Image processing and supervised machine learning for retinal microglia characterization in senescence

Choi, Soyoung; Hill, Daniel; Young, J. A.; Cordeiro, M. Francesca

doi:10.1016/bs.mcb.2022.12.008

Cited by 3 publications

(4 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In agreement with Chen et al [32] who showed increased myeloid cell phagocytosis in humanized APOE3Ch, we show that ApoeCh produces upregulation of several genes associated with autophagy/endocytosis and antigen presentation ( Mid1, Cd74, H2-Aa, H2-Ab1, Spp1, Gpnmb , Cst7 ) in 5xFAD mice. A recent report provides evidence that autophagy plays an important role in regulating microglial activation (i.e., DAM phenotype induction) and that deficiency in autophagy leads to senescence, reduces DAMs, impairs Aβ clustering around plaques, and aggravates AD pathology [65]. Given the reduction in amyloid-associated damage, these data implicate a neuroprotective role of enhanced DAM/microglial reactivity to amyloid pathology with the introduction of ApoeCh in 5xFAD mice.…”

Section: Discussionmentioning

confidence: 97%

APOE Christchurch enhances a disease-associated microglial response to plaque but suppresses response to tau pathology

Tran,

Kwang,

Gomez-Arboledas

et al. 2024

Preprint

View full text Add to dashboard Cite

BackgroundApolipoprotein E ε4 (APOE4) is the strongest genetic risk factor for late-onset Alzheimer’s disease (LOAD). A recent case report identified a rare variant in APOE, APOE3-R136S (Christchurch), proposed to confer resistance to autosomal dominant Alzheimer’s Disease (AD). However, it remains unclear whether and how this variant exerts its protective effects.MethodsWe introduced the R136S variant into mouseApoe(ApoeCh) and investigated its effect on the development of AD-related pathology using the 5xFAD model of amyloidosis and the PS19 model of tauopathy. We used immunohistochemical and biochemical analysis along with single-cell spatial transcriptomics and proteomics to explore the impact of theApoeChvariant on AD pathological development and the brain’s response to plaques and tau.ResultsIn 5xFAD mice,ApoeChenhances a Disease-Associated Microglia (DAM) phenotype in microglia surrounding plaques, and reduces plaque load, dystrophic neurites, and plasma neurofilament light chain. By contrast, in PS19 mice,ApoeChsuppresses the microglial and astrocytic responses to tau-laden neurons and does not reduce tau accumulation or phosphorylation, but partially rescues tau-induced synaptic and myelin loss. We compared how microglia responses differ between the two mouse models to elucidate the distinct DAM signatures induced byApoeCh. We identified upregulation of antigen presentation-related genes in the DAM response in a PS19 compared to a 5xFAD background, suggesting a differential response to amyloid versus tau pathology that is modulated by the presence ofApoeCh.ConclusionsThese findings highlight the ability of theApoeChvariant to modulate microglial responses based on the type of pathology, enhancing DAM reactivity in amyloid models and dampening neuroinflammation to promote protection in tau models. This suggests that the Christchurch variant’s protective effects likely involve multiple mechanisms, including changes in receptor binding and microglial programming.

show abstract

Section: Discussionmentioning

confidence: 97%

APOE Christchurch enhances a disease-associated microglial response to plaque but suppresses response to tau pathology

Tran,

Kwang,

Gomez-Arboledas

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…The positive correlation with Abeta42 and inverse correlation with pTau231 may indicate that acute activation of these pathways is beneficial after TBI, but this requires further investigation. Sequestosome1 (SQSTM1, also referred to as p62) mediated autophagy 51 is important for peripheral myeloid cell differentiation 52 and microglial functions, including degradation of amyloid plaques 53 . Raised SQSTM1 in acute TBI was associated with less axonal injury, as measured on DTI, supporting a role for post-injury autophagy in mitigating axonal injury.…”

Section: Discussionmentioning

confidence: 99%

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

Li,

Kodosaki,

Heselgrave

et al. 2024

Preprint

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

“…Deletion of autophagy gene Atg7 led to impaired ability of microglia to engage Aβ plaques and promoted microglial senescence, which was reversed by administration of senolytic drugs. 114 Nevertheless, the transcriptional states of microglia remain incompletely understood, as microglia may respond to multiple pathological stimuli in the brain simultaneously. For instance, microglia adopt two distinct DAM phenotypes when responding to amyloid pathology and myelin damage in 5xFAD mice with dysfunctional myelin (Cnp −/− 5xFAD mice), which may reflect the comorbid state of the aged brain.…”

Section: Roles Of Microglia In Neurodegenerative Diseasesmentioning

confidence: 99%

“…151 Autophagy deficiency disrupts microglial response to Aβ by inhibiting DAM development and inducing microglial senescence. 114 Moreover, the loss of functional microglial autophagy is deleterious as it exacerbates tau pathology and spreading in PS19 tau transgenic mice, 152 as well as contributes to elevated release of proinflammatory cytokines and NLR family pyrin domain-containing 3 (NLRP3) inflammasome activation in Becn1 +/− APP/PS1 mice. 153 Activated microglia also release chemokines that disrupt neuronal autophagy by altering the neuronal C-C chemokine receptor type 5 (CCR5)-mTORC1-autophagy pathway in HD and tauopathy mice.…”

Section: Roles Of Microglia In Neurodegenerative Diseasesmentioning

confidence: 99%

Microbiota–gut–brain axis and its therapeutic applications in neurodegenerative diseases

Loh,

Mak,

Tan

et al. 2024

Sig Transduct Target Ther

114

View full text Add to dashboard Cite

The human gastrointestinal tract is populated with a diverse microbial community. The vast genetic and metabolic potential of the gut microbiome underpins its ubiquity in nearly every aspect of human biology, including health maintenance, development, aging, and disease. The advent of new sequencing technologies and culture-independent methods has allowed researchers to move beyond correlative studies toward mechanistic explorations to shed light on microbiome–host interactions. Evidence has unveiled the bidirectional communication between the gut microbiome and the central nervous system, referred to as the “microbiota–gut–brain axis”. The microbiota–gut–brain axis represents an important regulator of glial functions, making it an actionable target to ameliorate the development and progression of neurodegenerative diseases. In this review, we discuss the mechanisms of the microbiota–gut–brain axis in neurodegenerative diseases. As the gut microbiome provides essential cues to microglia, astrocytes, and oligodendrocytes, we examine the communications between gut microbiota and these glial cells during healthy states and neurodegenerative diseases. Subsequently, we discuss the mechanisms of the microbiota–gut–brain axis in neurodegenerative diseases using a metabolite-centric approach, while also examining the role of gut microbiota-related neurotransmitters and gut hormones. Next, we examine the potential of targeting the intestinal barrier, blood–brain barrier, meninges, and peripheral immune system to counteract glial dysfunction in neurodegeneration. Finally, we conclude by assessing the pre-clinical and clinical evidence of probiotics, prebiotics, and fecal microbiota transplantation in neurodegenerative diseases. A thorough comprehension of the microbiota–gut–brain axis will foster the development of effective therapeutic interventions for the management of neurodegenerative diseases.

show abstract

Image processing and supervised machine learning for retinal microglia characterization in senescence

Cited by 3 publications

References 26 publications

APOE Christchurch enhances a disease-associated microglial response to plaque but suppresses response to tau pathology

APOE Christchurch enhances a disease-associated microglial response to plaque but suppresses response to tau pathology

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

Microbiota–gut–brain axis and its therapeutic applications in neurodegenerative diseases

Contact Info

Product

Resources

About