Association of cognitive impairment and reduced cortical thickness in prefrontal cortex and anterior cingulate cortex with treatment-resistant depression

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

Background

Major 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.

Methods

We 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.

Results

Differential 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.

Conclusions

The 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.

The effect of inflammation markers on cortical thinning in major depressive disorder: A possible mediator of depression and cortical changes

BACKGROUND

Major depressive disorder (MDD) is a prevalent mental health condition with significant societal impact. Owing to the intricate biological diversity of MDD, treatment efficacy remains limited. Immune biomarkers have emerged as potential predictors of treatment response, underscoring the interaction between the immune system and the brain. This study investigated the relationship between cytokine levels and cortical thickness in patients with MDD, focusing on the corticolimbic circuit, to elucidate the influence of neuroinflammation on structural brain changes and contribute to a deeper understanding of the pathophysiology of MDD.

METHOD

A total of 114 patients with MDD and 101 healthy controls (HC) matched for age, sex, and body mass index (BMI) were recruited. All participants were assessed for depression severity using the Hamilton Depression Rating Scale (HDRS), and 3.0 T T1 weighted brain MRI data were acquired. Additionally, cytokine levels were measured using a highly sensitive bead-based multiplex immunosorbent assay.

RESULTS

Patients diagnosed with MDD exhibited notably elevated levels of interleukin-6 (p = 0.005) and interleukin-8 (p = 0.005), alongside significant cortical thinning in the left anterior cingulate gyrus and left superior frontal gyrus, with these findings maintaining significance even after applying Bonferroni correction. Furthermore, increased interleukin-6 and interleukin-8 levels in patients with MDD are associated with alterations in the left frontomarginal gyrus and right anterior cingulate cortex (ACC).

CONCLUSIONS

This suggests a potential influence of neuroinflammation on right ACC function in MDD patients, warranting longitudinal research to explore interleukin-6 and interleukin-8 mediated neurotoxicity in MDD vulnerability and brain morphology changes.

Gray matter biomarkers for major depressive disorder and manic disorder using logistic regression

The study investigates morphometric changes using surface-based measures and logistic regression in Major depressive-disorder (MDD) and Manic-disorder patients as compared to controls. MDD (n = 21) and manic (n = 20) subjects were recruited from psychiatric clinics, along with 19 healthy-controls from local population, after structured and semi-structured clinical interview (DSM-IV, brief Psychotic-Rating Scale (BPRS), Young Mania Rating Scale (YMRS), Hamilton depression rating scale (HDRS), cognitive function by postgraduate Institute Battery of Brain Dysfunction (PGIBBD)). Using 3D T1-weighted images, gray matter (GM) cortical thickness and GM-based morphometric signatures (using logistic regression) were compared among MDD, manic disorder and controls using analysis of covariance (ANCOVA). No significant difference was found between the MDD and manic disorder patients. When compared to controls, cortical thinning was observed in bilateral rostral middle frontal gyrus and parsopercularis, right lateral occipital cortex, right lingual gyrus in MDD; and bilateral rostral middle frontal and superior frontal gyrus, right middle temporal gyrus, left supramarginal and left precentral gyrus in Manic disorders. Logistic regression analysis exhibited GM cortical thinning in the bilateral parsopercularis, right lateral occipital cortex and lingual gyrus in MDD; and bilateral rostral middle, superior frontal gyri, right middle temporal gyrus in Manic with a sensitivity and specificity of 85.7 % and 94.7 % and 90.0 % and 94.7 %, respectively in comparison with controls. Both groups exhibited GM loss in bilateral rostral middle frontal gyrus brain regions compared to controls. Multivariate analysis revealed common changes in GM in MDD and manic disorders associated with mood temperament, but differences when compared to controls.

Association between mental health symptoms and behavioral performance in younger vs. older online workers

Background

The COVID-19 pandemic has been associated with increased rates of mental health problems, particularly in younger people.

Objective

We quantified mental health of online workers before and during the COVID-19 pandemic, and cognition during the early stages of the pandemic in 2020. A pre-registered data analysis plan was completed, testing the following three hypotheses: reward-related behaviors will remain intact as age increases; cognitive performance will decline with age; mood symptoms will worsen during the pandemic compared to before. We also conducted exploratory analyses including Bayesian computational modeling of latent cognitive parameters.

Methods

Self-report depression (Patient Health Questionnaire 8) and anxiety (General Anxiety Disorder 7) prevalence were compared from two samples of Amazon Mechanical Turk (MTurk) workers ages 18-76: pre-COVID 2018 (N = 799) and peri-COVID 2020 (N = 233). The peri-COVID sample also completed a browser-based neurocognitive test battery.

Results

We found support for two out of three pre-registered hypotheses. Notably our hypothesis that mental health symptoms would increase in the peri-COVID sample compared to pre-COVID sample was not supported: both groups reported high mental health burden, especially younger online workers. Higher mental health symptoms were associated with negative impacts on cognitive performance (speed/accuracy tradeoffs) in the peri-COVID sample. We found support for two hypotheses: reaction time slows down with age in two of three attention tasks tested, whereas reward function and accuracy appear to be preserved with age.

Conclusion

This study identified high mental health burden, particularly in younger online workers, and associated negative impacts on cognitive function.