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Background and Aims: The use of cannabis has previously been linked to both depression and self‐harm; however, the role of genetics in this relationship is unclear. This study aimed to estimate the phenotypic and genetic associations between cannabis use and depression and self‐harm. Design Cross‐sectional data collected through UK Biobank were used to test the phenotypic association between cannabis use, depression and self‐harm. UK Biobank genetic data were then combined with consortia genome‐wide association study summary statistics to further test the genetic relationships between these traits using LD score regression, polygenic risk scoring and Mendelian randomization methods. Setting: United Kingdom, with additional international consortia data. Participants: A total of 126 291 British adults aged between 40 and 70 years, recruited into UK Biobank. Measurements Phenotypic outcomes were life‐time history of cannabis use (including initial and continued cannabis use), depression (including single‐episode and recurrent depression) and self‐harm. Genome‐wide genetic data were used and assessment centre, batch and the first six principal components were included as key covariates when handling genetic data. Findings In UK Biobank, cannabis use is associated with an increased likelihood of depression [odds ratio (OR) = 1.64, 95% confidence interval (CI) = 1.59–1.70] and self‐harm (OR = 2.85, 95% CI = 2.69–3.01). The strength of this phenotypic association is stronger when more severe trait definitions of cannabis use and depression are considered. Using consortia genome‐wide summary statistics, significant genetic correlations are seen between cannabis use and depression [rg = 0.289, standard error (SE) = 0.036]. Polygenic risk scores for cannabis use and depression explain a small but significant proportion of variance in cannabis use, depression and self‐harm within a UK Biobank target sample. However, two‐sample Mendelian randomization analyses were not significant. Conclusions: Cannabis use appeared to be both phenotypically and genetically associated with depression and self‐harm. Limitations in statistical power mean that conclusions could not be made on the direction of causality between these traits. [ABSTRACT FROM AUTHOR]

Despite over 400 peer-reviewed structural MRI publications documenting neuroanatomic abnormalities in bipolar disorder and schizophrenia, the confounding effects of head motion and the regional specificity of these defects are unclear. Using a large cohort of individuals scanned on the same research dedicated MRI with broadly similar protocols, we observe reduced cortical thickness indices in both illnesses, though less pronounced in bipolar disorder. While schizophrenia ( n = 226) was associated with wide-spread surface area reductions, bipolar disorder ( n = 227) and healthy comparison subjects ( n = 370) did not differ. We replicate earlier reports that head motion (estimated from time-series data) influences surface area and cortical thickness measurements and demonstrate that motion influences a portion, but not all, of the observed between-group structural differences. Although the effect sizes for these differences were small to medium, when global indices were covaried during vertex-level analyses, between-group effects became nonsignificant. This analysis raises doubts about the regional specificity of structural brain changes, possible in contrast to functional changes, in affective and psychotic illnesses as measured with current imaging technology. Given that both schizophrenia and bipolar disorder showed cortical thickness reductions, but only schizophrenia showed surface area changes, and assuming these measures are influenced by at least partially unique sets of biological factors, then our results could indicate some degree of specificity between bipolar disorder and schizophrenia. Hum Brain Mapp 38:3757-3770, 2017. © 2017 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Background and aims While the prevalence of major depression is elevated among cannabis users, the role of genetics in this pattern of comorbidity is not clear. This study aimed to estimate the heritability of cannabis use and major depression, quantify the genetic overlap between these two traits and localize regions of the genome that segregate in families with cannabis use and major depression. Design Family-based univariate and bivariate genetic analysis. Setting San Antonio, Texas, USA. Participants Genetics of Brain Structure and Function study (GOBS) participants: 1284 Mexican Americans from 75 large multi-generation families and an additional 57 genetically unrelated spouses. Measurements Phenotypes of life-time history of cannabis use and major depression, measured using the semistructured MINI-Plus interview. Genotypes measured using ~1 M single nucleotide polymorphisms (SNPs) on Illumina BeadChips. A subselection of these SNPs were used to build multi-point identity-by-descent matrices for linkage analysis. Findings Both cannabis use [ h2 = 0.614, P = 1.00 × 10−6, standard error (SE) = 0.151] and major depression ( h2 = 0.349, P = 1.06 × 10−5, SE = 0.100) are heritable traits, and there is significant genetic correlation between the two (ρg = 0.424, P = 0.0364, SE = 0.195). Genome-wide linkage scans identify a significant univariate linkage peak for major depression on chromosome 22 [logarithm of the odds (LOD) = 3.144 at 2 centimorgans (cM)], with a suggestive peak for cannabis use on chromosome 21 (LOD = 2.123 at 37 cM). A significant pleiotropic linkage peak influencing both cannabis use and major depression was identified on chromosome 11 using a bivariate model (LOD = 3.229 at 112 cM). Follow-up of this pleiotropic signal identified a SNP 20 kb upstream of NCAM1 (rs7932341) that shows significant bivariate association ( P = 3.10 × 10−5). However, this SNP is rare (seven minor allele carriers) and does not drive the linkage signal observed. Conclusions There appears to be a significant genetic overlap between cannabis use and major depression among Mexican Americans, a pleiotropy that appears to be localized to a region on chromosome 11q23 that has been linked previously to these phenotypes. [ABSTRACT FROM AUTHOR]