Cortical atrophy patterns in multiple sclerosis are non-random and clinically relevant

Grey matter atrophy is common in multiple sclerosis. However, in contrast with other neurodegenerative diseases, it is unclear whether grey matter atrophy in multiple sclerosis is a diffuse 'global' process or develops, instead, according to distinct anatomical patterns. Using source-based...

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Vydané v:	Brain (London, England : 1878) Ročník 139; číslo Pt 1; s. 115 - 126
Hlavní autori:	Steenwijk, Martijn D, Geurts, Jeroen J G, Daams, Marita, Tijms, Betty M, Wink, Alle Meije, Balk, Lisanne J, Tewarie, Prejaas K, Uitdehaag, Bernard M J, Barkhof, Frederik, Vrenken, Hugo, Pouwels, Petra J W
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	England 01.01.2016
Predmet:	Atrophy - pathology Case-Control Studies Cerebral Cortex - pathology Cognition Disorders - complications Cognition Disorders - pathology Disability Evaluation Female Gray Matter - pathology Humans Magnetic Resonance Imaging Male Middle Aged Models, Neurological Multiple Sclerosis - complications Multiple Sclerosis - pathology Neuroimaging White Matter - pathology neurodegeneration white matter grey matter MRI multiple sclerosis
ISSN:	1460-2156
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Abstract	Grey matter atrophy is common in multiple sclerosis. However, in contrast with other neurodegenerative diseases, it is unclear whether grey matter atrophy in multiple sclerosis is a diffuse 'global' process or develops, instead, according to distinct anatomical patterns. Using source-based morphometry we searched for anatomical patterns of co-varying cortical thickness and assessed their relationships with white matter pathology, physical disability and cognitive functioning. Magnetic resonance imaging was performed at 3 T in 208 patients with long-standing multiple sclerosis (141 females; age = 53.7 ± 9.6 years; disease duration = 20.2 ± 7.1 years) and 60 age- and sex-matched healthy controls. Spatial independent component analysis was performed on cortical thickness maps derived from 3D T1-weighted images across all subjects to identify co-varying patterns. The loadings, which reflect the presence of each cortical thickness pattern in a subject, were compared between patients with multiple sclerosis and healthy controls with generalized linear models. Stepwise linear regression analyses were used to assess whether white matter pathology was associated with these loadings and to identify the cortical thickness patterns that predict measures of physical and cognitive dysfunction. Ten cortical thickness patterns were identified, of which six had significantly lower loadings in patients with multiple sclerosis than in controls: the largest loading differences corresponded to the pattern predominantly involving the bilateral temporal pole and entorhinal cortex, and the pattern involving the bilateral posterior cingulate cortex. In patients with multiple sclerosis, overall white matter lesion load was negatively associated with the loadings of these two patterns. The final model for physical dysfunction as measured with Expanded Disability Status Scale score (adjusted R(2) = 0.297; P < 0.001) included the predictors age, overall white matter lesion load, the loadings of two cortical thickness patterns (bilateral sensorimotor cortex and bilateral insula), and global cortical thickness. The final model predicting average cognition (adjusted R(2) = 0.469; P < 0.001) consisted of age, the loadings of two cortical thickness patterns (bilateral posterior cingulate cortex and bilateral temporal pole), overall white matter lesion load and normal-appearing white matter integrity. Although white matter pathology measures were part of the final clinical regression models, they explained limited incremental variance (to a maximum of 4%). Several cortical atrophy patterns relevant for multiple sclerosis were found. This suggests that cortical atrophy in multiple sclerosis occurs largely in a non-random manner and develops (at least partly) according to distinct anatomical patterns. In addition, these cortical atrophy patterns showed stronger associations with clinical (especially cognitive) dysfunction than global cortical atrophy.
AbstractList	Grey matter atrophy is common in multiple sclerosis. However, in contrast with other neurodegenerative diseases, it is unclear whether grey matter atrophy in multiple sclerosis is a diffuse 'global' process or develops, instead, according to distinct anatomical patterns. Using source-based morphometry we searched for anatomical patterns of co-varying cortical thickness and assessed their relationships with white matter pathology, physical disability and cognitive functioning. Magnetic resonance imaging was performed at 3 T in 208 patients with long-standing multiple sclerosis (141 females; age = 53.7 ± 9.6 years; disease duration = 20.2 ± 7.1 years) and 60 age- and sex-matched healthy controls. Spatial independent component analysis was performed on cortical thickness maps derived from 3D T1-weighted images across all subjects to identify co-varying patterns. The loadings, which reflect the presence of each cortical thickness pattern in a subject, were compared between patients with multiple sclerosis and healthy controls with generalized linear models. Stepwise linear regression analyses were used to assess whether white matter pathology was associated with these loadings and to identify the cortical thickness patterns that predict measures of physical and cognitive dysfunction. Ten cortical thickness patterns were identified, of which six had significantly lower loadings in patients with multiple sclerosis than in controls: the largest loading differences corresponded to the pattern predominantly involving the bilateral temporal pole and entorhinal cortex, and the pattern involving the bilateral posterior cingulate cortex. In patients with multiple sclerosis, overall white matter lesion load was negatively associated with the loadings of these two patterns. The final model for physical dysfunction as measured with Expanded Disability Status Scale score (adjusted R(2) = 0.297; P < 0.001) included the predictors age, overall white matter lesion load, the loadings of two cortical thickness patterns (bilateral sensorimotor cortex and bilateral insula), and global cortical thickness. The final model predicting average cognition (adjusted R(2) = 0.469; P < 0.001) consisted of age, the loadings of two cortical thickness patterns (bilateral posterior cingulate cortex and bilateral temporal pole), overall white matter lesion load and normal-appearing white matter integrity. Although white matter pathology measures were part of the final clinical regression models, they explained limited incremental variance (to a maximum of 4%). Several cortical atrophy patterns relevant for multiple sclerosis were found. This suggests that cortical atrophy in multiple sclerosis occurs largely in a non-random manner and develops (at least partly) according to distinct anatomical patterns. In addition, these cortical atrophy patterns showed stronger associations with clinical (especially cognitive) dysfunction than global cortical atrophy.
Author	Daams, Marita Tijms, Betty M Uitdehaag, Bernard M J Wink, Alle Meije Pouwels, Petra J W Vrenken, Hugo Barkhof, Frederik Steenwijk, Martijn D Balk, Lisanne J Tewarie, Prejaas K Geurts, Jeroen J G
Author_xml	– sequence: 1 givenname: Martijn D surname: Steenwijk fullname: Steenwijk, Martijn D email: m.steenwijk@vumc.nl organization: 1 Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Centre, The Netherlands 2 Department of Physics and Medical Technology, Neuroscience Campus Amsterdam, VU University Medical Centre, The Netherlands m.steenwijk@vumc.nl – sequence: 2 givenname: Jeroen J G surname: Geurts fullname: Geurts, Jeroen J G organization: 3 Department of Anatomy and Neurosciences, Neuroscience Campus Amsterdam, VU University Medical Centre, The Netherlands – sequence: 3 givenname: Marita surname: Daams fullname: Daams, Marita organization: 1 Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Centre, The Netherlands 3 Department of Anatomy and Neurosciences, Neuroscience Campus Amsterdam, VU University Medical Centre, The Netherlands – sequence: 4 givenname: Betty M surname: Tijms fullname: Tijms, Betty M organization: 4 Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Centre, The Netherlands – sequence: 5 givenname: Alle Meije surname: Wink fullname: Wink, Alle Meije organization: 1 Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Centre, The Netherlands – sequence: 6 givenname: Lisanne J surname: Balk fullname: Balk, Lisanne J organization: 4 Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Centre, The Netherlands – sequence: 7 givenname: Prejaas K surname: Tewarie fullname: Tewarie, Prejaas K organization: 4 Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Centre, The Netherlands – sequence: 8 givenname: Bernard M J surname: Uitdehaag fullname: Uitdehaag, Bernard M J organization: 4 Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Centre, The Netherlands – sequence: 9 givenname: Frederik surname: Barkhof fullname: Barkhof, Frederik organization: 1 Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Centre, The Netherlands – sequence: 10 givenname: Hugo surname: Vrenken fullname: Vrenken, Hugo organization: 1 Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Centre, The Netherlands 2 Department of Physics and Medical Technology, Neuroscience Campus Amsterdam, VU University Medical Centre, The Netherlands – sequence: 11 givenname: Petra J W surname: Pouwels fullname: Pouwels, Petra J W organization: 2 Department of Physics and Medical Technology, Neuroscience Campus Amsterdam, VU University Medical Centre, The Netherlands
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Snippet	Grey matter atrophy is common in multiple sclerosis. However, in contrast with other neurodegenerative diseases, it is unclear whether grey matter atrophy in...
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SubjectTerms	Atrophy - pathology Case-Control Studies Cerebral Cortex - pathology Cognition Disorders - complications Cognition Disorders - pathology Disability Evaluation Female Gray Matter - pathology Humans Magnetic Resonance Imaging Male Middle Aged Models, Neurological Multiple Sclerosis - complications Multiple Sclerosis - pathology Neuroimaging White Matter - pathology
Title	Cortical atrophy patterns in multiple sclerosis are non-random and clinically relevant
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