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There is increasing recognition of the association between loneliness and social isolation (LNL-ISO) with schizophrenia. Here, we demonstrate significant LNL-ISO polygenic score prediction on schizophrenia in an independent case-control sample (N=3,488). We then dissect schizophrenia predisposing variation into subsets of variants based on their effect on LNL-ISO. Genetic variation with concordant effects in both phenotypes show significant SNP-based heritability enrichment, higher polygenic predictive ability in females and positive covariance with other mental disorders such as depression, anxiety, attention-deficit hyperactivity, alcohol use disorder, and autism. Conversely, genetic variation with discordant effects is only predictive in males and negatively correlated with those disorders. This correlation pattern is not observed for bipolar and obsessive-compulsive disorders. Mendelian randomization analyses demonstrate a plausible bi-directional causal relationship between LNL-ISO and schizophrenia, with a greater effect of LNL-ISO liability on schizophrenia. These results illustrate the genetic footprint of LNL-ISO on schizophrenia and suggest its role as a potential target for early intervention.

Genetics plays an important role in alcohol abuse/dependence. Its heritability has been estimated as 45-65%. Rare copy number variations (CNVs) have been confirmed as relevant genetic factors in other neuropsychiatric disorders, such as autism spectrum disorders, schizophrenia, epilepsy, or Tourette syndrome. In the present study, we analyzed the role of rare CNVs affecting exons of coding genes in a sample from Northwest Spain genotyped using the Illumina Infinium PsychArray Beadchip. After rigorous genotyping quality control procedure, 712 patients with alcohol abuse or dependence and 804 controls were used for CNV detection. CNV calling was performed using PennCNV and cnvPartition, and analyses were restricted to CNVs of at least 100 kb and including at least 10 single nucleotide polymorphisms. Logistic regression was used to test for the effect of CNV as well as number of genes affected by CNVs on case/control status, after adjustment for demographic and experimental covariates. We have found an excess of deletions (p = 0.008) and genes affected by deletions (p = 0.017) in cases. This effect was restricted to the 14.8% of affected genes that are intolerant to loss-of-function mutations (gene count p = 0.009). The importance of this subset of genes is emerging in other psychiatric disorders of neurodevelopmental origin, suggesting that disturbance in neurodevelopment mediated by genetic alterations may be a risk factor for alcohol use disorder.

Background: High alcohol consumption and alcohol dependence are only partly genetically correlated and they differ considerably in their correlations with other traits. The existence of genetic correlation among alcohol dependence and psychiatric disorders may be attributed to the presence of a general psychopathology factor, the p factor. This study investigates the relationship of polygenic risk to general psychopathology and to high alcohol consumption on alcohol dependence. Methods: Participants were 524 alcohol-dependent patients and 729 controls. Polygenic risk scores (PRS) were computed for alcohol consumption (drinks per week) and nine psychiatric disorders. Principal component analysis (PCA) applied to the psychiatric PRS was used to calculate the first principal component as a proxy of the polygenic p factor. Results: Both the polygenic p factor and the drinks per week PRS were associated with alcohol dependence in our sample. Both variables are only weakly correlated, contributing additively to the risk for alcohol dependence. Sensitivity analyses showed that the polygenic p factor was also associated with alcohol dependence in the subset of patients without any psychiatric or substance use comorbidity. Conclusions: Polygenic risk for alcohol dependence can be split at least into two components, involved in general psychopathology and high alcohol consumption. The first component of PCA based on PRS for different psychiatric disorders allows estimation of the contribution of the polygenic p factor to alcohol dependence. The pleiotropic effects of genetic variants across psychiatric disorders are mainly manifested as alcohol dependence in some patients.

Background Alcohol is the most commonly used and abused substance. Addictions to alcohol and other legal/illicit drugs are heritable disorders influenced by a large number of variants of small effect, frequently being a comorbidity of other psychiatric disorders. This comorbidity between a mental illness and a Substance Use Disorder (SUD) is consistently contributing to an increased disability in individuals. In spite of this evidence of important comorbidity, shared genetic factors remain partially understudied. Previous GWAS of SUD showed evidence of genetic overlap with schizophrenia, bipolar disorder and major depressive disorder. We tested individual associations using Polygenic Risk Scores (PRS) from the Psychiatric Genomics Consortium's Cross-Disorder meta-analysis as discovery samples, and each of the five psychiatric disorders included in the study (ADHD, AUT, BIP, MDD, and SCZ), including 2014 PGC schizophrenia mega-analysis results, and, as target sample, a 1144 individuals case/control sample of alcohol abuse/dependence from Galicia, northwest Spain. Methods A total of 572 substance dependent patients were included. Inclusion criteria were: age between 18 and 65, born in Galicia and follow DSM-IV criteria for dependence of at least one substance and abuse/dependence of other substance. The substances registered in the study were: alcohol, tobacco, cannabis, cocaine, opiates, hypnotics, stimulants, hallucinogens and solvents. Most patients (N=540) were diagnosed with alcohol abuse/dependence. A total number of 604 controls from Galicia were included (mean age at recruitment: 40.26, SD: 10.70). DNA was extracted from blood samples and genotyping was performed using Illumina Infinium PsychArray. Variant imputation was executed with SHAPEIT and IMPUTE2, and PRS models were derived from the summary statistics of the PGC cross-disorder meta-analysis (CROSS) and 2014 PGC schizophrenia mega-analysis (SCZ2). Extensive data cleaning and Quality Control (QC) was employed. SNPs within the extended MHC region were excluded from part of the analysis. Associations between every PRS model and our data were tested using logistics regression. Results After QC and imputation, a total number of 503 alcohol cases and 587 controls remained (728 males and 362 females) and genotypic data remained in a total number of 6294324 SNPs. Covariates were included in regression analysis for correction (missing genotyping rate, significant MDS dimensions, sex and age). General CROSS-disorder PRSs (5 disorders included) showed a strong association with alcohol dependence (P=7.39e-06, ΔR=2%). After analyzing each disease separately, significant results were found in bipolar disorder (P=0.0064, ΔR=0.7%) and schizophrenia (P=7.06e-05, ΔR=1.5%). A consistent result was achieved using the greater sample of SCZ2 were obtained a consistent (P=4.49e-10, ΔR=4.1%). SCZ2 and general CROSS-disorders results are robust after Bonferroni multiple test correction (7 thresholds and 7 pathologies employed). Discussion The use of a greater sample in SCZ2 improves results in schizophrenia, showing the consistency of these in this pathology. Moreover, the variability percent explained is high considering previous data of shared genetic susceptibility between schizophrenia and other psychiatric disorders. Despite the fact that the sample used in major depression disorder was bigger than the one in bipolar disorder, these results were not significant. It is necessary to consider that a fraction of PGC individuals show comorbidity with SUDs. As evidenced in this study, an increase in the number of PGC discovery individuals sample will improve the ability to detect this shared genetic susceptibility.

Common single-nucleotide polymorphisms (SNPs) account for a large proportion of the heritability of obsessive-compulsive disorder (OCD). Co-ocurrence of OCD and schizophrenia is commoner than expected based on their respective prevalences, complicating the clinical management of patients. This study addresses two main objectives: to identify particular genes associated with OCD by SNP-based and gene-based tests; and to test the existence of a polygenic risk shared with schizophrenia. The primary analysis was an exon-focused genome-wide association study of 370 OCD cases and 443 controls from Spain. A polygenic risk model based on the Psychiatric Genetics Consortium schizophrenia data set (PGC-SCZ2) was tested in our OCD data. A polygenic risk model based on our OCD data was tested on previous data of schizophrenia from our group. The most significant association at the gene-based test was found at DNM3 (P=7.9 × 10(-5)), a gene involved in synaptic vesicle endocytosis. The polygenic risk model from PGC-SCZ2 data was strongly associated with disease status in our OCD sample, reaching its most significant value after removal of the major histocompatibility complex region (lowest P=2.3 × 10(-6), explaining 3.7% of the variance). The shared polygenic risk was confirmed in our schizophrenia data. In conclusion, DNM3 may be involved in risk to OCD. The shared polygenic risk between schizophrenia and OCD may be partially responsible for the frequent comorbidity of both disorders, explaining epidemiological data on cross-disorder risk. This common etiology may have clinical implications. The study was supported by Fundación María José Jove, Fondo Europeo de Desarrollo Regional (FEDER), Xunta de Galicia; and by grants from the Instituto de Salud Carlos III FIS PI13/01136 to AC, CP11/00163 to JC, PI13/00918 to JMM, PI14/00413 to PA; the Generalitat de Catalunya AGAUR 2014 SGR-1138; the Spanish MINIECO SAF2013-49108- R Plan Estatal; and the European Commission 7th Framework Program, Project N. 262055 (ESGI) to XE. LD is supported by a Severo Ochoa fellowship of the Spanish MINIECO.

Genetic susceptibility to substance use disorders (SUDs) is partially shared between substances. Heritability of any substance dependence, estimated as 54%, is partly explained by additive effects of common variants. Comorbidity between SUDs and other psychiatric disorders is frequent. The present study aims to analyze the additive role of common variants in this comorbidity using polygenic scores (PGSs) based on genome-wide association study discovery samples of schizophrenia (SCZ), bipolar disorder, attention-deficit/hyperactivity disorder, autism spectrum disorder, major depressive disorder and anxiety disorders, available from large consortia. PGSs were calculated for 534 patients meeting DSM-IV criteria for dependence of a substance and abuse/dependence of another substance between alcohol, tobacco, cannabis, cocaine, opiates, hypnotics, stimulants, hallucinogens and solvents; and 587 blood donors from the same population, Iberians from Galicia, as controls. Significance of the PGS and percentage of variance explained were calculated by logistic regression. Using discovery samples of similar size, significant associations with SUDs were detected for SCZ PGS. SCZ PGS explained more variance in SUDs than in most psychiatric disorders. Cross-disorder PGS based on five psychiatric disorders was significant after adjustment for the effect of SCZ PGS. SCZ PGS was significantly higher in women than in men abusing alcohol. Our findings indicate that SUDs share genetic susceptibility with SCZ to a greater extent than with other psychiatric disorders, including externalizing disorders such as attention-deficit/hyperactivity disorder. Women have lower probability to develop substance abuse/dependence than men at similar PGS probably because of a higher social pressure against excessive drug use in women.