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.

Common Genetic Variation and Age of Onset of Anorexia Nervosa.

Background: Genetics and biology may influence the age of onset of anorexia nervosa (AN). The aims of this study were to determine whether common genetic variation contributes to age of onset of AN and to investigate the genetic associations between age of onset of AN and age at menarche. Methods: A secondary analysis of the Psychiatric Genomics Consortium genome-wide association study (GWAS) of AN was performed, which included 9335 cases and 31,981 screened controls, all from European ancestries. We conducted GWASs of age of onset, early-onset AN (<13 years), and typical-onset AN, and genetic correlation, genetic risk score, and Mendelian randomization analyses. Results: Two loci were genome-wide significant in the typical-onset AN GWAS. Heritability estimates (single nucleotide polymorphism-h 2) were 0.01-0.04 for age of onset, 0.16-0.25 for early-onset AN, and 0.17-0.25 for typical-onset AN. Early- and typical-onset AN showed distinct genetic correlation patterns with putative risk factors for AN. Specifically, early-onset AN was significantly genetically correlated with younger age at menarche, and typical-onset AN was significantly negatively genetically correlated with anthropometric traits. Genetic risk scores for age of onset and early-onset AN estimated from independent GWASs significantly predicted age of onset. Mendelian randomization analysis suggested a causal link between younger age at menarche and early-onset AN. Conclusions: Our results provide evidence consistent with a common variant genetic basis for age of onset and implicate biological pathways regulating menarche and reproduction.

Genome-wide association study of suicidal behaviour severity in mood disorders.

OBJECTIVE: Suicide is a major public health problem and it has a prominent genetic component. We performed a genome-wide association study (GWAS) of suicidal behaviour severity. METHODS: Suicide behaviour severity was assessed within the Schedules for Clinical Assessment in Neuropsychiatry in our mood disorder sample (n = 3506) for the GWAS. We also performed polygenic risk score analyses to explore genetic sharing between suicidal behaviour severity and a number of phenotypes, including bipolar disorder, major depressive disorder, alcoholism, post-traumatic stress disorder, impulsivity, insomnia, educational attainment, loneliness, maltreatment, and amygdala volume. RESULTS: We did not detect genome-wide significant findings at the single-marker or gene level. We report a number of suggestive single-marker and gene-based findings. Our polygenic risk score analyses did not yield significant findings with these phenotypes. CONCLUSIONS: Larger sample sizes are required to detect moderate effects.

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.

Childhood maltreatment and adult medical morbidity in mood disorders: comparison of unipolar depression with bipolar disorder.

BACKGROUND: The medical burden in mood disorders is high; various factors are thought to drive this pattern. Little research has examined the role of childhood maltreatment and its effects on medical morbidity in adulthood among people with unipolar depression and bipolar disorder.AimsThis is the first study to explore the association between childhood maltreatment and medical morbidity in bipolar disorder and in unipolar depression, and examine whether the impact of abuse and neglect are distinct or combined. METHOD: The participants consisted of 354 psychiatrically healthy controls, 248 participants with recurrent unipolar depression and 72 with bipolar disorder. Participants completed the Childhood Trauma Questionnaire and received a validated medical history interview. RESULTS: Any type of childhood maltreatment, child abuse and child neglect were significantly associated with the medical burden in bipolar disorder, but not unipolar depression or for controls. These associations worked in a dose-response fashion where participants with bipolar disorder with a history of two or more types of childhood maltreatment had the highest odds of having a medical illness relative to those without such history or those who reported one form. No such significant dose-response patterns were detected for participants with unipolar depression or controls. CONCLUSIONS: These findings suggest that childhood maltreatment may play a stronger role in the development of medical illnesses in individuals with bipolar disorder relative to those with unipolar depression. Individuals who had been maltreated with a mood disorder, especially bipolar disorder may benefit most from prevention and intervention efforts surrounding physical health.Declaration of interestNone.

Genes associated with anhedonia: a new analysis in a large clinical trial (GENDEP).

A key feature of major depressive disorder (MDD) is anhedonia, which is a predictor of response to antidepressant treatment. In order to shed light on its genetic underpinnings, we conducted a genome-wide association study (GWAS) followed by investigation of biological pathway enrichment using an anhedonia dimension for 759 patients with MDD in the GENDEP study. The GWAS identified 18 SNPs associated at genome-wide significance with the top one being an intronic SNP (rs9392549) in PRPF4B (pre-mRNA processing factor 4B) located on chromosome 6 (P = 2.07 × 10-9) while gene-set enrichment analysis returned one gene ontology term, axon cargo transport (GO: 0008088) with a nominally significant P value (1.15 × 10-5). Furthermore, our exploratory analysis yielded some interesting, albeit not statistically significant genetic correlation with Parkinson's Disease and nucleus accumbens gray matter. In addition, polygenic risk scores (PRSs) generated from our association analysis were found to be able to predict treatment efficacy of the antidepressants in this study. In conclusion, we found some markers significantly associated with anhedonia, and some suggestive findings of related pathways and biological functions, which could be further investigated in other studies.

Effect of cytochrome CYP2C19 metabolizing activity on antidepressant response and side effects: Meta-analysis of data from genome-wide association studies.

Cytochrome (CYP) P450 enzymes have a primary role in antidepressant metabolism and variants in these polymorphic genes are targets for pharmacogenetic investigation. This is the first meta-analysis to investigate how CYP2C19 polymorphisms predict citalopram/escitalopram efficacy and side effects. CYP2C19 metabolic phenotypes comprise poor metabolizers (PM), intermediate and intermediate+ metabolizers (IM; IM+), extensive and extensive+ metabolizers (EM [wild type]; EM+) and ultra-rapid metabolizers (UM) defined by the two most common CYP2C19 functional polymorphisms (rs4244285 and rs12248560) in Caucasians. These polymorphisms were genotyped or imputed from genome-wide data in four samples treated with citalopram or escitalopram (GENDEP, STAR*D, GenPod, PGRN-AMPS). Treatment efficacy was assessed by standardized percentage symptom improvement and by remission. Side effect data were available at weeks 2-4, 6 and 9 in three samples. A fixed-effects meta-analysis was performed using EM as the reference group. Analysis of 2558 patients for efficacy and 2037 patients for side effects showed that PMs had higher symptom improvement (SMD = 0.43, CI = 0.19-0.66) and higher remission rates (OR = 1.55, CI = 1.23-1.96) compared to EMs. At weeks 2-4, PMs showed higher risk of gastro-intestinal (OR = 1.26, CI = 1.08-1.47), neurological (OR = 1.28, CI = 1.07-1.53) and sexual side effects (OR = 1.52, CI = 1.23-1.87; week 6 values were similar). No difference was seen at week 9 or in total side effect burden. PMs did not have higher risk of dropout at week 4 compared to EMs. Antidepressant dose was not different among CYP2C19 groups. CYP2C19 polymorphisms may provide helpful information for guiding citalopram/escitalopram treatment, despite PMs being relatively rare among Caucasians (∼2%).

Genetic disposition to inflammation and response to antidepressants in major depressive disorder.

BACKGROUND: Inflammation may play an important role in depression and its treatment. A previous study found that increased C-reactive protein (CRP), a marker of systemic inflammation, is associated with worse response to the serotonergic antidepressant escitalopram and better response to the noradrenergic antidepressant nortriptyline. It is unclear whether this reflects genetic disposition to inflammation. METHODS: We analyzed genotype data and weekly Montgomery-Åsberg Depression Rating Scale scores (MADRS) from 755 unrelated individuals obtained over a 12-week period in the Genome-Based Therapeutic Drugs for Depression (GENDEP) study. We calculated a polygenic risk score for CRP level based on genome-wide meta-analysis results from the CHARGE Consortium. RESULTS: A higher polygenic risk score for CRP was associated with slightly better response to escitalopram and slightly worse response to nortriptyline, reflected in a statistically significant interaction between polygenic risk score and drug (beta = 1.07, 95% CI = 0.26-1.87, p = 0.0093). DISCUSSION: A differential association between CRP-PRS and antidepressant drug that is in a direction opposite to that found with serum CRP measurement suggests that previously observed effect of inflammation on antidepressant efficacy may be driven by state factors distinct from genetic influences on systemic inflammation.

Antidepressant drug-specific prediction of depression treatment outcomes from genetic and clinical variables.

Individuals with depression differ substantially in their response to treatment with antidepressants. Specific predictors explain only a small proportion of these differences. To meaningfully predict who will respond to which antidepressant, it may be necessary to combine multiple biomarkers and clinical variables. Using statistical learning on common genetic variants and clinical information in a training sample of 280 individuals randomly allocated to 12-week treatment with antidepressants escitalopram or nortriptyline, we derived models to predict remission with each antidepressant drug. We tested the reproducibility of each prediction in a validation set of 150 participants not used in model derivation. An elastic net logistic model based on eleven genetic and six clinical variables predicted remission with escitalopram in the validation dataset with area under the curve 0.77 (95%CI; 0.66-0.88; p = 0.004), explaining approximately 30% of variance in who achieves remission. A model derived from 20 genetic variables predicted remission with nortriptyline in the validation dataset with an area under the curve 0.77 (95%CI; 0.65-0.90; p < 0.001), explaining approximately 36% of variance in who achieves remission. The predictive models were antidepressant drug-specific. Validated drug-specific predictions suggest that a relatively small number of genetic and clinical variables can help select treatment between escitalopram and nortriptyline.

One year double blind study of high vs low frequency subcallosal cingulate stimulation for depression.

Subcallosal Brodmann's Area 25 (Cg25) Deep Brain Stimulation (DBS) is a new promising therapy for treatment resistant major depressive disorder (TR-MDD). While different DBS stimulating parameters may have an impact on the efficacy and safety of the therapy, there is no data to support a protocol for optimal stimulation parameters for depression. Here we present a prospective multi-center double-blind randomized crossed-over 13-month study that evaluated the effects of High (130 Hz) vs Low (20 Hz) frequency Cg25 stimulation for nine patients with TR-MDD. Four out of nine patients achieved response criteria (≥40% reduction of symptom score) compared to mean baseline values at the end of the study. The mean percent change of MADRS score showed a similar improvement in the high and low frequency stimulation groups after 6 months of stimulation (-15.4 ± 21.1 and -14.7 ± 21.1 respectively). The mean effect at the end of the second period (6 months after cross-over) was higher than the first period (first 6 months of stimulation) in all patients (-23.4 ± 19.9 (n = 6 periods) and -13.0 ± 22 (n = 9 periods) respectively). At the end of the second period, the mean percent change of the MADRS scores improved more in the high than low frequency groups (-31.3 ± 19.3 (n = 4 patients) and -7.7 ± 10.9 (n = 2 patients) respectively). Given the small numbers, detailed statistical analysis is challenging. Nonetheless the results of this study suggest that long term high frequency stimulation might confer the best results. Larger scale, randomized double blind trials are needed in order to evaluate the most effective stimulation parameters.

Childhood maltreatment and the medical morbidity in bipolar disorder: a case-control study.

BACKGROUND: Childhood maltreatment (abuse and neglect) can have long-term deleterious consequences, including increased risk for medical and psychiatric illnesses, such as bipolar disorder in adulthood. Emerging evidence suggests that a history of childhood maltreatment is linked to the comorbidity between medical illnesses and mood disorders. However, existing studies on bipolar disorder have not yet explored the specific influence of child neglect and have not included comparisons with individuals without mood disorders (controls). This study aimed to extend the existing literature by examining the differential influence of child abuse and child neglect on medical morbidity in a sample of bipolar cases and controls. METHODS: The study included 72 participants with bipolar disorder and 354 psychiatrically healthy controls (average age of both groups was 48 years), who completed the Childhood Trauma Questionnaire, and were interviewed regarding various medical disorders. RESULTS: A history of any type of childhood maltreatment was significantly associated with a diagnosis of any medical illness (adjusted OR = 6.28, 95% confidence intervals 1.70-23.12, p = 0.006) and an increased number of medical illnesses (adjusted OR = 3.77, 95% confidence intervals 1.34-10.57, p = 0.012) among adults with bipolar disorder. Exposure to child abuse was more strongly associated with medical disorders than child neglect. No association between childhood maltreatment and medical morbidity was detected among controls. CONCLUSIONS: To summarise, individuals with bipolar disorder who reported experiencing maltreatment during childhood, especially abuse, were at increased risk of suffering from medical illnesses and warrant greater clinical attention.

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.

Pharmacogenetics of antidepressant response: A polygenic approach.

BACKGROUND: Major depressive disorder (MDD) has a high personal and socio-economic burden and >60% of patients fail to achieve remission with the first antidepressant. The biological mechanisms behind antidepressant response are only partially known but genetic factors play a relevant role. A combined predictor across genetic variants may be useful to investigate this complex trait. METHODS: Polygenic risk scores (PRS) were used to estimate multi-allelic contribution to: 1) antidepressant efficacy; 2) its overlap with MDD and schizophrenia. We constructed PRS and tested whether these predicted symptom improvement or remission from the GENDEP study (n=736) to the STAR*D study (n=1409) and vice-versa, including the whole sample or only patients treated with escitalopram or citalopram. Using summary statistics from Psychiatric Genomics Consortium for MDD and schizophrenia, we tested whether PRS from these disorders predicted symptom improvement in GENDEP, STAR*D, and five further studies (n=3756). RESULTS: No significant prediction of antidepressant efficacy was obtained from PRS in GENDEP/STAR*D but this analysis might have been underpowered. There was no evidence of overlap in the genetics of antidepressant response with either MDD or schizophrenia, either in individual studies or a meta-analysis. Stratifying by antidepressant did not alter the results. DISCUSSION: We identified no significant predictive effect using PRS between pharmacogenetic studies. The genetic liability to MDD or schizophrenia did not predict response to antidepressants, suggesting differences between the genetic component of depression and treatment response. Larger or more homogeneous studies will be necessary to obtain a polygenic predictor of antidepressant response.

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.

Combining clinical variables to optimize prediction of antidepressant treatment outcomes.

The outcome of treatment with antidepressants varies markedly across people with the same diagnosis. A clinically significant prediction of outcomes could spare the frustration of trial and error approach and improve the outcomes of major depressive disorder through individualized treatment selection. It is likely that a combination of multiple predictors is needed to achieve such prediction. We used elastic net regularized regression to optimize prediction of symptom improvement and remission during treatment with escitalopram or nortriptyline and to identify contributing predictors from a range of demographic and clinical variables in 793 adults with major depressive disorder. A combination of demographic and clinical variables, with strong contributions from symptoms of depressed mood, reduced interest, decreased activity, indecisiveness, pessimism and anxiety significantly predicted treatment outcomes, explaining 5-10% of variance in symptom improvement with escitalopram. Similar combinations of variables predicted remission with area under the curve 0.72, explaining approximately 15% of variance (pseudo R(2)) in who achieves remission, with strong contributions from body mass index, appetite, interest-activity symptom dimension and anxious-somatizing depression subtype. Escitalopram-specific outcome prediction was more accurate than generic outcome prediction, and reached effect sizes that were near or above a previously established benchmark for clinical significance. Outcome prediction on the nortriptyline arm did not significantly differ from chance. These results suggest that easily obtained demographic and clinical variables can predict therapeutic response to escitalopram with clinically meaningful accuracy, suggesting a potential for individualized prescription of this antidepressant drug.

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.

Transcriptomics and the mechanisms of antidepressant efficacy.

The mechanisms by which antidepressants have their effects are not clear and the reasons for variability in treatment outcomes are also unknown. However, there is evidence from candidate gene research that indicates gene expression changes may be involved in antidepressant action. In this study, we examined antidepressant-induced alterations in gene expression on a transcriptome-wide scale, exploring associations with treatment response. Blood samples were taken from a subset of depressed patients from the GENDEP study (n=136) before and after eight weeks of treatment with either escitalopram or nortriptyline. Transcriptomic data were obtained from these samples using Illumina HumanHT-12 v4 Expression BeadChip microarrays. When analysing individual genes, we observed that changes in the expression of two genes (MMP28 and KXD1) were associated with better response to nortriptyline. Considering connectivity between genes, we identified modules of genes that were highly coexpressed. In the whole sample, changes in one of the ten identified coexpression modules showed significant correlation with treatment response (cor=0.27, p=0.0029). Using transcriptomic approaches, we have identified gene expression correlates of the therapeutic effects of antidepressants, highlighting possible molecular pathways involved in efficacious antidepressant treatment.

Phenotypic Association Analyses With Copy Number Variation in Recurrent Depressive Disorder.

BACKGROUND: Defining the molecular genomic basis of the likelihood of developing depressive disorder is a considerable challenge. We previously associated rare, exonic deletion copy number variants (CNV) with recurrent depressive disorder (RDD). Sex chromosome abnormalities also have been observed to co-occur with RDD. METHODS: In this reanalysis of our RDD dataset (N = 3106 cases; 459 screened control samples and 2699 population control samples), we further investigated the role of larger CNVs and chromosomal abnormalities in RDD and performed association analyses with clinical data derived from this dataset. RESULTS: We found an enrichment of Turner's syndrome among cases of depression compared with the frequency observed in a large population sample (N = 34,910) of live-born infants collected in Denmark (two-sided p = .023, odds ratio = 7.76 [95% confidence interval = 1.79-33.6]), a case of diploid/triploid mosaicism, and several cases of uniparental isodisomy. In contrast to our previous analysis, large deletion CNVs were no more frequent in cases than control samples, although deletion CNVs in cases contained more genes than control samples (two-sided p = .0002). CONCLUSIONS: After statistical correction for multiple comparisons, our data do not support a substantial role for CNVs in RDD, although (as has been observed in similar samples) occasional cases may harbor large variants with etiological significance. Genetic pleiotropy and sample heterogeneity suggest that very large sample sizes are required to study conclusively the role of genetic variation in mood disorders.

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.