Traumatic brain injury (TBI) and Alzheimer's disease (AD) are diseases during which the fine-tuned autoregulation of the brain is lost. Despite the stark contrast in their causal mechanisms, both TBI and AD are conditions which elicit a neuroinflammatory response that is coupled with physical, cognitive, and affective symptoms. One commonly reported symptom in both TBI and AD patients is disturbed sleep. Sleep is regulated by circadian and homeostatic processes such that pathological inflammation may disrupt the chemical signaling required to maintain a healthy sleep profile. In this way, immune system activation can influence sleep physiology. Conversely, sleep disturbances can exacerbate symptoms or increase the risk of inflammatory/neurodegenerative diseases. Both TBI and AD are worsened by a chronic pro-inflammatory microenvironment which exacerbates symptoms and worsens clinical outcome. Herein, a positive feedback loop of chronic inflammation and sleep disturbances is initiated. In this review, the bidirectional relationship between sleep disturbances and inflammation is discussed, where chronic inflammation associated with TBI and AD can lead to sleep disturbances and exacerbated neuropathology. The role of microglia and cytokines in sleep disturbances associated with these diseases is highlighted. The proposed sleep and inflammation-mediated link between TBI and AD presents an opportunity for a multifaceted approach to clinical intervention.
Few translational studies have examined how age-at-injury affects the glial response to traumatic brain injury (TBI). We hypothesized that rats injured at post-natal day (PND) 17 would exhibit a greater glial response, that would persist into early adulthood, compared to rats injured at PND35. PND17 and PND35 rats (n = 75) received a mild to moderate midline fluid percussion injury or sham surgery. In three cortical regions [peri-injury, primary somatosensory barrel field (S1BF), perirhinal], we investigated the glial response relative to age-at-injury (PND17 or PND35), time post-injury (2 hours, 1 day, 7 days, 25 days, or 43 days), and post-natal age, such that rats injured at PND17 or PND35 were compared at the same post-natal-age (e.g., PND17 + 25D post-injury = PND42; PND35 + 7D post-injury = PND42). We measured Iba1 positive microglia cells (area, perimeter) and quantified their activation status using skeletal analysis (branch length/cell, mean processes/cell, cell abundance). GFAP expression was examined using immunohistochemistry and pixel analysis. Data were analyzed using Bayesian multivariate multi-level models. Independent of age-at-injury, TBI activated microglia (shorter branches, fewer processes) in the S1BF and perirhinal cortex with more microglia in all regions compared to uninjured shams. TBI-induced microglial activation (shorter branches) was sustained in the S1BF into early adulthood (PND60). Overall, PND17 injured rats had more microglial activation in the perirhinal cortex than PND35 injured rats. Activation was not confounded by age-dependent cell size changes, and microglial cell body sizes were similar between PND17 and PND35 rats. There were no differences in astrocyte GFAP expression. Increased microglial activation in PND17 brain-injured rats suggests that TBI upregulates the glial response at discrete stages of development. Age-at-injury and aging with an injury are translationally important because experiencing a TBI at an early age may trigger an exaggerated glial response.
Microglial morphology is used to measure neuroinflammation and pathology. For reliable inference, it is critical that microglial morphology is accurately quantified and that results can be easily interpreted and compared across studies and laboratories. The process through which microglial morphology is quantified is a key methodological choice and little is known about how this choice may bias conclusions. We applied five of the most commonly used ImageJ-based methods for quantifying the microglial morphological response to a stimulus to identical photomicrographs and individual microglial cells isolated from these photomicrographs, which allowed for direct comparisons of results generated using these approaches. We found a lack of comparability across methods that analyzed full photomicrographs, with significant discrepancies in results among the five methods. Quantitative methods to analyze microglial morphology should be selected based on several criteria, and combinations of these methods may give the most biologically accurate representation of microglial morphology.
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