Severity is an important characteristic of major depression (MD) and an ‘episode specifier’ in DSM-IV classifying depressive episodes as ‘mild’, ‘moderate’ or ‘severe’. These severity subtypes rely on three different measures of severity: number of criteria symptoms, severity of the symptoms and degree of functional disability. No prior empirical study has evaluated the coherence and validity of the DSM-IV definition of severity of MD.

In a sample of 1015 (518 males, 497 females) Caucasian twins from a population-based registry who met criteria for MD in the year prior to interview, factor analysis and logistic regression were conducted to examine the inter-relationships of the three severity measures and their associations with a wide range of potential validators including demographic factors, risk for future episodes, risk of MD in the co-twin, characteristics of the depressive episode, the pattern of co-morbidity, and personality traits.

Correlations between the three severity measures were significant but moderate. Factor analysis indicated the existence of a general severity factor, but the factor was not highly coherent. The three severity measures showed differential predictive ability for most of the validators.

Severity of MD as defined by the DSM-IV is a multifaceted and heterogeneous construct. The three proposed severity measures reflect partly overlapping but partly independent domains with differential validity as assessed by a wide range of clinical characteristics. Clinicians should probably use a combination of severity measures as proposed in DSM-IV rather than privileging one.

Bipolar disorder (BD) is a highly heritable mood disorder with complex genetic architecture and poorly understood etiology. Previous transcriptomic BD studies have had inconsistent findings due to issues such as small sample sizes and difficulty in adequately accounting for confounders like medication use.

We performed a differential expression analysis in a well-characterized BD case-control sample (Nsubjects = 480) by RNA sequencing of whole blood. We further performed co-expression network analysis, functional enrichment, and cell type decomposition, and integrated differentially expressed genes with genetic risk.

While we observed widespread differential gene expression patterns between affected and unaffected individuals, these effects were largely linked to lithium treatment at the time of blood draw (FDR < 0.05, Ngenes = 976) rather than BD diagnosis itself (FDR < 0.05, Ngenes = 6). These lithium-associated genes were enriched for cell signaling and immune response functional annotations, among others, and were associated with neutrophil cell-type proportions, which were elevated in lithium users. Neither genes with altered expression in cases nor in lithium users were enriched for BD, schizophrenia, and depression genetic risk based on information from genome-wide association studies, nor was gene expression associated with polygenic risk scores for BD.

These findings suggest that BD is associated with minimal changes in whole blood gene expression independent of medication use but emphasize the importance of accounting for medication use and cell type heterogeneity in psychiatric transcriptomic studies. The results of this study add to mounting evidence of lithium's cell signaling and immune-related mechanisms.

There is still little knowledge of objective suicide risk stratification.

This study aims to develop models using machine-learning approaches to predict suicide attempt (1) among survey participants in a nationally representative sample and (2) among participants with lifetime major depressive episodes. We used a cohort called the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) that was conducted in two waves and included a nationally representative sample of the adult population in the United States. Wave 1 involved 43 093 respondents and wave 2 involved 34 653 completed face-to-face reinterviews with wave 1 participants. Predictor variables included clinical, stressful life events, and sociodemographic variables from wave 1; outcome included suicide attempt between wave 1 and wave 2.

The model built with elastic net regularization distinguished individuals who had attempted suicide from those who had not with an area under the ROC curve (AUC) of 0.89, balanced accuracy 81.86%, specificity 89.22%, and sensitivity 74.51% for the general population. For participants with lifetime major depressive episodes, AUC was 0.89, balanced accuracy 81.64%, specificity 85.86%, and sensitivity 77.42%. The most important predictor variables were a diagnosis of borderline personality disorder, post-traumatic stress disorder, and being of Asian descent for the model in all participants; and previous suicide attempt, borderline personality disorder, and overnight stay in hospital because of depressive symptoms for the model in participants with lifetime major depressive episodes. Random forest and artificial neural networks had similar performance.

Risk for suicide attempt can be estimated with high accuracy.

Major depressive disorder (MDD) is highly heterogeneous and can be classified as treatment-resistant depression (TRD) or antidepressant-responsive depression (non-TRD) based on patients' responses to antidepressant treatment. Methods for distinguishing between TRD and non-TRD are critical clinical concerns. Deficits of cortical inhibition (CI) have been reported to play an influential role in the pathophysiology of MDD. Whether TRD patients' CI is more impaired than that of non-TRD patients remains unclear.

Paired-pulse transcranial magnetic stimulation (ppTMS) was used to measure cortical inhibitory function including GABAA- and GABAB-receptor-related CI and cortical excitatory function including glutamate-receptor-related intracortical facilitation (ICF). We recruited 36 healthy controls (HC) and 36 patients with MDD (non-TRD, n = 16; TRD, n = 20). All participants received evaluations for depression severity and ppTMS examinations. Non-TRD patients received an additional ppTMS examination after 3 months of treatment with the SSRI escitalopram.

Patients with TRD exhibited reduced short-interval intracortical inhibition (SICI) and long-interval intracortical inhibition (LICI), as shown by abnormally higher estimates, than those with non-TRD or HC (F = 11.030, p < 0.001; F = 10.309, p < 0.001, respectively). After an adequate trial of escitalopram treatment, the LICI of non-TRD reduced significantly (t = − 3.628, p < 0.001), whereas the ICF remained lower than that of HC and showed no difference from pretreatment non-TRD.

TRD was characterized by relatively reduced CI, including both GABAA- and GABAB-receptor-mediated neurons while non-TRD preserved partial CI. In non-TRD, SSRIs may mainly modulate GABAB-receptor-related LICI. Our findings revealed distinguishable features of CI in antidepressant-resistant and responsive major depression.

Generalization of conditioned-fear, a core feature of post-traumatic stress disorder (PTSD), has been the focus of several recent neuroimaging studies. A striking outcome of these studies is the frequency with which neural correlates of generalization fall within hubs of well-established functional networks including salience (SN), central executive (CEN), and default networks (DN). Neural substrates of generalization found to date may thus reflect traces of large-scale brain networks that form more expansive neural representations of generalization. The present study includes the first network-based analysis of generalization and PTSD-related abnormalities therein.

fMRI responses in established intrinsic connectivity networks (ICNs) representing SN, CEN, and DN were assessed during a generalized conditioned-fear task in male combat veterans (N = 58) with wide-ranging PTSD symptom severity. The task included five rings of graded size. Extreme sizes served as conditioned danger-cues (CS+: paired with shock) and safety-cues (CS−), and the three intermediate sizes served as generalization stimuli (GSs) forming a continuum-of-size between CS+ and CS–. Generalization-gradients were assessed as behavioral and ICN response slopes from CS+, through GSs, to CS–. Increasing PTSD symptomatology was predicted to relate to less-steep slopes indicative of stronger generalization.

SN, CEN, and DN responses fell along generalization-gradients with levels of generalization within and between SN and CEN scaling with PTSD symptom severity.

Neural substrates of generalized conditioned-fear include large-scale networks that adhere to the functional organization of the brain. Current findings implicate levels of generalization in SN and CEN as promising neural markers of PTSD.

Although depression and mania are often assumed to be polar opposites, studies have shown that, in patients with bipolar disorder, they are weakly positively correlated and vary somewhat independently over time. Thus, when investigating relationships between specific psychological processes and specific symptoms (mania and depression), co-morbidity between the symptoms and changes over time must be taken into account.

A total of 253 bipolar disorder patients were assessed every 24 weeks for 18 months using the Hamilton Rating Scale for Depression (HAMD), the Bech–Rafaelsen Mania Assessment Scale (MAS), the Rosenberg Self-Esteem Questionnaire (RSEQ), the Dysfunctional Attitudes Scale (DAS), the Internal, Personal and Situational Attributions Questionnaire (IPSAQ) and the Personal Qualities Questionnaire (PQQ). We calculated multilevel models using the xtreg module of Stata 9.1, with psychological and clinical measures nested within each participant.

Mania and depression were weakly, yet significantly, associated; each was related to distinct psychological processes. Cross-sectionally, self-esteem showed the most robust associations with depression and mania: depression was associated with low positive and high negative self-esteem, and mania with high positive self-esteem. Depression was significantly associated with most of the other self-referential measures, whereas mania was weakly associated only with the externalizing bias of the IPSAQ and the achievement scale of the DAS. Prospectively, low self-esteem predicted future depression.

The associations between different self-referential thinking processes and different phases of bipolar disorder, and the presence of the negative self-concept in both depression and mania, have implications for therapeutic management, and also for future directions of research.

One putative psychological mechanism through which momentary stress impacts on psychosis in individuals with increased liability to the disorder is via affective disturbance. However, to date, this has not been systematically tested. We aimed to investigate whether (i) cross-sectional and temporal effects of momentary stress on psychotic experiences via affective disturbance, and (ii) the reverse pathway of psychotic experiences on stress via affective disturbance were modified by familial liability to psychosis.

The Experience Sampling Method was used in a pooled data set of six studies with three groups of 245 individuals with psychotic disorder, 165 unaffected first-degree relatives, and 244 healthy control individuals to index familial liability. Multilevel moderated mediation models were fitted to investigate indirect effects across groups cross-sectionally and multilevel cross-lagged panel models to investigate temporal effects in the proposed pathways across two measurement occasions.

Evidence on indirect effects from cross-sectional models indicated that, in all three groups, effects of stress on psychotic experiences were mediated by negative affect and, vice versa, effects of psychotic experiences on stress were mediated by negative affect, with all indirect effects being weakest in relatives. Longitudinal modelling of data provided no evidence of temporal priority of stress in exerting its indirect effects on psychotic experiences via affective disturbance or, vice versa.

Our findings tentatively suggest a rapid vicious cycle of stress impacting psychotic experiences via affective disturbances, which does, however, not seem to be consistently modified by familial liability to psychosis.

Few studies have examined the short-term course of cognitive impairments in bipolar disorder (BD). Key questions are whether trajectories in symptoms covary with cognitive function and whether BD is associated with increased intra-individual variability in cognitive abilities.

Forty-two out-patients with BD and 49 normal comparison (NC) subjects were administered a battery of neuropsychological tests at baseline, 6, 12 and 26 weeks, along with concurrent ratings of depressive and manic symptom severity. Mixed-effects regressions were used to model relationships between time, diagnosis and symptom severity on composite cognitive performance. Within-person variance in cognitive functioning across time was calculated for each subject.

BD patients had significantly worse performance in cognitive ability across time points, but both groups showed significant improvement in cognitive performance over repeated assessments (consistent with expected practice effects). BD was associated with significantly greater intra-individual variability in cognitive ability than NCs; within-person variation was negatively related to baseline cognitive ability in BD but not NC subjects. Changes in affective symptoms over time did not predict changes in cognitive ability.

Moderate changes in affective symptoms did not covary with cognitive ability in BD. The finding of elevated intra-individual variability in BD may reduce capacity to estimate trajectories of cognitive ability in observational and treatment studies.