Polygenic risk scores for schizophrenia and bipolar disorder associate with addiction

Cross-ancestry genetic investigation of schizophrenia, cannabis use disorder, and tobacco smoking

Individuals with schizophrenia frequently experience co-occurring substance use, including tobacco smoking and heavy cannabis use, and substance use disorders. There is interest in understanding the extent to which these relationships are causal, and to what extent shared genetic factors play a role. We explored the relationships between schizophrenia (Scz; European ancestry N = 161,405; African ancestry N = 15,846), cannabis use disorder (CanUD; European ancestry N = 886,025; African ancestry N = 120,208), and ever-regular tobacco smoking (Smk; European ancestry N = 805,431; African ancestry N = 24,278) using the largest available genome-wide studies of these phenotypes in individuals of African and European ancestries. All three phenotypes were positively genetically correlated (rgs = 0.17-0.62). Genetic instrumental variable analyses suggested the presence of shared heritable factors, but evidence for bidirectional causal relationships was also found between all three phenotypes even after correcting for these shared genetic factors. We identified 327 pleiotropic loci with 439 lead SNPs in the European ancestry data, 150 of which were novel (i.e., not genome-wide significant in the original studies). Of these pleiotropic loci, 202 had lead variants which showed convergent effects (i.e., same direction of effect) on Scz, CanUD, and Smk. Genetic variants convergent across all three phenotypes showed strong genetic correlations with risk-taking, executive function, and several mental health conditions. Our results suggest that both shared genetic factors and causal mechanisms may play a role in the relationship between CanUD, Smk, and Scz, but longitudinal, prospective studies are needed to confirm a causal relationship.

Genome-wide association studies of lifetime and frequency cannabis use in 131,895 individuals

Cannabis is one of the most widely used drugs globally. Decriminalization of cannabis is further increasing cannabis consumption. We performed genome-wide association studies (GWASs) of lifetime (N=131,895) and frequency (N=73,374) of cannabis use. Lifetime cannabis use GWAS identified two loci, one near CADM2 (rs11922956, p=2.40E-11) and another near GRM3 (rs12673181, p=6.90E-09). Frequency of use GWAS identified one locus near CADM2 (rs4856591, p=8.10E-09; r2 =0.76 with rs11922956). Both traits were heritable and genetically correlated with previous GWASs of lifetime use and cannabis use disorder (CUD), as well as other substance use and cognitive traits. Polygenic scores (PGSs) for lifetime and frequency of cannabis use associated cannabis use phenotypes in AllofUs participants. Phenome-wide association study of lifetime cannabis use PGS in a hospital cohort replicated associations with substance use and mood disorders, and uncovered associations with celiac and infectious diseases. This work demonstrates the value of GWASs of CUD transition risk factors.

Heterogeneity analysis provides evidence for a genetically homogeneous subtype of bipolar-disorder

Bipolar Disorder (BD) is a complex disease. It is heterogeneous, both at the phenotypic and genetic level, although the extent and impact of this heterogeneity is not fully understood. One way to assess this heterogeneity is to look for patterns in the subphenotype data, identify a more phenotypically homogeneous set of subjects, and perform a genome-wide association-study (GWAS) and subsequent secondary analyses restricted to this homogeneous subset. Because of the variability in how phenotypic data was collected by the various BD studies over the years, homogenizing the phenotypic data is a challenging task, and so is replication. As members of the Psychiatric Genomics Consortium (PGC), we have access to the raw genotypes of 18,711 BD cases and 29,738 controls. This amount of data makes it possible for us to set aside the intricacies of phenotype and allow the genetic data itself to determine which subjects define a homogeneous genetic subgroup. In this paper, we leverage recent advances in heterogeneity analysis to look for distinct homogeneous genetic BD subgroups (or biclusters) that manifest the broad phenotype we think of as Bipolar Disorder. As our data was generated by 27 studies and genotyped on a variety of platforms (OMEX, Affymetrix, Illumina), we use a biclustering algorithm capable of covariate-correction. Covariate-correction is critical if we wish to distinguish disease-related signals from those which are a byproduct of ancestry, study or genotyping platform. We rely on the raw genotyped data and do not include any data generated through imputation. We first apply this covariate-corrected biclustering algorithm to a cohort of 2524 BD cases and 4106 controls from the Bipolar Disease Research Network (BDRN: OMEX). We find evidence of genetic heterogeneity delineating a statistically significant bicluster comprising a subset of BD cases which exhibits a disease-specific pattern of differential-expression across a subset of SNPs. This pattern replicates across the remaining data-sets collected by the PGC containing 5781/8289 (OMEX), 3581/7591 (Illumina), and 6825/9752(Affymetrix) cases/controls, respectively. This bicluster includes subjects diagnosed with bipolar type-I, as well as subjects diagnosed with bipolar type-II. However, the bicluster is enriched for bipolar type-I over type-II and may represent a collection of correlated genetic risk-factors. By investigating the bicluster-informed polygenic-risk-scoring (PRS), we find that the disease-specific pattern highlighted by the bicluster can be leveraged to eliminate noise from our GWAS analyses and improve not only risk prediction, particularly when using only a relatively small subset (e.g., ~ 1%) of the available SNPs, but also SNP replication. Though our primary focus is only the analysis of disease-related signal, we also identify replicable control-related heterogeneity. Covariate-corrected biclustering of raw genetic data appears to be a promising route for untangling heterogeneity and identifying replicable homogeneous genetic subtypes of complex disease. It may also prove useful in identifying protective effects within the control group. This approach circumvents some of the difficulties presented by subphenotype data collected by meta-analyses or 23 andMe, e.g., missingness, assessment variation, and reliance on self-report.

A reduction in cigarette smoking improves health-related quality of life and does not worsen psychiatric symptoms in individuals with serious mental illness

INTRODUCTION

Individuals with serious mental illness (SMI) smoke cigarettes at a much higher rate than the general population, increasing their risk for medical illnesses and mortality. However, individuals with SMI do not get enough support to quit smoking, partially because of concerns from medical providers that reducing smoking may worsen their symptoms or quality of life.

METHODS

Veterans with SMI and nicotine dependence (n = 178) completed a 12-week smoking cessation trial (parent trial dates: 2010-2014) including assessments of smoking status, psychiatric symptoms (Brief Psychiatric Rating Scale), and quality of life (Lehman Quality of Life Interview-Short Version) at up to four time points: baseline, post-treatment, three-month follow-up, and 9-month follow-up. Bayesian multilevel modeling estimated the impact of changes in the self-reported number of cigarettes per day in the past seven days on psychiatric symptoms and quality of life.

RESULTS

Between subjects, each additional pack of cigarettes smoked per day was associated with a 0.83 point higher score (95%CI: 0.03 to 1.7) on a negative symptoms scale ranging from 0 to 35. Within subjects, each one-pack reduction in the number of cigarettes smoked per day was associated with an improvement of 0.32 (95%CI = 0.12 to 0.54) on the health-related quality of life scale, which ranges from 0 to 7 points. There were no other significant between- or within-subjects effects of smoking on psychiatric symptoms or quality of life.

CONCLUSIONS

Individuals with SMI and their providers should pursue smoking cessation without fear of worsening psychiatric symptoms or quality of life.

Interplay between polygenic risk for mood disorders and stressful life events in bipolar disorder

BACKGROUND

Although genetic and environmental factors are involved in the aetiology of bipolar disorder [BD], studies focused on their interplay are lacking. The current investigation examines interactions and correlations between polygenic risk scores [PRS] for BD and major depressive disorder [MDD] with stressful life events [SLEs] in liability for BD.

METHODS

This study used data from 1715 participants (862 bipolar cases and 853 controls) taken from UK and Canadian samples. The List of Threatening Experiences Questionnaire recorded SLEs that occurred 6 months before interview for controls and 6 months prior to the first (Canadian sample) and worst (UK sample) depressive and manic episodes for bipolar cases. PRS-BD and PRS-MDD were calculated from the Psychiatric Genomics Consortium.

RESULTS

For the worst depressive episode, the PRS-MDD was significantly correlated with total number of SLEs (β = 0.13, 95 % CI:0.04-0.22, p = 0.003) and dependent SLEs (β = 0.09, 95 % CI:0.02-0.16, p = 0.007). After correction for multiple testing nominally significant correlations were detected for PRS-BD with total number of SLEs (β = 0.11, 95 % CI:0.02-0.20, p = 0.015) and dependent SLEs (β = 0.08, 95 % CI:0.01-0.15, p = 0.019). Among bipolar cases, these associations were slightly stronger but were only of nominal significance for total number of SLEs (PRS-MDD: β = 0.19, 95 % CI:0.04-0.35, p = 0.015; PRS-BD: β = 0.16, 95 % CI:0.01-0.32, p = 0.042) and dependent SLEs (PRS-MDD: β = 0.14, 95 % CI:0.03-0.26, p = 0.015; PRS-BD: β = 0.12, 95 % CI:0.004-0.24, p = 0.043). No other significant gene-environment correlations or interactions were found.

LIMITATIONS

Use of a larger sample size would be beneficial.

CONCLUSIONS

The relationship between SLEs and genetic risk for mood disorders may be best explained through correlations rather than interactions.

Cross-ancestry genetic investigation of schizophrenia, cannabis use disorder, and tobacco smoking

Individuals with schizophrenia frequently experience co-occurring substance use, including tobacco smoking and heavy cannabis use, and substance use disorders. There is interest in understanding the extent to which these relationships are causal, and to what extent shared genetic factors play a role. We explored the relationships between schizophrenia (Scz), cannabis use disorder (CanUD), and ever-regular tobacco smoking (Smk) using the largest available genome-wide studies of these phenotypes in individuals of African and European ancestries. All three phenotypes were positively genetically correlated (rgs = 0.17 - 0.62). Causal inference analyses suggested the presence of horizontal pleiotropy, but evidence for bidirectional causal relationships was also found between all three phenotypes even after correcting for horizontal pleiotropy. We identified 439 pleiotropic loci in the European ancestry data, 150 of which were novel (i.e., not genome-wide significant in the original studies). Of these pleiotropic loci, 202 had lead variants which showed convergent effects (i.e., same direction of effect) on Scz, CanUD, and Smk. Genetic variants convergent across all three phenotypes showed strong genetic correlations with risk-taking, executive function, and several mental health conditions. Our results suggest that both horizontal pleiotropy and causal mechanisms may play a role in the relationship between CanUD, Smk, and Scz, but longitudinal, prospective studies are needed to confirm a causal relationship.

Relationship between mood disorders and substance involvement and the shared genetic liabilities: A population-based study in Taiwan

BACKGROUND

This study explored the phenotypic association of mood disorders, including major depressive disorder (MDD) and bipolar disorder (BPD), with a range of substance involvement, including lifetime experience and age at initiation of tobacco, alcohol, and betel nut use. Additionally, we elucidated polygenic risk score (PRS) association.

METHODS

In total, 132,615 community participants were recruited from the Taiwan Biobank. Genome-wide genotyping data were available for 106,806 unrelated individuals, and the PRS for MDD and BPD was calculated. The significance of mood disorders and PRSs associated with substance involvement were evaluated using a linear/logistic regression model with adjustment for potential confounders. Sex differences were assessed.

RESULTS

MDD and BPD were associated with regular alcohol consumption, drinking cessation, tobacco smoking, smoking cessation, betel nut chewing, and earlier onset of drinking. BPD was associated with an earlier onset of smoking. MDD PRS was associated with regular alcohol use (odds ratio [OR] per standard deviation increase in PRS = 1.03, p = 0.018), alcohol cessation (OR = 1.05, p = 0.03), regular tobacco use (OR = 1.08, p < 0.0001), and betel nut chewing (OR = 1.06, p < 0.0001), whereas BPD PRS was not associated with substance use. Phenotypic association strengths between MDD/BPD and regular drinking/smoking and the polygenic association between MDD PRS and regular smoking were larger in females than in males.

LIMITATIONS

Retrospective self-reported MDD/BPD diagnoses and substance involvement.

CONCLUSIONS

Mood disorders were associated with a range of substance involvement. Shared genetic architecture contributed to the co-occurrence of MDD and substance involvement. These findings may help design prevention and cessation strategies for substance use.

Progress and Implications from Genetic Studies of Bipolar Disorder

With the advancements in gene sequencing technologies, including genome-wide association studies, polygenetic risk scores, and high-throughput sequencing, there has been a tremendous advantage in mapping a detailed blueprint for the genetic model of bipolar disorder (BD). To date, intriguing genetic clues have been identified to explain the development of BD, as well as the genetic association that might be applied for the development of susceptibility prediction and pharmacogenetic intervention. Risk genes of BD, such as CACNA1C, ANK3, TRANK1, and CLOCK, have been found to be involved in various pathophysiological processes correlated with BD. Although the specific roles of these genes have yet to be determined, genetic research on BD will help improve the prevention, therapeutics, and prognosis in clinical practice. The latest preclinical and clinical studies, and reviews of the genetics of BD, are analyzed in this review, aiming to summarize the progress in this intriguing field and to provide perspectives for individualized, precise, and effective clinical practice.

Polygenic risk alters the penetrance of monogenic kidney disease

Chronic kidney disease (CKD) is determined by an interplay of monogenic, polygenic, and environmental risks. Autosomal dominant polycystic kidney disease (ADPKD) and COL4A-associated nephropathy (COL4A-AN) represent the most common forms of monogenic kidney diseases. These disorders have incomplete penetrance and variable expressivity, and we hypothesize that polygenic factors explain some of this variability. By combining SNP array, exome/genome sequence, and electronic health record data from the UK Biobank and All-of-Us cohorts, we demonstrate that the genome-wide polygenic score (GPS) significantly predicts CKD among ADPKD monogenic variant carriers. Compared to the middle tertile of the GPS for noncarriers, ADPKD variant carriers in the top tertile have a 54-fold increased risk of CKD, while ADPKD variant carriers in the bottom tertile have only a 3-fold increased risk of CKD. Similarly, the GPS significantly predicts CKD in COL4A-AN carriers. The carriers in the top tertile of the GPS have a 2.5-fold higher risk of CKD, while the risk for carriers in the bottom tertile is not different from the average population risk. These results suggest that accounting for polygenic risk improves risk stratification in monogenic kidney disease.

Polygenic Propensity for Longevity, APOE-ε4 Status, Dementia Diagnosis, and Risk for Cause-Specific Mortality: A Large Population-Based Longitudinal Study of Older Adults

To deepen the understanding of genetic mechanisms influencing mortality risk, we investigated the impact of genetic predisposition to longevity and APOE-ε4, on all-cause mortality and specific causes of mortality. We further investigated the mediating effects of dementia on these relationships. Using data on 7 131 adults aged ≥50 years (mean = 64.7 years, standard deviation [SD] = 9.5) from the English Longitudinal Study of Aging, genetic predisposition to longevity was calculated using the polygenic score approach (PGSlongevity). APOE-ε4 status was defined according to the absence or presence of ε4 alleles. The causes of death were ascertained from the National Health Service central register, which was classified into cardiovascular diseases, cancers, respiratory illness, and all other causes of mortality. Of the entire sample, 1 234 (17.3%) died during an average 10-year follow-up. One-SD increase in PGSlongevity was associated with a reduced risk for all-cause mortality (hazard ratio [HR] = 0.93, 95% confidence interval [CI]: 0.88-0.98, p = .010) and mortalities due to other causes (HR = 0.81, 95% CI: 0.71-0.93, p = .002) in the following 10 years. In gender-stratified analyses, APOE-ε4 status was associated with a reduced risk for all-cause mortality and mortalities related to cancers in women. Mediation analyses estimated that the percent excess risk of APOE-ε4 on other causes of mortality risk explained by the dementia diagnosis was 24%, which increased to 34% when the sample was restricted to adults who were aged ≤75 years old. To reduce the mortality rate in adults who are aged ≥50 years old, it is essential to prevent dementia onset in the general population.

The shared genetic architecture of smoking behaviours and psychiatric disorders: evidence from a population-based longitudinal study in England

BACKGROUND

Considering the co-morbidity of major psychiatric disorders and intelligence with smoking, to increase our understanding of why some people take up smoking or continue to smoke, while others stop smoking without progressing to nicotine dependence, we investigated the genetic propensities to psychiatric disorders and intelligence as determinants of smoking initiation, heaviness of smoking and smoking cessation in older adults from the general population.

RESULTS

Having utilised data from the English Longitudinal Study of Ageing (ELSA), our results showed that one standard deviation increase in MDD-PGS was associated with increased odds of being a moderate-heavy smoker (odds ratio [OR] = 1.11, SE = 0.04, 95%CI = 1.00-1.24, p = 0.028). There were no other significant associations between SZ-PGS, BD-PGS, or IQ-PGS and smoking initiation, heaviness of smoking and smoking cessation in older adults from the general population in the UK.

CONCLUSIONS

Smoking is a behaviour that does not appear to share common genetic ground with schizophrenia, bipolar disorders, and intelligence in older adults, which may suggest that it is more likely to be modifiable by smoking cessation interventions. Once started to smoke, older adults with a higher polygenic predisposition to major depressive disorders are more likely to be moderate to heavy smokers, implying that these adults may require targeted smoking cessation services.

Impaired extinction of operant cocaine in a genetic mouse model of schizophrenia risk

BACKGROUND

Individuals with schizophrenia have high rates of comorbid substance use problems. One potential explanation for this comorbidity is similar neuropathophysiology in substance use and schizophrenia, which may arise from shared genetic risk factors between the two disorders. Here we investigated if genetic risk for schizophrenia could affect drug reward and reinforcement for cocaine in an established mouse model of genetic risk for schizophrenia, the neuregulin 1 transmembrane domain heterozygous (Nrg1 TM HET) mouse.

METHODS

We examined drug-induced locomotor sensitization and conditioned place preference for several cocaine doses (5, 10, 20, 30 mg/kg) in male adult Nrg1 TM HET and wild-type-like (WT) littermates. We also investigated intravenous self-administration of and motivation for cocaine (doses 0.1, 0.5, 1 mg/kg/infusion), as well as extinction and cue-induced reinstatement of cocaine. In a follow-up experiment, we examined self-administration, extinction and cue-induced reinstatement of a natural reward, oral sucrose.

RESULTS

Cocaine preference was similar between Nrg1 TM HET mice and WT littermates at all doses tested. Locomotor sensitization to cocaine was not affected by Nrg1 genotype at any dose. Although self-administration and motivation for cocaine was unaffected, extinction of cocaine self-administration was impaired in Nrg1 TM HET compared to WT controls, and cue-induced reinstatement was greater in Nrg1 mutants in the middle of the reinstatement session. Sucrose self-administration and extinction thereof was not affected by genotype, but inactive lever responding was elevated during cue-induced reinstatement for operant sucrose in Nrg1 TM HET mice compared to WTs.

DISCUSSION

These results suggest impaired response inhibition for cocaine in Nrg1 TM HET mice and suggests Nrg1 mutation may contribute to behaviours which can limit control over cocaine use.

Polygenic risk affects the penetrance of monogenic kidney disease

Background

Chronic kidney disease (CKD) is a genetically complex disease determined by an interplay of monogenic, polygenic, and environmental risks. Most forms of monogenic kidney diseases have incomplete penetrance and variable expressivity. It is presently unknown if some of the variability in penetrance can be attributed to polygenic factors.

Methods

Using the UK Biobank (N=469,835 participants) and the All of Us (N=98,622 participants) datasets, we examined two most common forms of monogenic kidney disorders, autosomal dominant polycystic kidney disease (ADPKD) caused by deleterious variants in the PKD1 or PKD2 genes, and COL4A-associated nephropathy (COL4A-AN caused by deleterious variants in COL4A3, COL4A4, or COL4A5 genes). We used the eMERGE-III electronic CKD phenotype to define cases (estimated glomerular filtration rate (eGFR) <60 mL/min/1.73m2 or kidney failure) and controls (eGFR >90 mL/min/1.73m2 in the absence of kidney disease diagnoses). The effects of the genome-wide polygenic score (GPS) for CKD were tested in monogenic variant carriers and non-carriers using logistic regression controlling for age, sex, diabetes, and genetic ancestry.

Results

As expected, the carriers of known pathogenic and rare predicted loss-of-function variants in PKD1 or PKD2 had a high risk of CKD (ORmeta=17.1, 95% CI: 11.1-26.4, P=1.8E-37). The GPS was comparably predictive of CKD in both ADPKD variant carriers (ORmeta=2.28 per SD, 95%CI: 1.55-3.37, P=2.6E-05) and non-carriers (ORmeta=1.72 per SD, 95% CI=1.69-1.76, P< E-300) independent of age, sex, diabetes, and genetic ancestry. Compared to the middle tertile of the GPS distribution for non-carriers, ADPKD variant carriers in the top tertile had a 54-fold increased risk of CKD, while ADPKD variant carriers in the bottom tertile had only a 3-fold increased risk of CKD. Similarly, the GPS was predictive of CKD in both COL4-AN variant carriers (ORmeta=1.78, 95% CI=1.22-2.58, P=2.38E-03) and non-carriers (ORmeta=1.70, 95%CI: 1.68-1.73 P

Conclusions

Variable penetrance of kidney disease in ADPKD and COL4-AN is partially explained by differences in polygenic risk profiles. Accounting for polygenic factors has the potential to improve risk stratification in monogenic kidney disease and may have implications for genetic counseling.

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Key Words

• APOL1
• GWAS
• chronic kidney disease (CKD)
• polygenic risk score (PRS)

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MESH Headings Collapse

Grants

• OT2 OD026556 NIH HHS
• U2C OD023196 NIH HHS
• OT2 OD026551 NIH HHS
• U24 OD023121 NIH HHS
• OT2 OD026552 NIH HHS
• OT2 OD026549 NIH HHS
• OT2 OD025337 NIH HHS
• OT2 OD025277 NIH HHS
• OT2 OD026555 NIH HHS
• OT2 OD026550 NIH HHS
• OT2 OD026553 NIH HHS
• OT2 OD023205 NIH HHS
• U01 HG008680 NHGRI NIH HHS
• OT2 OD025276 NIH HHS
• OT2 OD026557 NIH HHS
• U24 OD023163 NIH HHS
• OT2 OD023206 NIH HHS
• R01 LM013061 NLM NIH HHS
• U24 OD023176 NIH HHS
• OT2 OD026548 NIH HHS
• OT2 OD025315 NIH HHS
• K25 DK128563 NIDDK NIH HHS
• OT2 OD026554 NIH HHS
• UL1 TR001873 NCATS NIH HHS

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Affiliation(s)

Atlas Khan Division of Nephrology, Dept of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY
Ning Shang Division of Nephrology, Dept of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY
Jordan G. Nestor Division of Nephrology, Dept of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY
Chunhua Weng Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
George Hripcsak Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
Peter C. Harris Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota 55905, USA
Ali G. Gharavi Division of Nephrology, Dept of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY
Krzysztof Kiryluk Division of Nephrology, Dept of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY

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Associating broad and clinically defined polygenic scores for depression with depression-related phenotypes

Twin studies indicate that 30-40% of the disease liability for depression can be attributed to genetic differences. Here, we assess the explanatory ability of polygenic scores (PGS) based on broad- (PGS_BD) and clinical- (PGS_MDD) depression summary statistics from the UK Biobank in an independent sample of adults (N = 210; 100% European Ancestry) who were extensively phenotyped for depression and related neurocognitive traits (e.g., rumination, emotion regulation, anhedonia, and resting frontal alpha asymmetry). The UK Biobank-derived PGS_BD had small associations with MDD, depression severity, anhedonia, cognitive reappraisal, brooding, and suicidal ideation but only the association with suicidal ideation remained statistically significant after correcting for multiple comparisons. Similarly small associations were observed for the PGS_MDD but none remained significant after correcting for multiple comparisons. These findings provide important initial guidance about the expected effect sizes between current UKB PGSs for depression and depression-related neurocognitive phenotypes.

Risk for alcohol use problems in severe mental illness: Interactions with sex and racial/ethnic minority status

BACKGROUND

Alcohol use disorder (AUD) is exceedingly common among individuals with bipolar disorder and schizophrenia. However, studies on alcohol use in psychiatric illness rely largely on population surveys with limited representation of severe mental illness (SMI); schizophrenia and bipolar disorder.

METHODS

Using data from the Genomic Psychiatry Cohort (GPC) (Pato MT, 2013), associations of bipolar disorder and schizophrenia with alcohol use problems were examined in a diverse US based sample, considering the influence of self-described race (African Ancestry (AA), European Ancestry (EA), or Latinx Ancestry (LA)), sex, and tobacco use. Participants answered alcohol use problem items derived from the CAGE instrument, yielding a summed "probable" alcohol use disorder (pAUD) risk score.

RESULTS

This study included 1952 individuals with bipolar disorder with psychosis (BDwP), 409 with bipolar disorder without psychosis (BD), 9218 with schizophrenia (SCZ), and 10,416 unaffected individuals. We found that SMI (BDwP, BD, SCZ) was associated with elevated AUD risk scores (B = 0.223, p < 0.001), an association which was strongest in females, particularly those of AA and LA, and in tobacco users. Schizophrenia was associated with the greatest increase in pAUD score (B = 0.141, p < 0.001). pAUD risk scores were increased among participants with bipolar disorder, with greater increases in BDwP (B = 0.125, p < 0.001) than in BD without psychosis (B = 0.027, p < 0.001).

LIMITATIONS

Limitations include reliance on self-report data, screening items for AUD, voluntary recruitment bias, and differences in race/sex distribution between groups, which were statistically adjusted for in analytic models.

CONCLUSIONS

SMI is associated with risk for AUD, particularly among females from racial minority groups, smokers, and those with psychotic disorders.

Investigation of convergent and divergent genetic influences underlying schizophrenia and alcohol use disorder

BACKGROUND

Alcohol use disorder (AUD) and schizophrenia (SCZ) frequently co-occur, and large-scale genome-wide association studies (GWAS) have identified significant genetic correlations between these disorders.

METHODS

We used the largest published GWAS for AUD (total cases = 77 822) and SCZ (total cases = 46 827) to identify genetic variants that influence both disorders (with either the same or opposite direction of effect) and those that are disorder specific.

RESULTS

We identified 55 independent genome-wide significant single nucleotide polymorphisms with the same direction of effect on AUD and SCZ, 8 with robust effects in opposite directions, and 98 with disorder-specific effects. We also found evidence for 12 genes whose pleiotropic associations with AUD and SCZ are consistent with mediation via gene expression in the prefrontal cortex. The genetic covariance between AUD and SCZ was concentrated in genomic regions functional in brain tissues (p = 0.001).

CONCLUSIONS

Our findings provide further evidence that SCZ shares meaningful genetic overlap with AUD.

Pairwise genetic meta-analyses between schizophrenia and substance dependence phenotypes reveals novel association signals with pharmacological significance

Almost half of individuals diagnosed with schizophrenia also present with a substance use disorder, however, little is known about potential molecular mechanisms underlying this comorbidity. We used genetic analyses to enhance our understanding of the molecular overlap between these conditions. Our analyses revealed a positive genetic correlation between schizophrenia and the following dependence phenotypes: alcohol (r_g = 0.368, SE = 0.076, P = 1.61 × 10^-6), cannabis use disorder (r_g = 0.309, SE = 0.033, P = 1.97 × 10^-20) and nicotine (r_g = 0.117, SE = 0.043, P = 7.0 × 10^-3), as well as drinks per week (r_g = 0.087, SE = 0.021, P = 6.36 × 10^-5), cigarettes per day (r_g = 0.11, SE = 0.024, P = 4.93 × 10^-6) and life-time cannabis use (r_g = 0.234, SE = 0.029, P = 3.74 × 10^-15). We further constructed latent causal variable (LCV) models to test for partial genetic causality and found evidence for a potential causal relationship between alcohol dependence and schizophrenia (GCP = 0.6, SE = 0.22, P = 1.6 × 10^-3). This putative causal effect with schizophrenia was not seen using a continuous phenotype of drinks consumed per week, suggesting that distinct molecular mechanisms underlying dependence are involved in the relationship between alcohol and schizophrenia. To localise the specific genetic overlap between schizophrenia and substance use disorders (SUDs), we conducted a gene-based and gene-set pairwise meta-analysis between schizophrenia and each of the four individual substance dependence phenotypes in up to 790,806 individuals. These bivariate meta-analyses identified 44 associations not observed in the individual GWAS, including five shared genes that play a key role in early central nervous system development. The results from this study further supports the existence of underlying shared biology that drives the overlap in substance dependence in schizophrenia, including specific biological systems related to metabolism and neuronal function.

Nongenetic Factors Associated With Psychotic Experiences Among UK Biobank Participants: Exposome-Wide Analysis and Mendelian Randomization Analysis

Importance

Although hypothesis-driven research has identified several factors associated with psychosis, this one-exposure-to-one-outcome approach fails to embrace the multiplicity of exposures. Systematic approaches, similar to agnostic genome-wide analyses, are needed to identify genuine signals.

Objective

To systematically investigate nongenetic correlates of psychotic experiences through data-driven agnostic analyses and genetically informed approaches to evaluate associations.

Design, Setting, Participants

This cohort study analyzed data from the UK Biobank Mental Health Survey from January 1 to June 1, 2021. An exposome-wide association study was performed in 2 equal-sized split discovery and replication data sets. Variables associated with psychotic experiences in the exposome-wide analysis were tested in a multivariable model. For the variables associated with psychotic experiences in the final multivariable model, the single-nucleotide variant-based heritability and genetic overlap with psychotic experiences using linkage disequilibrium score regression were estimated, and mendelian randomization (MR) approaches were applied to test potential causality. The significant associations observed in 1-sample MR analyses were further tested in multiple sensitivity tests, including collider-correction MR, 2-sample MR, and multivariable MR analyses.

Exposures

After quality control based on a priori criteria, 247 environmental, lifestyle, behavioral, and economic variables.

Main Outcomes and Measures

Psychotic experiences.

Results

The study included 155 247 participants (87 896 [57%] female; mean [SD] age, 55.94 [7.74] years). In the discovery data set, 162 variables (66%) were associated with psychotic experiences. Of these, 148 (91%) were replicated. The multivariable analysis identified 36 variables that were associated with psychotic experiences. Of these, 28 had significant genetic overlap with psychotic experiences. One-sample MR analyses revealed forward associations with 3 variables and reverse associations with 3. Forward associations with ever having experienced sexual assault and pleiotropy of risk-taking behavior and reverse associations without pleiotropy of experiencing a physically violent crime as well as cannabis use and the reverse association with pleiotropy of worrying too long after embarrassment were confirmed in sensitivity tests. Thus, associations with psychotic experiences were found with both well-studied and unexplored multiple correlated variables. For several variables, the direction of the association was reversed in the final multivariable and MR analyses.

Conclusions and Relevance

The findings of this study underscore the need for systematic approaches and triangulation of evidence to build a knowledge base from ever-growing observational data to guide population-level prevention strategies for psychosis.

A Systematic Review of Genetic Polymorphisms Associated with Bipolar Disorder Comorbid to Substance Abuse

It is currently unknown which genetic polymorphisms are involved in substance use disorder (SUD) comorbid with bipolar disorder (BD). The research on polymorphisms in BD comorbid with SUD (BD + SUD) is summarized in this systematic review. We looked for case-control studies that genetically compared adults and adolescents with BD and SUD, healthy controls, and BD without SUD. PRISMA was used to create our protocol, which is PROSPERO-registered (identification: CRD4221270818). The following bibliographic databases were searched indefinitely until December 2021 to identify potentially relevant articles: PubMed, PsycINFO, Scopus, and Web of Science. This systematic review, after the qualitative analysis of the study selection, included 17 eligible articles. In the selected studies, 66 polymorphisms in 29 genes were investigated. The present work delivers a group of potentially valuable genetic polymorphisms associated with BD + SUD: rs11600996 (ARNTL), rs228642/rs228682/rs2640909 (PER3), PONQ192R (PON1), rs945032 (BDKRB2), rs1131339 (NR4A3), and rs6971 (TSPO). It is important to note that none of those findings have been confirmed by two or more studies; thus, we believe that all the polymorphisms identified in this review require additional evidence to be confirmed.

Genome-wide polygenic score to predict chronic kidney disease across ancestries

Chronic kidney disease (CKD) is a common complex condition associated with high morbidity and mortality. Polygenic prediction could enhance CKD screening and prevention; however, this approach has not been optimized for ancestrally diverse populations. By combining APOL1 risk genotypes with genome-wide association studies (GWAS) of kidney function, we designed, optimized and validated a genome-wide polygenic score (GPS) for CKD. The new GPS was tested in 15 independent cohorts, including 3 cohorts of European ancestry (n = 97,050), 6 cohorts of African ancestry (n = 14,544), 4 cohorts of Asian ancestry (n = 8,625) and 2 admixed Latinx cohorts (n = 3,625). We demonstrated score transferability with reproducible performance across all tested cohorts. The top 2% of the GPS was associated with nearly threefold increased risk of CKD across ancestries. In African ancestry cohorts, the APOL1 risk genotype and polygenic component of the GPS had additive effects on the risk of CKD.

Specificity of Psychiatric Polygenic Risk Scores and their Effects on Associated Risk Phenotypes

Background

Polygenic risk scores (PRSs) are indices of genetic liability for illness, but their clinical utility for predicting risk for a specific psychiatric disorder is limited. Genetic overlap among disorders and their effects on allied phenotypes may be a possible explanation, but this has been difficult to quantify given focus on singular disorders and/or allied phenotypes.

Methods

We constructed PRSs for 5 psychiatric disorders (schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorder, attention-deficit/hyperactivity disorder) and 3 nonpsychiatric control traits (height, type II diabetes, irritable bowel disease) in the UK Biobank (N = 31,616) and quantified associations between PRSs and phenotypes allied with mental illness: behavioral (symptoms, cognition, trauma) and brain measures from magnetic resonance imaging. We then evaluated the extent of specificity among PRSs and their effects on these allied phenotypes.

Results

Correlations among psychiatric PRSs replicated previous work, with overlap between schizophrenia and bipolar disorder, which was distinct from overlap between autism spectrum disorder and attention-deficit/hyperactivity disorder; overlap between psychiatric and control PRSs was minimal. There was, however, substantial overlap of PRS effects on allied phenotypes among psychiatric disorders and among psychiatric disorders and control traits, where the extent and pattern of overlap was phenotype specific.

Conclusions

Results show that genetic distinctions between psychiatric disorders and between psychiatric disorders and control traits exist, but this does not extend to their effects on allied phenotypes. Although overlap can be informative, work is needed to construct PRSs that will function at the level of specificity needed for clinical application.

Associations between polygenic risk scores and amplitude of low-frequency fluctuation of inferior frontal gyrus in schizophrenia

Schizophrenia (SCZ) is a serious and complex mental disorder with high heritability. Polygenic risk score (PRS) is a useful tool calculating the accumulating effects of multiple common genetic variants of schizophrenia. The amplitude of low-frequency fluctuation (ALFF) is an efficient index to reflect spontaneous, intrinsic neuronal activity. Aberrant ALFF of brain regions were reported in schizophrenia frequently, but the relationship between PRS and ALFF has not been studied. In the present study, we compared PRS and ALFF in 101 schizophrenia patients and 106 age-matched healthy controls to test their associations with schizophrenia. Then, the correlation of PRS with ALFF was measured to reveal the effect of polygenic risk on brain activity in schizophrenia. We found that schizophrenia patients showed significant differences in PRS and ALFF compared with controls. Twenty-six brain regions showed significant difference of ALFF between schizophrenia cases and controls, of which left inferior frontal gyrus, triangular part (IFGtriang.L) showed increased activity in schizophrenia. PRS-SCZ was positively correlated with ALFF in IFGtriang.L in 57 non-chronic patients. Genes involved in synaptic organization and transmission, especially in glutamatergic synapse, were highly enriched in PRS-SCZ genes, suggesting the dysfunction of synapses in schizophrenia. These results help to understand the molecular mechanism underlying schizophrenia and related brain dysfunction.

Molecular genetics of cocaine use disorders in humans

Drug addiction, one of the major health problems worldwide, is characterized by the loss of control in drug intake, craving, and withdrawal. At the individual level, drugs of abuse produce serious consequences on health and have a negative impact on the family environment and on interpersonal and work relationships. At a wider scale, they have significant socio-economic and public health consequences and they cause delinquency and citizen insecurity. Cocaine, a psychostimulant substance, is one of the most used illicit drugs, especially in America, Western Europe, and Australia. Cocaine use disorders (CUD) are complex multifactorial conditions driven by both genetic and environmental influences. Importantly, not all people who use cocaine develop CUD, and this is due, at least in part, to biological factors that are encoded in the genome of individuals. Acute and repeated use of cocaine induces epigenetic and gene expression changes responsible for the neuronal adaptations and the remodeling of brain circuits that lead to the transition from use to abuse or dependence. The purpose of this review is to delineate such factors, which should eventually help to understand the inter-individual variability in the susceptibility to cocaine addiction. Heritability estimates for CUD are high and genetic risk factors for cocaine addiction have been investigated by candidate gene association studies (CGAS) and genome-wide association studies (GWAS), reviewed here. Also, the high comorbidity that exists between CUD and several other psychiatric disorders is well known and includes phenotypes like schizophrenia, aggression, antisocial or risk-taking behaviors. Such comorbidities are associated with a worse lifetime trajectory, and here we report shared genetic factors that may contribute to them. Gene expression changes and epigenetic modifications induced by cocaine use and chronic abuse in humans are addressed by reviewing transcriptomic studies performed on neuronal cells and on postmortem brains. We report some genes which expression is altered by cocaine that also bear genetic risk variants for the disorder. Finally, we have a glance to the pharmacogenetics of CUD treatments, still in early stages. A better understanding of the genetic underpinnings of CUD will foster the search of effective treatments and help to move forward to personalized medicine.

A polygenic approach to the association between smoking and schizophrenia

Smoking prevalence in schizophrenia is considerably larger than in general population, playing an important role in early mortality. We compared the polygenic contribution to smoking in schizophrenic patients and controls to assess if genetic factors may explain the different prevalence. Polygenic risk scores (PRSs) for smoking initiation and four genetically correlated traits were calculated in 1108 schizophrenic patients (64.4% smokers) and 1584 controls (31.1% smokers). PRSs for smoking initiation, educational attainment, body mass index and age at first birth were associated with smoking in patients and controls, explaining a similar percentage of variance in both groups. Attention-deficit hyperactivity disorder (ADHD) PRS was associated with smoking only in schizophrenia. This association remained significant after adjustment by psychiatric cross-disorder PRS. A PRS combining all the traits was more explanative than smoking initiation PRS alone, indicating that genetic susceptibility to the other traits plays an additional role in smoking behaviour. Smoking initiation PRS was also associated with schizophrenia in the whole sample, but the significance was lost after adjustment for smoking status. This same pattern was observed in the analysis of specific SNPs at the CHRNA5-CHRNA3-CHRNB4 cluster associated with both traits. Overall, the results indicate that the same genetic factors are involved in smoking susceptibility in schizophrenia and in general population and are compatible with smoking acting, directly or indirectly, as a risk factor for schizophrenia that contributes to the high prevalence of smoking in these patients. The contrasting results for ADHD PRS may be related to higher ADHD symptomatology in schizophrenic patients.

Examining pathways between genetic liability for schizophrenia and patterns of tobacco and cannabis use in adolescence

BACKGROUND

It is not clear to what extent associations between schizophrenia, cannabis use and cigarette use are due to a shared genetic etiology. We, therefore, examined whether schizophrenia genetic risk associates with longitudinal patterns of cigarette and cannabis use in adolescence and mediating pathways for any association to inform potential reduction strategies.

METHODS

Associations between schizophrenia polygenic scores and longitudinal latent classes of cigarette and cannabis use from ages 14 to 19 years were investigated in up to 3925 individuals in the Avon Longitudinal Study of Parents and Children. Mediation models were estimated to assess the potential mediating effects of a range of cognitive, emotional, and behavioral phenotypes.

RESULTS

The schizophrenia polygenic score, based on single nucleotide polymorphisms meeting a training-set p threshold of 0.05, was associated with late-onset cannabis use (OR = 1.23; 95% CI = 1.08,1.41), but not with cigarette or early-onset cannabis use classes. This association was not mediated through lower IQ, victimization, emotional difficulties, antisocial behavior, impulsivity, or poorer social relationships during childhood. Sensitivity analyses adjusting for genetic liability to cannabis or cigarette use, using polygenic scores excluding the CHRNA5-A3-B4 gene cluster, or basing scores on a 0.5 training-set p threshold, provided results consistent with our main analyses.

CONCLUSIONS

Our study provides evidence that genetic risk for schizophrenia is associated with patterns of cannabis use during adolescence. Investigation of pathways other than the cognitive, emotional, and behavioral phenotypes examined here is required to identify modifiable targets to reduce the public health burden of cannabis use in the population.

Polygenic Risk Scores for Prediction of Gastric Cancer Based on Bioinformatics Screening and Validation of Functional lncRNA SNPs

INTRODUCTION

Single-nucleotide polymorphisms (SNPs) are used to stratify the risk of gastric cancer. However, no study included gastric cancer-related long noncoding RNA (lncRNA) SNPs into the risk model for evaluation. This study aimed to replicate the associations of 21 lncRNA SNPs and to construct an individual risk prediction model for gastric cancer.

METHODS

The bioinformatics method was used to screen gastric cancer-related lncRNA functional SNPs and verified in population. Gastric cancer risk prediction models were constructed using verified SNPs based on polygenic risk scores (PRSs).

RESULTS

Twenty-one SNPs were screened, and the multivariate unconditional logistic regression analysis showed that 14 lncRNA SNPs were significantly associated with gastric cancer. In the distribution of genetic risk score in cases and controls, the mean value of PRS in cases was higher than that in controls. Approximately 20.1% of the cases was caused by genetic variation (P = 1.9 × 10-34) in optimal PRS model. The individual risk of gastric cancer in the lowest 10% of PRS was 82.1% (95% confidence interval [CI]: 0.102, 0.314) lower than that of the general population. The risk of gastric cancer in the highest 10% of PRS was 5.75-fold that of the general population (95% CI: 3.09, 10.70). The introduction of family history of tumor (area under the curve, 95% CI: 0.752, 0.69-0.814) and Helicobacter pylori infection (area under the curve, 95% CI: 0.773, 0.702-0.843) on the basis of PRS could significantly improve the recognition ability of the model.

DISCUSSION

PRSs based on lncRNA SNPs could identify individuals with high risk of gastric cancer and combined with risk factors could improve the stratification.

Genetic contributions to bipolar disorder: current status and future directions

Bipolar disorder (BD) is a highly heritable mental disorder and is estimated to affect about 50 million people worldwide. Our understanding of the genetic etiology of BD has greatly increased in recent years with advances in technology and methodology as well as the adoption of international consortiums and large population-based biobanks. It is clear that BD is also highly heterogeneous and polygenic and shows substantial genetic overlap with other psychiatric disorders. Genetic studies of BD suggest that the number of associated loci is expected to substantially increase in larger future studies and with it, improved genetic prediction of the disorder. Still, a number of challenges remain to fully characterize the genetic architecture of BD. First among these is the need to incorporate ancestrally-diverse samples to move research away from a Eurocentric bias that has the potential to exacerbate health disparities already seen in BD. Furthermore, incorporation of population biobanks, registry data, and electronic health records will be required to increase the sample size necessary for continued genetic discovery, while increased deep phenotyping is necessary to elucidate subtypes within BD. Lastly, the role of rare variation in BD remains to be determined. Meeting these challenges will enable improved identification of causal variants for the disorder and also allow for equitable future clinical applications of both genetic risk prediction and therapeutic interventions.

Unraveling the Association Between Schizophrenia and Substance Use Disorder-Predictors, Mechanisms and Treatment Modifications: A Systematic Review

Individuals with schizophrenia are particularly vulnerable to substance abuse problems. Comorbidity with substance use disorders (SUDs) frequently results in early death and increased dysfunction observed in schizophrenia. This dual diagnosis can be explained through multiple general mechanisms. Tobacco, alcohol, cannabis, and cocaine are substances widely used by individuals with schizophrenia. This study highlights the predictors, mechanisms responsible for the relationship between substance use disorder and schizophrenia and how it can help with the treatment of both disorders. The publications were rigorously reviewed after being found in multiple databases. The study's inclusion criteria were research published within the last five years, publications written in English, full-text availability, and human studies. A total of ten papers were selected for examination from a total of 9,106 articles found using the search method across several databases. This study follows the rules listed within the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist 2009. The information gathered from these published studies was used to investigate the elements that contribute to the link between schizophrenia and substance abuse. Here, we evaluate a close relationship between schizophrenia and substance use disorders. The articles studied exhibit a bidirectional association between the two disorders in most individuals. From our analysis, the comorbidity between the two disorders is partially due to shared polygenic liability. Individuals with schizophrenia have dysfunctional Mesocorticolimbic brain reward circuits indicating a history of substance use. An underlying genetic vulnerability to schizophrenia may be triggered by extensive cannabis usage at a young age. A combination of psychological and pharmacological interventions for both disorders can significantly improve the outcome.

Genetic overlap and causal associations between smoking behaviours and mental health

Cigarette smoking is a modifiable behaviour associated with mental health. We investigated the degree of genetic overlap between smoking behaviours and psychiatric traits and disorders, and whether genetic associations exist beyond genetic influences shared with confounding variables (cannabis and alcohol use, risk-taking and insomnia). Second, we investigated the presence of causal associations between smoking initiation and psychiatric traits and disorders. We found significant genetic correlations between smoking and psychiatric disorders and adult psychotic experiences. When genetic influences on known covariates were controlled for, genetic associations between most smoking behaviours and schizophrenia and depression endured (but not with bipolar disorder or most psychotic experiences). Mendelian randomization results supported a causal role of smoking initiation on psychiatric disorders and adolescent cognitive and negative psychotic experiences, although not consistently across all sensitivity analyses. In conclusion, smoking and psychiatric disorders share genetic influences that cannot be attributed to covariates such as risk-taking, insomnia or other substance use. As such, there may be some common genetic pathways underlying smoking and psychiatric disorders. In addition, smoking may play a causal role in vulnerability for mental illness.

Structural neuroimaging phenotypes of a novel multi-gene risk score in youth bipolar disorder

BACKGROUND

Bipolar disorder (BD) is among the most heritable psychiatric disorders, particularly in early-onset cases, owing to multiple genes of small effect. Here we examine a multi-gene risk score (MGRS), to address the gap in multi-gene research in early-onset BD.

METHODS

MGRS was derived from 34 genetic variants relevant to neuropsychiatric diseases and related systemic processes. Multiple MGRS were calculated across a spectrum of inclusion p-value thresholds, based on allelic associations with BD. Youth participants (123 BD, 103 healthy control [HC]) of European descent were included, of which 101 participants (58 BD, 43 HC) underwent MRI T1-weighted structural neuroimaging. Hierarchical regressions examined for main effects and MGRS-by-diagnosis interaction effects on 6 regions-of-interest (ROIs). Vertex-wise analysis also examined MGRS-by-diagnosis interactions.

RESULTS

MGRS based on allelic association p≤0.60 was most robust, explaining 6.8% of variance (t(226)=3.46, p=.001). There was an MGRS-by-diagnosis interaction effect on ventrolateral prefrontal cortex surface area (vlPFC; β=.21, p=.0007). Higher MGRS was associated with larger vlPFC surface area in BD vs. HC. There were 8 significant clusters in vertex-wise analyses, primarily in fronto-temporal regions, including vlPFC.

LIMITATIONS

Cross-sectional design, modest sample size.

CONCLUSIONS

There was a diagnosis-by-MGRS interaction effect on vlPFC surface area, a region involved in emotional processing, emotional regulation, and reward response. Vertex-wise analysis also identified several clusters overlapping this region. This preliminary study provides an example of an approach to imaging-genetics that is intermediate between candidate gene and genome-wide association studies, enriched for genetic variants with established relevance to neuropsychiatric diseases.

Genetic Basis of Dual Diagnosis: A Review of Genome-Wide Association Studies (GWAS) Focusing on Patients with Mood or Anxiety Disorders and Co-Occurring Alcohol-Use Disorders

(1) Background: Comorbidity between Alcohol Use Disorders (AUD), mood, and anxiety disorders represents a significant health burden, yet its neurobiological underpinnings are elusive. The current paper reviews all genome-wide association studies conducted in the past ten years, sampling patients with AUD and co-occurring mood or anxiety disorder(s). (2) Methods: In keeping with PRISMA guidelines, we searched EMBASE, Medline/PUBMED, and PsycINFO databases (January 2010 to December 2020), including references of enrolled studies. Study selection was based on predefined criteria and data underwent a multistep revision process. (3) Results: 15 studies were included. Some of them explored dual diagnoses phenotypes directly while others employed correlational analysis based on polygenic risk score approach. Their results support the significant overlap of genetic factors involved in AUDs and mood and anxiety disorders. Comorbidity risk seems to be conveyed by genes engaged in neuronal development, connectivity, and signaling although the precise neuronal pathways and mechanisms remain unclear. (4) Conclusion: given that genes associated with complex traits including comorbid clinical presentations are of small effect, and individually responsible for a very low proportion of the total variance, larger samples consisting of multiple refined comorbid combinations and confirmed by re-sequencing approaches will be necessary to disentangle the genetic architecture of dual diagnosis.

Cigarette smoking as a risk factor for schizophrenia or all non-affective psychoses

BACKGROUND

Smoking tobacco is regarded as an epiphenomenon in patients with schizophrenia when it may be causal. We aimed to examine whether smoking status is related to the onset of schizophrenia or the broader diagnosis of non-affective psychosis, including schizophrenia.

METHODS

We used data from The Health Improvement Network primary care database to identify people aged 15-24 between 1 January 2004 and 31 December 2009. We followed them until the earliest of: first diagnosis of schizophrenia (or psychosis), patient left the practice, practice left THIN, patient died or 31 December 2014.

RESULTS

In men, incidence rates for schizophrenia per 100 000 person years at risk were higher in smoking initiators (non-smoker who became a smoker during the study) than in non-smokers (adjusted IRR 1.94; 95% CI 1.29-2.91) and higher still in smokers (adjusted IRR 3.32; 95% CI 2.67-4.14). Among women, the incidence rate of schizophrenia was higher in smokers than in non-smokers (adjusted IRR 1.50; 95% CI 1.06-2.12), but no higher in smoking initiators than non-smokers. For non-affective psychosis, the pattern was similar for men but more evident in women where psychosis incidence rates were higher in smoking initiators (adjusted IRR 1.90; 95% CI 1.40-2.56) and in smokers (adjusted IRR 2.13; 95% CI 1.76-2.57) than in non-smokers.

CONCLUSIONS

We found an important and strong association between smoking and incidence of schizophrenia. Smoking may increase risk through as yet unknown pathways or smoking may share genetic risk with schizophrenia and non-affective psychoses.

Prevalence of Substance Use among Psychotic Patients and Determining Its Strongest Predictor

Objective: Although comorbidity of psychotic disorders and substance use can lead to increase in mortality, less is known about the outbreak and predictors. Psychotic patients tend to be overlooked during assessment; hence, the possibility of an undertreated or missed condition such as increasing substance use. This investigation aimed to measure the prevalence of substance use in psychotic patients and to survey the powerful predictors.

Method: In a 1-year cross-sectional study, 311 psychotic patients were assessed using the Structured Interview Based on DSM-5 for diagnostic confirmation as well as questions surveying prevalence and possible predictors of substance use.

Results: Prevalence of substance use among psychotic patients was 37.9%. Several variables were identified as factors associated with drug abuse among the psychotic patients. These included male gender, younger age, being currently homeless, a history of imprisonment, and having family history of drug use. The strongest predictors of substance use, however, were family history of drug use, male gender, and being currently homelessness.

Conclusion: Policymakers should note the importance of substance use among psychotic patients. Developing active screening strategies and comprehensive preventive plans, especially in the high-risk population, is suggested.

Smoking and the risk for bipolar disorder: evidence from a bidirectional Mendelian randomisation study

BACKGROUND

There is increasing evidence that smoking is a risk factor for severe mental illness, including bipolar disorder. Conversely, patients with bipolar disorder might smoke more (often) as a result of the psychiatric disorder.

AIMS

We conducted a bidirectional Mendelian randomisation (MR) study to investigate the direction and evidence for a causal nature of the relationship between smoking and bipolar disorder.

METHOD

We used publicly available summary statistics from genome-wide association studies on bipolar disorder, smoking initiation, smoking heaviness, smoking cessation and lifetime smoking (i.e. a compound measure of heaviness, duration and cessation). We applied analytical methods with different, orthogonal assumptions to triangulate results, including inverse-variance weighted (IVW), MR-Egger, MR-Egger SIMEX, weighted-median, weighted-mode and Steiger-filtered analyses.

RESULTS

Across different methods of MR, consistent evidence was found for a positive effect of smoking on the odds of bipolar disorder (smoking initiation ORIVW = 1.46, 95% CI 1.28-1.66, P = 1.44 × 10-8, lifetime smoking ORIVW = 1.72, 95% CI 1.29-2.28, P = 1.8 × 10-4). The MR analyses of the effect of liability to bipolar disorder on smoking provided no clear evidence of a strong causal effect (smoking heaviness betaIVW = 0.028, 95% CI 0.003-0.053, P = 2.9 × 10-2).

CONCLUSIONS

These findings suggest that smoking initiation and lifetime smoking are likely to be a causal risk factor for developing bipolar disorder. We found some evidence that liability to bipolar disorder increased smoking heaviness. Given that smoking is a modifiable risk factor, these findings further support investment into smoking prevention and treatment in order to reduce mental health problems in future generations.

Investigating the effects of genetic risk of schizophrenia on behavioural traits

To characterise the trait-effects of increased genetic risk for schizophrenia, and highlight potential risk mediators, we test the association between schizophrenia polygenic risk scores (PRSs) and 529 behavioural traits (personality, psychological, lifestyle, nutritional) in the UK Biobank. Our primary analysis is performed on individuals aged 38–71 with no history of schizophrenia or related disorders, allowing us to report the effects of schizophrenia genetic risk in the sub-clinical general population. Higher schizophrenia PRSs were associated with a range of traits, including lower verbal-numerical reasoning (P = 6 × 10^–61), higher nervous feelings (P = 1 × 10⁻⁴⁶) and higher self-reported risk-taking (P = 3 × 10⁻³⁸). We follow-up the risk-taking association, hypothesising that the association may be due to a genetic propensity for risk-taking leading to greater migration, urbanicity or drug-taking — reported environmental risk factors for schizophrenia, and all positively associated with risk-taking in these data. Next, to identify potential disorder or medication effects, we compare the PRS–trait associations in the general population to the trait values in 599 medicated and non-medicated individuals diagnosed with schizophrenia in the biobank. This analysis highlights, for example, levels of BMI, physical activity and risk-taking in cases in the opposite directions than expected from the PRS–trait associations in the general population. Our analyses offer simple yet potentially revealing insights into the possible causes of observed trait–disorder associations, which can complement approaches such as Mendelian Randomisation. While we urge caution in causal interpretations in PRS cross-trait studies that are highly powered to detect weak horizontal pleiotropy or population structure, we propose that well-designed polygenic score analyses have the potential to highlight modifiable risk factors that lie on the path between genetic risk and disorder.

Dimensions of Craving Interact with COMT Genotype to Predict Relapse in Individuals with Alcohol Use Disorder Six Months after Treatment

(1) Background: Alcohol use disorder (AUD) is associated with poor medical, psychological, and psychosocial outcomes and approximately 60% of individuals with AUD relapse six months after treatment. Craving is a core aspect of AUD and associated with high risk of relapse. One promising avenue to improve outcomes may be in understanding the relationship between COMT genotype, craving, and treatment outcomes. (2) Methods: To this end, we assessed craving, recent drinking history, and impulsivity in 70 individuals with AUD undergoing a standard course of treatment at a regional Veteran Affairs (VA) medical center. Saliva samples were collected to determine COMT genotype. In this prospective observational study, participants were followed for six months to determine who went on to relapse after treatment. (3) Results: Results revealed a significant interaction between craving and catechol-O-methyltransferse (COMT) genotype in predicting relapse. Post hoc exploratory analyses indicated that Met/Met homozygotes reported the highest levels of craving, and craving was associated with recent drinking history. Among Val/Val homozygotes, who had higher rates of relapse, craving was associated with impulsivity. (4) Conclusions: These associations highlight that specific profiles of psychological and biological factors may be important in understanding which individuals are at highest risk of relapse following treatment. Future studies that build on these findings are warranted.

Cigarette Smoking and Schizophrenia: Etiology, Clinical, Pharmacological, and Treatment Implications

Recent data suggests that the prevalence of smoking in schizophrenia remains high. While reports suggest that smoking increases the risk of developing schizophrenia, the potential causative role of smoking in this relationship needs further investigation. Smokers with schizophrenia are more likely to have more intense positive symptoms and lower cognitive function, but diminished intensity of extrapyramidal side effects than nonsmoking patients with schizophrenia. They were also more likely to exhibit aggressive behaviour compared to nonsmokers, which could suggest higher levels of baseline aggression. The significant cost associated with regular tobacco expenditure can detract from investment in key domains. Large-scale trials have shown that pharmacotherapy for smoking cessation is effective and does not worsen the risk of developing neuropsychiatric symptoms compared to placebo. Electronic cigarette use among schizophrenia patients is high, and there is emerging evidence supportive of its efficacy. Future improvements include large-scale trials assessing the utility, efficacy, and safety of electronic cigarettes in schizophrenia patients.

Expanding the genetic architecture of nicotine dependence and its shared genetics with multiple traits

Cigarette smoking is the leading cause of preventable morbidity and mortality. Genetic variation contributes to initiation, regular smoking, nicotine dependence, and cessation. We present a Fagerström Test for Nicotine Dependence (FTND)-based genome-wide association study in 58,000 European or African ancestry smokers. We observe five genome-wide significant loci, including previously unreported loci MAGI2/GNAI1 (rs2714700) and TENM2 (rs1862416), and extend loci reported for other smoking traits to nicotine dependence. Using the heaviness of smoking index from UK Biobank (N = 33,791), rs2714700 is consistently associated; rs1862416 is not associated, likely reflecting nicotine dependence features not captured by the heaviness of smoking index. Both variants influence nearby gene expression (rs2714700/MAGI2-AS3 in hippocampus; rs1862416/TENM2 in lung), and expression of genes spanning nicotine dependence-associated variants is enriched in cerebellum. Nicotine dependence (SNP-based heritability = 8.6%) is genetically correlated with 18 other smoking traits (rg = 0.40-1.09) and co-morbidities. Our results highlight nicotine dependence-specific loci, emphasizing the FTND as a composite phenotype that expands genetic knowledge of smoking.

The effects of polygenic risk for psychiatric disorders and smoking behaviour on psychotic experiences in UK Biobank

While psychotic experiences are core symptoms of mental health disorders like schizophrenia, they are also reported by 5-10% of the population. Both smoking behaviour and genetic risk for psychiatric disorders have been associated with psychotic experiences, but the interplay between these factors remains poorly understood. We tested whether smoking status, maternal smoking around birth, and number of packs smoked/year were associated with lifetime occurrence of three psychotic experiences phenotypes: delusions (n = 2067), hallucinations (n = 6689), and any psychotic experience (delusions or hallucinations; n = 7803) in 157,366 UK Biobank participants. We next calculated polygenic risk scores for schizophrenia (PRSSCZ), bipolar disorder (PRSBP), major depression (PRSDEP) and attention deficit hyperactivity disorder (PRSADHD) in 144,818 UK Biobank participants of European ancestry to assess whether association between smoking and psychotic experiences was attenuated after adjustment of diagnosis of psychiatric disorders and the PRSs. Finally, we investigated whether smoking exacerbates the effects of genetic predisposition on the psychotic phenotypes in gene-environment interaction models. Smoking status, maternal smoking, and number of packs smoked/year were associated with psychotic experiences (p < 1.77 × 10-5). Except for packs smoked/year, effects were attenuated but remained significant after adjustment for diagnosis of psychiatric disorders and PRSs (p < 1.99 × 10-3). Gene-environment interaction models showed the effects of PRSDEP and PRSADHD (but not PRSSCZ or PRSBP) on delusions (but not hallucinations) were significantly greater in current smokers compared to never smokers (p < 0.002). There were no significant gene-environment interactions for maternal smoking nor for number of packs smoked/year. Our results suggest that both genetic risk of psychiatric disorders and smoking status may have independent and synergistic effects on specific types of psychotic experiences.

Affective and Psychotic Disorders in War-Torn Eastern Part of the Democratic Republic of the Congo: A Cross-Sectional Study

BACKGROUND

There is lack of information about prevalence of affective and psychotic disorders triggered by traumatic events among people living in war-affected regions. This study is aimed at determining the prevalence rate of affective and psychotic disorders and the associated factors in a war-torn eastern part of Democratic Republic of the Congo.

METHODS

This epidemiological cross-sectional descriptive study was carried out from 1^st January 2019 to 31^st December 2019 at Cepima and Muyisa health centers. This study enrolled 344 patients that had experienced traumatic events in Eastern Democratic Republic of the Congo from the 1119 participants, of whom 229 had positive bipolar affective disorder and 115 patients had psychotic disorders.

RESULTS

The results revealed that bipolar affective disorders were two times more than psychotic disorders. Sexual abuse, sudden death of a relative, kidnapping, the physical torture, and childhood trauma were the psychological factors correlated to the occurrence of bipolar affective and psychotic disorders.

CONCLUSIONS

It was concluded that the traumatic experiences were precursors for the occurrence of bipolar affective and psychotic spectrum disorders.

Developing and testing high‐efficacy patient subgroups within a clinical trial using risk scores

There is the potential for high-dimensional information about patients collected in clinical trials (such as genomic, imaging, and data from wearable technologies) to be informative for the efficacy of a new treatment in situations where only a subset of patients benefits from the treatment. The adaptive signature design (ASD) method has been proposed for developing and testing the efficacy of a treatment in a high-efficacy patient group (the sensitive group) using genetic data. The method requires selection of three tuning parameters which may be highly computationally expensive. We propose a variation to the ASD method, the cross-validated risk scores (CVRS) design method, that does not require selection of any tuning parameters. The method is based on computing a risk score for each patient and dividing them into clusters using a nonparametric clustering procedure.We assess the properties of CVRS against the originally proposed cross-validated ASD using simulation data and a real psychiatry trial. CVRS, as assessed for various sample sizes and response rates, has a substantial reduction in the computational time required. In many simulation scenarios, there is a substantial improvement in the ability to correctly identify the sensitive group and the power of the design to detect a treatment effect in the sensitive group.We illustrate the application of the CVRS method on the psychiatry trial.

Association between polygenic liability for schizophrenia and substance involvement: A nationwide population-based study in Taiwan

Schizophrenia and substance involvement frequently co-occur in individuals, and a bidirectional relationship between the two has been proposed; shared underlying genetic factors could be an alternative explanation. This study investigated the genetic overlap between schizophrenia and substance involvement, including tobacco, alcohol and betel nut use. The study subjects were recruited from the Taiwan Biobank, and genome-wide genotyping data was available for 18 327 participants without schizophrenia. We calculated the Psychiatric Genomics Consortium-derived polygenic risk score (PRS) for schizophrenia in each participant. The significance of the schizophrenia PRS associated with substance involvement was evaluated using a regression model with adjustments for gender, age and population stratification components. The modified effect of gender or birth decade was also explored. The schizophrenia PRS was positively associated with lifetime tobacco smoking in women (OR in per SD increase in PRS = 1.12 with 95% CI 1.04-1.20, P = .002), but not in men (OR = 0.99 with 95% CI 0.95-1.04, P = .74), and the gender-PRS interaction reached significance (P = .006). The OR between PRS and lifetime tobacco smoking increased with the birth decade (P of birth decade-PRS interaction = .0002). In women, OR increased from 0.97 (P = .85) for subjects with a birth decade before 1950 to 1.21 (P = .04) for subjects with a birth decade after 1980; in men, the corresponding OR increased from 0.88 (P = .04) to 1.13 (P = .11). There was no association between schizophrenia PRS and alcohol/betel nut use phenotypes. This study provides evidence for the genetic overlap between schizophrenia and tobacco use in women, and this overlap was stronger in the younger population.

Polygenic Risk Scores for Psychiatric Disorders Reveal Novel Clues About the Genetics of Disordered Gambling

Disordered gambling (DG) is a rare but serious condition that results in considerable financial and interpersonal harms. Twin studies indicate that DG is heritable but are silent with respect to specific genes or pathways involved. Existing genomewide association studies (GWAS) of DG have been substantially underpowered. Larger GWAS of other psychiatric disorders now permit calculation of polygenic risk scores (PRSs) that reflect the aggregated effects of common genetic variants contributing risk for the target condition. The current study investigated whether gambling and DG are associated with PRSs for four psychiatric conditions found to be comorbid with DG in epidemiologic surveys: major depressive disorder (MDD), attention-deficit hyperactivity disorder (ADHD), bipolar disorder (BD) and schizophrenia (SCZ). Genotype data and survey responses were analyzed from the Wave IV assessment (conducted in 2008) of the National Longitudinal Study of Adolescent to Adult Health, a representative sample of adolescents recruited in 1994-1995 and followed into adulthood. Among participants classified as having European ancestry based on genetic analysis (N = 5215), 78.4% reported ever having gambled, and 1.3% reported lifetime DG. Polygenic risk for BD was associated with decreased odds of lifetime gambling, OR = 0.93 [0.87, 0.99], p = .045, pseudo-R2(%) = .12. The SCZ PRS was associated with increased odds of DG, OR = 1.54 [1.07, 2.21], p = .02, pseudo-R2(%) = .85. Polygenic risk scores for MDD and ADHD were not related to either gambling outcome. Investigating features common to both SCZ and DG might generate valuable clues about the genetically influenced liabilities to DG.

Impact of Polygenic Risk for Schizophrenia on Cortical Structure in UK Biobank

BACKGROUND

Schizophrenia is a neurodevelopmental disorder with many genetic variants of individually small effect contributing to phenotypic variation. Lower cortical thickness (CT), surface area, and cortical volume have been demonstrated in people with schizophrenia. Furthermore, a range of obstetric complications (e.g., lower birth weight) are consistently associated with an increased risk for schizophrenia. We investigated whether a high polygenic risk score for schizophrenia (PGRS-SCZ) is associated with CT, surface area, and cortical volume in UK Biobank, a population-based sample, and tested for interactions with birth weight.

METHODS

Data were available for 2864 participants (n_male/n_female = 1382/1482; mean age = 62.35 years, SD = 7.40). Linear mixed models were used to test for associations among PGRS-SCZ and cortical volume, surface area, and CT and between PGRS-SCZ and birth weight. Interaction effects of these variables on cortical structure were also tested.

RESULTS

We found a significant negative association between PGRS-SCZ and global CT; a higher PGRS-SCZ was associated with lower CT across the whole brain. We also report a significant negative association between PGRS-SCZ and insular lobe CT. PGRS-SCZ was not associated with birth weight and no PGRS-SCZ × birth weight interactions were found.

CONCLUSIONS

These results suggest that individual differences in CT are partly influenced by genetic variants and are most likely not due to factors downstream of disease onset. This approach may help to elucidate the genetic pathophysiology of schizophrenia. Further investigation in case-control and high-risk samples could help identify any localized effects of PGRS-SCZ, and other potential schizophrenia risk factors, on CT as symptoms develop.

Opioid Addiction, Genetic Susceptibility, and Medical Treatments: A Review

Opioid addiction is a chronic and complex disease characterized by relapse and remission. In the past decade, the opioid epidemic or opioid crisis in the United States has raised public awareness. Methadone, buprenorphine, and naloxone have proven their effectiveness in treating addicted individuals, and each of them has different effects on different opioid receptors. Classic and molecular genetic research has provided valuable information and revealed the possible mechanism of individual differences in vulnerability for opioid addiction. The polygenic risk score based on the results of a genome-wide association study (GWAS) may be a promising tool to evaluate the association between phenotypes and genetic markers across the entire genome. A novel gene editing approach, clustered, regularly-interspaced short palindromic repeats (CRISPR), has been widely used in basic research and potentially applied to human therapeutics such as mental illness; many applications against addiction based on CRISPR are currently under research, and some are successful in animal studies. In this article, we summarized the biological mechanisms of opioid addiction and medical treatments, and we reviewed articles about the genetics of opioid addiction, the promising approach to predict the risk of opioid addiction, and a novel gene editing approach. Further research on medical treatments based on individual vulnerability is needed.

Smoking in schizophrenia: recent findings about an old problem

PURPOSE OF REVIEW

Recent epidemiology, biological and clinical findings correlate high cigarette consumption in patients with schizophrenia, impeding both treatment strategies and the effectiveness of antipsychotics.

RECENT FINDINGS

New data suggests that despite world-wide efforts to curb cigarette consumption, smoking in patients with schizophrenia was still high. Recent reports could not confirm earlier findings regarding smoking's beneficial effects on cognitive dysfunction, however, the association between smoking, positive symptoms and suicidal behavior was revealed. As some patients smoked in an attempt to alleviate extrapyramidal symptoms (EPS) and negative symptoms, the molecular studies shared genetic roots correlating smoking and schizophrenia, revealing that smoking may increase the risk of developing schizophrenia. Preclinical and clinical studies clarified the complex relationship between schizophrenia's pathology and nicotine's effects on the human brain.

SUMMARY

Cigarette smoking continues to adversely affect the health of individuals with schizophrenia. Both smoking and heavy nicotine dependence, given the complex biological findings, might influence symptom severity in patients with schizophrenia. Regardless, ceasing smoking activities is strongly advocated to replace 'self-medication by nicotine' with safer and more effective medications.

Polygenic liability for schizophrenia predicts shifting-specific executive function deficits and tobacco use in a moderate drinking community sample

Individuals with schizophrenia have higher lifetime rates of substance use disorders than the general population, and research suggests high comorbidity rates may be partially explained by shared genetic influences related to common underlying etiology. Moreover, deficits in executive functions are thought to be central to the diagnosis of schizophrenia and are likewise associated with alcohol and tobacco use. The current study examined the associations between schizophrenia polygenic risk scores and tobacco and alcohol use and the mediation of these associations by executive function sub-domains. Results from the Psychiatric Genomics Consortium's meta-analysis of genome-wide association studies of schizophrenia were used to calculate polygenic risk scores in a sample of moderate drinkers. Schizophrenia risk scores were significantly associated with shifting-specific executive function deficits and tobacco use phenotypes. However, risk scores were not significantly associated with alcohol use and executive functions were not significantly associated with either tobacco or alcohol use. These findings extend previous research by suggesting that genetic risk for schizophrenia may be associated with specific sub-domains of executive function as well as smoking. The lack of a relation with alcohol use suggests genetic factors related to schizophrenia and executive functioning may not influence drinking in a non-disordered, social-drinking sample.

Genetic risk for schizophrenia is associated with substance use in emerging adulthood: an event-level polygenic prediction model

BACKGROUND

Emerging adulthood is a peak period of risk for alcohol and illicit drug use. Recent advances in psychiatric genetics suggest that the co-occurrence of substance use and psychopathology arises, in part, from a shared genetic etiology. We sought to extend this research by investigating the influence of genetic risk for schizophrenia on trajectories of four substance use behaviors as they occurred across emerging adulthood.

METHOD

Young adult participants of non-Hispanic European descent provided DNA samples and completed daily reports of substance use for 1 month per year across 4 years (N = 30 085 observations of N = 342 participants). A schizophrenia polygenic score was included in two-level hierarchical linear models designed to test associations between genetic risk for schizophrenia, participant age, and four substance use phenotypes.

RESULTS

Participants with a greater schizophrenia polygenic score experienced greater age-related increases in the likelihood of using substances across emerging adulthood (p < 0.005). Additionally, our results suggest that the polygenic score was positively associated with participants' overall likelihood to engage in illicit drug use but not alcohol-related substance use.

CONCLUSIONS

This study used a novel combination of polygenic prediction and intensive longitudinal methods to characterize the influence of genetic risk for schizophrenia on patterns of age-related change in substance use across emerging adulthood. Results suggest that genetic risk for schizophrenia has developmentally specific effects on substance use behaviors in a non-clinical population of young adults.

Linking Delay Discounting and Substance Use Disorders: Genotypes and Phenotypes

Research supports the idea that "delay discounting," also known as temporal discounting, intertemporal choice, or impulsive choice, is a transdisease process with a strong connection to substance use disorders (SUDs) and other psychopathologies, like attention deficit hyperactivity disorder and depression. This article briefly reviews the evidence used to conclude that delay discounting is heritable and should be considered to be an endophenotype, as well as evidence of its behavioral and genetic associations with SUDs. It also discusses the limitations that should be considered when evaluating the strength of these associations. Finally, this article briefly describes research examining relationships among delay discounting and SUD-associated intermediate phenotypes to better understand the conceptual relationships underlying the links between SUDs and delay discounting, and identifies research gaps that should be addressed.

Genome-wide association meta-analysis of cocaine dependence: Shared genetics with comorbid conditions

Cocaine dependence is a complex psychiatric disorder that is highly comorbid with other psychiatric traits. Twin and adoption studies suggest that genetic variants contribute substantially to cocaine dependence susceptibility, which has an estimated heritability of 65-79%. Here we performed a meta-analysis of genome-wide association studies of cocaine dependence using four datasets from the dbGaP repository (2085 cases and 4293 controls, all of them selected by their European ancestry). Although no genome-wide significant hits were found in the SNP-based analysis, the gene-based analysis identified HIST1H2BD as associated with cocaine-dependence (10% FDR). This gene is located in a region on chromosome 6 enriched in histone-related genes, previously associated with schizophrenia (SCZ). Furthermore, we performed LD Score regression analysis with comorbid conditions and found significant genetic correlations between cocaine dependence and SCZ, ADHD, major depressive disorder (MDD) and risk taking. We also found, through polygenic risk score analysis, that all tested phenotypes are significantly associated with cocaine dependence status: SCZ (R² = 2.28%; P = 1.21e-26), ADHD (R² = 1.39%; P = 4.5e-17), risk taking (R² = 0.60%; P = 2.7e-08), MDD (R² = 1.21%; P = 4.35e-15), children's aggressive behavior (R² = 0.3%; P = 8.8e-05) and antisocial behavior (R² = 1.33%; P = 2.2e-16). To our knowledge, this is the largest reported cocaine dependence GWAS meta-analysis in European-ancestry individuals. We identified suggestive associations in regions that may be related to cocaine dependence and found evidence for shared genetic risk factors between cocaine dependence and several comorbid psychiatric traits. However, the sample size is limited and further studies are needed to confirm these results.