Genome-wide search for replicable risk gene regions in alcohol and nicotine co-dependence

Modeling Brain Gene Expression in Alcohol Use Disorder with Genetic Animal Models

Animal genetic models have and will continue to provide important new information about the behavioral and physiological adaptations associated with alcohol use disorder (AUD). This chapter focuses on two models, ethanol preference and drinking in the dark (DID), their usefulness in interrogating brain gene expression data and the relevance of the data obtained to interpret AUD-related GWAS and TWAS studies. Both the animal and human data point to the importance for AUD of changes in synaptic transmission (particularly glutamate and GABA transmission), of changes in the extracellular matrix (specifically including collagens, cadherins and protocadherins) and of changes in neuroimmune processes. The implementation of new technologies (e.g., cell type-specific gene expression) is expected to further enhance the value of genetic animal models in understanding AUD.

Common and distinguishing genetic factors for substance use behavior and disorder: an integrated analysis of genomic and transcriptomic studies from both human and animal studies

BACKGROUND AND AIMS

Genomic and transcriptomic findings greatly broaden the biological knowledge regarding substance use. However, systematic convergence and comparison evidence of genome-wide findings is lacking for substance use. Here, we combined all the genome-wide findings from both substance use behavior and disorder (SUBD) and identified common and distinguishing genetic factors for different SUBDs.

METHODS

Systemic literature search for genome-wide association (GWAS) and RNA-seq studies of alcohol/nicotine/drug use behavior (partially meets or not reported diagnostic criteria) and alcohol use behavior and disorder (AUBD), nicotine use behavior and disorder (NUBD) and drug use behavior and disorder (DUBD) was performed using PubMed and the GWAS catalog. Drug use was focused upon cannabis, opioid, cocaine and methamphetamine use. GWAS studies required case-control or case/cohort samples. RNA-seq studies were based on brain tissues. The genes which contained significant single nucleotide polymorphism (P ≤ 1 × 10^-6 ) in GWAS and reported as significant in RNA-seq studies were extracted. Pathway enrichment was performed by using Metascape. Gene interaction networks were identified by using the Protein Interaction Network Analysis database.

RESULTS

Total SUBD-related 2910 genes were extracted from 75 GWAS studies (2 773 889 participants) and 17 RNA-seq studies. By overlapping the genes and pathways of AUBD, NUBD and DUBD, four shared genes (CACNB2, GRIN2B, PLXDC2 and PKNOX2), four shared pathways [two Gene Ontology (GO) terms of 'modulation of chemical synaptic transmission', 'regulation of trans-synaptic signaling', two Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of 'dopaminergic synapse', 'cocaine addiction'] were identified (significantly higher than random, P < 1 × 10^-5 ). The top shared KEGG pathways (Benjamini-Hochberg-corrected P-value < 0.05) in the pairwise comparison of AUBD versus DUBD, NUBD versus DUBD, AUBD versus NUBD were 'Epstein-Barr virus infection', 'protein processing in endoplasmic reticulum' and 'neuroactive ligand-receptor interaction', respectively. We also identified substance-specific genetic factors: i.e. ADH1B and ALDH2 were unique for AUBD, while CHRNA3 and CHRNA4 were unique for NUBD.

CONCLUSIONS

This systematic review identifies the shared and unique genes and pathways for alcohol, nicotine and drug use behaviors and disorders at the genome-wide level and highlights critical biological processes for the common and distinguishing vulnerability of substance use behaviors and disorders.

On the Use of Heterogeneous Stock Mice to Map Transcriptomes Associated With Excessive Ethanol Consumption

We and many others have noted the advantages of using heterogeneous (HS) animals to map genes and gene networks associated with both behavioral and non-behavioral phenotypes. Importantly, genetically complex Mus musculus crosses provide substantially increased resolution to examine old and new relationships between gene expression and behavior. Here we report on data obtained from two HS populations: the HS/NPT derived from eight inbred laboratory mouse strains and the HS-CC derived from the eight collaborative cross inbred mouse strains that includes three wild-derived strains. Our work has focused on the genes and gene networks associated with risk for excessive ethanol consumption, individual variation in ethanol consumption and the consequences, including escalation, of long-term ethanol consumption. Background data on the development of HS mice is provided, including advantages for the detection of expression quantitative trait loci. Examples are also provided of using HS animals to probe the genes associated with ethanol preference and binge ethanol consumption.

Novel biomarkers to assess in utero effects of maternal opioid use: First steps toward understanding short- and long-term neurodevelopmental sequelae

Maternal opioid use disorder is common, resulting in significant neonatal morbidity and cost. Currently, it is not possible to predict which opioid-exposed newborns will require pharmacotherapy for neonatal abstinence syndrome. Further, little is known regarding the effects of maternal opioid use disorder on the developing human brain. We hypothesized that novel methodologies utilizing fetal central nervous system-derived extracellular vesicles isolated from maternal blood can address these gaps in knowledge. Plasma from opioid users and controls between 9 and 21 weeks was precipitated and extracellular vesicles were isolated. Mu opioid and cannabinoid receptor levels were quantified. Label-free proteomics studies and unbiased small RNA next generation sequencing was performed in paired fetal brain tissue. Maternal opioid use disorder increased mu opioid receptor protein levels in extracellular vesicles independent of opioid equivalent dose. Moreover, cannabinoid receptor levels in extracellular vesicles were upregulated with opioid exposure indicating cross talk with endocannabinoids. Maternal opioid use disorder was associated with significant changes in extracellular vesicle protein cargo and fetal brain micro RNA expression, especially in male fetuses. Many of the altered cargo molecules and micro RNAs identified are associated with adverse clinical neurodevelopmental outcomes. Our data suggest that assays relying on extracellular vesicles isolated from maternal blood extracellular vesicles may provide information regarding fetal response to opioids in the setting of maternal opioid use disorder. Prospective clinical studies are needed to evaluate the association between extracellular vesicle biomarkers, risk of neonatal abstinence syndrome and neurodevelopmental outcomes.

Shared additive genetic variation for alcohol dependence among subjects of African and European ancestry

Alcohol dependence (AD) affects individuals from all racial/ethnic groups, and previous research suggests that there is considerable variation in AD risk between and among various ancestrally defined groups in the United States. Although the reasons for these differences are likely due in part to contributions of complex sociocultural factors, limited research has attempted to examine whether similar genetic variation plays a role across ancestral groups. Using a pooled sample of individuals of African and European ancestry (AA/EA) obtained through data shared within the Database for Genotypes and Phenotypes, we estimated the extent to which additive genetic similarity for AD between AA and EAs using common single nucleotide polymorphisms overlapped across the two populations. AD was represented as a factor score by using Diagnostic and Statistical Manual dependence criteria, and genetic data were imputed by using the 1000 Genomes Reference Panel. Analyses revealed a significant single nucleotide polymorphism-based heritability of 17 percent (SE = 5) in EAs and 24 percent (SE = 15) in AAs. Further, a significant genetic correlation of 0.77 (SE = 0.46) suggests that the allelic architecture influencing the AD factor for EAs and AAs is largely similar across the two populations. Analyses indicated that investigating the genetic underpinnings of alcohol dependence in different ethnic groups may serve to highlight core etiological factors common to both groups and unique etiological factors specific to each ethnic group.

Gene-Centric Analysis of Preeclampsia Identifies Maternal Association at PLEKHG1

The genetic susceptibility to preeclampsia, a pregnancy-specific complication with significant maternal and fetal morbidity, has been poorly characterized. To identify maternal genes associated with preeclampsia risk, we assembled 498 cases and 1864 controls of European ancestry from preeclampsia case-control collections in 5 different US sites (with additional matched population controls), genotyped samples on a cardiovascular gene-centric array composed of variants from ≈2000 genes selected based on prior genetic studies of cardiovascular and metabolic diseases and performed case-control genetic association analysis on 27 429 variants passing quality control. In silico replication testing of 9 lead signals with P<10-4 was performed in independent European samples from the SOPHIA (Study of Pregnancy Hypertension in Iowa) and Inova cohorts (212 cases, 456 controls). Multiethnic assessment of lead signals was then performed in samples of black (26 cases, 136 controls), Hispanic (132 cases, 468 controls), and East Asian (9 cases, 80 controls) ancestry. Multiethnic meta-analysis (877 cases, 3004 controls) revealed a study-wide statistically significant association of the rs9478812 variant in the pleiotropic PLEKHG1 gene (odds ratio, 1.40 [1.23-1.60]; Pmeta=5.90×10-7). The rs9478812 effect was even stronger in the subset of European cases with known early-onset preeclampsia (236 cases diagnosed <37 weeks, 1864 controls; odds ratio, 1.59 [1.27-1.98]; P=4.01×10-5). PLEKHG1 variants have previously been implicated in genome-wide association studies of blood pressure, body weight, and neurological disorders. Although larger studies are required to further define maternal preeclampsia heritability, this study identifies a novel maternal risk locus for further investigation.

Antidepressant drug-specific prediction of depression treatment outcomes from genetic and clinical variables

Individuals with depression differ substantially in their response to treatment with antidepressants. Specific predictors explain only a small proportion of these differences. To meaningfully predict who will respond to which antidepressant, it may be necessary to combine multiple biomarkers and clinical variables. Using statistical learning on common genetic variants and clinical information in a training sample of 280 individuals randomly allocated to 12-week treatment with antidepressants escitalopram or nortriptyline, we derived models to predict remission with each antidepressant drug. We tested the reproducibility of each prediction in a validation set of 150 participants not used in model derivation. An elastic net logistic model based on eleven genetic and six clinical variables predicted remission with escitalopram in the validation dataset with area under the curve 0.77 (95%CI; 0.66-0.88; p = 0.004), explaining approximately 30% of variance in who achieves remission. A model derived from 20 genetic variables predicted remission with nortriptyline in the validation dataset with an area under the curve 0.77 (95%CI; 0.65-0.90; p < 0.001), explaining approximately 36% of variance in who achieves remission. The predictive models were antidepressant drug-specific. Validated drug-specific predictions suggest that a relatively small number of genetic and clinical variables can help select treatment between escitalopram and nortriptyline.

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.

Genome-Wide Association Study of Dietary Pattern Scores

Dietary patterns, representing global food supplies rather than specific nutrients or food intakes, have been associated with cardiovascular disease (CVD) incidence and mortality. The contribution of genetic factors in the determination of food intakes, preferences and dietary patterns has been previously established. The current study aimed to identify novel genetic factors associated with reported dietary pattern scores. Reported dietary patterns scores were derived from reported dietary intakes for the preceding month and were obtained through a food frequency questionnaire and genome-wide association study (GWAS) conducted in a study sample of 141 individuals. Reported Prudent and Western dietary patterns demonstrated nominal associations (p < 1 × 10-5) with 78 and 27 single nucleotide polymorphisms (SNPs), respectively. Among these, SNPs annotated to genes previously associated with neurological disorders, CVD risk factors and obesity were identified. Further assessment of SNPs demonstrated an impact on gene expression levels in blood for SNPs located within/near BCKDHB (p = 0.02) and the hypothalamic glucosensor PFKFB3 (p = 0.0004) genes, potentially mediated through an impact on the binding of transcription factors (TFs). Overrepresentations of glucose/energy homeostasis and hormone response TFs were also observed from SNP-surrounding sequences. Results from the current GWAS study suggest an interplay of genes involved in the metabolic response to dietary patterns on obesity, glucose metabolism and food-induced response in the brain in the adoption of dietary patterns.

A novel relationship for schizophrenia, bipolar and major depressive disorder Part 5: a hint from chromosome 5 high density association screen

Familial clustering of schizophrenia (SCZ), bipolar disorder (BPD), and major depressive disorder (MDD) was systematically reported (Aukes, M. F. Genet Med 2012, 14, 338-341) and any two or even three of these disorders could co-exist in some families. In addition, evidence from symptomatology and psychopharmacology also imply that there are intrinsic connections between these three major disorders. A total of 56,569 single nucleotide polymorphism (SNPs) on chromosome 5 were genotyped by Affymetrix Genome-Wide Human SNP array 6.0 on 119 SCZ, 253 BPD (type-I), 177 MDD patients and 1000 controls. Associated SNPs and flanking genes was screen out systematically, and cadherin pathway genes (CDH6, CDH9, CDH10, CDH12, and CDH18) belong to outstanding genes. Unexpectedly, nearly all flanking genes of the associated SNPs distinctive for BPD and MDD were replicated in an enlarged cohort of 986 SCZ patients (P ≤ 9.9E-8). Considering multiple bits of evidence, our chromosome 5 analyses implicated that bipolar and major depressive disorder might be subtypes of schizophrenia rather than two independent disease entities. Also, cadherin pathway genes play important roles in the pathogenesis of the three major mental disorders.

Genetic variation in the exome: Associations with alcohol and tobacco co-use

Shared genetic factors represent one underlying mechanism thought to contribute to high rates of alcohol and tobacco co-use and dependence. Common variants identified by molecular genetic studies tend to confer only small disease risk, and rare protein-coding variants are posited to contribute to disease risk, as well. However, given that genotyping technologies allowing for their inclusion in association studies have only recently become available, the magnitude of their contribution is poorly understood. The current study examined genetic variation in protein-coding regions (i.e., the exome) for associations with measures of lifetime alcohol and tobacco co-use. Participants from the UCSF Family Alcoholism Study (N = 1,862) were genotyped using an exome-focused genotyping array, and assessed for DSM-IV diagnoses of alcohol and tobacco dependence and quantitative consumption measures using a modified version of the Semi-Structured Assessment for the Genetics of Alcoholism. Analyses included single variant, gene-based, and pathway-based tests of association. One EMR3 variant and a pathway related to genes upregulated in mesenchymal stem cells during the late phase of adipogenesis met criteria for statistical significance. Suggestive associations were consistent with previous findings from studies of substance use and dependence, including variants in the CHRNA5-CHRNA3-CHRNB4 gene cluster with cigarettes smoked per day. Further, several variants and genes demonstrated suggestive association across phenotypes, suggesting that shared genetic factors may underlie risk for increased levels of alcohol and tobacco use, as well as psychopathology more broadly, providing insight into our understanding of the genetic architecture underlying these traits. (PsycINFO Database Record

Promising pharmacogenetic targets for treating alcohol use disorder: evidence from preclinical models

Inherited genetic variants contribute to risk factors for developing an alcohol use disorder, and polymorphisms may inform precision medicine strategies for treating alcohol addiction. Targeting genetic mutations linked to alcohol phenotypes has provided promising initial evidence for reducing relapse rates in alcoholics. Although successful in some studies, there are conflicting findings and the reports of adverse effects may ultimately limit their clinical utility, suggesting that novel pharmacogenetic targets are necessary to advance precision medicine approaches. Here, we describe promising novel genetic variants derived from preclinical models of alcohol consumption and dependence that may uncover disease mechanisms that drive uncontrolled drinking and identify novel pharmacogenetic targets that facilitate therapeutic intervention for the treatment of alcohol use disorder.

Differential potassium channel gene regulation in BXD mice reveals novel targets for pharmacogenetic therapies to reduce heavy alcohol drinking

Alcohol (ethanol) dependence is a chronic relapsing brain disorder partially influenced by genetics and characterized by an inability to regulate harmful levels of drinking. Emerging evidence has linked genes that encode K_V7, K_IR, and K_Ca2 K⁺ channels with variation in alcohol-related behaviors in rodents and humans. This led us to experimentally test relations between K⁺ channel genes and escalation of drinking in a chronic-intermittent ethanol (CIE) exposure model of dependence in BXD recombinant inbred strains of mice. Transcript levels for K⁺ channel genes in the prefrontal cortex (PFC) and nucleus accumbens (NAc) covary with voluntary ethanol drinking in a non-dependent cohort. Transcripts that encode K_V7 channels covary negatively with drinking in non-dependent BXD strains. Using a pharmacological approach to validate the genetic findings, C57BL/6J mice were allowed intermittent access to ethanol to establish baseline consumption before they were treated with retigabine, an FDA-approved K_V7 channel positive modulator. Systemic administration significantly reduced drinking, and consistent with previous evidence, retigabine was more effective at reducing voluntary consumption in high-drinking than low-drinking subjects. We evaluated the specific K⁺ channel genes that were most sensitive to CIE exposure and identified a gene subset in the NAc and PFC that were dysregulated in the alcohol-dependent BXD cohort. CIE-induced modulation of nine genes in the NAc and six genes in the PFC covaried well with the changes in drinking induced by ethanol dependence. Here we identified novel candidate genes in the NAc and PFC that are regulated by ethanol dependence and correlate with voluntary drinking in non-dependent and dependent BXD mice. The findings that Kcnq expression correlates with drinking and that retigabine reduces consumption suggest that K_V7 channels could be pharmacogenetic targets to treat individuals with alcohol addiction.

The allostatic impact of chronic ethanol on gene expression: A genetic analysis of chronic intermittent ethanol treatment in the BXD cohort

The transition from acute to chronic ethanol exposure leads to lasting behavioral and physiological changes such as increased consumption, dependence, and withdrawal. Changes in brain gene expression are hypothesized to underlie these adaptive responses to ethanol. Previous studies on acute ethanol identified genetic variation in brain gene expression networks and behavioral responses to ethanol across the BXD panel of recombinant inbred mice. In this work, we have performed the first joint genetic and genomic analysis of transcriptome shifts in response to chronic intermittent ethanol (CIE) by vapor chamber exposure in a BXD cohort. CIE treatment is known to produce significant and sustained changes in ethanol consumption with repeated cycles of ethanol vapor. Using Affymetrix microarray analysis of prefrontal cortex (PFC) and nucleus accumbens (NAC) RNA, we compared CIE expression responses to those seen following acute ethanol treatment, and to voluntary ethanol consumption. Gene expression changes in PFC and NAC after CIE overlapped significantly across brain regions and with previously published expression following acute ethanol. Genes highly modulated by CIE were enriched for specific biological processes including synaptic transmission, neuron ensheathment, intracellular signaling, and neuronal projection development. Expression quantitative trait locus (eQTL) analyses identified genomic loci associated with ethanol-induced transcriptional changes with largely distinct loci identified between brain regions. Correlating CIE-regulated genes to ethanol consumption data identified specific genes highly associated with variation in the increase in drinking seen with repeated cycles of CIE. In particular, multiple myelin-related genes were identified. Furthermore, genetic variance in or near dynamin3 (Dnm3) on Chr1 at ∼164 Mb may have a major regulatory role in CIE-responsive gene expression. Dnm3 expression correlates significantly with ethanol consumption, is contained in a highly ranked functional group of CIE-regulated genes in the NAC, and has a cis-eQTL within a genomic region linked with multiple CIE-responsive genes.

Overview of the Genetics of Alcohol Use Disorder

AIMS

Alcohol Use Disorder (AUD) is a chronic psychiatric illness characterized by harmful drinking patterns leading to negative emotional, physical, and social ramifications. While the underlying pathophysiology of AUD is poorly understood, there is substantial evidence for a genetic component; however, identification of universal genetic risk variants for AUD has been difficult. Recent efforts in the search for AUD susceptibility genes will be reviewed in this article.

METHODS

In this review, we provide an overview of genetic studies on AUD, including twin studies, linkage studies, candidate gene studies, and genome-wide association studies (GWAS).

RESULTS

Several potential genetic susceptibility factors for AUD have been identified, but the genes of alcohol metabolism, alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH), have been found to be protective against the development of AUD. GWAS have also identified a heterogeneous list of SNPs associated with AUD and alcohol-related phenotypes, emphasizing the complexity and heterogeneity of the disorder. In addition, many of these findings have small effect sizes when compared to alcohol metabolism genes, and biological relevance is often unknown.

CONCLUSIONS

Although studies spanning multiple approaches have suggested a genetic basis for AUD, identification of the genetic risk variants has been challenging. Some promising results are emerging from GWAS studies; however, larger sample sizes are needed to improve GWAS results and resolution. As the field of genetics is rapidly developing, whole genome sequencing could soon become the new standard of interrogation of the genes and neurobiological pathways which contribute to the complex phenotype of AUD.

SHORT SUMMARY

This review examines the genetic underpinnings of Alcohol Use Disorder (AUD), with an emphasis on GWAS approaches for identifying genetic risk variants. The most promising results associated with AUD and alcohol-related phenotypes have included SNPs of the alcohol metabolism genes ADH and ALDH.

An efficient genome-wide association test for mixed binary and continuous phenotypes with applications to substance abuse research

We propose a new genome-wide association test for mixed binary and continuous phenotypes that uses an efficient numerical method to estimate the empirical distribution of the Fisher's combination statistic under the null hypothesis. Our simulation study shows that the proposed method controls the type I error rate and also maintains its power at the level of the permutation method. More importantly, the computational efficiency of the proposed method is much higher than the one of the permutation method. The simulation results also indicate that the power of the test increases when the genetic effect increases, the minor allele frequency increases, and the correlation between responses decreases. The statistical analysis on the database of the Study of Addiction: Genetics and Environment demonstrates that the proposed method combining multiple phenotypes can increase the power of identifying markers that may not be, otherwise, chosen using marginal tests.

Shared additive genetic influences on DSM-IV criteria for alcohol dependence in subjects of European ancestry

BACKGROUND AND AIMS

Genetic studies of alcohol dependence (AD) have identified several candidate loci and genes, but most observed effects are small and difficult to reproduce. A plausible explanation for inconsistent findings may be a violation of the assumption that genetic factors contributing to each of the seven DSM-IV criteria point to a single underlying dimension of risk. Given that recent twin studies suggest that the genetic architecture of AD is complex and probably involves multiple discrete genetic factors, the current study employed common single nucleotide polymorphisms in two multivariate genetic models to examine the assumption that the genetic risk underlying DSM-IV AD is unitary.

DESIGN, SETTING, PARTICIPANTS, MEASUREMENTS

AD symptoms and genome-wide single nucleotide polymorphism (SNP) data from 2596 individuals of European descent from the Study of Addiction: Genetics and Environment were analyzed using genomic-relatedness-matrix restricted maximum likelihood. DSM-IV AD symptom covariance was described using two multivariate genetic factor models.

FINDINGS

Common SNPs explained 30% (standard error=0.136, P=0.012) of the variance in AD diagnosis. Additive genetic effects varied across AD symptoms. The common pathway model approach suggested that symptoms could be described by a single latent variable that had a SNP heritability of 31% (0.130, P=0.008). Similarly, the exploratory genetic factor model approach suggested that the genetic variance/covariance across symptoms could be represented by a single genetic factor that accounted for at least 60% of the genetic variance in any one symptom.

CONCLUSION

Additive genetic effects on DSM-IV alcohol dependence criteria overlap. The assumption of common genetic effects across alcohol dependence symptoms appears to be a valid assumption.

Genome-wide association study of copy number variations (CNVs) with opioid dependence

Single-nucleotide polymorphisms that have been associated with opioid dependence (OD) altogether account for only a small proportion of the known heritability. Most of the genetic risk factors are unknown. Some of the 'missing heritability' might be explained by copy number variations (CNVs) in the human genome. We used Illumina HumanOmni1 arrays to genotype 5152 African-American and European-American OD cases and screened controls and implemented combined CNV calling methods. After quality control measures were applied, a genome-wide association study (GWAS) of CNVs with OD was performed. For common CNVs, two deletions and one duplication were significantly associated with OD genome-wide (eg, P=2 × 10(-8) and OR (95% CI)=0.64 (0.54-0.74) for a chromosome 18q12.3 deletion). Several rare or unique CNVs showed suggestive or marginal significance with large effect sizes. This study is the first GWAS of OD using CNVs. Some identified CNVs harbor genes newly identified here to be of biological importance in addiction, whereas others affect genes previously known to contribute to substance dependence risk. Our findings augment our specific knowledge of the importance of genomic variation in addictive disorders, and provide an addiction CNV pool for further research. These findings require replication.

Gene expression changes in serotonin, GABA-A receptors, neuropeptides and ion channels in the dorsal raphe nucleus of adolescent alcohol-preferring (P) rats following binge-like alcohol drinking

Alcohol binge-drinking during adolescence is a serious public health concern with long-term consequences. We used RNA sequencing to assess the effects of excessive adolescent ethanol binge-drinking on gene expression in the dorsal raphe nucleus (DRN) of alcohol preferring (P) rats. Repeated binges across adolescence (three 1h sessions across the dark-cycle per day, 5 days per week for 3 weeks starting at 28 days of age; ethanol intakes of 2.5-3 g/kg/session) significantly altered the expression of approximately one-third of the detected genes. Multiple neurotransmitter systems were altered, with the largest changes in the serotonin system (21 of 23 serotonin-related genes showed decreased expression) and GABA-A receptors (8 decreased and 2 increased). Multiple neuropeptide systems were also altered, with changes in the neuropeptide Y and corticotropin-releasing hormone systems similar to those associated with increased drinking and decreased resistance to stress. There was increased expression of 21 of 32 genes for potassium channels. Expression of downstream targets of CREB signaling was increased. There were also changes in expression of genes involved in inflammatory processes, axonal guidance, growth factors, transcription factors, and several intracellular signaling pathways. These widespread changes indicate that excessive binge drinking during adolescence alters the functioning of the DRN and likely its modulation of many regions of the central nervous system, including the mesocorticolimbic system.

Genetics of alcoholism

Alcohol use and alcohol use disorders are substantially heritable. Variants in genes coding for alcohol metabolic enzymes have long been known to influence consumption. More recent studies in family-based samples have implicated GABRA2, nicotinic receptor genes such as CHRNB3, and a number of other specific single genes as associated with alcohol use disorders. The growing use of genetic analyses, in particular studies using polygenic risk scores; neurobiologic pathways; and methods for quantifying gene × gene and gene × environment interactions have also contributed to an evolving understanding of the genetic architecture of alcohol use disorders. Additionally, the study of behavioral traits associated with alcohol dependence such as impulsivity and sensation seeking, and the influences of demographic factors (i.e., sex and ethnicity) have significantly enhanced the genetics of alcoholism literature. This article provides a brief overview of the current topically relevant findings in the field to date and includes areas of research still requiring attention.

On the analysis of a repeated measure design in genome-wide association analysis

Longitudinal data enables detecting the effect of aging/time, and as a repeated measures design is statistically more efficient compared to cross-sectional data if the correlations between repeated measurements are not large. In particular, when genotyping cost is more expensive than phenotyping cost, the collection of longitudinal data can be an efficient strategy for genetic association analysis. However, in spite of these advantages, genome-wide association studies (GWAS) with longitudinal data have rarely been analyzed taking this into account. In this report, we calculate the required sample size to achieve 80% power at the genome-wide significance level for both longitudinal and cross-sectional data, and compare their statistical efficiency. Furthermore, we analyzed the GWAS of eight phenotypes with three observations on each individual in the Korean Association Resource (KARE). A linear mixed model allowing for the correlations between observations for each individual was applied to analyze the longitudinal data, and linear regression was used to analyze the first observation on each individual as cross-sectional data. We found 12 novel genome-wide significant disease susceptibility loci that were then confirmed in the Health Examination cohort, as well as some significant interactions between age/sex and SNPs.

Genome-wide association studies in Africans and African Americans: expanding the framework of the genomics of human traits and disease

Genomic research is one of the tools for elucidating the pathogenesis of diseases of global health relevance and paving the research dimension to clinical and public health translation. Recent advances in genomic research and technologies have increased our understanding of human diseases, genes associated with these disorders, and the relevant mechanisms. Genome-wide association studies (GWAS) have proliferated since the first studies were published several years ago and have become an important tool in helping researchers comprehend human variation and the role genetic variants play in disease. However, the need to expand the diversity of populations in GWAS has become increasingly apparent as new knowledge is gained about genetic variation. Inclusion of diverse populations in genomic studies is critical to a more complete understanding of human variation and elucidation of the underpinnings of complex diseases. In this review, we summarize the available data on GWAS in recent African ancestry populations within the western hemisphere (i.e. African Americans and peoples of the Caribbean) and continental African populations. Furthermore, we highlight ways in which genomic studies in populations of recent African ancestry have led to advances in the areas of malaria, HIV, prostate cancer, and other diseases. Finally, we discuss the advantages of conducting GWAS in recent African ancestry populations in the context of addressing existing and emerging global health conditions.

Ethanol treatment of lymphoblastoid cell lines from alcoholics and non-alcoholics causes many subtle changes in gene expression

To elucidate the effects of a controlled exposure to ethanol on gene expression, we studied lymphoblastoid cell lines (LCLs) from 21 alcoholics and 21 controls. We cultured each cell line for 24 h with and without 75 mM ethanol and measured gene expression using microarrays. Differences in expression between LCLs from alcoholics and controls included 13 genes previously identified as associated with alcoholism or related traits, including KCNA3, DICER1, ZNF415, CAT, SLC9A9, and PPARGC1B. The paired design allowed us to detect very small changes due to ethanol treatment: ethanol altered the expression of 37% of the probe sets (51% of the unique named genes) expressed in these LCLs, most by modest amounts. Ninety-nine percent of the named genes expressed in the LCLs were also expressed in brain. Key pathways affected by ethanol include cytokine, TNF, and NFκB signaling. Among the genes affected by ethanol were ANK3, EPHB1, SLC1A1, SLC9A9, NRD1, and SH3BP5, which were reported to be associated with alcoholism or related phenotypes in 2 genome-wide association studies. Genes that either differed in expression between alcoholics and controls or were affected by ethanol exposure are candidates for further study.

Common PTP4A1-PHF3-EYS variants are specific for alcohol dependence

BACKGROUND AND OBJECTIVES

We previously reported a risk genomic region (ie, PTP4A1-PHF3-EYS) for alcohol dependence in a genome-wide association study (GWAS). We also reported a rare variant constellation across this region that was significantly associated with alcohol dependence. In the present study, we significantly increased the marker density within this region and examined the specificity of the associations of common variants for alcohol dependence.

METHODS

One African-American discovery sample (681 cases with alcohol dependence and 508 controls), one European-American replication sample (1,409 alcohol dependent cases and 1,518 controls), and one European-Australian replication sample (a total of 6,438 family subjects with 1,645 alcohol dependent probands) underwent association analysis. A total of 38,714 subjects from 18 other cohorts with 10 different neuropsychiatric disorders served as contrast groups.

RESULTS

We found 289 SNPs that were nominally associated with alcohol dependence in the discovery sample (p < .05). Fifty-six associations of them were significant after correction (1.9 × 10(-6) ≤ p ≤ 1.6 × 10(-5)). No markers were significantly associated with other neuropsychiatric disorders after experiment-wide correction.

CONCLUSIONS AND SCIENTIFIC SIGNIFICANCE

We confirmed with our previous findings that PTP4A1-PHF3-EYS variants were significantly associated with alcohol dependence, which were replicable across multiple independent populations and were specific for alcohol dependence. These findings suggested that this region might harbor a causal variant(s) for alcohol dependence.

Whole exome re-sequencing implicates CCDC38 and cilia structure and function in resistance to smoking related airflow obstruction

Chronic obstructive pulmonary disease (COPD) is a leading cause of global morbidity and mortality and, whilst smoking remains the single most important risk factor, COPD risk is heritable. Of 26 independent genomic regions showing association with lung function in genome-wide association studies, eleven have been reported to show association with airflow obstruction. Although the main risk factor for COPD is smoking, some individuals are observed to have a high forced expired volume in 1 second (FEV1) despite many years of heavy smoking. We hypothesised that these "resistant smokers" may harbour variants which protect against lung function decline caused by smoking and provide insight into the genetic determinants of lung health. We undertook whole exome re-sequencing of 100 heavy smokers who had healthy lung function given their age, sex, height and smoking history and applied three complementary approaches to explore the genetic architecture of smoking resistance. Firstly, we identified novel functional variants in the "resistant smokers" and looked for enrichment of these novel variants within biological pathways. Secondly, we undertook association testing of all exonic variants individually with two independent control sets. Thirdly, we undertook gene-based association testing of all exonic variants. Our strongest signal of association with smoking resistance for a non-synonymous SNP was for rs10859974 (P = 2.34 × 10(-4)) in CCDC38, a gene which has previously been reported to show association with FEV1/FVC, and we demonstrate moderate expression of CCDC38 in bronchial epithelial cells. We identified an enrichment of novel putatively functional variants in genes related to cilia structure and function in resistant smokers. Ciliary function abnormalities are known to be associated with both smoking and reduced mucociliary clearance in patients with COPD. We suggest that genetic influences on the development or function of cilia in the bronchial epithelium may affect growth of cilia or the extent of damage caused by tobacco smoke.

Identifying Genetic Variants for Addiction via Propensity Score Adjusted Generalized Kendall's Tau

Identifying replicable genetic variants for addiction has been extremely challenging. Besides the common difficulties with genome-wide association studies (GWAS), environmental factors are known to be critical to addiction, and comorbidity is widely observed. Despite the importance of environmental factors and comorbidity for addiction study, few GWAS analyses adequately considered them due to the limitations of the existing statistical methods. Although parametric methods have been developed to adjust for covariates in association analysis, difficulties arise when the traits are multivariate because there is no ready-to-use model for them. Recent nonparametric development includes U-statistics to measure the phenotype-genotype association weighted by a similarity score of covariates. However, it is not clear how to optimize the similarity score. Therefore, we propose a semiparametric method to measure the association adjusted by covariates. In our approach, the nonparametric U-statistic is adjusted by parametric estimates of propensity scores using the idea of inverse probability weighting. The new measurement is shown to be asymptotically unbiased under our null hypothesis while the previous non-weighted and weighted ones are not. Simulation results show that our test improves power as opposed to the non-weighted and two other weighted U-statistic methods, and it is particularly powerful for detecting gene-environment interactions. Finally, we apply our proposed test to the Study of Addiction: Genetics and Environment (SAGE) to identify genetic variants for addiction. Novel genetic variants are found from our analysis, which warrant further investigation in the future.

The genetics of alcohol dependence

Alcohol consumption dates back to the Neolithic period, and alcohol dependence contributes substantially to the current global burden of disease. Despite this, optimal therapies and preventive strategies are lacking. Formal genetic studies of alcohol dependence have shown that genetic factors play as large a role in disease etiology as environmental factors. Molecular genetic studies may identify causal factors and facilitate the development of novel preventive and therapeutic approaches. Whereas earlier studies involved the use of linkage- and candidate-gene approaches, recent years have witnessed the introduction of genome-wide association studies (GWAS). The present review provides a brief overview of the findings of formal genetic studies, summarizes the results of earlier molecular-genetic investigations, and presents a detailed overview of all published GWAS in the field of alcohol dependence research. To date, few genome-wide significant findings have been reported. However, through the polygenic approach, GWAS have both confirmed the existence of a multitude of novel risk genes and indicated interesting new candidates.