Genome-wide Association Study of Maximum Habitual Alcohol Intake in >140,000 U.S. European and African American Veterans Yields Novel Risk Loci

Multi-environment gene interactions linked to the interplay between polysubstance dependence and suicidality

Substance dependence diagnoses (SDs) are important risk factors for suicidality. We investigated the associations of multiple SDs with different suicidality outcomes, testing how genetic background moderates these associations. The Yale-Penn cohort (N = 15,557) was recruited to investigate the genetics of SDs. The Army STARRS (Study to Assess Risk and Resilience in Servicemembers) cohort (N = 11,236) was recruited to evaluate mental health risk and resilience among Army personnel. We applied multivariate logistic regression to investigate the associations of SDs with suicidality and, in the Yale-Penn cohort, we used the structured linear mixed model (StructLMM) to study multivariate gene-environment interactions. In Yale-Penn, lifetime polysubstance dependence was strongly associated with lifetime suicidality: having five SDs showed an association with suicidality, from odds ratio (OR) = 6.77 (95% confidence interval, CI = 5.74-7.99) for suicidal ideation (SI) to OR = 3.61 (95% CI = 2.7-4.86) for suicide attempt (SA). In Army STARRS, having multiple substance use disorders for alcohol and/or drugs was associated with increased suicidality ranging from OR = 2.88 (95% CI = 2.6-3.19) for SI to OR = 3.92 (95% CI = 3.19-4.81) for SA. In Yale-Penn, we identified multivariate gene-environment interactions (Bayes factors, BF > 0) of SI with respect to a gene cluster on chromosome 16 (LCAT, p = 1.82 × 10^-7; TSNAXIP1, p = 2.13 × 10^-7; CENPT, p = 2.32 × 10^-7; PARD6A, p = 5.57 × 10^-7) for opioid dependence (BF = 12.2), cocaine dependence (BF = 12.1), nicotine dependence (BF = 9.2), and polysubstance dependence (BF = 2.1). Comorbidity of multiple SDs is a significant associated with suicidality and heritability of suicidality is partially moderated by multivariate gene interactions.

Selective Serotonin Reuptake Inhibitor Pharmaco-Omics: Mechanisms and Prediction

Selective serotonin reuptake inhibitors (SSRIs) are a standard of care for the pharmacotherapy of patients suffering from Major Depressive Disorder (MDD). However, only one-half to two-thirds of MDD patients respond to SSRI therapy. Recently, a "multiple omics" research strategy was applied to identify genetic differences between patients who did and did not respond to SSRI therapy. As a first step, plasma metabolites were assayed using samples from the 803 patients in the PGRN-AMPS SSRI MDD trial. The metabolomics data were then used to "inform" genomics by performing a genome-wide association study (GWAS) for plasma concentrations of the metabolite most highly associated with clinical response, serotonin (5-HT). Two genome-wide or near genome-wide significant single nucleotide polymorphism (SNP) signals were identified, one that mapped near the TSPAN5 gene and another across the ERICH3 gene, both genes that are highly expressed in the brain. Knocking down TSPAN5 and ERICH3 resulted in decreased 5-HT concentrations in neuroblastoma cell culture media and decreased expression of enzymes involved in 5-HT biosynthesis and metabolism. Functional genomic studies demonstrated that ERICH3 was involved in clathrin-mediated vesicle formation and TSPAN5 was an ethanol-responsive gene that may be a marker for response to acamprosate pharmacotherapy of alcohol use disorder (AUD), a neuropsychiatric disorder highly co-morbid with MDD. In parallel studies, kynurenine was the plasma metabolite most highly associated with MDD symptom severity and application of a metabolomics-informed pharmacogenomics approach identified DEFB1 and AHR as genes associated with variation in plasma kynurenine levels. Both genes also contributed to kynurenine-related inflammatory pathways. Finally, a multiply replicated predictive algorithm for SSRI clinical response with a balanced predictive accuracy of 76% (compared with 56% for clinical data alone) was developed by including the SNPs in TSPAN5, ERICH3, DEFB1 and AHR. In summary, application of a multiple omics research strategy that used metabolomics to inform genomics, followed by functional genomic studies, identified novel genes that influenced monoamine biology and made it possible to develop a predictive algorithm for SSRI clinical outcomes in MDD. A similar pharmaco-omic research strategy might be broadly applicable for the study of other neuropsychiatric diseases and their drug therapy.

Identification of Functional Genetic Variants Associated With Alcohol Dependence and Related Phenotypes Using a High-Throughput Assay

BACKGROUND

Genome-wide association studies (GWAS) of alcohol dependence (AD) and related phenotypes have identified multiple loci, but the functional variants underlying the loci have in most cases not been identified. Noncoding variants can influence phenotype by affecting gene expression; for example, variants in the 3' untranslated regions (3'UTR) can affect gene expression posttranscriptionally.

METHODS

We adapted a high-throughput assay known as PASSPORT-seq (parallel assessment of polymorphisms in miRNA target sites by sequencing) to identify among variants associated with AD and related phenotypes those that cause differential expression in neuronal cell lines. Based upon meta-analyses of alcohol-related traits in African American and European Americans in the Collaborative Study on the Genetics of Alcoholism, we tested 296 single nucleotide polymorphisms (SNPs with meta-analysis p values ≤ 0.001) that were located in 3'UTRs.

RESULTS

We identified 60 SNPs that affected gene expression (false discovery rate [FDR] < 0.05) in SH-SY5Y cells and 92 that affected expression in SK-N-BE(2) cells. Among these, 30 SNPs altered RNA levels in the same direction in both cell lines. Many of these SNPs reside in the binding sites of miRNAs and RNA-binding proteins and are expression quantitative trait loci of genes including KIF6,FRMD4A,CADM2,ADD2,PLK2, and GAS7.

CONCLUSION

The SNPs identified in the PASSPORT-seq assay are functional variants that might affect the risk for AD and related phenotypes. Our study provides insights into gene regulation in AD and demonstrates the value of PASSPORT-seq as a tool to screen genetic variants in GWAS loci for one potential mechanism of action.

Large genome-wide association study identifies three novel risk variants for restless legs syndrome

Restless legs syndrome (RLS) is a common neurological sensorimotor disorder often described as an unpleasant sensation associated with an urge to move the legs. Here we report findings from a meta-analysis of genome-wide association studies of RLS including 480,982 Caucasians (cases = 10,257) and a follow up sample of 24,977 (cases = 6,651). We confirm 19 of the 20 previously reported RLS sequence variants at 19 loci and report three novel RLS associations; rs112716420-G (OR = 1.25, P = 1.5 × 10-18), rs10068599-T (OR = 1.09, P = 6.9 × 10-10) and rs10769894-A (OR = 0.90, P = 9.4 × 10-14). At four of the 22 RLS loci, cis-eQTL analysis indicates a causal impact on gene expression. Through polygenic risk score for RLS we extended prior epidemiological findings implicating obesity, smoking and high alcohol intake as risk factors for RLS. To improve our understanding, with the purpose of seeking better treatments, more genetics studies yielding deeper insights into the disease biology are needed.

Genome-wide translational profiling of amygdala Crh-expressing neurons reveals role for CREB in fear extinction learning

Fear and extinction learning are adaptive processes caused by molecular changes in specific neural circuits. Neurons expressing the corticotropin-releasing hormone gene (Crh) in central amygdala (CeA) are implicated in threat regulation, yet little is known of cell type-specific gene pathways mediating adaptive learning. We translationally profiled the transcriptome of CeA Crh-expressing cells (Crh neurons) after fear conditioning or extinction in mice using translating ribosome affinity purification (TRAP) and RNAseq. Differential gene expression and co-expression network analyses identified diverse networks activated or inhibited by fear vs extinction. Upstream regulator analysis demonstrated that extinction associates with reduced CREB expression, and viral vector-induced increased CREB expression in Crh neurons increased fear expression and inhibited extinction. These findings suggest that CREB, within CeA Crh neurons, may function as a molecular switch that regulates expression of fear and its extinction. Cell-type specific translational analyses may suggest targets useful for understanding and treating stress-related psychiatric illness.

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.

Genome-wide meta-analysis of problematic alcohol use in 435,563 individuals yields insights into biology and relationships with other traits

Problematic alcohol use (PAU) is a leading cause of death and disability worldwide. Although genome-wide association studies have identified PAU risk genes, the genetic architecture of this trait is not fully understood. We conducted a proxy-phenotype meta-analysis of PAU, combining alcohol use disorder and problematic drinking, in 435,563 European-ancestry individuals. We identified 29 independent risk variants, 19 of them novel. PAU was genetically correlated with 138 phenotypes, including substance use and psychiatric traits. Phenome-wide polygenic risk score analysis in an independent biobank sample (BioVU, n = 67,589) confirmed the genetic correlations between PAU and substance use and psychiatric disorders. Genetic heritability of PAU was enriched in brain and in conserved and regulatory genomic regions. Mendelian randomization suggested causal effects on liability to PAU of substance use, psychiatric status, risk-taking behavior and cognitive performance. In summary, this large PAU meta-analysis identified novel risk loci and revealed genetic relationships with numerous other traits.

Using polygenic scores for identifying individuals at increased risk of substance use disorders in clinical and population samples

Genome-wide, polygenic risk scores (PRS) have emerged as a useful way to characterize genetic liability. There is growing evidence that PRS may prove useful for early identification of those at increased risk for certain diseases. The current potential of PRS for alcohol use disorders (AUD) remains an open question. Using data from both a population-based sample [the FinnTwin12 (FT12) study] and a high-risk sample [the Collaborative Study on the Genetics of Alcoholism (COGA)], we examined the association between PRSs derived from genome-wide association studies (GWASs) of (1) alcohol dependence/alcohol problems, (2) alcohol consumption, and (3) risky behaviors with AUD and other substance use disorder (SUD) criteria. These PRSs explain ~2.5-3.5% of the variance in AUD (across FT12 and COGA) when all PRSs are included in the same model. Calculations of area under the curve (AUC) show PRS provide only a slight improvement over a model with age, sex, and ancestral principal components as covariates. While individuals in the top 20, 10, and 5% of the PRS distribution had greater odds of having an AUD compared to the lower end of the continuum in both COGA and FT12, the point estimates at each threshold were statistically indistinguishable. Those in the top 5% reported greater levels of licit (alcohol and nicotine) and illicit (cannabis and opioid) SUD criteria. PRSs are associated with risk for SUD in independent samples. However, usefulness for identifying those at increased risk in their current form is modest, at best. Improvement in predictive ability will likely be dependent on increasing the size of well-phenotyped discovery samples.

An update on the role of common genetic variation underlying substance use disorders

PURPOSE OF THE REVIEW

Sample size increases have resulted in novel and replicable loci for substance use disorders (SUDs). We summarize some of the latest insights into SUD genetics and discuss some next steps in addiction genetics.

RECENT FINDINGS

Genome-wide association studies have substantiated the role of previously known variants (e.g., rs1229984 in ADH1B for alcohol) and identified several novel loci for alcohol, tobacco, cannabis, opioid and cocaine use disorders. SUDs are genetically correlated with psychiatric outcomes, while liability to substance use is inconsistently associated with these outcomes and more closely associated with lifestyle factors. Specific variant associations appear to differ somewhat across populations, although similar genes and systems are implicated.

SUMMARY

The next decade of human genetic studies of addiction should focus on expanding to non-European populations, consider pleiotropy across SUD and with other psychiatric disorders, and leverage human and cross-species functional data to elucidate the biological mechanisms underlying SUDs.

Recent Efforts to Dissect the Genetic Basis of Alcohol Use and Abuse

Alcohol use disorder (AUD) is defined by several symptom criteria, which can be dissected further at the genetic level. Over the past several years, our understanding of the genetic factors influencing alcohol use and abuse has progressed tremendously; numerous loci have been implicated in different aspects of alcohol use. Previously known associations with alcohol-metabolizing enzymes (ADH1B, ALDH2) have been replicated definitively. In addition, novel associations with loci containing the genes KLB, GCKR, CRHR1, and CADM2 have been reported. Downstream analyses have leveraged these genetic findings to reveal important relationships between alcohol use behaviors and both physical and mental health. AUD and aspects of alcohol misuse have been shown to overlap strongly with psychiatric disorders, whereas aspects of alcohol consumption have shown stronger links to metabolism. These results demonstrate that the genetic architecture of alcohol consumption only partially overlaps with the genetics of clinically defined AUD. We discuss the limitations of using quantitative measures of alcohol use as proxy measures for AUD, and we outline how future studies will require careful phenotype harmonization to properly capture the genetic liability to AUD.

Translating Across Circuits and Genetics Toward Progress in Fear- and Anxiety-Related Disorders

Anxiety and fear-related disorders are common and disabling, and they significantly increase risk for suicide and other causes of morbidity and mortality. However, there is tremendous potential for translational neuroscience to advance our understanding of these disorders, leading to novel and powerful interventions and even to preventing their initial development. This overview examines the general circuits and processes thought to underlie fear and anxiety, along with the promise of translational research. It then examines some of the data-driven "next-generation" approaches that are needed for discovery and understanding but that do not always fit neatly into established models. From one perspective, these disorders offer among the most tractable problems in psychiatry, with a great deal of accumulated understanding, across species, of neurocircuit, behavioral, and, increasingly, genetic mechanisms, of how dysregulation of fear and threat processes contributes to anxiety-related disorders. One example is the progressively sophisticated understanding of how extinction underlies the exposure therapy component of cognitive-behavioral therapy approaches, which are ubiquitously used across anxiety and fear-related disorders. However, it is also critical to examine gaps in our understanding between reasonably well-replicated examples of successful translation, areas of significant deficits in knowledge, and the role of large-scale data-driven approaches in future progress and discovery. Although a tremendous amount of progress is still needed, translational approaches to understanding, treating, and even preventing anxiety and fear-related disorders offer great opportunities for successfully bridging neuroscience discovery to clinical practice.

Reproducible Genetic Risk Loci for Anxiety: Results From ∼200,000 Participants in the Million Veteran Program

OBJECTIVE

Anxiety disorders are common and often disabling. The goal of this study was to examine the genetic architecture of anxiety disorders and anxiety symptoms, which are also frequently comorbid with other mental disorders, such as major depressive disorder.

METHODS

Using one of the world's largest biobanks including genetic, environmental, and medical information, the Million Veteran Program, the authors performed a genome-wide association study (GWAS) of a continuous trait for anxiety (based on score on the Generalized Anxiety Disorder 2-item scale [GAD-2], N=199,611) as the primary analysis and self-report of physician diagnosis of anxiety disorder (N=224,330) as a secondary analysis.

RESULTS

The authors identified five genome-wide significant signals for European Americans and one for African Americans on GAD-2 score. The strongest were on chromosome 3 (rs4603973) near SATB1, a global regulator of gene expression, and on chromosome 6 (rs6557168) near ESR1, which encodes an estrogen receptor. The locus identified on chromosome 7 (rs56226325, MAF=0.17) near MAD1L1 was previously identified in GWASs of bipolar disorder and schizophrenia. The authors replicated these findings in the summary statistics of two major published GWASs for anxiety, and also found evidence of significant genetic correlation between the GAD-2 score results and previous GWASs for anxiety (rg=0.75), depression (rg=0.81), and neuroticism (rg=0.75).

CONCLUSIONS

This is the largest GWAS of anxiety traits to date. The authors identified novel genome-wide significant associations near genes involved with global regulation of gene expression (SATB1) and the estrogen receptor alpha (ESR1). Additionally, the authors identified a locus (MAD1L1) that may have implications for genetic vulnerability across several psychiatric disorders. This work provides new insights into genetic risk mechanisms underpinning anxiety and related psychiatric disorders.

The Genetics of Externalizing Problems

Externalizing problems generally refer to a constellation of behaviors and/or disorders characterized by impulsive action and behavioral disinhibition. Phenotypes on the externalizing spectrum include psychiatric disorders, nonclinical behaviors, and personality characteristics (e.g. alcohol use disorders, other illicit substance use, antisocial behaviors, risky sex, sensation seeking, among others). Research using genetic designs including latent designs from twin and family data and more recent designs using genome-wide data reveal that these behaviors and problems are genetically influenced and largely share a common genetic etiology. Large-scale gene-identification efforts have started to identify robust associations between genetic variants and these phenotypes. However, there is still considerable work to be done. This chapter provides an overview of the current state of research into the genetics of behaviors and disorders on the externalizing spectrum.