Changes In Major Depressive Disorder Research Articles

Common neural deficits across reward functions in major depression: a meta-analysis of fMRI studies.

Major depressive disorder (MDD) is characterized by deficient reward functions in the brain. However, existing findings on functional alterations during reward anticipation, reward processing, and learning among MDD patients are inconsistent, and it was unclear whether a common reward system implicated in multiple reward functions is altered in MDD. Here we meta-analyzed 18 past studies that compared brain reward functions between adult MDD patients (N = 477, mean age = 26.50 years, female = 59.40%) and healthy controls (N = 506, mean age = 28.11 years, females = 55.58%), and particularly examined group differences across multiple reward functions. Jack-knife sensitivity and subgroup meta-analyses were conducted to test robustness of findings across patient comorbidity, task paradigm, and reward nature. Meta-regression analyses assessed the moderating effect of patient symptom severity and anhedonia scores. We found during reward anticipation, MDD patients showed lower activities in the lateral prefrontal-thalamus circuitry. During reward processing, patients displayed reduced activities in the right striatum and prefrontal cortex, but increased activities in the left temporal cortex. During reward learning, patients showed reduced activity in the lateral prefrontal-thalamic-striatal circuitry and the right parahippocampal-occipital circuitry but higher activities in bilateral cerebellum and the left visual cortex. MDD patients showed decreased activity in the right thalamus during both reward anticipation and learning, and in the right caudate during both reward processing and learning. Larger functional changes in MDD were observed among patients with more severe symptoms and higher anhedonia levels. The thalamic-striatal circuitry functional alterations could be the key neural mechanism underlying MDD patients overarching reward function deficiencies.

Integrated analysis of transcriptional changes in major depressive disorder: Insights from blood and anterior cingulate cortex

BackgroundMajor depressive disorder (MDD) was involved in widely transcriptional changes in central and peripheral tissues. While, previous studies focused on single tissues, making it difficult to represent systemic molecular changes throughout the body. Thus, there is an urgent need to explore the central and peripheral biomarkers with intrinsic correlation. MethodsWe systematically retrieved gene expression profiles of blood and anterior cingulate cortex (ACC). 3 blood datatsets (84 MDD and 88 controls) and 6 ACC datasets (100 MDD and 100 controls) were obtained. Differential expression analysis, RobustRankAggreg (RRA) analysis, functional enrichment analysis, immune associated analysis and protein-protein interaction networks (PPI) were integrated. Furthermore, the key genes were validated in an independent ACC dataset (12 MDD and 15 controls) and a cohort with 120 MDD and 117 controls. ResultsDifferential expression analysis identified 2211 and 2021 differential expressed genes (DEGs) in blood and ACC, respectively. RRA identified 45 and 25 robust DEGs in blood and ACC based on DEGs, and all of them were closely associated with immune cells. Functional enrichment results showed both the robust DEGs in blood and ACC were enriched in humoral immune response. Furthermore, PPI identified 8 hub DEGs (CD79A, CD79B, CD19, MS4A1, PLP1, CLDN11, MOG, MAG) in blood and ACC. Independent ACC dataset showed the area under the curve (AUC) based on these hub DEGs was 0.77. Meanwhile, these hub DEGs were validated in the serum of MDD patients, and also showed a promising diagnostic power. ConclusionsThe biomarker panel based on hub DEGs yield a promising diagnostic efficacy, and all of these hub DEGs were strongly correlated with immunity. Humoral immune response may be the key link between the brain and blood in MDD, and our results may provide further understanding for MDD.

Linking inter-subject variability of cerebellar functional connectome to clinical symptoms in major depressive disorder

Major depressive disorder (MDD) is a highly prevalent psychiatric disorder with remarkable inter-subject variability in clinical manifestations. Neuroimaging changes of the cerebellum have been recently proposed as a way to characterize MDD-related brain disruptions and might further explain various clinical symptoms. However, the cerebellar contributions to MDD clinical heterogeneity remain largely unknown.The analyzed data consisted of 251 MDD patients and 235 matching healthy controls (HC). The inter-subject variability of functional connectomes (IVFC) was estimated via Pearson's correlation analysis between each pair of the cerebellar and cerebral regions based on resting-state functional magnetic resonance imaging (rs-fMRI). A partial least squares (PLS) regression analysis was performed to determine the potential dimension linking the IVFC to clinical symptom measures.The results indicated that similar spatial distribution patterns of the cerebellar IVFC were observed between MDD and HC, but the MDD group exhibited abnormal IVFC alterations in the bilateral Cerebelum_4_5, bilateral Cerebelum_6, Vermis_1_2 and Vermis_8. The PLS model revealed that the IVFC pattern in the left Cerebelum_6 was significantly associated with three HAMD-17 items including the work and activities, psychomotor retardation, and depressed mood. These findings provided new evidence for the cerebellar changes in MDD. Specifically, we found that the altered inter-subject variability measurements correlated with clinical manifestations of this illness. Elucidating this variability could prove helpful for the evaluation of MDD heterogeneity as well as for understanding its pathophysiological mechanism.

Alterations in gut microbiota caused by major depressive disorder or a low FODMAP diet and where they overlap.

Beneficial changes in microbiota observed in individuals with a major depressive disorder (MDD) may be initiated with a low fermentable oligosaccharide, disaccharide, monosaccharide, and polyol (FODMAP) elimination diet. Academic Search Ultimate, APA PsychINFO, Cochrane Library, MEDLINE, Scopus and Web of Science were searched for original research documenting differences in microbiota in MDD or changes with a low FODMAP diet in adults (age 18 years +). Studies with fecal microbiota, 16 s RNA sequencing and QIIME pipelines were included. Studies using antibiotics, probiotics, and medications such as antidepressants were excluded. Additionally, studies based on a single gender were excluded as gender impacts microbiota changes in MDD. Four studies addressed differences in microbiota with MDD and another four assessed shifts occurring with a low FODMAP diet. The abundance of Bacteroidetes, Bacteroidaceae and Bacteroides were lower in individuals with MDD but increased with a low FODMAP diet. Abundance of Ruminoccaceae was lower and Bilophila was higher with both a low FODMAP diet and MDD. These results provide preliminary evidence that a low FODMAP diet might drive changes in microbiota that also benefit people with MDD. Further research to assess whether a low FODMAP diet can treat MDD through modification of targeted microbiota is warranted.

Negative association between DNA methylation in brain-derived neurotrophic factor exon VI and left superior parietal gyrification in major depressive disorder

ObjectiveWe have recently reported significantly higher DNA methylation in brain-derived neurotrophic factor (BDNF) exon VI in major depressive disorder (MDD). This study aimed to investigated cortical changes and their associations with DNA methylations in BDNF exon VI in MDD. MethodsData of 93 patients with MDD and 59 controls were involved in statistics. General linear regressions (GLM) were performed to analyze thickness and gyrification changes in MDD and their association with DNA methylation in BDNF exon VI in patients with MDD and controls. ResultsSignificantly decreased cortical thickness (CT) in left lateral orbitofrontal cortex (LOFC), left superior temporal lobe (ST) and right frontal pole (FP) and decreased local gyrification index (lGI) in left superior parietal lobe (SP) were found in MDD. The associations between DNA methylation in 3 CpG sites in BDNF exon VI and lGI in left SP were significantly different in patients and controls. DNA methylations in BDNF132 (β = –0.359, P < 0.001), BDNF137 (β = –0.214, P = 0.032), and BDNF151 (β = –0.223, P = 0.025) were significantly negatively associated with lGI in left SP in MDD. ConclusionThe negative association between BDNF exon VI methylation and lGI in left SP might imply a potential epigenetic marker associated with cortical gyrification reduction in patients with MDD.

Dysbiosis of the Gut Microbiota and Kynurenine (Kyn) Pathway Activity as Potential Biomarkers in Patients with Major Depressive Disorder

With increasing attention paid to the concept of the microbiota-gut-brain axis, mounting evidence reveals that the gut microbiota is involved in a variety of neurological and psychiatric diseases. However, gut microbiota changes in major depressive disorder (MDD) patients and their association with disease mechanisms remain undefined. Fifty MDD patients and sixty healthy controls were recruited from the Shanghai Healthy Mental Center, China. Fecal samples were collected, and the compositional characteristics of the intestinal flora were determined in MDD patients by MiSeq sequencing. Venous blood was collected for the detection of plasma indoleamine-2,3-dioxygenase (Ido), kynurenine (Kyn) and tryptophan (Trp) levels. Stool samples of bacterial 16S sequencing was carried out. A total of 2,705,809 optimized sequences were obtained, with an average of 54,116 per sample. More unique OTUs were observed at the family, genus and species levels in the control group compared with the MDD cases. Further analysis showed significant changes in the α- and β-diversities and relative abundance levels of gut microbial entities in MDD patients, as well as elevated amounts of Ido and Kyn indicating Kyn pathway activation, KEGG bacterial 16S function prediction analysis shows a variety of amino acids and metabolic (including Ido, Trp and Kyn) changes in the body of patients with MDD. These may result in increased neurotoxic metabolites and reduced generation of serotonin in the disease process. These changed factors may potentially be utilized as biomarkers for MDD in the future, playing more important roles in the disease course.

What factors explain the changes in major depressive disorder symptoms by age group during the COVID-19 pandemic? A longitudinal study

BackgroundData collected during the COVID-19 pandemic suggest an increase in major depressive disorder (MDD) among younger adults. The current study aims to assess the association of age groups and MDD risk before and during the COVID-19 pandemic and quantify the effect of potential mediating variables such as loneliness, social support, resilience, and socioeconomic factors. MethodsA representative sample of Spanish adults was interviewed before (2019, N = 1880) and during (2020, N = 1103) the COVID-19 pandemic. MDD was assessed using the CIDI, loneliness through the UCLA scale, social support through the OSSS-3, resilience with the 6-BRS, and worsened economic circumstances and unemployment through a single question. Mixed-models were used to study changes in MDD by age group. Regression models were constructed to quantify the association between age and potential mediators, as well as their mediating effect on the association between age group and MDD. ResultsAmong the younger age cohorts (18-29 and 30-44 years) the probability of having MDD during the pandemic increased from 0.04 (95 % CI: 0.002-0.09) to 0.25 (0.12-0.39) and from 0.02 (-0.001-0.03) to 0.11 (0.04-0.17), respectively. Some 36.6 % of the association between age and risk of MDD during the pandemic was explained by loneliness (12.0 %), low resilience (10.7 %), and worsened economic situation (13.9 %). LimitationsReliance on self-report data and generalizability of the findings limited to the Spanish population. ConclusionsStrategies to decrease the impact of a pandemic on depressive symptoms among young adults should address loneliness, provide tools to improve resilience, and enjoy improved financial support.

Diagnosis of Major Depressive Disorder Using Machine Learning Based on Multisequence MRI Neuroimaging Features.

Previous studies have found qualitative structural and functional brain changes in major depressive disorder (MDD) patients. However, most studies ignored the complementarity of multisequence MRI neuroimaging features and cannot determine accurate biomarkers. To evaluate machine-learning models combined with multisequence MRI neuroimaging features to diagnose patients with MDD. Prospective. A training cohort including 111 patients and 90 healthy controls (HCs) and a test cohort including 28 patients and 22 HCs. A 3.0 T/T1-weighted imaging, resting-state functional MRI with echo-planar sequence, and single-shot echo-planar diffusion tensor imaging. Recruitment and integration were used to reflect the dynamic changes of functional networks, while gray matter volume and fractional anisotropy were used to reflect the changes in the morphological and anatomical network. We then fused features with significant differences in functional, morphological, and anatomical networks to evaluate a random forest (RF) classifier to diagnose patients with MDD. Furthermore, a support vector machine (SVM) classifier was used to verify the stability of neuroimaging features. Linear regression analyses were conducted to investigate the relationships among multisequence neuroimaging features and the suicide risk of patients. The comparison of functional network attributes between patients and controls by two-sample t-test. Network-based statistical analysis was used to identify structural and anatomical connectivity changes between MDD and HCs. The performance of the model was evaluated by receiver operating characteristic (ROC) curves. The performance of the RF model integrating multisequence neuroimaging features in the diagnosis of depression was significantly improved, with an AUC of 93.6%. In addition, we found that multisequence neuroimaging features could accurately predict suicide risk in patients with MDD (r=0.691). The RF model fusing functional, morphological, and anatomical network features performed well in diagnosing patients with MDD and provided important insights into the pathological mechanisms of MDD. 1. Stage 2.

Gyrification patterns in first-episode, drug-naïve major depression: Associations with plasma levels of brain-derived neurotrophic factor and psychiatric symptoms.

Cortical structural changes in major depressive disorder (MDD) are usually studied using a voxel-based morphometry approach to delineate the cortical gray matter volume. Among cortical structures, gyrification patterns are considered a relatively stable indicator. In this study, we investigated differences in gyrification patterns between MDD patients and healthy controls (HCs) and explored the association of gyrification patterns with plasma brain-derived neurotrophic factor (BDNF) levels and depressive symptoms in MDD patients. We evaluated 79 MDD patients and 94 HCs and assessed depression severity in the patients using the 17-item Hamilton Depression Rating Scale (HAM-D). Blood samples of both groups were collected to measure plasma BDNF levels. Magnetic resonance imaging (MRI) data were obtained using three-dimensional fast-spoiled gradient-recalled acquisition. Differences in plasma BDNF levels between groups were examined using the Mann-Whitney U test. Principal component analysis and orthogonal partial least squares discriminant analysis (OPLS-DA) were conducted to investigate the gyrification patterns which were significantly different between the groups, i.e., those with variable importance in projection (VIP) scores of >1.5 and p-value < 0.05 in multiple regression analyses adjusted for age and sex. Finally, multiple regression analysis was performed on the selected gyrification patterns to examine their association with BDNF levels in the two groups and HAM-D in the patients. There were no significant differences in plasma BDNF levels between the groups. We found that 108 (71.0%) of 152 total local gyrification indices were MDD < HC. We identified 10 disease-differentiating factors based on critical gyrification features (VIP > 1.5 and p-value adjusted for age and sex < 0.05). However, we found no significant correlations between the 10 gyrification patterns and plasma BDNF levels and no interaction with group. Moreover, no significant correlations were observed between the local gyrification indices and HAM-D total scores. These results suggest that abnormal early cortical neurodevelopment may mediate vulnerability to MDD, independent of plasma BDNF levels and depressive symptoms.

Cerebral blood flow changes and their genetic mechanisms in major depressive disorder: a combined neuroimaging and transcriptome study.

Extensive research has shown abnormal cerebral blood flow (CBF) in patients with major depressive disorder (MDD) that is a heritable disease. The objective of this study was to investigate the genetic mechanisms of CBF abnormalities in MDD. To achieve a more thorough characterization of CBF changes in MDD, we performed a comprehensive neuroimaging meta-analysis of previous literature as well as examined group CBF differences in an independent sample of 133 MDD patients and 133 controls. In combination with the Allen Human Brain Atlas, transcriptome-neuroimaging spatial association analyses were conducted to identify genes whose expression correlated with CBF changes in MDD, followed by a set of gene functional feature analyses. We found increased CBF in the reward circuitry and default-mode network and decreased CBF in the visual system in MDD patients. Moreover, these CBF changes were spatially associated with expression of 1532 genes, which were enriched for important molecular functions, biological processes, and cellular components of the cerebral cortex as well as several common mental disorders. Concurrently, these genes were specifically expressed in the brain tissue, in immune cells and neurons, and during nearly all developmental stages. Regarding behavioral relevance, these genes were associated with domains involving emotion and sensation. In addition, these genes could construct a protein-protein interaction network supported by 60 putative hub genes with functional significance. Our findings suggest a cerebral perfusion redistribution in MDD, which may be a consequence of complex interactions of a wide range of genes with diverse functional features.

Breathomics profiling of metabolic pathways affected by major depression: Possibilities and limitations.

Major depressive disorder (MDD) is one of the most common psychiatric disorders with multifactorial etiologies. Metabolomics has recently emerged as a particularly potential quantitative tool that provides a multi-parametric signature specific to several mechanisms underlying the heterogeneous pathophysiology of MDD. The main purpose of the present study was to investigate possibilities and limitations of breath-based metabolomics, breathomics patterns to discriminate MDD patients from healthy controls (HCs) and identify the altered metabolic pathways in MDD. Breath samples were collected in Tedlar bags at awakening, 30 and 60 min after awakening from 26 patients with MDD and 25 HCs. The non-targeted breathomics analysis was carried out by proton transfer reaction mass spectrometry. The univariate analysis was first performed by T-test to rank potential biomarkers. The metabolomic pathway analysis and hierarchical clustering analysis (HCA) were performed to group the significant metabolites involved in the same metabolic pathways or networks. Moreover, a support vector machine (SVM) predictive model was built to identify the potential metabolites in the altered pathways and clusters. The accuracy of the SVM model was evaluated by receiver operating characteristics (ROC) analysis. A total of 23 differential exhaled breath metabolites were significantly altered in patients with MDD compared with HCs and mapped in five significant metabolic pathways including aminoacyl-tRNA biosynthesis (p = 0.0055), branched chain amino acids valine, leucine and isoleucine biosynthesis (p = 0.0060), glycolysis and gluconeogenesis (p = 0.0067), nicotinate and nicotinamide metabolism (p = 0.0213) and pyruvate metabolism (p = 0.0440). Moreover, the SVM predictive model showed that butylamine (p = 0.0005, pFDR=0.0006), 3-methylpyridine (p = 0.0002, pFDR = 0.0012), endogenous aliphatic ethanol isotope (p = 0.0073, pFDR = 0.0174), valeric acid (p = 0.005, pFDR = 0.0162) and isoprene (p = 0.038, pFDR = 0.045) were potential metabolites within identified clusters with HCA and altered pathways, and discriminated between patients with MDD and non-depressed ones with high sensitivity (0.88), specificity (0.96) and area under curve of ROC (0.96). According to the results of this study, the non-targeted breathomics analysis with high-throughput sensitive analytical technologies coupled to advanced computational tools approaches offer completely new insights into peripheral biochemical changes in MDD.

Hemodynamic analysis of the frontal cortex using multi-task fNIRS in major depressive disorder

BackgroundAppropriate task selection is the key to fNIRS-based major depressive disorder (MDD) diagnosis and treatment; however, there exists no unified rule for task selection, which limits its clinical application. MethodsFour tasks were employed to investigate the hemodynamic characteristics of MDD during motor, emotional, cognitive, and combinational tasks. A total of 69 subjects were studied: 50 with MDD and 19 healthy controls. The integral value of oxy-hemoglobin and the asymmetric characteristics of the bilateral frontal lobe were used to demonstrate the hemodynamic changes in MDD during different tasks. A detailed analysis and comparison among different tasks were conducted. ResultsCompared with deoxy-hemoglobin (deoxy-Hb), oxy-Hb was more significant to differentiate between MDD subjects and healthy controls. In subjects with MDD, lower activation of the frontal lobe and smaller integral values of oxy-Hb were observed. In most task paradigms, MDD subjects and healthy controls exhibited diametrically opposite left-right frontal asymmetry. For the integral value of oxy-Hb and the asymmetric characteristics of the bilateral frontal lobe, the differences between MDD subjects and healthy controls under the combinational task were more significant than that under the single tasks. LimitationsBrain fatigue patterns over time and their effect on the hemodynamic analysis of MDD should be studied further. ConclusionsThe difference in hemodynamic characteristics between MDD subjects and healthy controls is closely related to the choice of task, and the combinational task showed better discrimination than the single tasks. It provides guidance for the appropriate task design for MDD in clinics.

Altered spontaneous brain activity in major depressive disorder: An activation likelihood estimation meta-analysis

BackgroundWide application of resting-state functional magnetic resonance imaging (fMRI) in psychiatric research has revealed that major depressive disorder (MDD) manifest abnormal neural activities in several brain regions involving key resting state networks. However, inconsistent results have hampered our understanding of the exact neuropathology associated with MDD. Therefore, our aim was to conduct a meta-analysis to identify the consistent vulnerable brain regions of MDD in resting state, and to reveal the potential pathogenesis of MDD. MethodsA systematic review analysis was conducted on studies involving brain resting-state changes in MDD using low-frequency amplitude (ALFF), fractional low-frequency amplitude (fALFF) and regional homogeneity (ReHo) analysis. The meta-analysis was based on the activation likelihood estimation method, using the software of Ginger ALE 2.3. Results25 studies (892 MDD and 799 healthy controls) were included. Based on the meta-analysis results of ReHo, we found robust reduction of resting-state spontaneous brain activity in MDD, including the left cuneus and right middle occipital gyrus (cluster size = 216, 256 mm3, uncorrected P < 0.0001), while no increased spontaneous activation in any of the brain regions. We also found reduced ALFF in the left middle occipital gyrus (cluster size = 224 mm3, uncorrected P < 0.0001), and no increased spontaneous brain activation in any regions. ConclusionOur meta-analysis study using the activation likelihood estimation method demonstrated that MDD showed significant abnormalities in spontaneous neural activity, compared with healthy controls, mainly in areas associated with visual processing, such as the cuneus and the middle occipital gyrus. Dysfunction of these brain regions may be one of the pathogenesis of MDD.

Insular-associated causal network of structural covariance evaluating progressive gray matter changes in major depressive disorder.

Morphometric studies demonstrated wide-ranging distribution of brain structural abnormalities in major depressive disorder (MDD). This study explored the progressive gray matter volume (GMV) changes pattern of structural network in 108 MDD patients throughout the illness duration by using voxel-based morphometric analysis. The causal structural covariance network method was applied to map the causal effects of GMV alterations between the original source of structural changes and other brain regions as the illness duration prolonged in MDD. This was carried out by utilizing the Granger causality analysis to T1-weighted data ranked based on the disease progression information. With greater illness duration, the GMV reduction was originated from the right insula and progressed to the frontal lobe, and then expanded to the occipital lobe, temporal lobe, dorsal striatum (putamen and caudate) and the cerebellum. Importantly, results revealed that the right insula was the prominent node projecting positive causal influences (i.e., GMV decrease) to frontal lobe, temporal lobe, postcentral gyrus, putamen, and precuneus. While opposite causal effects were detected from the right insula to the angular, parahippocampus, supramarginal gyrus and cerebellum. This work may provide further information and vital evidence showing that MDD is associated with progressive brain structural alterations.

Aberrant pattern of cerebral blood flow in patients with major depressive disorder: A meta-analysis of arterial spin labelling studies

BackgroundAccumulating evidence has suggested that patients with major depressive disorder (MDD) could exhibit resting-state cerebral blood flow (CBF) abnormalities. However, findings across studies are controversial. MethodsOur study aimed at identifying replicable CBF changes in MDD by conducting a case-control meta-analysis and meta-regression of arterial spin labelling studies using seed-based d mapping software. Fourteen studies encompassing 505 patients with MDD and 443 healthy controls were included. ResultsWe found increased CBF in the inferior parietal lobule, the striatum, and the bilateral thalamus in all patients with MDD relative to healthy controls. While decreased CBF was observed in the inferior frontal gyrus, the insula, the middle occipital gyrus and the bilateral superior temporal gyrus in patients with MDD. Moreover, increased CBF of the bilateral thalamus was associated with more severe depressive symptoms in patients with MDD. The subgroup meta-analysis showed that patients with acute phase had increased CBF in the bilateral thalamus, and decreased CBF in the left middle occipital gyrus and the left middle frontal gyrus. Chronic patients had decreased CBF in the left insula, the right calcarine sulcus, the right inferior frontal gyrus, and the left parahippocampal gyrus. Patients with medication-free had increased CBF in the right anterior cingulate cortex/medial prefrontal cortex, and decreased CBF in the left middle occipital gyrus, the left inferior frontal gyrus, and the left precentral gyrus. ConclusionsThese findings suggest an aberrant cerebral blood flow pattern of MDD involving the cortico-striatal-thalamic circuit, which may facilitate understanding of pathophysiology and suggest potential neural biomarkers for clinical assessment, monitoring and interventions of MDD. One important limitation is that eight recruited studies in our meta-analysis have recruited more males than females, which may have a selection bias of patients.

Common and specific large-scale brain changes in major depressive disorder, anxiety disorders, and chronic pain: a transdiagnostic multimodal meta-analysis of structural and functional MRI studies

Major depressive disorder (MDD), anxiety disorders (ANX), and chronic pain (CP) are closely-related disorders with both high degrees of comorbidity among them and shared risk factors. Considering this multi-level overlap, but also the distinct phenotypes of the disorders, we hypothesized both common and disorder-specific changes of large-scale brain systems, which mediate neural mechanisms and impaired behavioral traits, in MDD, ANX, and CP. To identify such common and disorder-specific brain changes, we conducted a transdiagnostic, multimodal meta-analysis of structural and functional MRI-studies investigating changes of gray matter volume (GMV) and intrinsic functional connectivity (iFC) of large-scale intrinsic brain networks across MDD, ANX, and CP. The study was preregistered at PROSPERO (CRD42019119709). 320 studies comprising 10,931 patients and 11,135 healthy controls were included. Across disorders, common changes focused on GMV-decrease in insular and medial-prefrontal cortices, located mainly within the so-called default-mode and salience networks. Disorder-specific changes comprised hyperconnectivity between default-mode and frontoparietal networks and hypoconnectivity between limbic and salience networks in MDD; limbic network hyperconnectivity and GMV-decrease in insular and medial-temporal cortices in ANX; and hypoconnectivity between salience and default-mode networks and GMV-increase in medial temporal lobes in CP. Common changes suggested a neural correlate for comorbidity and possibly shared neuro-behavioral chronification mechanisms. Disorder-specific changes might underlie distinct phenotypes and possibly additional disorder-specific mechanisms.

Anterior cingulate cortex in individuals with depressive symptoms: A structural MRI study

Several magnetic resonance imaging (MRI) studies have reported reduction in anterior cingulate cortex (ACC) volume in individuals with major depressive disorder (MDD). However, some MRI studies did not find significant ACC volumetric changes in MDD, and sample sizes were generally small. This cross-sectional structural MRI study examined the relationship between current depressive symptoms and ACC volume in a large community sample of 1803 adults. A series of multiple linear regression analyses were conducted to predict right and left ACC volumes using Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR) scores, intracranial volume, age, sex, race/ethnicity, alcohol use, tobacco use, and psychotropic medications as predictor variables. Right ACC volume was significantly negatively associated with QIDS-SR scores, while no significant association was found between left ACC volume and QIDS-SR scores. In addition, there was a significant negative association between QIDS-SR scores and right but not left ACC volumes in males, and no significant association between QIDS-SR scores and right or left ACC volumes in females. These findings suggest that right ACC volume is reduced in people with greater self-reported depressive symptom severity, and that this association is only significant in men.

White Matter Alterations Associated with Pro-inflammatory Cytokines in Patients with Major Depressive Disorder.

ObjectiveRegarding the neuroinflammatory theory of major depressive disorder (MDD), little is known about the effect of pro-inflammatory cytokines on white matter (WM) changes in MDD. We aimed to investigate the relationship between pro-inflammatory cytokines and WM alterations in patients with MDD.MethodsTwenty-two patients with MDD and 22 healthy controls (HC) were evaluated for brain imaging and pro-inflammatory cytokines including interleukin (IL)-1b, IL-6, IL-8, interferon-g and tumor necrosis factor (TNF)-α. Tract-based spatial statistics and FreeSurfer were used for brain image analysis.ResultsThe levels of TNF-α and IL-8 were significantly higher in the MDD group than in HC. Compared to HC, lower fractional anisotropy (FA), and higher median diffusivity (MD) and radial diffusivity (RD) values were found in the MDD group for several WM regions. Voxel-wise correlation analysis showed that the level of TNF-α was negatively correlated with FA, and positively correlated with MD and RD in the left body and genu of the corpus callosum, left anterior corona radiata, and left superior corona radiata.ConclusionOur findings suggest that TNF-α may play an important role in the WM alterations in depression, possibly through demyelination.

Whole-Transcriptome Brain Expression and Exon-Usage Profiling in Major Depression and Suicide

Identifying predictors for suicide in patients with Major depressive disorder (MDD) is particularly important. However, the biological mechanisms underlying MDD and suicide remain elusive. Gene expression profiling studies in the brains of individuals who died by suicide and had depression using oligonucleotide microarrays have often failed to distinguish MDD and suicide. To address these knowledge gaps, we applied next-generation sequencing technology to evaluate gene expression changes in MDD and suicide.

Remote Digital Measurement of Facial and Vocal Markers of Major Depressive Disorder Severity and Treatment Response: A Pilot Study.

Objectives: Multiple machine learning-based visual and auditory digital markers have demonstrated associations between major depressive disorder (MDD) status and severity. The current study examines if such measurements can quantify response to antidepressant treatment (ADT) with selective serotonin reuptake inhibitors (SSRIs) and serotonin–norepinephrine uptake inhibitors (SNRIs).Methods: Visual and auditory markers were acquired through an automated smartphone task that measures facial, vocal, and head movement characteristics across 4 weeks of treatment (with time points at baseline, 2 weeks, and 4 weeks) on ADT (n = 18). MDD diagnosis was confirmed using the Mini-International Neuropsychiatric Interview (MINI), and the Montgomery–Åsberg Depression Rating Scale (MADRS) was collected concordantly to assess changes in MDD severity.Results: Patient responses to ADT demonstrated clinically and statistically significant changes in the MADRS [F(2, 34) = 51.62, p < 0.0001]. Additionally, patients demonstrated significant increases in multiple digital markers including facial expressivity, head movement, and amount of speech. Finally, patients demonstrated significantly decreased frequency of fear and anger facial expressions.Conclusion: Digital markers associated with MDD demonstrate validity as measures of treatment response.