Thalamo-Habenular Connection Differences Between Patients With Major Depressive Disorder and Normal Controls.
Ontology highlight
ABSTRACT:
SUBMITTER: Cho SE
PROVIDER: S-EPMC8440934 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Bipolar disorder (BD) is a psychiatric disorder with high morbidity and mortality that cannot be distinguished from major depressive disorder (MDD) until the first manic episode. A biomarker able to differentiate BD and MDD could help clinicians avoid risks of treating BD with antidepressants without mood stabilizers.Cortical thickness differences were assessed using magnetic resonance imaging in BD depressed patients (n = 18), MDD depressed patients (n = 56), and healthy volunteers (HVs) (n = 54). A general linear model identified clusters of cortical thickness difference between diagnostic groups.Compared to the HV group, the BD group had decreased cortical thickness in six regions, after controlling for age and sex, located within the frontal and parietal lobes, and the posterior cingulate cortex. Mean cortical thickness changes in clusters ranged from 7.6 to 9.6% (cluster-wise p-values from 1.0 e-4 to 0.037). When compared to MDD, three clusters of lower cortical thickness in BD were identified that overlapped with clusters that differentiated the BD and HV groups. Mean cortical thickness changes in the clusters ranged from 7.5 to 8.2% (cluster-wise p-values from 1.0 e-4 to 0.023). The difference in cortical thickness was more pronounced when the subgroup of subjects with bipolar I disorder (BD-I) was compared to the MDD group.Cortical thickness patterns were distinct between BD and MDD. These results are a step toward developing an imaging test to differentiate the two disorders.
| S-EPMC4047134 | biostudies-other
Project description:ObjectiveGrowing evidence has implicated dysfunction of the thalamus and its projection cortical targets in depression. However, the anatomical specificity of thalamo-cortical connectivity in major depressive disorder (MDD) remains unknown due to the regional heterogeneity of the thalamus and limited methods to examine this.MethodsResting-state fMRI was collected on 70 MDD patients and 70 healthy controls. The thalamus was parcellated based on connectivity with six predefined cortical regions of interest (ROIs). The segmented thalamic nuclei were used as seeds to map connectivity with the rest of the whole brain. The cortical-to-thalamus connectivity values and thalamus-based connectivity maps were compared between groups.ResultsThe cortical ROIs demonstrated correlations with spatially distinct zones within the thalamus. We found a trend toward reduced parietal ROI-to-thalamus connectivity in MDD. Importantly, MDD patients demonstrated reduced connectivity between prefrontal and parietal thalamus ROIs and bilateral middle frontal gyrus (MFG) and the right posterior default mode network (DMN) and between the prefrontal and motor thalamus ROIs and lateral temporal regions. Conversely, increased connectivity emerged between the motor thalamus ROI and right MFG and right medial frontal gyrus/anterior cingulate; between motor/somatosensory thalamus ROIs and right posterior DMN; between prefrontal/somatosensory thalamus ROIs and cerebellum; and between the parietal thalamus ROI and left insula.ConclusionsThis study is the first to examine the anatomical specificity of thalamo-cortical connectivity disturbances in MDD. Subjects with MDD demonstrated altered thalamo-cortical connectivity characterized by a complex pattern of region-dependent hypo- or hyperconnectivity. We therefore speculate that selectively modulating the connectivity of thalamo-cortical circuitry may be a potential novel therapeutic mechanism for MDD.
| S-EPMC6490069 | biostudies-literature
Project description:Background: Major Depressive Disorder (MDD) is a moderately heritable disorder with a high lifetime prevalence. At present, laboratory blood tests to support MDD diagnosis are not available. Methods: We used a classifier approach on blood gene expression profiles of a unique set of non-medicated subjects (MDD patients and controls) to select genes of which expression is predictive for disease status. To reveal blood gene expression changes related to MDD disease, we applied a powerful ex vivo stimulus to the blood, i.e. incubation with lipopolysaccharide (LPS; 10 ng/ml blood). Results: Based on LPS-stimulated blood gene expression using whole-genome microarrays in 42 subjects (primary cohort; 21 MDD patients (mean age 42.3 years), 21 healthy controls (mean age 41.9 years)), we identified a set of genes (CAPRIN1, CLEC4A, KRT23, MLC1, PLSCR1, PROK2, ZBTB16) that serves as a molecular signature of MDD. These findings were validated for the primary cohort using an independent quantitative PCR method (P = 0.007). The difference between depressive patients and controls was confirmed (P = 0.019) in a replication cohort of 13 patients with MDD (mean age 42.8 years) and 14 controls (mean age 45.6 years). The MDD-signature score comprised of expression levels of 7 genes could discriminate depressive patients from controls with sensitivity of 76.9% and specificity of 71.8%. Conclusions: We show for the first time that molecular analysis of stimulated blood cells can be used as an endophenotype for MDD diagnosis, which is a milestone in establishing biomarkers for neuropsychiatric disorders with moderate heritability in general. Our results may provide a new entry point for following and predicting treatment outcome, as well as prediction of severity and recurrence of MDD. In total, 33 MDD patients and 34 healthy controls were analyzed using basal gene expression in whole blood, and gene expression from whole blood that was stimulated with LPS for 5-6 h, using microarrays. Patients were arbitrarily selected from all patients to serve as primary cohort (nMDD = 21 (MDD01-MDD21); nControls = 21 (Con01-Con21)), or replication cohort (nMDD = 12 (MDD22-MDD35); nControls = 13 (Con22-Con37)) using microarrays. This submission does not include Samples CON21_LPS or CON30_LPS.
2011-10-04 | E-GEOD-19738 | biostudies-arrayexpress
Project description:Background: Major Depressive Disorder (MDD) is a moderately heritable disorder with a high lifetime prevalence. At present, laboratory blood tests to support MDD diagnosis are not available. Methods: We used a classifier approach on blood gene expression profiles of a unique set of non-medicated subjects (MDD patients and controls) to select genes of which expression is predictive for disease status. To reveal blood gene expression changes related to MDD disease, we applied a powerful ex vivo stimulus to the blood, i.e. incubation with lipopolysaccharide (LPS; 10 ng/ml blood). Results: Based on LPS-stimulated blood gene expression using whole-genome microarrays in 42 subjects (primary cohort; 21 MDD patients (mean age 42.3 years), 21 healthy controls (mean age 41.9 years)), we identified a set of genes (CAPRIN1, CLEC4A, KRT23, MLC1, PLSCR1, PROK2, ZBTB16) that serves as a molecular signature of MDD. These findings were validated for the primary cohort using an independent quantitative PCR method (P = 0.007). The difference between depressive patients and controls was confirmed (P = 0.019) in a replication cohort of 13 patients with MDD (mean age 42.8 years) and 14 controls (mean age 45.6 years). The MDD-signature score comprised of expression levels of 7 genes could discriminate depressive patients from controls with sensitivity of 76.9% and specificity of 71.8%. Conclusions: We show for the first time that molecular analysis of stimulated blood cells can be used as an endophenotype for MDD diagnosis, which is a milestone in establishing biomarkers for neuropsychiatric disorders with moderate heritability in general. Our results may provide a new entry point for following and predicting treatment outcome, as well as prediction of severity and recurrence of MDD.
2011-10-05 | GSE19738 | GEO
Project description:Major depressive disorder (MDD) exhibits numerous clinical, epidemiological, and molecular features that are consistent with partially inherited and partially acquired epigenetic misregulation. We performed microarray based DNA modification study of MDD, utilizing affected and unaffected samples from white blood cells from monozygotic twins discordant for MDD, post-mortem prefrontal cortex tissues, and sperm samples. We performed DNA methylome analysis on white blood cells from monozygotic twins discordant for depression (n=200), pre-frontal cortex (n=71), and germline samples (n=33) from affected individuals and controls (total n=304). DNA samples were enriched for unmodified fraction of the genome using DNA-modification sensitive restriction enzyme digestion followed by adaptor-mediated PCR. The enriched fractions were labelled with a fluorescent dye (Cy5) and hybridized onto the array with a common reference pool (Cy3) generated from individuals unrelated to this study.
2012-04-27 | E-GEOD-37579 | biostudies-arrayexpress
Project description:We do this study to identify and validate the differentially expressed circRNAs in MDD patients and to evaluate their potential as diagnostic biomarkers and as novel therapeutic targets for MDD, to explore the potential clinical value and possible mechanism of circRNAs in MDD.
2022-03-21 | GSE190518 | GEO
Project description:Background:Dysfunctional attitudes play a key role in the development and prognosis of depression. Gender also plays an important role in many clinical features of major depressive disorder (MDD). This study is aimed at investigating the gender differences in dysfunctional attitudes in patients with MDD. Methods:One hundred and seventy-two patients with MDD and 159 healthy controls (HCs) were enrolled in this study. Dysfunctional attitudes were assessed by the Chinese version of the dysfunctional attitude scale-form A (C-DAS-A) and depression severity was assessed by the 24-item Hamilton rating scale for depression (HAMD24). The 14-item Hamilton Anxiety Rating Scale (HAMA14) was used to measure anxiety. Factorial analysis of variance (ANOVA) of gender and diagnosis on C-DAS-A total and factor scores was adopted with age, education, and body mass index (BMI) controlled. Multiple linear regression analyses of DAS were performed in the MDD group. Results:First, the C-DAS-A score in the MDD group was increased significantly than HCs. Second, female patients with MDD showed significantly higher scores in C-DAS-A total and three-factor scores (seeking applause, dependence, and self-determination attitude), while no significant difference between female HCs and male HCs was detected. Third, five variables (age, gender, smoking history, HAMD24, and HAMA14) had predictive effects on and gender showed the greatest contributions to C-DAS-A total and three-factor scores (seeking applause, dependence, and self-determination attitude). Conclusion:Females with MDD may be linked to more severe cognitive distortion than their male counterparts in seeking applause, dependence, and self-determination attitude, supporting the reasonableness for gender-specific psychosocial interventions.
| S-EPMC7057763 | biostudies-literature
Project description:BackgroundMajor depressive disorder (MDD) is characterized by sadness and anhedonia, but also physical symptoms such as changes in appetite and weight. Gut microbiota has been hypothesized to be involved in MDD through gut-brain axis signaling. Moreover, antidepressants display antibacterial properties in the gastrointestinal tract. The aim of this study was to compare the gut microbiota and systemic inflammatory profile of young patients with MDD before and after initiation of antidepressant treatment and/or psychotherapy in comparison with a non-depressed control group (nonMDD).MethodsFecal and blood samples were collected at baseline and at follow-up after four and twelve weeks, respectively. Patients started treatment immediately after collection of the baseline samples. The gut microbiota was characterized by 16 S rRNA gene sequencing targeting the hypervariable V4 region. Plasma levels of 49 unique immune markers were assessed using Mesoscale.ResultsIn total, 27 MDD patients and 32 nonMDD controls were included in the study. The gut microbiota in the baseline samples of MDD versus nonMDD participants did not differ regarding α- or β-diversity. However, there was a higher relative abundance of the genera Ruminococcus gnavus group, and a lower relative abundance of the genera Desulfovibrio, Tyzzerella, Megamonas, Olsenella, Gordonibacter, Allisonella and Rothia in the MDD group compared to the nonMDD group. In the MDD group, there was an increase in the genera Rothia, Desulfovibrio, Gordinobacteer and Lactobacillus, while genera belonging to the Firmicutes phylum were found depleted at twelve weeks follow-up compared to baseline. In the MDD group, IL-7, IL-8 and IL-17b levels were elevated compared to the nonMDD group at baseline. Furthermore, MDI score in the MDD group was found to correlate with Bray-Curtis dissimilarity at baseline, and several inflammatory markers at both baseline and after initiation of antidepressant treatment.ConclusionSeveral bacterial taxa differed between the MDD group and the nonMDD group at baseline and changed in relative abundance during antidepressant treatment and/or psychotherapy. The MDD group was furthermore found to have a pro-inflammatory profile compared to the nonMDD group at baseline. Further studies are required to investigate the gut microbiota and pro-inflammatory profile of patients with MDD.
| S-EPMC10832199 | biostudies-literature
Project description:The habenula is one of the most important brain regions for investigating the etiology of psychiatric diseases such as major depressive disorder (MDD). However, the habenula is challenging to delineate with the naked human eye in brain imaging due to its low contrast and tiny size, and the manual segmentation results vary greatly depending on the observer. Therefore, there is a great need for automatic quantitative analytic methods of the habenula for psychiatric research purposes. Here we propose an automated segmentation and volume estimation method for the habenula in 7 Tesla magnetic resonance imaging based on a deep learning-based semantic segmentation network. The proposed method, using the data of 69 participants (33 patients with MDD and 36 normal controls), achieved an average precision, recall, and dice similarity coefficient of 0.869, 0.865, and 0.852, respectively, in the automated segmentation task. Moreover, the intra-class correlation coefficient reached 0.870 in the volume estimation task. This study demonstrates that this deep learning-based method can provide accurate and quantitative analytic results of the habenula. By providing rapid and quantitative information on the habenula, we expect our proposed method will aid future psychiatric disease studies.
| S-EPMC8241874 | biostudies-literature
Project description:Identify blood proteins relevant to paroxetine response in patients with major depressive disorder (MDD)
2022-05-20 | PXD028947 | Pride