Skip to main content
Advertisement
  • Neurology.org
  • Journals
    • Neurology
    • Clinical Practice
    • Education
    • Genetics
    • Neuroimmunology & Neuroinflammation
  • Online Sections
    • Neurology Video Journal Club
    • Neurology: Neuroimmunology & Neuroinflammation COVID-19 Article Hub
    • Diversity, Equity, & Inclusion (DEI)
    • Innovations in Care Delivery
    • Practice Buzz
    • Practice Current
    • Residents & Fellows
    • Without Borders
  • Collections
    • COVID-19
    • Disputes & Debates
    • Health Disparities
    • Infographics
    • Null Hypothesis
    • Patient Pages
    • Topics A-Z
    • Translations
  • Podcast
  • CME
  • About
    • About the Journals
    • Contact Us
    • Editorial Board
  • Authors
    • Submit New Manuscript
    • Submit Revised Manuscript
    • Author Center

Advanced Search

Main menu

  • Neurology.org
  • Journals
    • Neurology
    • Clinical Practice
    • Education
    • Genetics
    • Neuroimmunology & Neuroinflammation
  • Online Sections
    • Neurology Video Journal Club
    • Neurology: Neuroimmunology & Neuroinflammation COVID-19 Article Hub
    • Diversity, Equity, & Inclusion (DEI)
    • Innovations in Care Delivery
    • Practice Buzz
    • Practice Current
    • Residents & Fellows
    • Without Borders
  • Collections
    • COVID-19
    • Disputes & Debates
    • Health Disparities
    • Infographics
    • Null Hypothesis
    • Patient Pages
    • Topics A-Z
    • Translations
  • Podcast
  • CME
  • About
    • About the Journals
    • Contact Us
    • Editorial Board
  • Authors
    • Submit New Manuscript
    • Submit Revised Manuscript
    • Author Center
  • Home
  • Articles
  • Issues
  • COVID-19 Article Hub
  • Infographics & Video Summaries

User menu

  • My Alerts
  • Log in

Search

  • Advanced search
Neurology Neuroimmunology & Neuroinflammation
Home
A peer-reviewed clinical and translational neurology open access journal
  • My Alerts
  • Log in
Site Logo
  • Home
  • Articles
  • Issues
  • COVID-19 Article Hub
  • Infographics & Video Summaries

Share

November 2019; 6 (6) EditorialOpen Access

Untangling normal aging from disease-related brain atrophy in MS

Tim Sinnecker, Jens Wuerfel
First published September 25, 2019, DOI: https://doi.org/10.1212/NXI.0000000000000617
Tim Sinnecker
From the Departments of Medicine (T.S.), Neurologic Clinic and Policlinic, University Hospital Basel and University of Basel; qbig (T.S., J.W.), Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel; Medical Image Analysis Center Basel AG (T.S., J.W.); and Translational Imaging in Neurology [ThINK] Basel (T.S.), Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Switzerland.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jens Wuerfel
From the Departments of Medicine (T.S.), Neurologic Clinic and Policlinic, University Hospital Basel and University of Basel; qbig (T.S., J.W.), Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel; Medical Image Analysis Center Basel AG (T.S., J.W.); and Translational Imaging in Neurology [ThINK] Basel (T.S.), Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Switzerland.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Full PDF
Citation
Untangling normal aging from disease-related brain atrophy in MS
Tim Sinnecker, Jens Wuerfel
Neurol Neuroimmunol Neuroinflamm Nov 2019, 6 (6) e617; DOI: 10.1212/NXI.0000000000000617

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Permissions

Make Comment

See Comments

Downloads
384

Share

  • Article
  • Info & Disclosures
Loading

An accelerated brain atrophy rate is highly prevalent already in early MS and is known to correlate with cognitive and physical disability.1 Brain volume loss has therefore emerged as an important outcome measure in clinical MS studies. Nonetheless, in our daily clinical routine, quantitative brain volume measurements have not been widely implemented to monitor disease activity or treatment responses of individual patients with MS. To do this, there are some biological and technical limitations to be taken into consideration:1

Brain volume changes quantified by MRI do not necessarily reflect brain parenchymal tissue loss. Indeed, brain volume changes may result from the current physiologic state, e.g., variations in hydration or time point in the circadian rhythm. Also, the degree of inflammatory edema may significantly influence the measurement of brain volumes. On top of that, current techniques to measure brain volumes and brain volumetric changes using MRI are not free of errors, which often exceed 0.1%–0.2% (median) for longitudinal techniques and 1% (median) for cross-sectional approaches.1

True brain atrophy reflects tissue degradation in normal aging or pathologic circumstances caused by neurodegenerative processes, which include loss of neurons, glial cells, and axons. The contributing factors may overlap and accumulate2 being of particular importance in patients with progressive MS. Untangling age- and disease-specific effects of brain atrophy by discerning novel biomarkers for MS-related neurodegeneration would thus be an important step toward clinical application of volumetric brain imaging.2

In this issue of Neurology: Neuroimmunology & Neuroinflammation, Azevedo et al.3 applied mixed-effects models to a large MS cohort and 2 smaller cohorts of healthy controls (HCs). In a cohort spanning several decades, the authors observed that during aging, the relative share of MS-specific brain volume change decreased, whereas the proportion of age-related brain volume change increased. In more detail, the rate of disease-attributed brain volume loss decreased from −0.38%/y by age 30 years to −0.12%/y when participants reached age 60 years. At the same time, the rate of age-attributed brain volume changes accelerated from 0.01%/y to −0.31%/y.

The present study supports previous findings4 that brain volume loss in MS is influenced by multiple factors and that the currently applied disease-modifying therapies may not have a direct impact on it.2

The second key finding of the study by Azevedo et al. is that the deceleration of MS-specific brain volume change and the acceleration of age-related brain volume change during aging were more pronounced in the thalamus compared with the whole brain, however not detectable in the putamen and caudate nuclei.

Other studies have investigated disease- and region-specific brain volume changes in MS. The same research group reported that thalamic volume loss was consistent not only throughout the MS disease duration, but also in radiologically isolated syndrome patients. However, the authors noted that a larger group of HCs was needed to draw final conclusions.5 A smaller study by Bishop et al.6 also observed higher volume changes in both younger and older patients with MS vs HCs within the putamen and the thalamus, but differences in caudate volume loss did not reach statistical significance. Finally, a large retrospective MRI study by Ghione et al.7 observed accelerated increase of the lateral ventricle volumes predominantly within HCs, but not in patients with MS.

If the concept of disease- and region-specific brain atrophy in MS holds true, it would indeed allow for a better untangling of age- and disease-specific brain atrophy in MS. Surrogate brain areas could be defined that are more susceptible to MS-specific brain atrophy than atrophy caused by other mechanisms. Although the study by Azevedo et al. provides novel insights into this field, some open research questions still have to be faced.

It is still not well understood whether—and to what extent—MS disease activity and disease course modulate the relationship between age- and MS-specific brain atrophy. The study by Azevedo et al. cannot shed light on this because their MS cohort is characterized by an overall low disease activity (mean Expanded Disability Status Scale score 1.8 after a mean disease duration of 9.2 years), only 7.3% of all patients had secondary progressive MS, and none had primary progressive MS.

On the other hand, it would be interesting to identify the effects of comorbidities and genetic or lifestyle factors such as diet, smoking, and alcohol consumption on the share of MS-specific brain atrophy in elderly patients, as all of these factors were shown to alter brain atrophy during aging.8 Information on comorbidities was not reported in the study of Azevedo et al.

Furthermore, it is worthwhile to study the discriminative abilities of spinal cord volume loss to distinguish relapsing from progressive MS subgroups or to differentiate between MS-specific and age-related CNS atrophy.9

From a methodological and technical point of view, a limitation of this study is that 2 different and relatively small HC cohorts with shorter follow-up and in part different sequence parameters in comparison to the MS cohort were included. In addition, one might hypothesize that the study lacks power to untangle age- vs MS-specific brain volume changes in the putamen and caudate nuclei, as the measurement error for volume changes within these small subcortical structures might be higher than for whole-brain volume changes.10

In summary, the study by Azevedo et al. improves our understanding on the complex interaction of age- and disease-specific brain atrophy in MS, as so far only limited information on this issue is available in the literature. Brain volume loss remains a complex phenomenon that is modulated by various factors and not merely the reflection of a single condition as MS.

Study funding

No targeted funding reported.

Disclosure

T. Sinnecker received travel support from Actelion and Roche and speaker fees from Biogen and is part-time employee of the Medical Image Analysis Center Basel. J. Wuerfel is CEO of the Medical Image Analysis Center Basel. He served on scientific advisory boards for Actelion, Biogen, Genzyme-Sanofi, Idorsia, Novartis, and Roche. He is or was supported by grants of the EU (Horizon 2020), German Federal Ministries of Education and Research (BMBF), and of Economic Affairs and Energy (BMWI). Go to Neurology.org/NN for full disclosures.

Footnotes

  • Go to Neurology.org/NN for full disclosures. Funding information is provided at the end of the article.

  • See page e616

  • Received July 31, 2019.
  • Accepted in final form August 19, 2019.
  • Copyright © 2019 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.

This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND), which permits downloading and sharing the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

References

  1. 1.↵
    1. Sinnecker T,
    2. Granziera C,
    3. Wuerfel J,
    4. Schlaeger R
    . Future brain and spinal cord volumetric imaging in the clinic for monitoring treatment response in MS. Curr Treat Options Neurol 2018;20:17.
    OpenUrl
  2. 2.↵
    1. Geraldes R,
    2. Esiri MM,
    3. DeLuca GC,
    4. Palace J
    . Age-related small vessel disease: a potential contributor to neurodegeneration in multiple sclerosis. Brain Pathol 2017;27:707–722.
    OpenUrl
  3. 3.↵
    1. Azevedo CJ,
    2. Cen SY,
    3. Jaberzadeh A,
    4. Zheng L,
    5. Hauser SL,
    6. Pelletier D
    . Contribution of normal aging to brain atrophy in MS. Neurol Neuroimmunol Neuroinflamm 2019;6:e616. doi: 10.1212/NXI.0000000000000616.
    OpenUrl
  4. 4.↵
    1. Opfer R,
    2. Ostwaldt AC,
    3. Sormani MP, et al
    . Estimates of age-dependent cutoffs for pathological brain volume loss using SIENA/FSL-a longitudinal brain volumetry study in healthy adults. Neurobiol Aging 2018;65:1–6.
    OpenUrl
  5. 5.↵
    1. Azevedo CJ,
    2. Cen SY,
    3. Khadka S, et al
    . Thalamic atrophy in multiple sclerosis: a magnetic resonance imaging marker of neurodegeneration throughout disease. Ann Neurol 2018;83:223–234.
    OpenUrlCrossRefPubMed
  6. 6.↵
    1. Bishop CA,
    2. Newbould RD,
    3. Lee JS, et al
    . Analysis of ageing-associated grey matter volume in patients with multiple sclerosis shows excess atrophy in subcortical regions. Neuroimage Clin 2016;13:9–15.
    OpenUrl
  7. 7.↵
    1. Ghione E,
    2. Bergsland N,
    3. Dwyer MG, et al
    . Aging and brain atrophy in multiple sclerosis. J Neuroimaging 2019;29:527–535.
    OpenUrl
  8. 8.↵
    1. Enzinger C,
    2. Fazekas F,
    3. Matthews PM, et al
    . Risk factors for progression of brain atrophy in aging: six-year follow-up of normal subjects. Neurology 2005;64:1704–1711.
    OpenUrlCrossRefPubMed
  9. 9.↵
    1. Tsagkas C,
    2. Magon S,
    3. Gaetano L, et al
    . Preferential spinal cord volume loss in primary progressive multiple sclerosis. Mult Scler 2019;25:947–957.
    OpenUrl
  10. 10.↵
    1. Meijerman A,
    2. Amiri H,
    3. Steenwijk MD, et al
    . Reproducibility of deep gray matter atrophy rate measurement in a large multicenter dataset. Am J Neuroradiol 2018;39:46–53.
    OpenUrlAbstract/FREE Full Text

Letters: Rapid online correspondence

No comments have been published for this article.
Comment

REQUIREMENTS

If you are uploading a letter concerning an article:
You must have updated your disclosures within six months: http://submit.neurology.org

Your co-authors must send a completed Publishing Agreement Form to Neurology Staff (not necessary for the lead/corresponding author as the form below will suffice) before you upload your comment.

If you are responding to a comment that was written about an article you originally authored:
You (and co-authors) do not need to fill out forms or check disclosures as author forms are still valid
and apply to letter.

Submission specifications:

  • Submissions must be < 200 words with < 5 references. Reference 1 must be the article on which you are commenting.
  • Submissions should not have more than 5 authors. (Exception: original author replies can include all original authors of the article)
  • Submit only on articles published within 6 months of issue date.
  • Do not be redundant. Read any comments already posted on the article prior to submission.
  • Submitted comments are subject to editing and editor review prior to posting.

More guidelines and information on Disputes & Debates

Compose Comment

More information about text formats

Plain text

  • No HTML tags allowed.
  • Web page addresses and e-mail addresses turn into links automatically.
  • Lines and paragraphs break automatically.
Author Information
NOTE: The first author must also be the corresponding author of the comment.
First or given name, e.g. 'Peter'.
Your last, or family, name, e.g. 'MacMoody'.
Your email address, e.g. higgs-boson@gmail.com
Your role and/or occupation, e.g. 'Orthopedic Surgeon'.
Your organization or institution (if applicable), e.g. 'Royal Free Hospital'.
Publishing Agreement
NOTE: All authors, besides the first/corresponding author, must complete a separate Publishing Agreement Form and provide via email to the editorial office before comments can be posted.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.

Vertical Tabs

You May Also be Interested in

Back to top
  • Article
    • Study funding
    • Disclosure
    • Footnotes
    • References
  • Info & Disclosures
Advertisement

SARS-CoV-2 Vaccination Safety in Guillain-Barré Syndrome, Chronic Inflammatory Demyelinating Polyneuropathy, and Multifocal Motor Neuropathy

Dr. Jeffrey Allen and Dr. Nicholas Purcell

► Watch

Related Articles

  • Contribution of normal aging to brain atrophy in MS

Topics Discussed

  • All Demyelinating disease (CNS)
  • Multiple sclerosis
  • Cerebrospinal Fluid
  • MRI

Alert Me

  • Alert me when eletters are published

Recommended articles

  • Article
    Evolution of Brain Volume Loss Rates in Early Stages of Multiple Sclerosis
    Tomas Uher, Jan Krasensky, Charles Malpas et al.
    Neurology: Neuroimmunology & Neuroinflammation, March 16, 2021
  • Article
    Teriflunomide slows BVL in relapsing MS
    A reanalysis of the TEMSO MRI data set using SIENA
    Ernst-Wilhelm Radue, Till Sprenger, Laura Gaetano et al.
    Neurology: Neuroimmunology & Neuroinflammation, August 09, 2017
  • Views & Reviews
    Mechanisms of action of disease-modifying agents and brain volume changes in multiple sclerosis
    R. Zivadinov, A. T. Reder, M. Filippi et al.
    Neurology, July 07, 2008
  • Article
    Fingolimod effect on gray matter, thalamus, and white matter in patients with multiple sclerosis
    Laura Gaetano, Dieter A. Häring, Ernst-Wilhelm Radue et al.
    Neurology, March 14, 2018
Neurology - Neuroimmunology Neuroinflammation: 10 (3)

Articles

  • Articles
  • Issues
  • Popular Articles

About

  • About the Journals
  • Ethics Policies
  • Editors & Editorial Board
  • Contact Us
  • Advertise

Submit

  • Author Center
  • Submit a Manuscript
  • Information for Reviewers
  • AAN Guidelines
  • Permissions

Subscribers

  • Subscribe
  • Sign up for eAlerts
  • RSS Feed
Site Logo
  • Visit neurology Template on Facebook
  • Follow neurology Template on Twitter
  • Visit Neurology on YouTube
  • Neurology
  • Neurology: Clinical Practice
  • Neurology: Education
  • Neurology: Genetics
  • Neurology: Neuroimmunology & Neuroinflammation
  • AAN.com
  • AANnews
  • Continuum
  • Brain & Life
  • Neurology Today

Wolters Kluwer Logo

Neurology: Neuroimmunology & Neuroinflammation
Online ISSN: 2332-7812

© 2023 American Academy of Neurology

  • Privacy Policy
  • Feedback
  • Advertise