BACKGROUND: Electroencephalography (EEG) is a noninvasive, cost-effective, and robust tool, which directly measures in vivo neuronal mass activity with high temporal resolution. Combined with state-of-the-art machine learning (ML) techniques, EEG recordings could potentially yield in silico biomarkers of severe mental disorders.
OBJECTIVE: Pathological and physiological aging processes influence the electrophysiological signatures of schizophrenia (SCZ) and major depressive disorder (MDD).
METHODS: From a single-center cohort (N = 735, 51.6% male) comprising healthy control individuals (HC, N = 245) and inpatients suffering from SCZ (N = 250) or MDD (N = 240), we acquired resting-state 19 channel-EEG recordings. Using repeated nested cross-validation, support vector machine models were trained to (1) classify patients with SCZ or MDD and HC individuals and (2) predict age in HC individuals. The age model was applied to patient groups to calculate Electrophysiological Age Gap Estimation (EphysAGE) as the difference between predicted and chronological age. The links between EphysAGE, diagnosis, and medication were then further explored.
RESULTS: The classification models robustly discriminated SCZ from HC (balanced accuracy, BAC = 72.7%, P < .001), MDD from HC (BAC = 67.0%, P < .001), and SCZ from MDD individuals (BAC = 63.2%, P < .001). Notably, central alpha (8-11 Hz) power decrease was the most consistently predictive feature for SCZ and MDD. Higher EphysAGE was associated with an increased likelihood of being misclassified as SCZ in HC and MDD (ρHC = 0.23, P < .001; ρMDD = 0.17, P = .01).
CONCLUSIONS: ML models can extract electrophysiological signatures of MDD and SCZ for potential clinical use. However, the impact of aging processes on diagnostic separability calls for timely application of such models, possibly in early recognition settings.

Parenting a child on the autism spectrum presents particular challenges that can lead to increased stress, anxiety, and depression among family members. Therefore, we aimed to investigate the prevalence of mental disorders in first-degree relatives of individuals on the autism spectrum. This article adheres to the Preferred Reporting Items for Systematic Review and Meta-Analyses Protocols (PRISMA-P) guidelines, including studies indexed in PubMed/Medline, Embase, PsycINFO, Biblioteca Virtual em Saúde (BVS), and SciELO. Nineteen articles met eligibility criteria for the systematic review. Using a random-effects model (N = 93,876), we found a pooled prevalence of affective disorders of 13% in mothers of people on the autism spectrum (95% CI 7-21%; I2 = 99%, p < 0.01). Additionally, another random-effects model pointed out that first-degree relatives of people on the autism spectrum (N = 93,263) were more likely to present affective disorders than relatives of people with neurotypical development (N = 152,455) (pooled OR: 2.17; 95% CI 1.81-2.61). Careful assessment for mental disorders in parents and siblings of individuals on the autism spectrum is crucial to ensure appropriate treatment for these family members. This approach can also contribute to optimizing care for the individuals on the autism spectrum.

Because the offspring of parents with an affective disorder (OAD) are at high risk for developing mental disorders, and persons with an affective disorder (AD) show dysfunctional hypothalamic-pituitary-adrenal (HPA) axis activity, changes in HPA functioning in OAD might be an etiological risk factor that precedes the development of ADs. The primary aim of the meta-analysis was to quantitatively summarize the existing data on different indices of diurnal cortisol in the OAD. The secondary aim was to explore potential moderators of this relation. Following PRISMA guidelines, we included 26 studies (3052 offspring) on diurnal cortisol in our meta-analysis after an initial screening of 3408 articles. Intercept-only and meta-regression models were computed using the robust variance estimation method. Analyses examining mean cortisol levels at discrete timepoints, total cortisol output, and the cortisol rise in response to awakening (CAR) were conducted separately. The results demonstrated that the OAD had higher mean levels of cortisol at different timepoints throughout the day compared to controls (Hedge\'s g = 0.21). There was evidence of publication bias in studies examining CAR, such that effect sizes were positively biased. The present findings are consistent with a meta-analysis showing elevated cortisol in youth having an AD. Notable limitations across studies include the method of cortisol measurement and assessment of ADs. Altogether, these results highlight the fact that increased cortisol levels may act as a potential neuroendocrine antecedent and/or risk factor for the development of ADs among high risk youth.

This mini-review presents our current understanding of serotonin type 7 receptor research focusing on the possible network mechanisms underlying the behavioral action of receptor antagonists. The serotonin type 7 receptor is expressed widely throughout the nervous system and known to be involved in various cognitive and physiological mechanisms. It became a clinically significant target after the discovery that its selective antagonist SB 269970 can exert rapid-onset antidepressant effects either alone or in combination with lower doses of conventional antidepressant drugs. Further research has shown that administration of SB 269970 can effectively counteract negative neurobiological outcomes in various chronic stress paradigms. The authors hope they can introduce a wider scientific audience to this promising pharmacological target which, if successful, could in time lead to more discoveries and a better understanding of the underlying serotonin receptor biology as well as its clinical potential. HIGHLIGHTS.

Inflammation and autoimmune responses contribute to the pathophysiology of Long COVID, and its affective and chronic fatigue syndrome symptoms, labeled \"the physio-affective phenome.\" To investigate whether Long COVID and its physio-affective phenome are linked to autoimmunity to the tight junction proteins, zonulin and occludin (ZOOC), and immune reactivity to lipopolysaccharides (LPS), and whether the latter are associated with signs of human herpes virus-6 (HHV-6) reactivation, autoimmunity directed against oligodendrocyte and neuronal proteins, including myelin basic protein. IgA/IgM/IgG responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), HHV-6, ZOOC, and neuronal proteins, C-reactive protein (CRP), and advanced oxidation protein products (AOPPs), were measured in 90 Long COVID patients and 90 healthy controls. The physio-affective phenome was conceptualized as a factor extracted from physical and affective symptom domains. Neural network identified IgA directed to LPS (IgA-LPS), IgG-ZOOC, IgG-LPS, and IgA-ZOOC as important variables associated with Long COVID diagnosis with an area under the ROC curve of 0.755. Partial Least Squares analysis showed that 40.9% of the variance in the physio-affective phenome was explained by CRP, IgA-myelin basic protein (MBP), and IgG-MBP. A large part of the variances in both autoimmune responses to MBP (36.3%-39.7%) was explained by autoimmunity (IgA and IgG) directed to ZOOC. The latter was strongly associated with indicants of HHV-6 reactivation, which in turn was associated with increased IgM-SARS-CoV-2. Autoimmunity against components of the tight junctions and increased bacterial translocation may be involved in the pathophysiology of Long COVID\'s physio-affective phenome.

OBJECTIVE: Minocycline suppresses chemotherapy-induced neuroinflammation in preclinical models, but its effects in cancer survivors are unknown. This study evaluated the longitudinal effects of minocycline on affective behaviors, cognitive functions, and inflammation in women with breast cancer (BC) undergoing chemotherapy.
METHODS: This is a pilot, double-blind, randomized controlled trial of oral minocycline (100 mg BID) versus placebo for chemotherapy-induced affective disorders in women initiating chemotherapy for stage I-III BC. Participants received minocycline or placebo up to one week before chemotherapy, continuing through cycle 4 (C4). Epidemiologic Studies Depression Scale (CES-D) and State-Trait Anxiety Inventory (STAI) were assessed at baseline, each cycle of chemotherapy (C1-C4), 2-3-week post-chemotherapy (end of chemotherapy), and 6-month post-chemotherapy (6 M) as the primary outcomes. Sub-group analysis of CES-D and STAI based on the severity of symptoms was also performed. Changes in self-reported cognition and serum inflammatory markers were also evaluated.
RESULTS: Fifty-seven women enrolled and 55 completed the study. Except for Interleukin-8 (p ≤ 0.03), changes in inflammatory markers, cognitive function, CES-D, and STAI were not significantly different between groups from baseline to any cycle or post-chemotherapy time point (all p > 0.05), adjusting for baseline scores. Increases in serum Interleukin-8 from baseline to C4 and 6 M were ameliorated by minocycline (p < 0.05). The sub-group symptomatic for depression (CES-D > = 16 at baseline) treated with minocycline had a greater reduction in CES-D score compared to placebo from baseline to 6 M (p = 0.01).
CONCLUSIONS: Despite attenuation of IL-8, minocycline did not alter self-reported affective symptoms or cognition in this cohort of BC survivors undergoing chemotherapy. The effect of minocycline on BC survivors symptomatic for depression before chemotherapy warrants further investigation.

Identifying components of modularized psychological interventions that contribute to symptom reduction is essential to improving depression treatment. In a secondary analysis of a randomized controlled trial (RCT), session-specific effects of Metacognitive Training-Silver, a group intervention for older adults with depression, were investigated. Thirty-eight older adults with major depressive disorder or dysthymia participated in up to eight sessions of MCT-Silver. A clinical assessment of depressive symptoms (Hamilton Depression Rating Scale) as well as additional interviews and questionnaires administered as part of the RCT were completed at pre- and post-intervention. Depressive symptoms, negative (meta)cognitive beliefs, emotion regulation strategies and attitudes toward aging were assessed pre- and post-session. The rate of change in each variable per module, elevation following the module in which the variable was addressed, and the rate of change post module were examined via linear mixed models. Clinician-rated depressive symptoms were significantly reduced from pre- to post-intervention (Cohens d = 1.31). Self-reported depression and negative mental filter measured within sessions improved significantly over treatment, whereas black-and-white thinking improved after module #3 (Should Statements, All or Nothing Thinking and Acceptance). Module-specific within-session effects were found for overgeneralization (module #1: Mental Filter) and rumination (module #6: Rumination and Social Withdrawal). Improvement in mental filter in module #1 was significantly associated with depression reduction. This study provides initial evidence that MCT-Silver partially meets its aims of reducing depression and specific cognitive variables within and across sessions. Improvement of the instrument used to measure change may improve detection of module-specific effects.Trial registration: NCT03691402.

BACKGROUND: Affective disorders (AD) have been linked to inflammatory processes, although the underlying mechanisms of this relationship are still not fully elucidated. It is hypothesized that demographic, somatic, lifestyle, and personality variables predict inflammatory parameters in AD.
OBJECTIVE: To identify biopsychosocial factors contributing to inflammation in AD measured with two parameters, C-reactive protein (CRP) and leukocytes.
METHODS: This observational study investigated 186 hospital inpatients diagnosed with AD using demographic parameters, serum inflammatory markers, somatic variables, psychological questionnaires, and lifestyle parameters. Hierarchical regression analyses were used to predict inflammatory markers from demographic, somatic, lifestyle, and personality variables.
RESULTS: Analyses showed that 33.8% of the variance of CRP was explained by body mass index and other somatic medication (e.g. anti-diabetics), age and education, and age of affective disorder diagnosis. For leukocytes, 20.1% of the variance was explained by smoking, diet, metabolic syndrome (MetS), and anti-inflammatory medication (e.g. non-steroidal anti-inflammatory drugs). Other psychiatric or behavioural variables did not reach significance.
CONCLUSIONS: Metabolic components seem important, with mounting evidence for a metabolic affective disorder subtype. Lifestyle modifications and psychoeducation should be employed to prevent or treat MetS in AD.

The concept of affective temperament has been extensively discussed throughout the history of psychopathology and represents a cornerstone in the study of mood disorders. This review aims to trace the evolution of the concept of affective temperaments (ATs) from Kraepelin\'s seminal work to the present day. In the 1980s, Akiskal redefined Kraepelin\'s concept of affective temperaments (ATs) by integrating the five recognized ATs into the broader framework of the soft bipolar spectrum. This conceptualization viewed ATs as non-pathological predispositions underlying psychiatric disorders, particularly mood disorders. Epidemiological and clinical studies have validated the existence of the five ATs. Furthermore, evidence suggests that ATs may serve as precursors to various psychiatric disorders and influence clinical dimensions such as disease course, psychopathology, and treatment adherence. Additionally, ATs appear to play a significant role in moderating phenomena such as suicide risk and stress coping. Incorporating an evaluation of temperamental bases of disorders into the multidimensional psychiatric diagnostic process could enhance treatment optimization and prognosis estimation.

Growth factors, T helper (Th)1 polarization, and the microbiome are involved in the pathophysiology of major depression (MDD). It remains unclear whether the combination of these three pathways could enhance the accuracy of predicting the features of MDD, including recurrence of illness (ROI), suicidal behaviors and the phenome. We measured serum stem cell factor (SCF), stem cell growth factor (SCGF), stromal cell-derived factor-1 (SDF-1), platelet-derived growth factor (PDGF), hepatocyte growth factor (HGF), macrophage-colony stimulating factor (M-CSF) and vascular endothelial growth factor (VEGF), the ratio of serum Th1/Th2 cytokines (zTh1-zTh2), and the abundances of gut microbiome taxa by analyzing stool samples using 16S rDNA sequencing from 32 MDD patients and 37 healthy controls. The results show that serum SCF is significantly lower and VEGF increased in MDD. Adverse childhood experiences (ACE) and ROI are significantly associated with lowered SCF and increasing VEGF. Lifetime and current suicidal behaviors are strongly predicted (63.5%) by an increased VEGF/SCF ratio, Th1 polarization, a gut microbiome enterotype indicating gut dysbiosis, and lowered abundance of Dorea and Faecalobacterium. Around 80.5% of the variance in the phenome\'s severity is explained by ROI, ACEs, and lowered Parabacteroides distasonis and Clostridium IV abundances. A large part of the variance in health-related quality of life (54.1%) is explained by the VEGF/SCF ratio, Th1 polarization, ACE, and male sex. In conclusion, key features of MDD are largely predicted by the cumulative effects of ACE, Th1 polarization, aberrations in growth factors and the gut microbiome with increased pathobionts but lowered beneficial symbionts.