Neuroinflammation in Late-Onset Schizophrenia: Viewing from the Standpoint of the Microglia Hypothesis

System biology approaches to identify hub genes linked with ECM organization and inflammatory signaling pathways in schizophrenia pathogenesis

Schizophrenia (SZ) is a chronic and devastating mental illness that affects around 20 million individuals worldwide. Cognitive deficits and structural and functional changes of the brain, abnormalities of brain ECM components, chronic neuroinflammation, and devastating clinical manifestation during SZ are likely etiological factors shown by affected individuals. However, the pathophysiological events associated with multiple regulatory pathways involved in the brain of this complex disorder are still unclear. This study aimed to develop a pipeline based on bioinformatics and systems biology approaches for identifying potential therapeutic targets involving possible biological mechanisms from SZ patients and healthy volunteers. About 420 overlapping differentially expressed genes (DEGs) from three RNA-seq datasets were identified. Gene ontology (GO), and pathways analysis showed several biological mechanisms enriched by the commonly shared DEGs, including extracellular matrix organization (ECM) organization, collagen fibril organization, integrin signaling pathway, inflammation mediated by chemokines and cytokines signaling pathway, and GABA-B receptor II and IL4 mediated signaling. Besides, 15 hub genes (FN1, COL1A1, COL3A1, COL1A2, COL5A1, COL2A1, COL6A2, COL6A3, MMP2, THBS1, DCN, LUM, HLA-A, HLA-C, and FBN1) were discovered by comprehensive analysis, which was mainly involved in the ECM organization and inflammatory signaling pathway. Furthermore, the miRNA target of the hub genes was analyzed with the random-forest-based approach software miRTarBase. In addition, the transcriptional factors and protein kinases regulating overlapping DEGs in SZ, namely, SUZ12, EZH2, TRIM28, TP53, EGR1, CSNK2A1, GSK3B, CDK1, and MAPK14, were also identified. The results point to a new understanding that the hub genes (fibronectin 1, collagen, matrix metalloproteinase-2, and lumican) in the ECM organization and inflammatory signaling pathways may be involved in the SZ occurrence and pathogenesis.

[Clinical and psychopathological characteristics of patients with late-onset schizophrenia and schizophrenia-like psychoses in clusters identified by biological parameters]

OBJECTIVE

To assess clinical and psychopathological characteristics of late-aged female patients with late-onset psychoses in clusters formed on the basis of biochemical and immunological blood parameters.

MATERIAL AND METHODS

We examined 59 women with schizophrenia and schizophrenia-like psychoses with onset after 40 years (ICD-10 F20, F22.8, F25, F23, F06.2), including 34 women with late-onset (40-60 years) and 25 with very late onset psychoses (after 60 years). At the time of hospitalization, a clinical/ psychopathological study was carried out using CGI-S, PANSS, CDSS, and HAMD-17, as well as the activities of glutathione reductase (GR) and glutathione-S-transferase (GT) have been determined in erythrocyte hemolysates, and the activities of leukocyte elastase (LE) and α1-proteinase inhibitor (α1-PI) have been assessed in blood plasma. Biochemical and immunological parameters have been also determined in 34 age-matched mentally healthy women.

RESULTS

Clustering by signs such as GR, GT, LE and α1-PI has yielded two clusters of objects (patients) significantly different in GT (p<0.0001), LE (p<0.0001), and α1-PI (p<0.001) activities. Relatively to the controls, in the cluster 1 patients, the activities of GST and α1-PI are increased, the activity of LE is decreased, whereas, in the cluster 2 patients, the activity of GR is decreased, and the activities of LE and α1-PI are increased. Cluster 1 patients differ from cluster 2 patients in greater severity of the condition (CGI-S, p=0.04) and higher total scores on PANSS subscales' items. Cluster 1 includes 76% of patients with very late onset. Different correlations between clinical and biological signs are found in two clusters.

CONCLUSION

The identified clusters have different clinical and psychopathological characteristics. Dividing patients into subgroups according to biochemical and immunological parameters is promising for the search for differentiated therapeutic approaches.

Serum Levels of Tumor Necrosis Factor-α and Vascular Endothelial Growth Factor in the Subtypes of Clinical High Risk Individuals: A Prospective Cohort Study

Introduction

Numerous studies have established the roles of inflammation and angioneurins in the pathogenesis of schizophrenia (SCZ). This study aimed to compare the serum levels of tumour necrosis factor (TNF)-α and vascular endothelial growth factor (VEGF) in patients at clinical high risk (CHR) for psychosis or SCZ at baseline and one year after treatment.

Methods

A total of 289 CHR participants from the Shanghai At Risk for Psychosis Extended Program (SHARP) were tracked for a year. They were divided into two and four subtypes based on symptom severity according to the Structured Interview for Prodromal Syndromes (SIPS) and received standard medical care. At baseline and one-year follow-up, TNF-α and VEGF were detected using enzyme-linked immunosorbent assay, and pathological features were assessed using the Global Assessment of Function (GAF) score.

Results

Baseline TNF-α levels did not differ significantly, while VEGF levels were lower in patients with more severe symptoms. VEGF showed a negative correlation with negative features, both overall (r = -0.212, p = 0.010) and in the subgroup with higher positive scores (r = -0.370, p = 0.005). TNF-α was positively correlated with negative symptoms in the subgroup with higher negative scores (r = 0.352, p = 0.002). A three-way multivariate analysis of variance demonstrated that participants in Subtype 1 of positive or negative symptoms performed better than those in Subtype 2, with significant main effects and interactions of group and both cytokines.

Discussion

TNF-α and VEGF levels are higher and lower, respectively, in CHR patients with more severe clinical symptoms, particularly negative symptoms, which point to a worsening inflammatory and vascular status in the brain.

Neuroinflammation: The Abused Concept

Scientific progress requires the relentless correction of errors and refinement of hypotheses. Clarity of terminology is essential for clarity of thought and proper experimental interrogation of nature. Therefore, the application of the same scientific term to different and even conflicting phenomena and concepts is not useful and must be corrected. Such abuse of terminology has happened and is still increasing in the case of "neuroinflammation," a term that until the 1990s meant classical inflammation affecting the central nervous system (CNS) and thereon was progressively used to mostly denote microglia activation. The resulting confusion is very wasteful and detrimental not only for scientists but also for patients, given the numerous failed clinical trials in acute and chronic CNS diseases over the last decade with "anti-inflammatory" drugs. Despite this failure, reassessments of the "neuroinflammation" concept are rare, especially considering the number of articles still using the term. This undesirable situation motivates this article. We review the origins and evolution of the term "neuroinflammation," discuss the unique tissue defense and repair strategies in the CNS, define CNS immunity, and emphasize the notion of gliopathies to help readdress, if not bury, the term "neuroinflammation" as it stands in the way of scientific progress.