Prospective biomarkers of major depressive disorder: a systematic review and meta-analysis

How intersectional identity and discrimination contribute to depressive symptoms and hair cortisol concentrations among low-income, racially and sexual diverse adults

Significant gaps remain in our understanding of how minority stress patterns health outcomes for adults at the intersection of ethnicity/ race and sexual orientation. In particular, little is known about how cumulative cortisol (measured via hair cortisol concentration as an indicator of chronic stress; HCC) and depressive symptoms are related to holding an intersectional minoritized identity (e.g., sexual minority people of color; SM-POC) and experiencing intersectional discrimination (e.g., heterosexism and racism). The current study examined the relationship between intersectional identity or discrimination and HCC or depressive symptoms. Participants were (N = 69) low-income, predominantly sexual minority and people of color in the Greater Los Angeles area. Participants completed self-report measures and provided a hair sample for cortisol assay. Intersectional identity was not associated with greater HCC or depressive symptoms. However, differences in HCC emerged based on discrimination type (F (2, 66) = 3.74, p = .03, η2= .10). Participants who reported intersectional heterosexism and racism had greater HCC concentrations (M = 30.71, SD = 29.71) than did participants who reported only a single type of discrimination (i.e., racism only or heterosexism only; M = 15.35, SD = 2.60, p = .03, 95 % CI = [2.01, 28.71]), or than participants who reported neither types (M = 12.40, SD = 16.11, p = .01, 95 % CI [4.85, 31.76]). There were no differences in depressive symptoms by discrimination type. These results provide initial empirical support to largely theoretical arguments about how to investigate mechanisms underlying disparities to understand why and how minority stress is patterned. Findings showing associations between intersectional discrimination and HCC, but not depressive symptoms, provide potential support for theories about examining allostatic load markers to identify stress-related etiological mechanisms linked to health disparities among minoritized populations.

Chronic mild stress disrupts mitophagy and mitochondrial status in rat frontal cortex

BACKGROUND

Mitochondria are very dynamic organelles that maintain cellular homeostasis, crucial in the central nervous system. Mitochondrial abnormalities have been described in neuropsychiatric diseases, namely major depression disorder (MDD) and schizophrenia. Since stress is the predominant non-genetic cause of MDD, and has a direct impact on mitochondrial networks, understanding how psychological stress affects mitochondrial health is vital to improve the current pharmacological therapies.

METHODS

The effect of 21 days of unpredictable stress was evaluated in frontal cortex of Wistar male rats comparing protein and gene markers of mitophagy (PINK1, PARKIN, BNIP3, NIX, FUNDC1), mitochondrial biosynthesis (PGC1α, NRF1, TFAM) and dynamics (MFN1, MFN2, OPA1, DRP1), and mitochondrial presence within microglia with the MitoTracker Green FM™ probe.

RESULTS

Chronic mild stress (CMS) caused the upregulation of mitochondrial mass, mitochondria depolarization, dysregulation in mitochondrial dynamics towards fusion, the increase of mitophagy markers and the induction of genes that activate mitochondrial biogenesis in frontal cortex. CMS also promoted microglia recruitment and mitochondrial number boosting within them.

CONCLUSIONS

There is a dysregulation of mitochondrial dynamics towards fusion, an upregulation of mitophagy markers, and the induction of genes associated with mitochondrial biogenesis in response to CMS in the frontal cortex of adult rats. This study highlights the impact of psychological stress on brain mitochondrial networks.

Predicting depression in healthy young adults: A machine learning approach using longitudinal neuroimaging data

Accurate prediction of depressive symptoms in healthy individuals can enable early intervention and reduce both individual and societal costs. This study aimed to develop predictive models for depression in young adults using machine learning (ML) techniques and longitudinal data from the Beck Depression Inventory, structural MRI (sMRI), and resting-state functional MRI (rs-fMRI). Feature selection methods, including the least absolute shrinkage and selection operator (LASSO), Boruta, and VSURF, were applied to identify MRI features associated with depression. Support vector machine and random forest algorithms were then used to construct prediction models. Eight MRI features were identified as predictive of depression, including brain regions in the Orbital Gyrus, Superior Frontal Gyrus, Middle Frontal Gyrus, Parahippocampal Gyrus, Cingulate Gyrus, and Inferior Parietal Lobule. The overlaps and the differences between selected features and brain regions with significant between-group differences in t-tests suggest that ML provides a unique perspective on the neural changes associated with depression. Six pairs of prediction models demonstrated varying performance, with accuracies ranging from 0.68 to 0.85 and areas under the curve (AUC) ranging from 0.57 to 0.81. The best-performing model achieved an accuracy of 0.85 and an AUC of 0.80, highlighting the potential of combining sMRI and rs-fMRI features with ML for early depression detection while revealing the potential of overfitting in small-sample and high-dimensional settings. This study necessitates further research to (1) replicate findings in independent larger datasets to address potential overfitting and (2) utilize different advanced ML techniques and multimodal data fusion to improve model performance.

Dissecting heterogeneity in major depressive disorder via normative model-driven subtyping of functional brain networks

BACKGROUND

Major depressive disorder (MDD) is a prevalent and intricate mental health condition characterized by a wide range of symptoms. A fundamental challenge in understanding MDD lies in elucidating the brain mechanisms underlying the complexity and diversity of these symptoms, particularly the heterogeneity reflected in individual differences and subtype variations within brain networks.

METHODS

To address this problem, we explored the brain network topology using resting-state functional magnetic resonance imaging (rs-fMRI) data from a cohort of 797 MDD patients and 822 matched healthy controls (HC). Utilizing normative modeling of HC, we quantified individual deviations in brain network degree centrality among MDD patients. Through k-means clustering of these deviation profiles, we identified two clinically meaningful MDD subtypes. Moreover, we employed Neurosynth to analyze the cognitive correlates of these subtypes.

RESULTS

Subtype 1 exhibited positive deviations of degree centrality in the limbic (LIM), frontoparietal (FPN), and default mode networks (DMN), but negative deviations in the visual (VIS) and sensorimotor networks (SMN), positively correlating with higher cognitive functions and negatively with basic perceptual processes. In contrast, subtype 2 demonstrated opposing patterns, characterized by negative deviations in degree centrality of the LIM, FPN, and DMN and positive deviations of the VIS and SMN, along with inverse cognitive associations.

CONCLUSIONS

Our findings underscore the heterogeneity within MDD, revealing two distinct patterns of network topology between unimodal and transmodal networks, offering a valuable reference for personalized diagnosis and treatment strategies.

Differences in baseline and dynamic plasma/saliva endocrine and linear/non-linear heart measures between patients with major depression and closely-matched healthy subjects: A 3-day combined overnight dexamethasone/metyrapone challenge study

BACKGROUND

Major depressive disorder (MDD) has been consistently associated with hypothalamic-pituitary-adrenal (HPA)-axis and autonomic nervous system (ANS) (re-)activity abnormalities, however, often with conflicting results.

METHODS

This study offers a concurrent multi-measure assessment of both HPA-axis and ANS activity and reactivity over 3 days to better characterize baseline and dynamic neuroendocrine alterations in MDD accounting for multiple individual factors. We therefore investigated group differences between 20 unmedicated MDD patients and 20 carefully-matched healthy controls (HC) by simultaneously assessing morning plasma (CORT, ACTH, copeptin) and awakening response saliva (CORT, DHEA, DHEA-s) endocrine measures, as well as multiple linear and non-linear measures of resting heart rate (HR) and its variability (HRV), before (baseline, day 1) and after a successive overnight metyrapone (HPA-axis stimulation, day 2) and dexamethasone (HPA-axis suppression, day 3) pharmaco-endocrine challenge, controlling for childhood trauma (CT) history.

RESULTS

Statistically significant group differences emerged only for baseline plasma CORT and ACTH levels (MDD > HC) and resting HR in all 3 days. No differences were found in dynamic plasma levels and all saliva endocrine measures, as well as all HRV measures. Baseline HR was the only significant predictor for MDD diagnosis.

CONCLUSIONS

Our detailed baseline and dynamic neuroendocrine comparison using closely matched HC indicates fewer neuroendocrine alterations in MDD than expected. These results challenge prior findings and support the importance of exact matching when investigating neuroendocrine biomarkers, as previously reported findings may rely on unaccounted individual but not group differences.

Parsing clinical and neurobiological sources of heterogeneity in depression

BACKGROUND

Patients with depression vary from one-another in their clinical and neuroimaging presentation, yet the relationship between clinical and neuroimaging sources of variation is poorly understood. Determining sources of heterogeneity in depression is important to gain insights into its diverse and complex neural etiology. This study aims to test if depression heterogeneity is characterized by subgroups that differ both clinically and neurobiologically and/or whether multiple neuroimaging profiles give rise to the same clinical presentation.

METHODS

This study utilizes population-based data from the UK Biobank over multiple imaging sites. Clinically dissociated groups were selected to isolate clinical characteristics of depression (symptoms of anhedonia, depressed mood, and somatic disturbance; severity indices of lifetime chronicity and acute impairment; and late onset). Residual neuroimaging heterogeneity within each group was assessed using neuroimaging driven clustering.

RESULTS

The clinically dissociated subgroups had significantly larger neuroimaging normative deviations than a comparison heterogeneous group and had distinct neuroimaging profiles from each other. Imaging driven clustering within each clinically dissociated group identified two stable subtypes within the acute impairment group that differed significantly in cognitive ability, despite identical clinical profiles.

CONCLUSIONS

The study identified distinct neuroimaging profiles related to particular clinical depression features that may explain inconsistencies in the literature and sub-clusters within the acute impairment group with cognitive differences that were only differentiable by neuroimaging. Our results provide evidence that multiple neuroimaging profiles may give rise to the same clinical presentation, emphasizing the presence of complex interactions between clinical and neuroimaging sources of heterogeneity.

Haematological markers of inflammation in major depressive disorder (MDD) patients with suicidal behaviour: A systematic review and meta-analysis

INTRODUCTION

Suicide is a significant global health issue linked to neuroinflammation. This study assessed neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR) as systemic inflammation indicators in suicidal behaviour of major depressive disorder (MDD) patients.

METHODS

The search included databases like Scopus, PubMed, PsycINFO, Web of Science, and CINAHL Complete, focusing on English-language observational studies up to March 2025. It examined the NLR, PLR, and MLR in individuals with MDD exhibiting suicidal behaviour, comparing them to MDD patients without such behaviors or healthy controls. Study quality was assessed using the Newcastle-Ottawa Scale (NOS), and data analysis utilized Stata software version 17.

RESULTS

From an initial 131 articles, ten studies were included, analyzing 2017 participants. MDD patients with suicidal behaviour had significantly elevated NLR levels compared to non-suicidal MDD patients (SMD: 0.34 [0.12, 0.56]; I2: 67.68 %) and healthy controls (SMD: 1.02 [0.28, 1.76]; I2: 96.15 %). Additionally, no differences in PLR levels were found in suicidal MDD patients compared to their non-suicidal counterparts (SMD: 0.11 [-0.04, 0.27]; I2: 38.39 %), but PLR levels were higher in comparison to healthy controls (SMD: 0.38 [0.17, 0.59]; I2: 38.02 %). Four studies showed higher MLR levels in suicidal MDD patients compared to the non-suicidal group (SMD: 0.33 [0.04, 0.62]; I2: 71.60 %) and healthy controls (SMD: 0.32 [0.06, 0.59]; I2: 44.37 %).

CONCLUSION

Increased inflammatory biomarkers in MDD patients with suicidal tendencies highlight the need for further research on their potential as suicide vulnerability indicators and the utility of NLR, PLR and MLR in clinical practice.

Psychological distress over 12 months post-diagnosis in an early inflammatory arthritis cohort

OBJECTIVES

People with inflammatory arthritis (IA) experience worsened mental wellbeing alongside disease progression. Using the National Early Inflammatory Arthritis Audit (NEIAA), we assessed trends in psychological distress during the 12 months following IA diagnosis, mapping these against clinical outcomes to identify associations.

METHODS

This is a prospective study of people recruited to NEIAA receiving an IA diagnosis and completing the baseline patient survey. Patient-reported outcomes (PROs) at baseline, 3 months and 12 months were collected, including psychological distress [assessed using Patient Health Questionnaire Anxiety and Depression Screener (PHQ4ADS)]. Mixed effects linear regression models estimated associations between predictor variables with psychological distress at baseline and over time.

RESULTS

Of 6873 eligible patients, 3451 (50.2%) showed psychological distress at baseline. Of those completing follow-ups, 30.0% and 24.1% were distressed at 3 months and 12 months, respectively. Higher psychological distress at diagnosis was more commonly reported by younger, female and non-White patients. Clinical factors, including higher counts of comorbidities, prior depression and higher disease activity at diagnosis were associated with higher distress. Higher distress at baseline was associated with poorer outcomes over time in quality of life, disability, work performance, disease activity, as well as reduced likelihood of achieving good treatment response by EULAR criteria.

CONCLUSION

Half of patients with IA show significant mental health comorbidity at presentation, which associated with worse disease outcomes and quality of life. Screening for anxiety and depression should be a universal standard, and access to effective mood therapies alongside arthritis treatments is essential. Strategies should be culturally valid and consider multi-morbidities.

Safety in treatment: Classical pharmacotherapeutics and new avenues for addressing maternal depression and anxiety during pregnancy

We aimed to review clinical research on the safety profiles of antidepressant drugs and associations with maternal depression and neonatal outcomes. We focused on neuroendocrine changes during pregnancy and their effects on antidepressant pharmacokinetics. Pregnancy-induced alterations in drug disposition and metabolism impacting mothers and their fetuses are discussed. We considered evidence for the risks of antidepressant use during pregnancy. Teratogenicity associated with ongoing treatment, new prescriptions during pregnancy, or pausing medication while pregnant was examined. The Food and Drug Administration advises caution regarding prenatal exposure to most drugs, including antidepressants, largely owing to a dearth of safety studies caused by the common exclusion of pregnant individuals in clinical trials. We contrasted findings on antidepressant use with the lack of treatment where detrimental effects to mothers and children are well researched. Overall, drug classes such as selective serotonin reuptake inhibitors and serotonin norepinephrine reuptake inhibitors appear to have limited adverse effects on fetal health and child development. In the face of an increasing prevalence of major mood and anxiety disorders, we assert that individuals should be counseled before and during pregnancy about the risks and benefits of antidepressant treatment given that withholding treatment has possible negative outcomes. Moreover, newer therapeutics, such as ketamine and κ-opioid receptor antagonists, warrant further investigation for use during pregnancy. SIGNIFICANCE STATEMENT: The safety of antidepressant use during pregnancy remains controversial owing to an incomplete understanding of how drug exposure affects fetal development, brain maturation, and behavior in offspring. This leaves pregnant people especially vulnerable, as pregnancy can be a highly stressful experience for many individuals, with stress being the biggest known risk factor for developing a mood or anxiety disorder. This review focuses on perinatal pharmacotherapy for treating mood and anxiety disorders, highlighting the current knowledge and gaps in our understanding of consequences of treatment.

Comparing Data-Driven Subtypes of Depression Informed by Clinical and Neuroimaging Data: A Registered Report

Background

Efforts to elucidate subtypes within depression have yet to establish a consensus. In this study, we aimed to rigorously compare different subtyping approaches in the same participant space to quantitatively test agreement across subtyping approaches and determine whether the different approaches are sensitive to different sources of heterogeneity in depression.

Methods

We implemented 6 different data-driven subtyping methods developed in previous work using the same UK Biobank participants (n = 2276 participants with depression, n = 1595 healthy control participants). The 6 approaches include 2 symptom-based, 2 structural neuroimaging-based, and 2 functional neuroimaging-based techniques. The resulting subtypes were compared based on participant assignment, stability, and sensitivity to subtype differences in demographics, general health, clinical characteristics, neuroimaging, trauma, cognition, genetics, and inflammation markers.

Results

We found almost no agreement between the resulting subtypes of the 6 approaches (mean adjusted Rand index [ARI] = 0.006), even within data domains. This finding was largely driven by differences in input feature set (mean ARI = 0.005) rather than clustering algorithm (mean ARI = 0.23). However, each approach had relatively high internal stability across bootstraps (ARI = 0.36-0.89); most approaches performed above null; and most approaches were sensitive to relevant phenotypes within their data domain.

Conclusions

Despite marginal overlap between approaches, we found the subtyping approaches to be internally consistent. These results explain why previous studies found strong evidence for subtypes within their analysis but with very little convergence between studies. We recommend that in future work, investigators incorporate systematic comparisons between their approach and alternative/previous approaches to facilitate consensus on depression subtypes.

Blunted cortisol as a biomarker of depression based on the attenuation hypothesis: A Mendelian randomization analysis using depression as exposure

BACKGROUND

Both elevated and blunted cortisol responses have been associated with depression. Previous Mendelian randomization (MR) studies have largely ruled out cortisol as a cause of depression. Based on the attenuation hypothesis, this MR study used depression as exposure to assess whether cortisol might be a consequence and therefore a biomarker of depression.

METHODS

Strong (P < 5 × 10-8) and independent (r2 < 0.001) single nucleotide polymorphisms (SNPs) associated with broadly defined depression (294,322 cases, 741,438 controls) were used as instruments. These were applied to genetic associations with morning, fasting, and random plasma cortisol in the CORtisol NETwork (CORNET) consortium (n = 25,314), METabolic Syndrome in Men (METSIM) study (n = 6667), and Canadian Longitudinal Study on Aging (CLSA) cohort (n = 8299). Multivariable MR, adjusting for childhood maltreatment and major mental disorders, was conducted to address potential horizontal pleiotropy from dichotomous depression. Instruments were also selected by evidence of colocalization with major depressive disorder to address non-specificity.

RESULTS

Using 133 SNPs as instruments, depression was inversely associated with morning plasma cortisol (β per log-odds of genetic liability to depression = -0.107 [95 % CI, -0.181 to -0.032]) in the CORNET consortium. Replication in the METSIM study (β = -0.203 [95 % CI, -0.367 to -0.040]) and CLSA cohort (β = -0.091 [95 % CI, -0.220 to 0.039]) showed consistent but not always significant associations. Multivariable MR and follow-up analysis incorporating colocalization supported these findings.

CONCLUSIONS

Consistent with the attenuation hypothesis, blunted cortisol response appeared to be a consequence and potentially a biomarker of depression. Future studies are needed to provide more interpretable effect sizes and validate other biomarker measures.

Identification and experimental validation of biomarkers associated with mitochondrial and programmed cell death in major depressive disorder

Background

Major depressive disorder (MDD) is associated with mitochondrial dysfunction and programmed cell death (PCD), though the underlying mechanisms remain unclear. This study aimed to investigate the molecular pathways involved in MDD using a transcriptomic analysis approach.

Methods

Transcriptomic data related to MDD were obtained from public databases. Differentially expressed genes (DEGs), PCD-related genes (PCDs), and mitochondrial-related genes (MitoGs) were analyzed to identify key gene sets: PCD-DEGs and MitoG-DEGs. Correlation analysis (|correlation coefficient| > 0.9, p < 0.05) was performed to select candidate genes. Protein-protein interaction (PPI) network analysis and intersection of four algorithms were used to identify key candidate genes. Machine learning and gene expression validation were employed, followed by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) for further validation. A nomogram was developed to predict MDD probability based on biomarkers. Additional analyses included immune infiltration, regulatory networks, and drug predictions.

Results

CD63, IL17RA, and IL1R1 were identified as potential biomarkers, with significantly higher expression levels in the MDD cohort. These findings were validated by RT-qPCR. A nomogram based on these biomarkers demonstrated predictive capacity for MDD. Differential immune cell infiltration was observed, with significant differences in nine immune cell types, including activated T cells and eosinophils, between the MDD and control groups. ATF1 was identified as a common transcription factor for CD63, IL17RA, and IL1R1. Shared miRNAs for CD63 and IL1R1 included hsa-miR-490-3p and hsa-miR-125a-3p. Drug prediction analysis identified 50 potential drugs, including verteporfin, etynodiol, and histamine, targeting these biomarkers.

Conclusion

CD63, IL17RA, and IL1R1 are key biomarkers for MDD, providing insights for diagnostic development and targeted therapies. The predictive nomogram and drug predictions offer valuable tools for MDD management.

Cortisol levels and depression suicide risk: a combined exploration of meta-analysis and case-control study

Objective

To evaluate the association between cortisol levels and suicide in patients with depression through a meta-analysis to provide an early warning for suicide prevention.

Methods

Databases including China National Knowledge Infrastructure (CNKI), Weipu Database (VIP), Wanfang Database, PubMed, Cochrane Library, Web of Science, and Embase were searched to collect case-control studies, cohort studies, and cross-sectional studies investigating the relationship between cortisol levels and suicide in patients with depression. The meta-analysis was conducted using Stata 18.0. Meanwhile, we collected data from 131 participants to measure their cortisol levels, including Hair cortisol levels (HCL) were calculated for the 0-1 cm and 1-2 cm segments.

Results

The meta-analysis indicated that cortisol levels in depressed patients with suicidal behavior were significantly higher than healthy individuals (SMD = 0.350, 95% CI [0.003, 0.696]). However, the cortisol levels in patients with suicidal behavior were only slightly higher than those in patients without suicidal behavior, and the pooled effect size (SMD = 0.108, 95% CI [-0.151, 0.367]) was non-significant. The depression patients with suicidal behaviors had significantly lower levels of 0-1 cm HCL (3.46 ± 1.92 ng/mg) than those in the depression patients without suicidal ideation (5.43 ± 2.42 ng/mg) (P=0.003) and in the depression patients with suicidal ideation (5.04 ± 2.30 ng/mg) (P=0.037). Similarly, 1-2 cm HCL was significantly lower in the depression with suicidal behavior group (3.21 ± 1.47 ng/mg) than in the depression without suicidal ideation group (5.65 ± 3.59 ng/mg) (P=0.009) and in the depression with suicidal ideation group (5.10 ± 2.88 ng/mg) (P=0.050).

Conclusion

The study found that cortisol levels in patients with depression who exhibited suicidal behavior were higher than those in the healthy population. However, no significant difference in cortisol levels was observed between patients with depression and suicidal behavior and those without suicidal behavior. The experiment revealed that patients with depression and suicidal behavior had lower hair cortisol levels (HCL) than those depression without suicidal behavior.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/view/CRD42024609538 , identifier CRD42024609538.

Lifetime heterosexist victimization and diurnal cortisol predict depression trajectories among sexual and gender minority emerging adults

Heterosexist victimization constitutes a severe source of social stress with enduring effects on mental health and the adrenocortical functioning of lesbian, gay, bisexual, transgender, and queer (LGTBQ) emerging adults. However, it is unknown what roles lower or higher diurnal cortisol at waking (cortisol intercepts) and less variable fluctuations ("flatter" slopes) play in the links between heterosexist victimization and depressive symptoms. In accordance with diathesis-stress, allostatic load, and biological embedding perspectives, we examined whether cortisol intercepts and slopes moderated or mediated the predictive associations of heterosexist victimization with depressive symptoms over 24-months. Heterosexist victimization was expected to predict depressive symptoms most strongly for LGBTQ emerging adults with flatter cortisol slopes (i.e., moderation), and cortisol intercepts and slopes were expected to indirectly link heterosexist victimization with depressive symptoms (i.e., mediation). Latinx and White LGBTQ emerging adults (N = 97; ages 18-29, M = 23.91 years, SD = 2.63) provided saliva samples and questionnaire responses during a four-day testing protocol at baseline; two additional assessments of depressive symptoms were completed 9- and 24-months later. Cortisol intercepts and slopes moderated associations of heterosexist victimization with both contemporaneous and prospective depressive symptoms. Heterosexist victimization was positively associated with contemporaneous depressive symptoms and decreases in depressive symptoms over two years when LGBTQ emerging adults also had steeper cortisol slopes. Heterosexist discrimination was associated with increases in depressive symptoms prospectively among participants with lower cortisol intercepts. There was no evidence for mediation. Thus, patterns of diurnal adrenocortical functioning may distinguish between LGBTQ emerging adults who are more prone to acute versus prolonged depressive symptoms when they experience heterosexist victimization.

Amygdala-insula response to neutral stimuli and the prospective prediction of anxiety sensitivity

BACKGROUND

Anxiety sensitivity (AS) - the tendency to perceive benign physiological stimuli as harmful - is a risk factor for anxiety disorders. Cross-sectionally, AS has been linked to increased negative > neutral neural activity in key nodes implicated in threat detection and interoceptive - i.e., the amygdala (AMYG) and insula (INS). Examining the unique contributions of AMYG-INS blood‑oxygen-level-dependent (BOLD) response to neutral and negative stimuli to the prospective prediction of AS could increase understanding of the factors predisposing individuals to worsening AS over time.

METHODS

Forty-six participants, including 33 patients with mixed internalizing disorders, underwent fMRI scans to assess insula and amygdala activation in response to neutral and negative pictures. AS was measured via self-report at baseline (Time 1) and approximately 1.5 years later (Time 2). We assessed whether BOLD to negative and/or neutral pictures at baseline predicted changes in AS over time.

RESULTS

Greater insula and amygdala activation in response to neutral pictures at baseline predicted higher AS 1.5 years later, controlling for initial levels of AS and BOLD response to negative pictures. Cross-sectionally, greater insula and amygdala activation in response to negative pictures relative to neutral pictures was associated with higher Time 1 AS.

CONCLUSIONS

Heightened AMYG-INS BOLD to benign stimuli precedes and may place individuals at risk for increased AS. Once established, heightened AS appears to be characterized by a neural pattern that is more often-observed in the internalizing disorders - i.e., exaggerated response to negative (> neutral) stimuli.

Advancing Depression Management Through Biomarker Discovery with a Focus on Genetic and Epigenetic Aspects: A Comprehensive Study on Neurobiological, Neuroendocrine, Metabolic, and Inflammatory Pathways

Introduction: Depression is a pervasive global health issue, affecting millions worldwide and causing significant disability. Despite its prevalence, current diagnostic and treatment approaches often yield suboptimal outcomes. The complexity of depression, characterized by diverse causes and symptoms, highlights the urgent need for advanced diagnostic tools and personalized therapies. Biomarkers, particularly genetic and epigenetic depression biomarkers, offer promise in uncovering the biological mechanisms underlying depression, potentially revolutionizing its management. Aim: Primary aim: To identify biomarkers associated with depressive disorders, with a focus on genetic and epigenetic biomarkers. Secondary aim: To optimize the current classification of biomarkers associated with different types of depressive disorders, with a focus on genetic and epigenetic biomarkers. Methods: We integrated findings with strategic keywords extracted from relevant studies, conducting a thorough literature review across the Google Scholar, PubMed, and Web of Science databases. Lastly, final reference inclusion had stringent criteria: recent, diverse peer-reviewed articles in English, all study designs, ensuring up-to-date coverage of genetic and epigenetic depression biomarker research. Results: The review reveals the classification of genetic and epigenetic biomarkers in regard to the type of biomarker, the system of the human body it derives from, and the sampling entity. All of the findings show promise in diagnosing depression, with the potential of predicting treatment outcomes and guiding personalized therapeutic approaches. We defined the significant correlations between genetic and epigenetic biomarker profiles and clinical parameters such as symptom severity and treatment response, thereby enhancing diagnostic accuracy and guiding treatment strategies tailored to individual patient needs across diverse depressive subtypes and treatment responses. Conclusion: Identifying biomarkers associated with depressive disorders, with a focus on genetic and epigenetic biomarkers, represents a critical step toward improving diagnostic precision and treatment efficacy. By elucidating the complex biological underpinnings of depression, this study contributes to the development of targeted therapies that address the diverse needs of individuals affected by this debilitating group of disorders. Future research should focus on validating these genetic and epigenetic biomarkers in larger cohorts and clinical trials to facilitate their clinical implementation and enhance patient outcomes.

Peripheral biological correlates of suicidality in children and adolescents: A systematic review and meta-analysis

A systematic review and meta-analysis were conducted to identify peripheral biological correlates of suicidality in children and adolescents. The review was pre-registered through PROSPERO (CRD42023417128) and included four databases (PubMed, Cochrane Library, Embase, and PsycINFO). From 27,977 non-duplicated articles, 102 full-text studies were selected. Studies investigated suicide attempts (n = 52), suicidal ideation (n = 42), or individuals with suicidal ideation or attempts grouped together (n = 22). Seropositive toxoplasmosis, cortisol, neutrophil, and neutrophil to lymphocyte ratio (NLR) exhibited significant effect size after Bonferroni correction. Effect sizes for biological correlates of suicidality were pooled using Cohen's d (effect size = -0.04, 95% confidence interval [CI]: -1.36 to 1.27) and odds ratio (effect size = -0.31, 95% CI: -1.06 to 0.42). Meta-regression analysis revealed that type of suicidality, type of control, means collected, and sample size significantly impacted the pooled effect size. Analysis showed significant publication bias and heterogeneity, as well as notable moderators and potential biomarkers for future research.

Serum multi-biomarkers for predicting relapse in patients with depressive disorders under psychopharmacotherapy

BACKGROUND

Effective predictive biomarkers for depression relapse remain elusive. This study examined the association of a multi-modal serum biomarker panel with relapse among outpatients with depressive disorders under psychopharmacotherapy, utilizing a naturalistic 24-month prospective design.

METHODS

atients were recruited from a University hospital in South Korea between March 2012 and April 2017. At baseline, 14 serum biomarkers along with socio-demographic and clinical characteristics were assessed in 1094 patients. Following initial antidepressant monotherapy, patients who responded (Hamilton Depression Rating Scale [HAMD] ≤ 14) at the 12-week mark (N = 823) were monitored for relapse (HAMD >14) every three months up to 24 months (N = 710). Logistic regression models, adjusted for relevant covariates, were used to evaluate predictive biomarkers of relapse.

RESULTS

The combined scores of four serum biomarkers (cortisol, high-sensitivity C-reactive protein, tumor necrosis factor-alpha, and brain-derived neurotrophic factor) showed a significant and graded association with depression relapse (P-value <0.001), even after adjustments.

CONCLUSIONS

The application of a combined multi-serum biomarker panel could significantly enhance the predictability of depression relapse. Further validation of these biomarkers in diverse populations and settings is warranted to confirm their utility in clinical practice.

Abnormal network homogeneity in patients with bipolar disorder in attention network

Bipolar disorder (BD) is a complex psychiatric condition marked by significant mood fluctuations that deeply affect quality of life. Understanding the neural mechanisms underlying BD is critical for improving diagnostic accuracy and developing more effective treatments. This study utilized resting-state functional magnetic resonance imaging (rs-fMRI) to investigate functional connectivity within the ventral and dorsal attention networks in 52 patients with BD and 51 healthy controls. Independent Component Analysis (ICA) was employed to establish network templates, while Network Homogeneity (NH) analysis facilitated the comparison of NH values across various brain regions. We examined the association of NH values with clinical measures, including the Hamilton Depression Scale, Perceptual Deficit Questionnaire, and Young Mania Scale. Results indicated that BD patients exhibited lower NH values in the right inferior temporal gyrus of the dorsal attention network and the right middle temporal gyrus of the ventral attention network compared to controls. Notably, NH values in the right superior marginal gyrus of the ventral network were higher in the BD group. Although no significant correlations were found between NH values and clinical symptoms, Support Vector Machine (SVM) analysis demonstrated over 60% accuracy in differentiating BD patients based on NH values. These findings highlight the potential of NH measures as biomarkers for BD, underscore the importance of advanced neuroimaging in uncovering the disorder's complex neural dynamics, and point to the challenges and need for further research to improve predictive accuracy.

Systematic Review and Meta-Analysis: Predictors of Relapsing, Recurrent, and Chronic Depression in Young People

OBJECTIVE

Youth depression disrupts the social and vocational transition into adulthood. Most depression burden is caused by recurring or chronic episodes. Identifying young people at risk for relapsing, recurring, or chronic depression is critical. We systematically reviewed and meta-analyzed the literature on prognostic factors for relapsing, recurrent, and chronic depression in young people.

METHOD

We searched the literature up (MEDLINE, PsycINFO, CINAHL, Embase, CENTRAL, WHO ICTRP, ClinicalTrials.gov, bioRxiv, MedRxiv) to March 6, 2024, and included cohort studies and randomized trials that assessed any prognostic factor for relapse, recurrence, or chronicity of depression in young people (aged 10-25 years at baseline) with a minimum of a 3-month follow-up. We assessed individual study risk of bias using the QUIPS tool and the certainty of evidence via the GRADE approach. We conducted random-effects meta-analyses with Hartung-Knapp-Sidik-Jonkman adjustment when 3 or more estimates on the same prognostic factor were available. Qualitative synthesis was conducted to identify promising prognostic factors that could not be meta-analyzed.

RESULTS

A total of 76 reports of 46 studies (unique cohorts or trials) were included that tested 388 unique prognostic factors in 7,488 young people experiencing depression. The majority of the reports were at high risk of bias (87%). We conducted 22 meta-analyses on unadjusted, and 7 on adjusted, prognostic factors of a poor course trajectory (ie, combined relapse, recurrence, and chronicity). Female sex (adjusted; odds ratio [95% CI] = 1.49 [1.15, 1.93], p = .003), higher severity of depressive symptoms (unadjusted; standardized mean difference [95% CI] = 0.53 [0.33, 0.73], p < .001), lower global functioning (unadjusted; standardized mean difference [95% CI] = -0.35 [-0.60, -0.10], p = .005), more suicidal thoughts and behaviors (unadjusted; standardized mean difference [95% CI] = 0.52 [0.03, 1.01], p = .045), and longer sleep-onset latency (unadjusted; mean difference [95% CI] = 6.96 [1.48, 12.44] minutes, p = .013) at baseline predicted a poor course trajectory of depression. The certainty of the evidence was overall very low to moderate. Promising prognostic factors that could not be meta-analyzed included relational/interpersonal factors (friend relationships and family relationships/structure).

CONCLUSION

Our findings demonstrate the prognostic value of demographic and clinical factors for poor course trajectories of depression in young people. More research is needed to confirm the potential value of relational/interpersonal factors in predicting poor depression course. Limitations of the literature include the high risk of bias of included studies, which indicates that future studies should include large sample sizes and wider diversity of prognostic markers (eg, genetic and neurobiological) in multivariable models. The critical next step is to combine the identified prognostic factors and to evaluate their clinical value in identifying individuals at risk for a poor course trajectory of depression during youth, a life stage in which most of the disability and burden attributable to depression can be averted.

STUDY PREREGISTRATION INFORMATION

Prognostic factors for relapsing, recurrent or chronic depression in youth: a systematic review with meta-analysis; https://www.crd.york.ac.uk/PROSPERO/view/CRD42023458646.

The associations between paternal postpartum depressive symptoms and testosterone and cortisol levels in hair over the first two years postpartum

BACKGROUND

After the birth of a child, also fathers may develop postpartum depression. Altered steroid hormone concentrations are discussed as a possible underlying mechanism, as these have been associated with depressive symptoms in previous studies outside the postpartum period. While higher paternal testosterone levels have been found to protect against paternal postpartum depressive symptoms (PPDS), an association between higher cortisol levels and PPDS has been seen in postpartum mothers, with no comparable studies available on fathers.

OBJECTIVE

This study aimed to investigate cross-sectional and longitudinal associations between testosterone and cortisol levels in hair and PPDS over a period of 2 years postpartum.

METHODS

Data from N = 226 fathers, who took part in the endocrine sub-study DREAMHAIR of the longitudinal prospective cohort study DREAM, were used. PPDS were assessed 8 weeks, 14 months, and 24 months after birth using the Edinburgh Postnatal Depression Scale. At the same time, fathers provided 2 cm scalp-near hair samples in which testosterone (HairT) and cortisol (HairF) levels were determined. Cross-sectional and longitudinal associations between HairT, HairF and paternal PPDS were investigated.

RESULTS

Correlation analyses showed a negative cross-sectional association between HairF levels and paternal PPDS 14 months after birth. A random intercept cross-lagged panel model revealed prospective relationships between paternal PPDS 8 weeks postpartum and HairF 14 months postpartum, and additionally between 14 months and 2 years postpartum in an exploratory model with similarly good model fit. No further significant associations of HairF with paternal PPDS emerged, and none of the analyses with HairT became significant. The overall pattern of results was confirmed when controlling for the influence of batch and storage time on HairT and HairF levels.

CONCLUSION

No consistent relationships between HairT or HairF and paternal PPDS emerged in this relatively healthy cohort. In HairF analyses with significant results, lower HairF was associated with more severe PPDS. Longitudinal results imply that altered cortisol secretion may rather follow than precede changes in paternal PPDS. Further research on hormonal changes in PPDS in fathers should consider possible covariates and examine fathers with higher depressive burden, which may help to identify fathers at risk and inform future preventive and interventive approaches.

Blood cytokines in major depressive disorder in drug-naïve adolescents: A systematic review and meta-analysis

BACKGROUND

Major depressive disorder (MDD) is the most common mental health problem worldwide. Increased levels of inflammation are associated with MDD, though this relationship has been suggested to be bidirectional. The first incidence of a depressive episode usually occurs during adolescence. Hence, examining depressed, drug-naïve adolescents is important to understand the role of inflammation in the pathophysiology of MDD. Cytokines might play a crucial role in inflammation associated with MDD. Therefore, this article aims to investigate the changes in the levels of peripheral blood cytokines in adolescents with MDD.

METHODS

We conducted a systematic review and meta-analysis to assess the changes in peripheral blood cytokines in drug-naïve adolescents (10-18 years) with MDD. A comprehensive search across four databases was performed to identify original research articles. Studies in which the diagnosis of MDD was set by semi-structured interview were included.

RESULTS

Of 2291 articles, 12 met the inclusion criteria for the review, with seven suitable for meta-analysis & including up to five studies per cytokine. The meta-analysis revealed significant associations between tumor necrosis factor (TNF)-α (n = 222, Hedge's g = 0.51, p <0.01) and MDD in adolescents compared to healthy individuals. However, other blood cytokines, including interleukin (IL)-1β, IL-4, IL-6, IL-8, and interferon (IFN)-γ, did not significantly correlate with MDD in adolescents.

CONCLUSION

TNF-α was significantly elevated in drug-naïve adolescents with MDD. To further understand the role of TNF-α in MDD, a thorough investigation is required, taking into account the diversity, subtypes, chronicity, and severity of MDD.

Hormone circuit explains why most HPA drugs fail for mood disorders and predicts the few that work

Elevated cortisol in chronic stress and mood disorders causes morbidity including metabolic and cardiovascular diseases. There is therefore interest in developing drugs that lower cortisol by targeting its endocrine pathway, the hypothalamic-pituitary-adrenal (HPA) axis. However, several promising HPA-modulating drugs have failed to reduce long-term cortisol in mood disorders, despite effectiveness in other hypercortisolism conditions such as Cushing's syndrome. The reasons for these failures remain unclear. Here, we use a mathematical model of the HPA axis to demonstrate that the pituitary and adrenal glands compensate for drug effects by adjusting their functional mass, a feedback mechanism absent in Cushing tumors. Our systematic in silico analysis identifies two interventions targeting corticotropin-releasing hormone (CRH) as effective for lowering long-term cortisol. Other targets either fail due to gland mass compensation or harm other aspects of the HPA axis. We propose CRH-neutralizing antibodies and CRH-synthesis inhibitors as potential targets for reducing long-term cortisol in mood disorders and chronic stress. More generally, this study indicates that understanding the slow compensatory mechanisms in endocrine axes can be crucial to prioritize drug targets.

Oxidative alterations in exfoliated oral mucosa cells of patients with major depressive disorder

Objectives

This study aimed to investigate oxidative stress markers in the oral mucosal cells of individuals diagnosed with major depressive disorder (MDD).

Methods

A case-control design was used, including twenty patients diagnosed with MDD, based on the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria, and twenty healthy controls. Oral exfoliated cells were collected from all participants. Intracellular levels of reactive oxygen species (ROS), mitochondrial membrane potential (ΔΨm), caspase-3 and -7 activity, and reduced glutathione (GSH) were measured in Arbitrary Fluorescence Units (AFU).

Results

The MDD group demonstrated significantly elevated intracellular ROS levels (p = 0.0012) and caspase-3 and -7 activity (p = 0.0171) in comparison to the control group. Additionally, a decrease in ΔΨm expression was observed in the oral cells of MDD patients (p = 0.0265), whereas GSH expression levels did not differ significantly between the two groups (p = 0.8908).

Conclusions

The findings indicate heightened oxidative stress in the oral exfoliated cells of individuals with MDD. This study supports the potential use of oral cells as a non-invasive biomarker source for assessing oxidative stress in depressive disorders.

Salivary hormones in depression: the future in diagnosis and treatment

Depression is associated with a significant burden on individuals, families, and communities. It leads to impaired social and occupational functioning, increased disability, decreased quality of life, and higher mortality rates, often due to suicide. A recent estimate from the World Health Organization (WHO) states that over 280 million people of all ages suffer from depression, which equals approximately 3.8% of the world population. Despite effective treatments for mental disorders, a dire treatment gap persists. This treatment gap could be reduced by effective and available diagnostic methods that have the potential to aid in depression diagnosis, stratification of patient subgroups, and treatment monitoring. In this regard, salivary hormones have been studied as potential markers for different types and etiologies of depression due to the convenience of non-invasive sample collection and their correlation with certain aspects of mood and mental health. The literature suggests they can help clinicians assess an individual's stress response, hormonal imbalances, and treatment response, leading to more personalized and effective interventions. In this review, we offer an up-to-date look at all studied salivary hormones associated with depression, including Cortisol, Melatonin, Oxytocin, Serotonin, Dehydroepiandrosterone, Testosterone, Progesterone, and Estradiol.

Association between the functional brain network and antidepressant responsiveness in patients with major depressive disorders: a resting-state EEG study

BACKGROUND

Recent neuroimaging studies have demonstrated that the heterogeneous antidepressant responsiveness in patients with major depressive disorder (MDD) is associated with diverse resting-state functional brain network (rsFBN) topology; however, only limited studies have explored the rsFBN using electroencephalography (EEG). In this study, we aimed to identify EEG-derived rsFBN-based biomarkers to predict pharmacotherapeutic responsiveness.

METHODS

The resting-state EEG signals were acquired for demography-matched three groups: 98 patients with treatment-refractory MDD (trMDD), 269 those with good-responding MDD (grMDD), and 131 healthy controls (HCs). The source-level rsFBN was constructed using 31 sources as nodes and beta-band power envelope correlation (PEC) as edges. The degree centrality (DC) and clustering coefficients (CCs) were calculated for various sparsity levels. Network-based statistic and one-way analysis of variance models were employed for comparing PECs and network indices, respectively. The multiple comparisons were controlled by the false discovery rate.

RESULTS

Patients with trMDD were characterized by the altered dorsal attention network and salience network. Specifically, they exhibited hypoconnection between eye fields and right parietal regions (p = 0.0088), decreased DC in the right supramarginal gyrus (q = 0.0057), and decreased CC in the reward circuit (qs < 0.05). On the other hand, both MDD groups shared increased DC but decreased CC in the posterior cingulate cortex.

CONCLUSIONS

We confirmed that network topology was more severely deteriorated in patients with trMDD, particularly for the attention-regulatory networks. Our findings suggested that the altered rsFBN topologies could serve as potential pathologically interpretable biomarkers for predicting antidepressant responsiveness.

How pharmacology can aid in the diagnosis of mental disorders

The precise diagnosis of mental disorders constitutes a formidable problem. Mental disorders are currently diagnosed based on clinical symptoms, which are often subjective. Various drug classes, traditionally referred to as "antidepressants," "antipsychotics" and "mood stabilizers" are then used empirically to treat affected patients. The previous decade has witnessed an increasing extension of the use of drug classes beyond their traditional indications (e.g., "antidepressants" in the treatment of anxiety disorders). Therefore, we would like to initiate a discussion in the pharmacological and psychiatric research communities on an alternative classification of mental disorders: Instead of using the traditional categorical classification of mental disorders physicians should rather diagnose symptoms (e.g., anhedonia) without bias to a traditional categorization (e.g., depression). The appropriate most effective drugs are then selected based on these symptoms. Depending on the responsiveness of the patient towards a given drug X, the disease should be classified, e.g., as drug X-responsive disease. This approach will also help us elucidate the still poorly understood molecular mechanisms underlying mental disorders, i.e., drugs can also be viewed and used as molecular diagnostic tools. In several fields of medicine, drugs are already used as molecular diagnostic tools. Thus, there is already precedence for the concept proposed here for mental disorders.

Electrochemical biosensors for depression: Diagnosis and therapeutic monitoring

Electrochemical biosensors have revolutionized the detection of biomarkers related to depression and the quantification of antidepressant drugs. These biosensors leverage nanomaterials and advanced assay designs to achieve high sensitivity and selectivity for clinically relevant analytes. Key neurotransmitters implicated in depression, such as serotonin, dopamine, and glutamate, can be accurately measured via biosensors, providing insights into the effects of antidepressant treatments on neurotransmission. Biosensors can also detect biomarkers of inflammation, oxidative stress, and neuronal health that are altered in depression. Real-time biosensing techniques such as fast-scan cyclic voltammetry enable monitoring of dynamic neurotransmitter changes during depressive episodes and pharmacological interventions. Advancements incorporating graphene, gold nanoparticles, and other nanomaterials have enhanced biosensor performance, enabling the detection of low biomarker concentrations. Closed-loop biosensing systems hold promise for precision medicine by automating antidepressant dosage adjustments on the basis of neurotransmitter levels. A wide range of depression biomarkers, including apolipoprotein A4, heat shock protein 70, brain-derived neurotrophic factor, microRNAs, proteins, and combinatorial biomarker panels, have been detected via sophisticated biosensor platforms. Emerging biosensors show selectivity for antidepressant drugs such as serotonin-norepinephrine reuptake inhibitors, tricyclic antidepressants, and selective serotonin reuptake inhibitors in biological samples. This review emphasizes the transformative potential of electrochemical biosensors in combating depression. By facilitating earlier and more accurate diagnoses, these biosensors can revolutionize patient care and enhance treatment outcomes.

Effect of Antidepressant Treatment on 5-HT4 Receptor Binding and Associations With Clinical Outcomes and Verbal Memory in Major Depressive Disorder

BACKGROUND

Brain serotonin 4 receptor (5-HT4R) levels are lower in untreated patients with major depressive disorder (MDD) and are linked to verbal memory. Here, we investigated the relationship between 5-HT4R levels, clinical outcomes, and cognitive function in patients with MDD who initiated selective serotonin reuptake inhibitor drug treatment.

METHODS

Ninety patients with moderate to severe depression underwent molecular brain imaging to measure 5-HT4R binding prior to antidepressant treatment with escitalopram. Pretreatment 5-HT4R binding was assessed for its ability to predict treatment outcome at weeks 4, 8, or 12. In 40 patients who were rescanned 8 weeks posttreatment, change in cerebral 5-HT4R binding was correlated with change in verbal memory and with change in depressive symptoms, as evaluated by the 6-item Hamilton Depression Rating Scale.

RESULTS

After 8 weeks of serotonergic intervention, neostriatal 5-HT4R binding was reduced by 9%. Global change in 5-HT4R binding from baseline was associated with verbal memory outcomes, but not with overall clinical depressive symptom outcomes. Pretreatment 5-HT4R binding did not predict clinical recovery status at week 8 and was not associated with change in the 6-item Hamilton Depression Rating Scale scores.

CONCLUSIONS

In patients with moderate to severe MDD, treatment with selective serotonin reuptake inhibitors downregulated neostriatal 5-HT4R levels, which is consistent with the notion that the drugs increase cerebral extracellular serotonin. The less global brain 5-HT4R levels were downregulated after selective serotonin reuptake inhibitors, the more verbal memory improved, highlighting the potential importance of 5-HT4R as a treatment target in MDD. The findings offer insights into mechanisms that underlie antidepressant effects and point to new directions for precision medicine treatments for MDD.

Altered association between cortisol and adrenocorticotropic hormone levels in the early stage of type 2 diabetic ketoacidosis

Objectives

In the early stages of various critical infections and diseases, altered association of cortisol and adrenocorticotropic hormone (ACTH) levels occurs, with cortisol levels increasing and ACTH levels remaining normal or decreasing. This study aimed to explore the relationship between ACTH and cortisol levels in patients with diabetic ketoacidosis (DKA) and the influence of the severity of DKA.

Methods

A total of 106 type 2 diabetes patients with DKA admitted to the Endocrinology Department of Yantai Yuhuangding Hospital from February 2018 to May 2023 were divided into groups without (n=54) and with bacterial infection (n=52). Twenty type 2 diabetes patients without infection or DKA admitted during the same period were included as the control group. Cortisol and ACTH levels were measured on the first day of admission and the day after DKA correction for patients with DKA and on the first day of admission and the day before discharge for the control group.

Results

Compared with the control group, the DKA groups both with and without infection had significantly higher cortisol levels (P<0.05) and significantly lower ACTH levels (P<0.01) at admission. DKA patients with infection had significantly higher cortisol levels at admission than those without infection (734.51 ± 348.69 nmol/L vs 508.79 ± 268.72 nmol/L, P<0.01), while ACTH levels did not differ significantly between the two groups (P>0.05). After correction of DKA, no differences in cortisol or ACTH levels were observed among the three groups. Compared with levels at admission, DKA patients both with and without infection had lower cortisol levels and higher ACTH levels after DKA correction (all P<0.001). Multiple stepwise regression analysis showed that for all DKA patients and for subgroups with and without infection, the cortisol level at admission was independently positively correlated with the ACTH level and negatively correlated with the bicarbonate level (both P<0.01).

Conclusions

In the early stage of DKA, a phenomenon of altered association between cortisol-ACTH occurs and is especially prominent in DKA patients with infection. This altered association between cortisol-ACTH disappears after DKA correction, and the severity of DKA is an independent influencing factor on the cortisol level in early-stage DKA.

Ultrasound Applications in the Treatment of Major Depressive Disorder (MDD): A Systematic Review of Techniques and Efficacy

Objective

Major depressive disorder (MDD) is a debilitating mental health condition characterized by persistent feelings of sadness, loss of interest, and impaired daily functioning. It affects approximately 8% of the U.S. population, posing a significant personal and economic burden. Around 30% of patients with MDD do not respond to conventional antidepressant and psychotherapeutic treatments. Current treatment options for refractory MDD include transcranial magnetic stimulation (TMS) and invasive surgical procedures such as surgical ablation, vagus nerve stimulation, and deep brain stimulation. TMS has modest efficacy, and surgical procedures are associated with surgical risk and low patient acceptance. With the unique advantage of combining non-invasiveness with selective targeting, therapeutic ultrasound emerges as a promising alternative for treating refractory MDD. Over the past 10 years, there has been a growth in focused ultrasound research, leading to an exponential increase in academic and public interest in the technology. To support the continued development of ultrasound for treating MDD, we conducted a systematic review following Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines.

Methods

We included peer-reviewed prospective cohort studies, case-control studies, and randomized control trials that evaluate the efficacy of ultrasonic treatment for depression (PROSPERO registration number: CRD42024626093). We summarized ultrasonic techniques for treating depression and their efficacy. Furthermore, we identified key challenges and future directions for applying ultrasound in treating MDD.

Results

We identified 67 potentially relevant articles, of which 18 studies met all inclusion criteria. The techniques of applying ultrasound to treat depression include magnetic resonance-guided focused ultrasound (MRgFUS) for capsulotomy and low-intensity focused ultrasound (LIFUS) neuromodulation. In human trials, the response rate (⩾50% improvement from baseline on depression score) is 53.85% for MRgFUS and 80.49% for LIFUS neuromodulation. In all preclinical studies using rodent models (8 studies), LIFUS neuromodulation had a medium to large effect (|Cohen's d| > 0.6) on resolving depressive-like behavior in rodents without causing adverse effects such as tissue damage. MRgFUS faces inconsistent lesioning success and a limited response rate, while LIFUS neuromodulation lacks systematic exploration of parameter space and a clear understanding of its mechanistic effects. Future work should refine patient selection for MRgFUS and focus on individualized functional targeting.

Conclusion

LIFUS neuromodulation showed a medium to large effect in reducing depressive behaviors in both rodent models and human trials, representing a promising, noninvasive option for treating refractory MDD.

Regulation of Stress-Induced Immunosuppression in the Context of Neuroendocrine, Cytokine, and Cellular Processes

Understanding the regulatory mechanisms of stress-induced immunosuppression and developing reliable diagnostic methods are important tasks in clinical medicine. This will allow for the development of effective strategies for the prevention and treatment of conditions associated with immune system dysfunction induced by chronic stress. The purpose of this review is to conduct a comprehensive analysis and synthesis of existing data on the regulatory mechanisms of stress-induced immunosuppression. The review is aimed at identifying key neuroendocrine, cytokine, and cellular processes underlying the suppression of the immune response under stress. This study involved a search of scientific literature covering the neuroendocrine, cellular, and molecular mechanisms of stress-induced immunosuppression regulation, as well as modern methods for its diagnosis. Major international bibliographic databases covering publications in biomedicine, psychophysiology, and immunology were selected for the search. The results of the analysis identified key mechanisms regulating stress-induced immunosuppression. The reviewed publications provided detailed descriptions of the neuroendocrine and cytokine processes underlying immune response suppression under stress. A significant portion of the data confirms that the activation of the hypothalamic-pituitary-adrenal (HPA) axis and subsequent elevation of cortisol levels exert substantial immunosuppressive effects on immune cells, particularly macrophages and lymphocytes, leading to the suppression of innate and adaptive immune responses. The data also highlight the crucial role of cortisol and catecholamines (adrenaline and noradrenaline) in initiating immunosuppressive mechanisms under chronic stress.

Depression unveiled: Insights into etiology and animal models for behavioral assessment, exploring the multifactorial nature and treatment of depression

Over the past century, significant shifts in daily living have led to an increased prevalence of mental disorders, often linked to hormonal imbalances. Among these, anxiety and depression stand out as prevalent diagnoses, particularly in industrialized nations. Depression, according to the DSM-5, is a heterogeneous condition that affects emotional, cognitive, and physical functioning, with symptoms including insomnia, sexual dysfunction, and weight changes. Cognitive theories of depression highlight its impact on judgment, decision-making, thinking, and focus. Depression's multifaceted nature means that no two patients experience identical symptoms, risk factors, or treatment responses. The COVID-19 pandemic has exacerbated mental health issues, with social isolation, restricted contact, and altered daily routines contributing to increased anxiety and depression, especially among adolescents and young adults. The pandemic's psychological toll underscores the need for effective treatment strategies for mental disorders. The physical manifestations of major depressive disorder (MDD) are associated with a heightened risk of developing various medical conditions, including metabolic disorders, cardiovascular disease, stroke, epilepsy, and dementia. This review provides a comprehensive exploration of depression and anxiety, covering their different types, epidemiology, potential causes, diagnostic criteria, and available treatment options. It delves into the role of pharmacological interventions and examines recent advancements to enhance therapeutic outcomes. Additionally, the review assesses the therapeutic potential of drugs, offering insights into their efficacy in treating these complex mental health disorders. By targeting the multifactorial etiology of depression through drug repurposing and new drug development, researchers aim to enhance treatment efficacy and achieve better outcomes for patients with depression.

Neurobiological mechanisms of antidepressant properties of psilocybin: A systematic review of blood biomarkers

Psilocybin represents a novel therapeutic approach for individuals with major depressive disorder (MDD) who do not respond to conventional antidepressant treatment. Investigating the influence of psilocybin on the pathophysiological processes involved in MDD could enhance our neurobiological understanding of the presumed antidepressant action mechanism. This systematic review aims to summarize the results of human studies investigating changes in blood-based biomarkers of MDD to guide future research on potentially relevant analytes that could be monitored in clinical trials. A systematic search was performed in MEDLINE, Embase, and Web of Science to retrieve studies investigating changes in serum and plasma levels of neurotrophic, immunologic, neuroendocrine, and metabolic markers. Nine studies were included, describing findings on 15 biomarkers, exclusively in healthy participants. Studies consistently reported a decrease in interleukin-6, C-reactive protein, and eosinophils, and an increase in cortisol, prolactin, oxytocin, thyroid-stimulating hormone, adrenocorticotropic hormone, brain-derived neurotrophic factor, and free fatty acids following psilocybin administration. Less consistent effects were observed on interleukin-1β, interleukin-8, tumour necrosis factor-alpha, soluble urokinase plasminogen activator receptor, and growth hormone. The results are in line with preclinical studies and provide initial support from human studies that psilocybin potentially leads to beneficial effects on biomarkers of MDD. However, given the limited number of studies, findings should be approached with caution prior to replication. Further research should include larger samples, clinical populations, longer-term assessment, rigorous experimental designs, and account for the potential confounding of psychological stress related to the psychedelic experience.

Developing a translational research framework for MDD: combining biomolecular mechanisms with a spiraling risk factor model

Objective

The global incidence and burden of Major Depressive Disorder (MDD) are increasing annually, with current antidepressant treatments proving ineffective for 30-40% of patients. Biomolecular mechanisms within the microbiota-gut-brain axis (MGBA) may significantly contribute to MDD, potentially paving the way for novel treatment approaches. However, integrating the MGBA with the psychological and environmental aspects of MDD remains challenging. This manuscript aims to: 1) investigate the underlying biomolecular mechanisms of MDD using a modeling approach, and 2) integrate this knowledge into a comprehensive 'spiraling risk factor model' to develop a biopsychosocial translational research framework for the prevention and treatment of MDD.

Methods

For the first aim, a systematic review (PROSPERO registration) was conducted using PubMed, Embase, and Scopus to query literature published between 2016-2020, with select additional sources. A narrative review was performed for the second aim.

Results

In addition to genetics and neurobiology, research consistently indicates that hyperactivation of the HPA axis and a pro-inflammatory state are interrelated components of the MGBA and likely underlying mechanisms of MDD. Dysregulation of the MGBA, along with imbalances in mental and physical conditions, lifestyle factors, and pre-existing treatments, can trigger a downward spiral of stress and anxiety, potentially leading to MDD.

Conclusions

MDD is not solely a brain disorder but a heterogeneous condition involving biomolecular, psychological, and environmental risk factors. Future interdisciplinary research can utilize the integrated biopsychosocial insights from this manuscript to develop more effective lifestyle-focused multimodal treatment interventions, enhance diagnosis, and stimulate early-stage prevention of MDD.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42020215412.

Higher amplitudes of visual networks are associated with trait- but not state-depression

Despite depression being a leading cause of global disability, neuroimaging studies have struggled to identify replicable neural correlates of depression or explain limited variance. This challenge may, in part, stem from the intertwined state (current symptoms; variable) and trait (general propensity; stable) experiences of depression.Here, we sought to disentangle state from trait experiences of depression by leveraging a longitudinal cohort and stratifying individuals into four groups: those in remission ('trait depression group'), those with large longitudinal severity changes in depression symptomatology ('state depression group'), and their respective matched control groups (total analytic n = 1030). We hypothesized that spatial network organization would be linked to trait depression due to its temporal stability, whereas functional connectivity between networks would be more sensitive to state-dependent depression symptoms due to its capacity to fluctuate.We identified 15 large-scale probabilistic functional networks from resting-state fMRI data and performed group comparisons on the amplitude, connectivity, and spatial overlap between these networks, using matched control participants as reference. Our findings revealed higher amplitude in visual networks for the trait depression group at the time of remission, in contrast to controls. This observation may suggest altered visual processing in individuals predisposed to developing depression over time. No significant group differences were observed in any other network measures for the trait-control comparison, nor in any measures for the state-control comparison. These results underscore the overlooked contribution of visual networks to the psychopathology of depression and provide evidence for distinct neural correlates between state and trait experiences of depression.

Hypothalamic-pituitary-adrenal axis function in the offspring of parents with bipolar disorder and the impact of the family environment: A pilot study of the Reducing Unwanted Stress in the Home (RUSH) prevention program

BACKGROUND

The home environment of offspring of parents with bipolar disorder (OBD) has been characterized by high levels of stress and disorganization, which may impact development of the hypothalamic-pituitary-adrenal (HPA) axis and their subsequent risk for affective disorders. The present study examined the effects of a family-based preventative intervention on the OBD's HPA axis functioning and whether intervention-related changes in the home environment might have driven change in the HPA axis.

METHODS

Fifty-five children (6-11 years) were recruited from families having a parent with bipolar disorder (n=26) or families having two parents with no current mental disorders (n=29). Only those families with a parent having bipolar disorder participated in the preventative intervention. Both groups completed assessments at baseline, post-prevention, 3-, and 6-months post-prevention. At each assessment, family organization, control, cohesion, conflict, and expressiveness, in addition to childhood internalizing problems, were measured, and offspring saliva samples were collected across two consecutive days.

RESULTS

Hierarchical Linear Modelling found no significant differences in HPA axis functioning between groups at baseline or across time. Improvements in family organization, however, were associated with elevations in participants' cortisol awakening response (CAR; p =.004) and total daily output (p =.023), and a steepening of their diurnal slope (p =.003) across time. Similar findings were obtained for family cohesion with respect to CAR (p <.001) and, to a lesser degree, diurnal slope (p =.064).

DISCUSSION

HPA axis functioning did not differ between the OBD and healthy controls at baseline or in response to the preventative intervention. However, intervention-related improvements in family organization and, to a lesser degree, cohesion, were associated with adaptive changes in HPA functioning over time.

Towards a consensus roadmap for a new diagnostic framework for mental disorders

Current nosology claims to separate mental disorders into distinct categories that do not overlap with each other. This nosological separation is not based on underlying pathophysiology but on convention-based clustering of qualitative symptoms of disorders which are typically measured subjectively. Yet, clinical heterogeneity and diagnostic overlap in disease symptoms and dimensions within and across different diagnostic categories of mental disorders is huge. While diagnostic categories provide the basis for general clinical management, they do not describe the underlying neurobiology that gives rise to individual symptomatic presentations. The ability to incorporate neurobiology into the diagnostic framework and to stratify patients accordingly will be a critical step forward for the development of new treatments for mental disorders. Furthermore, it will also allow physicians to provide patients with a better understanding of their illness's complexities and management. To realize this ambition, a paradigm shift is needed to build an understanding of how neuropsychiatric conditions can be defined more precisely using quantitative (multimodal) biological processes and markers and thus to significantly improve treatment success. The ECNP New Frontiers Meeting 2024 set out to develop a consensus roadmap for building a new diagnostic framework for mental disorders by discussing its rationale, outlook, and consequences with all stakeholders involved. This framework would instantiate a set of principles and procedures by which research could continuously improve precision diagnostics while moving away from traditional nosology. In this meeting report, the speakers' summaries from their presentations are combined to address three key elements for generating such a roadmap, namely, the application of innovative technologies, understanding the biology of mental illness, and translating biological understanding into new approaches. In general, the meeting indicated a crucial need for a biology-informed framework to establish more precise diagnosis and treatment for mental disorders to facilitate bringing the right treatment to the right patient at the right time.

Acoustic speech features are associated with late-life depression and apathy symptoms: Preliminary findings

BACKGROUND

Late-life depression (LLD) is a heterogenous disorder related to cognitive decline and neurodegenerative processes, raising a need for the development of novel biomarkers. We sought to provide preliminary evidence for acoustic speech signatures sensitive to LLD and their relationship to depressive dimensions.

METHODS

Forty patients (24 female, aged 65-82 years) were assessed with the Geriatric Depression Scale (GDS). Vocal features were extracted from speech samples (reading a pre-written text) and tested as classifiers of LLD using random forest and XGBoost models. Post hoc analyses examined the relationship between these acoustic features and specific depressive dimensions.

RESULTS

The classification models demonstrated moderate discriminative ability for LLD with receiver operating characteristic = 0.78 for random forest and 0.84 for XGBoost in an out-of-sample testing set. The top classifying features were most strongly associated with the apathy dimension (R 2 = 0.43).

DISCUSSION

Acoustic vocal features that may support the diagnosis of LLD are preferentially associated with apathy.

Highlights

The depressive dimensions in late-life depression (LLD) have different cognitive correlates, with apathy characterized by more pronounced cognitive impairment.Acoustic speech features can predict LLD. Using acoustic features, we were able to train a random forest model to predict LLD in a held-out sample.Acoustic speech features that predict LLD are preferentially associated with apathy. These results indicate a predominance of apathy in the vocal signatures of LLD, and suggest that the clinical heterogeneity of LLD should be considered in development of acoustic markers.

Role of oral-gut-brain axis in psychiatric and neurological disorders

The oral cavity and gut are two important microbial habitats in the human body, harboring the most ecologically rich and taxonomically diverse microbial communities in humans, which play a key role in microbiome related diseases. In recent years, the emerging concept of the oral-gut-brain axis has attracted widespread attention in the fields of neuroscience, digestive science, and microbiology. It is not only an anatomical description, but also a comprehensive concept that covers multiple physiological functions and pathological mechanisms. Simply put, the oral-gut-brain axis refers to the complex network that connects the mouth, gut, and brain tightly together through neural connections and hormonal and immune pathways. With the deepening of research on the oral-gut-brain axis theory, more and more evidence shows that it plays an important role in depression, Parkinson's disease, and other neurodegenerative diseases. This article reviews the recent progress in research of the oral-gut-brain axis in psychiatric and neurological diseases.

PET imaging assist investigation of HDAC6 expression change in MDD and evaluating antidepressant efficacy of a newly developed HDAC6 inhibitor

The histone deacetylase 6 (HDAC6) is closely related to the pathogenesis of depression in epigenetic regulation. However, it remains unclear how HDAC6 expression changes in depression pathophysiology and whether it is a target for antidepressant treatment. Herein, we investigate the expression change of HDAC6 in major depressive disorder (MDD) and evaluate the efficacy of a novel HDAC6 inhibitor, PB200, using positron emission tomography (PET) imaging. PET imaging studies with an HDAC6 PET probe [18F]Bavarostat allied with in vitro experiments demonstrated significantly increased HDAC6 expression in the brains of MDD mice. To investigate if pharmacological inhibition of HDAC6 can exert antidepressant effects, a series of naphthyridine-based HDAC6 inhibitors were designed and synthesized, among which PB200 demonstrated high selectivity and inhibitory activity against HDAC6, favorable metabolic stability, and excellent brain uptake. Moreover, PB200 exhibited significant antidepressant effects by restoring abnormal HDAC6 expression level and alleviating neuroinflammation. These results imply that targeting HDAC6 shows promise as a therapeutic strategy for depression, and PB200 is a potential therapeutic option for treating MDD.

EEG measures of brain arousal in relation to symptom improvement in patients with major depressive disorder: Results from a randomized placebo-controlled clinical trial

Hyperstable arousal regulation during a 15-min resting electroencephalogram (EEG) has been linked to a favorable response to antidepressants. The EMBARC study, a multicenter randomized placebo-controlled clinical trial, provides an opportunity to examine arousal stability as putative antidepressant response predictor in short EEG recordings. We tested the hypothesis that high arousal stability during a 2-min resting EEG at baseline is related to better outcome in the sertraline arm and explored the specificity of this effect. Outpatients with chronic/recurrent MDD were recruited from four university hospitals and randomized to treatment with sertraline (n = 100) or placebo (n = 104). The change in the Hamilton Rating Scale for Depression (HRSD-17) was the main outcome. Patients were stratified into high and low arousal stability groups. In mixed-model repeated measures (MMRM) analysis HRSD-17 change differed significantly between arousal groups, with high arousal stability being associated with a better outcome in the sertraline arm, and worse outcome in the placebo arm at week 4, with moderate effect sizes. When considering both treatment arms, a significant arousal group x time x treatment interaction emerged, highlighting specificity to the sertraline arm. Although findings indicate that arousal stability is likely to be a treatment-specific marker of response, further out-of-sample validation is warranted.

A cross-section study of the comparison of plasma inflammatory cytokines and short-chain fatty acid in patients with depression and schizophrenia

BACKGROUND

Major depressive disorder (MDD) and schizophrenia (SCH) are common and severe mental disorders that are mainly diagnosed depending on the subjective identification by psychiatrists. Finding potential objective biomarkers that can distinguish these two diseases is still meaningful.

METHODS

In the present study, we investigate the differences in plasma inflammatory cytokines and short-chain fatty acids (SCFAs) among patients with MDD (n = 24) and SCH (n = 24), and gender- and age-matched healthy controls (HC, n = 27) and identify potential plasma biomarkers.

RESULTS

We found that the concentrations of pro-inflammatory cytokines were increased, whereas the anti-inflammatory cytokines were decreased in both MDD and SCH. Meanwhile, except for an increase in 4-Methylvaleric acid, other SCFAs with statistical differences were reduced in both MDD and SCH. Moreover, potential biomarker panels were developed that can effectively discriminate MDD from HC (AUC = 0.997), SCH from HC (AUC = 0.999), and from each other (MDD from SCH, AUC = 0.983).

CONCLUSIONS

These data suggest that alterations in plasma cytokines and SCFAs might be one of the potential features for distinguishing MDD and SCH.

TRIAL REGISTRATION

Chinese Clinical Trial Registry: ChiCTR2100051243, registration date: 2021/09/16.

Interoception mediates the association between social support and sociability in patients with major depressive disorder

BACKGROUND

Interoception dysfunction has an important impact on the onset and development of major depressive disorder (MDD). Social support serves as a protective factor against MDD, and sociability also plays a significant role in this condition. These interconnected constructs-social support and sociability-play pivotal roles in MDD. However, no research on the mechanisms underlying the associations between social support and sociability, particularly the potential role of interoception, have been reported.

AIM

To investigate the mediating effect of interoception between social support and social ability and to explore the independent role of social support in sociability.

METHODS

The participants included 292 patients with MDD and 257 healthy controls (HCs). The patient health questionnaire 9, the multidimensional assessment of interoception awareness, version 2 (MAIA-2), the social support rating scale (SSRS), and the Texas social behavior inventory (TSBI) were used to assess depression, interoception, social support, and sociability, respectively. A mediation analysis model for the eight dimensions of interoception (noticing, not distracting, not worrying, attention regulation, emotional awareness, self-regulation, body listening, and trust), social support, and sociability were established to evaluate the mediating effects.

RESULTS

A partial correlation analysis of eight dimensions of the MAIA-2, SSRS, and TSBI scores, with demographic data as control variables, revealed pairwise correlations between the SSRS score and both the MAIA-2 score and TSBI score. In the major depression (MD) group, the SSRS score had a positive direct effect on the TSBI score, while the scores for body listening, emotional awareness, self-regulation, and trust in the MAIA-2C had indirect effects on the TSBI score. In the HC group, the SSRS score had a positive direct effect on the TSBI score, and the scores for attention regulation, emotional awareness, self-regulation, and trust in the MAIA-2C had indirect effects on the TSBI score. The proportion of mediators in the MD group was lower than that in the HC group.

CONCLUSION

Interoceptive awareness is a mediating factor in the association between social support and sociability in both HCs and depressed patients. Training in interoceptive awareness might not only help improve emotional regulation in depressed patients but also enhance their social skills and support networks.

Evolutionary neural architecture search for automated MDD diagnosis using multimodal MRI imaging

Major depressive disorder (MDD) is a prevalent mental disorder with serious impacts on life and health. Neuroimaging offers valuable diagnostic insights. However, traditional computer-aided diagnosis methods are limited by reliance on researchers' experience. To address this, we proposed an evolutionary neural architecture search (M-ENAS) framework for automatically diagnosing MDD using multi-modal magnetic resonance imaging (MRI). M-ENAS determines the optimal weight and network architecture through a two-stage search method. Specifically, we designed a one-shot network architecture search (NAS) strategy to train supernet weights and a self-defined evolutionary search to optimize the network structure. Finally, M-ENAS was evaluated on two datasets, demonstrating that M-ENAS outperforms existing hand-designed methods. Additionally, our findings reveal that brain regions within the somatomotor network play important roles in the diagnosis of MDD, providing additional insight into the biological mechanisms underlying the disorder.

Structural Neuroimaging and Molecular Signatures of Drug-Naive Depression With Melancholic Features

Objectives: Melancholic depression (MD) is a common subtype of major depressive disorder (MDD). It is difficult to treat because its neurobiological basis is poorly understood. Therefore, to investigate whether MD patients have any structural changes in gray matter (GM) and the molecular foundation of these changes, we combined voxel-based morphometry (VBM) analysis with neurotransmitter system-derived mapping from public data. Methods: 137 drug-naive MDD patients and 75 healthy controls (HCs) were recruited for structural magnetic resonance imaging. The imaging results were analyzed using VBM analysis. MDD patients were then divided into MD and nonmelancholic depression (NMD) subgroups according to their scores on the Montgomery-Asberg Depression Rating Scale (MADRS) and the Hamilton Depression Rating Scale. Next, we analyzed the spatial correlation between the changes in the gray matter volume (GMV) maps and the neurotransmitter receptor/transporter protein density maps provided by the JuSpace toolbox. Results: Compared to HCs, patients with MD had significant GMV reduction in the bilateral hippocampus, bilateral thalamus, right amygdala, and right posterior cingulate cortex (PCC)/precuneus. Compared to patients with NMD, MD patients had significant GMV reduction in the bilateral PCC/precuneus and lateral occipital cortex. Moreover, compared to HCs, changes in GMV introduced by MD were spatially associated with the serotonin transporter, cannabinoid receptor, and μ-opioid receptor. Compared to NMD patients, changes in GMV introduced by MD were spatially associated with the vesicular acetylcholine transporter. Conclusion: The present study discovered abnormal GMV alterations in patients with subtypes of depression. We also found a series of neurotransmitter receptors that may be associated with the alterations. The findings of the current study may provide a more comprehensive understanding of the molecular mechanisms underlying the structural abnormalities in subtypes of depression and potentially offer new insights into developing new therapeutic strategies.

The Dynamic Interplay Between Puberty and Structural Brain Development as a Predictor of Mental Health Difficulties in Adolescence: A Systematic Review

Puberty is a time of intense reorganization of brain structure and a high-risk period for the onset of mental health problems, with variations in pubertal timing and tempo intensifying this risk. We conducted 2 systematic reviews of articles published up to February 1, 2024, focusing on 1) the role of brain structure in the relationship between puberty and mental health, and 2) precision psychiatry research evaluating the utility of puberty in making individualized predictions of mental health outcomes in young people. The first review provides inconsistent evidence about whether and how pubertal and psychopathological processes may interact in relation to brain development. While most studies found an association between early puberty and mental health difficulties in adolescents, evidence on whether brain structure mediates this relationship is mixed. The pituitary gland was found to be associated with mental health status during this time, possibly through its central role in regulating puberty and its function in the hypothalamic-pituitary-gonadal and hypothalamic-pituitary-adrenal axes. In the second review, the design of studies that have explored puberty in predictive models did not allow for a quantification of its predictive power. However, when puberty was evaluated through physically observable characteristics rather than hormonal measures, it was more commonly identified as a predictor of depression, anxiety, and suicidality in adolescence. Social processes may be more relevant than biological ones to the link between puberty and mental health problems and represent an important target for educational strategies.

High rates of mood disorders in patients with chronic idiopathic eosinopenia

Background

Mood disorders (MD) are multifactorial disorders. Identifying new biomarkers for the early diagnosis of MD and predicting response to treatment is currently a significant research topic. Both eosinopenia and MD are associated with increased activity of the hypothalamic-pituitary-adrenal axis. The present study, therefore, used a clear definition of chronic idiopathic eosinopenia (CIE) to determine the rate of MD in a large cohort of individuals with CIE.

Methods

This retrospective population-based, case-control study uses data of seven consecutive years from the database of Leumit Health Services (LHS) - a nationwide health maintenance organization in Israel.

Results

Participants were 13928 LHS members with CIE and 27858 negative controls. The CIE group exhibited significantly higher rates of MD than the control group throughout the whole study period, except for atypical depressive disorder at baseline.

Conclusions

CIE might be associated with a higher prevalence of MD. Further basic research should elucidate the pathophysiologic mechanisms linking CIE and MD.

Dual Approach to Depression: The Combined Efficacy of Intermittent Hypoxia and Fluoxetine in Modulating Behavioral and Inflammatory Responses

Background/Objectives: Mental disorders pose a significant public health challenge, affecting millions worldwide. Given the limitations of current therapies, many patients experience inadequate responses and adverse effects. Intermittent hypoxia (IH) has demonstrated anxiolytic, antidepressant, and neuroprotective properties in various protocols. This study investigated the effects of acute IH (13% O2, 1 h), fluoxetine (FLX) and their combination on depression-like behavior, serum corticosterone, and inflammatory cytokine levels induced by acute restraint stress in C57BL/6 female mice. Methods: Behavioral assessments included the tail suspension test, forced swim test, and open field test. Results: The combined IH + FLX treatment exhibited a synergistic effect, reducing immobility time and increasing latency time, respectively, in the tail suspension test (46%, p = 0.0014; 73%, p = 0.0033) and forced swim test (56%, p = 0.0082; 48%, p = 0.0322) compared to the ARS group. Biochemical analysis revealed that individual and combined treatments significantly reduced most inflammatory interleukins by up to 96%. Corticosterone levels were reduced by 30% only in the IH group. Conclusions: These findings highlight the potential of a one-hour IH session, particularly when combined with fluoxetine, to alleviate depressive-like behaviors and exert anti-inflammatory effects, suggesting a promising therapeutic approach for depression.

Pathogenesis and therapeutic strategies for cancer-related depression

Depression is a common co-morbidity among cancer cases, which has a detrimental influence on cancer treatment and prognosis. Recent advancements in the neurobiology of depression and cancer pathophysiology have revealed several shared biobehavioral mechanisms and introduced new therapeutic strategies. In this review, we summarize the biological mechanisms driving cancer-related depression, including psychosocial factors, immuno-inflammatory processes, chronic stress, dysbiosis of gut microbiota, and medically-induced factors. Interventions used for cancer-related depression may include psychosocial therapies, pharmacological therapies, immunotherapies, psychobiological medications, and dietary strategies. This review could inspire the elucidation of possible co-occurring mechanisms and complex interactions between cancer and depression, provide an opportunity to propose faster and more effective therapies for cancer-related depression, and well as new strategies for cancer in the future.