Genome-wide interaction study of a proxy for stress-sensitivity and its prediction of major depressive disorder

Individual response to stress is correlated with neuroticism and is an important predictor of both neuroticism and the onset of major depressive disorder (MDD). Identification of the genetics underpinning individual differences in response to negative events (stress-sensitivity) may improve our understanding of the molecular pathways involved, and its association with stress-related illnesses. We sought to generate a proxy for stress-sensitivity through modelling the interaction between SNP allele and MDD status on neuroticism score in order to identify genetic variants that contribute to the higher neuroticism seen in individuals with a lifetime diagnosis of depression compared to unaffected individuals. Meta-analysis of genome-wide interaction studies (GWIS) in UK Biobank (N = 23,092) and Generation Scotland: Scottish Family Health Study (N = 7,155) identified no genome-wide significance SNP interactions. However, gene-based tests identified a genome-wide significant gene, ZNF366, a negative regulator of glucocorticoid receptor function implicated in alcohol dependence (p = 1.48x10-7; Bonferroni-corrected significance threshold p < 2.79x10-6). Using summary statistics from the stress-sensitivity term of the GWIS, SNP heritability for stress-sensitivity was estimated at 5.0%. In models fitting polygenic risk scores of both MDD and neuroticism derived from independent GWAS, we show that polygenic risk scores derived from the UK Biobank stress-sensitivity GWIS significantly improved the prediction of MDD in Generation Scotland. This study may improve interpretation of larger genome-wide association studies of MDD and other stress-related illnesses, and the understanding of the etiological mechanisms underpinning stress-sensitivity

Measuring social-emotional development in middle childhood: the Middle Years Development Instrument

This paper discusses the conceptualization, development, validation, and application of the Middle Years Development Instrument (MDI) – a population-based child self-report tool that assesses children\u27s social-emotional development and well-being in the context of their home, school, and neighborhood. The MDI is administered at a population-level to 4th and 7th grade students within participating public school districts across British Columbia, Canada. Children respond to items in five domains: (1) social-emotional development, (2) connectedness to peers and adults, (3) school experiences, (4) physical health and well-being, and (5) constructive use of after-school time. Results are aggregated for schools and communities and reported back in comprehensive reports and community maps to inform planning and decision making at local and regional levels. Shared testimonials exemplify how MDI results have been used by educators, community organizers, and city planners as a catalyst for promoting children\u27s social and emotional competence and facilitating collaboration between schools and communities

DNA sequence level analyses reveal potential phenotypic modifiers in a large family with psychiatric disorders

Psychiatric disorders are a group of genetically related diseases with highly polygenic architectures. Genome-wide association analyses have made substantial progress towards understanding the genetic architecture of these disorders. More recently, exome- and whole-genome sequencing of cases and families have identified rare, high penetrant variants that provide direct functional insight. There remains, however, a gap in the heritability explained by these complementary approaches. To understand how multiple genetic variants combine to modify both severity and penetrance of a highly penetrant variant, we sequenced 48 whole genomes from a family with a high loading of psychiatric disorder linked to a balanced chromosomal translocation. The (1;11)(q42;q14.3) translocation directly disrupts three genes: DISC1, DISC2, DISC1FP and has been linked to multiple brain imaging and neurocognitive outcomes in the family. Using DNA sequence-level linkage analysis, functional annotation and population-based association, we identified common and rare variants in GRM5 (minor allele frequency (MAF) > 0.05), PDE4D (MAF > 0.2) and CNTN5 (MAF < 0.01) that may help explain the individual differences in phenotypic expression in the family. We suggest that whole-genome sequencing in large families will improve the understanding of the combined effects of the rare and common sequence variation underlying psychiatric phenotypes

PKA Phosphorylation of NDE1 Is DISC1/PDE4 Dependent and Modulates Its Interaction with LIS1 and NDEL1

Nuclear distribution factor E-homolog 1 (NDE1), Lissencephaly 1 (LIS1), and NDE-like 1 (NDEL1) together participate in essential neurodevelopmental processes, including neuronal precursor proliferation and differentiation, neuronal migration, and neurite out-growth. NDE1/LIS1/NDEL1 interacts with Disrupted in Schizophrenia 1 (DISC1) and the cAMP-hydrolyzing enzyme phosphodiesterase 4 (PDE4). DISC1, PDE4, NDE1, and NDEL1 have each been implicated as genetic risk factors for major mental illness. Here, we demonstrate that DISC1 and PDE4 modulate NDE1 phosphorylation by cAMP-dependent protein kinase A (PKA) and identify a novel PKA substrate site on NDE1 at threonine-131 (T131). Homology modeling predicts that phosphorylation at T131 modulates NDE1–LIS1 and NDE1–NDEL1 interactions, which we confirm experimentally. DISC1–PDE4 interaction thus modulates organization of the NDE1/NDEL1/LIS1 complex. T131-phosphorylated NDE1 is present at the postsynaptic density, in proximal axons, within the nucleus, and at the centrosome where it becomes substantially enriched during mitosis. Mutation of the NDE1 T131 site to mimic PKA phosphorylation inhibits neurite outgrowth. Thus PKA-dependent phosphorylation of the NDE1/LIS1/NDEL1 complex is DISC1–PDE4 modulated and likely to regulate its neural functions

Genetic Overlap Profiles of Cognitive Ability in Psychotic and Affective Illnesses::A Multi-Site Study of Multiplex Pedigrees

BACKGROUND: Cognitive impairment is a key feature of psychiatric illness, making cognition an important tool for exploring of the genetics of illness risk. It remains unclear which measures should be prioritized in pleiotropy-guided research. Here, we generate profiles of genetic overlap between psychotic and affective disorders and cognitive measures in Caucasian and Hispanic groups. METHODS: Data were from four samples of extended pedigrees (N = 3046). Coefficient of relationship analyses were used to estimate genetic overlap between illness risk and cognitive ability. Results were meta-analyzed. FINDINGS: Psychosis was characterized by cognitive impairments on all measures with a generalized profile of genetic overlap. General cognitive ability shared greatest genetic overlap with psychosis risk (average Endophenotype Ranking Value (ERV) across samples from a random-effects meta-analysis = 0.32) followed by Verbal Memory (ERV = 0.24), Executive Function (ERV = 0.22), and Working Memory (ERV = 0.21). For bipolar disorder, there was genetic overlap with Processing Speed (ERV = 0.05) and Verbal Memory (ERV = 0.11), but these were confined to select samples. Major depression was characterized by enhanced Working and Face Memory performance, as reflected in significant genetic overlap in two samples. INTERPRETATION: There is substantial genetic overlap between risk for psychosis and a range of cognitive abilities (including general intelligence). Most of these effects are largely stable across of ascertainment strategy and ethnicity. Genetic overlap between affective disorders and cognition, on the other hand, tend to be specific to ascertainment strategy, ethnicity, and cognitive test battery

Rare variants implicate NMDA receptor signaling and cerebellar gene networks in risk for bipolar disorder

Bipolar disorder is an often-severe mental health condition characterized by alternation between extreme mood states of mania and depression. Despite strong heritability and the recent identification of 64 common variant risk loci of small effect, pathophysiological mechanisms remain unknown. Here, we analyzed genome sequences from 41 multiply-affected pedigrees and identified variants in 741 genes with nominally significant linkage or association with bipolar disorder. These 741 genes overlapped known risk genes for neurodevelopmental disorders and clustered within gene networks enriched for synaptic and nuclear functions. The top variant in this analysis - prioritized by statistical association, predicted deleteriousness, and network centrality - was a missense variant in the gene encoding D-amino acid oxidase (DAOG131V). Heterologous expression of DAOG131V in human cells resulted in decreased DAO protein abundance and enzymatic activity. In a knock-in mouse model of DAOG131, DaoG130V/+, we similarly found decreased DAO protein abundance in hindbrain regions, as well as enhanced stress susceptibility and blunted behavioral responses to pharmacological inhibition of N-methyl-D-aspartate receptors (NMDARs). RNA sequencing of cerebellar tissue revealed that DaoG130V resulted in decreased expression of two gene networks that are enriched for synaptic functions and for genes expressed, respectively, in Purkinje neurons or granule neurons. These gene networks were also down-regulated in the cerebellum of patients with bipolar disorder compared to healthy controls and were enriched for additional rare variants associated with bipolar disorder risk. These findings implicate dysregulation of NMDAR signaling and of gene expression in cerebellar neurons in bipolar disorder pathophysiology and provide insight into its genetic architecture

Haplotype-based association analysis of general cognitive ability in Generation Scotland, the English Longitudinal Study of Ageing, and UK Biobank

Background: Cognitive ability is a heritable trait with a polygenic architecture, for which several associated variants have been identified using genotype-based and candidate gene approaches. Haplotype-based analyses are a complementary technique that take phased genotype data into account, and potentially provide greater statistical power to detect lower frequency variants. Methods: In the present analysis, three cohort studies (ntotal = 48,002) were utilised: Generation Scotland: Scottish Family Health Study (GS:SFHS), the English Longitudinal Study of Ageing (ELSA), and the UK Biobank. A genome-wide haplotype-based meta-analysis of cognitive ability was performed, as well as a targeted meta-analysis of several gene coding regions. Results: None of the assessed haplotypes provided evidence of a statistically significant association with cognitive ability in either the individual cohorts or the meta-analysis. Within the meta-analysis, the haplotype with the lowest observed P-value overlapped with the D-amino acid oxidase activator (DAOA) gene coding region. This coding region has previously been associated with bipolar disorder, schizophrenia and Alzheimer’s disease, which have all been shown to impact upon cognitive ability. Another potentially interesting region highlighted within the current genome-wide association analysis (GS:SFHS: P = 4.09 x 10-7), was the butyrylcholinesterase (BCHE) gene coding region. The protein encoded by BCHE has been shown to influence the progression of Alzheimer’s disease and its role in cognitive ability merits further investigation. Conclusions: Although no evidence was found for any haplotypes with a statistically significant association with cognitive ability, our results did provide further evidence that the genetic variants contributing to the variance of cognitive ability are likely to be of small effect

The cortical thickness phenotype of individuals with <i>DISC1</i> translocation resembles schizophrenia

BACKGROUND. The disrupted in schizophrenia 1 (DISC1) gene locus was originally identified in a Scottish pedigree with a high incidence of psychiatric disorders that is associated with a balanced t(1;11)(q42.1;q14.3) chromosomal translocation. Here, we investigated whether members of this family carrying the t(1;11)(q42.1;q14.3) translocation have a common brain-related phenotype and whether this phenotype is similar to that observed in schizophrenia (SCZ), using multivariate pattern recognition techniques. METHODS. We measured cortical thickness, cortical surface area, subcortical volumes, and regional cerebral blood flow (rCBF) in healthy controls (HC) (n = 24), patients diagnosed with SCZ (n = 24), patients diagnosed with bipolar disorder (BP) (n = 19), and members of the original Scottish family (n = 30) who were either carriers (T+) or noncarriers (T–) of the DISC1 translocation. Binary classification models were developed to assess the differences and similarities across groups. RESULTS. Based on cortical thickness, 72% of the T– group were assigned to the HC group, 83% of the T+ group were assigned to the SCZ group, and 45% of the BP group were classified as belonging to the SCZ group, suggesting high specificity of this measurement in predicting brain-related phenotypes. Shared brain-related phenotypes between SCZ and T+ individuals were found for cortical thickness only. Finally, a classification accuracy of 73% was achieved when directly comparing the pattern of cortical thickness of T+ and T– individuals. CONCLUSION. Together, the results of this study suggest that the DISC1 translocation may increase the risk of psychiatric disorders in this pedigree by affecting neurostructural phenotypes such as cortical thickness. FUNDING. This work was supported by the National Health Service Research Scotland, the Scottish Translational Medicine Research Collaboration, the Innovative Medicines Initiative (IMI), the Engineering and Physical Sciences Research Council (EPSRC), The Wellcome Trust, the National Institute of Health Research (NIHR), and Pfizer

Genome-wide association study of antidepressant treatment resistance in a population-based cohort using health service prescription data and meta-analysis with GENDEP

Antidepressants demonstrate modest response rates in the treatment of major depressive disorder (MDD). Despite previous genome-wide association studies (GWAS) of antidepressant treatment response, the underlying genetic factors are unknown. Using prescription data in a population and family-based cohort (Generation Scotland: Scottish Family Health Study; GS:SFHS), we sought to define a measure of (a) antidepressant treatment resistance and (b) stages of antidepressant resistance by inferring antidepressant switching as non-response to treatment. GWAS were conducted separately for antidepressant treatment resistance in GS:SFHS and the Genome-based Therapeutic Drugs for Depression (GENDEP) study and then meta-analysed (meta-analysis n = 4213, cases = 358). For stages of antidepressant resistance, a GWAS on GS:SFHS only was performed (n = 3452). Additionally, we conducted gene-set enrichment, polygenic risk scoring (PRS) and genetic correlation analysis. We did not identify any significant loci, genes or gene sets associated with antidepressant treatment resistance or stages of resistance. Significant positive genetic correlations of antidepressant treatment resistance and stages of resistance with neuroticism, psychological distress, schizotypy and mood disorder traits were identified. These findings suggest that larger sample sizes are needed to identify the genetic architecture of antidepressant treatment response, and that population-based observational studies may provide a tractable approach to achieving the necessary statistical power