Multiple Sclerosis (MS) is a debilitating disease that severely affects the central nervous system (CNS). Apart from neurological symptoms, it is also characterized by neuropsychiatric comorbidities, such as anxiety and depression. Phosphodiesterase-5 inhibitors (PDE5Is) such as Sildenafil and Tadalafil have been shown to possess antidepressant-like effects, but the mechanisms underpinning such effects are not fully characterized. To address this question, we used the EAE model of MS, behavioral tests, immunofluorescence, immunohistochemistry, western blot, and 16 S rRNA sequencing. Here, we showed that depressive-like behavior in Experimental Autoimmune Encephalomyelitis (EAE) mice is due to neuroinflammation, reduced synaptic plasticity, dysfunction in glutamatergic neurotransmission, glucocorticoid receptor (GR) resistance, increased blood-brain barrier (BBB) permeability, and immune cell infiltration to the CNS, as well as inflammation, increased intestinal permeability, and immune cell infiltration in the distal colon. Furthermore, 16 S rRNA sequencing revealed that behavioral dysfunction in EAE mice is associated with changes in the gut microbiota, such as an increased abundance of Firmicutes and Saccharibacteria and a reduction in Proteobacteria, Parabacteroides, and Desulfovibrio. Moreover, we detected an increased abundance of Erysipelotrichaceae and Desulfovibrionaceae and a reduced abundance of Lactobacillus johnsonii. Surprisingly, we showed that Tadalafil likely exerts antidepressant-like effects by targeting all aforementioned disease aspects. In conclusion, our work demonstrated that anxiety- and depressive-like behavior in EAE is associated with a plethora of neuroimmune and gut microbiota-mediated mechanisms and that Tadalafil exerts antidepressant-like effects probably by targeting these mechanisms. Harnessing the knowledge of these mechanisms of action of Tadalafil is important to pave the way for future clinical trials with depressed patients.

BACKGROUND: Major depressive disorder (MDD) is a widespread mental health issue, impacting spatial and temporal aspects of brain activity. The neural mechanisms behind MDD remain unclear. To address this gap, we introduce a novel measure, spatiotemporal topology (SPT), capturing both the hierarchy and dynamic attributes of brain activity in depressive disorder patients.
METHODS: We analyzed fMRI data from 285 MDD inpatients and 141 healthy controls (HC). SPT was assessed by coupling brain gradient measurement and time delay estimation. A nested machine learning process distinguished between MDD and HC using SPT. Person\'s correlation tested the link between SPT\'s and symptom severity, and another machine learning method predicted the gap between patients\' chronological and brain age.
RESULTS: SPT demonstrated significant differences between patients and healthy controls (F = 2.944, p < 0.001). Machine learning approaches revealed SPT\'s ability to discriminate between patients and healthy controls (Accuracy = 0.65, Sensitivity = 0.67, Specificity = 0.64). Moreover, SPT correlated with the severity of depression symptom (r = 0.32. pFDR = 0.045) and predicted the gap between patients\' chronological age and brain age (r = 0.756, p < 0.001).
CONCLUSIONS: Evaluation of brain dynamics was constrained by MRI temporal resolution.
CONCLUSIONS: Our study introduces SPT as a promising metric to characterize the spatiotemporal signature of brain function, providing insights into deviant brain activity associated with depressive disorders and advancing our understanding of their psychopathological mechanisms.

BACKGROUND: Both low vagally-mediated heart rate variability (HRV) and depression have been shown to be risk factors for cardiovascular disease (CVD). We recently identified an HRV cutpoint below which persons have an increased risk for several cardiometabolic disorders. However, no cutpoint exists to identify those at risk for depression.
METHODS: The association between daytime HRV and diagnostically validated depression cutoffs using the five-item World Health Organization Well-being Index (WHO-5) was examined in adults from the Mannheim Industrial Cohort Study (n = 9973; Mage = 41.9[10.9]; 20 % women [n = 1934]). The aim was to identify HRV cutpoints for individuals who may have clinical depression.
RESULTS: Regression adjusting for age, sex, and linear trend showed a significant quadratic association between depression, indexed by WHO-5 scores and HRV, indexed by the root mean square successive differences (RMSSD) in milliseconds (ms) (p < 0.001). Logistic regression models adjusting for age, sex, and heart period (i.e., inter-beat intervals) compared the clinically depressed (WHO-5 ≤ 28) and those with a screening diagnosis of depression (WHO-5 ≤ 50) to the rest of the population. Significant odds ratios suggested two RMSSD values 25 ± 2 ms (OR = 1.39 [1.17, 1.64]) and 35 ± 2 ms (OR = 1.17 [1.02, 1.34]) that may be used to identify those with an elevated risk for depression.
CONCLUSIONS: The sample was primarily German men. Fitness and anti-depressant use were not available.
CONCLUSIONS: As HRV is a brief measure that can be used in clinical settings, our HRV cutpoints have implications for the early detection of those at risk for psychological and cardiometabolic disorders.

BACKGROUND: Major depressive disorder (MDD) and schizophrenia (SCZ) are heritable brain disorders characterized by alterations in cortical thickness. However, the shared genetic basis for cortical thickness changes in these disorders remains unclear.
METHODS: We conducted a systematic literature search on cortical thickness in MDD and SCZ through PubMed and Web of Science. A coordinate-based meta-analysis was performed to identify cortical thickness changes. Additionally, utilizing summary statistics from the largest genome-wide association studies for depression (Ncase = 268,615, Ncontrol = 667,123) and SCZ (Ncase = 53,386, Ncontrol = 77,258), we explored shared genomic loci using conjunctional false discovery rate (conjFDR) analysis. Transcriptome-neuroimaging association analysis was then employed to identify shared genes associated with cortical thickness alterations, and enrichment analysis was finally carried out to elucidate the biological significance of these genes.
RESULTS: Our search yielded 34 MDD (Ncase = 1621, Ncontrol = 1507) and 19 SCZ (Ncase = 1170, Ncontrol = 1043) neuroimaging studies for cortical thickness meta-analysis. Specific alterations in the left supplementary motor area were observed in MDD, while SCZ exhibited widespread reductions in various brain regions, particularly in the frontal and temporal areas. The conjFDR approach identified 357 genomic loci jointly associated with MDD and SCZ. Within these loci, 55 genes were found to be associated with cortical thickness alterations in both disorders. Enrichment analysis revealed their involvement in nervous system development, apoptosis, and cell communication.
CONCLUSIONS: This study revealed the shared genetic architecture underlying cortical thickness alterations in MDD and SCZ, providing insights into common neurobiological pathways. The identified genes and pathways may serve as potential transdiagnostic markers, informing precision medicine approaches in psychiatric care.

BACKGROUND: The intricate pathophysiological mechanisms of major depressive disorder (MDD) necessitate the development of comprehensive early indicators that reflect the complex interplay of emotional, physical, and cognitive factors. Despite its potential to fulfill these criteria, interoception remains underexplored in MDD. This study aimed to evaluate the potential of interoception in transforming MDD\'s clinical practices by examining interoception deficits across various MDD stages and analyzing their complex associations with the spectrum of depressive symptoms.
METHODS: This study included 431 healthy individuals, 206 subclinical depression individuals, and 483 MDD patients. Depressive symptoms and interoception function were assessed using the PHQ-9 and MAIA-2, respectively.
RESULTS: Interoception dysfunction occurred in the preclinical phase of MDD and further impaired in the clinical stage. Antidepressant therapies showed limited efficacy in improving interoception and might damage some dimensions. Interoceptive dimensions might predict depressive symptoms, primarily enhancing negative thinking patterns. The predictive model based on interoception was built with random split verification and demonstrated good discrimination and predictive performance in identifying MDD.
CONCLUSIONS: Early alterations in the preclinical stage, multivariate associations with depressive symptoms, and good discrimination and predictive performance highlight the importance of interoception in MDD management, pointing to a paradigm shift in diagnostic and therapeutic approaches.

Major depressive disorder (MDD) is a form of glial cell-based synaptic dysfunction disease in which glial cells interact closely with neuronal synapses and perform synaptic information processing. Glial cells, particularly astrocytes, are active components of the brain and are responsible for synaptic activity through the release gliotransmitters. A reduced density of astrocytes and astrocyte dysfunction have both been identified the brains of patients with MDD. Furthermore, gliotransmission, i.e., active information transfer mediated by gliotransmitters between astrocytes and neurons, is thought to be involved in the pathogenesis of MDD. However, the mechanism by which astrocyte-mediated gliotransmission contributes to depression remains unknown. This review therefore summarizes the alterations in astrocytes in MDD, including astrocyte marker, connexin 43 (Cx43) expression, Cx43 gap junctions, and Cx43 hemichannels, and describes the regulatory mechanisms of astrocytes involved in synaptic plasticity. Additionally, we investigate the mechanisms acting of the glutamatergic, gamma-aminobutyric acidergic, and purinergic systems that modulate synaptic function and the antidepressant mechanisms of the related receptor antagonists. Further, we summarize the roles of glutamate, gamma-aminobutyric acid, d-serine, and adenosine triphosphate in depression, providing a basis for the identification of diagnostic and therapeutic targets for MDD.

BACKGROUND: Observational studies have shown that individual sleep traits habits are potential risk factors for major depression. However, it is not known whether there is a causal relationship between individual sleep traits habits such as continuous sleep duration, short sleep duration, short sleep duration, insomnia, nap during the day, snoring, and major depression. In this study, Mendelian randomization (MR) was used to predict major depressive disorder (MDD) in individuals sleep traits habits.
METHODS: Data were obtained from the genome-wide association study (GWAS). Nine MR analysis methods were used: Inverse Variance Weighted (IVW) [fixed effects/multiplicative random effects], simple mode, simple mode, weighted mode, simple median, weighted median, penalised weighted median, and MR-Egger, MR Egger (bootstrap). IVW was used as the main analysis method for the MR analysis of two samples, and the other methods were used as supplements.
RESULTS: The results obtained through the IVW method supported a causal relationship between sleep duration and decreased risk of MDD (odds ratio, ORivw: 0.998; 95 % CI: 0.996-0.999, P<0.001). Two-Sample MR, results showed that short sleep duration has a causal effect on the increased risk of MDD (odds ratio, ORivw: 1.179; 95 % CI: 1.108-1.255, P<0.001). However, there were no sufficient evidence supported that long sleep duration has a causal effect on the decreased risk of MDD (odds ratio, ORivw: 0.991; 95 % CI: 0.924-1.062, P = 0.793). A significant causal relationship between insomnia and increased risk of MDD was observed (OR: 1.233; 95 % CI: 1.214-1.253, P<0.001). Interestingly, our study also found that daytime napping has a causal effect on the increased risk of MDD (odds ratio, ORivw: 1.519; 95 % CI: 1.376-1.678, P<0.001). The present results did not show a significant causal relationship between snoring and the risk of MDD (ORivw: 1.000; 95 % CI: 0.998-1.002, P = 0.906). Obstructive sleep apnea (odds ratio, ORivw: 1.021; 95 % CI: 0.972-1.072, P = 0.407) and morning person (odds ratio, ORivw: 1.021; 95 % CI: 0.972-1.072, P = 0.407) have no causal effect on the increased risk of MDD.
CONCLUSIONS: The study could not ascertain whether there were genetic differences among different ethnicities, nations, and regions, as it only included participants of European ancestry.
CONCLUSIONS: In summary, our research provides genetic evidence for the relationship between individual sleep traits (short sleep duration, insomnia, daytime napping) and the increased risk of MDD. Interventions targeting lifestyle factors may reduce the risk of MDD.

Puberty is a vulnerable period for the onset of major depressive disorder (MDD) due to considerable neurodevelopmental changes. Prior diffusion tensor imaging (DTI) studies in depressed youth have had heterogeneous participants, making assessment of early pathology challenging due to illness chronicity and medication confounds. This study leveraged whole-brain DTI and graph theory approaches to probe white matter (WM) abnormalities and disturbances in structural network topology related to first-episode, treatment-naïve pediatric MDD. Participants included 36 first-episode, unmedicated adolescents with MDD (mean age 15.8 years) and 29 age- and sex-matched healthy controls (mean age 15.2 years). Compared to controls, the MDD group showed reduced fractional anisotropy in the internal and external capsules, unveiling novel regions of WM disruption in early-onset depression. The right thalamus and superior temporal gyrus were identified as network hubs where betweenness centrality changes mediated links between WM anomalies and depression severity. A diagnostic model incorporating demographics, DTI, and network metrics achieved an AUROC of 0.88 and a F1 score of 0.80 using a neural network algorithm. By examining first-episode, treatment-naïve patients, this work identified novel WM abnormalities and a potential causal pathway linking WM damage to symptom severity via regional structural network alterations in brain hubs.

UNASSIGNED: Major depressive disorder (MDD) can present a variety of clinical presentations and has high inter-individual heterogeneity. Multiple studies have suggested various subtype models related to symptoms, etiology, sex, and treatment response. Employing different regimens is common when treating MDD, and identifying effective therapeutics requires time. Frequent treatment attempts and failures can lead to a diagnosis of treatment resistance, and the heterogeneity of treatment responses among individuals makes it difficult to understand and interpret the biological mechanisms underlying MDD.
UNASSIGNED: This study explored the differentially expressed proteins and commonly altered protein networks across drug treatments by comparing the serum proteomes of patients with MDD treated with drug regimens (T-MDD, n = 20) and untreated patients (NT-MDD, n = 20).
UNASSIGNED: Differentially expressed proteins were profiled in non-drug-treated and drug-treated patients with depression using liquid chromatography-mass spectrometry. The common protein networks affected by different medications were studied.
UNASSIGNED: Of the proteins profiled, 12 were significantly differentially expressed between the T-MDD and NT-MDD groups. Commonly altered proteins and networks of various drug treatments for depression were related to the complement system and immunity.
UNASSIGNED: Our results provide information on common biological changes across different pharmacological treatments employed for depression and provide an alternative perspective for improving our understanding of the biological mechanisms of drug response in MDD with great heterogeneity in the background of the disease.

Depression is among the most common psychiatric illnesses, which imposes a major socioeconomic burden on patients, caregivers, and the public health system. Treatment with classical antidepressants (e.g. tricyclic antidepressants and selective serotonine reuptake inhibitors), which primarily affect monoaminergic systems has several limitations, such as delayed onset of action and moderate efficacy in a relatively large proportion of depressed patients. Furthermore, depression is highly heterogeneus, and its different subtypes, including post-partum depression, involve distinct neurobiology, warranting a differential approach to pharmacotherapy. Given these shortcomings, the need for novel antidepressants that are superior in efficacy and faster in onset of action is fully justified. The development and market introduction of rapid-acting antidepressants has accelerated in recent years. Some of these new antidepressants act through the GABAergic system. In this review, we discuss the discovery, efficacy, and limitations of treatment with classic antidepressants. We provide a detailed discussion of GABAergic neurotransmission, with a special focus on GABAA receptors, and possible explanations for the mood-enhancing effects of GABAergic medications (in particular neurosteroids acting at GABAA receptors), and ultimately, we present the most promising molecules belonging to this family which are currently used in clinical practice or are in late phases of clinical development.