Background: The efficacy and prognosis of major depressive disorder (MDD) are limited by its heterogeneity. MDD with melancholic features is an important subtype of MDD. The present study aimed to reveal the white matter (WM) network changes in melancholic depression.
Materials And Methods: Twenty-three first-onset, untreated melancholic MDD, 59 non-melancholic MDD patients and 63 health controls underwent diffusion tensor imaging (DTI) scans. WM network analysis based on graph theory and support vector machine (SVM) were used for image data analysis.
Results: Compared with HC, small-worldness was reduced and abnormal node attributes were in the right orbital inferior frontal gyrus, left orbital superior frontal gyrus, right caudate nucleus, right orbital superior frontal gyrus, right orbital middle frontal gyrus, left rectus gyrus, and left median cingulate and paracingulate gyrus of MDD patients. Compared with non-melancholic MDD, small-worldness was reduced and abnormal node attributes were in right orbital inferior frontal gyrus, left orbital superior frontal gyrus and right caudate nucleus of melancholic MDD. For correlation analysis, the 7th item score of the HRSD-17 (work and interest) was positively associated with increased node betweenness centrality (aBC) values in right orbital inferior frontal gyrus, while negatively associated with the decreased aBC in left orbital superior frontal gyrus. SVM analysis results showed that abnormal aBC in right orbital inferior frontal gyrus and left orbital superior frontal gyrus showed the highest accuracy of 81.0% (69/83), the sensitivity of 66.3%, and specificity of 85.2% for discriminating MDD patients with or without melancholic features.
Conclusion: There is a significant difference in WM network changes between MDD patients with and without melancholic features.
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http://dx.doi.org/10.3389/fpsyt.2022.816191 | DOI Listing |
Alzheimers Dement
December 2024
Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
Background: Positron emission tomography (PET) imaging greatly impacted Alzheimer's disease (AD) research and diagnosis. which makes predicting PET brain imaging alterations using blood data is of high interest. Additionally, integrating PET and omics data can provide new insights into AD pathophysiology.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
VA Boston Healthcare System, Boston, MA, USA.
Background: T-cell infiltration into the brain parenchyma is associated with hyperphosphorylated tau (p-tau) accumulation in neurodegenerative diseases. Chronic traumatic encephalopathy (CTE) is a progressive tauopathy caused by exposure to repetitive head impacts (RHI). CTE is defined by the perivascular accumulation of p-tau at the cortical sulcal depths and can be stratified into mild and severe pathological stages.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Allen Institute for Brain Science, Seattle, WA, USA.
Background: Alzheimer's Disease is marked by the gradual aggregation of pathological proteins, Tau and beta-amyloid, throughout various areas of the brain. The progression of these pathologies follows a consistent pattern, impacting various cellular populations as it advances through each brain region. Previously, we used Bayesian algorithms to create a continuous progression score to mathematically capture the collective aggregation of multiple pathological variables within a specific brain region.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
University of California, Irvine, Irvine, CA, USA.
Background: Limbic-predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC) is a common cause of dementia in older age. LATE-NC was first coined in 2019 with proposed staging criteria of TDP-43 progressing from amygdala (stage 1), to hippocampus (stage 2), to middle frontal gyrus (stage 3). Criteria were updated in 2023 to further categorize stage 1 to either TDP-43 inclusions in amygdala alone (stage 1a) or hippocampus alone (stage 1b).
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Allen Institute for Brain Science, Seattle, WA, USA.
Background: Numerous studies have identified AD-associated molecular and cellular changes to the cortex using single nucleus RNA sequencing (snRNA-seq) and, to a lesser extent, single nucleus ATAC-seq (snATAC-seq), applied to millions of cells across hundreds of donors. It has proven challenging, however, to determine whether changes are consistent because of differences in cohort selection, reported clinical metadata, data pre-processing, cellular taxonomy construction/mapping, and analytical strategies across studies.
Method: We uniformly re-processed 10 publicly available datasets (Table 1) that had applied snRNA-seq to 4.
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