Neuroticism is associated with the onset and maintenance of a number of mental health conditions, as well as a number of deleterious outcomes (e.g. physical health problems, higher divorce rates, lost productivity, and increased treatment seeking); thus, the consideration of whether this trait can be addressed in treatment is warranted. To date, outcome research has yielded mixed results regarding neuroticism's responsiveness to treatment, perhaps due to the fact that study interventions are typically designed to target disorder symptoms rather than neuroticism itself. The purpose of the current study was to explore whether a course of treatment with the unified protocol (UP), a transdiagnostic intervention that was explicitly developed to target neuroticism, results in greater reductions in neuroticism compared to gold-standard, symptom focused cognitive behavioral therapy (CBT) protocols and a waitlist (WL) control condition.

Patients with principal anxiety disorders (N = 223) were included in this study. They completed a validated self-report measure of neuroticism, as well as clinician-rated measures of psychological symptoms.

At week 16, participants in the UP condition exhibited significantly lower levels of neuroticism than participants in the symptom-focused CBT (t(218) = −2.17, p = 0.03, d = −0.32) and WL conditions(t(207) = −2.33, p = 0.02, d = −0.43), and these group differences remained after controlling for simultaneous fluctuations in depression and anxiety symptoms.

Treatment effects on neuroticism may be most robust when this trait is explicitly targeted.

Two common approaches to identify subgroups of patients with bipolar disorder are clustering methodology (mixture analysis) based on the age of onset, and a birth cohort analysis. This study investigates if a birth cohort effect will influence the results of clustering on the age of onset, using a large, international database.

The database includes 4037 patients with a diagnosis of bipolar I disorder, previously collected at 36 collection sites in 23 countries. Generalized estimating equations (GEE) were used to adjust the data for country median age, and in some models, birth cohort. Model-based clustering (mixture analysis) was then performed on the age of onset data using the residuals. Clinical variables in subgroups were compared.

There was a strong birth cohort effect. Without adjusting for the birth cohort, three subgroups were found by clustering. After adjusting for the birth cohort or when considering only those born after 1959, two subgroups were found. With results of either two or three subgroups, the youngest subgroup was more likely to have a family history of mood disorders and a first episode with depressed polarity. However, without adjusting for birth cohort (three subgroups), family history and polarity of the first episode could not be distinguished between the middle and oldest subgroups.

These results using international data confirm prior findings using single country data, that there are subgroups of bipolar I disorder based on the age of onset, and that there is a birth cohort effect. Including the birth cohort adjustment altered the number and characteristics of subgroups detected when clustering by age of onset. Further investigation is needed to determine if combining both approaches will identify subgroups that are more useful for research.

L’introduction de l’agomélatine est peu fréquente au sein de notre établissement, 39 patients sur les 925 patients sous antidépresseurs ont été répertoriés en un an, soit 4,21 %. L’objectif de cette étude était de comprendre pourquoi cet antidépresseur était si peu prescrit.

Une étude rétrospective a été réalisée sur 1 an (du 1/06/2014 au 1/06/2015) pour l’ensemble des services d’hospitalisation de l’établissement. Une analyse des prescriptions d’agomélatine a été effectuée à partir du logiciel Pharma® : posologie, durée, nombre de patients. La cause d’un éventuel arrêt ou d’un relais par une autre molécule a été évaluée à partir des informations recueillies dans les dossiers patients (logiciel Crossway®).

Sur les 39 patients ayant reçu de l’agomélatine, la posologie était de 1 comprimé par jour pour 82 % des patients et 2 comprimés par jour pour les 18 % restant. Seize patients (41 %) ont arrêté le traitement sur cette période, la moyenne de durée de leur traitement était de 25 jours [1–90]. Concernant les causes d’arrêt du traitement, 6 patients (37,5 %) l’ont arrêté à cause d’effets secondaires somatiques (5 pour des troubles hépatiques, 1 pour trouble du sommeil type insomnie), 5 (31,25 %) pour cause d’inefficacité de la molécule dont 3 patients pour lesquels le traitement a été arrêté avant les 15 jours recommandés. Pour 3 patients la cause d’arrêt n’a pas été retrouvée. L’arrêt du traitement a été suivi par la prescription d’un autre antidépresseur sauf pour 2 patients où l’indication n’était plus retrouvée.

Le peu de prescription d’agomélatine peut s’expliquer par une efficacité jugée discutable de la molécule sur les pathologies dépressives nécessitant une hospitalisation mais aussi des effets secondaires hépatiques fréquents imposant une surveillance accrue. L’indication de l’agomélatine pour la pathologie dépressive traitée en hospitalisation est donc « discutée ».

Recent evidence points to a critical role of redox dysregulation induced oxidative stress in the pathophysiology of early phases of schizophrenia. An add-on trial with n-acetyl-cysteine (NAC) led to a reduction in negative symptoms in chronic schizophrenia patients. Aim of this study was to explore impact of addition of NAC to standard treatment in early psychosis (EP) patients.

Double-blind, randomized, placebo-controlled trial of addition of NAC, 2700 mg daily, to antipsychotic treatment over 6 months. Monthly assessment of PANSS, GAF, SOFAS and antipsychotics treatment; quantification of brain glutathione levels (GSHmPFC) by 1H-magnetic-resonance-spectroscopy and of blood cells glutathione (GSHBC) and glutathione peroxidase activity (GPxBC) as marker of oxidation status at the beginning and end of treatment.

Overall, 63 patients were included. Spectroscopy data showed that GSHmPFC increased by +23% in the NAC group, while it tended to decrease by −5% in the placebo group (P = 0.005). No significant difference between NAC and placebo was observed on global changes in negative symptoms, positive symptoms or functional outcome. However, in patients with high-baseline oxidation status (GPxBC>22.3U/gHb), subgroup explorations revealed an improvement of positive symptoms over time compared to patients with low-baseline GPx (P = 0.02).

While addition of NAC induced an increase of brain GSH, it had no impact on symptomatic and functional outcome in EP patients. However, in patients with high oxidation status, addition of NAC leads to significantly greater improvement in positive symptoms. Future studies on antioxidant interventions in EP should consider biomarker-guided treatment.

The authors have not supplied their declaration of competing interest.

Postoperative cognitive impairment is among the most common medical complications associated with surgical interventions – particularly in elderly patients. In our aging society, it is an urgent medical need to determine preoperative individual risk prediction to allow more accurate cost–benefit decisions prior to elective surgeries. So far, risk prediction is mainly based on clinical parameters. However, these parameters only give a rough estimate of the individual risk. At present, there are no molecular or neuroimaging biomarkers available to improve risk prediction and little is known about the etiology and pathophysiology of this clinical condition. In this short review, we summarize the current state of knowledge and briefly present the recently started BioCog project (Biomarker Development for Postoperative Cognitive Impairment in the Elderly), which is funded by the European Union. It is the goal of this research and development (R&D) project, which involves academic and industry partners throughout Europe, to deliver a multivariate algorithm based on clinical assessments as well as molecular and neuroimaging biomarkers to overcome the currently unsatisfying situation.

Major depressive disorder (MDD) is a highly heterogeneous condition in terms of symptom presentation and, likely, underlying pathophysiology. Accordingly, it is possible that only certain individuals with MDD are well-suited to antidepressants. A potentially fruitful approach to parsing this heterogeneity is to focus on promising endophenotypes of depression, such as neuroticism, anhedonia, and cognitive control deficits.

Within an 8-week multisite trial of sertraline v. placebo for depressed adults (n = 216), we examined whether the combination of machine learning with a Personalized Advantage Index (PAI) can generate individualized treatment recommendations on the basis of endophenotype profiles coupled with clinical and demographic characteristics.

Five pre-treatment variables moderated treatment response. Higher depression severity and neuroticism, older age, less impairment in cognitive control, and being employed were each associated with better outcomes to sertraline than placebo. Across 1000 iterations of a 10-fold cross-validation, the PAI model predicted that 31% of the sample would exhibit a clinically meaningful advantage [post-treatment Hamilton Rating Scale for Depression (HRSD) difference ⩾3] with sertraline relative to placebo. Although there were no overall outcome differences between treatment groups (d = 0.15), those identified as optimally suited to sertraline at pre-treatment had better week 8 HRSD scores if randomized to sertraline (10.7) than placebo (14.7) (d = 0.58).

A subset of MDD patients optimally suited to sertraline can be identified on the basis of pre-treatment characteristics. This model must be tested prospectively before it can be used to inform treatment selection. However, findings demonstrate the potential to improve individual outcomes through algorithm-guided treatment recommendations.

Adults with major depressive disorder (MDD) demonstrate increased susceptibility to interfering effects of anxiety on cognitive control; although under certain conditions adults with MDD are able to compensate for these effects. The brain mechanisms that may facilitate the ability to compensate for anxiety either via the recruitment of additional cognitive resources or via the regulation of interference from anxiety remain largely unknown. To clarify these mechanisms, we examined the effects of anxiety on brain activity and amygdala–prefrontal functional connectivity in adults diagnosed with MDD.

A total of 22 unmedicated adults with MDD and 18 healthy controls (HCs) performed the Tower of London task under conditions designed to induce anxiety, while undergoing a functional magnetic resonance imaging assessment.

During the easy condition, the MDD group demonstrated equivalent planning accuracy, longer planning times, elevated amygdala activity and left rostrolateral prefrontal cortex (RLPFC) hyperactivity relative to HCs. Anxiety mediated observed group differences in planning times, as well as differences in amygdala activation, which subsequently mediated observed differences in RLPFC activation. During the easy condition, the MDD group also demonstrated increased negative amygdala–dorsolateral prefrontal cortex (DLPFC) connectivity which correlated with improved planning accuracy. During the hard condition, HCs demonstrated greater DLPFC activation and stronger negative amygdala–DLPFC connectivity, which was unrelated to planning accuracy.

Our results suggest that persons with MDD compensate for anxiety-related limbic activation during low-load cognitive tasks by recruiting additional RLPFC activation and through increased inhibitory amygdala–DLPFC communication. Targeting these neural mechanisms directly may improve cognitive functioning in MDD.

Depression can adversely affect employment status.

To examine whether there is a relative advantage of cognitive therapy or antidepressant medication in improving employment status following treatment, using data from a previously reported trial.

Random assignment to cognitive therapy (n = 48) or the selective serotonin reuptake inhibitor paroxetine (n = 93) for 4 months; treatment responders were followed for up to 24 months. Differential effects of treatment on employment status were examined.

At the end of 28 months, cognitive therapy led to higher rates of full-time employment (88.9%) than did antidepressant medication among treatment responders (70.8%), χ2 1 = 5.78, P = 0.02, odds ratio (OR) = 5.66, 95% CI 1.16–27.69. In the shorter-term, the main effect of treatment on employment status was not significant following acute treatment(χ2 1 = 1.74, P = 0.19, OR = 1.77, 95% CI 0.75–4.17); however, we observed a site×treatment interaction(χ2 1 = 6.87, P = 0.009) whereby cognitive therapy led to a higher rate of full-time employment at one site but not at the other.

Cognitive therapy may produce greater improvements in employmentv. medication, particularly over the longer term.

Pattern analysis has emerged as a tool to depict the role of multiple nutrients/foods in relation to health outcomes. The present study aimed at extracting nutrient patterns with respect to breast cancer (BC) aetiology.

Nutrient patterns were derived with treelet transform (TT) and related to BC risk. TT was applied to twenty-three log-transformed nutrient densities from dietary questionnaires. Hazard ratios (HR) and 95 % confidence intervals computed using Cox proportional hazards models quantified the association between quintiles of nutrient pattern scores and risk of overall BC, and by hormonal receptor and menopausal status. Principal component analysis was applied for comparison.

The European Prospective Investigation into Cancer and Nutrition (EPIC).

Women (n 334 850) from the EPIC study.

The first TT component (TC1) highlighted a pattern rich in nutrients found in animal foods loading on cholesterol, protein, retinol, vitamins B12 and D, while the second TT component (TC2) reflected a diet rich in β-carotene, riboflavin, thiamin, vitamins C and B6, fibre, Fe, Ca, K, Mg, P and folate. While TC1 was not associated with BC risk, TC2 was inversely associated with BC risk overall (HRQ5 v. Q1=0·89, 95 % CI 0·83, 0·95, Ptrend<0·01) and showed a significantly lower risk in oestrogen receptor-positive (HRQ5 v. Q1=0·89, 95 % CI 0·81, 0·98, Ptrend=0·02) and progesterone receptor-positive tumours (HRQ5 v. Q1=0·87, 95 % CI 0·77, 0·98, Ptrend<0·01).

TT produces readily interpretable sparse components explaining similar amounts of variation as principal component analysis. Our results suggest that participants with a nutrient pattern high in micronutrients found in vegetables, fruits and cereals had a lower risk of BC.

Neuroimaging measures of behavioral and emotional dysregulation can yield biomarkers denoting developmental trajectories of psychiatric pathology in youth. We aimed to identify functional abnormalities in emotion regulation (ER) neural circuitry associated with different behavioral and emotional dysregulation trajectories using latent class growth analysis (LCGA) and neuroimaging.

A total of 61 youth (9–17 years) from the Longitudinal Assessment of Manic Symptoms study, and 24 healthy control youth, completed an emotional face n-back ER task during scanning. LCGA was performed on 12 biannual reports completed over 5 years of the Parent General Behavior Inventory 10-Item Mania Scale (PGBI-10M), a parental report of the child's difficulty regulating positive mood and energy.

There were two latent classes of PGBI-10M trajectories: high and decreasing (HighD; n = 22) and low and decreasing (LowD; n = 39) course of behavioral and emotional dysregulation over the 12 time points. Task performance was >89% in all youth, but more accurate in healthy controls and LowD versus HighD (p < 0.001). During ER, LowD had greater activity than HighD and healthy controls in the dorsolateral prefrontal cortex, a key ER region, and greater functional connectivity than HighD between the amygdala and ventrolateral prefrontal cortex (p's < 0.001, corrected).

Patterns of function in lateral prefrontal cortical–amygdala circuitry in youth denote the severity of the developmental trajectory of behavioral and emotional dysregulation over time, and may be biological targets to guide differential treatment and novel treatment development for different levels of behavioral and emotional dysregulation in youth.