of genes involved in synaptic structure, chemical synaptic transmission, and nervous system development. Our findings imply that placental epigenetic changes due to prenatal opioid exposure could result in placental dysfunction, leading to abnormal fetal brain development and the symptoms of opioid withdrawal in neonates.

Network-Based Pharmacology Study Reveals Protein Targets for Medical Benefits and Harms of Cannabinoids in Humans

This network-based pharmacology study intends to uncover the underlying mechanisms of cannabis leading to a therapeutic benefit and the pathogenesis for a wide range of diseases claimed to benefit from or be caused by the use of the cannabis plant. Cannabis contains more than 600 chemical components. Among these components, cannabinoids are well-known to have multifarious pharmacological activities. In this work, twelve cannabinoids were selected as active compounds through text mining and drug-like properties screening and used for initial protein-target prediction. The disease-associated biological functions and pathways were enriched through GO and KEGG databases. Various biological networks [i.e., protein-protein interaction, target-pathway, pathway-disease, and target-(pathway)-target interaction] were constructed, and the functional modules and essential protein targets were elucidated through the topological analyses of the networks. Our study revealed that eighteen proteins (CAT, COMT, CYP17A1, GSTA2, GSTM3, GSTP1, HMOX1, AKT1, CASP9, PLCG1, PRKCA, PRKCB, CYCS, TNF, CNR1, CNR2, CREB1, GRIN2B) are essential targets of eight cannabinoids (CBD, CBDA, Δ9-THC, CBN, CBC, CBGA, CBG, Δ8-THC), which involve in a variety of pathways resulting in beneficial and adverse effects on the human body. The molecular docking simulation confirmed that these eight cannabinoids bind to their corresponding protein targets with high binding affinities. This study generates a verifiable hypothesis of medical benefits and harms of key cannabinoids with a model which consists of multiple components, multiple targets, and multiple pathways, which provides an important foundation for further deployment of preclinical and clinical studies of cannabis.

Genome-wide association study on blood pressure traits in the Iranian population suggests ZBED9 as a new locus for hypertension

High blood pressure is the heritable risk factor for cardiovascular and kidney diseases. Genome-wide association studies(GWAS) on blood pressure traits increase our understanding of its underlying genetic basis. However, a large proportion of GWAS was conducted in Europeans, and some roadblocks deprive other populations to benefit from their results. Iranians population with a high degree of genomic specificity has not been represented in international databases to date, so to fill the gap, we explored the effects of 652,919 genomic variants on Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP), and Hypertension (HTN) in 7694 Iranian adults aged 18 and over from Tehran Cardiometabolic Genetic Study (TCGS). We identified consistent signals on ZBED9 associated with HTN in the genome-wide borderline threshold after adjusting for different sets of environmental predictors. Moreover, strong signals on ABHD17C and suggestive signals on FBN1 were detected for DBP and SBP, respectively, while these signals were not consistent in different GWA analysis. Our finding on ZBED9 was confirmed for all BP traits by linkage analysis in an independent sample. We found significant associations with similar direction of effects and allele frequency of genetic variants on ZBED9 with DBP (genome-wide threshold) and HTN (nominal threshold) in GWAS summary data of UK Biobank. Although there is no strong evidence to support the function of ZBED9 in blood pressure regulation, it provides new insight into the pleiotropic effects of hypertension and other cardiovascular diseases.

cAMP-Fyn signaling in the dorsomedial striatum direct pathway drives excessive alcohol use

Fyn kinase in the dorsomedial striatum (DMS) of rodents plays a central role in mechanisms underlying excessive alcohol intake. The DMS is comprised of medium spiny neurons (MSNs) that project directly (dMSNs) or indirectly (iMSNs) to the substantia nigra. Here, we examined the cell-type specificity of Fyn's actions in alcohol use. First, we knocked down Fyn selectively in DMS dMSNs or iMSNs of mice and measured the level of alcohol consumption. We found that downregulation of Fyn in dMSNs, but not in iMSNs, reduces excessive alcohol but not saccharin intake. D1Rs are coupled to Gαs/olf, which activate cAMP signaling. To examine whether Fyn's actions are mediated through cAMP signaling, DMS dMSNs were infected with GαsDREADD, and the activation of Fyn signaling was measured following CNO treatment. We found that remote stimulation of cAMP signaling in DMS dMSNs activates Fyn and promotes the phosphorylation of the Fyn substrate, GluN2B. In contract, remote activation of GαsDREADD in DLS dMSNs did not alter Fyn signaling. We then tested whether activation of GαsDREADD in DMS dMSNs or iMSNs alters alcohol intake and observed that CNO-dependent activation of GαsDREADD in DMS dMSNs but not iMSNs increases alcohol but not saccharin intake. Finally, we examined the contribution of Fyn to GαsDREADD-dependent increase in alcohol intake, and found that systemic administration of the Fyn inhibitor, AZD0503 blocks GαsDREADD-dependent increase in alcohol consumption. Our results suggest that the cAMP-Fyn axis in the DMS dMSNs is a molecular transducer of mechanisms underlying the development of excessive alcohol consumption.

Alcohol Sensitivity as an Endophenotype of Alcohol Use Disorder: Exploring Its Translational Utility between Rodents and Humans

Alcohol use disorder (AUD) is a complex, chronic, relapsing disorder with multiple interacting genetic and environmental influences. Numerous studies have verified the influence of genetics on AUD, yet the underlying biological pathways remain unknown. One strategy to interrogate complex diseases is the use of endophenotypes, which deconstruct current diagnostic categories into component traits that may be more amenable to genetic research. In this review, we explore how an endophenotype such as sensitivity to alcohol can be used in conjunction with rodent models to provide mechanistic insights into AUD. We evaluate three alcohol sensitivity endophenotypes (stimulation, intoxication, and aversion) for their translatability across human and rodent research by examining the underlying neurobiology and its relationship to consumption and AUD. We show examples in which results gleaned from rodents are successfully integrated with information from human studies to gain insight in the genetic underpinnings of AUD and AUD-related endophenotypes. Finally, we identify areas for future translational research that could greatly expand our knowledge of the biological and molecular aspects of the transition to AUD with the broad hope of finding better ways to treat this devastating disorder.

The Fyn kinase inhibitor, AZD0530, suppresses mouse alcohol self-administration and seeking

Fyn is a member of the Src family of protein tyrosine kinases (PTKs) that plays an important role not only in normal synaptic functions but also in brain pathologies including alcohol use disorder. We previously reported that repeated cycles of binge drinking and withdrawal activate Fyn in the dorsomedial striatum (DMS) of rodents, and that Fyn signaling in the DMS contributes to rat alcohol intake and relapse. Here, we used AZD0530, a CNS penetrable inhibitor of Src PTKs developed for the treatment of Alzheimer disease and cancer and tested its efficacy to suppress alcohol-dependent molecular and behavioral effects. We show that systemic administration of AZD0530 prevents alcohol-induced Fyn activation and GluN2B phosphorylation in the DMS of mice. We further report that a single dose of AZD0530 reduces alcohol operant self-administration and promotes extinction of alcohol self-administration without altering basal and dopamine D1 receptor-dependent locomotion. Together, our findings suggest that AZD0530, through its inhibitory actions on Fyn kinase, dampens alcohol seeking and drinking.

Altered gating of Kv1.4 in the nucleus accumbens suppresses motivation for reward

Deficient motivation contributes to numerous psychiatric disorders, including withdrawal from drug use, depression, schizophrenia, and others. Nucleus accumbens (NAc) has been implicated in motivated behavior, but it remains unclear whether motivational drive is linked to discrete neurobiological mechanisms within the NAc. To examine this, we profiled cohorts of Sprague-Dawley rats in a test of motivation to consume sucrose. We found that substantial variability in willingness to exert effort for reward was not associated with operant responding under low-effort conditions or stress levels. Instead, effort-based motivation was mirrored by a divergent NAc shell transcriptome with differential regulation at potassium and dopamine signaling genes. Functionally, motivation was inversely related to excitability of NAc principal neurons. Furthermore, neuronal and behavioral outputs associated with low motivation were linked to faster inactivation of a voltage-gated potassium channel, Kv1.4. These results raise the prospect of targeting Kv1.4 gating in psychiatric conditions associated with motivational dysfunction.

KCNMA1-linked channelopathy

Bailey et al. review a new neurological channelopathy associated with KCNMA1, encoding the BK voltage- and Ca²⁺-activated K⁺ channel.

KCNMA1 encodes the pore-forming α subunit of the “Big K⁺” (BK) large conductance calcium and voltage-activated K⁺ channel. BK channels are widely distributed across tissues, including both excitable and nonexcitable cells. Expression levels are highest in brain and muscle, where BK channels are critical regulators of neuronal excitability and muscle contractility. A global deletion in mouse (KCNMA1^−/−) is viable but exhibits pathophysiology in many organ systems. Yet despite the important roles in animal models, the consequences of dysfunctional BK channels in humans are not well characterized. Here, we summarize 16 rare KCNMA1 mutations identified in 37 patients dating back to 2005, with an array of clinically defined pathological phenotypes collectively referred to as “KCNMA1-linked channelopathy.” These mutations encompass gain-of-function (GOF) and loss-of-function (LOF) alterations in BK channel activity, as well as several variants of unknown significance (VUS). Human KCNMA1 mutations are primarily associated with neurological conditions, including seizures, movement disorders, developmental delay, and intellectual disability. Due to the recent identification of additional patients, the spectrum of symptoms associated with KCNMA1 mutations has expanded but remains primarily defined by brain and muscle dysfunction. Emerging evidence suggests the functional BK channel alterations produced by different KCNMA1 alleles may associate with semi-distinct patient symptoms, such as paroxysmal nonkinesigenic dyskinesia (PNKD) with GOF and ataxia with LOF. However, due to the de novo origins for the majority of KCNMA1 mutations identified to date and the phenotypic variability exhibited by patients, additional evidence is required to establish causality in most cases. The symptomatic picture developing from patients with KCNMA1-linked channelopathy highlights the importance of better understanding the roles BK channels play in regulating cell excitability. Establishing causality between KCNMA1-linked BK channel dysfunction and specific patient symptoms may reveal new treatment approaches with the potential to increase therapeutic efficacy over current standard regimens.

Genome-wide association study identifies loci associated with liability to alcohol and drug dependence that is associated with variability in reward-related ventral striatum activity in African- and European-Americans

Genetic influences on alcohol and drug dependence partially overlap, however, specific loci underlying this overlap remain unclear. We conducted a genome-wide association study (GWAS) of a phenotype representing alcohol or illicit drug dependence (ANYDEP) among 7291 European-Americans (EA; 2927 cases) and 3132 African-Americans (AA: 1315 cases) participating in the family-based Collaborative Study on the Genetics of Alcoholism. ANYDEP was heritable (h 2 in EA = 0.60, AA = 0.37). The AA GWAS identified three regions with genome-wide significant (GWS; P < 5E-08) single nucleotide polymorphisms (SNPs) on chromosomes 3 (rs34066662, rs58801820) and 13 (rs75168521, rs78886294), and an insertion-deletion on chromosome 5 (chr5:141988181). No polymorphisms reached GWS in the EA. One GWS region (chromosome 1: rs1890881) emerged from a trans-ancestral meta-analysis (EA + AA) of ANYDEP, and was attributable to alcohol dependence in both samples. Four genes (AA: CRKL, DZIP3, SBK3; EA: P2RX6) and four sets of genes were significantly enriched within biological pathways for hemostasis and signal transduction. GWS signals did not replicate in two independent samples but there was weak evidence for association between rs1890881 and alcohol intake in the UK Biobank. Among 118 AA and 481 EA individuals from the Duke Neurogenetics Study, rs75168521 and rs1890881 genotypes were associated with variability in reward-related ventral striatum activation. This study identified novel loci for substance dependence and provides preliminary evidence that these variants are also associated with individual differences in neural reward reactivity. Gene discovery efforts in non-European samples with distinct patterns of substance use may lead to the identification of novel ancestry-specific genetic markers of risk.

Exome-wide search and functional annotation of genes associated in patients with severe tick-borne encephalitis in a Russian population

Background

Tick-borne encephalitis (TBE) is a viral infectious disease caused by tick-borne encephalitis virus (TBEV). TBEV infection is responsible for a variety of clinical manifestations ranging from mild fever to severe neurological illness. Genetic factors involved in the host response to TBEV that may potentially play a role in the severity of the disease are still poorly understood. In this study, using whole-exome sequencing, we aimed to identify genetic variants and genes associated with severe forms of TBE as well as biological pathways through which the identified variants may influence the severity of the disease.

Results

Whole-exome sequencing data analysis was performed on 22 Russian patients with severe forms of TBE and 17 Russian individuals from the control group. We identified 2407 candidate genes harboring rare, potentially pathogenic variants in exomes of patients with TBE and not containing any rare, potentially pathogenic variants in exomes of individuals from the control group. According to DAVID tool, this set of 2407 genes was enriched with genes involved in extracellular matrix proteoglycans pathway and genes encoding proteins located at the cell periphery. A total of 154 genes/proteins from these functional groups have been shown to be involved in protein-protein interactions (PPIs) with the known candidate genes/proteins extracted from TBEVHostDB database. By ranking these genes according to the number of rare harmful minor alleles, we identified two genes (MSR1 and LMO7), harboring five minor alleles, and three genes (FLNA, PALLD, PKD1) harboring four minor alleles.

When considering genes harboring genetic variants associated with severe forms of TBE at the suggestive P-value < 0.01, 46 genes containing harmful variants were identified. Out of these 46 genes, eight (MAP4, WDFY4, ACTRT2, KLHL25, MAP2K3, MBD1, OR10J1, and OR2T34) were additionally found among genes containing rare pathogenic variants identified in patients with TBE; and five genes (WDFY4,ALK, MAP4, BNIPL, EPPK1) were found to encode proteins that are involved in PPIs with proteins encoded by genes from TBEVHostDB. Three genes out of five (MAP4, EPPK1, ALK) were found to encode proteins located at cell periphery.

Conclusions

Whole-exome sequencing followed by systems biology approach enabled to identify eight candidate genes (MAP4, WDFY4, ACTRT2, KLHL25, MAP2K3, MBD1, OR10J1, and OR2T34) that can potentially determine predisposition to severe forms of TBE. Analyses of the genetic risk factors for severe forms of TBE revealed a significant enrichment with genes controlling extracellular matrix proteoglycans pathway as well as genes encoding components of cell periphery.

Electronic supplementary material

The online version of this article (10.1186/s12920-019-0503-x) contains supplementary material, which is available to authorized users.

Genes in immune pathways associated with abnormal white matter integrity in first-episode and treatment-naïve patients with schizophrenia

BACKGROUND

Previous studies have inferred a strong genetic component in schizophrenia. However, the genetic variants involved in the susceptibility to schizophrenia remain unclear.AimsTo detect potential gene pathways and networks associated with schizophrenia, and to explore the relationship between common and rare variants in these pathways and abnormal white matter integrity in schizophrenia.

METHOD

The analysis included 100 first-episode treatment-naïve patients with schizophrenia and 140 healthy controls. A network-based analysis was carried out on the data collected from the Psychiatric Genomics Consortium Phase I (PGC-I). Based on our genome-wide association study and whole-exome sequencing data-sets, we performed a gene-set analysis to detect associations between the combining effects of common and rare genetic variants and abnormal white matter integrity in schizophrenia.

RESULTS

Patients had significantly reduced functional anisotropy in the left and right anterior cingulate cortex, left and right precuneus and extra-nuclear (t = 4.61-5.10, PFDR &lt; 0.01), compared with controls. Generated from co-expression network analysis of the PGC-1 summary statistics of schizophrenia, a subnetwork of 207 genes associated with schizophrenia was identified (P &lt; 0.01), and 176 genes were co-expressed in four gene modules. Functional enrichment analysis for genes in each module revealed that the yellow module was enriched with highly co-expressed, innate immune response genes. Furthermore, rare variants of enriched genes in the yellow module were associated with reduced functional anisotropy in the left anterior cingulate cortex (P = 0.006; Padjusted = 0.024) in patients only.

CONCLUSIONS

The pathogenesis of schizophrenia may be substantially influenced by genes involved in the immune system, via both pathway and network.Declaration of interestsNone.

Cross-species alcohol dependence-associated gene networks: Co-analysis of mouse brain gene expression and human genome-wide association data

Genome-wide association studies on alcohol dependence, by themselves, have yet to account for the estimated heritability of the disorder and provide incomplete mechanistic understanding of this complex trait. Integrating brain ethanol-responsive gene expression networks from model organisms with human genetic data on alcohol dependence could aid in identifying dependence-associated genes and functional networks in which they are involved. This study used a modification of the Edge-Weighted Dense Module Searching for genome-wide association studies (EW-dmGWAS) approach to co-analyze whole-genome gene expression data from ethanol-exposed mouse brain tissue, human protein-protein interaction databases and alcohol dependence-related genome-wide association studies. Results revealed novel ethanol-responsive and alcohol dependence-associated gene networks in prefrontal cortex, nucleus accumbens, and ventral tegmental area. Three of these networks were overrepresented with genome-wide association signals from an independent dataset. These networks were significantly overrepresented for gene ontology categories involving several mechanisms, including actin filament-based activity, transcript regulation, Wnt and Syndecan-mediated signaling, and ubiquitination. Together, these studies provide novel insight for brain mechanisms contributing to alcohol dependence.

Multivariate Analyses Reveal Biological Components Related to Neuronal Signaling and Immunity Mediating Electroencephalograms Abnormalities in Alcohol-Dependent Individuals from the Collaborative Study on the Genetics of Alcoholism Cohort

BACKGROUND

The underlying molecular mechanisms associated with alcohol use disorder (AUD) risk have only been partially revealed using traditional approaches such as univariate genomewide association and linkage-based analyses. We therefore aimed to identify gene clusters related to Electroencephalograms (EEG) neurobiological phenotypes distinctive to individuals with AUD using a multivariate approach.

METHODS

The current project adopted a bimultivariate data-driven approach, parallel independent component analysis (para-ICA), to derive and explore significant genotype-phenotype associations in a case-control subset of the Collaborative Study on the Genetics of Alcoholism (COGA) dataset. Para-ICA subjects comprised N = 799 self-reported European Americans (367 controls and 432 AUD cases), recruited from COGA, who had undergone resting EEG and genotyping. Both EEG and genomewide single nucleotide polymorphism (SNP) data were preprocessed prior to being subjected to para-ICA in order to derive genotype-phenotype relationships.

RESULTS

From the data, 4 EEG frequency and 4 SNP components were estimated, with 2 significantly correlated EEG-genetic relationship pairs. The first such pair primarily represented theta activity, negatively correlated with a genetic cluster enriched for (but not limited to) ontologies/disease processes representing cell signaling, neurogenesis, transmembrane drug transportation, alcoholism, and lipid/cholesterol metabolism. The second component pair represented mainly alpha activity, positively correlated with a genetic cluster with ontologies similarly enriched as the first component. Disease-related enrichments for this component revealed heart and autoimmune disorders as top hits. Loading coefficients for both the alpha and theta components were significantly reduced in cases compared to controls.

CONCLUSIONS

Our data suggest plausible multifactorial genetic components, primarily enriched for neuronal/synaptic signaling/transmission, immunity, and neurogenesis, mediating low-frequency alpha and theta abnormalities in alcohol addiction.

Beyond genome-wide significance: integrative approaches to the interpretation and extension of GWAS findings for alcohol use disorder

Alcohol use disorder (AUD) is a heritable complex behavior. Due to the highly polygenic nature of AUD, identifying genetic variants that comprise this heritable variation has proved to be challenging. With the exception of functional variants in alcohol metabolizing genes (e.g. ADH1B and ALDH2), few other candidate loci have been confidently linked to AUD. Genome-wide association studies (GWAS) of AUD and other alcohol-related phenotypes have either produced few hits with genome-wide significance or have failed to replicate on further study. These issues reinforce the complex nature of the genetic underpinnings for AUD and suggest that both GWAS studies with larger samples and additional analysis approaches that better harness the nominally significant loci in existing GWAS are needed. Here, we review approaches of interest in the post-GWAS era, including in silico functional analyses; functional partitioning of single nucleotide polymorphism heritability; aggregation of signal into genes and gene networks; and validation of identified loci, genes and gene networks in postmortem brain tissue and across species. These integrative approaches hold promise to illuminate our understanding of the biological basis of AUD; however, we recognize that the main challenge continues to be the extremely polygenic nature of AUD, which necessitates large samples to identify multiple loci associated with AUD liability.

Common and Rare Genetic Risk Factors Converge in Protein Interaction Networks Underlying Schizophrenia

Hundreds of genomic loci have been identified with the recent advances of schizophrenia in genome-wide association studies (GWAS) and sequencing studies. However, the functional interactions among those genes remain largely unknown. We developed a network-based approach to integrate multiple genetic risk factors, which lead to the discovery of new susceptibility genes and causal sub-networks, or pathways in schizophrenia. We identified significantly and consistently over-represented pathways in the largest schizophrenia GWA studies, which are highly relevant to synaptic plasticity, neural development and signaling transduction, such as long-term potentiation, neurotrophin signaling pathway, and the ERBB signaling pathway. We also demonstrated that genes targeted by common SNPs are more likely to interact with genes harboring de novo mutations (DNMs) in the protein-protein interaction (PPI) network, suggesting a mutual interplay of both common and rare variants in schizophrenia. We further developed an edge-based search algorithm to identify the top-ranked gene modules associated with schizophrenia risk. Our results suggest that the N-methyl-D-aspartate receptor (NMDAR) interactome may play a leading role in the pathology of schizophrenia, as it is highly targeted by multiple types of genetic risk factors.

Distinct Roles for Two Chromosome 1 Loci in Ethanol Withdrawal, Consumption, and Conditioned Place Preference

We previously identified a region on chromosome 1 that harbor quantitative trait loci (QTLs) with large effects on alcohol withdrawal risk using both chronic and acute models in mice. Here, using newly created and existing QTL interval-specific congenic (ISC) models, we report the first evidence that this region harbors two distinct alcohol withdrawal QTLs (Alcw1₁and Alcw1₂), which underlie 13% and 3–6%, respectively, of the genetic variance in alcohol withdrawal severity measured using the handling-induced convulsion. Our results also precisely localize Alcw1₁ and Alcw1₂ to discreet chromosome regions (syntenic with human 1q23.1–23.3) that encompass a limited number of genes with validated genotype-dependent transcript expression and/or non-synonymous sequence variation that may underlie QTL phenotypic effects. ISC analyses also implicate Alcw1₁and Alcw1₂ in withdrawal-induced anxiety-like behavior, representing the first evidence for their broader roles in alcohol withdrawal beyond convulsions; but detect no evidence for Alcw1₂ involvement in ethanol conditioned place preference (CPP) or consumption. Our data point to high-quality candidates for Alcw1₂, including genes involved in mitochondrial respiration, spatial buffering, and neural plasticity, and to Kcnj9 as a high-quality candidate for Alcw1₁. Our studies are the first to show, using two null mutant models on different genetic backgrounds, that Kcnj9^−/− mice demonstrate significantly less severe alcohol withdrawal than wildtype littermates using acute and repeated exposure paradigms. We also demonstrate that Kcnj9^−/− voluntarily consume significantly more alcohol (20%, two-bottle choice) than wildtype littermates. Taken together with evidence implicating Kcnj9 in ethanol CPP, our results support a broad role for this locus in ethanol reward and withdrawal phenotypes. In summary, our results demonstrate two distinct chromosome 1 QTLs that significantly affect risk for ethanol withdrawal, and point to their distinct unique roles in alcohol reward phenotypes.

Targeting the intracellular signaling "STOP" and "GO" pathways for the treatment of alcohol use disorders

In recent years, research has identified the molecular and neural substrates underlying the transition of moderate "social" consumption of alcohol to the characteristic alcohol use disorder (AUD) phenotypes including excessive and compulsive alcohol use which we define in the review as the GO signaling pathways. In addition, growing evidence points to the existence of molecular mechanisms that keep alcohol consumption in check and that confer resilience for the development of AUD which we define herein as the STOP signaling pathways. In this review, we focus on examples of the GO and the STOP intracellular signaling pathways and discuss our current knowledge of how manipulations of these pathways may be used for the treatment of AUD.

An association study revealed substantial effects of dominance, epistasis and substance dependence co-morbidity on alcohol dependence symptom count

Alcohol dependence is a complex disease involving polygenes, environment and their interactions. Inadequate consideration of these interactions may have hampered the progress on genome-wide association studies of alcohol dependence. By using the dataset of the Study of Addiction: Genetics and Environment with 3838 subjects, we conducted a genome-wide association studies of alcohol dependence symptom count (ADSC) with a full genetic model considering additive, dominance, epistasis and their interactions with ethnicity, as well as conditions of co-morbid substance dependence. Twenty quantitative trait single nucleotide polymorphisms (QTSs) showed highly significant associations with ADSC, including four previously reported genes (ADH1C, PKNOX2, CPE and KCNB2) and the reported intergenic rs1363605, supporting the overall validity of the analysis. Two QTSs within or near ADH1C showed very strong association in a dominance inheritance mode and increased the phenotype value of ADSC when the effect of co-morbid opiate or marijuana dependence was controlled. Highly significant association was also identified in variants within four novel genes (RGS6, FMN1, NRM and BPTF), two non-coding RNA and two epistasis loci. QTS rs7616413, located near PTPRG encoding a protein tyrosine phosphatase receptor, interacted with rs10090742 within ANGPT1 encoding a protein tyrosine phosphatase in an additive × additive or dominance × additive manner. The detected QTSs contributed to about 20 percent of total heritability, in which dominance and epistasis effects accounted for over 50 percent. These results demonstrated that perturbations arising from gene-gene interaction and conditions of co-morbidity substantially influence the genetic architecture of complex trait.

A novel network analysis approach reveals DNA damage, oxidative stress and calcium/cAMP homeostasis-associated biomarkers in frontotemporal dementia

Frontotemporal Dementia (FTD) is the form of neurodegenerative dementia with the highest prevalence after Alzheimer’s disease, equally distributed in men and women. It includes several variants, generally characterized by behavioural instability and language impairments. Although few mendelian genes (MAPT, GRN, and C9orf72) have been associated to the FTD phenotype, in most cases there is only evidence of multiple risk loci with relatively small effect size. To date, there are no comprehensive studies describing FTD at molecular level, highlighting possible genetic interactions and signalling pathways at the origin FTD-associated neurodegeneration. In this study, we designed a broad FTD genetic interaction map of the Italian population, through a novel network-based approach modelled on the concepts of disease-relevance and interaction perturbation, combining Steiner tree search and Structural Equation Model (SEM) analysis. Our results show a strong connection between Calcium/cAMP metabolism, oxidative stress-induced Serine/Threonine kinases activation, and postsynaptic membrane potentiation, suggesting a possible combination of neuronal damage and loss of neuroprotection, leading to cell death. In our model, Calcium/cAMP homeostasis and energetic metabolism impairments are primary causes of loss of neuroprotection and neural cell damage, respectively. Secondly, the altered postsynaptic membrane potentiation, due to the activation of stress-induced Serine/Threonine kinases, leads to neurodegeneration. Our study investigates the molecular underpinnings of these processes, evidencing key genes and gene interactions that may account for a significant fraction of unexplained FTD aetiology. We emphasized the key molecular actors in these processes, proposing them as novel FTD biomarkers that could be crucial for further epidemiological and molecular studies.

Jumping across biomedical contexts using compressive data fusion

Motivation: The rapid growth of diverse biological data allows us to consider interactions between a variety of objects, such as genes, chemicals, molecular signatures, diseases, pathways and environmental exposures. Often, any pair of objects—such as a gene and a disease—can be related in different ways, for example, directly via gene–disease associations or indirectly via functional annotations, chemicals and pathways. Different ways of relating these objects carry different semantic meanings. However, traditional methods disregard these semantics and thus cannot fully exploit their value in data modeling.

Results: We present Medusa, an approach to detect size-k modules of objects that, taken together, appear most significant to another set of objects. Medusa operates on large-scale collections of heterogeneous datasets and explicitly distinguishes between diverse data semantics. It advances research along two dimensions: it builds on collective matrix factorization to derive different semantics, and it formulates the growing of the modules as a submodular optimization program. Medusa is flexible in choosing or combining semantic meanings and provides theoretical guarantees about detection quality. In a systematic study on 310 complex diseases, we show the effectiveness of Medusa in associating genes with diseases and detecting disease modules. We demonstrate that in predicting gene–disease associations Medusa compares favorably to methods that ignore diverse semantic meanings. We find that the utility of different semantics depends on disease categories and that, overall, Medusa recovers disease modules more accurately when combining different semantics.

Availability and implementation: Source code is at http://github.com/marinkaz/medusa

Contact:marinka@cs.stanford.edu, blaz.zupan@fri.uni-lj.si

Network-assisted analysis of GWAS data identifies a functionally-relevant gene module for childhood-onset asthma

The number of genetic factors associated with asthma remains limited. To identify new genes with an undetected individual effect but collectively influencing asthma risk, we conducted a network-assisted analysis that integrates outcomes of genome-wide association studies (GWAS) and protein-protein interaction networks. We used two GWAS datasets, each consisting of the results of a meta-analysis of nine childhood-onset asthma GWASs (5,924 and 6,043 subjects, respectively). We developed a novel method to compute gene-level P-values (fastCGP), and proposed a parallel dense-module search and cross-selection strategy to identify an asthma-associated gene module. We identified a module of 91 genes with a significant joint effect on childhood-onset asthma (P < 10⁻⁵). This module contained a core subnetwork including genes at known asthma loci and five peripheral subnetworks including relevant candidates. Notably, the core genes were connected to APP (encoding amyloid beta precursor protein), a major player in Alzheimer’s disease that is known to have immune and inflammatory components. Functional analysis of the module genes revealed four gene clusters involved in innate and adaptive immunity, chemotaxis, cell-adhesion and transcription regulation, which are biologically meaningful processes that may underlie asthma risk. Our findings provide important clues for future research into asthma aetiology.

Alcohol-dependent molecular adaptations of the NMDA receptor system

Phenotypes such as motivation to consume alcohol, goal-directed alcohol seeking and habit formation take part in mechanisms underlying heavy alcohol use. Learning and memory processes greatly contribute to the establishment and maintenance of these behavioral phenotypes. The N-methyl-d-aspartate receptor (NMDAR) is a driving force of synaptic plasticity, a key cellular hallmark of learning and memory. Here, we describe data in rodents and humans linking signaling molecules that center around the NMDARs, and behaviors associated with the development and/or maintenance of alcohol use disorder (AUD). Specifically, we show that enzymes that participate in the regulation of NMDAR function including Fyn kinase as well as signaling cascades downstream of NMDAR including calcium/calmodulin-dependent protein kinase II (CamKII), the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) and the mammalian target of rapamycin complex 1 (mTORC1) play a major role in mechanisms underlying alcohol drinking behaviors. Finally, we emphasize the brain region specificity of alcohol's actions on the above-mentioned signaling pathways and attempt to bridge the gap between the molecular signaling that drive learning and memory processes and alcohol-dependent behavioral phenotypes. Finally, we present data to suggest that genes related to NMDAR signaling may be AUD risk factors.

Voltage-Sensitive Potassium Channels of the BK Type and Their Coding Genes Are Alcohol Targets in Neurons

Among all members of the voltage-gated, TM6 ion channel superfamily, the proteins that constitute calcium- and voltage-gated potassium channels of large conductance (BK) and their coding genes are unique for their involvement in ethanol-induced disruption of normal physiology and behavior. Moreover, in vitro studies document that BK activity is modified by ethanol with an EC₅₀~23 mM, which is near blood alcohol levels considered legal intoxication in most states of the USA (0.08 g/dL = 17.4 mM). Following a succinct introduction to our current understanding of BK structure and function in central neurons, with a focus on neural circuits that contribute to the neurobiology of alcohol use disorders (AUD), we review the modifications in organ physiology by alcohol exposure via BK and the different molecular elements that determine the ethanol response of BK in alcohol-naïve systems, including the role of an ethanol-recognizing site in the BK-forming slo1 protein, modulation of accessory BK subunits, and their coding genes. The participation of these and additional elements in determining the response of a system or an organism to protracted ethanol exposure is consequently analyzed, with insights obtained from invertebrate and vertebrate models. Particular emphasis is put on the role of BK and coding genes in different forms of tolerance to alcohol exposure. We finally discuss genetic results on BK obtained in invertebrate organisms and rodents in light of possible extrapolation to human AUD.

Genome-wide association studies and gene expression profiles of rheumatoid arthritis: An analysis

OBJECTIVES

The molecular mechanism of rheumatoid arthritis (RA) remains elusive. We conducted a protein-protein interaction network-based integrative analysis of genome-wide association studies (GWAS) and gene expression profiles of RA.

METHODS

We first performed a dense search of RA-associated gene modules by integrating a large GWAS meta-analysis dataset (containing 5539 RA patients and 20 169 healthy controls), protein interaction network and gene expression profiles of RA synovium and peripheral blood mononuclear cells (PBMCs). Gene ontology (GO) enrichment analysis was conducted by DAVID. The protein association networks of gene modules were generated by STRING.

RESULTS

For RA synovium, the top-ranked gene module is HLA-A, containing TAP2, HLA-A, HLA-C, TAPBP and LILRB1 genes. For RA PBMCs, the top-ranked gene module is GRB7, consisting of HLA-DRB5, HLA-DRA, GRB7, CD63 and KIT genes. Functional enrichment analysis identified three significant GO terms for RA synovium, including antigen processing and presentation of peptide antigen via major histocompatibility complex class I (false discovery rate (FDR) = 4.86 × 10 - 4), antigen processing and presentation of peptide antigen (FDR = 2.33 × 10 - 3) and eukaryotic translation initiation factor 4F complex (FDR = 2.52 × 10 - 2).

CONCLUSION

This study reported several RA-associated gene modules and their functional association networks.Cite this article: X. Xiao, J. Hao, Y. Wen, W. Wang, X. Guo, F. Zhang. Genome-wide association studies and gene expression profiles of rheumatoid arthritis: an analysis. Bone Joint Res 2016;5:314-319. DOI: 10.1302/2046-3758.57.2000502.

BK Channels in the Central Nervous System

Large conductance Ca(2+)- and voltage-activated K(+) (BK) channels are widely distributed in the postnatal central nervous system (CNS). BK channels play a pleiotropic role in regulating the activity of brain and spinal cord neural circuits by providing a negative feedback mechanism for local increases in intracellular Ca(2+) concentrations. In neurons, they regulate the timing and duration of K(+) influx such that they can either increase or decrease firing depending on the cellular context, and they can suppress neurotransmitter release from presynaptic terminals. In addition, BK channels located in astrocytes and arterial myocytes modulate cerebral blood flow. Not surprisingly, both loss and gain of BK channel function have been associated with CNS disorders such as epilepsy, ataxia, mental retardation, and chronic pain. On the other hand, the neuroprotective role played by BK channels in a number of pathological situations could potentially be leveraged to correct neurological dysfunction.

AGGrEGATOr: A Gene-based GEne-Gene interActTiOn test for case-control association studies

Among the large of number of statistical methods that have been proposed to identify gene-gene interactions in case-control genome-wide association studies (GWAS), gene-based methods have recently grown in popularity as they confer advantage in both statistical power and biological interpretation. All of the gene-based methods jointly model the distribution of single nucleotide polymorphisms (SNPs) sets prior to the statistical test, leading to a limited power to detect sums of SNP-SNP signals. In this paper, we instead propose a gene-based method that first performs SNP-SNP interaction tests before aggregating the obtained p-values into a test at the gene level. Our method called AGGrEGATOr is based on a minP procedure that tests the significance of the minimum of a set of p-values. We use simulations to assess the capacity of AGGrEGATOr to correctly control for type-I error. The benefits of our approach in terms of statistical power and robustness to SNPs set characteristics are evaluated in a wide range of disease models by comparing it to previous methods. We also apply our method to detect gene pairs associated to rheumatoid arthritis (RA) on the GSE39428 dataset. We identify 13 potential gene-gene interactions and replicate one gene pair in the Wellcome Trust Case Control Consortium dataset at the level of 5%. We further test 15 gene pairs, previously reported as being statistically associated with RA or Crohn's disease (CD) or coronary artery disease (CAD), for replication in the Wellcome Trust Case Control Consortium dataset. We show that AGGrEGATOr is the only method able to successfully replicate seven gene pairs.

Network-assisted analysis of primary Sjögren's syndrome GWAS data in Han Chinese

Primary Sjögren's syndrome (pSS) is a complex autoimmune disorder. So far, genetic research in pSS has lagged far behind and the underlying biological mechanism is unclear. Further exploring existing genome-wide association study (GWAS) data is urgently expected to uncover disease-related gene combination patterns. Herein, we conducted a network-based analysis by integrating pSS GWAS in Han Chinese with a protein-protein interactions network to identify pSS candidate genes. After module detection and evaluation, 8 dense modules covering 40 genes were obtained for further functional annotation. Additional 31 MHC genes with significant gene-level P-values (sigMHC-gene) were also remained. The combined module genes and sigMHC-genes, a total of 71 genes, were denoted as pSS candidate genes. Of these pSS candidates, 14 genes had been reported to be associated with any of pSS, RA, and SLE, including STAT4, GTF2I, HLA-DPB1, HLA-DRB1, PTTG1, HLA-DQB1, MBL2, TAP2, CFLAR, NFKBIE, HLA-DRA, APOM, HLA-DQA2 and NOTCH4. This is the first report of the network-assisted analysis for pSS GWAS data to explore combined gene patterns associated with pSS. Our study suggests that network-assisted analysis is a useful approach to gaining further insights into the biology of associated genes and providing important clues for future research into pSS etiology.

Applying the new genomics to alcohol dependence

This review summarizes the proceedings of a symposium presented at the "Alcoholism and Stress: A Framework for Future Treatment Strategies" conference held in Volterra, Italy on May 6-9, 2014. The overall goal of the symposium titled "Applying the New Genomics to Alcohol Dependence", chaired by Dr. Adron Harris, was to highlight recent genomic discoveries and applications for profiling alcohol use disorder (AUD). Dr. Sean Farris discussed the gene expression networks related to lifetime consumption of alcohol within human prefrontal cortex. Dr. Andrzej Pietrzykowski presented the effects of alcohol on microRNAs in humans and animal models. Alcohol-induced alterations in the synaptic transcriptome were discussed by Dr. Michael Miles. Dr. Pietro Sanna examined methods to probe the gene regulatory networks that drive excessive alcohol drinking, and Dr. Samir Zakhari served as a panel discussant and summarized the proceedings. Collectively, the presentations emphasized the power of integrating multiple levels of genetics and transcriptomics with convergent biological processes and phenotypic behaviors to determine causal factors of AUD. The combined use of diverse data types demonstrates how unique approaches and applications can help categorize genetic complexities into relevant biological networks using a systems-level model of disease.

BK Channel β1 Subunit Contributes to Behavioral Adaptations Elicited by Chronic Intermittent Ethanol Exposure

BACKGROUND

Large conductance, calcium- and voltage-activated potassium (BK) channels regulate neuronal excitability and neurotransmission. They can be directly activated by ethanol (EtOH) and they may be implicated in EtOH dependence. In this study, we sought to determine the influence of the auxiliary β1 and β4 subunits on EtOH metabolism, acute sensitivity to EtOH intoxication, acute functional tolerance, chronic tolerance, and handling-induced convulsions during withdrawal.

METHODS

Motor coordination, righting reflex, and body temperature were evaluated in BK β1 and β4 knockout, heterozygous, and wild-type mice following acute EtOH administration. Chronic tolerance and physical dependence were induced by chronic intermittent inhalation of EtOH vapor.

RESULTS

Constitutive deficiency in BK β1 or β4 subunits did not alter the clearance rate of EtOH, acute sensitivity to EtOH-induced ataxia, sedation, and hypothermia, nor acute functional tolerance to ataxia. BK β1 deletion reduced chronic tolerance to sedation and abolished chronic tolerance to hypothermia, while BK β4 deletion did not affect these adaptations to chronic EtOH exposure. Finally, the absence of BK β1 accelerated the appearance, while the absence of BK β4 delayed the resolution, of the hyperexcitable state associated with EtOH withdrawal.

CONCLUSIONS

Altogether, the present findings reveal the critical role of BK β1 in behavioral adaptations to prolonged, repeated EtOH intoxication.

A genome-wide association study confirms PNPLA3 and identifies TM6SF2 and MBOAT7 as risk loci for alcohol-related cirrhosis

Alcohol misuse is the leading cause of cirrhosis and the second most common indication for liver transplantation in the Western world. We performed a genome-wide association study for alcohol-related cirrhosis in individuals of European descent (712 cases and 1,426 controls) with subsequent validation in two independent European cohorts (1,148 cases and 922 controls). We identified variants in the MBOAT7 (P = 1.03 × 10(-9)) and TM6SF2 (P = 7.89 × 10(-10)) genes as new risk loci and confirmed rs738409 in PNPLA3 as an important risk locus for alcohol-related cirrhosis (P = 1.54 × 10(-48)) at a genome-wide level of significance. These three loci have a role in lipid processing, suggesting that lipid turnover is important in the pathogenesis of alcohol-related cirrhosis.

Dissecting ancestry genomic background in substance dependence genome-wide association studies

AIMS

To understand the role of ancestral genomic background in substance dependence (SD) genome-wide association studies (GWAS), we analyzed population diversity at genetic loci associated with SD traits and evaluated its effect on GWAS outcomes.

MATERIALS & METHODS

We investigated 24 genes with variants associated with SD by GWAS; and 82 loci with putative subordinate roles with respect to SD-associated genes.

RESULTS

We observed high ancestry-related frequency differences in common functional alleles in GWAS relevant genes and their interactive partners. Common functional alleles with high frequency differences demonstrated significant effects on the GWAS outcomes.

CONCLUSION

Population differences in SD GWAS outcomes seem not to be influenced by general variation across the genome, but by ancestry-related local haplotype structures at SD-associated loci.

Premorbid risk factors for major depressive disorder: are they associated with early onset and recurrent course?

Premorbid risk for major depressive disorder (MDD) and predictors of an earlier onset and recurrent course were examined in two studies in a large, community-based sample of parents and offspring, prospectively assessed from late childhood into adulthood. In Study 1 (N = 2,764 offspring and their parents), parental psychiatric status, offspring personality at age 11, and age 11 offspring internalizing and externalizing symptoms predicted the subsequent development of MDD, as did poor quality parent-child relationships, poor academic functioning, early pubertal development, and childhood maltreatment by age 11. Parental MDD and adult antisocial behavior, offspring negative emotionality and disconstraint, externalizing symptoms, and childhood maltreatment predicted an earlier onset of MDD, after accounting for course; lower positive emotionality, trait anxiety, and childhood maltreatment predicted recurrent MDD, after accounting for age of onset. In Study 2 (N = 7,146), we examined molecular genetic risk for MDD by extending recent reports of associations with glutamatergic system genes. We failed to confirm associations with MDD using either individual single nucleotide polymorphism based tests or gene-based analyses. Overall, results speak to the pervasiveness of risk for MDD, as well as specific risk for early onset MDD; risk for recurrent MDD appears to be largely a function of its often earlier onset.

Alcohol Dependence Genetics: Lessons Learned From Genome-Wide Association Studies (GWAS) and Post-GWAS Analyses

BACKGROUND

Alcohol dependence (AD) is a complex psychiatric disorder and a significant public health problem. Twin and family-based studies have consistently estimated its heritability to be approximately 50%, and many studies have sought to identify specific genetic variants associated with susceptibility to AD. These studies have been primarily linkage or candidate gene based and have been mostly unsuccessful in identifying replicable risk loci. Genome-wide association studies (GWAS) have improved the detection of specific loci associated with complex traits, including AD. However, findings from GWAS explain only a small proportion of phenotypic variance, and alternative methods have been proposed to investigate the associations that do not meet strict genome-wide significance criteria.

METHODS

This review summarizes all published AD GWAS and post-GWAS analyses that have sought to exploit GWAS data to identify AD-associated loci.

RESULTS

Findings from AD GWAS have been largely inconsistent, with the exception of variants encoding the alcohol-metabolizing enzymes. Analyses of GWAS data that go beyond standard association testing have demonstrated the polygenic nature of AD and the large contribution of common variants to risk, nominating novel genes and pathways for AD susceptibility.

CONCLUSIONS

Findings from AD GWAS and post-GWAS analyses have greatly increased our understanding of the genetic etiology of AD. However, it is clear that larger samples will be necessary to detect loci in addition to those that encode alcohol-metabolizing enzymes, which may only be possible through consortium-based efforts. Post-GWAS approaches to studying the genetic influences on AD are increasingly common and could greatly increase our knowledge of both the genetic architecture of AD and the specific genes and pathways that influence risk.

Gene network analysis shows immune-signaling and ERK1/2 as novel genetic markers for multiple addiction phenotypes: alcohol, smoking and opioid addiction

Background

Addictions to alcohol and tobacco, known risk factors for cancer, are complex heritable disorders. Addictive behaviors have a bidirectional relationship with pain. We hypothesize that the associations between alcohol, smoking, and opioid addiction observed in cancer patients have a genetic basis. Therefore, using bioinformatics tools, we explored the underlying genetic basis and identified new candidate genes and common biological pathways for smoking, alcohol, and opioid addiction.

Results

Literature search showed 56 genes associated with alcohol, smoking and opioid addiction. Using Core Analysis function in Ingenuity Pathway Analysis software, we found that ERK1/2 was strongly interconnected across all three addiction networks. Genes involved in immune signaling pathways were shown across all three networks. Connect function from IPA My Pathway toolbox showed that DRD2 is the gene common to both the list of genetic variations associated with all three addiction phenotypes and the components of the brain neuronal signaling network involved in substance addiction. The top canonical pathways associated with the 56 genes were: 1) calcium signaling, 2) GPCR signaling, 3) cAMP-mediated signaling, 4) GABA receptor signaling, and 5) G-alpha i signaling.

Conlusions

Cancer patients are often prescribed opioids for cancer pain thus increasing their risk for opioid abuse and addiction. Our findings provide candidate genes and biological pathways underlying addiction phenotypes, which may be future targets for treatment of addiction. Further study of the variations of the candidate genes could allow physicians to make more informed decisions when treating cancer pain with opioid analgesics.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-015-0167-x) contains supplementary material, which is available to authorized users.

Pharmacotherapy for alcohol dependence: A stratified approach

Alcohol dependence is a common disorder in many societies worldwide, and remains difficult to identify and treat. It is also a risk factor for many secondary non-communicable diseases. Pharmacotherapy is one available treatment option, but appears to be underutilised in practice. Major barriers to use of medications in this area include lack of clinical guidance and questionable efficacy. However, for each medication there appears to be a subpopulation that responds positively, and understanding the moderating factors to treatment efficacy is an important research goal. Thus, this review provides a narrative regarding potential stratification techniques in pharmacological treatment of alcohol dependence, with a specific focus on typologies and pharmacogenetics. In addition, we discuss the basic background of stratified medicine and recent studies on genetic predisposition to alcohol dependence. A growing repository of data exists for both approved and non-approved pharmacotherapies, but failure to replicate findings, inadequate sample sizes, and insufficient funding has resulted in a translational gap. Implementing evidence-based stratified/personalised therapy and identifying new therapeutic agents may lead to improved clinical outcomes and reduced financial burden. Despite some promising findings to date, much work is still required.

An inexpensive, scalable behavioral assay for measuring ethanol sedation sensitivity and rapid tolerance in Drosophila

Alcohol use disorder (AUD) is a serious health challenge. Despite a large hereditary component to AUD, few genes have been unambiguously implicated in their etiology. The fruit fly, Drosophila melanogaster, is a powerful model for exploring molecular-genetic mechanisms underlying alcohol-related behaviors and therefore holds great promise for identifying and understanding the function of genes that influence AUD. The use of the Drosophila model for these types of studies depends on the availability of assays that reliably measure behavioral responses to ethanol. This report describes an assay suitable for assessing ethanol sensitivity and rapid tolerance in flies. Ethanol sensitivity measured in this assay is influenced by the volume and concentration of ethanol used, a variety of previously reported genetic manipulations, and also the length of time the flies are housed without food immediately prior to testing. In contrast, ethanol sensitivity measured in this assay is not affected by the vigor of fly handling, sex of the flies, and supplementation of growth medium with antibiotics or live yeast. Three different methods for quantitating ethanol sensitivity are described, all leading to essentially indistinguishable ethanol sensitivity results. The scalable nature of this assay, combined with its overall simplicity to set-up and relatively low expense, make it suitable for small and large scale genetic analysis of ethanol sensitivity and rapid tolerance in Drosophila.

An Assay for Measuring the Effects of Ethanol on the Locomotion Speed of Caenorhabditis elegans

Alcohol use disorders are a significant public health concern, for which there are few effective treatment strategies. One difficulty that has delayed the development of more effective treatments is the relative lack of understanding of the molecular underpinnings of the effects of ethanol on behavior. The nematode, Caenorhabditis elegans (C. elegans), provides a useful model in which to generate and test hypotheses about the molecular effects of ethanol. Here, we describe an assay that has been developed and used to examine the roles of particular genes and environmental factors in behavioral responses to ethanol, in which locomotion is the behavioral output. Ethanol dose-dependently causes an acute depression of crawling on an agar surface. The effects are dynamic; animals exposed to a high concentration demonstrate an initial strong depression of crawling, referred to here as initial sensitivity, and then partially recover locomotion speed despite the continued presence of the drug. This ethanol-induced behavioral plasticity is referred to here as the development of acute functional tolerance. This assay has been used to demonstrate that these two phenotypes are distinct and genetically separable. The straightforward locomotion assay described here is suitable for examining the effects of both genetic and environmental manipulations on these acute behavioral responses to ethanol in C. elegans.

Genomic influences on alcohol problems in a population-based sample of young adults

AIMS

Alcohol problems (AP) contribute substantially to the global disease burden. Twin and family studies suggest that AP are genetically influenced, although few studies have identified variants or genes that are robustly associated with risk. This study identifies genetic and genomic influences on AP during young adulthood, which is often when drinking habits are established.

DESIGN

We conducted a genome-wide association study of AP. We further conducted gene-based tests, gene ontology analyses and functional genomic enrichment analyses to assess genomic factors beyond single variants that are relevant to AP.

SETTING

The Avon Longitudinal Study of Parents and Children, a large population-based study of a UK birth cohort.

PARTICIPANTS

Genetic and phenotypical data were available for 4304 participants.

MEASUREMENTS

The AP phenotype was a factor score derived from items from the Alcohol Use Disorders Identification Test, symptoms of DSM-IV alcohol dependence, and three additional problem-related items.

FINDINGS

One variant met genome-wide significance criteria. Four out of 22,880 genes subjected to gene-based analyses survived a stringent significance threshold (q < 0.05); none of these have been implicated previously in alcohol-related phenotypes. Several biologically plausible gene ontologies were statistically over-represented among implicated single nucleotide polymorphisms (SNPs). SNPs on the Illumina 550 K SNP chip accounted for ~5% of the phenotypical variance in AP.

CONCLUSIONS

Genetic and genomic factors appear to play a role in alcohol problems in young adults. Genes involved in nervous system-related processes, such as signal transduction and neurogenesis, potentially contribute to liability to alcohol problems, as do genes expressed in non-brain tissues.

XRCC5 as a risk gene for alcohol dependence: evidence from a genome-wide gene-set-based analysis and follow-up studies in Drosophila and humans

Genetic factors have as large role as environmental factors in the etiology of alcohol dependence (AD). Although genome-wide association studies (GWAS) enable systematic searches for loci not hitherto implicated in the etiology of AD, many true findings may be missed owing to correction for multiple testing. The aim of the present study was to circumvent this limitation by searching for biological system-level differences, and then following up these findings in humans and animals. Gene-set-based analysis of GWAS data from 1333 cases and 2168 controls identified 19 significantly associated gene-sets, of which 5 could be replicated in an independent sample. Clustered in these gene-sets were novel and previously identified susceptibility genes. The most frequently present gene, ie in 6 out of 19 gene-sets, was X-ray repair complementing defective repair in Chinese hamster cells 5 (XRCC5). Previous human and animal studies have implicated XRCC5 in alcohol sensitivity. This phenotype is inversely correlated with the development of AD, presumably as more alcohol is required to achieve the desired effects. In the present study, the functional role of XRCC5 in AD was further validated in animals and humans. Drosophila mutants with reduced function of Ku80-the homolog of mammalian XRCC5-due to RNAi silencing showed reduced sensitivity to ethanol. In humans with free access to intravenous ethanol self-administration in the laboratory, the maximum achieved blood alcohol concentration was influenced in an allele-dose-dependent manner by genetic variation in XRCC5. In conclusion, our convergent approach identified new candidates and generated independent evidence for the involvement of XRCC5 in alcohol dependence.

Translating Alcohol Research: Opportunities and Challenges

Alcohol use disorder (AUD) and its sequelae impose a major burden on the public health of the United States, and adequate long-term control of this disorder has not been achieved. Molecular and behavioral basic science research findings are providing the groundwork for understanding the mechanisms underlying AUD and have identified multiple candidate targets for ongoing clinical trials. However, the translation of basic research or clinical findings into improved therapeutic approaches for AUD must become more efficient. Translational research is a multistage process of stream-lining the movement of basic biomedical research findings into clinical research and then to the clinical target populations. This process demands efficient bidirectional communication across basic, applied, and clinical science as well as with clinical practitioners. Ongoing work suggests rapid progress is being made with an evolving translational framework within the alcohol research field. This is helped by multiple interdisciplinary collaborative research structures that have been developed to advance translational work on AUD. Moreover, the integration of systems biology approaches with collaborative clinical studies may yield novel insights for future translational success. Finally, appreciation of genetic variation in pharmacological or behavioral treatment responses and optimal communication from bench to bedside and back may strengthen the success of translational research applications to AUD.

Genetics of complex traits in psychiatry

Virtually all psychiatric traits are genetically complex. This article discusses the genetics of complex traits in psychiatry. The complexity is accounted for by numerous factors, including multiple risk alleles, epistasis, and epigenetic effects such as methylation. Risk alleles can individually be common or rare, and can include, for example, single nucleotide polymorphisms and copy number variants that are transmitted or are new mutations, and other kinds of variation. Many different kinds of variation can be important for trait risk, either together in various proportions or as different factors in different subjects. Until more recently, approaches to complex traits were limited, and consequently only a few variants, usually of individually minor effect, were identified. At the present time, a much richer armamentarium exists that includes the routine application of genome-wide association studies and next-generation high-throughput sequencing and the combination of this information with other biologically relevant information, such as expression data. We have also seen the emergence of large meta-analysis and mega-analysis consortia. These developments are extremely important for psychiatric genetics, have advanced the field substantially, and promise formidable gains in the years to come as they are applied more widely.

Selecting causal genes from genome-wide association studies via functionally coherent subnetworks

Genome-wide association (GWA) studies have linked thousands of loci to human diseases, but the causal genes and variants at these loci generally remain unknown. Although investigators typically focus on genes closest to the associated polymorphisms, the causal gene is often more distal. Reliance on published work to prioritize candidates is biased toward well-characterized genes. We describe a 'prix fixe' strategy and software that uses genome-scale shared-function networks to identify sets of mutually functionally related genes spanning multiple GWA loci. Using associations from ∼100 GWA studies covering ten cancer types, our approach outperformed the common alternative strategy in ranking known cancer genes. As more GWA loci are discovered, the strategy will have increased power to elucidate the causes of human disease.

Integrative analysis of GWASs, human protein interaction, and gene expression identified gene modules associated with BMDs

CONTEXT

To date, few systems genetics studies in the bone field have been performed. We designed our study from a systems-level perspective by integrating genome-wide association studies (GWASs), human protein-protein interaction (PPI) network, and gene expression to identify gene modules contributing to osteoporosis risk.

METHODS

First we searched for modules significantly enriched with bone mineral density (BMD)-associated genes in human PPI network by using 2 large meta-analysis GWAS datasets through a dense module search algorithm. One included 7 individual GWAS samples (Meta7). The other was from the Genetic Factors for Osteoporosis Consortium (GEFOS2). One was assigned as a discovery dataset and the other as an evaluation dataset, and vice versa.

RESULTS

In total, 42 modules and 129 modules were identified significantly in both Meta7 and GEFOS2 datasets for femoral neck and spine BMD, respectively. There were 3340 modules identified for hip BMD only in Meta7. As candidate modules, they were assessed for the biological relevance to BMD by gene set enrichment analysis in 2 expression profiles generated from circulating monocytes in subjects with low versus high BMD values. Interestingly, there were 2 modules significantly enriched in monocytes from the low BMD group in both gene expression datasets (nominal P value <.05). Two modules had 16 nonredundant genes. Functional enrichment analysis revealed that both modules were enriched for genes involved in Wnt receptor signaling and osteoblast differentiation.

CONCLUSION

We highlighted 2 modules and novel genes playing important roles in the regulation of bone mass, providing important clues for therapeutic approaches for osteoporosis.

Understanding the addiction cycle: a complex biology with distinct contributions of genotype vs. sex at each stage

Ethanol abuse can lead to addiction, brain damage and premature death. The cycle of alcohol addiction has been described as a composite consisting of three stages: intoxication, withdrawal and craving/abstinence. There is evidence for contributions of both genotype and sex to alcoholism, but an understanding of the biological underpinnings is limited. Utilizing both sexes of genetic animal models with highly divergent alcohol withdrawal severity, Withdrawal Seizure-Resistant (WSR) and Withdrawal Seizure-Prone (WSP) mice, the distinct contributions of genotype/phenotype and of sex during addiction stages on neuroadaptation were characterized. Transcriptional profiling was performed to identify expression changes as a consequence of chronic intoxication in the medial prefrontal cortex. Significant expression differences were identified on a single platform and tracked over a behaviorally relevant time course that covered each stage of alcohol addiction; i.e., after chronic intoxication, during peak withdrawal, and after a defined period of abstinence. Females were more sensitive to ethanol with higher fold expression differences. Bioinformatics showed a strong effect of sex on the data structure of expression profiles during chronic intoxication and at peak withdrawal irrespective of genetic background. However, during abstinence, differences were observed instead between the lines/phenotypes irrespective of sex. Confirmation of identified pathways showed distinct inflammatory signaling following intoxication at peak withdrawal, with a pro-inflammatory phenotype in females but overall suppression of immune signaling in males. Combined, these results suggest that each stage of the addiction cycle is influenced differentially by sex vs. genetic background and support the development of stage- and sex-specific therapies for alcohol withdrawal and the maintenance of sobriety.