Microglia activation in postmortem brains with schizophrenia demonstrates distinct morphological changes between brain regions

Abstract

Schizophrenia (SCZ) is a psychiatric disorder that can include symptoms of disorganized speech and thoughts with uncertain underlying mechanisms possibly linked to over-activated microglia. In this study, we used brain samples from sixteen donors with SCZ and thirteen control donors to assess the differential activation of microglia by quantifying density and 3D reconstruction of microglia stained with ionized calcium-binding adaptor molecule-1 (Iba1). Our samples consisted of sections from the frontal, temporal, and cingulate cortical gray matter, subcortical white matter regions (SCWM), and included the anterior corpus callosum. In the first series of studies, we performed a density

Gcm: a novel anti-inflammatory transcriptional cascade conserved from flies to humans

“…To further corroborate these findings, we examined microglial cell morphology in conditional mGcm2 icKO and control mice in LPC demyelinated lesions, in vivo . Spinal cord sections throughout the demyelinated lesions were labelled with the microglial marker Iba1 and microglia morphology was evaluated with VisioPharm (57). In line with the above data, the number of ramifications point per microglial cell decreases significantly in mGcm2 icKO compared to controls, specifically in demyelinated lesions at 7 and 14 dpi ( Figure 6J ).…”

Emerging Evidence for the Widespread Role of Glutamatergic Dysfunction in Neuropsychiatric Diseases

“…Similar to other immune-priming processes, the activation and release of mediators by microglia do not occur until a subsequent immune challenge presents, often years later. Activation involving toxin and mediator release causes dendritic and axonal destruction, especially of the frontal cortex and temporal areas [ 132 ]. The process probably occurs in the years prior to overt symptoms appearing, as there is clear evidence of long-standing destruction of brain networks and neuronal loss by the time of diagnosis [ 133 ].…”

A novel automated morphological analysis of microglia activation using a deep learning assisted model

“…Furthermore, the increased sampling capacity of these microglia activation models relative to previously published methods [18] expanded the quantification of Iba1+ microglia to a scale more commonly applied in other areas of bioinformatics such as proteomics [44]. While there are other automated methods of microglia morphology quantification [16,19,45] and potentially more sophisticated study-specific AI models [20][21][22]46], the methods we now describe offer a streamlined workflow for meaningful results and an accessibility to flexible deep learning tools that could be appealing to researchers without formal computer science training.…”

“…Currently, quantification of the area/perimeter ratio is achieved using ImageJ or FIJI software, sometimes with the Sholl analysis plugin [16,17]. Other automated and semiautomated methods often require custom designed software or scripts that can be challenging to apply across research environments [18][19][20]. However, many of these methods require manual cell imaging at high magnifications on bright field or confocal microscopes, which can increase the duration of time needed to complete a full analysis and potentially introduce a sampling bias.…”