Clinical factors predicting treatment resistant depression: affirmative results from the European multicenter study.

OBJECTIVES: Clinical variables were investigated in the 'treatment resistant depression (TRD)- III' sample to replicate earlier findings by the European research consortium 'Group for the Study of Resistant Depression' (GSRD) and enable cross-sample prediction of treatment outcome in TRD. EXPERIMENTAL PROCEDURES: TRD was defined by a Montgomery and Åsberg Depression Rating Scale (MADRS) score ≥22 after at least two antidepressive trials. Response was defined by a decline in MADRS score by ≥50% and below a threshold of 22. Logistic regression was applied to replicate predictors for TRD among 16 clinical variables in 916 patients. Elastic net regression was applied for prediction of treatment outcome. RESULTS: Symptom severity (odds ratio (OR) = 3.31), psychotic symptoms (OR = 2.52), suicidal risk (OR = 1.74), generalized anxiety disorder (OR = 1.68), inpatient status (OR = 1.65), higher number of antidepressants administered previously (OR = 1.23), and lifetime depressive episodes (OR = 1.15) as well as longer duration of the current episode (OR = 1.022) increased the risk of TRD. Prediction of TRD reached an accuracy of 0.86 in the independent validation set, TRD-I. CONCLUSION: Symptom severity, suicidal risk, higher number of lifetime depressive episodes, and comorbid anxiety disorder were replicated as the most prominent risk factors for TRD. Significant predictors in TRD-III enabled robust prediction of treatment outcome in TRD-I.

Clinical correlates of augmentation/combination treatment strategies in major depressive disorder.

OBJECTIVE: This multicenter, multinational, cross-sectional study aimed to investigate clinical characteristics and treatment outcomes associated with augmentation/combination treatment strategies in major depressive disorder (MDD). METHOD: Sociodemographic, clinical, and treatment features of 1410 adult MDD patients were compared between MDD patients treated with monotherapy and augmentation/combination medication using descriptive statistics, analyses of covariance (ancova), and Spearman's correlation analyses. RESULTS: 60.64% of all participants received augmentation and/or combination strategies with a mean number of 2.18 ± 1.22 simultaneously prescribed psychiatric drugs. We found male gender, older age, Caucasian descent, higher weight, low educational status, absence of occupation, psychotic symptoms, melancholic and atypical features, suicide risk, in-patient treatment, longer duration of hospitalization, some psychiatric comorbidities (panic disorder, agoraphobia, obsessive-compulsive disorder, and bulimia nervosa), comorbid somatic comorbidity in general and concurrent hypertension, thyroid dysfunction, diabetes, and heart disease in particular, higher current and retrospective Montgomery and Åsberg Depression Rating Scale total scores, treatment resistance, and higher antidepressant dosing to be significantly associated with augmentation/combination treatment. These findings were corroborated when examining the number of concurrently administered psychiatric drugs in the statistical analyses. CONCLUSION: Our findings suggest a clear association between augmentation/combination strategies and treatment-resistant/difficult-to-treat MDD conditions characterized by severe symptomatology and high amount of psychiatric and somatic comorbidities.

New insights into the pharmacogenomics of antidepressant response from the GENDEP and STAR*D studies: rare variant analysis and high-density imputation.

Genome-wide association studies have generally failed to identify polymorphisms associated with antidepressant response. Possible reasons include limited coverage of genetic variants that this study tried to address by exome genotyping and dense imputation. A meta-analysis of Genome-Based Therapeutic Drugs for Depression (GENDEP) and Sequenced Treatment Alternatives to Relieve Depression (STAR*D) studies was performed at the single-nucleotide polymorphism (SNP), gene and pathway levels. Coverage of genetic variants was increased compared with previous studies by adding exome genotypes to previously available genome-wide data and using the Haplotype Reference Consortium panel for imputation. Standard quality control was applied. Phenotypes were symptom improvement and remission after 12 weeks of antidepressant treatment. Significant findings were investigated in NEWMEDS consortium samples and Pharmacogenomic Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) for replication. A total of 7062 950 SNPs were analyzed in GENDEP (n=738) and STAR*D (n=1409). rs116692768 (P=1.80e-08, ITGA9 (integrin α9)) and rs76191705 (P=2.59e-08, NRXN3 (neurexin 3)) were significantly associated with symptom improvement during citalopram/escitalopram treatment. At the gene level, no consistent effect was found. At the pathway level, the Gene Ontology (GO) terms GO: 0005694 (chromosome) and GO: 0044427 (chromosomal part) were associated with improvement (corrected P=0.007 and 0.045, respectively). The association between rs116692768 and symptom improvement was replicated in PGRN-AMPS (P=0.047), whereas rs76191705 was not. The two SNPs did not replicate in NEWMEDS. ITGA9 codes for a membrane receptor for neurotrophins and NRXN3 is a transmembrane neuronal adhesion receptor involved in synaptic differentiation. Despite their meaningful biological rationale for being involved in antidepressant effect, replication was partial. Further studies may help in clarifying their role.

Neuronal cell adhesion genes and antidepressant response in three independent samples.

Drug-effect phenotypes in human lymphoblastoid cell lines recently allowed to identify CHL1 (cell adhesion molecule with homology to L1CAM), GAP43 (growth-associated protein 43) and ITGB3 (integrin beta 3) as new candidates for involvement in the antidepressant effect. CHL1 and ITGB3 code for adhesion molecules, while GAP43 codes for a neuron-specific cytosolic protein expressed in neuronal growth cones; all the three gene products are involved in synaptic plasticity. Sixteen polymorphisms in these genes were genotyped in two samples (n=369 and 90) with diagnosis of major depressive episode who were treated with antidepressants in a naturalistic setting. Phenotypes were response, remission and treatment-resistant depression. Logistic regression including appropriate covariates was performed. Genes associated with outcomes were investigated in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) genome-wide study (n=1861) as both individual genes and through a pathway analysis (Reactome and String databases). Gene-based analysis suggested CHL1 rs4003413, GAP43 rs283393 and rs9860828, ITGB3 rs3809865 as the top candidates due to their replication across the largest original sample and the STAR*D cohort. GAP43 molecular pathway was associated with both response and remission in the STAR*D, with ELAVL4 representing the gene with the highest percentage of single nucleotide polymorphisms (SNPs) associated with outcomes. Other promising genes emerging from the pathway analysis were ITGB1 and NRP1. The present study was the first to analyze cell adhesion genes and their molecular pathways in antidepressant response. Genes and biomarkers involved in neuronal adhesion should be considered by further studies aimed to identify predictors of antidepressant response.

Familiality and SNP heritability of age at onset and episodicity in major depressive disorder.

BACKGROUND: Strategies to dissect phenotypic and genetic heterogeneity of major depressive disorder (MDD) have mainly relied on subphenotypes, such as age at onset (AAO) and recurrence/episodicity. Yet, evidence on whether these subphenotypes are familial or heritable is scarce. The aims of this study are to investigate the familiality of AAO and episode frequency in MDD and to assess the proportion of their variance explained by common single nucleotide polymorphisms (SNP heritability). METHOD: For investigating familiality, we used 691 families with 2-5 full siblings with recurrent MDD from the DeNt study. We fitted (square root) AAO and episode count in a linear and a negative binomial mixed model, respectively, with family as random effect and adjusting for sex, age and center. The strength of familiality was assessed with intraclass correlation coefficients (ICC). For estimating SNP heritabilities, we used 3468 unrelated MDD cases from the RADIANT and GSK Munich studies. After similarly adjusting for covariates, derived residuals were used with the GREML method in GCTA (genome-wide complex trait analysis) software. RESULTS: Significant familial clustering was found for both AAO (ICC = 0.28) and episodicity (ICC = 0.07). We calculated from respective ICC estimates the maximal additive heritability of AAO (0.56) and episodicity (0.15). SNP heritability of AAO was 0.17 (p = 0.04); analysis was underpowered for calculating SNP heritability of episodicity. CONCLUSIONS: AAO and episodicity aggregate in families to a moderate and small degree, respectively. AAO is under stronger additive genetic control than episodicity. Larger samples are needed to calculate the SNP heritability of episodicity. The described statistical framework could be useful in future analyses.

Investigation of blood mRNA biomarkers for suicidality in an independent sample.

Changes in the blood expression levels of SAT1, PTEN, MAP3K3 and MARCKS genes have been reported as biomarkers of high versus low suicidality state (Le-Niculescu et al.). Here, we investigate these expression biomarkers in the Genome-Based Therapeutic Drugs for Depression (GENDEP) study, of patients with major depressive disorder on a 12-week antidepressant treatment. Blood gene expression levels were available at baseline and week 8 for patients who experienced suicidal ideation during the study (n=20) versus those who did not (n=37). The analysis is well powered to detect the effect sizes reported in the original paper. Within either group, there was no significant change in the expression of these four genes over the course of the study, despite increasing suicidal ideation or initiation of antidepressant treatment. Comparison of the groups showed that the gene expression did not differ between patients with or without treatment-related suicidality. This independent study does not support the validity of the proposed biomarkers.

[Therapeutic management of bipolar disorder in France and Europe: a multinational longitudinal study (WAVE-bd)]. / Prise en charge thérapeutique des patients présentant un trouble bipolaire en France et en Europe : étude multinationale longitudinale WAVE-bd.

BACKGROUND: Bipolar disorder is a complex disease which requires multiple healthcare resources and complex medical care programs including pharmacological and non pharmacological treatment. If mood stabilizers remain the corner stone for bipolar disorder treatment, the development of atypical antipsychotics and their use as mood stabilizers has significantly modified therapeutic care. At the present time, psychiatrists have a large variety of psychotropic drugs for bipolar disorder: mood stabilizers, atypical antipsychotics, antidepressants, anxiolytics… However, despite the publication of guidelines on pharmacological treatment, with a high degree of consensus, everyday clinical practices remain heterogeneous. Moreover, there are few longitudinal studies to describe therapeutic management of bipolar disorder, whatever the phase of the disease is. Indeed, most of the studies are carried out on a specific phase of the disease or treatment. And there is no study comparing French and European practices. OBJECTIVES: In this paper, we aim to present the comparison of the management of pharmacological treatments of bipolar disorder between France and Europe, using the data of the observational Wide AmbispectiVE study of the clinical management and burden of bipolar disorder (WAVE-bd study). METHODS: The WAVE-bd study is a multinational, multicentre and non-interventional cohort study of patients diagnosed with BD type I or type II, according to DSM IV-TR criteria, in any phase of the disorder, who have experienced at least one mood event during the 12 months before enrolment. In total, 2507 patients have been included across 8 countries of Europe (480 in France). Data collection was retrospective (from 3 to 12 months), but also prospective (from 9 to 15 months) for a total study length of 12 to 27 months. Main outcome measures were the healthcare resource use and pharmacological treatments. RESULTS: Our results show differences in the therapeutic management of bipolar disorder between France and other European countries. Regarding healthcare resource use, our results show that French patients consult more frequently a psychiatrist or a psychologist and less frequently a general practitioner or the emergency ward in comparison with patients from other European countries. In the whole European population, including France, atypical antipsychotics are widely used. Only 25% of the patients receive lithium and more than 50% of the patients receive antidepressants, while their use in bipolar disorder remains controversial. Most of the patients receive polymedication. Considering all phases of the disease pooled, less lithium and less atypical antipsychotics are prescribed to French patients, whereas they receive more antidepressants and more benzodiazepines than patients from other European countries. On the over hand, prescription of anticonvulsants and electroconvulsive therapy are equal. Moreover, data analyses by polarity of the episodes globally confirm these trends. There are a few exceptions: mixed states, in which lithium is twice more prescribed in France in comparison to other countries; depressive states, in which antidepressants are even more prescribed in other countries than in France; and less prescription of anticonvulsants in manic, mixed and euthymic phases in France. CONCLUSION: The WAVE-bd study is the first observational study conducted on a large sample of bipolar I and II patients that compares therapeutic management between France and other European countries. The differences observed in therapeutic care across the different phases of the disease show that treatments differ depending on the countries studied, but also according to the preventive or curative phases, polarity of the bipolar disorder, comorbidities, impact of guidelines, and care organization. Although French patients have been treated by less lithium and less atypical antipsychotics than other European patients, they receive more antidepressants and more benzodiazepines. Finally, patients generally receive polymedication and the diversity in prescriptions shows how bipolar disorder is a complex disorder.

PPP3CC gene: a putative modulator of antidepressant response through the B-cell receptor signaling pathway.

Antidepressant pharmacogenetics represents a stimulating, but often discouraging field. The present study proposes a combination of several methodologies across three independent samples. Genes belonging to monoamine, neuroplasticity, circadian rhythm and transcription factor pathways were investigated in two samples (n=369 and 88) with diagnosis of major depression who were treated with antidepressants. Phenotypes were response, remission and treatment-resistant depression. Logistic regression including appropriate covariates was performed. Genes associated with outcomes were investigated in the STAR*D (Sequenced Treatment Alternatives to Relieve Depression) genome-wide study (n=1861). Top genes were further studied through a pathway analysis. In both original samples, markers associated with outcomes were concentrated in the PPP3CC gene. Other interesting findings were particularly in the HTR2A gene in one original sample and the STAR*D. The B-cell receptor signaling pathway proved to be the putative mediator of PPP3CC's effect on antidepressant response (P=0.03). Among innovative candidates, PPP3CC, involved in the regulation of immune system and synaptic plasticity, seems promising for further investigation.

Copy number variants and therapeutic response to antidepressant medication in major depressive disorder.

It would be beneficial to find genetic predictors of antidepressant response to help personalise treatment of major depressive disorder (MDD). Rare copy number variants (CNVs) have been implicated in several psychiatric disorders, including MDD, but their role in antidepressant response has yet to be investigated. CNV data were available for 1565 individuals with MDD from the NEWMEDS (Novel Methods leading to New Medications in Depression and Schizophrenia) consortium with prospective data on treatment outcome with either a serotonergic or noradrenergic antidepressant. No association was seen between the presence of CNV (rare or common), the overall number of CNVs or genomic CNV 'burden' and antidepressant response. Specific CNVs were nominally associated with antidepressant response, including 15q13.3 duplications and exonic NRXN1 deletions. These were associated with poor response to antidepressants. Overall burden of CNVs is unlikely to contribute to personalising antidepressant treatment. Specific CNVs associated with antidepressant treatment require replication and further study to confirm their role in the therapeutic action of antidepressant.

[Antipsychotics in depression]. / Des antipsychotiques dans la dépression.

Depression is a major public health problem. In the treatment of depression, the main objectives must be complete remission and prevention of recurrence. However, the objective of remission remains difficult in clinical practice. Several pharmacological strategies exist to handle treatment resistant depression and achieve remission. Among these options, addition of an atypical antipsychotic has become a popular choice. Second generation antipsychotics have been investigated in clinical trials in treatment resistant depression and in bipolar depression. Scientific data are available particularly for aripiprazole and quetiapine XR.

Physical co-morbidity among treatment resistant vs. treatment responsive patients with major depressive disorder.

Co-morbid physical illness has been suggested to play an important role among the factors contributing to treatment resistance in patients with major depressive disorder. In the current study we compared the rate of physical co-morbidity, defined by ICD-10, among a large multicenter sample of 702 patients with major depressive disorder. A total of 356 of the participants were defined as treatment resistant depression (TRD) patients-having failed two or more adequate antidepressant trials. No significant difference was found between TRD and non-TRD participants in the prevalence of any ICD-10 category. This finding suggests that although physical conditions such as diabetes, thyroid dysfunction, hypertension, ischemic heart disease, and peptic diseases are often accompanied by co-morbid MDD, they do not necessarily have an impact on the course of MDD or the likelihood to respond to treatment. Marginally higher rates of co-morbid breast cancer, migraine and glaucoma were found among TRD participants. Possible explanations for these findings and their possible relation to TRD are discussed.

[Bipolar disorder: a multifactorial disease]. / Le trouble bipolaire: une affection bien complexe.

Bipolar disorder is a multifactorial disease with a strong genetic component. However, environmental factors also play a role in the onset of the disease and in manic and depressive recurrence. The onset of the disorder is the consequence of a complex interaction between genetic and environmental factors. This gene-environment interaction is well illustrated by the influence of childhood trauma on the clinical expression of the disease in terms of age of onset, comorbidity and suicide. The complexity and heterogeneity of bipolar disorder require the identification of homogenous sub-groups with the use of biomarkers that could help reduce the etiological heterogeneity and better target the therapeutical options.

Non-steroidal anti-inflammatory drugs and efficacy of antidepressants in major depressive disorder.

BACKGROUND: It has been proposed that non-steroidal anti-inflammatory drugs (NSAIDs) may interfere with the efficacy of antidepressants and contribute to treatment resistance in major depressive disorder (MDD). This effect requires replication and a test of whether it is specific to serotonin-reuptake inhibiting (SRI) antidepressants. METHOD: We tested the effect of concomitant medication with NSAIDs on the efficacy of escitalopram, a SRI antidepressant, and nortriptyline, a tricyclic antidepressant, among 811 subjects with MDD treated for up to 12 weeks in the GENDEP study. Effects of NSAIDs on improvement of depressive symptoms were tested in mixed-effect linear models. Effects on remission were tested in logistic regression. Age, sex, baseline severity and centre of recruitment were considered as potential confounding factors. RESULTS: Ten percent (n=78) of subjects were taking NSAIDs during the antidepressant treatment. Older subjects were significantly more likely to take NSAIDs. After controlling for age, sex, centre of recruitment and baseline severity, concomitant medication with NSAIDs did not significantly influence the efficacy of escitalopram [ß=0.035, 95% confidence interval (CI) -0.145 to 0.215, p=0.704] or nortriptyline (ß=0.075, 95% CI -0.131 to 0.281, p=0.476). Although slightly fewer subjects who took NSAIDs reached remission [odds ratio (OR) 0.80, 95% CI 0.49-1.31, p=0.383], this non-significant effect was reversed after controlling for age, sex, baseline severity and recruitment centre effects (OR 1.04, 95% CI 0.61-1.77, p=0.882). CONCLUSIONS: NSAIDs are unlikely to affect the efficacy of SRI or other antidepressants. Concurrent use of NSAIDs and antidepressants does not need to be avoided.

The impact of COMT gene polymorphisms on suicidality in treatment resistant major depressive disorder--a European multicenter study.

Many association studies have reported associations between the catechol-O-methyltransferase (COMT) gene and psychiatric disorders including major depression (MDD). The COMT gene has further been associated with suicidal behaviour, as well as with treatment response, although with conflicting results. In the present study, we further elucidate the impact of COMT in treatment response in MDD patients with suicide risk and/or a personal history of suicide attempts. Two hundred fifty MDD patients were collected in the context of a European multicentre resistant depression study and treated with antidepressants at adequate doses for at least 4 weeks. Suicidality was assessed using Mini International Neuropsychiatric Interview (MINI) and the Hamilton Rating Scale for Depression (HAM-D). Treatment response was defined as HAM-D ≤ 17 and remission as HAM-D ≤ 7 after 4 weeks of treatment with antidepressants at adequate dose. Genotyping was performed for seven SNPs (rs4680, rs2075507, rs737865, rs6269, rs4633, rs4818 and rs165599) within the COMT gene. With regard to suicide risk and personal history of suicide attempts, neither single marker nor haplotypic association was found with any SNP after multiple testing correction. In non-responders, we found significant single marker and haplotypic association with suicide risk, but not in responders. The same holds true for both remitters and non-remitters, and when testing for association with a personal history of suicide attempts and treatment response phenotypes. In conclusion, we found significant association of COMT SNPs with suicide risk in MDD patients not responding to antidepressant treatment. Larger well-defined cohorts will be required to dissect this further.

Depression symptom dimensions as predictors of antidepressant treatment outcome: replicable evidence for interest-activity symptoms.

BACKGROUND: Symptom dimensions have not yet been comprehensively tested as predictors of the substantial heterogeneity in outcomes of antidepressant treatment in major depressive disorder. METHOD: We tested nine symptom dimensions derived from a previously published factor analysis of depression rating scales as predictors of outcome in 811 adults with moderate to severe depression treated with flexibly dosed escitalopram or nortriptyline in Genome-based Therapeutic Drugs for Depression (GENDEP). The effects of symptom dimensions were tested in mixed-effect regression models that controlled for overall initial depression severity, age, sex and recruitment centre. Significant results were tested for replicability in 3637 adult out-patients with non-psychotic major depression treated with citalopram in level I of Sequenced Treatment Alternatives to Relieve Depression (STAR*D). RESULTS: The interest-activity symptom dimension (reflecting low interest, reduced activity, indecisiveness and lack of enjoyment) at baseline strongly predicted poor treatment outcome in GENDEP, irrespective of overall depression severity, antidepressant type and outcome measure used. The prediction of poor treatment outcome by the interest-activity dimension was robustly replicated in STAR*D, independent of a comprehensive list of baseline covariates. CONCLUSIONS: Loss of interest, diminished activity and inability to make decisions predict poor outcome of antidepressant treatment even after adjustment for overall depression severity and other clinical covariates. The prominence of such symptoms may require additional treatment strategies and should be accounted for in future investigations of antidepressant response.

Genome-wide association study of increasing suicidal ideation during antidepressant treatment in the GENDEP project.

Suicidal thoughts during antidepressant treatment have been the focus of several candidate gene association studies. The aim of the present genome-wide association study was to identify additional genetic variants involved in increasing suicidal ideation during escitalopram and nortriptyline treatment. A total of 706 adult participants of European ancestry, treated for major depression with escitalopram or nortriptyline over 12 weeks in the Genome-Based Therapeutic Drugs for Depression (GENDEP) study were genotyped with Illumina Human 610-Quad Beadchips (Illumina, San Diego, CA, USA). A total of 244 subjects experienced an increase in suicidal ideation during follow-up. The genetic marker most significantly associated with increasing suicidality (8.28 × 10(-7)) was a single-nucleotide polymorphism (SNP; rs11143230) located 30 kb downstream of a gene encoding guanine deaminase (GDA) on chromosome 9q21.13. Two suggestive drug-specific associations within KCNIP4 (Kv channel-interacting protein 4; chromosome 4p15.31) and near ELP3 (elongation protein 3 homolog; chromosome 8p21.1) were found in subjects treated with escitalopram. Suggestive drug by gene interactions for two SNPs near structural variants on chromosome 4q12, one SNP in the apolipoprotein O (APOO) gene on chromosome Xp22.11 and one on chromosome 11q24.3 were found. The most significant association within a set of 33 candidate genes was in the neurotrophic tyrosine kinase receptor type 2 (NTRK2) gene. Finally, we also found trend for an association within genes previously associated with psychiatric phenotypes indirectly linked to suicidal behavior, that is, GRIP1, NXPH1 and ANK3. The results suggest novel pathways involved in increasing suicidal ideation during antidepressant treatment and should help to target treatment to reduce the risk of this dramatic adverse event. Limited power precludes definitive conclusions and replication in larger sample is warranted.

Interaction between serotonin transporter gene variants and life events predicts response to antidepressants in the GENDEP project.

There is substantial inter-individual variation in response to antidepressants, and genetic variation may, in part, explain these differences. For example, there is evidence to suggest that variation in the serotonin transporter gene (SLC6A4) predicts response to selective serotonin reuptake inhibitors (SSRIs). Environmental factors such as the occurrence of stressful life events before treatment may also be important. One prior report suggests that both factors interact in predicting response to antidepressants. GENDEP, a prospective part-randomized pharmacogenomics trial, collected longitudinal data on the outcome of 811 patients with major depression undergoing treatment with either an SSRI (escitalopram) or a tricyclic antidepressant (nortriptyline). Life events experienced over 6 months preceding treatment were measured using a List of Threatening Experiences Questionnaire, and several polymorphisms in the serotonin transporter gene (SLC6A4) have been genotyped including the serotonin transporter-linked polymorphic region (5-HTTLPR). Stressful life events were shown to predict a significantly better response to escitalopram but had no effect on response to nortriptyline. Variation in the 5-HTTLPR and another polymorphism in the gene, STin4, significantly modified these effects. Gene-environment interactions including life events may therefore be important not only in the aetiology of depression, but also in predicting response to antidepressant medication.

Trajectories of change in depression severity during treatment with antidepressants.

BACKGROUND: Response and remission defined by cut-off values on the last observed depression severity score are commonly used as outcome criteria in clinical trials, but ignore the time course of symptomatic change and may lead to inefficient analyses. We explore alternative categorization of outcome by naturally occurring trajectories of symptom change. METHOD: Growth mixture models were applied to repeated measurements of depression severity in 807 participants with major depression treated for 12 weeks with escitalopram or nortriptyline in the part-randomized Genome-based Therapeutic Drugs for Depression study. Latent trajectory classes were validated as outcomes in drug efficacy comparison and pharmacogenetic analyses. RESULTS: The final two-piece growth mixture model categorized participants into a majority (75%) following a gradual improvement trajectory and the remainder following a trajectory with rapid initial improvement. The rapid improvement trajectory was over-represented among nortriptyline-treated participants and showed an antidepressant-specific pattern of pharmacogenetic associations. In contrast, conventional response and remission favoured escitalopram and produced chance results in pharmacogenetic analyses. Controlling for drop-out reduced drug differences on response and remission but did not affect latent trajectory results. CONCLUSIONS: Latent trajectory mixture models capture heterogeneity in the development of clinical response after the initiation of antidepressants and provide an outcome that is distinct from traditional endpoint measures. It differentiates between antidepressants with different modes of action and is robust against bias due to differential discontinuation.

Chromosome 10q harbors a susceptibility locus for bipolar disorder in Ashkenazi Jewish families.

We report the results of a 10 cM density genome-wide scan and further fine mapping of three chromosomal candidate regions in 10 Belgian multigenerational families with bipolar (BP) disorder. This two-stage approach revealed significant evidence for linkage on chromosome 10q21.3-10q22.3, showing a maximum multipoint parametric heterogeneity logarithm of odds (HLOD) score of 3.28 and a nonparametric linkage (NPL) score of 4.00. Most of the chromosome 10q evidence was derived from a single, large Ashkenazi Jewish pedigree. Haplotype analysis in this pedigree shows that the patients share a 14-marker haplotype, defining a chromosomal candidate region of 19.2 cM. This region was reported previously as a candidate region for BP disorder in several independent linkage analysis studies and in one large meta-analysis. It was also implicated in a linkage study on schizophrenia (SZ) in Ashkenazi Jewish families. Additionally, we found suggestive evidence for linkage on chromosome 19q13.2-13.4 (HLOD 2.01, NPL 1.09) and chromosome 7q21-q22 (HLOD 1.45, NPL 2.28). Together, these observations suggest that a gene located on chromosome 10q21.3-10q22.3 is underlying the susceptibility both for SZ and for BP disorder in at least the Ashkenazi Jewish population.