Multi-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes.

Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviours and although strides have been made using genome-wide association studies to identify risk variants, most variants identified have been for nicotine consumption, rather than TUD. Here we leveraged four US biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records) in 653,790 individuals (495,005 European, 114,420 African American and 44,365 Latin American) and data from UK Biobank (ncombined = 898,680). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviours in children and hundreds of medical outcomes, including HIV infection, heart disease and pain. This work furthers our biological understanding of TUD and establishes electronic health records as a source of phenotypic information for studying the genetics of TUD.

Genetic contribution to the comorbidity between attention-deficit/hyperactivity disorder and substance use disorders.

We characterized the genetic architecture of the attention-deficit hyperactivity disorder-substance use disorder (ADHD-SUD) relationship by investigating genetic correlation, causality, pleiotropy, and common polygenic risk. Summary statistics from genome-wide association studies (GWAS) were used to investigate ADHD (Neff = 51,568), cannabis use disorder (CanUD, Neff = 161,053), opioid use disorder (OUD, Neff = 57,120), problematic alcohol use (PAU, Neff = 502,272), and problematic tobacco use (PTU, Neff = 97,836). ADHD, CanUD, and OUD GWAS meta-analyses included cohorts with case definitions based on different diagnostic criteria. PAU GWAS combined information related to alcohol use disorder, alcohol dependence, and the items related to alcohol problematic consequences assessed by the alcohol use disorders identification test. PTU GWAS was generated a multi-trait analysis including information regarding Fagerström Test for Nicotine Dependence and cigarettes per day. Linkage disequilibrium score regression analyses indicated positive genetic correlation with CanUD, OUD, PAU, and PTU. Genomic structural equation modeling showed that these genetic correlations were related to two latent factors: one including ADHD, CanUD, and PTU and the other with OUD and PAU. The evidence of a causal effect of PAU and PTU on ADHD was stronger than the reverse in the two-sample Mendelian randomization analysis. Conversely, similar strength of evidence was found between ADHD and CanUD. CADM2 rs62250713 was a pleiotropic SNP between ADHD and all SUDs. We found seven, one, and twenty-eight pleiotropic variants between ADHD and CanUD, PAU, and PTU, respectively. Finally, OUD, CanUD, and PAU PRS were associated with increased odds of ADHD. Our findings demonstrated the contribution of multiple pleiotropic mechanisms to the comorbidity between ADHD and SUDs.

Pleiotropy and genetically inferred causality linking multisite chronic pain to substance use disorders.

Individuals suffering from chronic pain develop substance use disorders (SUDs) more often than others. Understanding the shared genetic influences underlying the comorbidity between chronic pain and SUDs will lead to a greater understanding of their biology. Genome-wide association statistics were obtained from the UK Biobank for multisite chronic pain (MCP, Neffective = 387,649) and from the Million Veteran Program and the Psychiatric Genomics Consortium meta-analyses for alcohol use disorder (AUD, Neffective = 296,974), cannabis use disorder (CanUD, Neffective = 161,053), opioid use disorder (OUD, Neffective = 57,120), and problematic tobacco use (PTU, Neffective = 270,120). SNP-based heritability was estimated for each of the traits and genetic correlation (rg) analyses were performed to assess MCP-SUD pleiotropy. Bidirectional Mendelian Randomization analyses evaluated possible causal relationships. Finally, to identify and characterize individual loci, we performed a genome-wide pleiotropy analysis and a brain-wide analysis using imaging phenotypes available from the UK Biobank. MCP was positively genetically correlated with AUD (rg = 0.26, p = 7.55 × 10-18), CanUD (rg = 0.37, p = 8.21 × 10-37), OUD (rg = 0.20, p = 1.50 × 10-3), and PTU (rg = 0.29, p = 8.53 × 10-12). Although the MR analyses supported bi-directional relationships, MCP had larger effects on AUD (pain-exposure: beta = 0.18, p = 8.21 × 10-4; pain-outcome: beta = 0.07, p = 0.018), CanUD (pain-exposure: beta = 0.58, p = 2.70 × 10-6; pain-outcome: beta = 0.05, p = 0.014) and PTU (pain-exposure: beta = 0.43, p = 4.16 × 10-8; pain-outcome: beta = 0.09, p = 3.05 × 10-6) than the reverse. The genome-wide analysis identified two SNPs pleiotropic between MCP and all SUD investigated: IHO1 rs7652746 (ppleiotropy = 2.69 × 10-8), and CADM2 rs1248857 (ppleiotropy = 1.98 × 10-5). In the brain-wide analysis, rs7652746 was associated with multiple cerebellum and amygdala imaging phenotypes. When analyzing MCP pleiotropy with each SUD separately, we found 25, 22, and 4 pleiotropic variants for AUD, CanUD, and OUD, respectively. To our knowledge, this is the first large-scale study to provide evidence of potential causal relationships and shared genetic mechanisms underlying MCP-SUD comorbidity.

Machine Learning of Functional Connectivity to Biotype Alcohol and Nicotine Use Disorders.

BACKGROUND: Magnetic resonance imaging provides noninvasive tools to investigate alcohol use disorder (AUD) and nicotine use disorder (NUD) and neural phenotypes for genetic studies. A data-driven transdiagnostic approach could provide a new perspective on the neurobiology of AUD and NUD. METHODS: Using samples of individuals with AUD (n = 140), individuals with NUD (n = 249), and healthy control participants (n = 461) from the UK Biobank, we integrated clinical, neuroimaging, and genetic markers to identify biotypes of AUD and NUD. We partitioned participants with AUD and NUD based on resting-state functional connectivity (FC) features associated with clinical metrics. A multitask artificial neural network was trained to evaluate the cluster-defined biotypes and jointly infer AUD and NUD diagnoses. RESULTS: Three biotypes-primary NUD, mixed NUD/AUD with depression and anxiety, and mixed AUD/NUD-were identified. Multitask classifiers incorporating biotype knowledge achieved higher area under the curve (AUD: 0.76, NUD: 0.74) than single-task classifiers without biotype differentiation (AUD: 0.61, NUD: 0.64). Cerebellar FC features were important in distinguishing the 3 biotypes. The biotype of mixed NUD/AUD with depression and anxiety demonstrated the largest number of FC features (n = 5), all related to the visual cortex, that significantly differed from healthy control participants and were validated in a replication sample (p < .05). A polymorphism in TNRC6A was associated with the mixed AUD/NUD biotype in both the discovery (p = 7.3 × 10-5) and replication (p = 4.2 × 10-2) sets. CONCLUSIONS: Biotyping and multitask learning using FC features can characterize the clinical and genetic profiles of AUD and NUD and help identify cerebellar and visual circuit markers to differentiate the AUD/NUD group from the healthy control group. These markers support a new growing body of literature.

Multi-ancestry genome-wide association study of cannabis use disorder yields insight into disease biology and public health implications.

As recreational use of cannabis is being decriminalized in many places and medical use widely sanctioned, there are growing concerns about increases in cannabis use disorder (CanUD), which is associated with numerous medical comorbidities. Here we performed a genome-wide association study of CanUD in the Million Veteran Program (MVP), followed by meta-analysis in 1,054,365 individuals (ncases = 64,314) from four broad ancestries designated by the reference panel used for assignment (European n = 886,025, African n = 123,208, admixed American n = 38,289 and East Asian n = 6,843). Population-specific methods were applied to calculate single nucleotide polymorphism-based heritability within each ancestry. Statistically significant single nucleotide polymorphism-based heritability for CanUD was observed in all but the smallest population (East Asian). We discovered genome-wide significant loci unique to each ancestry: 22 in European, 2 each in African and East Asian, and 1 in admixed American ancestries. A genetically informed causal relationship analysis indicated a possible effect of genetic liability for CanUD on lung cancer risk, suggesting potential unanticipated future medical and psychiatric public health consequences that require further study to disentangle from other known risk factors such as cigarette smoking.

GWAS Meta-Analysis of Suicide Attempt: Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors.

OBJECTIVE: Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide association studies (GWASs) recently discovered and cross-validated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS meta-analysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures. METHODS: This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry admixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and genetic causal proportion analyses. RESULTS: Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values <5×10-8. These loci were mostly intergenic and implicated DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2. The multi-ancestry SNP-based heritability estimate of SA was 5.7% on the liability scale (SE=0.003, p=5.7×10-80). Significant brain tissue gene expression and drug set enrichment were observed. There was shared genetic variation of SA with attention deficit hyperactivity disorder, smoking, and risk tolerance after conditioning SA on both major depressive disorder and posttraumatic stress disorder. Genetic causal proportion analyses implicated shared genetic risk for specific health factors. CONCLUSIONS: This multi-ancestry analysis of suicide attempt identified several loci contributing to risk and establishes significant shared genetic covariation with clinical phenotypes. These findings provide insight into genetic factors associated with suicide attempt across ancestry admixture populations, in veteran and civilian populations, and in attempt versus death.

Genome-wide association study of antisocial personality disorder diagnostic criteria provides evidence for shared risk factors across disorders.

INTRODUCTION: While progress has been made in determining the genetic basis of antisocial behaviour, little progress has been made for antisocial personality disorder (ASPD), a condition that often co-occurs with other psychiatric conditions including substance use disorders, attention deficit hyperactivity disorder (ADHD), and anxiety disorders. This study aims to improve the understanding of the genetic risk for ASPD and its relationship with other disorders and traits. METHODS: We conducted a genome-wide association study (GWAS) of the number of ASPD diagnostic criteria data from 3217 alcohol-dependent participants recruited in the UK (UCL, N = 644) and the USA (Yale-Penn, N = 2573). RESULTS: We identified rs9806493, a chromosome 15 variant, that showed a genome-wide significant association ( Z -score = -5.501, P = 3.77 × 10 -8 ) with ASPD criteria. rs9806493 is an eQTL for SLCO3A1 (Solute Carrier Organic Anion Transporter Family Member 3A1), a ubiquitously expressed gene with strong expression in brain regions that include the anterior cingulate and frontal cortices. Polygenic risk score analysis identified positive correlations between ASPD and smoking, ADHD, depression traits, and posttraumatic stress disorder. Negative correlations were observed between ASPD PRS and alcohol intake frequency, reproductive traits, and level of educational attainment. CONCLUSION: This study provides evidence for an association between ASPD risk and SLCO3A1 and provides insight into the genetic architecture and pleiotropic associations of ASPD.

Association Patterns of Antisocial Personality Disorder across Substance Use Disorders.

There is a high prevalence of antisocial personality disorder (ASPD) in individuals affected by substance use disorders (SUD). However, there is limited information on the specific patterns of association of ASPD with SUD severity and specific SUD diagnostic criteria. We investigated the association of alcohol, cannabis, cocaine, opioid, and tobacco use disorders (AUD, CanUD, CocUD, OUD, and TUD, respectively) in 1,660 individuals with ASPD and 6,640 controls matched by sex (24% female), age, and racial/ethnic background in a sample ascertained for addiction-related traits. Generalized linear regressions were used to test the association of ASPD with the five DSM-5 SUD diagnoses, their severity (i.e., mild, moderate, severe), and their individual diagnostic criteria. We found that ASPD is associated with the diagnosis and severity of AUD (Odds Ratio, ORs=1.89 and 1.25), CanUD (ORs=2.13 and 1.32), and TUD (ORs=1.50 and 1.21) ( ps <.003). Of the specific diagnostic criteria, the "hazardous use" criterion showed the strongest association with ASPD across the five SUDs investigated (from OR TUD =1.88 to OR CanUD =1.37). However, when criteria of different SUDs were included in the same model, ASPD was independently associated only with TUD "hazardous use" and CocUD "attempts to quit". Attempting to quit cocaine was inversely related to the presence of ASPD and remained significant (OR=0.57, 95% confidence interval = 0.36-0.89) after controlling for interactive effects with sex. The current work provides novel insights into how different SUDs, their severity, and their diagnostic criteria associate with ASPD, potentially furthering our understanding of the impact of polysubstance addiction on mental health.

Polysubstance addiction patterns among 7,989 individuals with cocaine use disorder.

To characterize polysubstance addiction (PSA) patterns of cocaine use disorder (CoUD), we performed a latent class analysis (LCA) in 7,989 participants with a lifetime DSM-5 diagnosis of CoUD. This analysis identified three PSA subgroups among CoUD participants (i.e., low, 17%; intermediate, 38%; high, 45%). While these subgroups varied by age, sex, and racial-ethnic distribution (p < 0.001), there was no difference with respect to education or income (p > 0.05). After accounting for sex, age, and race-ethnicity, the CoUD subgroup with high PSA had higher odds of antisocial personality disorder (OR = 21.96 vs. 6.39, difference-p = 8.08✕10-6), agoraphobia (OR = 4.58 vs. 2.05, difference-p = 7.04✕10-4), mixed bipolar episode (OR = 10.36 vs. 2.61, difference-p = 7.04✕10-4), posttraumatic stress disorder (OR = 11.54 vs. 5.86, difference-p = 2.67✕10-4), antidepressant medication use (OR = 13.49 vs. 8.02, difference-p = 1.42✕10-4), and sexually transmitted diseases (OR = 5.92 vs. 3.38, difference-p = 1.81✕10-5) than the low-PSA CoUD subgroup. These findings underscore the importance of modeling PSA severity and comorbidities when examining the clinical, molecular, and neuroimaging correlates of CoUD.

Identifying genetic loci and phenomic associations of substance use traits: A multi-trait analysis of GWAS (MTAG) study.

BACKGROUND AND AIMS: Genome-wide association studies (GWAS) of opioid use disorder (OUD) and cannabis use disorder (CUD) have lagged behind those of alcohol use disorder (AUD) and smoking, where many more loci have been identified. We sought to identify novel loci for substance use traits (SUTs) in both African- (AFR) and European- (EUR) ancestry individuals to enhance our understanding of the traits' genetic architecture. DESIGN: We used multi-trait analysis of GWAS (MTAG) to analyze four SUTs in EUR subjects (OUD, CUD, AUD and smoking initiation [SMKinitiation]), and three SUTs in AFR subjects (OUD, AUD and smoking trajectory [SMKtrajectory]). We conducted gene-set and protein-protein interaction analyses and calculated polygenic risk scores (PRS) in two independent samples. SETTING: This study was conducted in the United States. PARTICIPANTS: A total of 5692 EUR and 4918 AFR individuals in the Yale-Penn sample and 29 054 EUR and 10 265 AFR individuals in the Penn Medicine BioBank sample. FINDINGS: MTAG identified genome-wide significant (GWS) single nucleotide polymorphisms (SNPs) for all four traits in EUR: 41 SNPs in 36 loci for OUD; 74 SNPs in 60 loci for CUD; 63 SNPs in 52 loci for AUD; and 183 SNPs in 144 loci for SMKinitiation. MTAG also identified GWS SNPs in AFR: 2 SNPs in 2 loci for OUD; 3 SNPs in 3 loci for AUD; and 1 SNP in 1 locus for SMKtrajectory. In the Yale-Penn sample, the MTAG-derived PRS consistently yielded more significant associations with both the corresponding substance use disorder diagnosis and multiple related phenotypes than the GWAS-derived PRS. CONCLUSIONS: Multi-trait analysis of genome-wide association studies boosted the number of loci found for substance use traits, identifying genes not previously linked to any substance, and increased the power of polygenic risk scores. Multi-trait analysis of genome-wide association studies can be used to identify novel associations for substance use, especially those for which the samples are smaller than those for historically legal substances.

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

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

Multivariate genome-wide association meta-analysis of over 1 million subjects identifies loci underlying multiple substance use disorders.

Genetic liability to substance use disorders can be parsed into loci that confer general or substance-specific addiction risk. We report a multivariate genome-wide association meta-analysis that disaggregates general and substance-specific loci for published summary statistics of problematic alcohol use, problematic tobacco use, cannabis use disorder, and opioid use disorder in a sample of 1,025,550 individuals of European descent and 92,630 individuals of African descent. Nineteen independent SNPs were genome-wide significant (P < 5e-8) for the general addiction risk factor (addiction-rf), which showed high polygenicity. Across ancestries, PDE4B was significant (among other genes), suggesting dopamine regulation as a cross-substance vulnerability. An addiction-rf polygenic risk score was associated with substance use disorders, psychopathologies, somatic conditions, and environments associated with the onset of addictions. Substance-specific loci (9 for alcohol, 32 for tobacco, 5 for cannabis, 1 for opioids) included metabolic and receptor genes. These findings provide insight into genetic risk loci for substance use disorders that could be leveraged as treatment targets.

Multi-ancestry meta-analysis of tobacco use disorder prioritizes novel candidate risk genes and reveals associations with numerous health outcomes.

Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviors, and although strides have been made using genome-wide association studies (GWAS) to identify risk variants, the majority of variants identified have been for nicotine consumption, rather than TUD. We leveraged five biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records, EHR) in 898,680 individuals (739,895 European, 114,420 African American, 44,365 Latin American). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviors in children, and hundreds of medical outcomes, including HIV infection, heart disease, and pain. This work furthers our biological understanding of TUD and establishes EHR as a source of phenotypic information for studying the genetics of TUD.

Does polygenic risk for substance-related traits predict ages of onset and progression of symptoms?

BACKGROUND AND AIMS: Genetic risk can influence disease progression. We measured the impact of genetic risk for substance use disorders (SUDs) on substance use onset and progression of symptoms. DESIGN, SETTING, PARTICIPANTS: Using findings from genome-wide association studies (GWASs) of alcohol use disorder (AUD), opioid use disorder (OUD) and smoking trajectory (SMK) as discovery samples, we calculated polygenic risk scores (PRSs) in a deeply phenotyped independent target sample. Participants in the target sample were recruited from 2000 to 2020 from US inpatient or outpatient settings or through advertisements and comprised 5692 European-ancestry individuals (EUR) (56.2% male) and 4918 African-ancestry individuals (AFR) (54.9% male). MEASUREMENTS: This study measured age of first substance use, regular use, reported problems and dependence diagnosis and progression from regular use to onset of problems and dependence for alcohol, opioids and smoking. We examined the contribution of PRS to each milestone and progression measure. FINDINGS: EUR and males reported an earlier onset and shorter progression times than AFR and females, respectively. Among EUR, higher AUD PRS predicted earlier onset and more rapid progression to alcohol-related milestones (P < 0.001). Although the AUD PRS was a stronger moderator of problem onset among females (P = 0.017), it was more predictive of the progression to problems among males (P = 0.005). OUD and SMK PRS in EUR also predicted earlier onset of the respective milestones (P < 0.001). Among AFR, where power is lower due to the smaller discovery sample, AUD PRS predicted age of regular alcohol use (P = 0.039) and dependence (P = 0.001) and progression from regular use to diagnosis (P = 0.045), while SMK PRS predicted earlier age of initiation (P = 0.036). CONCLUSIONS: Genetic risk for SUDs appears to predict substance use milestones and symptom progression among European-ancestry individuals and, to a lesser extent, African-ancestry individuals.

Peripheral and Central Iron Measures in Alcohol Use Disorder and Aging: A Quantitative Susceptibility Mapping Pilot Study.

Chronic excessive alcohol use has neurotoxic effects, which may contribute to cognitive decline and the risk of early-onset dementia. Elevated peripheral iron levels have been reported in individuals with alcohol use disorder (AUD), but its association with brain iron loading has not been explored. We evaluated whether (1) serum and brain iron loading are higher in individuals with AUD than non-dependent healthy controls and (2) serum and brain iron loading increase with age. A fasting serum iron panel was obtained and a magnetic resonance imaging scan with quantitative susceptibility mapping (QSM) was used to quantify brain iron concentrations. Although serum ferritin levels were higher in the AUD group than in controls, whole-brain iron susceptibility did not differ between groups. Voxel-wise QSM analyses revealed higher susceptibility in a cluster in the left globus pallidus in individuals with AUD than controls. Whole-brain iron increased with age and voxel-wise QSM indicated higher susceptibility with age in various brain areas including the basal ganglia. This is the first study to analyze both serum and brain iron loading in individuals with AUD. Larger studies are needed to examine the effects of alcohol use on iron loading and its associations with alcohol use severity, structural and functional brain changes, and alcohol-induced cognitive impairments.

Polysubstance addiction and psychiatric, somatic comorbidities among 7,989 individuals with cocaine use disorder: a latent class analysis.

Aims: We performed a latent class analysis (LCA) in a sample ascertained for addiction phenotypes to investigate cocaine use disorder (CoUD) subgroups related to polysubstance addiction (PSA) patterns and characterized their differences with respect to psychiatric and somatic comorbidities. Design: Cross-sectional study. Setting: United States. Participants: Adult participants aged 18-76, 39% female, 47% African American, 36% European American with a lifetime DSM-5 diagnosis of CoUD (N=7,989) enrolled in the Yale-Penn cohort. The control group included 2,952 Yale-Penn participants who did not meet for alcohol, cannabis, cocaine, opioid, or tobacco use disorders. Measurements: Psychiatric disorders and related traits were assessed via the Semi-structured Assessment for Drug Dependence and Alcoholism. These features included substance use disorders (SUD), family history of substance use, sociodemographic information, traumatic events, suicidal behaviors, psychopathology, and medical history. LCA was conducted using diagnoses and diagnostic criteria of alcohol, cannabis, opioid, and tobacco use disorders. Findings: Our LCA identified three subgroups of PSA (i.e., low, 17%; intermediate, 38%; high, 45%) among 7,989 CoUD participants. While these subgroups varied by age, sex, and racial-ethnic distribution (p<0.001), there was no difference on education or income (p>0.05). After accounting for sex, age, and race-ethnicity, the CoUD subgroup with high PSA had higher odds of antisocial personality disorder (OR=21.96 vs. 6.39, difference-p=8.08×10 -6 ), agoraphobia (OR=4.58 vs. 2.05, difference-p=7.04×10 -4 ), mixed bipolar episode (OR=10.36 vs. 2.61, difference-p=7.04×10 -4 ), posttraumatic stress disorder (OR=11.54 vs. 5.86, difference-p=2.67×10 -4 ), antidepressant medication use (OR=13.49 vs. 8.02, difference-p=1.42×10 -4 ), and sexually transmitted diseases (OR=5.92 vs. 3.38, difference-p=1.81×10 -5 ) than the low-PSA CoUD subgroup. Conclusions: We found different patterns of PSA in association with psychiatric and somatic comorbidities among CoUD cases within the Yale-Penn cohort. These findings underscore the importance of modeling PSA severity and comorbidities when examining the clinical, molecular, and neuroimaging correlates of CoUD.

Molecular Imaging of Pulmonary Inflammation in Users of Electronic and Combustible Cigarettes: A Pilot Study.

Electronic cigarette (EC) use has increased dramatically, particularly among adolescents and young adults, and, like cigarette use, can cause pulmonary inflammation and increase the risk of lung disease. Methods: This preliminary study used PET with 18F-6-(1/2)(2-fluoro-propyl)-4-methylpyridin-2-amine (18F-NOS) to quantify inducible nitric oxide synthase expression to characterize oxidative stress and inflammation in the lungs in vivo in 3 age- and sex-matched groups: 5 EC users, 5 cigarette smokers, and 5 controls who had never smoked or vaped. Results: EC users showed greater 18F-NOS nondisplaceable binding potential (BPND) than cigarette smokers (P = 0.03) and controls (P = 0.01), whereas BPND in cigarette smokers did not differ from that in controls (P > 0.1). 18F-NOS lung tissue delivery and inducible nitric oxide synthase distribution volume did not significantly differ among groups. Although there were no group differences in peripheral inflammatory biomarker concentrations, 18F-NOS BPND correlated with the proinflammatory cytokine tumor necrosis factor-α concentrations (rs = 0.87, P = 0.05) in EC users. Additionally, when EC users and cigarette smokers were pooled together, number of vaping episodes or cigarettes per day correlated with interleukin-6 levels (rs = 0.86, P = 0.006). Conclusion: This is the first PET imaging study to compare lung inflammation between EC and cigarette users in vivo. We found preliminary evidence that EC users have greater pulmonary inflammation than cigarette smokers and controls, with a positive association between pulmonary and peripheral measures of inflammation.

Phenome-wide Association Analysis of Substance Use Disorders in a Deeply Phenotyped Sample.

BACKGROUND: Substance use disorders (SUDs) are associated with a variety of co-occurring psychiatric disorders and other SUDs, which partly reflects genetic pleiotropy. Polygenic risk scores (PRSs) and phenome-wide association studies are useful in evaluating pleiotropic effects. However, the comparatively low prevalence of SUDs in population samples and the lack of detailed information available in electronic health records limit these data sets' informativeness for such analyses. METHODS: We used the deeply phenotyped Yale-Penn sample (n = 10,610 with genetic data; 46.3% African ancestry, 53.7% European ancestry) to examine pleiotropy for 4 major substance-related traits: alcohol use disorder, opioid use disorder, smoking initiation, and lifetime cannabis use. The sample includes both affected and control subjects interviewed using the Semi-Structured Assessment for Drug Dependence and Alcoholism, a comprehensive psychiatric interview. RESULTS: In African ancestry individuals, PRS for alcohol use disorder, and in European individuals, PRS for alcohol use disorder, opioid use disorder, and smoking initiation were associated with their respective primary DSM diagnoses. These PRSs were also associated with additional phenotypes involving the same substance. Phenome-wide association study analyses of PRS in European individuals identified associations across multiple phenotypic domains, including phenotypes not commonly assessed in phenome-wide association study analyses, such as family environment and early childhood experiences. CONCLUSIONS: Smaller, deeply phenotyped samples can complement large biobank genetic studies with limited phenotyping by providing greater phenotypic granularity. These efforts allow associations to be identified between specific features of disorders and genetic liability for SUDs, which help to inform our understanding of the pleiotropic pathways underlying them.

Integrating human brain proteomic data with genome-wide association study findings identifies novel brain proteins in substance use traits.

Despite the identification of a growing number of genetic risk loci for substance use traits (SUTs), the impact of these loci on protein abundance and the potential utility of relevant proteins as therapeutic targets are unknown. We conducted a proteome-wide association study (PWAS) in which we integrated human brain proteomes from discovery (Banner; N = 152) and validation (ROSMAP; N = 376) datasets with genome-wide association study (GWAS) summary statistics for 4 SUTs. The 4 samples comprised GWAS of European-ancestry individuals for smoking initiation [Smk] (N = 1,232,091), alcohol use disorder [AUD] (N = 313,959), cannabis use disorder [CUD] (N = 384,032), and opioid use disorder [OUD] (N = 302,585). We conducted transcriptome-wide association studies (TWAS) with human brain transcriptomic data to examine the overlap of genetic effects at the proteomic and transcriptomic levels and characterize significant genes through conditional, colocalization, and fine-mapping analyses. We identified 27 genes (Smk = 21, AUD = 3, CUD = 2, OUD = 1) that were significantly associated with cis-regulated brain protein abundance. Of these, 7 showed evidence for causality (Smk: NT5C2, GMPPB, NQO1, RHOT2, SRR and ACTR1B; and AUD: CTNND1). Cis-regulated transcript levels for 8 genes (Smk = 6, CUD = 1, OUD = 1) were associated with SUTs, indicating that genetic loci could confer risk for these SUTs by modulating both gene expression and proteomic abundance. Functional studies of the high-confidence risk proteins identified here are needed to determine whether they are modifiable targets and useful in developing medications and biomarkers for these SUTs.

Genome-wide meta-analysis of alcohol use disorder in East Asians.

Alcohol use disorder (AUD) is a leading cause of death and disability worldwide. Genome-wide association studies (GWAS) have identified ~30 AUD risk genes in European populations, but many fewer in East Asians. We conducted GWAS and genome-wide meta-analysis of AUD in 13,551 subjects with East Asian ancestry, using published summary data and newly genotyped data from five cohorts: (1) electronic health record (EHR)-diagnosed AUD in the Million Veteran Program (MVP) sample; (2) DSM-IV diagnosed alcohol dependence (AD) in a Han Chinese-GSA (array) cohort; (3) AD in a Han Chinese-Cyto (array) cohort; and (4) two AD Thai cohorts. The MVP and Thai samples included newly genotyped subjects from ongoing recruitment. In total, 2254 cases and 11,297 controls were analyzed. An AUD polygenic risk score was analyzed in an independent sample with 4464 East Asians (Genetic Epidemiology Research in Adult Health and Aging (GERA)). Phenotypes from survey data and ICD-9-CM diagnoses were tested for association with the AUD PRS. Two risk loci were detected: the well-known functional variant rs1229984 in ADH1B and rs3782886 in BRAP (near the ALDH2 gene locus) are the lead variants. AUD PRS was significantly associated with days per week of alcohol consumption (beta = 0.43, SE = 0.067, p = 2.47 × 10-10) and nominally associated with pack years of smoking (beta = 0.09, SE = 0.05, p = 4.52 × 10-2) and ever vs. never smoking (beta = 0.06, SE = 0.02, p = 1.14 × 10-2). This is the largest GWAS of AUD in East Asians to date. Building on previous findings, we were able to analyze pleiotropy, but did not identify any new risk regions, underscoring the importance of recruiting additional East Asian subjects for alcohol GWAS.