Multiparametric in vivo analyses of the brain and spine identify structural and metabolic biomarkers in men with adrenomyeloneuropathy

Leriglitazone halts disease progression in adult patients with early cerebral adrenoleukodystrophy

Cerebral adrenoleukodystrophy (CALD) is an X-linked rapidly progressive demyelinating disease leading to death usually within a few years. The standard of care is haematopoietic stem cell transplantation (HSCT), but many men are not eligible due to age, absence of a matched donor or lesions of the corticospinal tracts (CST). Based on the ADVANCE study showing that leriglitazone decreases the occurrence of CALD, we treated 13 adult CALD patients (19-67 years of age) either not eligible for HSCT (n = 8) or awaiting HSCT (n = 5). Patients were monitored every 3 months with standardized neurological scores, plasma biomarkers and brain MRI comprising lesion volumetrics and diffusion tensor imaging. The disease stabilized clinically and radiologically in 10 patients with up to 2 years of follow-up. Five patients presented with gadolinium enhancing CST lesions that all turned gadolinium negative and, remarkably, regressed in four patients. Plasma neurofilament light chain levels stabilized in all 10 patients and correlated with lesion load. The two patients who continued to deteriorate were over 60 years of age with prominent cognitive impairment. One patient died rapidly from coronavirus disease 2019. These results suggest that leriglitazone can arrest disease progression in adults with early-stage CALD and may be an alternative treatment to HSCT.

Hematopoietic stem cell transplantation in leukodystrophies

More than 50 leukodystrophies have been described. This group of inherited disorders affects myelin development and/or maintenance and can manifest from birth to adulthood. Neuroinflammation is a hallmark of some leukodystrophies, explaining in part the therapeutic benefit of hematopoietic stem cell transplantation (HSCT). Indeed, in addition to supplying the CNS with myelomonocyte donor cells expressing the deficient protein or enzyme, HSCT allows the restoration of normal microglia function, which may act on neuroinflammation. In this chapter, we explore the rationale, indication, and outcome of HSCT in Cerebral Adrenoleukodystrophy (CALD), Metachromatic Leukodystrophy (MLD), Krabbe Disease (KD), and Adult-onset Leukoencephalopathy with Axonal Spheroids and Pigmented Glia (ALSP), which are among the most frequent leukodystrophies. For these leukodystrophies, HSCT may modify notably the natural history and improve CNS-related deficits, provided that the procedure is performed early into the disease course. In addition, we discuss the recent development of ex vivo gene therapy for CALD and MLD as a promising alternative to allograft.

Brain MRI detects early-stage alterations and disease progression in Friedreich ataxia

Friedreich ataxia is a progressive neurodegenerative disorder characterized by cerebellar and spinal atrophy. However, studies to elucidate the longitudinal progression of the pathology in the brain are somewhat inconsistent and limited, especially for early-stage Friedreich ataxia. Using a multimodal neuroimaging protocol, combined with advanced analysis methods, we sought to identify macrostructural and microstructural alterations in the brain of patients with early-stage Friedreich ataxia to better understand its distribution patterns and progression. We enrolled 28 patients with Friedreich ataxia and 20 age- and gender-matched controls. Longitudinal clinical and imaging data were collected in the patients at baseline, 12, 24 and 36 months. Macrostructural differences were observed in patients with Friedreich ataxia, compared to controls, including lower volume of the cerebellar white matter (but not cerebellar grey matter), superior cerebellar peduncle, thalamus and brainstem structures, and higher volume of the fourth ventricle. Diffusion tensor imaging and fixel-based analysis metrics also showed microstructural differences in several brain regions, especially in the cerebellum and corticospinal tract. Over time, many of these macrostructural and microstructural alterations progressed, especially cerebellar grey and white matter volumes, and microstructure of the superior cerebellar peduncle, posterior limb of the internal capsule and superior corona radiata. In addition, linear regressions showed significant associations between many of those imaging metrics and clinical scales. This study provides evidence of early-stage macrostructural and microstructural alterations and of progression over time in the brain in Friedreich ataxia. Moreover, it allows to non-invasively map such brain alterations over a longer period (3 years) than any previous study, and identifies several brain regions with significant involvement in the disease progression besides the cerebellum. We show that fixel-based analysis of diffusion MRI data is particularly sensitive to longitudinal change in the cerebellar peduncles, as well as motor and sensory white matter tracts. In combination with other morphometric measures, they may therefore provide sensitive imaging biomarkers of disease progression for clinical trials.

Development of PPARγ Agonists for the Treatment of Neuroinflammatory and Neurodegenerative Diseases: Leriglitazone as a Promising Candidate

Increasing evidence suggests that the peroxisome proliferator-activated receptor γ (PPARγ), a member of the nuclear receptor superfamily, plays an important role in physiological processes in the central nervous system (CNS) and is involved in cellular metabolism and repair. Cellular damage caused by acute brain injury and long-term neurodegenerative disorders is associated with alterations of these metabolic processes leading to mitochondrial dysfunction, oxidative stress, and neuroinflammation. PPARγ agonists have demonstrated the potential to be effective treatments for CNS diseases in preclinical models, but to date, most drugs have failed to show efficacy in clinical trials of neurodegenerative diseases including amyotrophic lateral sclerosis, Parkinson's disease, and Alzheimer's disease. The most likely explanation for this lack of efficacy is the insufficient brain exposure of these PPARγ agonists. Leriglitazone is a novel, blood-brain barrier (BBB)-penetrant PPARγ agonist that is being developed to treat CNS diseases. Here, we review the main roles of PPARγ in physiology and pathophysiology in the CNS, describe the mechanism of action of PPARγ agonists, and discuss the evidence supporting the use of leriglitazone to treat CNS diseases.

Fixel-based Analysis of Diffusion MRI: Methods, Applications, Challenges and Opportunities

Diffusion MRI has provided the neuroimaging community with a powerful tool to acquire in-vivo data sensitive to microstructural features of white matter, up to 3 orders of magnitude smaller than typical voxel sizes. The key to extracting such valuable information lies in complex modelling techniques, which form the link between the rich diffusion MRI data and various metrics related to the microstructural organization. Over time, increasingly advanced techniques have been developed, up to the point where some diffusion MRI models can now provide access to properties specific to individual fibre populations in each voxel in the presence of multiple "crossing" fibre pathways. While highly valuable, such fibre-specific information poses unique challenges for typical image processing pipelines and statistical analysis. In this work, we review the "Fixel-Based Analysis" (FBA) framework, which implements bespoke solutions to this end. It has recently seen a stark increase in adoption for studies of both typical (healthy) populations as well as a wide range of clinical populations. We describe the main concepts related to Fixel-Based Analyses, as well as the methods and specific steps involved in a state-of-the-art FBA pipeline, with a focus on providing researchers with practical advice on how to interpret results. We also include an overview of the scope of all current FBA studies, categorized across a broad range of neuro-scientific domains, listing key design choices and summarizing their main results and conclusions. Finally, we critically discuss several aspects and challenges involved with the FBA framework, and outline some directions and future opportunities.

Cognitive Functions in Adult-Onset Phenotypes of X-Linked Adrenoleukodystrophy

OBJECTIVE

X-linked adrenoleukodystrophy (X-ALD) is a rare genetic disorder characterized by progressive demyelination ranging from mild myelopathic forms (adrenomyeloneuropathy [AMN]) to severe cerebral variants (adult cerebral adrenoleukodystrophy [ACALD]). The aim of this study was to compare cognitive function in adult-onset X-ALD phenotypes.

METHODS

Cognitive function in various domains (intelligence, attention, memory, executive function, and processing speed) was assessed in 172 adults (117 with AMN, 30 with arrested ACALD, and 25 with acute ACALD) using comprehensive neuropsychological batteries. Phenotype differences were examined by analyses of variance.

RESULTS

X-ALD phenotypes significantly differed in nonverbal intelligence, sustained attention, verbal encoding, nonverbal recognition, and processing speed (ps < 0.050). No group differences emerged regarding verbal intelligence, verbal retrieval and recognition, and executive function (ps > 0.050). Specifically, patients with acute ACALD showed severe cognitive deficits compared to AMN and normal data, with largest effects on processing speed. Contrary, cognition was overall intact in patients with AMN, independent of sex and corticospinal tract involvement, and those with arrested ACALD showed mild cognitive dysfunction, particularly in verbal encoding and processing speed.

INTERPRETATION

Cerebral demyelination in patients with X-ALD causes white matter dementia, mainly characterized by an extreme slowdown in processing speed associated with deficits in attention and learning. Most patients with AMN show intact cognitive function. Future prospective, longitudinal studies with more sensitive imaging techniques are required to clarify whether early mild cognitive dysfunction found in some patients with AMN may be associated with subtle myelin abnormalities that do not yet appear as white matter lesions on cerebral MRI (cMRI) but have the potential to serve as early predictors of later cerebral progression. ANN NEUROL 2021;90:266-273.

Minimum detectable spinal cord atrophy with automatic segmentation: Investigations using an open-access dataset of healthy participants

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Evaluate the robustness of an automated analysis pipeline for detecting SC atrophy.

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Simulate spinal cord atrophy and scan-rescan variability.

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Fully automated analysis method available on an open access database.

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Evaluation of sample size and inter/intra-subject variability for T1w and T2w images.

Spinal cord atrophy is a well-known biomarker in multiple sclerosis (MS) and other diseases. It is measured by segmenting the spinal cord on an MRI image and computing the average cross-sectional area (CSA) over a few slices. Introduced about 25 years ago, this procedure is highly sensitive to the quality of the segmentation and is prone to rater-bias. Recently, fully-automated spinal cord segmentation methods, which remove the rater-bias and enable the automated analysis of large populations, have been introduced. A lingering question related to these automated methods is: How reliable are they at detecting atrophy? In this study, we evaluated the precision and accuracy of automated atrophy measurements by simulating scan-rescan experiments.

Spinal cord MRI data from the open-access spine-generic project were used. The dataset aggregates 42 sites worldwide and consists of 260 healthy subjects and includes T1w and T2w contrasts. To simulate atrophy, each volume was globally rescaled at various scaling factors. Moreover, to simulate patient repositioning, random rigid transformations were applied. Using the DeepSeg algorithm from the Spinal Cord Toolbox, the spinal cord was segmented and vertebral levels were identified. Then, the average CSA between C3-C5 vertebral levels was computed for each Monte Carlo sample, allowing us to derive measures of atrophy, intra/inter-subject variability, and sample-size calculations.

The minimum sample size required to detect an atrophy of 2% between unpaired study arms, commonly seen in MS studies, was 467 +/− 13.9 using T1w and 467 +/− 3.2 using T2w images. The minimum sample size to detect a longitudinal atrophy (between paired study arms) of 0.8% was 60 +/− 25.1 using T1w and 10 +/− 1.2 using T2w images. At the intra-subject level, the estimated CSA, observed in this study, showed good precision compared to other studies with COVs (across Monte Carlo transformations) of 0.8% for T1w and 0.6% for T2w images.

While these sample sizes seem small, we would like to stress that these results correspond to a “best case” scenario, in that the dataset used here was of particularly good quality and the model for simulating atrophy does not encompass all the variability met in real-life datasets. The simulated atrophy and scan-rescan variability may over-simplify the biological reality. The proposed framework is open-source and available at https://csa-atrophy.readthedocs.io/.