Brain structure alterations in depression: Psychoradiological evidence

Genetic evidence suggests a genetic association between major depressive disorder and reduced cortical gray matter volume: A Mendelian randomization study and mediation analysis

BACKGROUND

Several studies have suggested an association between major depressive disorder (MDD) and abnormal brain structure. However, it is unclear whether MDD affects cortical gray matter volume, a common indicator of cognitive function. We aimed to determine whether MDD was associated with decreased cortical gray matter volume (GMV) through a Mendelian randomization (MR) study.

METHODS

We obtained summary genetic data from a study conducted by the Psychiatric Genomics Consortium, which recruited a total of 480,359 participants (135,458 cases and 344,901 controls). Genetic tools-single nucleotide polymorphisms (SNPs)-of MDD were extracted from the study and their effects on gray matter volumes of the cortex and total brain were evaluated in a large cohort from the UK Biobank (n = 8427). The effects of the SNPs were pooled using inverse variance weighted (IVW) analysis and further tested in several sensitivity analyses. We tested whether C-reactive protein (CRP) levels and interleukin-6 signaling were the mediators of the effects using a multivariate MR model.

RESULTS

Thirty-three SNPs were identified and adopted as genetic tools for predicting MDD. IVW analysis showed that MDD was associated with lower overall GMV (beta value -0.106, 95%CI -0.188 to -0.023, p = 0.011) in the frontal pole (left frontal pole, -0.152, 95%CI -0.177 to -0.127, p = 0.013; right frontal pole, -0.133, 95%CI -0.253 to -0.013, p = 0.028). Multivariate and mediation analysis showed that interleukin-6 was an important mediator of GMV reduction. Reverse causality analysis found no evidence that total GMV affected the risk of MDD, but showed that increased left precuneus cortex volume and left posterior cingulate cortex volume were associated with increased risk of MDD.

LIMITATIONS

Potential pleiotropic effects and overestimation of real-world effects. Key assumptions for MR analysis may not be satisfactorily met.

CONCLUSION

MDD was associated with a reduced GMV, and interleukin-6 might be a mediator of GMV reduction.

Association of Retinal Neurovascular Impairment with Disease Severity in Patients with Major Depressive Disorder: An Optical Coherence Tomography Angiography Study

Background

Identifying the fundus objective biomarkers for the major depressive disorders (MDD) may help promote mental health. The aim of this study was to evaluate retinal neurovascular changes and further investigate their association with disease severity in MDD.

Methods

This cross-sectional study conducted in the hospital enrolled patients with MDD and healthy controls.The retinal neurovascular parameters for all subjects, including vessel density (VD), thickness of ganglion cell complex (GCC) and retinal nerve fiber layer (RNFL), and optic nerve head (ONH) eg are automatically calculated by the software in optical coherence tomography angiography (OCTA). The severity of MDD including depressive symptoms, anxiety, cognition, and insomnia was assessed by Hamilton Depression Rating Scale (HAMD), Hamilton Anxiety Scale (HAMA), Montreal Cognitive Assessment (MoCA), and Insomnia Severity Index (ISI) respectively.

Results

This study included 74 MDD patients (n=74 eyes) and 60 healthy controls (HCs) (n=60 eyes). MDD patients showed significantly decreased VD of superficial and deep capillary plexus, thickness of GCC and RNFL, and volume of ONH (all p<0.05) and increased vertical cup-to-disc ratio and global loss volume (GLV) (all p<0.05) compared to HCs. Positive associations were found between HAMD scores and cup area (r=0.30, p=0.035), cup volume (r=0.31, p=0.029), and disc area (r=0.33, p=0.020) as well as ISI scores and RNFL thickness (r=0.34, p=0.047).

Conclusion

We found the retinal neurovascular impairment and its association with disease severity in MDD patients. OCTA showed promise as a potential complementary assessment tool for MDD.

Functional and Structural Abnormalities in the Pain Network of Generalized Anxiety Disorder Patients with Pain Symptoms

Pain symptoms significantly impact the well-being and work capacity of individuals with generalized anxiety disorder (GAD), and hinder treatment and recovery. Despite existing literature focusing on the neural substrate of pain and anxiety separately, further exploration is needed to understand the possible neuroimaging mechanisms of the pain symptoms in GAD patients. We recruited 73 GAD patients and 75 matched healthy controls (HC) for clinical assessments, as well as resting-state functional and structural magnetic resonance imaging scans. We defined a pain-related network through a published meta-analysis, including the insula, thalamus, periaqueductal gray, prefrontal cortex, anterior cingulate cortex, amygdala, and hippocampus. Subsequently, we conducted the regional homogeneity (ReHo) and the gray matter volume (GMV) within the pain-related network. Correlation analysis was then employed to explore associations between abnormal regions and self-reported outcomes, assessed using the Patient Health Questionnaire-15 (PHQ-15) and pain scores. We observed significantly increased ReHo in the bilateral insula but decreased GMV in the bilateral thalamus of GAD compared to HC. Further correlation analysis revealed a positive correlation between ReHo of the left anterior insula and pain scores in GAD patients, while a respective negative correlation between GMV of the bilateral thalamus and PHQ-15 scores. In summary, GAD patients exhibit structural and functional abnormalities in pain-related networks. The enhanced ReHo in the left anterior insula is correlated with pain symptoms, which might be a crucial brain region of pain symptoms in GAD.

A Shared Multivariate Brain-Behavior Relationship in a Transdiagnostic Sample of Adolescents

BACKGROUND

Internalizing and externalizing psychopathology typically present in early childhood and can have negative implications on general functioning and quality of life. Prior work has linked increased psychopathology symptoms with altered brain structure. Multivariate analysis such as partial least squares correlation can help identify patterns of covariation between brain regions and psychopathology symptoms. This study examined the relationship between gray matter volume (GMV) and psychopathology symptoms in adolescents with various psychiatric diagnoses.

METHODS

Structural magnetic resonance imaging data were collected from 490 participants with various internalizing and externalizing diagnoses (197 female/293 male; age = 14.68 ± 2.35 years; IQ = 104.05 ± 13.11). Cortical and subcortical volumes were parcellated using the Desikan-Killiany atlas. Partial least squares correlation was used to identify multivariate linear relationships between GMV and the Strength and Difficulties Questionnaire difficulties domains (emotional, peer, conduct, and hyperactivity issues). Resampling approaches were used to determine significance (permutation test), stability (bootstrap resampling), and reproducibility (split-half resampling) of identified relationships.

RESULTS

We found a significant, stable, and largely reproducible dimension that linked lower Strength and Difficulties Questionnaire scores (less impairment) across all difficulties domains with greater widespread GMV (singular value = 1.17, accounts for 87.1% of the covariance; p < .001). This dimension emphasized the relationship between lower conduct problems and greater GMV in frontotemporal regions.

CONCLUSIONS

Our results indicate that the most significant and stable brain-behavior relationship in a transdiagnostic sample is a domain-general relationship, linking lower psychopathology symptom scores to greater global GMV. This finding suggests that a shared brain-behavior relationship may be present across adolescents with and without clinically significant psychopathology symptoms.

Neurological and metabolic related pathophysiologies and treatment of comorbid diabetes with depression

BACKGROUND

The comorbidity between diabetes mellitus and depression was revealed, and diabetes mellitus increased the prevalence of depressive disorder, which ranked 13th in the leading causes of disability-adjusted life-years. Insulin resistance, which is common in diabetes mellitus, has increased the risk of depressive symptoms in both humans and animals. However, the mechanisms behind the comorbidity are multi-factorial and complicated. There is still no causal chain to explain the comorbidity exactly. Moreover, Selective serotonin reuptake inhibitors, insulin and metformin, which are recommended for treating diabetes mellitus-induced depression, were found to be a risk factor in some complications of diabetes.

AIMS

Given these problems, many researchers made remarkable efforts to analyze diabetes complicating depression from different aspects, including insulin resistance, stress and Hypothalamic-Pituitary-Adrenal axis, neurological system, oxidative stress, and inflammation. Drug therapy, such as Hydrogen Sulfide, Cannabidiol, Ascorbic Acid and Hesperidin, are conducive to alleviating diabetes mellitus and depression. Here, we reviewed the exact pathophysiology underlying the comorbidity between depressive disorder and diabetes mellitus and drug therapy.

METHODS

The review refers to the available literature in PubMed and Web of Science, searching critical terms related to diabetes mellitus, depression and drug therapy.

RESULTS

In this review, we found that brain structure and function, neurogenesis, brain-derived neurotrophic factor and glucose and lipid metabolism were involved in the pathophysiology of the comorbidity. Obesity might lead to diabetes mellitus and depression through reduced adiponectin and increased leptin and resistin. In addition, drug therapy displayed in this review could expand the region of potential therapy.

CONCLUSIONS

The review summarizes the mechanisms underlying the comorbidity. It also overviews drug therapy with anti-diabetic and anti-depressant effects.

Taste dysfunction as a predictor of depression in schizophrenia: A systematic review and meta-analysis

OBJECTIVE

This study aims to investigate the relationship between taste dysfunction and depression among patients with schizophrenia, to achieve early detection of depression in clinical practice.

METHODS

Following PRISMA guidance, a comprehensive literature search was conducted globally, covering papers published from 1961 to June 2023. A total of 17 manuscripts were selected through meta-analysis and sensitivity analysis after examining available materials from seven databases to determine the correlation between depression and taste dysfunction.

RESULTS

The comparison of the 17 selected manuscripts revealed that individuals with gustatory dysfunction may be more likely to experience depressive symptoms (SMD, 0.51, 95% CI, 0.08 to 0.93, p = 0.02). Depression is associated with taste dysfunction in certain aspects, as indicated by the pleasantness ratings of sucrose solutions (SMD, -0.53, 95% confidence interval [CI] -1.11 to 0.05, p = 0.08), gustatory identification ability (SMD, 0.96, 95% CI, 0.03 to 1.89, p = 0.04), and the perception threshold of sweet taste (MD, 0.80, 95% CI, 0.79 to 0.81, p < 0.00001).

CONCLUSIONS

Due to variations in the methods, designs, and selection criteria employed in the included studies, it is necessary to establish a feasible framework. Future research using detailed and targeted approaches can provide clearer and more unified conclusions on the relationship between taste dysfunction and depression. Moreover, further high-quality research is needed to obtain clearer conclusions and explore the potential of taste dysfunction as an effective tool for early screening of depression.

TRIAL REGISTRATION

This review has been registered in the PROSPERO on April 2022 with the identifier CRD42023400172.

Opportunities and obstacles in non-invasive brain stimulation

Non-invasive brain stimulation (NIBS) is a complex and multifaceted approach to modulating brain activity and holds the potential for broad accessibility. This work discusses the mechanisms of the four distinct approaches to modulating brain activity non-invasively: electrical currents, magnetic fields, light, and ultrasound. We examine the dual stochastic and deterministic nature of brain activity and its implications for NIBS, highlighting the challenges posed by inter-individual variability, nebulous dose-response relationships, potential biases and neuroanatomical heterogeneity. Looking forward, we propose five areas of opportunity for future research: closed-loop stimulation, consistent stimulation of the intended target region, reducing bias, multimodal approaches, and strategies to address low sample sizes.

Characterizing major depressive disorder and substance use disorder using heatmaps and variable interactions: The utility of operant behavior and brain structure relationships

BACKGROUND

Rates of depression and addiction have risen drastically over the past decade, but the lack of integrative techniques remains a barrier to accurate diagnoses of these mental illnesses. Changes in reward/aversion behavior and corresponding brain structures have been identified in those with major depressive disorder (MDD) and cocaine-dependence polysubstance abuse disorder (CD). Assessment of statistical interactions between computational behavior and brain structure may quantitatively segregate MDD and CD.

METHODS

Here, 111 participants [40 controls (CTRL), 25 MDD, 46 CD] underwent structural brain MRI and completed an operant keypress task to produce computational judgment metrics. Three analyses were performed: (1) linear regression to evaluate groupwise (CTRL v. MDD v. CD) differences in structure-behavior associations, (2) qualitative and quantitative heatmap assessment of structure-behavior association patterns, and (3) the k-nearest neighbor machine learning approach using brain structure and keypress variable inputs to discriminate groups.

RESULTS

This study yielded three primary findings. First, CTRL, MDD, and CD participants had distinct structure-behavior linear relationships, with only 7.8% of associations overlapping between any two groups. Second, the three groups had statistically distinct slopes and qualitatively distinct association patterns. Third, a machine learning approach could discriminate between CTRL and CD, but not MDD participants.

CONCLUSIONS

These findings demonstrate that variable interactions between computational behavior and brain structure, and the patterns of these interactions, segregate MDD and CD. This work raises the hypothesis that analysis of interactions between operant tasks and structural neuroimaging might aide in the objective classification of MDD, CD and other mental health conditions.

A structural equation modeling approach using behavioral and neuroimaging markers in major depressive disorder

Major depressive disorder (MDD) has consistently proven to be a multifactorial and highly comorbid disease. Despite recent depression-related research demonstrating causalities between MDD-related factors and a small number of variables, including brain structural changes, a high-statistical power analysis of the various factors is yet to be conducted. We retrospectively analyzed data from 155 participants (84 healthy controls and 71 patients with MDD). We used magnetic resonance imaging and diffusion tensor imaging data, scales assessing childhood trauma, depression severity, cognitive dysfunction, impulsivity, and suicidal ideation. To simultaneously evaluate the causalities between multivariable, we implemented two types of MDD-specified structural equation models (SEM), the behavioral and neurobehavioral models. Behavioral SEM showed significant results in the MDD group: Comparative Fit Index [CFI] = 1.000, Root Mean Square Error of Approximation [RMSEA]) = 0.000), with a strong correlation in the scales for childhood trauma, depression severity, suicidal ideation, impulsivity, and cognitive dysfunction. Based on behavioral SEM, we established neurobehavioral models showing the best-fit in MDD, especially including the right cingulate cortex, central to the posterior corpus callosum, right putamen, pallidum, whole brainstem, and ventral diencephalon, including the thalamus (CFI >0.96, RMSEA <0.05). Our MDD-specific model revealed that the limbic-associated regions are strongly connected with childhood trauma rather than depression severity, and that they independently affect suicidal ideation and cognitive dysfunction. Furthermore, cognitive dysfunction could affect impulsivity.

Neuronal ablation of GHSR mitigates diet-induced depression and memory impairment via AMPK-autophagy signaling-mediated inflammation

Obesity is associated with chronic inflammation in the central nervous system (CNS), and neuroinflammation has been shown to have detrimental effects on mood and cognition. The growth hormone secretagogue receptor (GHSR), the biologically relevant receptor of the orexigenic hormone ghrelin, is primarily expressed in the brain. Our previous study showed that neuronal GHSR deletion prevents high-fat diet-induced obesity (DIO). Here, we investigated the effect of neuronal GHSR deletion on emotional and cognitive functions in DIO. The neuron-specific GHSR-deficient mice exhibited reduced depression and improved spatial memory compared to littermate controls under DIO. We further examined the cortex and hippocampus, the major regions regulating cognitive and emotional behaviors, and found that the neuronal deletion of GHSR reduced DIO-induced neuroinflammation by suppressing proinflammatory chemokines/cytokines and decreasing microglial activation. Furthermore, our data showed that neuronal GHSR deletion suppresses neuroinflammation by downregulating AMPK-autophagy signaling in neurons. In conclusion, our data reveal that neuronal GHSR inhibition protects against DIO-induced depressive-like behavior and spatial cognitive dysfunction, at least in part, through AMPK-autophagy signaling-mediated neuroinflammation.

Association of hippocampal subfield volumes with prevalence, course and incidence of depressive symptoms: The Maastricht Study

BACKGROUND

Late-life depression has been associated with volume changes of the hippocampus. However, little is known about its association with specific hippocampal subfields over time.

AIMS

We investigated whether hippocampal subfield volumes were associated with prevalence, course and incidence of depressive symptoms.

METHOD

We extracted 12 hippocampal subfield volumes per hemisphere with FreeSurfer v6.0 using T1-weighted and fluid-attenuated inversion recovery 3T magnetic resonance images. Depressive symptoms were assessed at baseline and annually over 7 years of follow-up (9-item Patient Health Questionnaire). We used negative binominal, logistic, and Cox regression analyses, corrected for multiple comparisons, and adjusted for demographic, cardiovascular and lifestyle factors.

RESULTS

A total of n = 4174 participants were included (mean age 60.0 years, s.d. = 8.6, 51.8% female). Larger right hippocampal fissure volume was associated with prevalent depressive symptoms (odds ratio (OR) = 1.26, 95% CI 1.08-1.48). Larger bilateral hippocampal fissure (OR = 1.37-1.40, 95% CI 1.14-1.71), larger right molecular layer (OR = 1.51, 95% CI 1.14-2.00) and smaller right cornu ammonis (CA)3 volumes (OR = 0.61, 95% CI 0.48-0.79) were associated with prevalent depressive symptoms with a chronic course. No associations of hippocampal subfield volumes with incident depressive symptoms were found. Yet, lower left hippocampal amygdala transition area (HATA) volume was associated with incident depressive symptoms with chronic course (hazard ratio = 0.70, 95% CI 0.55-0.89).

CONCLUSIONS

Differences in hippocampal fissure, molecular layer and CA volumes might co-occur or follow the onset of depressive symptoms, in particular with a chronic course. Smaller HATA was associated with an increased risk of incident (chronic) depression. Our results could capture a biological foundation for the development of chronic depressive symptoms, and stresses the need to discriminate subtypes of depression to unravel its biological underpinnings.

Depression and treatment with anti-calcitonin gene related peptide (CGRP) (ligand or receptor) antibodies for migraine

BACKGROUND AND PURPOSE

The aim was to evaluate the effect of anti-calcitonin gene related peptide (CGRP) (ligand or receptor) antibodies on depressive symptoms in subjects with migraine and to determine whether depressive symptoms predict treatment response.

METHODS

Patients with migraine treated with erenumab and fremanezumab at the Leiden Headache Centre completed daily E-headache diaries. A control group was included. Depressive symptoms were assessed using the Hospital Anxiety and Depression Scale (HADS) and the Center for Epidemiological Studies Depression Scale (CES-D) questionnaires at baseline (T0) and after 3 months (T1). First, the effect of treatment on the reduction in HADS-D and CES-D scores was assessed, with reduction in depression scores as the dependent variable and reduction in monthly migraine days (MMD) and treatment with anti-CGRP medication as independent variables. Second, depression as a predictor of treatment response was investigated, using the absolute reduction in MMD as a dependent variable and age, gender, MMD, active depression, impact, stress and locus of control scores as independent variables.

RESULTS

In total, n = 108 patients were treated with erenumab, n = 90 with fremanezumab and n = 68 were without active treatment. Treatment with anti-CGRP medication was positively associated with a reduction in the HADS-D (β = 1.65, p = 0.01) compared to control, independent of MMD reduction. However, the same effect was not found for the CES-D (β = 2.15, p = 0.21). Active depression predicted poorer response to erenumab (p = 0.02) but not to fremanezumab (p = 0.09).

CONCLUSION

Anti-CGRP (ligand or receptor) monoclonals lead to improvement of depressive symptoms in individuals with migraine, independent of migraine reduction. Depression may predict treatment response to erenumab but not to fremanezumab.

Transdiagnostic subgroups of cognitive impairment in early affective and psychotic illness

Cognitively impaired and spared patient subgroups were identified in psychosis and depression, and in clinical high-risk for psychosis (CHR). Studies suggest differences in underlying brain structural and functional characteristics. It is unclear whether cognitive subgroups are transdiagnostic phenomena in early stages of psychotic and affective disorder which can be validated on the neural level. Patients with recent-onset psychosis (ROP; N = 140; female = 54), recent-onset depression (ROD; N = 130; female = 73), CHR (N = 128; female = 61) and healthy controls (HC; N = 270; female = 165) were recruited through the multi-site study PRONIA. The transdiagnostic sample and individual study groups were clustered into subgroups based on their performance in eight cognitive domains and characterized by gray matter volume (sMRI) and resting-state functional connectivity (rsFC) using support vector machine (SVM) classification. We identified an impaired subgroup (NROP = 79, NROD = 30, NCHR = 37) showing cognitive impairment in executive functioning, working memory, processing speed and verbal learning (all p < 0.001). A spared subgroup (NROP = 61, NROD = 100, NCHR = 91) performed comparable to HC. Single-disease subgroups indicated that cognitive impairment is stronger pronounced in impaired ROP compared to impaired ROD and CHR. Subgroups in ROP and ROD showed specific symptom- and functioning-patterns. rsFC showed superior accuracy compared to sMRI in differentiating transdiagnostic subgroups from HC (BACimpaired = 58.5%; BACspared = 61.7%, both: p < 0.01). Cognitive findings were validated in the PRONIA replication sample (N = 409). Individual cognitive subgroups in ROP, ROD and CHR are more informative than transdiagnostic subgroups as they map onto individual cognitive impairment and specific functioning- and symptom-patterns which show limited overlap in sMRI and rsFC. CLINICAL TRIAL REGISTRY NAME: German Clinical Trials Register (DRKS). Clinical trial registry URL: https://www.drks.de/drks_web/ . Clinical trial registry number: DRKS00005042.

Association between depressive symptoms and dynamic balance among young adults in the community

Background

Detecting and addressing depression symptoms at their outset can reduce the burden on individuals and society; however, it has a limitation in that such evaluations mainly rely on self-reports. Several studies have demonstrated a strong association between motor symptoms and early depression. We aimed to associate body balance measured by the Lower Quarter Y Balance Test (YBT-LQ) with depressive symptoms among young adults in the community, to confirm the current evidence that depression negatively influences body balance.

Research question

Is the YBT-LQ an objective tool for measuring and evaluating young adults' depression risks, as well as assessing whether depression negatively influences body balance?

Methods

Our participants comprised 36 young adults. We assessed their depressive symptoms using the Center for Epidemiological Studies Depression Scale (CES-D) via a Google survey, measured their body balance with the YBT-LQ, and analyzed data with Spearman's rank-order correlation coefficient test, using SPSS version 27.0.

Results

We found that the right leg's anterior, posteromedial, and posterolateral scores- Z = -2.129, p = .033; Z = -2.181, p = .029; and Z = -2.250, p = .024, respectively-and composite scores-Z = 73.00, p = .027 -were significantly lower in the group with risk for clinical depression compared to the normal group. The CES-D total score had a negative association with all YBT-LQ scores, except for the anterior score of the left leg. Among the CES-D sub-factors, somatic and retarded activity showed negative correlations with all the YBT-LQ scores.

Significance

Our findings revealed that depressive symptoms have a negative association with balance, and that the YBT-LQ can be a reliable tool for measuring motor symptoms of depression, specifically among young adults.

Converged avenues: depression and Alzheimer's disease- shared pathophysiology and novel therapeutics

Depression, a highly prevalent disorder affecting over 280 million people worldwide, is comorbid with many neurological disorders, particularly Alzheimer's disease (AD). Depression and AD share overlapping pathophysiology, and the search for accountable biological substrates made it an essential and intriguing field of research. The paper outlines the neurobiological pathways coinciding with depression and AD, including neurotrophin signalling, the hypothalamic-pituitary-adrenal axis (HPA), cellular apoptosis, neuroinflammation, and other aetiological factors. Understanding overlapping pathways is crucial in identifying common pathophysiological substrates that can be targeted for effective management of disease state. Antidepressants, particularly monoaminergic drugs (first-line therapy), are shown to have modest or no clinical benefits. Regardless of the ineffectiveness of conventional antidepressants, these drugs remain the mainstay for treating depressive symptoms in AD. To overcome the ineffectiveness of traditional pharmacological agents in treating comorbid conditions, a novel therapeutic class has been discussed in the paper. This includes neurotransmitter modulators, glutamatergic system modulators, mitochondrial modulators, antioxidant agents, HPA axis targeted therapy, inflammatory system targeted therapy, neurogenesis targeted therapy, repurposed anti-diabetic agents, and others. The primary clinical challenge is the development of therapeutic agents and the effective diagnosis of the comorbid condition for which no specific diagnosable scale is present. Hence, introducing Artificial Intelligence (AI) into the healthcare system is revolutionary. AI implemented with interdisciplinary strategies (neuroimaging, EEG, molecular biomarkers) bound to have accurate clinical interpretation of symptoms. Moreover, AI has the potential to forecast neurodegenerative and psychiatric illness much in advance before visible/observable clinical symptoms get precipitated.

Single-nucleus transcriptomic analysis reveals the relationship between gene expression in oligodendrocyte lineage and major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is a common mental illness that affects millions of people worldwide and imposes a heavy burden on individuals, families and society. Previous studies on MDD predominantly focused on neurons and employed bulk homogenates of brain tissues. This paper aims to decipher the relationship between oligodendrocyte lineage (OL) development and MDD at the single-cell resolution level.

METHODS

Here, we present the use of a guided regularized random forest (GRRF) algorithm to explore single-nucleus RNA sequencing profiles (GSE144136) of the OL at four developmental stages, which contains dorsolateral prefrontal cortex of 17 healthy controls (HC) and 17 MDD cases, generated by Nagy C et al. We prioritized and ordered differentially expressed genes (DEGs) based on Nagy et al., which could predominantly discriminate cells in the four developmental stages and two adjacent developmental stages of the OL. We further screened top-ranked genes that distinguished between HC and MDD in four developmental stages. Moreover, we estimated the performance of the GRRF model via the area under the curve value. Additionally, we validated the pivotal candidate gene Malat1 in animal models.

RESULTS

We found that, among the four developmental stages, the onset development of OL (OPC2) possesses the best predictive power for distinguishing HC and MDD, and long noncoding RNA MALAT1 has top-ranked importance value in candidate genes of four developmental stages. In addition, results of fluorescence in situ hybridization assay showed that Malat1 plays a critical role in the occurrence of depression.

CONCLUSIONS

Our work elucidates the mechanism of MDD from the perspective of OL development at the single-cell resolution level and provides novel insight into the occurrence of depression.

A neuroimaging study of brain activity alterations in treatment-resistant depression after a dual target accelerated transcranial magnetic stimulation

In this study, we designed a new transcranial magnetic stimulation (TMS) protocol using a dual-target accelerated transcranial magnetic stimulation (aTMS) for patients with treatment resistant depression (TRD). There are 58 TRD patients were recruited from the Second People's Hospital of Guizhou Province, who were, respectively, received dual-target (real continuous theta burst stimulation (cTBS) at right orbitofrontal cortex (OFC) and real repetitive transcranial magnetic stimulation (rTMS) at left dorsolateral prefrontal cortex (DLPFC)), single- target (sham cTBS at right OFC and real rTMS at left DLPFC), and sham stimulation (sham cTBS at right OFC and sham rTMS at left DLPFC). Resting-state functional magnetic resonance imaging (rs-fMRI) was acquired before and after aTMS treatment to compare characteristics of brain activities by use of amplitude of low-frequency fluctuations (ALFF), fractional low-frequency fluctuations (fALFF) and functional connectivity (FC). At the same time, Hamilton Depression Scale-24 (HAMD24) were conducted to assess the effect. HAMD24 scores reduced significantly in dual group comparing to the single and sham group. Dual-target stimulation decreased not only the ALFF values of right fusiform gyrus (FG) and fALFF values of the left superior temporal gyrus (STG), but also the FC between the right FG and the bilateral middle frontal gyrus (MFG), left triangular part of inferior frontal gyrus (IFG). Higher fALFF value in left STG at baseline may predict better reaction for bilateral arTMS. Dual-targe stimulation can significantly change resting-state brain activities and help to improve depressive symptoms.

Abnormal changes of dynamic topological characteristics in patients with major depressive disorder

BACKGROUND

Most studies have detected abnormalities of static topological characteristics in major depressive disorder (MDD). However, whether dynamic alternations in brain topology are influenced by MDD remains unknown.

METHODS

An approach was proposed to capture the dynamic topological characteristics with sliding-window and graph theory for a large data sample from the REST-meta-MDD project.

RESULTS

It was shown that patients with MDD were characterized by decreased nodal efficiency of the left orbitofrontal cortex. The temporal variability of topological characteristics was focused on the left opercular part of inferior frontal gyrus, and the right part of middle frontal gyrus, inferior parietal gyrus, precuneus and thalamus.

LIMITATIONS

Future studies need larger and diverse samples to explore the relationship between dynamic topological network characteristics and MDD symptoms.

CONCLUSIONS

The results support that the altered dynamic topology in cortex of frontal and parietal lobes and thalamus during resting-state activity may be involved in the neuropathological mechanism of MDD.

Treatment status of psychiatric disorders and falls in the workplace among Japanese workers: a nationwide cross-sectional study

OBJECTIVES

In Japan, the most common injury requiring sick leave is a fall in the workplace; therefore, it is very important to prevent falls. Most measures to prevent falls involve aspects of the workplace environment and safety. However, few measures consider the perspective of individual health. We investigated the relationship between psychiatric disorders and falls in the workplace and whether treatment status for a psychiatric disorder is associated with workplace falls.

METHODS

We conducted a cross-sectional study among workers aged 20 years or older in Japan from February 28 to March 3, 2022. In total, the data of 27 693 participants were analyzed. We used a questionnaire to query participants' status of treatment for any psychiatric disorder and whether they had experienced a fall in the workplace. The association between treatment for a psychiatric disorder and workplace falls was examined using logistic regression analysis.

RESULTS

Compared with participants receiving appropriate treatment for a psychiatric disorder, the odds ratio (OR) of a workplace fall was significantly lower among participants who did not require treatment for a psychiatric disorder, at 0.56 (95% CI: 0.47-0.66; P < .001); the OR of a workplace fall was significantly higher among participants whose treatment for a psychiatric disorder was interrupted, at 1.47 (95% CI: 1.21-1.78; P < .001), after adjusting for age, sex, household income, number of workplace employees, sleeping hours, exercise habits, and psychological distress.

CONCLUSIONS

Our findings suggest that receiving appropriate treatment for psychiatric disorders may contribute to preventing falls in the workplace.

Neuroplasticity: Pathophysiology and Role in Major Depressive Disorder

Neuroplasticity is characterized by the brain's ability to change its activity in response to extrinsic and intrinsic factors and is thought to be the mechanism behind all brain functions. Neuroplasticity causes structural and functional changes on a molecular level, specifically the growth of different regions in the brain and changes in synaptic and post-synaptic activities. The four types of neuroplasticity are homologous area adaption, compensatory masquerade, cross-modal reassignment, and map expansion. All of these help the brain work around injuries or new information inputs. In addition to baseline physical functions, neuroplasticity is thought to be the basis of emotional and mental regulations and the impairment of it can cause various mental illnesses. Concurrently, these mental illnesses further the damage of synaptic plasticity in the brain. Major depressive disorder (MDD) is one of the most common mental illnesses. It is affected by and accelerates the impairment of neuroplasticity. It is characterized by a chronically depressed state of mind that can impact the patient's daily life, including work life and interests. This review will focus on highlighting the physiological aspects of the disease and the role of neuroplasticity in the pathogenesis and pathology of the disorder. Moreover, the role of monoamine regulation and ketamine uptake will be discussed in terms of their antidepressant effects on the outcomes of MDD.

Psychopharmacological Approaches for Neural Plasticity and Neurogenesis in Major Depressive Disorders

Major depressive disorder (MDD) is a mental health disorder associated with cognitive impairment, dysregulated appetite, fatigue, insomnia or hypersomnia, and severe mood changes that significantly impact the ability of the affected individual to perform day-to-day tasks, leading to suicide in the worst-case scenario. As MDD is becoming more prevalent, affecting roughly 300 million individuals worldwide, its treatment has become a major point of interest. Antidepressants acting as selective serotonin reuptake inhibitors (SSRIs) are currently used as the first line of treatment for MDD. Other antidepressants currently used for the treatment of MDD include the serotonin and norepinephrine reuptake inhibitors (SNRIs), tricyclic antidepressants (TCAs), and monoamine oxidase inhibitors (MAOIs). However, although effective in alleviating symptoms of MDD, most antidepressants require weeks or even months of regular administration prior to eliciting a rational clinical effect. Owing to the strong evidence showing a relationship between neural plasticity, neurogenesis, and MDD, researchers have also looked at the possibility of using treatment modalities that target these processes in an attempt to improve clinical outcome. The overarching aim of this chapter is to highlight the role of neural plasticity and neurogenesis in the pathophysiology of MDD and discuss the most recently studied treatment strategies that target these processes by presenting supporting evidence from both animal and human studies.

Impact of subjective sleep quality on objective measures of neurocognitive dysfunction in patients with major depressive disorder

Background

Sleep disturbances are prevalent in major depressive disorder (MDD). MDD and sleep disturbances are both linked to cognitive impairments. Studies exploring the mechanisms and impact of sleep disturbances on neurocognitive functioning in depressed patients are lacking and proper assessment and therapeutic interventions for sleep disturbances are not part of clinical management of MDD.

Aim

We investigated the association between subjective sleep quality and neurocognitive dysfunction in patients with MDD.

Materials and Methods

Patients with moderate MDD episode were matched and assigned to two groups with poor and good sleep quality. We used Pittsburgh Sleep Quality Index (PSQI) to assess sleep quality. To measure frontotemporally mediated cognitive functioning, following tests were administered: Wisconsin Card Sorting Test (WCST) and degraded continuous performance test (CPT-DS). Two-tailed independent samples t tests or Mann-Whitney U tests and Pearson's correlation coefficient were performed for the statistical analysis of sleep latency, sleep duration, overall sleep quality, CPT d' value, WCST correct answers, errors, and perseverative errors.

Results

Participants with MDD and poor sleep quality performed worse on cognitive tests compared to patients with MDD and good sleep quality. Scores of subjective sleep on PSQI positively correlated with WCST errors (r (60) =0.8883 P = .001) and negatively correlated with WCST correct answers (r (60) = -.869 P = .001) and measures of CPT-DS d' value (r (60) = -.9355 P = .001).

Conclusions

Poor sleep quality, notably sleep duration and sleep latency, worsens the neurocognitive impairments of MDD patients. As these impairments are found to be associated with treatment outcomes, sleep disturbances should be additionally assessed and treated in MDD episode.

Interplay of G-proteins and Serotonin in the Neuroimmunoinflammatory Model of Chronic Stress and Depression: A Narrative Review

INTRODUCTION

This narrative review addresses the clinical challenges in stress-related disorders such as depression, focusing on the interplay between neuron-specific and pro-inflammatory mechanisms at the cellular, cerebral, and systemic levels.

OBJECTIVE

We aim to elucidate the molecular mechanisms linking chronic psychological stress with low-grade neuroinflammation in key brain regions, particularly focusing on the roles of G proteins and serotonin (5-HT) receptors.

METHODS

This comprehensive review of the literature employs systematic, narrative, and scoping review methodologies, combined with systemic approaches to general pathology. It synthesizes current research on shared signaling pathways involved in stress responses and neuroinflammation, including calcium-dependent mechanisms, mitogen-activated protein kinases, and key transcription factors like NF-κB and p53. The review also focuses on the role of G protein-coupled neurotransmitter receptors (GPCRs) in immune and pro-inflammatory responses, with a detailed analysis of how 13 of 14 types of human 5-HT receptors contribute to depression and neuroinflammation.

RESULTS

The review reveals a complex interaction between neurotransmitter signals and immunoinflammatory responses in stress-related pathologies. It highlights the role of GPCRs and canonical inflammatory mediators in influencing both pathological and physiological processes in nervous tissue.

CONCLUSION

The proposed Neuroimmunoinflammatory Stress Model (NIIS Model) suggests that proinflammatory signaling pathways, mediated by metabotropic and ionotropic neurotransmitter receptors, are crucial for maintaining neuronal homeostasis. Chronic mental stress can disrupt this balance, leading to increased pro-inflammatory states in the brain and contributing to neuropsychiatric and psychosomatic disorders, including depression. This model integrates traditional theories on depression pathogenesis, offering a comprehensive understanding of the multifaceted nature of the condition.

Simvastatin ameliorates synaptic plasticity impairment in chronic mild stress-induced depressed mice by modulating hippocampal NMDA receptor

BACKGROUND

In our previous study, we showed simvastatin exerts an antidepressant effect and inhibits neuroinflammation. Given the role of synaptic impairment in depression development, we investigate the effect of simvastatin on synaptic plasticity in depression and the related mechanisms.

METHODS

Electrophysiological analysis, Golgi staining, and transmission electron microscope were performed to analyze the effect of simvastatin on synaptic impairment in depression. In addition, the localization and reactivity of N-methyl-D-aspartate receptor (NMDAR) subunits and the downstream signaling were investigated to explore the mechanism of simvastatin's effect on synaptic plasticity.

RESULTS

Simvastatin ameliorated the reduction of the magnitude of long-term potentiation (LTP) in Schaffer collateral-CA1, restored hippocampal dendritic spine density loss, improved the number of spine synapses, reversed the reduction in BrdU-positive cells in chronic mild stress (CMS)-induced depressed mice, and ameliorated NMDA-induced neurotoxicity in hippocampal neurons. Dysfunction of NMDAR activity in the hippocampus is associated with depression. Simvastatin treatment reversed the surface expression and phosphorylation changes of NMDAR subunits in NMDA-treated hippocampal neurons and depressed mice. In addition, simvastatin further increased the levels of mature BDNF, activating TrkB-Akt-mTOR signaling, which is critical for synaptic plasticity.

CONCLUSIONS

These findings suggest that simvastatin can improve the dysfunction of NMDAR and ameliorate hippocampal synaptic plasticity impairment in depressed mice.

Predicting amyloid-PET status in a memory clinic: The role of the novel antero-posterior index and visual rating scales

INTRODUCTION

Visual rating scales are increasingly utilized in clinical practice to assess atrophy in crucial brain regions among patients with cognitive disorders. However, their capacity to predict Alzheimer's disease (AD)-related pathology remains unexplored, particularly within a heterogeneous memory clinic population. This study aims to assess the accuracy of a novel visual rating assessment, the antero-posterior index (API) scale, in predicting amyloid-PET status. Furthermore, the study seeks to determine the optimal cohort-based cutoffs for the medial temporal atrophy (MTA) and parietal atrophy (PA) scales and to integrate the main visual rating scores into a predictive model.

METHODS

We conducted a retrospective analysis of brain MRI and high-resolution TC scans from 153 patients with cognitive disorders who had undergone amyloid-PET assessments due to suspected AD pathology in a real-world memory clinic setting.

RESULTS

The API scale (cutoff ≥1) exhibited the highest accuracy (AUC = 0.721) among the visual rating scales. The combination of the cohort-based MTA and PA threshold with the API yielded favorable accuracy (AUC = 0.787). Analyzing a cohort of MCI/Mild dementia patients below 75 years of age, the API scale and the predictive model improved their accuracy (AUC = 0.741 and 0.813, respectively), achieving excellent results in the early-onset population (AUC = 0.857 and 0.949, respectively).

CONCLUSION

Our study emphasizes the significance of visual rating scales in predicting amyloid-PET positivity within a real-world memory clinic. Implementing the novel API scale, alongside our cohort-based MTA and PA thresholds, has the potential to substantially enhance diagnostic accuracy.

Loneliness is related to smaller gray matter volumes in ACC and right VLPFC in people with major depression: a UK biobank study

The anterior cingulate cortex (ACC) and right ventrolateral prefrontal cortex (VLPFC) are thought to have important roles in loneliness (feeling of social isolation/exclusion) experience or regulation and in the pathophysiology of their disturbance in major depressive disorder (MDD). However, the structural abnormalities of these regions and the correlates with loneliness in MDD across the healthy population have not fully been clarified. The study analyzed the link between loneliness and gray matter volumes (GMVs) in the ACC and right VLPFC among 1,005 patients with MDD and 7,247 healthy controls (HCs) using UK Biobank data. Significant reductions in GMV in the right VLPFC were found in MDD males compared to HCs. MDD males also showed a higher association between loneliness and reduced GMVs in the right VLPFC and bilateral ACC than HCs. No such associations were found in MDD females. The findings suggest that loneliness may influence brain structures crucial for emotion experience and regulation, particularly in middle-older aged men with MDD. This highlights the potential adverse effects of loneliness on brain structure in MDD and suggests that social engagement could have a positive impact.

Identification and Analyses of Crucial Genes Associated with Pathogenesis of Major Depressive Disorder

Background

Major depressive disorder is a debilitating mental condition that causes severe disability leading to a high fatality rate. No valid blood-based biomarkers for major depressive disorder are currently available. The purpose of this research is to investigate gene biomarkers and pathways that may be linked to major depressive disorder pathogenesis.

Methods

Two microarray databases were retrieved from Gene Expression Omnibus for screening of candidate differentially expressed genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed followed by protein-protein interaction network of differentially expressed genes.

Results

About 1181 differentially expressed genes were identified from the microarray databases. Gene Ontology analyses indicated that these differentially expressed genes were significantly enriched in mRNA splicing via spliceosome, neutrophil degranulation, peptide antigen assembly with MHC class II protein complex, and immunoglobulin production-mediated immune response. The most enriched Kyoto Encyclopedia of Genes and Genomes pathway terms of the 10 significant were Hematopoietic cell lineage. About 20 genes were identified as hub genes after pathway analyses, mostly involved in colorectal cancer and the composition of ribosomes and protein processing, including KRAS, CD86, RPL9, RPL3, and RPL18.

Conclusion

New candidate genes have been identified using bioinformatic approaches that suggest their involvement in the pathogenesis of major depressive disorder and serve as potential genetic diagnostic markers as well as new therapeutic targets.

Increased brain iron in patients with thyroid-associated ophthalmopathy: a whole-brain analysis

Background

To investigate the whole-brain iron deposition alternations in patients with thyroid-associated ophthalmopathy (TAO) using quantitative susceptibility mapping (QSM).

Methods

Forty-eight patients with TAO and 33 healthy controls (HCs) were enrolled. All participants underwent brain magnetic resonance imaging scans and clinical scale assessments. QSM values were calculated and compared between TAO and HCs groups using a voxel-based analysis. A support vector machine (SVM) analysis was performed to evaluate the performance of QSM values in differentiating patients with TAO from HCs.

Results

Compared with HCs, patients with TAO showed significantly increased QSM values in the bilateral caudate nucleus (CN), left thalamus (TH), left cuneus, left precuneus, right insula and right middle frontal gyrus. In TAO group, QSM values in left TH were positively correlated with Hamilton Depression Rating Scale (HDRS) scores (r = 0.414, p = 0.005). The QSM values in right CN were negatively correlated with Montreal Cognitive Assessment (MoCA) scores (r = -0.342, p = 0.021). Besides that, a nearly negative correlation was found between QSM values in left CN and MoCA scores (r = -0.286, p = 0.057). The SVM model showed a good performance in distinguishing patients with TAO from the HCs (area under the curve, 0.958; average accuracy, 90.1%).

Conclusion

Patients with TAO had significantly increased iron deposition in brain regions corresponding to known visual, emotional and cognitive deficits. QSM values could serve as potential neuroimaging markers of TAO.

Triple network connectivity changes in patients with major depressive disorder versus healthy controls via structural network imaging after electroconvulsive therapy treatment

OBJECTIVE

To investigate the effect of electroconvulsive treatment (ECT) on dynamic structural network connectivity in major depressive disorder (MDD), based on the triple-network model.

METHODS

Twenty-one first-episode, drug-naïve patients with MDD and 21 age- and sex-matched healthy subjects were recruited. Bilateral electrical stimulation was performed thrice a week for a total of 4-5 weeks in the MDD group. MRI data were obtained, and triple-network structural connectivity was evaluated using source-based morphometry (SBM) analysis. A paired t-test was used to analyze structural connectivity differences between pre- and post-ECT MDD groups, one-way analysis was used to calculate three intrinsic network differences between HCs, pre- and post-ECT groups, and partial least squares structural equation modelling was used to investigate dynamic structural network connectivity (dSNC) across groups.

RESULTS

Pre-ECT patients with MDD exhibited significantly lower salience network (SN) structural connectivity (p = 0.010) than the healthy control (HC) group and after ECT therapy SN structural connectivity was significantly elevated (p = 0.002) in post-ECT group compared with pre-ECT. PLS-SEM analysis conducted on inter-network connectivity in the triple-network model indicated a significant difference between SN and central executive network (CEN) in all three groups. The HC and post-ECT MDD groups showed notable direct connectivity between the SN and default mode network (DMN), while the pre-ECT MDD group showed consequential pathological connectivity between the CEN and DMN. A mediation analysis revealed a significant indirect effect of the SN on the DMN through the CEN (β = 0.363, p = 0.008) only in the pre-ECT MDD group.

CONCLUSIONS

ECT may be an effective and minimally invasive treatment for addressing structural changes in the SN and direct communication abnormalities between the three core brain networks in patients with MDD, with possible beneficial correction of indirect connections.

Association between limbic system lesions and anxiety in persons with multiple sclerosis

BACKGROUND

Persons with Multiple Sclerosis (PwMS) have a higher rate of anxiety and depression than the general population. Depression has been associated with clinical relapses; temporal lesions were shown to predict depression severity. Anxiety is considerably understudied. The role of MS lesions in the limbic system is also understudied, partly due to difficulties identifying limbic lesions on standard 1.5 and 3 Tesla MRI.

METHODS

This is a retrospective study of 23 PwMS who underwent 7T MRI on the same day as completing the Hospital Anxiety and Depression Scale (HADS). MRI was performed on a Siemens 7T MRI Plus and an 8-channel transmit coil with 32 receiver channels operating in pTx mode. MP2RAGE and DIR-SPACE sequences were analyzed to determine the number of lesions within the limbic system.

RESULTS

The median number of lesions in the limbic system was 2.0 (range 0-7). When comparing the presence or absence of lesions in the limbic system, there was a significant relationship with anxiety (X2 (1, N = 23)=4.44, p = 0.035), but not for depression.

CONCLUSION

Although only a small sample size, this study provides preliminary evidence that lesions in the limbic system are associated with the presence of anxiety in PwMS. This relationship warrants further investigation.

Altered single-subject gray matter structural networks in first-episode drug-naïve adolescent major depressive disorder

Although previous studies have demonstrated regional gray matter (GM) structural abnormalities in adolescents with major depressive disorder (MDD), how the topological organization of GM networks is affected in these patients is still unclear. Structural magnetic resonance imaging data were acquired from 100 first-episode drug-naïve adolescent MDD patients and 80 healthy controls (HCs). Whole-brain GM structural network was constructed for each subject, and a graph theory analysis was used to calculate the topological metrics of GM networks. Adolescent MDD patients showed significantly lower cluster coefficient and local efficiency compared to HCs. Compared to controls, adolescent MDD patients showed higher nodal centralities in the bilateral cuneus, left lingual gyrus, and right middle occipital gyrus and lower nodal centralities in the bilateral dorsolateral superior frontal gyrus, bilateral middle frontal gyrus, right anterior cingulate and paracingulate gyri, bilateral hippocampus, bilateral amygdala, bilateral caudate nucleus, and bilateral thalamus. Nodal centralities of the hippocampus were negatively associated with symptom severity and illness duration. Our findings suggest disrupted topological organization of GM structural networks in adolescent MDD patients. Impaired local segregation and abnormal nodal centralities in the prefrontal-subcortical-limbic areas and visual cortex regions may play important roles in the neurobiology of adolescent-onset MDD.

Serotonin Transporter mRNA Expression Is Reduced in the Peripheral Blood Mononuclear Cells of Subjects with Major Depression but Normal in Fibromyalgia

BACKGROUND

Fibromyalgia (FM) and major depression disorder (MDD) frequently co-occur. Both disorders may share common serotonergic alterations, although there is less evidence of such alterations in FM. It is also unclear as to whether these alterations are persistent over time or transient. The objectives of this study were to (i) examine the changes in mRNA expression of serotonin transporter (SERT) on the surface of peripheral blood mononuclear cells (PBMCs) in FM, MDD, and the FM + MDD subjects compared to healthy controls, and to (ii) evaluate the effect of drug treatment on SERT expression.

METHODS

PBMCs were isolated from FM, MDD, FM + MDD, and control subjects. SERT expression was analyzed at the mRNA level via quantitative real-time polymerase chain reaction. Statistical analyses were performed using analyses of variance and linear mixed-effects models.

RESULTS

SERT mRNA expression was significantly reduced in MDD subjects compared to controls (p < 0.001), but not in FM nor in FM + MDD subjects. Although the drug treatments improved symptoms in FM, MDD, and FM + MDD subjects, they had no significant effect on SERT mRNA expression.

CONCLUSIONS

These results corroborate the role of the SERT in the pathophysiology of MDD, but not in FM, and show that the decreased mRNA expression of SERT is a persistent, rather than transient, phenomenon.

Long-term effects of prenatal infection on the human brain: a prospective multimodal neuroimaging study

There is convincing evidence from rodent studies suggesting that prenatal infections affect the offspring's brain, but evidence in humans is limited. Here, we assessed the occurrence of common infections during each trimester of pregnancy and examined associations with brain outcomes in adolescent offspring. Our study was embedded in the Generation R Study, a large-scale sociodemographically diverse prospective birth cohort. We included 1094 mother-child dyads and investigated brain morphology (structural MRI), white matter microstructure (DTI), and functional connectivity (functional MRI), as outcomes at the age of 14. We focused on both global and focal regions. To define prenatal infections, we composed a score based on the number and type of infections during each trimester of pregnancy. Models were adjusted for several confounders. We found that prenatal infection was negatively associated with cerebral white matter volume (B = -0.069, 95% CI -0.123 to -0.015, p = 0.011), and we found an association between higher prenatal infection scores and smaller volumes of several frontotemporal regions of the brain. After multiple testing correction, we only observed an association between prenatal infections and the caudal anterior cingulate volume (B = -0.104, 95% CI -0.164 to -0.045, p < 0.001). We did not observe effects of prenatal infection on other measures of adolescent brain morphology, white matter microstructure, or functional connectivity, which is reassuring. Our results show potential regions of interest in the brain for future studies; data on the effect of severe prenatal infections on the offspring's brain in humans are needed.

Deficits in specific executive functions manifest by severity in major depressive disorder: a comparison of antidepressant naïve inpatient, outpatient, subclinical, and healthy control groups

Introduction

Previous research has highlighted the executive function (EF) deficits present in depressed patients; however, conflicting results exist regarding the impact of depression severity on the size of these deficits. This study aimed to compare deficits in EF between antidepressant naïve inpatient and outpatient depressed, a group with subclinical depression symptoms, and a healthy control group while controlling for education, sex, and age.

Methods

In cross-sectional research, 245 antidepressant naive participants (46 inpatient, 68 outpatient, 65 subclinical, and 67 healthy control individuals) were recruited by convenience sampling. The Structured Clinical Interview for DSM-5 Disorders (SCID-5) and Beck Depression Inventory-II (BDI-II) were used to assess depression. EF was measured using several neuropsychological tests, including the Stroop Color-Word Test, the Wisconsin Card Sorting Test, and the N-back Test, which assessed the components of Inhibition, Shifting, and Updating, respectively. Multivariate analysis of covariance revealed a significant difference between the groups in EF components (p < 0.001). Pairwise comparisons further showed that inpatient and outpatient patients had more depressive symptoms and worse EF performance than subclinical and healthy control groups (p < 0.05).

Results

In the analysis of EF measures, a significant difference was found among the four groups, with post-hoc tests revealing variations in specific EF components. Overall, patients with more severe depressive symptoms show more deficits in EF. Additionally, correlations between clinical characteristics and EF measures varied across patient groups, but many correlations became non-significant after adjusting for the false discovery rate (FDR).

Discussion

This study emphasizes the impact of depression severity on deficits in the EF of depressed patients and at-risk populations. Consequently, it is important to consider executive dysfunctions as an underlying vulnerability in the development and persistence of depressive disorder.

Analysis of Automated Clinical Depression Diagnosis in a Chinese Corpus

Depression clinical interview corpora are essential for advancing automated depression diagnosis. While previous studies have used written speech material in controlled settings, these materials do not accurately represent spontaneous conversational speech. Additionally, self-reported measures of depression are subject to bias, making the data unreliable for training models for real-world scenarios. This study introduces a new corpus of depression clinical interviews collected directly from a psychiatric hospital, containing 113 recordings with 52 healthy and 61 depressive patients. The subjects were examined using the Montgomery-Asberg Depression Rating Scale (MADRS) in Chinese. Their final diagnosis was based on medical evaluations through a clinical interview conducted by a psychiatry specialist. All interviews were audio-recorded and transcribed verbatim, and annotated by experienced physicians. This dataset is a valuable resource for automated depression detection research and is expected to advance the field of psychology. Baseline models for detecting and predicting depression presence and level were built, and descriptive statistics of audio and text features were calculated. The decision-making process of the model was also investigated and illustrated. To the best of our knowledge, this is the first study to collect a depression clinical interview corpus in Chinese and train machine learning models to diagnose depression patients.

Brain-based Sex Differences in Depression: A Systematic Review of Neuroimaging Studies

Major depressive disorder (MDD) is a common psychiatric illness with a wide range of symptoms such as mood decline, loss of interest, and feelings of guilt and worthlessness. Women develop depression more often than men, and the diagnostic criteria for depression mainly rely on female patients' symptoms. By contrast, male depression usually manifests as anger attacks, aggression, substance use, and risk-taking behaviors. Various studies have focused on the neuroimaging findings in psychiatric disorders for a better understanding of their underlying mechanisms. With this review, we aimed to summarize the existing literature on the neuroimaging findings in depression, separated by male and female subjects. A search was conducted on PubMed and Scopus for magnetic resonance imaging (MRI), functional MRI (fMRI), and diffusion tensor imaging (DTI) studies of depression. After screening the search results, 15 MRI, 12 fMRI, and 4 DTI studies were included. Sex differences were mainly reflected in the following regions: 1) total brain, hippocampus, amygdala, habenula, anterior cingulate cortex, and corpus callosum volumes, 2) frontal and temporal gyri functions, along with functions of the caudate nucleus and prefrontal cortex, and 3) frontal fasciculi and frontal projections of corpus callosum microstructural alterations. Our review faces limitations such as small sample sizes and heterogeneity in populations and modalities. But in conclusion, it reflects the possible roles of sex-based hormonal and social factors in the depression pathophysiology.

Neural association between cognitive function and anhedonia in adolescents with melancholic major depressive disorder: A fNIRS study

BACKGROUND

Cognitive dysfunction is common among adolescent patients with major depressive disorder (MDD). However, the pattern and magnitude of cognition impairment in patients during melancholic episodes remains unclear. The purpose of this study was to compare the neurocognitive performance and the underlying cerebral blood flow activation of adolescent patients with melancholic and non-melancholic features.

METHODS

Fifty-seven and 44 adolescent patients with MDD with or without melancholic feature (MDD-MEL/nMEL) and 58 healthy controls (HCs) were recruited. We used the repeatable battery for the assessment of neuropsychological status (RBANS) measuring neurocognitive function, and used functional near infrared spectroscopy (fNIRS) monitoring cerebral hemodynamic changes, described by β value. The non-parametric test and post-hoc analysis were conducted in RBANS scores and β values among three groups. Spearman correlation and mediating analysis was performed for RBANS scores, β values, and clinical symptoms in the MDD-MEL group.

RESULTS

There were no significant difference in RBANS scores between MDD-MEL and MDD-nMEL group. Compared with patients in MDD-nMEL, patients in MDD-MEL have lower β values in eight channels (ch10, ch16, ch20, ch25, ch27, ch37, ch41, ch45). The cognitive function is significantly correlated with anhedonia, and the β values play a partial mediating role between anhedonia and cognitive function.

LIMITATION

It's a cross-sectional study and monitoring longitudinal effects are needed to further elucidate the mechanism.

CONCLUSION

The cognitive function in adolescents with MDD-MEL may not significantly differ from those with MDD-nMEL. However, the anhedonia may influenced the cognitive function by altering the function of medial frontal cortex.

Network Analysis of Depression Using Magnetoencephalogram Based on Polynomial Kernel Granger Causality

Depression is a psychiatric disorder characterized by anxiety, pessimism, and suicidal tendencies, which has serious impact on human's life. In this paper, we use Granger causality index based on polynomial kernel as network node connectivity coefficient to construct brain networks from the magnetoencephalogram (MEG) of 5 depressed patients and 11 healthy individuals under positive, neutral, and negative emotional stimuli, respectively. We found that depressed patients had more information exchange between the frontal and occipital regions compared to healthy individuals and less causal connections in the parietal and central regions. We further analyzed the topological properties of the network revealed and found that depressed patients had higher average degrees under negative stimuli (p = 0.008) and lower average clustering coefficients than healthy individuals (p = 0.034). When comparing the average degree and average clustering coefficient of the same sample under different emotional stimuli, we found that depressed patients had a higher average degree and average clustering coefficient under negative stimuli than neutral and positive stimuli. We also found that the characteristic path lengths of patients under negative and neutral stimuli significantly deviated from small-world network. Our results suggest that the analysis of polynomial kernel Granger causality brain networks can effectively characterize the pathology of depression.

Roles of Nrf2/HO-1 and ICAM-1 in the Protective Effect of Nano-Curcumin against Copper-Induced Lung Injury

Copper (Cu) is an essential trace element for maintaining normal homeostasis in living organisms. Yet, an elevated level of Cu beyond homeostatic capacity may lead to oxidative damage of cellular components in several organs, including the lungs. This work investigated the effects of curcumin (Curc) and nano-curcumin (nCurc) against Cu-induced lung injury, accenting the roles of oxidative stress, inflammation, and the nuclear factor erythroid 2-related factor/heme oxygenase-1 Nrf2/HO-1 pathway. Rats were challenged with 100 mg/kg of copper sulfate (CuSO4) while being treated with Curc or nCurc for 7 days. Cu-triggered lung oxidative stress detected as dysregulation of oxidative/antioxidant markers, a downregulation of Nrf-2/HO-1 signaling, and an increase in the inflammatory markers interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), and intracellular adhesion molecule-1 (ICAM-1). Additionally, it decreased the expression of lung-specific proteins, surfactant protein-C (SP-C), and mucin-1 (MUC-1), induced apoptosis, and caused changes in lung histology. Curc and nCurc alleviated CuSO4-induced lung injury by suppressing oxidative damage and inflammation and activating Nrf-2/HO-1. They also prevented apoptosis and restored the normal expression of SP-C and MUC-1. We concluded that nCurc exhibited superior efficacy compared with Curc in mitigating CuSO4-induced lung injury. This was associated with reduced oxidative stress, inflammation, and apoptotic responses and increased Nrf2/HO-1 signaling and expression of SP-C and MUC-1.

Differences in White Matter Structural Networks in Family Risk of Major Depressive Disorder and Suicidality: A Connectome Analysis

Background

Depression and suicide are leading global causes of disability and death and are highly familial. Family and individual history of depression are associated with neurobiological differences including decreased white matter connectivity; however, this has only been shown for individual regions. We use graph theory models to account for the network structure of the brain with high levels of specialization and integration and examine whether they differ by family history of depression or of suicidality within a three-generation longitudinal family study with well-characterized clinical histories.

Methods

Clinician interviews across three generations were used to classify family risk of depression and suicidality. Then, we created weighted network models using 108 cortical and subcortical regions of interest for 96 individuals using diffusion tensor imaging derived fiber tracts. Global and local summary measures (clustering coefficient, characteristic path length, and global and local efficiencies) and network-based statistics were utilized for group comparison of family history of depression and, separately, of suicidality, adjusted for personal psychopathology.

Results

Clustering coefficient (connectivity between neighboring regions) was lower in individuals at high family risk of depression and was associated with concurrent clinical symptoms. Network-based statistics showed hypoconnected subnetworks in individuals with high family risk of depression and of suicidality, after controlling for personal psychopathology. These subnetworks highlighted cortical-subcortical connections including between the superior frontal cortex, thalamus, precuneus, and putamen.

Conclusions

Family history of depression and of suicidality are associated with hypoconnectivity between subcortical and cortical regions, suggesting brain-wide impaired information processing, even in those personally unaffected.

Integrative bioinformatics and artificial intelligence analyses of transcriptomics data identified genes associated with major depressive disorders including NRG1

Major depressive disorder (MDD) is a common mental disorder and is amongst the most prevalent psychiatric disorders. MDD remains challenging to diagnose and predict its onset due to its heterogeneous phenotype and complex etiology. Hence, early detection using diagnostic biomarkers is critical for rapid intervention. In this study, a mixture of AI and bioinformatics were used to mine transcriptomic data from publicly available datasets including 170 MDD patients and 121 healthy controls. Bioinformatics analysis using gene set enrichment analysis (GSEA) and machine learning (ML) algorithms were applied. The GSEA revealed that differentially expressed genes in MDD patients are mainly enriched in pathways related to immune response, inflammatory response, neurodegeneration pathways and cerebellar atrophy pathways. Feature selection methods and ML provided predicted models based on MDD-altered genes with ≥75% of accuracy. The integrative analysis between the bioinformatics and ML approaches identified ten key MDD-related biomarkers including NRG1, CEACAM8, CLEC12B, DEFA4, HP, LCN2, OLFM4, SERPING1, TCN1 and THBS1. Among them, NRG1, active in synaptic plasticity and neurotransmission, was the most robust and reliable to distinguish between MDD patients and healthy controls amongst independent external datasets consisting of a mixture of populations. Further evaluation using saliva samples from an independent cohort of MDD and healthy individuals confirmed the upregulation of NRG1 in patients with MDD compared to healthy controls. Functional mapping to the human brain regions showed NRG1 to have high expression in the main subcortical limbic brain regions implicated in depression. In conclusion, integrative bioinformatics and ML approaches identified putative non-invasive diagnostic MDD-related biomarkers panel for the onset of depression.

Low myelin-related values in the fornix and thalamus of 7 Tesla MRI of major depressive disorder patients

Introduction

Abnormalities in myelin are believed to be one of the important causes of major depressive disorder, and it is becoming important to more accurately quantify myelin in in vivo magnetic resonance imaging of major depressive disorder patients. We aimed to investigate the difference in myelin concentration in the white matter and subcortical areas using new quantitative myelin-related maps of high-resolution 7 Tesla (7 T) magnetic resonance imaging between patients with major depressive disorder and healthy controls.

Methods

Myelin-related comparisons of the white matter and nearby subcortical regions were conducted between healthy controls (n = 36) and patients with major depressive disorder (n = 34). Smoothed quantitative ratio (sq-Ratio) myelin-related maps were created using the multi-echo magnetization-prepared two rapid gradient echoes (ME-MP2RAGE) sequence of the T1 and T2* images of 7 T magnetic resonance imaging. Differences in the myelin-related values of the regions of interest between the two groups were analyzed using a two-sample t-test, and multiple comparison corrections were performed using the false discovery rate.

Results

The average sq-Ratio myelin-related values were 2.62% higher in the white matter and 2.26% higher in the subcortical regions of the healthy controls group than in the major depressive disorder group. In the group analysis of the healthy control and major depressive disorder groups, the sq-Ratio myelin-related values were significantly different in the fornix area of the white matter (false discovery rate-corrected p = 0.012). In addition, significant differences were observed in both the left (false discovery rate-corrected p = 0.04) and right thalamus (false discovery rate-corrected p = 0.040) among the subcortical regions.

Discussion

The average sq-ratio myelin-related value and sq-ratio myelin-related values in the fornix of the white matter and both thalami were higher in the healthy controls group than in the major depressive disorder group. We look forward to replicating our findings in other populations using larger sample sizes.

Interventional Mental Health: A Transdisciplinary Approach to Novel Psychiatric Care Delivery

Mental health disorders are among the most common health conditions in the United States. Traditional clinical treatments rely on psychiatric counseling and, in many cases, prescription medications. We propose an innovative model, Interventional Mental Health, which employs a combination of modalities through a multifaceted approach to treat conditions that have exhibited limited responsiveness to traditional methods and individuals afflicted with multiple comorbidities simultaneously. We hypothesize that creating a unique treatment algorithm combining current therapeutic modalities such as Stellate Ganglion Blocks (SGB), Transcranial Magnetic Stimulation (TMS) therapy, and ketamine therapy, within a consolidated timeframe, will yield synergistic outcomes among patients presenting with comorbid post-traumatic stress disorder (PTSD), depression, and/or anxiety.

Recent advances in the study of sepsis-induced depression

Progress in medicine such as the use of anti-infective drugs and development of the advanced life support equipment has greatly improved the survival rate of patients with sepsis. However, the incidence of sepsis-related diseases is increasing. These include severe neurologic and psychologic disorders, cognitive decline, anxiety, depression, and post-traumatic stress disorder. Cerebral dysfunction occurs via multiple interacting mechanisms, with different causative pathogens having distinct effects. Because sepsis-related diseases place a substantial burden on patients and their families, it is important to elucidate the underlying pathophysiologic mechanisms to develop effective treatments.

Serum alkaline phosphatase was independently associated with depression in patients with cerebrovascular disease

BACKGROUND AND PURPOSE

Blood markers have important value in the diagnosis of depressive disorders. Serum alkaline phosphatase (ALP) not only predicts stroke recurrence and poor functional prognosis in cerebrovascular disease (CVD) patients but also increases significantly in middle-aged women with depression. Thus, it has not been reported whether serum ALP is associated with the development of depression and/or vascular depression (VDe) in CVD patients.

METHODS

This was a cross-sectional study of 353 CVD patients (stroke patients, n = 291; cerebral small vessel disease (CSVD) patients, n = 62). Baseline demographic information, fasting blood markers (such as blood counts, liver function, kidney function and lipids), and brain CT/MRI scans were collected. CVD patients were divided into non-depression, suspected vascular depression (SVD), and positive vascular depression (PVD) groups according to their Hamilton Rating Scale for Depression (HAMD) scores. Univariate analysis of baseline data, blood markers, and the prevalence of lesions (> 1.5 cm) was performed. Subsequently, the diagnostic performance of the univariate and combined variables for SVD and PVD was analyzed using binary logistic regression. The diagnostic value of the multivariate model for VDe was analyzed by ordinal logistic regression.

RESULTS

(1) Serum ALP (p = 0.003) and hypersensitive C-reactive protein (hs-CRP, p = 0.001) concentrations increased as HAMD scores increased, and the prevalence of brain atrophy (p = 0.016) and lesions in the basal ganglia (p = 0.001) and parietal (p = 0.001), temporal (p = 0.002), and frontal lobes (p = 0.003) also increased, whereas the concentrations of hemoglobin (Hb, p = 0.003), cholinesterase (ChE, p = 0.001), and high-density lipoprotein cholesterol (HDL-C, p = 0.005) declined. Among these variables, hs-CRP (r = 0.218, p < 0.001) had a weak positively association with HAMD scores, and ChE (r = -0.226, p < 0.001) had a weak negative association. (2) The combination of Hb, hs-CRP, ChE, ALP, and HDL-C improved diagnostic performance for VDe [AUC = 0.775, 95% CI (0.706, 0.844), p < 0.001]. (3) Hb (OR = 0.986, p = 0.049), ChE (OR = 0.999, p = 0.020), ALP (OR = 1.017, p = 0.003), and basal ganglia lesions (OR = 2.197, p < 0.001) were important factors impacting VDe development. After adjusting for Hb, hs-CRP, ChE, HDL-C, lesions in the above mentioned four locations, sex, age and the prevalence of CSVD and brain atrophy, ALP [OR = 1.016, 95% CI (1.005, 1.027), p = 0.004] was independently associated with VDe.

CONCLUSION

Hb, hs-CRP, ChE, ALP, and HDL-C concentrations are potential blood markers of depression in CVD patients and, when combined, may improve diagnostic performance for VDe. Serum ALP was independently associated with VDe in patients with CVD.

Exercise for Mental Well-Being: Exploring Neurobiological Advances and Intervention Effects in Depression

Depression is a common mental disorder in which patients often experience feelings of sadness, fatigue, loss of interest, and pleasure. Exercise is a widely used intervention for managing depression, but the specific molecular mechanisms underlying its antidepressant effect are unclear. In this narrative review, we aim to synthesize current knowledge on the molecular, neural, and physiological mechanisms through which exercise exerts its antidepressant effect and discuss the various exercise interventions used for managing depression. We conducted a narrative review of the literature on the topic of exercise and depression. Our review suggests that exercise impacts peripheral tryptophan metabolism, central inflammation, and brain-derived neurotrophic factors through the peroxisome proliferator-activated receptor γ activating factor 1α (PGC-1α) in skeletal muscles. The uncarboxylated osteocalcin facilitates "bone-brain crosstalk", and exercise corrects atypical expression of brain-gut peptides, modulates cytokine production and neurotransmitter release, and regulates inflammatory pathways and microRNA expression. Aerobic exercise is recommended at frequencies of 3 to 5 times per week with medium to high intensity. Here we highlight the significant potential of exercise therapy in managing depression, supported by the molecular, neural, and physiological mechanisms underlying its antidepressant effect. Understanding the molecular pathways and neural mechanisms involved in exercise's antidepressant effect opens new avenues for developing novel therapies for managing depression.

Associations of neuroimaging markers with depressive symptoms over time in middle-aged and elderly persons

BACKGROUND

Cerebrovascular disease is regarded as a potential cause of late-life depression. Yet, evidence for associations of neuroimaging markers of vascular brain disease with depressive symptoms is inconclusive. We examined the associations of neuroimaging markers and depressive symptoms in a large population-based study of middle-aged and elderly persons over time.

METHODS

A total of 4943 participants (mean age = 64.6 ± 11.1 years, 55.7% women) from the Rotterdam Study were included. At baseline, total brain volume, gray matter volume, white matter volume, white matter hyperintensities volume, cortical infarcts, lacunar infarcts, microbleeds, white matter fractional anisotropy, and mean diffusivity (MD) were measured with a brain MRI (1.5T). Depressive symptoms were assessed twice with the Center for Epidemiologic Studies Depression scale (median follow-up time: 5.5 years, IQR = 0.9). To assess temporal associations of neuroimaging markers and depressive symptoms, linear mixed models were used.

RESULTS

A smaller total brain volume (β = -0.107, 95% CI -0.192 to -0.022), larger white matter hyperintensities volume (β = 0.047, 95% CI 0.010-0.084), presence of cortical infarcts (β = 0.194, 95% CI 0.047-0.341), and higher MD levels (β = 0.060, 95% CI 0.022-0.098) were cross-sectionally associated with more depressive symptoms. Longitudinal analyses showed that small total brain volume (β = -0.091, 95% CI -0.167 to -0.015) and presence of cortical infarcts (β = 0.168, 95% CI 0.022-0.314) were associated with increasing depressive symptoms over time. After stratification on age, effect sizes were more pronounced at older ages.

CONCLUSIONS

Neuroimaging markers of white matter microstructural damage were associated with depressive symptoms longitudinally in this study of middle-aged and elderly persons. These associations were more pronounced at older ages, providing evidence for the role of white matter structure in late-life depressive symptomatology.

Abnormal voxel-wise whole-brain functional connectivity in first-episode, drug-naïve adolescents with major depression disorder

Major depression disorder (MDD) is one of the most common psychiatric disorders. Previous studies have demonstrated structural and functional abnormalities in adult depression. However, the neurobiology of adolescent depression has not been fully understood. The aim of this study was to investigate the intrinsic dysconnectivity pattern of voxel-level whole-brain functional networks in first-episode, drug-naïve adolescents with MDD. Resting-state functional magnetic resonance imaging data were acquired from 66 depressed adolescents and 47 matched healthy controls. Voxel-wise degree centrality (DC) analysis was performed to identify voxels that showed altered whole-brain functional connectivity (FC) with other voxels. We further conducted seed-based FC analysis to investigate in more detail the connectivity patterns of the identified DC changes. The relationship between altered DC and clinical variables in depressed adolescents was also analyzed. Compared with controls, depressed adolescents showed lower DC in the bilateral hippocampus, left superior temporal gyrus and right insula. Seed-based analysis revealed that depressed adolescents, relative to controls, showed hypoconnectivity between the hippocampus to the medial prefrontal regions and right precuneus. Furthermore, the DC values in the bilateral hippocampus were correlated with the Hamilton Depression Rating Scale score and duration of disease (all P < 0.05, false discovery rate corrected). Our study indicates abnormal intrinsic dysconnectivity patterns of whole-brain functional networks in drug-naïve, first-episode adolescents with MDD, and abnormal DC in the hippocampus may affect the association of prefrontal-hippocampus circuit. These findings may provide new insights into the pathophysiology of adolescent-onset MDD.

Prediction of early improvement of major depressive disorder to antidepressant medication in adolescents with radiomics analysis after ComBat harmonization based on multiscale structural MRI

BACKGROUND

Due to individual differences and lack of objective biomarkers, only 30-40% patients with major depressive disorder (MDD) achieve remission after initial antidepressant medication (ADM). We aimed to employ radiomics analysis after ComBat harmonization to predict early improvement to ADM in adolescents with MDD by using brain multiscale structural MRI (sMRI) and identify the radiomics features with high prediction power for selection of selective serotonin reuptake inhibitors (SSRIs) and serotonin norepinephrine reuptake inhibitors (SNRIs).

METHODS

121 MDD patients were recruited for brain sMRI, including three-dimensional T1 weighted imaging (3D-T₁WI)and diffusion tensor imaging (DTI). After receiving SSRIs or SNRIs for 2 weeks, the subjects were divided into ADM improvers (SSRIs improvers and SNRIs improvers) and non-improvers according to reduction rate of the Hamilton Depression Rating Scale, 17 item (HAM-D₁₇) score. Then, sMRI data were preprocessed, and conventional imaging indicators and radiomics features of gray matter (GM) based on surface-based morphology (SBM) and voxel-based morphology (VBM) and diffusion properties of white matter (WM) were extracted and harmonized with ComBat harmonization. Two-level reduction strategy with analysis of variance (ANOVA) and recursive feature elimination (RFE) was utilized sequentially to decrease high-dimensional features. Support vector machine with radial basis function kernel (RBF-SVM) was used to integrate multiscale sMRI features to construct models for early improvement prediction. Area under the curve (AUC), accuracy, sensitivity, and specificity based on the leave-one-out cross-validation (LOO-CV) and receiver operating characteristic (ROC) curve analysis were calculated to evaluate the model performance. Permutation tests were used for assessing the generalization rate.

RESULTS

After 2-week ADM, 121 patients were divided into 67 ADM improvers (31 SSRIs improvers and 36 SNRIs improvers) and 54 ADM non-improvers. After two-level dimensionality reduction, 8 conventional indicators (2 VBM-based features and 6 diffusion features) and 49 radiomics features (16 VBM-based features and 33 diffusion features) were selected. The overall accuracy of RBF-SVM models based on conventional indicators and radiomics features was 74.80% and 88.19%. The radiomics model achieved the AUC, sensitivity, specificity, and accuracy of 0.889, 91.2%, 80.1% and 85.1%, 0.954, 89.2%, 87.4% and 88.5%, 0.942, 91.9%, 82.5% and 86.8% for predicting ADM improvers, SSRIs improvers and SNRIs improvers, respectively. P value of permutation tests were less than 0.001. The radiomics features predicting ADM improver were mainly located in the hippocampus, medial orbitofrontal gyrus, anterior cingulate gyrus, cerebellum (lobule vii-b), body of corpus callosum, etc. The radiomics features predicting SSRIs improver were primarily distributed in hippocampus, amygdala, inferior temporal gyrus, thalamus, cerebellum (lobule vi), fornix, cerebellar peduncle, etc. The radiomics features predicting SNRIs improver were primarily located in the medial orbitofrontal cortex, anterior cingulate gyrus, ventral striatum, corpus callosum, etc. CONCLUSIONS: These findings suggest the radiomics analysis based on brain multiscale sMRI after ComBat harmonization could effectively predict the early improvement of ADM in adolescent MDD patients with a high accuracy, which was superior to the model based on the conventional indicators. The radiomics features with high prediction power may help for the individual selection of SSRIs and SNRIs.

Malnutrition, Depression, Poor Sleep Quality, and Difficulty Falling Asleep at Night Are Associated with a Higher Risk of Cognitive Frailty in Older Adults during the COVID-19 Restrictions

The COVID-19 restrictions, such as social isolation and disruption of daily routines, can have detrimental effects, including increased stress, anxiety, sleep disturbance, and physical and cognitive decline among older adults. This study aimed to examine the association between nutritional status, depression, sleep quality, falling asleep at night, and cognitive frailty (CF) among older Thai adults during the COVID-19 pandemic. This cross-sectional study included 408 older adults with an average age of 70.54 (5.49) years. CF was determined using Fried's frailty phenotype and the Montreal Cognitive Assessment Basic. The Mini Nutritional Assessment-Short Form, Pittsburgh Sleep Quality Index, and geriatric depression assessment were used for assessment. Multiple logistic regression analysis demonstrated that participants who were malnourished (OR 3.786; 95%CI 1.719-8.335), depressed (OR 5.003; 95%CI 2.399-10.434), had poor sleep quality (OR 1.613; 95%CI 1.041-2.500), and engaged in difficulty falling asleep (OR 1.809; 95%CI 1.022-3.203) had a higher risk of CF compared to those who did not exhibit these factors. Therefore, malnutrition, depression, poor sleep quality, and difficulty falling asleep were identified as risk factors for CF among older adults in Thailand linked to the impact of the COVID-19 pandemic. It is crucial to develop interventions to prevent CF resulting from the mentioned variables.