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Pathological evaluation is the gold standard for identifying processes related to multiple sclerosis that explain disease manifestations, and for guiding the development of new treatments. However, there are limitations to the techniques used, including the small number of donors available, samples often representing uncommon cases, and impossibility of follow-up. Correlative studies have demonstrated that MRI is sensitive to the different pathological substrates of multiple sclerosis (inflammation, demyelination, and neuro-axonal loss). The role of MRI in evaluating other pathological processes, such as leptomeningeal involvement, central vein and rim of lesions, microstructural abnormalities, iron accumulation, and recovery mechanisms, has been investigated. Although techniques used for quantifying pathological processes in different regions of the CNS have advanced diagnosis and monitoring of disease course and treatment of multiple sclerosis, new perspectives and questions have emerged, including how different pathological processes interact over the disease course and when remyelination might occur. Addressing these questions will require longitudinal studies using MRI in large cohorts of patients with different phenotypes.

Quantitative susceptibility mapping (QSM) and effective transverse relaxation rate (R2*) mapping are both highly sensitive to variations in brain iron content. Clinical Magnetic Resonance Imaging (MRI) studies report changes of susceptibilities and relaxation rates in various neurological diseases which are often equated with changes in regional brain iron content. However, these mentioned metrics lack specificity for iron, since they are also influenced by the presence of myelin. In this study, we assessed the extent to which QSM and R2* reflect iron concentration as well as histological iron and myelin intensities. Six unfixed human post-mortem brains were imaged in situ with a 7 T MRI scanner. After formalin fixation, the brains were sliced axially and punched. 671 tissue punches were subjected to ferrozine iron quantification. Subsequently, brain slices were embedded in paraffin, and histological double-hemispheric axial brain slices were stained for Luxol fast blue (myelin) and diaminobenzidine (DAB)-enhanced Turnbull blue (iron). 3331 regions of interest (ROIs) were drawn on the histological stainings to assess myelin and iron intensities, which were compared with MRI data in corresponding ROIs. QSM more closely reflected quantitative ferrozine iron values (r = 0.755 vs. 0.738), whereas R2* correlated better with iron staining intensities (r = 0.619 vs. 0.445). Myelin intensities correlated negatively with QSM (r = −0.352), indicating a diamagnetic effect of myelin on susceptibility. Myelin intensities were higher in the thalamus than in the basal ganglia. A significant relationship was nonetheless observed between quantitative iron values and QSM, confirming the applicability of the latter in this brain region for iron quantification. •Brain iron can be visualized using quantitative susceptibility (QSM) and R2* mapping.•Anatomical structures show different contributions of iron and myelin to QSM or R2*.•Iron and myelin have opposite effects on QSM throughout the human brain.•The relation between brain iron and myelin differs between anatomical structures.

•Synthesized myelin and iron stainings can be generated from 7T MRI data via deep learning.•Combined T1, R2*, and QSM gave the best results for myelin staining image synthesis.•Adding synthesized myelin improved iron staining image quality.•Overlapped patching enhanced details in staining images and reduced edge artifacts.•Model generalizes to other ex vivo and in vivo to predict myelin and iron maps. Iron and myelin are key biomarkers for studying neurodegenerative and demyelinating brain diseases. Multi-contrast MRI techniques, such as R2* and QSM, are commonly used for iron assessment, with histology as the reference standard, but non-invasive myelin assessment remains challenging. To address this, we developed a deep learning model to generate iron and myelin staining images from in vivo multi-contrast MRI data, with a resolution comparable to ex vivo histology macro-scans. A cadaver head was scanned using a 7T MR scanner to acquire T1-weighted and multi-echo GRE data for R2*, and QSM processing, followed by histological staining for myelin and iron. To evaluate the generalizability of the model, a second cadaver head and two in vivo MRI datasets were included. After MRI-to-histology registration in the training subject, a self-attention generative adversarial network (GAN) was trained to synthesize myelin and iron staining images using various combinations of MRI contrast. The model achieved optimal myelin prediction when combining T1w, R2*, and QSM images. Incorporating the synthesized myelin images improved the subsequent prediction of iron staining. The generated images displayed fine details similar to those in histology data and demonstrated generalizability across healthy control subjects. Synthesized myelin images clearly differentiated myelin concentration between white and gray matter, while synthesized iron staining presented distinct patterns such as particularly high deposition in deep gray matter. This study shows that deep learning can transform MRI data into histological feature images, offering ex vivo insights from in vivo data and contributing to advancements in brain histology research.

Neuroglia critically shape the brain´s response to ischemic stroke. However, their phenotypic heterogeneity impedes a holistic understanding of the cellular composition of the early ischemic lesion. Here we present a single cell resolution transcriptomics dataset of the brain´s acute response to infarction. Oligodendrocyte lineage cells and astrocytes range among the most transcriptionally perturbed populations and exhibit infarction- and subtype-specific molecular signatures. Specifically, we find infarction restricted proliferating oligodendrocyte precursor cells (OPCs), mature oligodendrocytes and reactive astrocytes, exhibiting transcriptional commonalities in response to ischemic injury. OPCs and reactive astrocytes are involved in a shared immuno-glial cross talk with stroke-specific myeloid cells. Within the perilesional zone, osteopontin positive myeloid cells accumulate in close proximity to CD44 + proliferating OPCs and reactive astrocytes. In vitro, osteopontin increases the migratory capacity of OPCs. Collectively, our study highlights molecular cross talk events which might govern the cellular composition of acutely infarcted brain tissue. Ischemic stroke, caused by sudden oxygen and substrate deprivation of the CNS, is a leading cause of disability and death. Here, the authors characterize in a rodent model the molecular signature of glial cells in response to ischemic stroke at single cell resolution.

In multiple sclerosis (MS), sustained inflammatory activity can be visualized by iron-sensitive magnetic resonance imaging (MRI) at the edges of chronic lesions. These paramagnetic rim lesions (PRLs) are associated with clinical worsening, although the cell type-specific and molecular pathways of iron uptake and metabolism are not well known. We studied two postmortem cohorts: an exploratory formalin-fixed paraffin-embedded (FFPE) tissue cohort of 18 controls and 24 MS cases and a confirmatory snap-frozen cohort of 6 controls and 14 MS cases. Besides myelin and non-heme iron imaging, the haptoglobin-hemoglobin scavenger receptor CD163, the iron-metabolizing markers HMOX1 and HAMP as well as immune-related markers P2RY12, CD68, C1QA and IL10 were visualized in myeloid cell (MC) subtypes at RNA and protein levels across different MS lesion areas. In addition, we studied PRLs in vivo in a cohort of 98 people with MS (pwMS) via iron-sensitive 3 T MRI and haptoglobin genotyping by PCR. CSF samples were available from 38 pwMS for soluble CD163 (sCD163) protein level measurements by ELISA. In postmortem tissues, we observed that iron uptake was linked to rim-associated C1QA -expressing MC subtypes, characterized by upregulation of CD163 , HMOX1 , HAMP and, conversely, downregulation of P2RY12 . We found that pwMS with ≥ 4 PRLs had higher sCD163 levels in the CSF than pwMS with ≤ 3 PRLs with sCD163 correlating with the number of PRLs. The number of PRLs was associated with clinical worsening but not with age, sex or haptoglobin genotype of pwMS. However, pwMS with Hp2-1/Hp2-2 haplotypes had higher clinical disability scores than pwMS with Hp1-1 . In summary, we observed upregulation of the CD163-HMOX1-HAMP axis in MC subtypes at chronic active lesion rims, suggesting haptoglobin-bound hemoglobin but not transferrin-bound iron as a critical source for MC-associated iron uptake in MS. The correlation of CSF-associated sCD163 with PRL counts in MS highlights the relevance of CD163-mediated iron uptake via haptoglobin-bound hemoglobin. Also, while Hp haplotypes had no noticeable influence on PRL counts, pwMS carriers of a Hp2 allele might have a higher risk to experience clinical worsening.

Previous studies have reported that microglia depletion leads to impairment of synapse formation and these cells rapidly repopulate from CNS progenitors. However, the impact of microglia depletion and repopulation in the long-term state of the CNS environment has not been characterized. Here, we report that acute and synchronous microglia depletion and subsequent repopulation induces gray matter microgliosis, neuronal death in the somatosensory cortex and ataxia-like behavior. We find a type 1 interferon inflammatory signature in degenerating somatosensory cortex from microglia-depleted mice. Transcriptomic and mass cytometry analysis of repopulated microglia demonstrates an interferon regulatory factor 7-driven activation state. Minocycline and anti-IFNAR1 antibody treatment attenuate the CNS type 1 interferon-driven inflammation, restore microglia homeostasis and reduce ataxic behavior. Neither microglia depletion nor repopulation impact neuropathology or T-cell responses during experimental autoimmune encephalomyelitis. Together, we found that acute microglia ablation induces a type 1 interferon activation state of gray matter microglia associated with acute neurodegeneration. Previous studies have shown that depletion of microglia at early developmental stages leads to neuronal death. Here the authors use an inducible system to ablate microglia in adulthood, showing that such depletion leads to ataxia-like behavior and neuronal loss, and identifying the inflammatory components that may contribute.

T2*-weighted multi-echo gradient-echo magnetic resonance imaging and its reciprocal R2* are used in brain imaging due to their sensitivity to iron content. In patients with multiple sclerosis who display pathological alterations in iron and myelin contents, the use of R2* may offer a unique way to untangle mechanisms of disease. Coronal slices from 8 brains of deceased multiple sclerosis patients were imaged using a whole-body 7.0 Tesla MRI scanner. The scanning protocol included three-dimensional (3D) T2*-w multi-echo gradient-echo and 2D T2-w turbo spin echo (TSE) sequences. Histopathological analyses of myelin and iron content were done using Luxol fast blue and proteolipid myelin staining and 3,3'-diaminobenzidine tetrahydrochloride enhanced Turnbull blue staining. Quantification of R2*, myelin and iron intensity were obtained. Variations in R2* were found to be affected differently by myelin and iron content in different regions of multiple sclerosis brains. The data shall inform clinical investigators in addressing the role of T2*/R2* variations as a biomarker of tissue integrity in brains of MS patients, in vivo.

The myelin‐associated inhibitor Nogo‐A (Reticulon 4, RTN4) restricts axonal outgrowth, plasticity, and neural circuitry formation in experimental models of spinal cord injury (SCI) and is targeted in clinical interventions starting treatment within 4 weeks post‐SCI. Specifically, Nogo‐A expressed by oligodendroglia restricts compensatory neurite sprouting. To interrogate the hypothesis of an inducible, lesion reactive Nogo‐A expression over time, we analyzed the spatiotemporal Nogo‐A expression at the spinal lesion core (region of tissue necrosis and axonal damage/pruning) and perilesional rim (region of plasticity formation). Spinal cord specimens of SCI subjects (n = 22) were compared to neuropathologically unaltered controls (n = 9). Nogo‐A expression was investigated ranging from acute (0–3 days), early subacute (4–21 days), late subacute (22–90 days) to early chronic–chronic (91 days to 1.5 years after SCI) stages after SCI. Nogo‐A expression in controls is confined to motoneurons in the anterior horn and to oligodendrocytes in gray and white matter. After SCI, the number of Nogo‐A+ and TPPP/p25+ oligodendrocytes (i) inclined at the organizing perilesional rim specifically, (ii) increased further over time, and (iii) peaked at chronic stages after SCI. By contrast, at the lesion core, the number of Nogo‐A+ and TPPP/p25+ oligodendrocytes did not increase. Increasing numbers of Nogo‐A+ oligodendrocytes coincided with oligodendrogenesis corroborated by Nogo‐A coexpression of Ki67+, TPPP/p25+ proliferating oligodendrocytes. Nogo‐A oligodendrocyte expression emerges at perilesional (plasticity) regions over time and suggests an extended therapeutical window for anti‐Nogo‐A pathway targeting interventions beyond 4 weeks in patients after SCI. Nogo‐A oligodendrocytes expression emerges at perilesional regions over time and suggests an extended therapeutical window for anti‐Nogo‐A pathway trageting interventrions beyond four weeks in patients after spinal cord injury.

Neocortical lesions (NLs) are an important pathological component of multiple sclerosis (MS), but their visualization by magnetic resonance imaging (MRI) remains challenging. We aimed at assessing the sensitivity of multi echo gradient echo (ME-GRE) T2*-weighted MRI at 7.0 Tesla in depicting NLs compared to myelin and iron staining. Samples from two MS patients were imaged post mortem using a whole body 7 T MRI scanner with a 24-channel receive-only array. Isotropic 200 micron resolution images with varying T2* weighting were reconstructed from the ME-GRE data and converted into R2* maps. Immunohistochemical staining for myelin (proteolipid protein, PLP) and diaminobenzidine-enhanced Turnbull blue staining for iron were performed. Prospective and retrospective sensitivities of MRI for the detection of NLs were 48% and 67% respectively. We observed MRI maps detecting only a small portion of 20 subpial NLs extending over large cortical areas on PLP stainings. No MRI signal changes suggestive of iron accumulation in NLs were observed. Conversely, R2* maps indicated iron loss in NLs, which was confirmed by histological quantification. High-resolution post mortem imaging using R2* and magnitude maps permits detection of focal NLs. However, disclosing extensive subpial demyelination with MRI remains challenging.

Changes in brain iron levels are a consistent feature of multiple sclerosis (MS) over its disease course. They encompass iron loss in oligodendrocytes in myelinated brain regions and iron accumulation in myeloid cells at so-called paramagnetic rims of chronic active lesions. Here, we explore the mechanisms behind this overall shift of iron from oligodendrocytes (OLs) to myeloid cells (MCs) and the loss of total brain-iron in MS. We investigated the expression of various iron importers and exporters, applying immunohistochemistry to a sample of control and MS autopsy cases. Additionally, we studied the transcriptional response of iron-related genes in primary rodent OL progenitor cells (OPCs) and microglia (MG) to various combinations of known MS-relevant pro-inflammatory stimuli together with iron loading. Histologically, we identified a correlation of OL-iron accumulation and the expression of the ferritin receptor TIM1 in myelinated white matter and observed an increase in the expression of iron-related proteins in myeloid cells at the lesion rims of MS plaques. qPCR revealed a marked increase of the heme scavenging and degradation machinery of MG under IFN-γ exposure, while OPCs changed to a more iron-inert phenotype with apparent decreased iron handling capabilities under MS-like inflammatory stimulation. Collectively, our data suggest that OL iron loss in MS is mainly due to a decrease in ferritin iron import. Iron accumulation in MCs at rims of chronic active lesions is in part driven by up-regulation of heme import and metabolism, while these cells also actively export ferritin.