Search

Aims and Method: Questions often follow the suicide of someone who presented to general adult psychiatry (GAP) when expressing suicidal thoughts: 'Why were they not admitted, or managed differently, when they said they were suicidal?' Answering these questions requires knowledge of the prevalence of suicidal ideation in patients presenting to GAP. Therefore, we determined the general clinical characteristics, including suicidal ideation, of a large sample of patients presenting to a GAP emergency assessment service or referred as non-emergencies to a GAP service., Results: Suicidal ideation was very common, being present in 76.4% of emergency presentations and 33.4% of non-emergency referrals. It was very weakly associated with suicide, varied between different diagnostic categories, and previous assessment by GAP did not appear to affect it. The suicide rate during the contingent episode of care was estimated as 66 per 100 000 episodes., Clinical Implications: This, and other evidence, shows that suicide cannot be predicted with an accuracy that is useful for clinical decision-making. This is not widely appreciated but has serious consequences for patients and healthcare resources.

Background: Preterm birth can lead to impaired language development. This study aimed to predict language outcomes at 2 years corrected gestational age (CGA) for children born preterm., Methods: We analysed data from 89 preterm neonates (median GA 29 weeks) who underwent diffusion MRI (dMRI) at term-equivalent age and language assessment at 2 years CGA using the Bayley-III. Feature selection and a random forests classifier were used to differentiate typical versus delayed (Bayley-III language composite score <85) language development., Results: The model achieved balanced accuracy: 91%, sensitivity: 86%, and specificity: 96%. The probability of language delay at 2 years CGA is increased with: increasing values of peak width of skeletonized fractional anisotropy (PSFA), radial diffusivity (PSRD), and axial diffusivity (PSAD) derived from dMRI; among twins; and after an incomplete course of, or no exposure to, antenatal corticosteroids. Female sex and breastfeeding during the neonatal period reduced the risk of language delay., Conclusions: The combination of perinatal clinical information and MRI features leads to accurate prediction of preterm infants who are likely to develop language deficits in early childhood. This model could potentially enable stratification of preterm children at risk of language dysfunction who may benefit from targeted early interventions., Impact: A combination of clinical perinatal factors and neonatal DTI measures of white matter microstructure leads to accurate prediction of language outcome at 2 years corrected gestational age following preterm birth. A model that comprises clinical and MRI features that has potential to be scalable across centres. It offers a basis for enhancing the power and generalizability of diagnostic and prognostic studies of neurodevelopmental disorders associated with language impairment. Early identification of infants who are at risk of language delay, facilitating targeted early interventions and support services, which could improve the quality of life for children born preterm., (© 2021. Crown.)

STratifying Resilience and Depression Longitudinally (STRADL) is a population-based study built on the Generation Scotland: Scottish Family Health Study (GS:SFHS) resource. The aim of STRADL is to subtype major depressive disorder (MDD) on the basis of its aetiology, using detailed clinical, cognitive, and brain imaging assessments. The GS:SFHS provides an important opportunity to study complex gene-environment interactions, incorporating linkage to existing datasets and inclusion of early-life variables for two longitudinal birth cohorts. Specifically, data collection in STRADL included: socio-economic and lifestyle variables; physical measures; questionnaire data that assesses resilience, early-life adversity, personality, psychological health, and lifetime history of mood disorder; laboratory samples; cognitive tests; and brain magnetic resonance imaging. Some of the questionnaire and cognitive data were first assessed at the GS:SFHS baseline assessment between 2006-2011, thus providing longitudinal measures relevant to the study of depression, psychological resilience, and cognition. In addition, routinely collected historic NHS data and early-life variables are linked to STRADL data, further providing opportunities for longitudinal analysis. Recruitment has been completed and we consented and tested 1,188 participants., Competing Interests: Competing interests: ISP-V and MRM are co-directors of Jericoe Ltd, a company that designs software for the assessment and modification of emotion recognition., (Copyright: © 2021 Habota T et al.)

Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.

Microglia, the immune cells of the brain, are important for neurodevelopment and have been hypothesized to play a role in the pathogenesis of schizophrenia (SCZ). Although previous postmortem studies pointed toward presence of microglial activation, this view has been challenged by more recent hypothesis-driven and hypothesis-free analyses. The aim of the present study is to further understand the observed microglial changes in SCZ. We first performed a detailed meta-analysis on studies that analyzed microglial cell density, microglial morphology, and expression of microglial-specific markers. We then further explored findings from the temporal cortex by performing immunostainings and qPCRs on an additional dataset. A random effect meta-analysis showed that the density of microglial cells was unaltered in SCZ (ES: 0.144 95% CI: 0.102 to 0.390, p = .250), and clear changes in microglial morphology were also absent. The expression of several microglial specific genes, such as CX3CR1, CSF1R, IRF8, OLR1, and TMEM119 was decreased in SCZ (ES: -0.417 95% CI: -0.417 to -0.546, p < .0001), consistent with genome-wide transcriptome meta-analysis results. These results indicate a change in microglial phenotype rather than density, which was validated with the use of TMEM119/Iba1 immunostainings on temporal cortex of a separate cohort. Changes in microglial gene expression were overlapping between SCZ and other psychiatric disorders, but largely opposite from changes reported in Alzheimer's disease. This distinct microglial phenotype provides a crucial molecular hallmark for future research into the role of microglia in SCZ and other psychiatric disorders., (© 2021 The Authors. Glia published by Wiley Periodicals LLC.)

Competing Interests: Declaration of competing interest The authors declare no potential conflict of interest.

STratifying Resilience and Depression Longitudinally (STRADL) is a population-based study built on the Generation Scotland: Scottish Family Health Study (GS:SFHS) resource. The aim of STRADL is to subtype major depressive disorder (MDD) on the basis of its aetiology, using detailed clinical, cognitive, and brain imaging assessments. The GS:SFHS provides an important opportunity to study complex gene-environment interactions, incorporating linkage to existing datasets and inclusion of early-life variables for two longitudinal birth cohorts. Specifically, data collection in STRADL included: socio-economic and lifestyle variables; physical measures; questionnaire data that assesses resilience, early-life adversity, personality, psychological health, and lifetime history of mood disorder; laboratory samples; cognitive tests; and brain magnetic resonance imaging. Some of the questionnaire and cognitive data were first assessed at the GS:SFHS baseline assessment between 2006-2011, thus providing longitudinal measures of depression and resilience. Similarly, routine NHS data and early-life variables are linked to STRADL data, further providing opportunities for longitudinal analysis. Recruitment has been completed and we consented and tested 1,188 participants., Competing Interests: Competing interests: ISP-V and MRM are co-directors of Jericoe Ltd, a company that designs software for the assessment and modification of emotion recognition., (Copyright: © 2019 Habota T et al.)

Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10 -4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10 -8 ) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder.

Objectives: Antidepressants are the most commonly prescribed psychiatric medication but concern has been raised about significant increases in their usage in high income countries. We aimed to quantify antidepressant prevalence, incidence, adherence and predictors of use in the adult population., Methods: The study record-linked administrative prescribing and morbidity data to the Generation Scotland cohort ( N = 11,052), between 2009 and 2016. Prevalence and incidence of any antidepressant use was determined. Antidepressant adherence was measured using Proportion of Days Covered and Medication Possession Ratio. Time-to-event analysis for incident antidepressant use within 5 years of Generation Scotland: Scottish Family Health Study (GS:SFHS) recruitment was performed to reveal patient-level predictors of use., Results: Almost one-third (28.0%, 95%CI 26.9-29.1) of the adults in our sample were prescribed at least one antidepressant in the 5-year period 2012-2016. There was a 36.2% increase in annual prevalence between 2010 and 2016. Incidence was 2.4(2.1-2.7)% per year. The majority of antidepressant episodes (57.6%) were greater than 9 months duration and adherence was generally high (69.0% with Proportion of Days Covered >80%). Predictors of new antidepressant use included history of affective disorder, being female, physical comorbidities, higher neuroticism scores, and lower cognitive function scores., Conclusions: Antidepressant prevalence is greater than previously reported but incidence remains relatively stable. We found the majority of antidepressant episodes to be of relatively long duration with good estimated adherence. Our study supports the hypothesis that increased long-term use among existing (and returning) users, along with wider ranges of indications for antidepressants, has significantly increased the prevalence of these medications.

Stress is associated with poorer physical and mental health. To improve our understanding of this link, we performed genome-wide association studies (GWAS) of depressive symptoms and genome-wide by environment interaction studies (GWEIS) of depressive symptoms and stressful life events (SLE) in two UK population-based cohorts (Generation Scotland and UK Biobank). No SNP was individually significant in either GWAS, but gene-based tests identified six genes associated with depressive symptoms in UK Biobank (DCC, ACSS3, DRD2, STAG1, FOXP2 and KYNU; p < 2.77 × 10 -6 ). Two SNPs with genome-wide significant GxE effects were identified by GWEIS in Generation Scotland: rs12789145 (53-kb downstream PIWIL4; p = 4.95 × 10 -9 ; total SLE) and rs17070072 (intronic to ZCCHC2; p = 1.46 × 10 -8 ; dependent SLE). A third locus upstream CYLC2 (rs12000047 and rs12005200, p < 2.00 × 10 -8 ; dependent SLE) when the joint effect of the SNP main and GxE effects was considered. GWEIS gene-based tests identified: MTNR1B with GxE effect with dependent SLE in Generation Scotland; and PHF2 with the joint effect in UK Biobank (p < 2.77 × 10 -6 ). Polygenic risk scores (PRSs) analyses incorporating GxE effects improved the prediction of depressive symptom scores, when using weights derived from either the UK Biobank GWAS of depressive symptoms (p = 0.01) or the PGC GWAS of major depressive disorder (p = 5.91 × 10 -3 ). Using an independent sample, PRS derived using GWEIS GxE effects provided evidence of shared aetiologies between depressive symptoms and schizotypal personality, heart disease and COPD. Further such studies are required and may result in improved treatments for depression and other stress-related conditions.

Depression has well-established influences from genetic and environmental risk factors. This has led to the diathesis-stress theory, which assumes a multiplicative gene-by-environment interaction (GxE) effect on risk. Recently, Colodro-Conde et al. empirically tested this theory, using the polygenic risk score for major depressive disorder (PRS, genes) and stressful life events (SLE, environment) effects on depressive symptoms, identifying significant GxE effects with an additive contribution to liability. We have tested the diathesis-stress theory on an independent sample of 4919 individuals. We identified nominally significant positive GxE effects in the full cohort (R 2  = 0.08%, p = 0.049) and in women (R 2  = 0.19%, p = 0.017), but not in men (R 2  = 0.15%, p = 0.07). GxE effects were nominally significant, but only in women, when SLE were split into those in which the respondent plays an active or passive role (R 2  = 0.15%, p = 0.038; R 2  = 0.16%, p = 0.033, respectively). High PRS increased the risk of depression in participants reporting high numbers of SLE (p = 2.86 × 10 -4 ). However, in those participants who reported no recent SLE, a higher PRS appeared to increase the risk of depressive symptoms in men (β = 0.082, p = 0.016) but had a protective effect in women (β = -0.061, p = 0.037). This difference was nominally significant (p = 0.017). Our study reinforces the evidence of additional risk in the aetiology of depression due to GxE effects. However, larger sample sizes are required to robustly validate these findings.

Background: It has been suggested that improving access to mental health services, supporting self-management, and increasing clinical productivity can be achieved through the delivery of technology-enabled care by personal mobile-based and internet-based services. There is little evidence available about whether working-age and older adults with mental health problems or their caregivers have access to these technologies or their confidence with these technologies., Objective: This study aimed to ascertain the prevalence and range of devices used to access the internet in patients and caregivers attending general and older adult psychiatry outpatient services and their confidence in using these technologies., Methods: We conducted an anonymous survey of 77 patients and caregivers from a general psychiatry and old age psychiatry clinic to determine rates of internet access and device ownership, and attitudes to technology-enabled care., Results: We found high levels of internet access and confidence in using the internet in working-age adults, their caregivers, and older adult caregivers but not in older adult patients. The smartphone usage predominated in working-age adults and their caregivers. Older adult caregivers were more likely to use desktop or laptop computers. In our sample, tablets were the least popular form factor., Conclusions: Access rates and uptake of internet-based services have the potential to be high in working-age adults and their caregivers but are likely to be markedly lower among older adult patients attending psychiatry clinics. Applications designed for tablets are likely to have low uptake. All groups identified appointment reminders as likely to be beneficial., (©Callum Cruickshank, Donald J MacIntyre. Originally published in JMIR Aging (http://aging.jmir.org), 22.11.2018.)

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology., (Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.

Objectives: To establish the feasibility of the Digital Support Platform (DSP), an internet-based, postdiagnostic tool designed for families living with a diagnosis of dementia., Design: Qualitative methods using normalisation process theory as an analysis framework for semistructured interview transcriptions., Setting: A community care setting in the South-East Scotland., Participants: We interviewed 10 dyads of people with Alzheimer's, vascular or mixed dementia (PWD), and their family carers, who had been given and had used the DSP for at least 2 months., Results: Our analysis revealed that the DSP was predominantly understood and used by the carers rather than PWD, and was used alongside tools and methods they already used to care for their relative. The DSP was interpreted as a tool that may be of benefit to those experiencing later stages of dementia or with physical care needs. Carers stated that the DSP may be of benefit in the future, reflecting a disinclination to prepare for or anticipate for future needs, rather than focus on those needs present at the time of distribution. PWD spoke positively about an interest in learning to use technology more effectively and enjoyed having their own tablet devices., Conclusions: The DSP was not wholly appropriate for families living with dementia in its early stages. The views of carers confirmed that postdiagnostic support was valued, but emphasised the importance of tailoring this support to the exact needs and current arrangements of families. There may be a benefit to introducing, encouraging, providing and teaching internet-enabled technology to those PWD who do not currently have access. Training should be provided when introducing new technology to PWD., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

Background: The genetics of depression has been explored in genome-wide association studies that focused on either major depressive disorder or depressive symptoms with mostly negative findings. A broad depression phenotype including both phenotypes has not been tested previously using a genome-wide association approach. We aimed to identify genetic polymorphisms significantly associated with a broad phenotype from depressive symptoms to major depressive disorder., Methods: We analyzed two prior studies of 70,017 participants of European ancestry from general and clinical populations in the discovery stage. We performed a replication meta-analysis of 28,328 participants. Single nucleotide polymorphism (SNP)-based heritability and genetic correlations were calculated using linkage disequilibrium score regression. Discovery and replication analyses were performed using a p-value-based meta-analysis. Lifetime major depressive disorder and depressive symptom scores were used as the outcome measures., Results: The SNP-based heritability of major depressive disorder was 0.21 (SE = 0.02), the SNP-based heritability of depressive symptoms was 0.04 (SE = 0.01), and their genetic correlation was 1.001 (SE = 0.2). We found one genome-wide significant locus related to the broad depression phenotype (rs9825823, chromosome 3: 61,082,153, p = 8.2 × 10 -9 ) located in an intron of the FHIT gene. We replicated this SNP in independent samples (p = .02) and the overall meta-analysis of the discovery and replication cohorts (1.0 × 10 -9 )., Conclusions: This large study identified a new locus for depression. Our results support a continuum between depressive symptoms and major depressive disorder. A phenotypically more inclusive approach may help to achieve the large sample sizes needed to detect susceptibility loci for depression., (Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: Major depressive disorder (MDD) is the second largest cause of global disease burden. It has an estimated heritability of 37%, but published genome-wide association studies have so far identified few risk loci. Haplotype-block-based regional heritability mapping (HRHM) estimates the localized genetic variance explained by common variants within haplotype blocks, integrating the effects of multiple variants, and may be more powerful for identifying MDD-associated genomic regions., Methods: We applied HRHM to Generation Scotland: The Scottish Family Health Study, a large family- and population-based Scottish cohort (N = 19,896). Single-single nucleotide polymorphism (SNP) and haplotype-based association tests were used to localize the association signal within the regions identified by HRHM. Functional prediction was used to investigate the effect of MDD-associated SNPs within the regions., Results: A haplotype block across a 24-kb region within the TOX2 gene reached genome-wide significance in HRHM. Single-SNP- and haplotype-based association tests demonstrated that five of nine genotyped SNPs and two haplotypes within this block were significantly associated with MDD. The expression of TOX2 and a brain-specific long noncoding RNA RP1-269M15.3 in frontal cortex and nucleus accumbens basal ganglia, respectively, were significantly regulated by MDD-associated SNPs within this region. Both the regional heritability and single-SNP associations within this block were replicated in the UK-Ireland group of the most recent release of the Psychiatric Genomics Consortium (PGC), the PGC2-MDD (Major Depression Dataset). The SNP association was also replicated in a depressive symptom sample that shares some individuals with the PGC2-MDD., Conclusions: This study highlights the value of HRHM for MDD and provides an important target within TOX2 for further functional studies., (Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Major depressive disorder (MDD) is a common, complex psychiatric disorder and a leading cause of disability worldwide. Despite twin studies indicating its modest heritability (~30-40%), extensive heterogeneity and a complex genetic architecture have complicated efforts to detect associated genetic risk variants. We combined single-nucleotide polymorphism (SNP) summary statistics from the CONVERGE and PGC studies of MDD, representing 10 502 Chinese (5282 cases and 5220 controls) and 18 663 European (9447 cases and 9215 controls) subjects. We determined the fraction of SNPs displaying consistent directions of effect, assessed the significance of polygenic risk scores and estimated the genetic correlation of MDD across ancestries. Subsequent trans-ancestry meta-analyses combined SNP-level evidence of association. Sign tests and polygenic score profiling weakly support an overlap of SNP effects between East Asian and European populations. We estimated the trans-ancestry genetic correlation of lifetime MDD as 0.33; female-only and recurrent MDD yielded estimates of 0.40 and 0.41, respectively. Common variants downstream of GPHN achieved genome-wide significance by Bayesian trans-ancestry meta-analysis (rs9323497; log 10 Bayes Factor=8.08) but failed to replicate in an independent European sample (P=0.911). Gene-set enrichment analyses indicate enrichment of genes involved in neuronal development and axonal trafficking. We successfully demonstrate a partially shared polygenic basis of MDD in East Asian and European populations. Taken together, these findings support a complex etiology for MDD and possible population differences in predisposing genetic factors, with important implications for future genetic studies.

Background: Genome-wide association studies (GWASs) of major depressive disorder (MDD) have identified few significant associations. Testing the aggregation of genetic variants, in particular biological pathways, may be more powerful. Regional heritability analysis can be used to detect genomic regions that contribute to disease risk., Methods: We integrated pathway analysis and multilevel regional heritability analyses in a pipeline designed to identify MDD-associated pathways. The pipeline was applied to two independent GWAS samples [Generation Scotland: The Scottish Family Health Study (GS:SFHS, N = 6455) and Psychiatric Genomics Consortium (PGC:MDD) (N = 18,759)]. A polygenic risk score (PRS) composed of single nucleotide polymorphisms from the pathway most consistently associated with MDD was created, and its accuracy to predict MDD, using area under the curve, logistic regression, and linear mixed model analyses, was tested., Results: In GS:SFHS, four pathways were significantly associated with MDD, and two of these explained a significant amount of pathway-level regional heritability. In PGC:MDD, one pathway was significantly associated with MDD. Pathway-level regional heritability was significant in this pathway in one subset of PGC:MDD. For both samples the regional heritabilities were further localized to the gene and subregion levels. The NETRIN1 signaling pathway showed the most consistent association with MDD across the two samples. PRSs from this pathway showed competitive predictive accuracy compared with the whole-genome PRSs when using area under the curve statistics, logistic regression, and linear mixed model., Conclusions: These post-GWAS analyses highlight the value of combining multiple methods on multiple GWAS data for the identification of risk pathways for MDD. The NETRIN1 signaling pathway is identified as a candidate pathway for MDD and should be explored in further large population studies., (Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: Major depressive disorder (MDD) is a disabling mood disorder, and despite a known heritable component, a large meta-analysis of genome-wide association studies revealed no replicable genetic risk variants. Given prior evidence of heterogeneity by age at onset in MDD, we tested whether genome-wide significant risk variants for MDD could be identified in cases subdivided by age at onset., Methods: Discovery case-control genome-wide association studies were performed where cases were stratified using increasing/decreasing age-at-onset cutoffs; significant single nucleotide polymorphisms were tested in nine independent replication samples, giving a total sample of 22,158 cases and 133,749 control subjects for subsetting. Polygenic score analysis was used to examine whether differences in shared genetic risk exists between earlier and adult-onset MDD with commonly comorbid disorders of schizophrenia, bipolar disorder, Alzheimer's disease, and coronary artery disease., Results: We identified one replicated genome-wide significant locus associated with adult-onset (>27 years) MDD (rs7647854, odds ratio: 1.16, 95% confidence interval: 1.11-1.21, p = 5.2 × 10 -11 ). Using polygenic score analyses, we show that earlier-onset MDD is genetically more similar to schizophrenia and bipolar disorder than adult-onset MDD., Conclusions: We demonstrate that using additional phenotype data previously collected by genetic studies to tackle phenotypic heterogeneity in MDD can successfully lead to the discovery of genetic risk factor despite reduced sample size. Furthermore, our results suggest that the genetic susceptibility to MDD differs between adult- and earlier-onset MDD, with earlier-onset cases having a greater genetic overlap with schizophrenia and bipolar disorder., (Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: Both genetic and environmental factors contribute to risk of depression, but estimates of their relative contributions are limited. Commonalities between clinically-assessed major depressive disorder (MDD) and self-declared depression (SDD) are also unclear., Methods: Using data from a large Scottish family-based cohort (GS:SFHS, N=19,994), we estimated the genetic and environmental variance components for MDD and SDD. The components representing the genetic effect associated with genome-wide common genetic variants (SNP heritability), the additional pedigree-associated genetic effect and non-genetic effects associated with common environments were estimated in a linear mixed model (LMM)., Findings: Both MDD and SDD had significant contributions from components representing the effect from common genetic variants, the additional genetic effect associated with the pedigree and the common environmental effect shared by couples. The estimate of correlation between SDD and MDD was high (r=1.00, se=0.20) for common-variant-associated genetic effect and lower for the additional genetic effect from the pedigree (r=0.57, se=0.08) and the couple-shared environmental effect (r=0.53, se=0.22)., Interpretation: Both genetics and couple-shared environmental effects were major factors influencing liability to depression. SDD may provide a scalable alternative to MDD in studies seeking to identify common risk variants. Rarer variants and environmental effects may however differ substantially according to different definitions of depression., (Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.)

Aims: This study assess differences in clinical variables in diabetes patients prescribed antipsychotic medication and determines relative schizophrenia prevalence in the diabetes population., Methods: This population-based case-control study utilizing Scotland's national diabetes registry (SCI-diabetes) and linked psychiatric hospital discharge data (SMR04) established diabetes phenotypes in a patient cohort prescribed long term antipsychotic medication (n=2362) (cases). Cases were matched 1:10 to diabetes patients not prescribed antipsychotic medication (controls) for BMI, gender; diabetes type; birth year; diagnosis date; smoking status. Sub-groups with defined schizophrenia (n=196) or bipolar disorder (n=190) were further examined. Schizophrenia prevalence in the diabetes versus general population was compared., Results: During follow up, antipsychotic prescription was associated with lower HbA1c (55.1 (95% CI 54.5-55.8) or 7.2 (95% CI 7.1-7.3)% vs 58.2 (58.0-58.4) mmol or 7.5 (95% CI 7.5-7.5)% p<0.001) lower serum total cholesterol, 4.2 (4.1-4.2) vs 4.3 (4.2-4.3) mmol/l, p<0.001, lower blood pressure (systolic 130 (130.17-131.29) vs 134 (134.3-134.7) mmHg, p<0.001), higher prescription of oral hypoglycaemic medication (42% (40-45) vs 38% (37-39) p<0.001), similar statin prescriptions (85% (81-89) vs 85% (84-86), p=0.55), and lower retinopathy rates (28% (25.6-30.5) vs 32% (31.5-33.1), p<0.001). HbA1c at diagnosis was similar (p=0.27). Schizophrenia prevalence was higher in the diabetes versus general population with differences across age groups (Scottish population versus diabetic population rate of 522.2 (522.1-522.3) versus 717.4 (703.4-731.9) per 100,000)., Conclusions: We confirm higher diabetes rates in schizophrenia up to age 70, similar attendance rates and clinical measurements that are not worse in a large well-matched population-based Scottish sample prescribed antipsychotic medication versus matched general diabetes patients., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Alcohol dependence is frequently co-morbid with cognitive impairment. The relationship between these traits is complex as cognitive dysfunction may arise as a consequence of heavy drinking or exist prior to the onset of dependence. In the present study, we tested the genetic overlap between cognitive abilities and alcohol dependence using polygenic risk scores (PGRS). We created two independent PGRS derived from two recent genome-wide association studies (GWAS) of alcohol dependence (SAGE GWAS: n = 2750; Yale-Penn GWAS: n = 2377) in a population-based cohort, Generation Scotland: Scottish Family Health Study (GS:SFHS) (n = 9863). Data on alcohol consumption and four tests of cognitive function [Mill Hill Vocabulary (MHV), digit symbol coding, phonemic verbal fluency (VF) and logical memory] were available. PGRS for alcohol dependence were negatively associated with two measures of cognitive function: MHV (SAGE: P = 0.009, β = -0.027; Yale-Penn: P = 0.001, β = -0.034) and VF (SAGE: P = 0.0008, β = -0.036; Yale-Penn: P = 0.00005, β = -0.044). VF remained robustly associated after adjustment for education and social deprivation; however, the association with MHV was substantially attenuated. Shared genetic variants may account for some of the phenotypic association between cognitive ability and alcohol dependence. A significant negative association between PGRS and social deprivation was found (SAGE: P = 5.2 × 10(-7) , β = -0.054; Yale-Penn: P = 0.000012, β = -0.047). Individuals living in socially deprived regions were found to carry more alcohol dependence risk alleles which may contribute to the increased prevalence of problem drinking in regions of deprivation. Future work to identify genes which affect both cognitive impairment and alcohol dependence will help elucidate biological processes common to both disorders., (© 2015 The Authors. Addiction Biology published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction.)

Cognitive impairment is common among individuals diagnosed with autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD). It has been suggested that some aspects of intelligence are preserved or even superior in people with ASD compared with controls, but consistent evidence is lacking. Few studies have examined the genetic overlap between cognitive ability and ASD/ADHD. The aim of this study was to examine the polygenic overlap between ASD/ADHD and cognitive ability in individuals from the general population. Polygenic risk for ADHD and ASD was calculated from genome-wide association studies of ASD and ADHD conducted by the Psychiatric Genetics Consortium. Risk scores were created in three independent cohorts: Generation Scotland Scottish Family Health Study (GS:SFHS) (n=9863), the Lothian Birth Cohorts 1936 and 1921 (n=1522), and the Brisbane Adolescent Twin Sample (BATS) (n=921). We report that polygenic risk for ASD is positively correlated with general cognitive ability (beta=0.07, P=6 × 10(-7), r(2)=0.003), logical memory and verbal intelligence in GS:SFHS. This was replicated in BATS as a positive association with full-scale intelligent quotient (IQ) (beta=0.07, P=0.03, r(2)=0.005). We did not find consistent evidence that polygenic risk for ADHD was associated with cognitive function; however, a negative correlation with IQ at age 11 years (beta=-0.08, Z=-3.3, P=0.001) was observed in the Lothian Birth Cohorts. These findings are in individuals from the general population, suggesting that the relationship between genetic risk for ASD and intelligence is partly independent of clinical state. These data suggest that common genetic variation relevant for ASD influences general cognitive ability.

The heritability of Major Depressive Disorder (MDD) has been estimated at 37% based largely on twin studies that rely on contested assumptions. More recently, the heritability of MDD has been estimated on large populations from registries such as the Swedish, Finnish, and Chinese cohorts. Family-based designs utilise a number of different relationships and provide an alternative means of estimating heritability. Generation Scotland: Scottish Family Health Study (GS:SFHS) is a large (n = 20,198), family-based population study designed to identify the genetic determinants of common diseases, including Major Depressive Disorder. Two thousand seven hundred and six individuals were SCID diagnosed with MDD, 13.5% of the cohort, from which we inferred a population prevalence of 12.2% (95% credible interval: 11.4% to 13.1%). Increased risk of MDD was associated with being female, unemployed due to a disability, current smokers, former drinkers, and living in areas of greater social deprivation. The heritability of MDD in GS:SFHS was between 28% and 44%, estimated from a pedigree model. The genetic correlation of MDD between sexes, age of onset, and illness course were examined and showed strong genetic correlations. The genetic correlation between males and females with MDD was 0.75 (0.43 to 0.99); between earlier (≤ age 40) and later (> age 40) onset was 0.85 (0.66 to 0.98); and between single and recurrent episodic illness course was 0.87 (0.72 to 0.98). We found that the heritability of recurrent MDD illness course was significantly greater than the heritability of single MDD illness course. The study confirms a moderate genetic contribution to depression, with a small contribution of the common family environment (variance proportion = 0.07, CI: 0.01 to 0.15), and supports the relationship of MDD with previously identified risk factors. This study did not find robust support for genetic differences in MDD due to sex, age of onset, or illness course. However, we found an intriguing difference in heritability between recurrent and single MDD illness course. These findings establish GS:SFHS as a valuable cohort for the genetic investigation of MDD.

Major depressive disorder (MDD) and obesity are frequently co-morbid and this correlation is partly due to genetic factors. Although specific genetic risk variants are associated with body mass index (BMI) and with larger effect sizes in depressed individuals, the genetic overlap and interaction with depression has not been addressed using whole-genome data. Polygenic profile scores for MDD and BMI were created in 13,921 members of Generation Scotland: the Scottish Family Health Study and tested for their association with BMI, MDD, neuroticism and scores on the General Health Questionnaire (GHQ) (current psychological distress). The association between BMI polygenic profile scores and BMI was tested fitting GHQ, neuroticism or MDD status as an interaction term to test for a moderating effect of mood disorder. BMI polygenic profile scores were not associated with lifetime MDD status or neuroticism although a significant positive association with GHQ scores was found (P = 0.0001, β = 0.034, r(2) = 0.001). Polygenic risk for MDD was not associated with BMI. A significant interaction between BMI polygenic profile scores and MDD (P = 0.0003, β = 0.064), GHQ (P = 0.0005, β = 0.027) and neuroticism (P = 0.003, β = 0.023) was found when BMI was the dependent variable. The effect of BMI-increasing alleles was greater in those with MDD, high neuroticism or current psychological distress. MDD, neuroticism and current psychological distress amplify the effect of BMI polygenic profile scores on BMI. Depressed individuals with a greater polygenic load for obesity are at greater risk of becoming obese than control individuals.

Objective: An interaction effect of depressive symptoms and APOE e4 allele status on cognitive decline has been shown in old age: e4 allele carriers with more depressive symptoms have faster cognitive decline than those with either depression or the e4 allele. We test this interaction effect on four cognitive domains, using a clinical depression measure comparing current versus lifetime depression., Methods: 14,379 individuals aged 18 to 59 years, and 3944 individuals aged 60 to 94 years from the Generation Scotland: Scottish Family Health Study participated. Linear-mixed models-accounting for participant relatedness and demographic and health indices-tested for effects of depression and APOE on cognitive abilities., Results: There was no interaction between depression and APOE on cognition (p > .05). Current depression was associated with poorer speed (in both groups) and memory (18- to 59-year-olds); differences ranged from 0.01 to 0.03 standard deviation [SD]. For lifetime depression, cognitive performance was lower for digit symbol in younger adults, but higher for vocabulary in both younger (0.03 SD) and older (0.05 SD) adults. A negative effect of the APOE e4 allele on speed and memory was found in the group 60 years and older (effect sizes of 0.04 SD)., Conclusions: The absence of a depression by APOE interaction on cognitive abilities suggests that these synergistic effects only operate at the level of cognitive decline. This implies that it is those biological pathways especially affected by aging that become compromised further by the combined presence of depression and APOE e4 in an individual.

A balanced t(1;11) translocation that transects the Disrupted in schizophrenia 1 (DISC1) gene shows genome-wide significant linkage for schizophrenia and recurrent major depressive disorder (rMDD) in a single large Scottish family, but genome-wide and exome sequencing-based association studies have not supported a role for DISC1 in psychiatric illness. To explore DISC1 in more detail, we sequenced 528 kb of the DISC1 locus in 653 cases and 889 controls. We report 2718 validated single-nucleotide polymorphisms (SNPs) of which 2010 have a minor allele frequency of <1%. Only 38% of these variants are reported in the 1000 Genomes Project European subset. This suggests that many DISC1 SNPs remain undiscovered and are essentially private. Rare coding variants identified exclusively in patients were found in likely functional protein domains. Significant region-wide association was observed between rs16856199 and rMDD (P=0.026, unadjusted P=6.3 × 10(-5), OR=3.48). This was not replicated in additional recurrent major depression samples (replication P=0.11). Combined analysis of both the original and replication set supported the original association (P=0.0058, OR=1.46). Evidence for segregation of this variant with disease in families was limited to those of rMDD individuals referred from primary care. Burden analysis for coding and non-coding variants gave nominal associations with diagnosis and measures of mood and cognition. Together, these observations are likely to generalise to other candidate genes for major mental illness and may thus provide guidelines for the design of future studies.

Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17-29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD and major depressive disorder (0.32 ± 0.07 s.e.), low between schizophrenia and ASD (0.16 ± 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn's disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.

GS:SFHS is a family-based genetic epidemiology study with DNA and socio-demographic and clinical data from about 24 000 volunteers across Scotland aged 18-98 years, from February 2006 to March 2011. Biological samples and anonymized data form a resource for research on the genetics of health, disease and quantitative traits of current and projected public health importance. Specific and important features of GS:SFHS include the family-based recruitment, with the intent of obtaining family groups; the breadth and depth of phenotype information, including detailed data on cognitive function, personality traits and mental health; consent and mechanisms for linkage of all data to comprehensive routine health-care records; and 'broad' consent from participants to use their data and samples for a wide range of medical research, including commercial research, and for re-contact for the potential collection of other data or samples, or for participation in related studies and the design and review of the protocol in parallel with in-depth sociological research on (potential) participants and users of the research outcomes. These features were designed to maximize the power of the resource to identify, replicate or control for genetic factors associated with a wide spectrum of illnesses and risk factors, both now and in the future.

Hyperpolarization-activated cyclic nucleotide-gated (HCN) channels are encoded by four genes (HCN1-4) and, through activation by cyclic AMP (cAMP), represent a point of convergence for several psychosis risk genes. On the basis of positive preliminary data, we sought to test whether genetic variation in HCN1-4 conferred risk of depression or cognitive impairment in the Generation Scotland: Scottish Family Health Study. HCN1, HCN2, HCN3, and HCN4 were genotyped for 43 haplotype-tagging SNPs and tested for association with DSM-IV depression, neuroticism, and a battery of cognitive tests assessing cognitive ability, memory, verbal fluency, and psychomotor performance. No association was found between any HCN channel gene SNP and risk of depression, neuroticism, or on any cognitive measure. The current study does not support a genetic role for HCN channels in conferring risk of depression or cognitive impairment in individuals from the Scottish population.

Variation in the complement receptor 1 gene (CR1) has been identified in recent genome-wide association studies as a risk factor for Alzheimer's disease. Here, we show that two Alzheimer's disease-associated CR1 variants, rs6656401 and rs3818361, are associated with major recurrent depression in females in a population-based cohort using individuals from the Generation Scotland: Scottish Family Health Study., (Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.)

Background: Studies of antisocial populations have found that they show deficits in recognition of facial affect. Such deficits are also found in other populations with clinical conditions such as autism spectrum disorders, schizophrenia and obsessive compulsive disorder., Aims: We aimed to investigate the hypothesis that facial affect recognition in the Scottish prison population would differ from matched controls. In addition, we aimed to investigate any relationship between facial affect recognition deficits and offence history., Methods: A sample of serving convicted prisoners, drawn from a larger study, was assessed for ability to recognise facial affect. Other variables were also measured and a self-report offending history obtained., Results: 127 prisoners were assessed in 11 prisons. Male prisoners were significantly worse than age, sex and IQ-matched controls at recognising negative facial emotions, specifically anger, fear, sadness and disgust. Within the sample of prisoners, deficits in fear recognition were associated with a history of previous prison sentences but not previous convictions. With respect to offending history, sex offenders were relatively better at recognising sadness and worse at recognising surprise than the other offenders. These relationships remain after controlling for IQ., Conclusions: Scottish convicted prisoners show deficits in recognising negative facial emotions in a pattern consistent with other antisocial populations. We also demonstrated a relationship between particular patterns of deficit and types of offending history not previously described., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

Major depressive disorder (MDD) is a common complex disorder with a partly genetic etiology. We conducted a genome-wide association study of the MDD2000+ sample (2431 cases, 3673 screened controls and >1 M imputed single-nucleotide polymorphisms (SNPs)). No SNPs achieved genome-wide significance either in the MDD2000+ study, or in meta-analysis with two other studies totaling 5763 cases and 6901 controls. These results imply that common variants of intermediate or large effect do not have main effects in the genetic architecture of MDD. Suggestive but notable results were (a) gene-based tests suggesting roles for adenylate cyclase 3 (ADCY3, 2p23.3) and galanin (GAL, 11q13.3); published functional evidence relates both of these to MDD and serotonergic signaling; (b) support for the bipolar disorder risk variant SNP rs1006737 in CACNA1C (P=0.020, odds ratio=1.10); and (c) lack of support for rs2251219, a SNP identified in a meta-analysis of affective disorder studies (P=0.51). We estimate that sample sizes 1.8- to 2.4-fold greater are needed for association studies of MDD compared with those for schizophrenia to detect variants that explain the same proportion of total variance in liability. Larger study cohorts characterized for genetic and environmental risk factors accumulated prospectively are likely to be needed to dissect more fully the etiology of MDD.