Depressed patients show evidence of both proinflammatory changes and neurophysiological abnormalities such as increased amygdala reactivity and volumetric decreases of the hippocampus and ventromedial prefrontal cortex (vmPFC). However, very little is known about the relationship between inflammation and neuroimaging abnormalities in mood disorders. A whole genome expression analysis of peripheral blood mononuclear cells yielded 12 protein-coding genes (ADM, APBB3, CD160, CFD, CITED2, CTSZ, IER5, NFKBIZ, NR4A2, NUCKS1, SERTAD1, TNF) that were differentially expressed between 29 unmedicated depressed patients with a mood disorder (8 bipolar disorder, 21 major depressive disorder) and 24 healthy controls (HCs). Several of these genes have been implicated in neurological disorders and/or apoptosis. Ingenuity Pathway Analysis yielded two genes networks, one centered around TNF with NFKβ, TGFβ, and ERK as connecting hubs, and the second network indicating cell cycle and/or kinase signaling anomalies. fMRI scanning was conducted using a backward-masking task in which subjects were presented with emotionally-valenced faces. Compared with HCs, the depressed subjects displayed a greater hemodynamic response in the right amygdala, left hippocampus, and the ventromedial prefrontal cortex to masked sad versus happy faces. The mRNA levels of several genes were significantly correlated with the hemodynamic response of the amygdala, vmPFC and hippocampus to masked sad versus happy faces. Differentially-expressed transcripts were significantly correlated with thickness of the left subgenual ACC, and volume of the hippocampus and caudate. Our results raise the possibility that molecular-level immune dysfunction can be mapped onto macro-level neuroimaging abnormalities, potentially elucidating a mechanism by which inflammation leads to depression.
Interleukin-7 is widely accepted as a major homeostatic factor involved in T cell development. To assess the IL-7 responsiveness of thymocytes involved in selection processes, we used a new sensitive flow cytometry-based assay to detect intracellular phosphorylation of STAT-5 induced by IL-7 in defined mouse thymocyte subsets. Using this method, we found the earliest thymocyte subset (CD4−CD8−CD25−CD44+) to contain both IL-7-responsive and nonresponsive cells. Transition through the next stages of development (CD4−CD8−CD25+CD44+ and −) was associated with responsiveness of all thymocytes within these populations. Passage of thymocytes through β-selection resulted in a significant reduction in IL-7 sensitivity. In the next phases of development (TCR− and TCRlowCD69−), thymocytes were completely insensitive to the effects of IL-7. STAT-5 phosphorylation in response to IL-7 was again observed, however, in thymocytes involved in the positive selection process (TCRlowCD69+ and TCRintermediate). As expected, CD4 and CD8 single-positive thymocytes were responsive to IL-7. These findings delineate an IL-7-insensitive population between the β-selection and positive selection checkpoints encompassing thymocytes predicted to die by neglect due to failure of positive selection. This pattern of sensitivity suggests a two-signal mechanism by which survival of thymocytes at these checkpoints is governed.
CD27 and CD28 have emerged as indicators demarcating the transition of thymocytes through beta-selection. We found that CD28 exhibits a greater dynamic range of expression during this phase, thus it was employed to further parse the DN/CD44(-) compartment in order to assess IL-7 signaling during the beta-selection process. Plotting CD28 versus CD25 expression revealed six DN/CD44(-) populations. OP9-DL1 stromal cell co-culture was used to demonstrate a developmental linkage from DN3a (CD25(+)CD28(-/lo)) to DN3b (CD25(+)CD28(+)) to DN3c (CD25(int)CD28(+)) to DN4a (CD25(-)CD28(+)) to double positive (DP) and showed the DN4b (CD25(-)CD28(hi)) and DN4c (CD25(-)CD28(-/lo)) populations to be inefficient in producing DP cells. Using CD69 as an additional marker to further parse the DN4a population, we found the pre-DP cells to be the CD44(-)CD25(-)CD28(int)CD69(-)CD4(-/lo)CD8(-/lo) subset. Using this refined developmental scheme, IL-7R alpha expression was found to be transiently up-regulated post-beta-selection in the DN3b and DN3c subsets; however, this increase did not confer enhanced responsiveness over that observed in the DN3a population. CD28 messenger RNA expression was up-regulated in post-beta-selected cells, whereas transcripts for CD27, IL-7R alpha and Bcl-2 were lower than that observed in the DN3a population. This study refines the current thymocyte differentiation scheme to allow for more detailed evaluation of events controlling early T-cell development, specifically surrounding the beta-selection checkpoint.
Genomic variation underlying major depressive disorder (MDD) likely involves the interaction and regulation of multiple genes in a network. Data-driven co-expression network module inference has the potential to account for variation within regulatory networks, reduce the dimensionality of RNA-Seq data, and detect significant gene-expression modules associated with depression severity. We performed an RNA-Seq gene co-expression network analysis of mRNA data obtained from the peripheral blood mononuclear cells of unmedicated MDD (n = 78) and healthy control (n = 79) subjects. Across the combined MDD and HC groups, we assigned genes into modules using hierarchical clustering with a dynamic tree cut method and projected the expression data onto a lower-dimensional module space by computing the single-sample gene set enrichment score of each module. We tested the single-sample scores of each module for association with levels of depression severity measured by the Montgomery-Åsberg Depression Scale (MADRS). Independent of MDD status, we identified 23 gene modules from the co-expression network. Two modules were significantly associated with the MADRS score after multiple comparison adjustment (adjusted p = 0.009, 0.028 at 0.05 FDR threshold), and one of these modules replicated in a previous RNA-Seq study of MDD (p = 0.03). The two MADRS-associated modules contain genes previously implicated in mood disorders and show enrichment of apoptosis and B cell receptor signaling. The genes in these modules show a correlation between network centrality and univariate association with depression, suggesting that intramodular hub genes are more likely to be related to MDD compared to other genes in a module.
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