Megalencephalic leukoencephalopathy with subcortical cysts is a developmental disorder of the gliovascular unit
- Collège de France, France
- GIP Cyceron, France
- ESPCI, France
- University of Paris, France
- Hopital Trousseau, France
- Institut Cochin, France
- University of Barcelona, Spain
- INSERM U919, France
Abstract
Absence of the astrocyte-specific membrane protein MLC1 is responsible for megalencephalic leukoencephalopathy with subcortical cysts (MLC), a rare type of leukodystrophy characterized by early-onset macrocephaly and progressive white matter vacuolation that lead to ataxia, spasticity, and cognitive decline. During postnatal development (from P5 to P15 in the mouse), MLC1 forms a membrane complex with GlialCAM (another astrocytic transmembrane protein) at the junctions between perivascular astrocytic processes. Perivascular astrocytic processes along with blood vessels form the gliovascular unit. It was not previously known how MLC1 influences the physiology of the gliovascular unit. Here, using the Mlc1 knock-out (KO) mouse model of MLC, we demonstrated that MLC1 controls the postnatal development and organization of perivascular astrocytic processes, vascular smooth muscle cell contractility, neurovascular coupling and intraparenchymal interstitial fluid clearance. Our data suggest that MLC is a developmental disorder of the gliovascular unit, and perivascular astrocytic processes and vascular smooth muscle cell maturation defects are primary events in the pathogenesis of MLC and therapeutic targets for this disease.
Data availability
All data has been included in the manuscript and supporting files (please see supplementary tables for raw data).
Article and author information
Author details
Anne-Cécile Boulay
Salvatore Cisternino
Martine Cohen-Salmon
Funding
Association Européenne contre les Leucodystrophies (ELA2012-014C2B)
- Martine Cohen-Salmon
Fondation Maladies Rares (20170603)
- Martine Cohen-Salmon
Fondation pour la Recherche Médicale (PLP20170939025p60)
- Alice Gilbert
Fondation pour la Recherche Médicale (AJE20171039094)
- Martine Cohen-Salmon
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: All animal experiments were carried out in compliance with the European Directive 2010/63/EU on the protection of animals used for scientific purposes and the guidelines issued by the French National Animal Care and Use Committee (reference: 2019021814073504 and 2019022113258393).
Human subjects: Our study included specimens obtained from the brain collection "Hôpitaux Universitaires de l'Est Parisien - Neuropathologie du développement" (Biobank identification number BB-0033-00082). Informed consent was obtained for autopsy of the brain and histological examination.
Copyright
© 2021, Gilbert et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 1,344
- views
-
- 244
- downloads
-
- 20
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Megalencephalic leukoencephalopathy with subcortical cysts is a developmental disorder of the gliovascular unit
eLife 10:e71379.
https://doi.org/10.7554/eLife.71379
Further reading
-
- Neuroscience
Research on brain plasticity, particularly in the context of deafness, consistently emphasizes the reorganization of the auditory cortex. But to what extent do all individuals with deafness show the same level of reorganization? To address this question, we examined the individual differences in functional connectivity (FC) from the deprived auditory cortex. Our findings demonstrate remarkable differentiation between individuals deriving from the absence of shared auditory experiences, resulting in heightened FC variability among deaf individuals, compared to more consistent FC in the hearing group. Notably, connectivity to language regions becomes more diverse across individuals with deafness. This does not stem from delayed language acquisition; it is found in deaf native signers, who are exposed to natural language since birth. However, comparing FC diversity between deaf native signers and deaf delayed signers, who were deprived of language in early development, we show that language experience also impacts individual differences, although to a more moderate extent. Overall, our research points out the intricate interplay between brain plasticity and individual differences, shedding light on the diverse ways reorganization manifests among individuals. It joins findings of increased connectivity diversity in blindness and highlights the importance of considering individual differences in personalized rehabilitation for sensory loss.
-
- Computational and Systems Biology
- Neuroscience
Fiber photometry has become a popular technique to measure neural activity in vivo, but common analysis strategies can reduce the detection of effects because they condense within-trial signals into summary measures, and discard trial-level information by averaging across-trials. We propose a novel photometry statistical framework based on functional linear mixed modeling, which enables hypothesis testing of variable effects at every trial time-point, and uses trial-level signals without averaging. This makes it possible to compare the timing and magnitude of signals across conditions while accounting for between-animal differences. Our framework produces a series of plots that illustrate covariate effect estimates and statistical significance at each trial time-point. By exploiting signal autocorrelation, our methodology yields joint 95% confidence intervals that account for inspecting effects across the entire trial and improve the detection of event-related signal changes over common multiple comparisons correction strategies. We reanalyze data from a recent study proposing a theory for the role of mesolimbic dopamine in reward learning, and show the capability of our framework to reveal significant effects obscured by standard analysis approaches. For example, our method identifies two dopamine components with distinct temporal dynamics in response to reward delivery. In simulation experiments, our methodology yields improved statistical power over common analysis approaches. Finally, we provide an open-source package and analysis guide for applying our framework.
