Abstract
OBJECTIVE: To understand the progressive nature of amyotrophic lateral sclerosis (ALS) by investigating differential brain patterns of gray and white matter involvement in clinically or genetically defined subgroups of patients using cross-sectional, longitudinal, and multimodal MRI. METHODS: We assessed cortical thickness, subcortical volumes, and white matter connectivity from T1-weighted and diffusion-weighted MRI in 292 patients with ALS (follow-up: n = 150) and 156 controls (follow-up: n = 72). Linear mixed-effects models were used to assess changes in structural brain measurements over time in patients compared to controls. RESULTS: Patients with a C9orf72 mutation (n = 24) showed widespread gray and white matter involvement at baseline, and extensive loss of white matter integrity in the connectome over time. In C9orf72-negative patients, we detected cortical thinning of motor and frontotemporal regions, and loss of white matter integrity of connections linked to the motor cortex. Patients with spinal onset displayed widespread white matter involvement at baseline and gray matter atrophy over time, whereas patients with bulbar onset started out with prominent gray matter involvement. Patients with unaffected cognition or behavior displayed predominantly motor system involvement, while widespread cerebral changes, including frontotemporal regions with progressive white matter involvement over time, were associated with impaired behavior or cognition. Progressive loss of gray and white matter integrity typically occurred in patients with shorter disease durations (<13 months), independent of progression rate. CONCLUSIONS: Heterogeneity of phenotype and C9orf72 genotype relates to distinct patterns of cerebral degeneration. We demonstrate that imaging studies have the potential to monitor disease progression and early intervention may be required to limit cerebral degeneration.
Original language | English |
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Pages (from-to) | e2592-e2604 |
Number of pages | 14 |
Journal | Neurology |
Volume | 94 |
Issue number | 24 |
DOIs | |
Publication status | Published - 16 Jun 2020 |
Funding
This work was supported by the ALS Foundation Netherlands. M.P.v.d.H. was further supported by the Netherlands Organization for Scientific Research VIDI grant (VIDI-452-16-015). M.A.v.E. was supported by the Netherlands Organization for Scientific Research VENI grant (91614039). L.H.v.d.B. further received funding from the Netherlands Organization for Scientific Research VICI grant and the Netherlands Organization for Health Research and Development, funded through the EU Joint Programme–Neurodegenerative Disease Research, JPND. L.H.v.d.B. received travel grants and consultancy fees from Shire and serves on scientific advisory boards for Treeway, Cytokinetics, and Biogen Idec. J.H.V. has received funding from the European Research Council under the European Union's Horizon 2020 research and innovation programme (grant agreement 772376–EScORIAL). H. van der Burgh, H.-J. Westeneng, R. Walhout, K. van Veenhuijzen, H. Tan, J. Meier, L. Bakker, J. Hendrikse, M. van Es, J. Veldink, and M. van den Heuvel report no disclosures. L. van den Berg reports grants from ALS Foundation Netherlands, The Netherlands Organization for Health Research and Development (VICI scheme, funded through the EU Joint Programme–Neurodegenerative Disease Research, JPND [SOPHIA, STRENGTH, ALS-CarE projects]), and personal fees from Shire, Cytokinetics, and Treeway, outside the submitted work. Go to Neurology.org/N for full disclosures. The Article Processing Charge was funded by UMC Utrecht.
Funders | Funder number |
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EU Joint Programme – Neurodegenerative Disease Research | |
Cytokinetics | |
European Commission | |
European Research Council | |
ZonMw | |
Nederlandse Organisatie voor Wetenschappelijk Onderzoek | 91614039, VIDI-452-16-015 |
Universitair Medisch Centrum Utrecht | |
Shire | |
Horizon 2020 | 772376–EScORIAL |
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A multimodal longitudinal study of structural brain involvement in amyotrophic lateral sclerosis
van der Burgh, H. K. (Contributor), DRYAD, 1 Jan 2020
DOI: 10.5061/dryad.8931zcrkv, http://datadryad.org/stash/dataset/doi:10.5061/dryad.8931zcrkv
Dataset / Software: Dataset