Transient enlargement of brain ventricles during relapsing-remitting multiple sclerosis and experimental autoimmune encephalomyelitis
Jason M. Millward, … , Thoralf Niendorf, Sonia Waiczies
Jason M. Millward, … , Thoralf Niendorf, Sonia Waiczies
Published November 5, 2020
Citation Information: JCI Insight. 2020;5(21):e140040. https://doi.org/10.1172/jci.insight.140040.
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Research Article Inflammation

Transient enlargement of brain ventricles during relapsing-remitting multiple sclerosis and experimental autoimmune encephalomyelitis

Abstract

The brain ventricles are part of the fluid compartments bridging the CNS with the periphery. Using MRI, we previously observed a pronounced increase in ventricle volume (VV) in the experimental autoimmune encephalomyelitis (EAE) model of multiple sclerosis (MS). Here, we examined VV changes in EAE and MS patients in longitudinal studies with frequent serial MRI scans. EAE mice underwent serial MRI for up to 2 months, with gadolinium contrast as a proxy of inflammation, confirmed by histopathology. We performed a time-series analysis of clinical and MRI data from a prior clinical trial in which RRMS patients underwent monthly MRI scans over 1 year. VV increased dramatically during preonset EAE, resolving upon clinical remission. VV changes coincided with blood-brain barrier disruption and inflammation. VV was normal at the termination of the experiment, when mice were still symptomatic. The majority of relapsing-remitting MS (RRMS) patients showed dynamic VV fluctuations. Patients with contracting VV had lower disease severity and a shorter duration. These changes demonstrate that VV does not necessarily expand irreversibly in MS but, over short time scales, can expand and contract. Frequent monitoring of VV in patients will be essential to disentangle the disease-related processes driving short-term VV oscillations from persistent expansion resulting from atrophy.

Authors

Jason M. Millward, Paula Ramos Delgado, Alina Smorodchenko, Laura Boehmert, Joao Periquito, Henning M. Reimann, Christian Prinz, Antje Els, Michael Scheel, Judith Bellmann-Strobl, Helmar Waiczies, Jens Wuerfel, Carmen Infante-Duarte, Claudia Chien, Joseph Kuchling, Andreas Pohlmann, Frauke Zipp, Friedemann Paul, Thoralf Niendorf, Sonia Waiczies

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Figure 5

Schematic for time-series analysis workflow.

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Schematic for time-series analysis workflow. From the cohort of n = 33 R...
From the cohort of n = 33 RRMS patients, we performed the time-series analysis on the subset of n = 24 patients who showed contractions in ventricle volume greater than the ± 6% range of normal variation. Ventricle volumes were measured at 13 monthly time points. At the same time points, an additional 8 MRI parameters and 4 clinical parameters were measured. This allowed each of these measures to be considered as a time series. Using the cross-correlation function, the cross-correlation coefficients between 2 time series can be calculated; significant coefficients indicate that events of one series precede (negative time lag) or follow (positive time lag) the events of another series. In the current study, we limited the consideration of significant cross-correlation coefficients to ± 2 time lags (i.e., ± 2 months). From n = 24 patients, n = 12 variables, and n = 5 time lags (including the 0 time lag), a total of 1440 coefficients was calculated. From the coefficients with nominal P < 0.05, the FDR correction for multiple comparisons was applied, to yield the corrected significant cross-correlation coefficients, which were then displayed in the 3D plots.