Neuropathology of white matter disorders.

The hallmark neuropathologic feature of all leukodystrophies is depletion or alteration of the white matter of the central nervous system; however increasing genetic discoveries highlight the genetic heterogeneity of white matter disorders. These discoveries have significantly helped to advance the understanding of the complexity of molecular mechanisms involved in the biogenesis and maintenance of healthy white matter. Accordingly, genetic discoveries and functional studies have enabled us to firmly establish that multiple distinct structural defects can lead to white matter pathology. Leukodystrophies can develop not only due to defects in proteins essential for myelin biogenesis and maintenance or oligodendrocyte function, but also due to mutations encoding myriad of proteins involved in the function of neurons, astrocytes, microglial cells as well as blood vessels. To a variable extent, some leukodystrophies also show gray matter, peripheral nervous system, or multisystem involvement. Depending on the genetic defect and its role in the formation or maintenance of the white matter, leukodystrophies can present either in early childhood or adulthood. In this chapter, the classification of leukodystrophies will be discussed from the cellular defect point of view, followed by a description of known neuropathologic alterations for all leukodystrophies.

Large-scale neurophysiology and single-cell profiling in human neuroscience.

Advances in large-scale single-unit human neurophysiology, single-cell RNA sequencing, spatial transcriptomics and long-term ex vivo tissue culture of surgically resected human brain tissue have provided an unprecedented opportunity to study human neuroscience. In this Perspective, we describe the development of these paradigms, including Neuropixels and recent brain-cell atlas efforts, and discuss how their convergence will further investigations into the cellular underpinnings of network-level activity in the human brain. Specifically, we introduce a workflow in which functionally mapped samples of human brain tissue resected during awake brain surgery can be cultured ex vivo for multi-modal cellular and functional profiling. We then explore how advances in human neuroscience will affect clinical practice, and conclude by discussing societal and ethical implications to consider. Potential findings from the field of human neuroscience will be vast, ranging from insights into human neurodiversity and evolution to providing cell-type-specific access to study and manipulate diseased circuits in pathology. This Perspective aims to provide a unifying framework for the field of human neuroscience as we welcome an exciting era for understanding the functional cytoarchitecture of the human brain.

Machine learning of dissection photographs and surface scanning for quantitative 3D neuropathology.

We present open-source tools for three-dimensional (3D) analysis of photographs of dissected slices of human brains, which are routinely acquired in brain banks but seldom used for quantitative analysis. Our tools can: (1) 3D reconstruct a volume from the photographs and, optionally, a surface scan; and (2) produce a high-resolution 3D segmentation into 11 brain regions per hemisphere (22 in total), independently of the slice thickness. Our tools can be used as a substitute for ex vivo magnetic resonance imaging (MRI), which requires access to an MRI scanner, ex vivo scanning expertise, and considerable financial resources. We tested our tools on synthetic and real data from two NIH Alzheimer's Disease Research Centers. The results show that our methodology yields accurate 3D reconstructions, segmentations, and volumetric measurements that are highly correlated to those from MRI. Our method also detects expected differences between post mortem confirmed Alzheimer's disease cases and controls. The tools are available in our widespread neuroimaging suite 'FreeSurfer' (https://surfer.nmr.mgh.harvard.edu/fswiki/PhotoTools).

Every year, thousands of human brains are donated to science. These brains are used to study normal aging, as well as neurological diseases like Alzheimer's or Parkinson's. Donated brains usually go to 'brain banks', institutions where the brains are dissected to extract tissues relevant to different diseases. During this process, it is routine to take photographs of brain slices for archiving purposes. Often, studies of dead brains rely on qualitative observations, such as 'the hippocampus displays some atrophy', rather than concrete 'numerical' measurements. This is because the gold standard to take three-dimensional measurements of the brain is magnetic resonance imaging (MRI), which is an expensive technique that requires high expertise ­ especially with dead brains. The lack of quantitative data means it is not always straightforward to study certain conditions. To bridge this gap, Gazula et al. have developed an openly available software that can build three-dimensional reconstructions of dead brains based on photographs of brain slices. The software can also use machine learning methods to automatically extract different brain regions from the three-dimensional reconstructions and measure their size. These data can be used to take precise quantitative measurements that can be used to better describe how different conditions lead to changes in the brain, such as atrophy (reduced volume of one or more brain regions). The researchers assessed the accuracy of the method in two ways. First, they digitally sliced MRI-scanned brains and used the software to compute the sizes of different structures based on these synthetic data, comparing the results to the known sizes. Second, they used brains for which both MRI data and dissection photographs existed and compared the measurements taken by the software to the measurements obtained with MRI images. Gazula et al. show that, as long as the photographs satisfy some basic conditions, they can provide good estimates of the sizes of many brain structures. The tools developed by Gazula et al. are publicly available as part of FreeSurfer, a widespread neuroimaging software that can be used by any researcher working at a brain bank. This will allow brain banks to obtain accurate measurements of dead brains, allowing them to cheaply perform quantitative studies of brain structures, which could lead to new findings relating to neurodegenerative diseases.

Classifying Alzheimer's Disease Neuropathology Using Clinical and MRI Measurements.

Background: Computer-aided machine learning models are being actively developed with clinically available biomarkers to diagnose Alzheimer's disease (AD) in living persons. Despite considerable work with cross-sectional in vivo data, many models lack validation against postmortem AD neuropathological data. Objective: Train machine learning models to classify the presence or absence of autopsy-confirmed severe AD neuropathology using clinically available features. Methods: AD neuropathological status are assessed at postmortem for participants from the National Alzheimer's Coordinating Center (NACC). Clinically available features are utilized, including demographics, Apolipoprotein E(APOE) genotype, and cortical thicknesses derived from ante-mortem MRI scans encompassing AD meta regions of interest (meta-ROI). Both logistic regression and random forest models are trained to identify linearly and nonlinearly separable features between participants with the presence (N = 91, age-at-MRI = 73.6±9.24, 38 women) or absence (N = 53, age-at-MRI = 68.93±19.69, 24 women) of severe AD neuropathology. The trained models are further validated in an external data set against in vivo amyloid biomarkers derived from PET imaging (amyloid-positive: N = 71, age-at-MRI = 74.17±6.37, 26 women; amyloid-negative: N = 73, age-at-MRI = 71.59±6.80, 41 women). Results: Our models achieve a cross-validation accuracy of 84.03% in classifying the presence or absence of severe AD neuropathology, and an external-validation accuracy of 70.14% in classifying in vivo amyloid positivity status. Conclusions: Our models show that clinically accessible features, including APOE genotype and cortical thinning encompassing AD meta-ROIs, are able to classify both postmortem confirmed AD neuropathological status and in vivo amyloid status with reasonable accuracies. These results suggest the potential utility of AD meta-ROIs in determining AD neuropathological status in living persons.

Induced Pluripotent Stem Cells and Organoids in Advancing Neuropathology Research and Therapies.

This review delves into the groundbreaking impact of induced pluripotent stem cells (iPSCs) and three-dimensional organoid models in propelling forward neuropathology research. With a focus on neurodegenerative diseases, neuromotor disorders, and related conditions, iPSCs provide a platform for personalized disease modeling, holding significant potential for regenerative therapy and drug discovery. The adaptability of iPSCs, along with associated methodologies, enables the generation of various types of neural cell differentiations and their integration into three-dimensional organoid models, effectively replicating complex tissue structures in vitro. Key advancements in organoid and iPSC generation protocols, alongside the careful selection of donor cell types, are emphasized as critical steps in harnessing these technologies to mitigate tumorigenic risks and other hurdles. Encouragingly, iPSCs show promising outcomes in regenerative therapies, as evidenced by their successful application in animal models.

Historical review: The golden age of the Golgi method in human neuropathology.

Golgi methods were used to study human neuropathology in the 1970s, 1980s, and 1990s of the last century. Although a relatively small number of laboratories applied these methods, their impact was crucial by increasing knowledge about: (1) the morphology, orientation, and localization of neurons in human cerebral and cerebellar malformations and ganglionic tumors, and (2) the presence of abnormal structures including large and thin spines (spine dysgenesis) in several disorders linked to mental retardation, focal enlargements of the axon hillock and dendrites (meganeurites) in neuronal storage diseases, growth cone-like appendages in Alzheimer disease, as well as abnormal structures in other dementias. Although there were initial concerns about their reliability, reduced dendritic branches and dendritic spines were identified as common alterations in mental retardation, dementia, and other pathological conditions. Similar observations in appropriate experimental models have supported many abnormalities that were first identified using Golgi methods in human material. Moreover, electron microscopy, immunohistochemistry, fluorescent tracers, and combined methods have proven the accuracy of pioneering observations uniquely visualized as 3D images of fully stained individual neurons. Although Golgi methods had their golden age many years ago, these methods may still be useful complementary tools in human neuropathology.

Ranking and filtering of neuropathology features in the machine learning evaluation of dementia studies.

Early diagnosis of dementia diseases, such as Alzheimer's disease, is difficult because of the time and resources needed to perform neuropsychological and pathological assessments. Given the increasing use of machine learning methods to evaluate neuropathology features in the brains of dementia patients, it is important to investigate how the selection of features may be impacted and which features are most important for the classification of dementia. We objectively assessed neuropathology features using machine learning techniques for filtering features in two independent ageing cohorts, the Cognitive Function and Aging Studies (CFAS) and Alzheimer's Disease Neuroimaging Initiative (ADNI). The reliefF and least loss methods were most consistent with their rankings between ADNI and CFAS; however, reliefF was most biassed by feature-feature correlations. Braak stage was consistently the highest ranked feature and its ranking was not correlated with other features, highlighting its unique importance. Using a smaller set of highly ranked features, rather than all features, can achieve a similar or better dementia classification performance in CFAS (60%-70% accuracy with Naïve Bayes). This study showed that specific neuropathology features can be prioritised by feature filtering methods, but they are impacted by feature-feature correlations and their results can vary between cohort studies. By understanding these biases, we can reduce discrepancies in feature ranking and identify a minimal set of features needed for accurate classification of dementia.

Chronic Traumatic Encephalopathy in the Brains of Military Personnel.

BACKGROUND: Persistent neuropsychiatric sequelae may develop in military personnel who are exposed to combat; such sequelae have been attributed in some cases to chronic traumatic encephalopathy (CTE). Only limited data regarding CTE in the brains of military service members are available. METHODS: We performed neuropathological examinations for the presence of CTE in 225 consecutive brains from a brain bank dedicated to the study of deceased service members. In addition, we reviewed information obtained retrospectively regarding the decedents' histories of blast exposure, contact sports, other types of traumatic brain injury (TBI), and neuropsychiatric disorders. RESULTS: Neuropathological findings of CTE were present in 10 of the 225 brains (4.4%) we examined; half the CTE cases had only a single pathognomonic lesion. Of the 45 brains from decedents who had a history of blast exposure, 3 had CTE, as compared with 7 of 180 brains from those without a history of blast exposure (relative risk, 1.71; 95% confidence interval [CI], 0.46 to 6.37); 3 of 21 brains from decedents with TBI from an injury during military service caused by the head striking a physical object without associated blast exposure (military impact TBI) had CTE, as compared with 7 of 204 without this exposure (relative risk, 4.16; 95% CI, 1.16 to 14.91). All brains with CTE were from decedents who had participated in contact sports; 10 of 60 contact-sports participants had CTE, as compared with 0 of 165 who had not participated in contact sports (point estimate of relative risk not computable; 95% CI, 6.16 to infinity). CTE was present in 8 of 44 brains from decedents with non-sports-related TBI in civilian life, as compared with 2 of 181 brains from those without such exposure in civilian life (relative risk, 16.45; 95% CI, 3.62 to 74.79). CONCLUSIONS: Evidence of CTE was infrequently found in a series of brains from military personnel and was usually reflected by minimal neuropathologic changes. Risk ratios for CTE were numerically higher among decedents who had contact-sports exposure and other exposures to TBI in civilian life than among those who had blast exposure or other military TBI, but the small number of CTE cases and wide confidence intervals preclude causal conclusions. (Funded by the Department of Defense-Uniformed Services University Brain Tissue Repository and Neuropathology Program and the Henry M. Jackson Foundation for the Advancement of Military Medicine.).

Advances in Deep Neuropathological Phenotyping of Alzheimer Disease: Past, Present, and Future.

Alzheimer disease (AD) is a neurodegenerative disorder characterized pathologically by the presence of neurofibrillary tangles and amyloid beta (Aß) plaques in the brain. The disease was first described in 1906 by Alois Alzheimer, and since then, there have been many advancements in technologies that have aided in unlocking the secrets of this devastating disease. Such advancements include improving microscopy and staining techniques, refining diagnostic criteria for the disease, and increased appreciation for disease heterogeneity both in neuroanatomic location of abnormalities as well as overlap with other brain diseases; for example, Lewy body disease and vascular dementia. Despite numerous advancements, there is still much to achieve as there is not a cure for AD and postmortem histological analyses is still the gold standard for appreciating AD neuropathologic changes. Recent technological advances such as in-vivo biomarkers and machine learning algorithms permit great strides in disease understanding, and pave the way for potential new therapies and precision medicine approaches. Here, we review the history of human AD neuropathology research to include the notable advancements in understanding common co-pathologies in the setting of AD, and microscopy and staining methods. We also discuss future approaches with a specific focus on deep phenotyping using machine learning.

Discovery of a dual-action small molecule that improves neuropathological features of Alzheimer's disease mice.

Alzheimer's disease (AD) is characterized by complex, multifactorial neuropathology, suggesting that small molecules targeting multiple neuropathological factors are likely required to successfully impact clinical progression. Acid sphingomyelinase (ASM) activation has been recognized as an important contributor to these neuropathological features in AD, leading to the concept of using ASM inhibitors for the treatment of this disorder. Here we report the identification of KARI 201, a direct ASM inhibitor evaluated for AD treatment. KARI 201 exhibits highly selective inhibition effects on ASM, with excellent pharmacokinetic properties, especially with regard to brain distribution. Unexpectedly, we found another role of KARI 201 as a ghrelin receptor agonist, which also has therapeutic potential for AD treatment. This dual role of KARI 201 in neurons efficiently rescued neuropathological features in AD mice, including amyloid beta deposition, autophagy dysfunction, neuroinflammation, synaptic loss, and decreased hippocampal neurogenesis and synaptic plasticity, leading to an improvement in memory function. Our data highlight the possibility of potential clinical application of KARI 201 as an innovative and multifaceted drug for AD treatment.

Milk fat globule membrane attenuates high fat diet-induced neuropathological changes in obese Ldlr-/-.Leiden mice.

BACKGROUND: Milk-fat globule membrane (MFGM) is a complex structure secreted by the mammary gland and present in mammalian milk. MFGM contains lipids and glycoproteins as well as gangliosides, which may be involved in myelination processes. Notably, myelination and thereby white matter integrity are often altered in obesity. Furthermore, MFGM interventions showed beneficial effects in obesity by affecting inflammatory processes and the microbiome. In this study, we investigated the impact of a dietary MFGM intervention on fat storage, neuroinflammatory processes and myelination in a rodent model of high fat diet (HFD)-induced obesity. METHODS: 12-week-old male low density lipoprotein receptor-deficient Leiden mice were exposed to a HFD, a HFD enriched with 3% whey protein lipid concentrate (WPC) high in MFGM components, or a low fat diet. The impact of MFGM supplementation during 24-weeks of HFD-feeding was examined over time by analyzing body weight and fat storage, assessing cognitive tasks and MRI scanning, analyzing myelinization with polarized light imaging and examining neuroinflammation using immunohistochemistry. RESULTS: We found in this study that 24 weeks of HFD-feeding induced excessive fat storage, increased systolic blood pressure, altered white matter integrity, decreased functional connectivity, induced neuroinflammation and impaired spatial memory. Notably, supplementation with 3% WPC high in MFGM components restored HFD-induced neuroinflammation and attenuated the reduction in hippocampal-dependent spatial memory and hippocampal functional connectivity. CONCLUSIONS: We showed that supplementation with WPC high in MFGM components beneficially contributed to hippocampal-dependent spatial memory, functional connectivity in the hippocampus and anti-inflammatory processes in HFD-induced obesity in rodents. Current knowledge regarding exact biological mechanisms underlying these effects should be addressed in future studies.

ASNTR's Venture into a Hybrid Conference: Lessons Learned During the COVID-19 Pandemic.

The 28th American Society for Neural Therapy and Repair (ASNTR) returned to the Sheraton Sand Key in Clearwater Beach, Florida after an 18 month hiatus. Like nearly all conferences during the pandemic, the ASNTR conference was held in person while offering a virtual option to the event. These formats are advantageous for those under travel restrictions or personal constraints, but they lack the spontaneity of in-person connections. Highlights from the meeting included the return of the Bernard Sanberg Memorial Award and the Roy Bakay Memorial lecture. The presidential lecture was given by Gabriel de Erausquin, who discussed the possibility of long-term CNS effects resulting from SARS-CoV2 infection. With both virtual and in-person events, including oral and poster presentations, the ASNTR managed to maintain the unique essence of this small important meeting.

Neural Injury and Repair in a Novel Neonatal Mouse Model of Listeria Monocytogenes Meningoencephalitis.

To improve the therapy of neonatal central nervous system infections, well-characterized animal models are urgently needed. The present study analyzes neuropathological alterations with particular focus on neural injury and repair in brains of neonatal mice with Listeria monocytogenes (LM) meningitis/meningoencephalitis using a novel nasal infection model. The hippocampal formation and frontal cortex of 14 neonatal mice with LM meningitis/meningoencephalitis and 14 uninfected controls were analyzed by histology, immunohistochemistry, and in situ tailing for morphological alterations. In the dentate gyrus of the hippocampal formation of mice with LM meningitis/meningoencephalitis, an increased density of apoptotic neurons visualized by in situ tailing (p = 0.04) and in situ tailing plus immunohistochemistry for activated Caspase-3 (p < 0.0001) was found. A decreased density of dividing cells stained with an anti-PCNA-antibody (p < 0.0001) and less neurogenesis visualized by anti-calretinin (p < 0.0001) and anti-calbindin (p = 0.01) antibodies were detected compared to uninfected controls. The density of microglia was higher in LM meningitis (p < 0.0001), while the density of astrocytes remained unchanged. Infiltrating monocytes and neutrophilic granulocytes likely contributed to tissue damage. In conclusion, in the brains of LM-infected mice a strong immune response was observed which led to neuronal apoptosis and an impaired neural regeneration. This model appears very suitable to study therapies against long-term sequelae of neonatal LM meningitis.

The Neuropathology of 1p36 Deletion Syndrome: An Autopsy Case Series.

1p36 deletion syndrome is the most common terminal deletion syndrome, manifesting clinically as abnormal facies and developmental delay with frequent cardiac, skeletal, urogenital, and renal abnormalities. Limited autopsy case reports describe the neuropathology of 1p36 deletion syndrome. The most extensive single case report described a spectrum of abnormalities, mostly related to abnormal neuronal migration. We report the largest published series of 1p36 autopsy cases, with an emphasis on neuropathologic findings. Our series consists of 3 patients: 2 infants (5-hours old and 23-days old) and 1 older child (11 years). Our patients showed abnormal cortical gyration together with a spectrum of neuronal migration abnormalities, including heterotopias and hippocampal abnormalities, as well as cerebellar hypoplasia. Our findings thus support the role of neuronal migration defects in the pathogenesis of cognitive defects in 1p36 deletion syndrome and broaden the reported neuropathologic spectrum of this common syndrome.

What Every Neuropathologist Needs to Know: Practical Aspects and Pitfalls in Molecular Diagnosis of Brain Tumors.

Molecular testing has become part of the routine diagnostic workup of brain tumors after the implementation of integrated histomolecular diagnoses in the 2016 WHO classification update. It is important for every neuropathologist to be aware of practical preanalytical, analytical, and postanalytical factors that impact the performance and interpretation of molecular tests. Prior to testing, optimizing tumor purity and tumor amount increases the ability of the molecular test to detect the genetic alteration of interest. Recognizing basic molecular testing platform analytical characteristics allows selection of the optimal platform for each clinicopathological scenario. Finally, postanalytical considerations to properly interpret molecular test results include understanding the clinical significance of the detected genetic alteration, recognizing that detected clinically significant genetic alterations are occasionally germline constitutional rather than somatic tumor-specific, and being cognizant that recommended and commonly used genetic nomenclature may differ. Potential pitfalls in brain tumor molecular diagnosis are also discussed.

Fetal and Perinatal Brain Autopsy: Useful Macroscopic Techniques Including Agar In-situ and Pre-Embedding Methods.

Fragile perinatal and fetal brains are the rule rather than the exception for developmental neuropathologists. Retrieving the fresh brain from the skull and examining early fetal, macerated or severely hydrocephalic brains after fixation can be a challenge. Textbooks on neurodevelopmental pathology mention these challenges to macroscopic examination of the developing central nervous system only in passing, but many perinatal pathologists recognize this diagnostic problem. We reviewed protocols and publications on the removal, fixation, slicing and sampling of these fetal- and perinatal brains. In addition, we describe a technique to facilitate the removal of severely hydrocephalic brains with very thin cerebral walls from the skull by replacing the intraventricular fluid with agar in-situ. Furthermore, we present a method for post-fixation pre-embedding in agar to facilitate slicing, macroscopic examination and sampling of fragile and macerated brains.

Clusterin secreted from astrocyte promotes excitatory synaptic transmission and ameliorates Alzheimer's disease neuropathology.

BACKGROUND: Genome-wide association studies have established clusterin (CLU) as a genetic modifier for late-onset Alzheimer's disease (AD). Both protective and risk alleles have been identified which may be associated with its expression levels. However, the physiological function of clusterin in the central nervous system remains largely unknown. METHODS: We examined Clu expression in mouse brains by immunohistochemistry and high-resolution imaging. We performed electrophysiological recordings and morphological analysis of dendritic spines in wild-type and Clu knockout mice. We tested synaptic function of astrocytic Clu using neuron-glia co-cultures and by AAV-mediated astroglial Clu expression in vivo. Finally, we investigated the role of astrocytic Clu on synaptic properties and amyloid pathology in 5xFAD transgenic mouse model of AD. RESULTS: We show that astrocyte secreted Clu co-localizes with presynaptic puncta of excitatory neurons. Loss of Clu led to impaired presynaptic function and reduced spine density in vivo. Neurons co-cultured with Clu-overexpressing astrocytes or treated with conditioned media from HEK293 cells transfected with Clu displayed enhanced excitatory neurotransmission. AAV-mediated astroglial Clu expression promoted excitatory neurotransmission in wild-type mice and rescued synaptic deficits in Clu knockout mice. Overexpression of Clu in the astrocytes of 5xFAD mice led to reduced Aß pathology and fully rescued the synaptic deficits. CONCLUSION: We identify Clu as an astrocyte-derived synaptogenic and anti-amyloid factor; the combination of these activities may influence the progression of late-onset AD.