Fundamental Neurochemistry Review: Microglial immunometabolism in traumatic brain injury

Strogulski, Nathan R.; Portela, Luis V.; Polster, Brian M.; Loane, David J.

doi:10.1111/jnc.15959

Cited by 11 publications

(2 citation statements)

References 239 publications

(411 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Cell metabolism changes are also important in TBI pathophysiology 54 . Experimental studies have found reduced astrocytic malate dehydrogenase 1 (MDH1) expression in concussive TBI models 55 and increased thalamic expression in blast TBI models 56 .…”

Section: Discussionmentioning

confidence: 99%

High-dimensional proteomic analysis for pathophysiological classification of Traumatic Brain Injury

Li,

Kodosaki,

Heselgrave

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

Pathophysiology and outcomes after Traumatic Brain Injury (TBI) are complex and highly heterogenous. Current classifications are uninformative about pathophysiology, which limits prognostication and treatment. Fluid-based biomarkers can identify pathways and proteins relevant to TBI pathophysiology. Proteomic approaches are well suited to exploring complex mechanisms of disease, as they enable sensitive assessment of an expansive range of proteins. We used novel high-dimensional, multiplex proteomic assays to study changes in plasma protein expression in acute moderate-severe TBI. We analysed samples from 88 participants in the longitudinal BIO-AX-TBI cohort (n=38 TBI within 10 days of injury, n=22 non-TBI trauma, n=28 non-injured controls) on two platforms: Alamar NULISA(TM) CNS Diseases and OLINK(R) Target 96 Inflammation. Participants also had data available from Simoa(R) (neurofilament light, GFAP, total tau, UCHL1) and Millipore (S100B). The Alamar panel assesses 120 proteins, most of which have not been investigated before in TBI, as well as proteins, such as GFAP, which differentiate TBI from non-injured and non-TBI trauma controls. A subset (n=29 TBI, n=24 non-injured controls) also had subacute 3T MRI measures of lesion volume and white matter injury (fractional anisotropy, scanned 10 days to 6 weeks after injury). Differential Expression analysis identified 16 proteins with TBI-specific significantly different plasma expression. These were neuronal markers (calbindin2, UCHL1, visinin-like protein1), astroglial markers (S100B, GFAP), tau and other neurodegenerative disease proteins (total tau, pTau231, PSEN1, amyloid beta42, 14-3-3γ), inflammatory cytokines (IL16, CCL2, ficolin2), cell signalling (SFRP1), cell metabolism (MDH1) and autophagy related (sequestome1) proteins. Acute plasma levels of UCHL1, PSEN1, total tau and pTau231 correlated with subacute lesion volume, while sequestome1 was correlated with whole white matter skeleton fractional anisotropy and CCL2 was inversely correlated with corpus callosum FA. Neuronal, astroglial, tau and neurodegenerative proteins correlated with each other, and IL16, MDH1 and sequestome1. Clustering (k means) by acute protein expression identified 3 TBI subgroups which had differential injury patterns, but did not differ in age or outcome. Proteins that overlapped on two platforms had excellent (r>0.8) correlations between values. We identified TBI-specific changes in acute plasma levels of proteins involved in amyloid processing, inflammatory and cellular processes such as autophagy. These changes were related to patterns of injury, thus demonstrating that processes previously only studied in animal models are also relevant in human TBI pathophysiology. Our study highlights the potential of proteomic analysis to improve the classification and understanding of TBI pathophysiology, with implications for prognostication and treatment development.

show abstract

Section: Discussionmentioning

confidence: 99%

High-dimensional proteomic analysis for pathophysiological classification of Traumatic Brain Injury

Li,

Kodosaki,

Heselgrave

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Inflammation within the central nervous system (CNS) is an integral feature of neurodegenerative diseases as well as neurotrauma [1][2][3][4]. Although this inflammation may initially be beneficial, chronic neuroinflammation can escalate or worsen neuropathology and cause disease progression.…”

Section: Introductionmentioning

confidence: 99%

Telmisartan Reduces LPS-Mediated Inflammation and Induces Autophagy of Microglia

Affram,

Janatpour,

Shanbhag

et al. 2024

Neuroglia

View full text Add to dashboard Cite

Background: Chronic neuroinflammation mediated by persistent microglial activation is strongly linked to neurodegeneration. Therefore, targeting microglial activation could be beneficial in treating neurodegenerative disorders. Angiotensin receptor blockers (ARBs), commonly prescribed for high blood pressure, exhibit prominent anti-inflammatory effects in the brain and are considered potential therapies for neurodegenerative diseases and neurotrauma. Although all ARBs are angiotensin II receptor type I antagonists, some ARBs act through other signaling pathways, allowing for multiple mechanisms of action. The anti-inflammatory mechanisms of ARBs are not well understood. Methods: In this study, we compared eight different FDA-approved ARBs for their ability to reduce the LPS stimulation of primary microglia or BV2 cells through analyses of nitric oxide production, reactive oxygen species generation, and the mRNA of proinflammatory cytokines. Finding specific and unique effects of telmisartan, we interrogated signaling pathways and other downstream effectors of telmisartan activity on microglia. Results: Our findings indicate that telmisartan showed the greatest efficacy in reducing the LPS induction of reactive oxygen species (ROS) and nitric oxide production in microglia. Uniquely amongst ARBs, telmisartan activated AMPK phosphorylation and inhibited mTOR phosphorylation. Telmisartan’s anti-inflammatory activity was partially inhibited by the AMPK inhibitor compound C. Furthermore, telmisartan uniquely induced markers of autophagy in microglia through an AMPK–mTOR–autophagy pathway. Telmisartan also reduced microglial viability. Telmisartan’s cytotoxicity was partially ameliorated by an autophagy inhibitor and a pan-caspase inhibitor, indicating a link between microglial autophagy and apoptosis. Conclusions: We conclude that telmisartan has unique properties relative to other ARBs, including potent anti-inflammatory actions and an induction of microglial autophagy, which may enable specific therapeutic uses.

show abstract

Soluble Urokinase-Type Plasminogen Activator Receptor and Inflammatory Biomarker Response with Prognostic Significance after Acute Neuronal Injury – a Prospective Cohort Study

Sajanti,

Hellström,

Bennett

et al. 2024

Inflammation

View full text Add to dashboard Cite

Aneurysmal subarachnoid hemorrhage (aSAH), ischemic stroke (IS), and traumatic brain injury (TBI) are severe conditions impacting individuals and society. Identifying reliable prognostic biomarkers for predicting survival or recovery remains a challenge. Soluble urokinase type plasminogen activator receptor (suPAR) has gained attention as a potential prognostic biomarker in acute sepsis. This study evaluates suPAR and related neuroinflammatory biomarkers in serum for brain injury prognosis. This prospective study included 31 aSAH, 30 IS, 13 TBI, and three healthy controls (n = 77). Serum samples were collected on average 5.9 days post-injury, analyzing suPAR, IL-1β, cyclophilin A, and TNFα levels using ELISA. Outcomes were assessed 90 days post-injury with the modified Rankin Scale (mRS), categorized as favorable (mRS 0-2) or unfavorable (mRS 3-6). Statistical analyses included 2-tailed t-tests, Pearson’s correlations, and machine learning linear discriminant analysis (LDA) for biomarker combinations. Elevated suPAR levels were found in brain injury patients compared to controls (p = 0.017). Increased suPAR correlated with unfavorable outcomes (p = 0.0018) and showed prognostic value (AUC = 0.66, p = 0.03). IL-1β levels were higher in the unfavorable group (p = 0.0015). LDA combinatory analysis resulted a fair prognostic accuracy with canonical equation = 0.775[suPAR] + 0.667[IL1-β] (AUC = 0.77, OR 0.296, sensitivity 93.1%, specificity 53.1%, p = 0.0007). No correlation was found between suPAR and CRP or infection status. Elevated suPAR levels in acute brain injury patients were associated with poorer outcomes, highlighting suPAR’s potential as a prognostic biomarker across different brain injury types. Combining IL-1β with suPAR improved prognostic accuracy, supporting a multimodal biomarker approach for predicting outcomes.

show abstract

Fundamental Neurochemistry Review: Microglial immunometabolism in traumatic brain injury

Cited by 11 publications

References 239 publications

High-dimensional proteomic analysis for pathophysiological classification of Traumatic Brain Injury

High-dimensional proteomic analysis for pathophysiological classification of Traumatic Brain Injury

Telmisartan Reduces LPS-Mediated Inflammation and Induces Autophagy of Microglia

Soluble Urokinase-Type Plasminogen Activator Receptor and Inflammatory Biomarker Response with Prognostic Significance after Acute Neuronal Injury – a Prospective Cohort Study

Contact Info

Product

Resources

About