Optimizing the Prediction of Depression Remission: A Longitudinal Machine Learning Approach.

Decisions about when to change antidepressant treatment are complex and benefit from accurate prediction of treatment outcome. Prognostic accuracy can be enhanced by incorporating repeated assessments of symptom severity collected during treatment. Participants (n = 714) from the Genome-Based Therapeutic Drugs for Depression study received escitalopram or nortriptyline over 12 weeks. Remission was defined as scoring ≤ 7 on the Hamilton Rating Scale. Predictors included demographic, clinical, and genetic variables (at 0 weeks) and measures of symptom severity (at 0, 2, 4, and 6 weeks). Longitudinal descriptors extracted with growth curves and topological data analysis were used to inform prediction of remission. Repeated assessments produced gradual and drug-specific improvements in predictive performance. By Week 4, models' discrimination in all samples reached levels that might usefully inform treatment decisions (area under the receiver operating curve (AUC) = 0.777 for nortriptyline; AUC = 0.807 for escitalopram; AUC = 0.794 for combined sample). Decisions around switching or modifying treatments for depression can be informed by repeated symptom assessments collected during treatment, but not until 4 weeks after the start of treatment.

Dimensions of temperament and character as predictors of antidepressant discontinuation, response and adverse reactions during treatment with nortriptyline and escitalopram.

BACKGROUND: Personality traits may predict antidepressant discontinuation and response. However, previous studies were rather small, only explored a few personality traits and did not include adverse drug effects nor the interdependency between antidepressant discontinuation patterns and response. METHODS: GENDEP included 589 patients with unipolar moderate-severe depression treated with escitalopram or nortriptyline for 12 weeks. Seven personality dimensions were measured using the self-reported 240-item Temperament and Character Inventory-Revised (TCI-R). We applied Cox proportional models to study discontinuation patterns, logistic and linear regression to investigate response and remission after 8 and 12 weeks, and mixed-effects linear models regarding time-varying treatment response and adverse drug reactions. RESULTS: Low harm avoidance, low cooperativeness, high self-transcendence and high novelty seeking were associated with higher risks for antidepressant discontinuation, independent of depressed mood, adverse drug reactions, drug, sex and age. Regression analyses showed that higher novelty seeking and cooperativeness scores were associated with a greater likelihood of response and remission after 8 and 12 weeks, respectively, but we found no correlations with response in the mixed-effects models. Only high harm avoidance was associated with more self-reported adverse effects. CONCLUSIONS: This study, representing the largest investigation between several personality traits and response to two different antidepressants, suggests that correlations between personality traits and antidepressant treatment response may be confounded by differential rates of discontinuation. Future trials on personality in the treatment of depression need to consider this interdependency and study whether interventions aiming at improving compliance for some personality types may improve response to antidepressants.

Investigating rare pathogenic/likely pathogenic exonic variation in bipolar disorder.

Bipolar disorder (BD) is a serious mental illness with substantial common variant heritability. However, the role of rare coding variation in BD is not well established. We examined the protein-coding (exonic) sequences of 3,987 unrelated individuals with BD and 5,322 controls of predominantly European ancestry across four cohorts from the Bipolar Sequencing Consortium (BSC). We assessed the burden of rare, protein-altering, single nucleotide variants classified as pathogenic or likely pathogenic (P-LP) both exome-wide and within several groups of genes with phenotypic or biologic plausibility in BD. While we observed an increased burden of rare coding P-LP variants within 165 genes identified as BD GWAS regions in 3,987 BD cases (meta-analysis OR = 1.9, 95% CI = 1.3-2.8, one-sided p = 6.0 × 10-4), this enrichment did not replicate in an additional 9,929 BD cases and 14,018 controls (OR = 0.9, one-side p = 0.70). Although BD shares common variant heritability with schizophrenia, in the BSC sample we did not observe a significant enrichment of P-LP variants in SCZ GWAS genes, in two classes of neuronal synaptic genes (RBFOX2 and FMRP) associated with SCZ or in loss-of-function intolerant genes. In this study, the largest analysis of exonic variation in BD, individuals with BD do not carry a replicable enrichment of rare P-LP variants across the exome or in any of several groups of genes with biologic plausibility. Moreover, despite a strong shared susceptibility between BD and SCZ through common genetic variation, we do not observe an association between BD risk and rare P-LP coding variants in genes known to modulate risk for SCZ.

Advancing psychiatric genetics through dissecting heterogeneity.

There has been substantial progress in psychiatric genetics in recent years, through collaborative efforts to build large samples sizes for case/control analyses for a number of psychiatric disorders. The identification of replicated trait-associated genomic loci represents a large stride forward in a field where little is known about the biological processes involved in disorder. As researchers build on this early foundation, they are beginning to advance the field towards more fine-grained approaches that interrogate the many sources of heterogeneity within psychiatric genetics that can obscure the identification of genotypic influences on disorder. In this review, we provide a brief overview, across a range of psychiatric diagnoses, of recent approaches that have been employed to dissect heterogeneity to give a flavour of the current direction of the field. We group these into three main categories; tackling the heterogeneity in phenotype that is found within the diagnostic categories used within psychiatry, the many different forms of genetic variation that might influence psychiatric traits and then finally, the heterogeneity that is seen across individuals of different ancestries.

Effect of antidepressant switching between nortriptyline and escitalopram after a failed first antidepressant treatment among patients with major depressive disorder.

BACKGROUND: For patients with major depressive disorder (MDD) experiencing side-effects or non-response to their first antidepressant, little is known regarding the effect of switching between a tricyclic antidepressant (TCA) and a selective serotonin reuptake inhibitor (SSRI).AimsTo compare the switch between the TCA nortriptyline and the SSRI escitalopram. METHOD: Among 811 adults with MDD treated with nortriptyline or escitalopram for up to 12 weeks, 108 individuals switched from nortriptyline to escitalopram or vice versa because of side-effects or non-response (trial registration: EudraCT No.2004-001723-38 (https://eudract.ema.europa.eu/) and ISRCTN No.03693000 (http://www.controlled-trials.com)). Patients were followed for up to 26 weeks after switching and response was measured with the Montgomery-Åsberg Depression Rating scale (MADRS). We performed adjusted mixed-effects linear regression models with full information maximum likelihood estimation reporting ß-coefficients with 95% CIs. RESULTS: Switching antidepressants resulted in a significant decrease in MADRS scores. This was present for switchers from escitalopram to nortriptyline (n = 36, ß = -0.38, 95% CI -0.51 to -0.25, P<0.001) and from nortriptyline to escitalopram (n = 72, ß = -0.34, 95% CI -0.41 to -0.26, P<0.001). Both switching options resulted in significant improvement among individuals who switched because of non-response or side-effects. The results were supported by analyses on other rating scales and symptom dimensions. CONCLUSIONS: These results suggest that switching from a TCA to an SSRI or vice versa after non-response or side-effects to the first antidepressant may be a viable approach to achieve response among patients with MDD.Declarations of interestK.J.A. holds an Alberta Centennial Addiction and Mental Health Research Chair, funded by the Government of Alberta. K.J.A. has been a member of various advisory boards, received consultancy fees and honoraria, and has received research grants from various companies including Johnson and Johnson Pharmaceuticals Research and Development and Bristol-Myers Squibb Pharmaceuticals Limited. D.S. has served on advisory boards for, and received unrestricted grants from, Lundbeck and AstraZeneca. A.F. and P.M. have received honoraria for participating in expert panels for Lundbeck and GlaxoSmithKline.

Interaction between the FTO gene, body mass index and depression: meta-analysis of 13701 individuals.

BackgroundDepression and obesity are highly prevalent, and major impacts on public health frequently co-occur. Recently, we reported that having depression moderates the effect of the FTO gene, suggesting its implication in the association between depression and obesity.AimsTo confirm these findings by investigating the FTO polymorphism rs9939609 in new cohorts, and subsequently in a meta-analysis.MethodThe sample consists of 6902 individuals with depression and 6799 controls from three replication cohorts and two original discovery cohorts. Linear regression models were performed to test for association between rs9939609 and body mass index (BMI), and for the interaction between rs9939609 and depression status for an effect on BMI. Fixed and random effects meta-analyses were performed using METASOFT.ResultsIn the replication cohorts, we observed a significant interaction between FTO, BMI and depression with fixed effects meta-analysis (ß = 0.12, P = 2.7 × 10-4) and with the Han/Eskin random effects method (P = 1.4 × 10-7) but not with traditional random effects (ß = 0.1, P = 0.35). When combined with the discovery cohorts, random effects meta-analysis also supports the interaction (ß = 0.12, P = 0.027) being highly significant based on the Han/Eskin model (P = 6.9 × 10-8). On average, carriers of the risk allele who have depression have a 2.2% higher BMI for each risk allele, over and above the main effect of FTOConclusionsThis meta-analysis provides additional support for a significant interaction between FTO, depression and BMI, indicating that depression increases the effect of FTO on BMI. The findings provide a useful starting point in understanding the biological mechanism involved in the association between obesity and depression.

Association between C-reactive protein (CRP) with depression symptom severity and specific depressive symptoms in major depression.

INTRODUCTION: Population-based studies have associated inflammation, particularly higher C-reactive protein (CRP), with depressive severity, but clinical trials in major depressive disorder were rather non-specific without examining the role of gender. We aimed to investigate the association between CRP and overall depression severity including specific depressive symptoms and to examine potential gender differences. METHODS: We included 231 individuals with major depressive disorder from the Genome-Based Therapeutics Drugs for Depression (GENDEP) study. At baseline, we assessed high-sensitivity CRP levels and psychopathology with the Montgomery Aasberg Depression Rating Scale (MADRS). We performed linear regression analyses to investigate the association between baseline CRP levels with overall MADRS severity and specific symptoms at baseline and adjusted for age, gender, anti-inflammatory and psychotropic drug treatment, body mass index, smoking, inflammatory diseases, and recruitment center. RESULTS: Higher CRP levels were significantly associated with greater overall MADRS symptom severity (p=0.02), which was significant among women (p=0.02) but not among men (p=0.68). Among women, higher CRP was associated with increased severity on observed mood, cognitive symptoms, interest-activity, and suicidality, but we found no significant associations among men. Interaction analyses showed no significant gender differences on the overall MADRS score or specific symptoms. DISCUSSION: Our results support the sickness syndrome theory suggesting that chronic low-grade inflammation may be associated with a subtype of depression. The potential gender differences in psychopathology may be explained by biological and/or psychosocial factors, e.g. differential modulation of immune responses by sex hormones. Clinical studies should investigate symptom-specific and/or gender-specific treatment guided by peripheral inflammatory markers.

Stressful life events and catechol-O-methyl-transferase (COMT) gene in bipolar disorder.

BACKGROUND: A small body of research suggests that gene-environment interactions play an important role in the development of bipolar disorder. The aim of the present study is to contribute to this work by exploring the relationship between stressful life events and the catechol-O-methyl-transferase (COMT) Val158 Met polymorphism in bipolar disorder. METHODS: Four hundred eighty-two bipolar cases and 205 psychiatrically healthy controls completed the List of Threatening Experiences Questionnaire. Bipolar cases reported the events experienced 6 months before their worst depressive and manic episodes; controls reported those events experienced 6 months prior to their interview. The genotypic information for the COMT Val158 Met variant (rs4680) was extracted from GWAS analysis of the sample. RESULTS: The impact of stressful life events was moderated by the COMT genotype for the worst depressive episode using a Val dominant model (adjusted risk difference = 0.09, 95% confidence intervals = 0.003-0.18, P = .04). For the worst manic episodes no significant interactions between COMT and stressful life events were detected. CONCLUSIONS: This is the first study to explore the relationship between stressful life events and the COMT Val158 Met polymorphism focusing solely on bipolar disorder. The results of this study highlight the importance of the interplay between genetic and environmental factors for bipolar depression.

Highly polygenic architecture of antidepressant treatment response: Comparative analysis of SSRI and NRI treatment in an animal model of depression.

Response to antidepressant (AD) treatment may be a more polygenic trait than previously hypothesized, with many genetic variants interacting in yet unclear ways. In this study we used methods that can automatically learn to detect patterns of statistical regularity from a sparsely distributed signal across hippocampal transcriptome measurements in a large-scale animal pharmacogenomic study to uncover genomic variations associated with AD. The study used four inbred mouse strains of both sexes, two drug treatments, and a control group (escitalopram, nortriptyline, and saline). Multi-class and binary classification using Machine Learning (ML) and regularization algorithms using iterative and univariate feature selection methods, including InfoGain, mRMR, ANOVA, and Chi Square, were used to uncover genomic markers associated with AD response. Relevant genes were selected based on Jaccard distance and carried forward for gene-network analysis. Linear association methods uncovered only one gene associated with drug treatment response. The implementation of ML algorithms, together with feature reduction methods, revealed a set of 204 genes associated with SSRI and 241 genes associated with NRI response. Although only 10% of genes overlapped across the two drugs, network analysis shows that both drugs modulated the CREB pathway, through different molecular mechanisms. Through careful implementation and optimisations, the algorithms detected a weak signal used to predict whether an animal was treated with nortriptyline (77%) or escitalopram (67%) on an independent testing set. The results from this study indicate that the molecular signature of AD treatment may include a much broader range of genomic markers than previously hypothesized, suggesting that response to medication may be as complex as the pathology. The search for biomarkers of antidepressant treatment response could therefore consider a higher number of genetic markers and their interactions. Through predominately different molecular targets and mechanisms of action, the two drugs modulate the same Creb1 pathway which plays a key role in neurotrophic responses and in inflammatory processes. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

Evaluation of the validity and utility of a transdiagnostic psychosis dimension encompassing schizophrenia and bipolar disorder.

BACKGROUND: In recent years, the Kraepelinian dichotomy has been challenged in light of evidence on shared genetic and environmental factors for schizophrenia and bipolar disorder, but empirical efforts to identify a transdiagnostic phenotype of psychosis remain remarkably limited. AIMS: To investigate whether schizophrenia spectrum and bipolar disorder lie on a transdiagnostic spectrum with overlapping non-affective and affective psychotic symptoms. METHOD: Multidimensional item-response modelling was conducted on symptom ratings of the OPerational CRITeria (OPCRIT) system in 1168 patients with schizophrenia spectrum and bipolar disorder. RESULTS: A bifactor model with one general, transdiagnostic psychosis dimension underlying affective and non-affective psychotic symptoms and five specific dimensions of positive, negative, disorganised, manic and depressive symptoms provided the best model fit and diagnostic utility for categorical classification. CONCLUSIONS: Our findings provide support for including dimensional approaches into classification systems and a directly measurable clinical phenotype for cross-disorder investigations into shared genetic and environmental factors of psychosis.

Immune signatures and disorder-specific patterns in a cross-disorder gene expression analysis.

BACKGROUND: Recent studies point to overlap between neuropsychiatric disorders in symptomatology and genetic aetiology. AIMS: To systematically investigate genomics overlap between childhood and adult attention-deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD) and major depressive disorder (MDD). METHOD: Analysis of whole-genome blood gene expression and genetic risk scores of 318 individuals. Participants included individuals affected with adult ADHD (n = 93), childhood ADHD (n = 17), MDD (n = 63), ASD (n = 51), childhood dual diagnosis of ADHD-ASD (n = 16) and healthy controls (n = 78). RESULTS: Weighted gene co-expression analysis results reveal disorder-specific signatures for childhood ADHD and MDD, and also highlight two immune-related gene co-expression modules correlating inversely with MDD and adult ADHD disease status. We find no significant relationship between polygenic risk scores and gene expression signatures. CONCLUSIONS: Our results reveal disorder overlap and specificity at the genetic and gene expression level. They suggest new pathways contributing to distinct pathophysiology in psychiatric disorders and shed light on potential shared genomic risk factors.

A genetic risk score combining 32 SNPs is associated with body mass index and improves obesity prediction in people with major depressive disorder.

BACKGROUND: Obesity is strongly associated with major depressive disorder (MDD) and various other diseases. Genome-wide association studies have identified multiple risk loci robustly associated with body mass index (BMI). In this study, we aimed to investigate whether a genetic risk score (GRS) combining multiple BMI risk loci might have utility in prediction of obesity in patients with MDD. METHODS: Linear and logistic regression models were conducted to predict BMI and obesity, respectively, in three independent large case-control studies of major depression (Radiant, GSK-Munich, PsyCoLaus). The analyses were first performed in the whole sample and then separately in depressed cases and controls. An unweighted GRS was calculated by summation of the number of risk alleles. A weighted GRS was calculated as the sum of risk alleles at each locus multiplied by their effect sizes. Receiver operating characteristic (ROC) analysis was used to compare the discriminatory ability of predictors of obesity. RESULTS: In the discovery phase, a total of 2,521 participants (1,895 depressed patients and 626 controls) were included from the Radiant study. Both unweighted and weighted GRS were highly associated with BMI (P < 0.001) but explained only a modest amount of variance. Adding 'traditional' risk factors to GRS significantly improved the predictive ability with the area under the curve (AUC) in the ROC analysis, increasing from 0.58 to 0.66 (95% CI, 0.62-0.68; χ(2) = 27.68; P < 0.0001). Although there was no formal evidence of interaction between depression status and GRS, there was further improvement in AUC in the ROC analysis when depression status was added to the model (AUC = 0.71; 95% CI, 0.68-0.73; χ(2) = 28.64; P <0.0001). We further found that the GRS accounted for more variance of BMI in depressed patients than in healthy controls. Again, GRS discriminated obesity better in depressed patients compared to healthy controls. We later replicated these analyses in two independent samples (GSK-Munich and PsyCoLaus) and found similar results. CONCLUSIONS: A GRS proved to be a highly significant predictor of obesity in people with MDD but accounted for only modest amount of variance. Nevertheless, as more risk loci are identified, combining a GRS approach with information on non-genetic risk factors could become a useful strategy in identifying MDD patients at higher risk of developing obesity.

Modulatory effects of brain-derived neurotrophic factor Val66Met polymorphism on prefrontal regions in major depressive disorder.

BACKGROUND: Brain-derived neurotrophic factor (BDNF) Val66Met polymorphism contributes to the development of depression (major depressive disorder, MDD), but it is unclear whether neural effects observed in healthy individuals are sustained in MDD. AIMS: To investigate BDNF Val66Met effects on key regions in MDD neurocircuitry: amygdala, anterior cingulate, middle frontal and orbitofrontal regions. METHOD: Magnetic resonance imaging scans were acquired in 79 persons with MDD (mean age 49 years) and 74 healthy volunteers (mean age 50 years). Effects on surface area and cortical thickness were examined with multiple comparison correction. RESULTS: People who were Met allele carriers showed reduced caudal middle frontal thickness in both study groups. Significant interaction effects were found in the anterior cingulate and rostral middle frontal regions, in which participants in the MDD group who were Met carriers showed the greatest reduction in surface area. CONCLUSIONS: Modulatory effects of the BDNF Val66Met polymorphism on distinct subregions in the prefrontal cortex in MDD support the neurotrophin model of depression.

Common genetic determinants of intraocular pressure and primary open-angle glaucoma.

Intraocular pressure (IOP) is a highly heritable risk factor for primary open-angle glaucoma and is the only target for current glaucoma therapy. The genetic factors which determine IOP are largely unknown. We performed a genome-wide association study for IOP in 11,972 participants from 4 independent population-based studies in The Netherlands. We replicated our findings in 7,482 participants from 4 additional cohorts from the UK, Australia, Canada, and the Wellcome Trust Case-Control Consortium 2/Blue Mountains Eye Study. IOP was significantly associated with rs11656696, located in GAS7 at 17p13.1 (p=1.4×10(-8)), and with rs7555523, located in TMCO1 at 1q24.1 (p=1.6×10(-8)). In a meta-analysis of 4 case-control studies (total N = 1,432 glaucoma cases), both variants also showed evidence for association with glaucoma (p=2.4×10(-2) for rs11656696 and p=9.1×10(-4) for rs7555523). GAS7 and TMCO1 are highly expressed in the ciliary body and trabecular meshwork as well as in the lamina cribrosa, optic nerve, and retina. Both genes functionally interact with known glaucoma disease genes. These data suggest that we have identified two clinically relevant genes involved in IOP regulation.

The relationship between schizophrenia and rheumatoid arthritis revisited: genetic and epidemiological analyses.

Epidemiological studies are inconsistent on the relationship between schizophrenia (SCZ) and rheumatoid arthritis (RA). Several studies have shown that SCZ has a protective effect on RA, with RA occurring less frequently in SCZ cases than would be expected by chance, whilst other studies have failed to replicate this. We sought to test the hypothesis that this effect is due to a protective effect of SCZ risk alleles on RA onset. We first reviewed the literature on the comorbidity of RA and SCZ and performed a meta-analysis. We then used polygenic risk scoring in an RA case control study in order to investigate the contribution of SCZ risk alleles to RA risk. Meta-analysis across studies over the past half-century showed that prevalence of RA in SCZ cases was significantly reduced (OR=0.48, 95% CI: 0.34-0.67, p<0.0001). The relationship between SCZ genetic risk and RA status was weak. Polygenic risk of SCZ explained a small (0.1%) and non-significant (p=0.085) proportion of variance in RA case control status. This relationship was nominally positive, with RA cases carrying more SCZ risk alleles than controls. The current findings do not support the assertion that the relationship between RA and SCZ is explained by genetic factors, which appear to have little or no effect. The protective effect of SCZ on RA may be due to environmental factors, such as an anti-inflammatory effect of anti-psychotic medication or merely due to confounding limitations in study designs.

Genetic risk score analysis indicates migraine with and without comorbid depression are genetically different disorders.

Migraine and major depressive disorder (MDD) are comorbid, moderately heritable and to some extent influenced by the same genes. In a previous paper, we suggested the possibility of causality (one trait causing the other) underlying this comorbidity. We present a new application of polygenic (genetic risk) score analysis to investigate the mechanisms underlying the genetic overlap of migraine and MDD. Genetic risk scores were constructed based on data from two discovery samples in which genome-wide association analyses (GWA) were performed for migraine and MDD, respectively. The Australian Twin Migraine GWA study (N = 6,350) included 2,825 migraine cases and 3,525 controls, 805 of whom met the diagnostic criteria for MDD. The RADIANT GWA study (N = 3,230) included 1,636 MDD cases and 1,594 controls. Genetic risk scores for migraine and for MDD were used to predict pure and comorbid forms of migraine and MDD in an independent Dutch target sample (NTR-NESDA, N = 2,966), which included 1,476 MDD cases and 1,058 migraine cases (723 of these individuals had both disorders concurrently). The observed patterns of prediction suggest that the 'pure' forms of migraine and MDD are genetically distinct disorders. The subgroup of individuals with comorbid MDD and migraine were genetically most similar to MDD patients. These results indicate that in at least a subset of migraine patients with MDD, migraine may be a symptom or consequence of MDD.

Interaction between stress and the BDNF Val66Met polymorphism in depression: a systematic review and meta-analysis.

BACKGROUND: Major depression is a disabling psychiatric illness with complex origins. Life stress (childhood adversity and recent stressful events) is a robust risk factor for depression. The relationship between life stress and Val66Met polymorphism in the brain-derived neurotrophic factor (BDNF) gene has received much attention. The aim of the present work was to review and conduct a meta-analysis on the results from published studies examining this interaction. METHODS: A literature search was conducted using PsychINFO and PubMed databases until 22 November 2013. A total of 22 studies with a pooled total of 14,233 participants met the inclusion criteria, the results of which were combined and a meta-analysis performed using the Liptak-Stouffer z-score method. RESULTS: The results suggest that the Met allele of BDNF Val66Met significantly moderates the relationship between life stress and depression (P = 0.03). When the studies were stratified by type of environmental stressor, the evidence was stronger for an interaction with stressful life events (P = 0.01) and weaker for interaction of BDNF Val66Met with childhood adversity (P = 0.051). CONCLUSIONS: The interaction between BDNF and life stress in depression is stronger for stressful life events rather than childhood adversity. Methodological limitations of existing studies include poor measurement of life stress.

The endogenous and reactive depression subtypes revisited: integrative animal and human studies implicate multiple distinct molecular mechanisms underlying major depressive disorder.

BACKGROUND: Traditional diagnoses of major depressive disorder (MDD) suggested that the presence or absence of stress prior to onset results in either 'reactive' or 'endogenous' subtypes of the disorder, respectively. Several lines of research suggest that the biological underpinnings of 'reactive' or 'endogenous' subtypes may also differ, resulting in differential response to treatment. We investigated this hypothesis by comparing the gene-expression profiles of three animal models of 'reactive' and 'endogenous' depression. We then translated these findings to clinical samples using a human post-mortem mRNA study. METHODS: Affymetrix mouse whole-genome oligonucleotide arrays were used to measure gene expression from hippocampal tissues of 144 mice from the Genome-based Therapeutic Drugs for Depression (GENDEP) project. The study used four inbred mouse strains and two depressogenic 'stress' protocols (maternal separation and Unpredictable Chronic Mild Stress) to model 'reactive' depression. Stress-related mRNA differences in mouse were compared with a parallel mRNA study using Flinders Sensitive and Resistant rat lines as a model of 'endogenous' depression. Convergent genes differentially expressed across the animal studies were used to inform candidate gene selection in a human mRNA post-mortem case control study from the Stanley Brain Consortium. RESULTS: In the mouse 'reactive' model, the expression of 350 genes changed in response to early stresses and 370 in response to late stresses. A minimal genetic overlap (less than 8.8%) was detected in response to both stress protocols, but 30% of these genes (21) were also differentially regulated in the 'endogenous' rat study. This overlap is significantly greater than expected by chance. The VAMP-2 gene, differentially expressed across the rodent studies, was also significantly altered in the human study after correcting for multiple testing. CONCLUSIONS: Our results suggest that 'endogenous' and 'reactive' subtypes of depression are associated with largely distinct changes in gene-expression. However, they also suggest that the molecular signature of 'reactive' depression caused by early stressors differs considerably from that of 'reactive' depression caused by late stressors. A small set of genes was consistently dysregulated across each paradigm and in post-mortem brain tissue of depressed patients suggesting a final common pathway to the disorder. These genes included the VAMP-2 gene, which has previously been associated with Axis-I disorders including MDD, bipolar depression, schizophrenia and with antidepressant treatment response. We also discuss the implications of our findings for disease classification, personalized medicine and case-control studies of MDD.

Genome-wide association study of bipolar disorder in Canadian and UK populations corroborates disease loci including SYNE1 and CSMD1.

BACKGROUND: Recently, genome-wide association studies (GWAS) for cases versus controls using single nucleotide polymorphism microarray data have shown promising findings for complex neuropsychiatric disorders, including bipolar disorder (BD). METHODS: Here we describe a comprehensive genome-wide study of bipolar disorder (BD), cross-referencing analysis from a family-based study of 229 small families with association analysis from over 950 cases and 950 ethnicity-matched controls from the UK and Canada. Further, loci identified in these analyses were supported by pathways identified through pathway analysis on the samples. RESULTS: Although no genome-wide significant markers were identified, the combined GWAS findings have pointed to several genes of interest that support GWAS findings for BD from other groups or consortia, such as at SYNE1 on 6q25, PPP2R2C on 4p16.1, ZNF659 on 3p24.3, CNTNAP5 (2q14.3), and CDH13 (16q23.3). This apparent corroboration across multiple sites gives much confidence to the likelihood of genetic involvement in BD at these loci. In particular, our two-stage strategy found association in both our combined case/control analysis and the family-based analysis on 1q21.2 (closest gene: sphingosine-1-phosphate receptor 1 gene, S1PR1) and on 1q24.1 near the gene TMCO1, and at CSMD1 on 8p23.2, supporting several previous GWAS reports for BD and for schizophrenia. Pathway analysis suggests association of pathways involved in calcium signalling, neuropathic pain signalling, CREB signalling in neurons, glutamate receptor signalling and axonal guidance signalling. CONCLUSIONS: The findings presented here show support for a number of genes previously implicated genes in the etiology of BD, including CSMD1 and SYNE1, as well as evidence for previously unreported genes such as the brain-expressed genes ADCY2, NCALD, WDR60, SCN7A and SPAG16.