Alterations in splenic function and gene expression in mice with depressive-like behavior induced by exposure to corticosterone

Intravenous Reelin Treatment Rescues Atrophy of Spleen White Pulp and Correlates to Rescue of Forced Swim Test Immobility and Neurochemical Alterations Induced by Chronic Stress

Reelin, an extracellular matrix protein with putative antidepressant-like properties, becomes dysregulated by chronic stress. Improvement in cognitive dysfunction and depression-like behavior induced by chronic stress has been reported with both intrahippocampal and intravenous Reelin treatment but the mechanisms responsible are not clear. To determine if treatment with Reelin modifies chronic stress-induced dysfunction in immune organs and whether this relates to behavioral and/or neurochemical outcomes, spleens were collected from both male (n = 62) and female (n = 53) rats treated with daily corticosterone injections for three weeks that received Reelin or vehicle. Reelin was intravenously administered once on the final day of chronic stress, or repeatedly, with weekly treatments throughout chronic stress. Behavior was assessed during the forced swim test and the object-in-place test. Chronic corticosterone caused significant atrophy of the spleen white pulp, but treatment with a single shot of Reelin restored white pulp in both males and females. Repeated Reelin injections also resolved atrophy in females. Correlations were observed between recovery of white pulp atrophy and recovery of behavioral deficits and expression of both Reelin and glutamate receptor 1 in the hippocampus, supporting a role of the peripheral immune system in the recovery of chronic stress-induced behaviors following treatment with Reelin. Our data adds to research indicating Reelin could be a valuable therapeutic target for chronic stress-related disorders including major depression.

Multi-omic modeling of antidepressant response implicates dynamic immune and inflammatory changes in individuals who respond to treatment

BACKGROUND

Major depressive disorder (MDD) is a leading cause of disability worldwide, and is commonly treated with antidepressant drugs (AD). Although effective, many patients fail to respond to AD treatment, and accordingly identifying factors that can predict AD response would greatly improve treatment outcomes. In this study, we developed a machine learning tool to integrate multi-omic datasets (gene expression, DNA methylation, and genotyping) to identify biomarker profiles associated with AD response in a cohort of individuals with MDD.

MATERIALS AND METHODS

Individuals with MDD (N = 111) were treated for 8 weeks with antidepressants and were separated into responders and non-responders based on the Montgomery-Åsberg Depression Rating Scale (MADRS). Using peripheral blood samples, we performed RNA-sequencing, assessed DNA methylation using the Illumina EPIC array, and performed genotyping using the Illumina PsychArray. To address this rich multi-omic dataset with high dimensional features, we developed integrative Geneset-Embedded non-negative Matrix factorization (iGEM), a non-negative matrix factorization (NMF) based model, supplemented with auxiliary information regarding gene sets and gene-methylation relationships. In particular, we factorize the subjects by features (i.e., gene expression or DNA methylation) into subjects-by-factors and factors-by-features. We define the factors as the meta-phenotypes as they represent integrated composite scores of the molecular measurements for each subject.

RESULTS

Using our model, we identified a number of meta-phenotypes which were related to AD response. By integrating geneset information into the model, we were able to relate these meta-phenotypes to biological processes, including a meta-phenotype related to immune and inflammatory functions as well as other genes related to depression or AD response. The meta-phenotype identified several genes including immune interleukin 1 receptor like 1 (IL1RL1) and interleukin 5 receptor (IL5) subunit alpha (IL5RA), AKT/PIK3 pathway related phosphoinositide-3-kinase regulatory subunit 6 (PIK3R6), and sphingomyelin phosphodiesterase 3 (SMPD3), which has been identified as a target of AD treatment.

CONCLUSIONS

The derived meta-phenotypes and associated biological functions represent both biomarkers to predict response, as well as potential new treatment targets. Our method is applicable to other diseases with multi-omic data, and the software is open source and available on Github (https://github.com/li-lab-mcgill/iGEM).

Higher Concentration of Adrenocorticotropic Hormone Predicts Post-Stroke Depression

Background

Post-stroke depression (PSD) is the most common neuropsychiatric complication after stroke, seriously affecting the quality of survivors’ life. As one of the important causes of PSD, neuroendocrine mechanism has been widely studied in recent years. The main objective of this study was to investigate the relationship between adrenocorticotropic hormone (ACTH) on admission and PSD at 3 months.

Methods

This is a hospital-based prospective cohort study, which was conducted at three independent hospitals (Tongji Hospital, Wuhan First Hospital and Wuhan Central Hospital) between August 2018 and June 2019. A total of 768 ischemic stroke patients were finally eligible for analysis and categorized into equal tertiles according to the distribution of ACTH and the number of patients. The χ²-test, Mann–Whitney U-test and Kruskal–Wallis test were used to check for statistical significance. And restricted cubic spline (RCS) regression model was used to explore the non-linear relationship between continuous ACTH levels and PSD at 3 months.

Results

The optimal cut-off points of ACTH were as follows: (T1) 0.32–20.55 pg/mL, (T2) 20.56–39.79 pg/mL, (T3) 39.80–143.40 pg/mL. A total of 305 patients (39.7%) were diagnosed as PSD at 3 months follow-up. Significant differences were found between the PSD and non-PSD groups in ACTH concentration (P = 0.001). After adjustment for all conventional confounders, the odds ratios of PSD were 1.735 (95% CI = 1.176–2.560, P = 0.005) for the highest tertile of ACTH and 1.496 (95% CI = 1.019–2.194, P = 0.040) for the middle tertile of ACTH, as compared with the lowest tertile. In multiple-adjusted RCS regression, continuous ACTH showed saturation effect relation with PSD risk after 31.02 pg/mL (P for nonlinear = 0.0143).

Conclusion

Higher ACTH level on admission is a significant and independent biomarker to predict the development of PSD at 3 months follow-up. Besides, saturation effect was revealed even if the underlying mechanism is unclear. For stroke patients, doctors should pay attention to the baseline ACTH for screening high-risk PSD in clinical practice.

Is (R)-ketamine a Potential Therapeutic Agent for Treatment-Resistant Depression with Less Detrimental Side Effects? A Review of Molecular Mechanisms Underlying Ketamine and its Enantiomers

Approximately one-third of individuals with major depressive disorder are resistant to conventional antidepressants (i.e., monoamine-based therapies), and, even among respondents, a proper therapeutic effect may require weeks of treatment. Ketamine, a racemic mixture of the two enantiomers, (R)-ketamine and (S)-ketamine, is an N-methyl-d-aspartate receptor (NMDAR) antagonist and has been shown to have rapid-acting antidepressant properties in patients with treatment-resistant depression (TRD). Although (R)-ketamine has a lower affinity for NMDAR, it presents greater potency and longer-lasting antidepressant properties, with no major side effects, than racemic ketamine or (S)-ketamine in preclinical findings. Thereby, ketamine and its enantiomers have not only an antagonistic effect on NMDAR but also a strong synaptogenic-modulatory effect, which is impaired in TRD pathophysiology. In this review, we summarize the current evidence regarding the modulation of neurotransmission, neuroplasticity, and neural network activity as putative mechanisms of these rapid-acting antidepressants, highlighting differences on intracellular signaling pathways of synaptic proteins such as mammalian target of rapamycin (mTOR), extracellular signal-regulated kinase (ERK) and brain-derived neurotrophic factor (BDNF). In addition, we discuss probable mechanisms involved in the side effects of ketamine and its enantiomers.

A Comprehensive Analysis of Unique and Recurrent Copy Number Variations in Alzheimer's Disease and its Related Disorders

BACKGROUND

Copy number variations (CNVs) play an important role in the genetic etiology of various neurological disorders, including Alzheimer's disease (AD). Type 2 diabetes mellitus (T2DM) and major depressive disorder (MDD) were shown to have share mechanisms and signaling pathways with AD.

OBJECTIVE

We aimed to assess CNVs regions that may harbor genes contributing to AD, T2DM, and MDD in 67 Saudi familial and sporadic AD patients, with no alterations in the known genes of AD and genotyped previously for APOE.

METHODS

DNA was analyzed using the CytoScan-HD array. Two layers of filtering criteria were applied. All the identified CNVs were checked in the Database of Genomic Variants (DGV).

RESULTS

A total of 1086 CNVs (565 gains and 521 losses) were identified in our study. We found 73 CNVs harboring genes that may be associated with AD, T2DM or MDD. Nineteen CNVs were novel. Most importantly, 42 CNVs were unique in our studied cohort existing only in one patient. Two large gains on chromosomes 1 and 13 harbored genes implicated in the studied disorders. We identified CNVs in genes that encode proteins involved in the metabolism of amyloid-β peptide (AGRN, APBA2, CR1, CR2, IGF2R, KIAA0125, MBP, RER1, RTN4R, VDR and WISPI) or Tau proteins (CACNAIC, CELF2, DUSP22, HTRA1 and SLC2A14).

CONCLUSION

The present work provided information on the presence of CNVs related to AD, T2DM, and MDD in Saudi Alzheimer's patients.

Inter-individual differences in immune profiles of outbred rats screened for an emotional reactivity phenotype

Inter-individual differences in emotional reactivity predict susceptibility versus resilience to mood pathology. Using experimentally-naïve outbred rats that vary in locomotor reactivity to the mild stress of an inescapable novel environment [i.e., top and bottom 1/3rd of the population identified as high responders (HR) and low responders (LR) respectively], we determined baseline variations in immune functions. Innate and adaptive immune responses vary basally in LRHR rats, namely a shift towards TH1 in LRs and TH2 in HRs was observed. These inter-individual variations in immune profiles in LRHRs could have significant implications in mood alterations and immune reactivity to microbes and cancer.

Abnormal expression of colony stimulating factor 1 receptor (CSF1R) and transcription factor PU.1 (SPI1) in the spleen from patients with major psychiatric disorders: A role of brain-spleen axis

BACKGROUND

The colony stimulating factor 1 receptor (CSF1R) regulates microglia/macrophage proliferation, differentiation and survival; however, the precise role of this protein in psychiatric disorders is unknown. CSF1R is also known to interact with the transcription factor PU.1 (SPI1). Here we studied whether the expressions of CSF1R and SPI1 are altered in the postmortem samples (parietal cortex, cerebellum, spleen) from patients with major psychiatric disorders.

METHODS

Protein expression of CSF1R and SPI1 in the parietal cortex, cerebellum and spleen from control, major depressive disorder (MDD), schizophrenia (SZ), and bipolar disorder (BD) groups was measured.

RESULTS

Levels of CSF1R in the spleen, but not cerebellum and parietal cortex, from MDD and SZ groups were significantly lower than the control group. There was a positive correlation between CSF1R levels in the spleen and CSF1R levels in the parietal cortex in the all subjects from four groups. Furthermore, levels of SPI1 in the cerebellum and spleen from MDD and SZ groups were significantly higher than the control group. Levels of SPI1 in the parietal cortex were not different among the four groups. Interestingly, there was a negative correlation between CSF1R and SPI1 levels in the spleen of the all subjects from four groups. There was also a negative correlation between CSF1R and SPI1 levels in the spleen of MDD group.

LIMITATIONS

The small number in each group may limit our interpretation.

CONCLUSIONS

Abnormalities in CSF1R and SPI1 in the brain-spleen axis might, in part, play a role in the pathophysiology of MDD.

Dysfunction of inflammation-resolving pathways is associated with postoperative cognitive decline in elderly mice

BACKGROUND

Postoperative cognitive dysfunction (POCD) refers to a reversible, perioperative mental disorder. POCD increases the likelihood of postoperative complications and the risk for postoperative mortality, typically among elderly patients (age 65 or older). The importance of the cholinergic anti-inflammatory pathway (CAP) in resolving neuro-inflammatory and cognitive decline caused by sterile trauma has been recognized. We speculate that the POCD in elderly mice is associated with dysfunction of CAP.

METHODS

Mice were assigned to several groups (n = 5 in each group): AM (adult mice) Sham, AM (adult mice) Surgery, EM (elderly mice) Sham, EM (elderly mice) Surgery, and EMP (elderly mice with PNU) Surgery. At 24 h after surgery, assessed the cognitive levels. Pro-inflammatory cytokines in peripheral blood and splenic monocytes (TNF-α, IL-6 and IL-10) were assessed by ELISA and qPCR. Levels of M2 macrophages in hippocampus were visualized by immunofluorescence. Detecting CD11b/c⁺α7 nAChR⁺ cells in the spleens with flow cytometry.

RESULTS

At postoperative 24 h, elderly mice exhibited significantly increased POCD compared with adult mice. The proinflammatory factor TNF-α and IL-6 were higher among elderly surgery mice (EM) compared with adult surgery (AM) and elderly-P surgery mice (EM-P); the anti-inflammatory factor IL-10 and M2 macrophages were lower among EM surgery mice compared with AM surgery and EM-P surgery mice. The CD11b/c⁺α7 nAChR⁺ population of splenocytes was reduced in the EM surgery mice.

CONCLUSIONS

The exaggerated and persistent cognitive decline and inflammatory response among elderly mice were associated with dysfunction of CAP, and these phenomena were reversed by α7nAch receptor agonists.

The clinical significance of collagen family gene expression in esophageal squamous cell carcinoma

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is a subtype of esophageal cancer with high incidence and mortality. Due to the poor 5-year survival rates of patients with ESCC, exploring novel diagnostic markers for early ESCC is emergent. Collagen, the abundant constituent of extracellular matrix, plays a critical role in tumor growth and epithelial-mesenchymal transition. However, the clinical significance of collagen genes in ESCC has been rarely studied. In this work, we systematically analyzed the gene expression of whole collagen family in ESCC, aiming to search for ideal biomarkers.

METHODS

Clinical data and gene expression profiles of ESCC patients were collected from The Cancer Genome Atlas and the gene expression omnibus databases. Bioinformatics methods, including differential expression analysis, survival analysis, gene sets enrichment analysis (GSEA) and co-expression network analysis, were performed to investigate the correlation between the expression patterns of 44 collagen family genes and the development of ESCC.

RESULTS

A total of 22 genes of collagen family were identified as differentially expressed genes in both the two datasets. Among them, COL1A1, COL10A1 and COL11A1 were particularly up-regulated in ESCC tissues compared to normal controls, while COL4A4, COL6A5 and COL14A1 were notably down-regulated. Besides, patients with low COL6A5 expression or high COL18A1 expression showed poor survival. In addition, a 7-gene prediction model was established based on collagen gene expression to predict patient survival, which had better predictive accuracy than the tumor-node-metastasis staging based model. Finally, GSEA results suggested that collagen genes might be tightly associated with PI3K/Akt/mTOR pathway, p53 pathway, apoptosis, cell cycle, etc.

CONCLUSION

Several collagen genes could be potential diagnostic and prognostic biomarkers for ESCC. Moreover, a novel 7-gene prediction model is probably useful for predicting survival outcomes of ESCC patients. These findings may facilitate early detection of ESCC and help improves prognosis of the patients.