Histopathology seminars

Yuankai Huo presents a computational workflow for turning whole-slide tissue images into quantitative, spatially resolved pathomics measurements. The session covers scalable feature extraction through spatial indexing, processing within computational regions, and matrix-based computation. It connects tissue morphology and spatial topology with biological and clinical outcomes, then considers generative artificial-intelligence methods for visualizing and interpreting correlated pathomics features. The emphasis is on scalable, explainable analysis for biomedical researchers.

Microglia are the resident CNS macrophages of the brain parenchyma. They have many and opposing roles in health and disease, ranging from inflammatory to anti-inflammatory and protective functions, depending on the developmental stage and the disease context. In Multiple Sclerosis, microglia are involved to important hallmarks of the disease, such as inflammation, demyelination, axonal damage and remyelination, however the exact mechanisms controlling their transformation towards a protective or devastating phenotype during the disease progression remains largely unknown until now. We wish to understand how brain microglia respond to demyelinating insults and how their behaviour changes in recovery. To do so we developed a novel histopathological analysis approach in 3D and a cell-based analysis tool that when applied in the cuprizone model of demyelination revealed region- and disease- dependent changes in microglial dynamics in the brain grey matter during demyelination and remyelination. We now use similar approaches with the aim to unravel sensitive changes in microglial dynamics during neuroinflammation in the EAE model. Furthermore, we employ constitutive knockout and tamoxifen-inducible gene-targeting approaches, immunological techniques, genetics and bioinformatics and currently seek to clarify the specific role of the brain resident microglial NF-κB molecular pathway versus other tissue macrophages in EAE.

Epilepsy is one of the most common neurological diseases according to the World Health Organization (WHO) affecting around 70 million people worldwide [WHO]. Patients who suffer from epilepsy also suffer from a variety of neuro-psychiatric co-morbidities, which they can experience as crippling as the seizure condition itself. Adequate organization of cerebral white matter is utterly important for cognitive development. The failure of integration of neurologic function with cognition is reflected in neuro-psychiatric disease, such as autism spectrum disorder (ASD). However, in epilepsy we know little about the importance of white matter abnormalities in epilepsy-associated co-morbidities. Epilepsy surgery is an important therapy strategy in patients where conventional anti-epileptic drug treatment fails . On histology of the resected brain samples, malformations of cortical development (MCD) are common among the epilepsy surgery population, especially focal cortical dysplasia (FCD) and tuberous sclerosis complex (TSC). Both pathologies are associated with constitutive activation of the mTOR pathway. Interestingly, some type of FCD is morphological similar to TSC cortical tubers including the abnormalities of the white matter. Hypomyelination with lack of myelin-producing cells, the oligodendrocytes, within the lesional area is a striking phenomenon. Impairment of the complex myelination process can have a major impact on brain function. In the worst case leading to distorted or interrupted neurotransmissions. It is still unclear whether the observed myelin pathology in epilepsy surgical specimens is primarily related to the underlying malformation process or is just a secondary phenomenon of recurrent epileptic seizures creating a toxic micro-environment which hampers myelin formation. Interestingly, mTORC1 has been implicated as key signal for myelination, thus, promoting the maturation of oligodendrocytes . These results, however, remain controversial. Regardless of the underlying pathophysiologic mechanism, alterations of myelin dynamics, depending on their severity, are known to be linked to various kinds of developmental disorders or neuropsychiatric manifestations.

Epilepsy is one of the most common neurological diseases according to the World Health Organization (WHO) affecting around 70 million people worldwide [WHO]. Patients who suffer from epilepsy also suffer from a variety of neuro-psychiatric co-morbidities, which they can experience as crippling as the seizure condition itself. Adequate organization of cerebral white matter is utterly important for cognitive development. The failure of integration of neurologic function with cognition is reflected in neuro-psychiatric disease, such as autism spectrum disorder (ASD). However, in epilepsy we know little about the importance of white matter abnormalities in epilepsy-associated co-morbidities. Epilepsy surgery is an important therapy strategy in patients where conventional anti-epileptic drug treatment fails . On histology of the resected brain samples, malformations of cortical development (MCD) are common among the epilepsy surgery population, especially focal cortical dysplasia (FCD) and tuberous sclerosis complex (TSC). Both pathologies are associated with constitutive activation of the mTOR pathway. Interestingly, some type of FCD is morphological similar to TSC cortical tubers including the abnormalities of the white matter. Hypomyelination with lack of myelin-producing cells, the oligodendrocytes, within the lesional area is a striking phenomenon. Impairment of the complex myelination process can have a major impact on brain function. In the worst case leading to distorted or interrupted neurotransmissions. It is still unclear whether the observed myelin pathology in epilepsy surgical specimens is primarily related to the underlying malformation process or is just a secondary phenomenon of recurrent epileptic seizures creating a toxic micro-environment which hampers myelin formation. Interestingly, mTORC1 has been implicated as key signal for myelination, thus, promoting the maturation of oligodendrocytes . These results, however, remain controversial. Regardless of the underlying pathophysiologic mechanism, alterations of myelin dynamics, depending on their severity, are known to be linked to various kinds of developmental disorders or neuropsychiatric manifestations.

Glymphatic perivascular exchange is supported by the astroglial water channel aquaporin-4 (AQP4), which localizes to perivascular astrocytic endfeet surrounding the cerebral vasculature. In aging mice, impairment of glymphatic function is associated with reduced perivascular AQP4 localization, yet whether these changes contribute to the development of neurodegenerative disease, such as Alzheimer’s disease (AD), remains unknown. Using post mortem human tissue, we evaluated perivascular AQP4 localization in the frontal cortical gray matter, white matter, and hippocampus of cognitively normal subjects and those with AD. Loss of perivascular and increasing cellular localization of AQP4 in the frontal gray matter was specifically associated with AD status, amyloid β (Aβ) and tau pathology, and cognitive decline in the early stages of disease. Using AAV-PHP.B to drive expression on non-perivascular AQP4 in wild type and Tg2576 (APPSwe, mouse model of Aβ deposition) mice, increased cellular AQP4 localization did not slow glymphatic function or change Aβ deposition. Using the Snta1 knockout line (which lacks perivascular AQP4 localization), we observed that loss AQP4 from perivascular endfeet slowed glymphatic function in wild type mice and accelerated Aβ plaque deposition in Tg2576 mice. These findings demonstrate that loss of perivascular AQP4 localization, and not increased cellular AQP4 localization, slows glymphatic function and promotes the development of AD pathology. To evaluate whether naturally occurring variation in the human AQP4 gene, or the alpha syntrophin (SNTA1), dystrobrevin (DTNA) or dystroglycan (DAG1) genes (whose products maintain perivascular AQP4 localization) confer risk for or protection from AD pathology or clinical progression, we evaluated 56 tag single nucleotide polymorphisms (SNPs) across these genes for association with CSF AD biomarkers, MRI measures of cortical and hippocampal atrophy, and longitudinal cognitive decline in the Alzheimer’s Disease Neuroimaging Initiative I (ADNI I) cohort. We identify 25 different significant associations between AQP4, SNTA1, DTNA, and DAG1 tag SNPs and phenotypic measures of AD pathology and progression. These findings provide complimentary human genetic evidence for the contribution of perivascular glymphatic dysfunction to the development of AD in human populations.

Age-associated dementias are neuropathologically characterized by the identification of hallmark intracellular and extracellular deposition of proteins, i.e., hyperphosphorylated-tau, amyloid-β, and α-synuclein, or cerebrovascular lesions. The neuropathological assessment and staging of these pathologies allows for a diagnosis of a distinct disease, e.g., amyloid-β plaques and hyperphosphorylated tau pathology in Alzheimer's disease. Neuropathological assessment in large scale cohorts, such as the UK’s Brains for Dementia Research (BDR) programme, has made it increasingly clear that the ageing brain is characterized by the presence of multiple age-associated pathologies rather than just the ‘pure’ hallmark lesion as commonly perceived. These additional pathologies can range from low/intermediate levels, that are assumed to have little if any clinical significance, to a full-blown mixed disease where there is the presence of two distinct diseases. In our recent paper (McAleese et al. 2021 Concomitant neurodegenerative pathologies contribute to the transition from mild cognitive impairment to dementia, https://alz-journals.onlinelibrary.wiley.com/doi/full/10.1002/alz.12291, Alzheimer's & Dementia), using the BDR cohort, we investigated the frequency of multimorbidity and specifically investigated the impact of additional low-level pathology on cognition. In this study, of 670 donated post-mortem brains, we found that almost 70% of cases exhibited multimorbidity and only 22% were considered a pure diagnosis. Importantly, no case of Lewy Body dementia or vascular dementia was considered pure. A key finding is that the presence of low levels of additional pathology increased the likelihood of having mild dementia vs mild cognitive impairment by almost 20-fold, indicating low levels of additional pathology do impact the clinical progression of a distinct disease. Given the high prevalence and the potential clinical impact, cerebral multimorbidity should be at the forefront of consideration in dementia research.

We recently analyzed a large cohort of multiple sclerosis (MS) autopsy cases of the Netherlands Brain Bank (NBB) and showed that 57% of the lesion in advanced MS is active (containing activated microglia/macrophages). These active lesions correlated with disease severity and differed between males and female MS patients.1 Already in normal appearing white matter microglia show early signs of demyelination.5 T cells are also frequently present in advanced stages of MS and have a tissue resident memory (Trm) phenotype, are more frequently CD8+ then CD4+, are located perivascular, enriched in active and mixed active/inactive MS lesions and correlated with lesion activity, lesion load and disease severity.2-4 Like Trm cells, B cells are located perivascular and were also enriched in active MS lesions but in lower numbers and a proportion of the MS patients had almost no detectable B cells in the regions analyzed. MS patients with limited presence of B cells had less severe MS, and less active and mixed active /inactive lesions. We conclude that advanced MS is characterize by a high innate and adaptive immune activity which is heterogeneous and relates to the clinical disease course.

Deep learning is an emerging computational approach inspired by the human brain’s neural connectivity that has transformed machine-based image analysis. By using histopathology as a model of an expert-level pattern recognition exercise, we explore the ability for humans to teach machines to learn and mimic image-recognition and decision making. Moreover, these models also allow exploration into the ability for computers to independently learn salient histological patterns and complex ontological relationships that parallel biological and expert knowledge without the need for explicit direction or supervision. Deciphering the overlap between human and unsupervised machine reasoning may aid in eliminating biases and improving automation and accountability for artificial intelligence-assisted vision tasks and decision-making. Aleksandar Ivanov Title: