Neurological abnormalities in individuals with Marfan syndrome: results from a genetically confirmed Italian cohort.

BACKGROUND AND AIMS: Neurological abnormalities have been frequently reported in individuals with Marfan Syndrome (MFS). However, available data relies solely on retrospective studies predating current diagnostic criteria. METHODS: Cross-sectional study comprehensively investigating neurological abnormalities within a prospective cohort of adults (≥ 18 years) with genetically confirmed MFS referred to an Italian hub center for heritable connective tissue diseases (Jan. 1st - Nov. 15th, 2021). RESULTS: We included a total of 38 individuals (53% female). The commonest neurological symptom was migraine (58%), usually without aura (73%). Neuropsychological testing was generally unremarkable, whilst anxiety and depression were highly prevalent within our cohort (42% and 34%, respectively). The most frequent brain parenchymal abnormality was the presence of cortico-subcortical hypointense spots on brain MRI T2* Gradient-Echo sequences (39%), which were found only in patients with a prior history of aortic surgery. Migraineurs had a higher frequency of brain vessels tortuosity vs. individuals without migraine (73% vs. 31%; p = 0.027) and showed higher average and maximum tortuosity indexes in both anterior and posterior circulation brain vessels (all p < 0.05). At univariate regression analysis, the presence of brain vessels tortuosity was significantly associated with a higher risk of migraine (OR 5.87, CI 95% 1.42-24.11; p = 0.014). CONCLUSIONS: Our study confirms that neurological abnormalities are frequent in individuals with MFS. While migraine appears to be associated with brain vessels tortuosity, brain parenchymal abnormalities are typical of individuals with a prior history of aortic surgery. Larger prospective studies are needed to understand the relationship between parenchymal abnormalities and long-term cognitive outcomes.

A novel gradient echo data based vein segmentation algorithm and its application for the detection of regional cerebral differences in venous susceptibility.

Accurate segmentation of cerebral venous vasculature from gradient echo data is of central importance in several areas of neuroimaging such as for the susceptibility-based assessment of brain oxygenation or planning of electrode placement in deep brain stimulation. In this study, a vein segmentation algorithm for single- and multi-echo gradient echo data is proposed. First, susceptibility maps, true susceptibility-weighted images, and, in the multi-echo case, R2* maps were generated from the gradient echo data. These maps were filtered with an inverted Hamming filter to suppress background contrast as well as artifacts from field inhomogeneities at the brain boundaries. A shearlet-based scale-wise representation was generated to calculate a vesselness function and to generate segmentations based on local thresholding. The accuracy of the proposed algorithm was evaluated for different echo times and image resolutions using a manually generated reference segmentation and two vein segmentation algorithms (Frangi vesselness-based, recursive vesselness filter) as a reference with the Dice and Cohen's coefficients as well as the modified Hausdorff distance. The Frangi-based and recursive vesselness filter methods were significantly outperformed with regard to all error metrics. Applying the algorithm, susceptibility differences likely related to differences in blood oxygenation between superficial and deep venous territories could be demonstrated.

SARS-CoV-2 spike S1 subunit protein-mediated increase of beta-secretase 1 (BACE1) impairs human brain vessel cells.

Increasing evidence suggests incomplete recovery of COVID-19 patients, who continue to suffer from cardiovascular diseases, including cerebral vascular disorders (CVD) and neurological symptoms. Recent findings indicate that some of the damaging effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, especially in the brain, may be induced by the spike protein, leading to the disruption of the initial blood-brain barrier (BBB). SARS-CoV-2-infected cells and animals exhibit age-dependent pathogenesis. In this study, we identified endothelial BACE1 as a critical mediator of BBB disruption and cellular senescence induced by the SARS-CoV-2 spike S1 subunit protein. Increased BACE1 in human brain microvascular endothelial cells (HBMVEC) decreases the levels of tight junction proteins, including ZO-1, occludin, and claudins. Moreover, BACE1 overexpression leads to the accumulation of p16 and p21, typical hallmarks of cellular senescence. Our findings show that the SARS-CoV-2 spike S1 subunit protein upregulated BACE1 expression in HBMVECs, causing endothelial leakage. In addition, the SARS-CoV-2 spike S1 subunit protein induced p16 and p21 expression, indicating BACE1-mediated cellular senescence, confirmed by ß-Gal staining in HBMVECs. In conclusion, this study demonstrated that BACE1-mediated endothelial cell damage and senescence may be linked to CVD after COVID-19 infection.

Autonomic function and brain volume.

OBJECTIVE: The aim of this study is to review the evidence on the role of the autonomic nervous system as a determinant of brain volume. Brain volume measures have gained increasing attention given its biological importance, particularly as a measurement of neurodegeneration. METHODS: Using an integrative approach, we reviewed publications addressing the anatomical and physiological characteristics of brain autonomic innervation focusing on evidence from diverse clinical populations with respect to brain volume. RESULTS: Multiple mechanisms contribute to changes in brain volume. Autonomic influence on cerebral blood volume is of significant interest. CONCLUSION: We suggest a role for the autonomic innervation of brain vessels in fluctuations of cerebral blood volume. Further investigation in several clinical populations including multiple sclerosis is warranted to understand the specific role of parenchyma versus blood vessels changes on final brain volume.

CAVE: Cerebral artery-vein segmentation in digital subtraction angiography.

Cerebral X-ray digital subtraction angiography (DSA) is a widely used imaging technique in patients with neurovascular disease, allowing for vessel and flow visualization with high spatio-temporal resolution. Automatic artery-vein segmentation in DSA plays a fundamental role in vascular analysis with quantitative biomarker extraction, facilitating a wide range of clinical applications. The widely adopted U-Net applied on static DSA frames often struggles with disentangling vessels from subtraction artifacts. Further, it falls short in effectively separating arteries and veins as it disregards the temporal perspectives inherent in DSA. To address these limitations, we propose to simultaneously leverage spatial vasculature and temporal cerebral flow characteristics to segment arteries and veins in DSA. The proposed network, coined CAVE, encodes a 2D+time DSA series using spatial modules, aggregates all the features using temporal modules, and decodes it into 2D segmentation maps. On a large multi-center clinical dataset, CAVE achieves a vessel segmentation Dice of 0.84 (±0.04) and an artery-vein segmentation Dice of 0.79 (±0.06). CAVE surpasses traditional Frangi-based k-means clustering (P < 0.001) and U-Net (P < 0.001) by a significant margin, demonstrating the advantages of harvesting spatio-temporal features. This study represents the first investigation into automatic artery-vein segmentation in DSA using deep learning. The code is publicly available at https://github.com/RuishengSu/CAVE_DSA.

Pericytes and vascular smooth muscle cells in central nervous system arteriovenous malformations.

Previously considered passive support cells, mural cells-pericytes and vascular smooth muscle cells-have started to garner more attention in disease research, as more subclassifications, based on morphology, gene expression, and function, have been discovered. Central nervous system (CNS) arteriovenous malformations (AVMs) represent a neurovascular disorder in which mural cells have been shown to be affected, both in animal models and in human patients. To study consequences to mural cells in the context of AVMs, various animal models have been developed to mimic and predict human AVM pathologies. A key takeaway from recently published work is that AVMs and mural cells are heterogeneous in their molecular, cellular, and functional characteristics. In this review, we summarize the observed perturbations to mural cells in human CNS AVM samples and CNS AVM animal models, and we discuss various potential mechanisms relating mural cell pathologies to AVMs.

Preparing the Astrocyte Perivascular Endfeet Transcriptome to Investigate Astrocyte Molecular Regulations at the Brain-Vascular Interface.

Astrocytes send out long processes that are terminated by endfeet at the vascular surface and regulate vascular functions in particular through the expression of a specific molecular repertoire in perivascular endfeet. We recently proposed that local translation might sustain this structural and functional polarization. More specifically we showed that a subset of mRNAs is distributed in astrocyte endfeet and characterized this transcriptome. We also identified among these endfeet RNAs, the ones bound to ribosomes, the polysomal astrocyte endfeet mRNAs, which we called the endfeetome. Here, we describe experimental strategies to identify mRNAs and polysomes in astrocyte perivascular endfeet, which are based on the combination of gliovascular unit purification and astrocyte-specific translating ribosome affinity purification.

Isolation of Rodent Brain Vessels.

The prevalence of neurodegenerative diseases is increasing worldwide. Cerebrovascular disorders and/or conditions known to affect brain vasculature, such as diabetes, are well-known risk factors for neurodegenerative diseases. Thus, the evaluation of the brain vasculature is of great importance to better understand the mechanisms underlying brain damage. We established a protocol for the isolation of brain vessels from rodents. This is a simple, non-enzymatic isolation protocol that allows us to perform comparative studies in different animal models of disease, helping understand the impact of several pathological conditions on brain vasculature and how those alterations predispose to neurodegenerative conditions.