Search bioRxiv⌕ Search

bioRxiv · 10.1101/2021.02.01.429067

Increasing age is independently associated with higher free water in non-active MS brain - A multi-compartment analysis using FAST-T2

Abstract

PurposeTo explore the relationship between the cerebral cortical perivascular space (PVS) and aging in non-active MS subjects by using the multi-echo T2 relaxometry based cerebrospinal fluid fraction (CSFF) map. MethodsMulti-echo spiral T2 data from 111 subjects with non-active multiple sclerosis (MS) were retrospectively investigated by fitting the T2 data into a three-compartment model, the three water compartments including myelin water, intra-extracellular water, and cerebrospinal fluid. Segmentation of T1w image was performed to get the region of interest (ROI) in cerebral cortical regions. The white matter lesion segmentation was conducted using a convolutional neural network (CNN) based segmentation tool. The CSFF in the ROIs were correlated with age by controlling the gender, white matter hyperintensity lesion burden, and MS disease duration. Multiple linear models were created for the analysis of aging effect on the CSFF. ResultsThe ROI analysis shows that the CSFF in the cerebral cortical regions (temporal, occipital, parietal, front, hippo, and mtl) are significantly linear increasing with age (p<0.01). The intra-extracellular water fraction (IEWF) in the ROIs are significantly linear decreasing (p<0.01). ConclusionThe multi-echo T2 based three-compartment model can be used to quantify the CSFF. The linear increase of CSF water contents in the cerebral cortical regions indicates increased perivascular space load in cortex with aging. The quantification of CSFF may provide a way to understand the glymphatic clearance function in aging and neurodegenerations. HighlightsO_LIMR T2 relaxometry is a valid method to quantify the cerebrospinal fluid fraction (CSFF) in cerebral cortical regions C_LIO_LIThe CSFF in the cerebral cortical regions are positively correlated with age by controlling the white matter lesion load in non-active MS subjects. C_LIO_LIQuantification of cerebral CSFF may reflect the perivascular space load in cortex and better interpret the disease progression in neurodegenerative disease, such as MS. C_LI

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Zhou, L., Li, Y., Wang, X. H., Sweeney, E., Zhang, H., Tanzi, E. B., Prince, J., Su-Ortiz, V. A., Gauthier, S. A., Nguyen, T. D.. 2021-02-02. Increasing age is independently associated with higher free water in non-active MS brain - A multi-compartment analysis using FAST-T2. https://doi.org/10.1101/2021.02.01.429067

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience↗

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience↗

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience↗