Abstract Background This study aimed to examine the neurotrophic factors secreted from brain in depression by analyzing astrocyte-derived extracellular vesicles (ADEVs) isolated from plasma, and to explore the causal relationship between the expression of neurotrophic factors in the brain and depression. Methods A total of 40 patients with treatment-resistant depression (TRD) and 35 matched healthy controls (HCs) were recruited at baseline, and 34 TRD patients completed the post-electroconvulsive therapy (ECT) visits. The concentrations of five neurotrophic factors in ADEVs were measured. A correlation analysis was performed between neurotrophic factors in ADEVs and neurogenesis marker doublecortin (DCX) in neuron-derived extracellular vesicles (NDEVs). Subsequently, Mendelian randomization (MR) study and cell experiments were conducted. Results Our findings revealed a decrease in the level of epidermal growth factor (EGF) in ADEVs among TRD patients, with an increase observed post-ECT. The corrected area under the curve for EGF were larger than those for other neurotrophic factors: 0.99 (95% CI: 0.98-1.00). MR suggested that decreased expression levels of the EGF gene in the cortex constitute a risk factor for depression. We observed a positive correlation between the levels of EGF in ADEVs and DCX in NDEVs. Subsequently, cell experiments suggested that EGF can activate EGF receptor (EGFR) to trigger the PI3K-Akt pathway, participating in the promotion of DCX. Conclusions This study provides the in vivo evidences supporting that a reduction in EGF levels in the central nervous system could potentially contribute to depression and serve as a biomarker for it. Additionally, the EGF/EGFR signaling pathway may be involved in regulating early neurogenesis traits in depression.
Abstract Post-traumatic stress disorder (PTSD) may be linked to abnormalities in neural circuits that facilitate fear learning and memory processes. The precise degree to which this connection is influenced by genetic factors is still uncertain. This study aimed to investigate the genetic association between PTSD and its corresponding brain circuitry components. We first conducted a meta-analysis using the summary of PTSD genome-wide association studies (GWAS) from multiple cohorts to enhance statistical power (sample size = 306,400). Then, based on the result of the GWAS meta-analysis, and utilizing the lifetime trauma events (LTE) trait as a control for PTSD, we proceeded with subsequent investigations. We investigated the genetic association of PTSD and LTE with nine brain structure traits related to the brain circuitry by various methodologies, including heritability tissue enrichment analysis, global and local genetic correlations, polygenic overlap analysis, and causal inference. As a result, we discovered an enrichment of heritability for PTSD within circuitry-relevant brain regions such as the cingulate cortex and frontal cortex, alongside the identification of weak genetic correlations between PTSD and these brain regions. We have observed a polygenic overlap between the two trauma-related traits and nine traits of brain circuitry components such as global cortical area and cingulum. A total of 31 novel jointly significant genetic loci (conjunction FDR < 0.05) associated with PTSD and nine brain structures were identified, suggesting a potential connection between them, and these loci are involved in the process of DNA damage and repair as well as the pathway of neurodegenerative diseases. We also identified a potential causal relationship between PTSD and the surface area of the frontal pole. Our findings offer a valuable understanding of the genetic mechanisms underlying PTSD and its associated brain circuitry.
ABSTRACT Background Systemic inflammation and insomnia often co-occur in patients with depression. However, there is no suitable animal model to investigate the relationship between inflammation, sleep deprivation (SD), and depression. Methods To model interactions between insomnia, inflammation, and depression, we developed a novel “two-hit” rodent model of depressive-like behaviors using continuous SD followed by daily lipopolysaccharide (LPS) treatment. Control groups received SD, LPS, or sterile phosphate-buffered salinealone. The model’s validity was assessed at the cellular and molecular levels, with fluoxetine rescue applied to confirm model validity. Results The model group demonstrated significant depressive-like behaviors that were rescued by fluoxetine treatment. Transcriptomic analysis revealed alterations in neuroinflammation and synaptic plasticity pathways within the hippocampus and prefrontal cortex (PFC) of model rats. Western blotting validated alterations in key protein markers related to both processes, and immunofluorescence confirmed microglia and astrocyte activation, indicative of neuroinflammation. Additionally, transmission electron microscopy and Golgi-Cox staining revealed reduced synapse and dendritic spine density in the model group. Fluoxetine treatment reversed these structural changes. Sixteen genes associated with neuroinflammation and synaptic function were validated in human genetic studies by transcriptome-wide association analysis. Conclusion This reliable two-hit model will be useful for investigating the roles of insomnia and inflammation in depression.
Cortical morphometry is an intermediate phenotype that is closely related to the genetics and onset of major depressive disorder (MDD), and cortical morphometric networks are considered more relevant to disease mechanisms than brain regions. We sought to investigate changes in cortical morphometric networks in MDD and their relationship with genetic risk in healthy controls.
Methods:
We recruited healthy controls and patients with MDD of Han Chinese descent. Participants underwent DNA extraction and magnetic resonance imaging, including T1-weighted and diffusion tensor imaging. We calculated polygenic risk scores (PRS) based on previous summary statistics from a genome-wide association study of the Chinese Han population. We used a novel method based on Kullback–Leibler divergence to construct the morphometric inverse divergence (MIND) network, and we included the classic morphometric similarity network (MSN) as a complementary approach. Considering the relationship between cortical and white matter networks, we also constructed a streamlined density network. We conducted group comparison and PRS correlation analyses at both the regional and network level.
Results:
We included 130 healthy controls and 195 patients with MDD. The results indicated enhanced connectivity in the MIND network among patients with MDD and people with high genetic risk, particularly in the somatomotor (SMN) and default mode networks (DMN). We did not observe significant findings in the MSN. The white matter network showed disruption among people with high genetic risk, also primarily in the SMN and DMN. The MIND network outperformed the MSN network in distinguishing MDD status.
Limitations:
Our study was cross-sectional and could not explore the causal relationships between cortical morphological changes, white matter connectivity, and disease states. Some patients had received antidepressant treatment, which may have influenced brain morphology and white matter network structure.
Conclusion:
The genetic mechanisms of depression may be related to white matter disintegration, which could also be associated with decoupling of the SMN and DMN. These findings provide new insights into the genetic mechanisms and potential biomarkers of MDD.
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