Brain Pathology最新文献

The majority of patients with Alzheimer's disease (AD) exhibit aggregates of Trans-active response DNA binding protein 43 (TDP-43) in their hippocampus, which is associated with a more aggressive disease progression. The TDP-43 inclusions are commonly found in neurons, but also in astrocytes. The impact of the inclusions in astrocytes is less known. In the current study, we investigate the presence of phosphorylated TDP-43 (pTDP-43) inclusions in astrocytic endfeet and their potential association with blood–brain barrier (BBB) damage, glymphatic system dysfunction, and AD pathology. By staining postmortem hippocampal sections from AD patients and non-demented controls against TDP-43 and pTDP-43 together with the astrocytic markers glial fibrillary acidic protein (GFAP), astrocytic endfeet marker Aquaporin-4 (AQP4), and markers for BBB alterations (CD146) and leakiness (Immunoglobulin A), we demonstrate a close association between perivascular pTDP-43 or TDP-43 inclusions and GFAP or AQP4. These perivascular inclusions were more prominent in AD and correlated with the disease severity and loss of CD146 and AQP4. The findings indicate a relationship between pTDP-43 accumulation in astrocytic endfeet and BBB and glymphatic system dysfunction, which may contribute to the downstream pathological events seen in AD patients and the aggressive disease progression.

Three distinct MN1::BEND2 fusion-positive tumors in pediatric patients. (A) Clinical course for each patient was variable in part due to differences in initial diagnosis. Each patient responded favorably to gross total resection and is stable at last follow-up. (B) Histologic diversity, lack of prominent classical astroblastoma features, and variable immunoexpression of key markers makes microscopic diagnosis challenging.

The main genetic risk factors for Parkinson's disease (PD) are presently represented by variants in GBA1 gene encoding for the β-glucocerebrosidase (GCase). Searching for a peripheral biomarker that can be used for selecting and monitoring patients in clinical trials targeting GBA1-associated PD (GBA1-PD) is a current challenge. We previously demonstrated that α-synuclein oligomers expressed as proximity ligation assay (PLA) score in synaptic terminals of skin biopsy are a reliable biomarker for distinguishing idiopathic PD (iPD) from healthy controls (HC). This cross-sectional study investigates an unexplored cohort of GBA1-PD (n = 27) compared to 28 HC, and 36 iPD cases to (i) analyze α-synuclein oligomers and quantify them throughout PLA score, (ii) investigate GCase expression in brain and synaptic terminals targeting the sweat gland, (iii) unravel indicators that could differentiate patients with specific GBA1 mutations. PLA score discriminates GBA1-PD from HC with sensitivity = 88.9% (95% CI 70.84–97.65), specificity = 88.5% (95% CI 69.85–97.55), and PPV = 88.9% (95% CI 73.24–95.90), AUC value = 0.927 (95% CI 0.859–0.996). No difference was found between GBA1-PD patients and iPD, suggesting a common pathological pathway based on α-synuclein oligomers. GCase score did not differ in GBA1-PD, iPD, and HC in the synaptic terminals, whereas a positive correlation was found between PLA score and GCase score. Moreover, a significant increase in synaptic density was observed in GBA1-PD compared to iPD and HC (P < 0.0001). Employing ROC curve to discriminate GBA1-PD from iPD, we found an AUC value for synaptic density = 0.855 (95% CI 0.749–0.961) with sensitivity = 85.2% (95% CI 66.27%–95.81%), specificity = 77.1% (95% CI 59.86%–89.58%), and PPV = 74.19% (60.53%–84.35%). The highest synaptic density values were observed in p.N409S patients. This work points out to the value of both PLA score and synaptic density in distinguishing GBA1-PD from iPD and to their potential to stratify and monitor patients in the context of new pathway-specific therapeutic options.

The vast majority of pituitary neuroendocrine tumors (PitNETs) are benign and slow growing with a low relapse rate over many years after surgical resection. However, about 40% are locally invasive and may not be surgically cured, and about one percentage demonstrate an aggressive clinical behavior. Exceptionally, these aggressive tumors may metastasize outside the sellar region to the central nervous system and/or systemically. The 2017 (4th Edition) WHO Classification of Pituitary Tumors abandoned the terminology “atypical adenoma” for tumors previously considered to have potential for a more aggressive behavior since its prognostic value was not established. The 2022 (5th Edition) WHO Classification of the Pituitary Tumors emphasizes the concept that morphological features distinguish indolent tumors from locally aggressive ones, however, the proposed histological subtypes are not consistent with the real life clinical characteristics of patients with aggressive tumors/carcinomas. So far, no single clinical, radiological or histological parameter can determine the risk of growth or malignant progression. Novel promising molecular prognostic markers, such as mutations in ATRX, TP53, SF3B1, and epigenetic DNA modifications, will need to be verified in larger tumor cohorts. In this review, we provide a critical analysis of the WHO guidelines for prognostic stratification and diagnosis of aggressive and metastatic PitNETs. In addition, we discuss the new WHO recommendations for changing ICD-O and ICD-11 codes for PitNET tumor behavior from a neoplasm either “benign” or “unspecified, borderline, or uncertain behavior” to “malignant” neoplasm regardless of the clinical presentation, histopathological subtype, and tumor location. We encourage multidisciplinary initiatives for integrated clinical, histological and molecular classification, which would enable early recognition of these challenging tumors and initiation of more appropriate and aggressive treatments, ultimately improving the outcome.

The evolution of classification systems of pituitary adenomas (now PitNETs) has culminated in the use of transcription factor (TF) immunohistochemistry (IHC), forming a cell lineage-based system. However, several issues remain to be addressed, including the additional financial and logistic burden of undertaking the complete array of anterior pituitary hormones and TF IHC. To that end, several groups have suggested algorithms to minimise the number of tests performed, with varying levels of diagnostic accuracy. Although the proportion of null cell tumours has decreased following the use of TFs, “multilineage” tumours have been reported and characterised using transcriptomic signatures, most prominently the PIT1-SF1 co-expressing PitNETs, which do not bear a position in the present system of classification. In this review, we examine the proposed practical approaches to the diagnosis of PitNETs. We review the literature on reported PitNET types that challenge the existing classification system, such as those that express multiple TFs, with their potential clinical implications. Finally, we assess limitations in the present system, such as the lack of a standardised system for IHC interpretation, that need to be addressed in the future.

Pituitary adenoma/pituitary neuroendocrine tumors (PitNETs) are the second most common primary intracranial tumor and the most frequent neuroendocrine tumors/neoplasms of the human body. Thus, they are one of the most frequent diagnoses in neuropathologist's practise. 2022 5th edition WHO Classification of Endocrine and Neuroendocrine Tumors does not support a grading and/or staging system for PitNETs and argues that histological typing and subtyping are more robust than proliferation rate and invasiveness to stratify tumors. Numerous studies suggest the existence of clinically relevant molecular subgroups encouraging an integrated histo-molecular approach to the diagnosis of PitNETs to deepen the understanding of their biology and overcome the unresolved problem of grading system. The present review illustrates the main issues involved in establishing a grading and a staging system, as well as alternative systems validated by independent series to date. The state of art of the current histological and molecular markers is detailed, demonstrating that a standardized and reproducible clinico-pathological approach, combined with the integration of molecular data may help build a workflow to refine the definition of PitNETs with ‘malignant potential’ and most importantly, avoid delay in patient treatment. Next molecular studied are needed to validate an integrated histo-molecular grading for PitNETs.

The major vascular cause of dementia is cerebral small vessel disease (SVD). Its diagnosis relies on imaging hallmarks, such as white matter hyperintensities (WMH). WMH present a heterogenous pathology, including myelin and axonal loss. Yet, these might be only the “tip of the iceberg.” Imaging modalities imply that microstructural alterations underlie still normal-appearing white matter (NAWM), preceding the conversion to WMH. Unfortunately, direct pathological characterization of these microstructural alterations affecting myelinated axonal fibers in WMH, and especially NAWM, is still missing. Given that there are no treatments to significantly reduce WMH progression, it is important to extend our knowledge on pathological processes that might already be occurring within NAWM. Staining of myelin with Luxol Fast Blue, while valuable, fails to assess subtle alterations in white matter microstructure. Therefore, we aimed to quantify myelin surrounding axonal fibers and axonal- and microstructural damage in detail by combining (immuno)histochemistry with polarized light imaging (PLI). To study the extent (of early) microstructural damage from periventricular NAWM to the center of WMH, we refined current analysis techniques by using deep learning to define smaller segments of white matter, capturing increasing fluid-attenuated inversion recovery signal. Integration of (immuno)histochemistry and PLI with post-mortem imaging of the brains of individuals with hypertension and normotensive controls enables voxel-wise assessment of the pathology throughout periventricular WMH and NAWM. Myelin loss, axonal integrity, and white matter microstructural damage are not limited to WMH but already occur within NAWM. Notably, we found that axonal damage is higher in individuals with hypertension, particularly in NAWM. These findings highlight the added value of advanced segmentation techniques to visualize subtle changes occurring already in NAWM preceding WMH. By using quantitative MRI and advanced diffusion MRI, future studies may elucidate these very early mechanisms leading to neurodegeneration, which ultimately contribute to the conversion of NAWM to WMH.