Gray matter networks and cognitive impairment in multiple sclerosis
Coordinated patterns of gray matter morphology can be represented as networks, and network disruptions may explain cognitive dysfunction related to multiple sclerosis (MS). To investigate whether single-subject gray matter network properties are related to impaired cognition in MS. We studied 148 MS...
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| Vydané v: | Multiple sclerosis Ročník 25; číslo 3; s. 382 |
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| Hlavní autori: | , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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England
01.03.2019
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| ISSN: | 1477-0970, 1477-0970 |
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| Abstract | Coordinated patterns of gray matter morphology can be represented as networks, and network disruptions may explain cognitive dysfunction related to multiple sclerosis (MS).
To investigate whether single-subject gray matter network properties are related to impaired cognition in MS.
We studied 148 MS patients (99 female) and 33 healthy controls (HC, 21 female). Seven network parameters were computed and compared within MS between cognitively normal and impaired subjects, and associated with performance on neuropsychological tests in six cognitive domains with regression models. Analyses were controlled for age, gender, whole-brain gray matter volumes, and education level.
Compared to MS subjects with normal cognition, MS subjects with cognitive impairment showed a more random network organization as indicated by lower lambda values (all p < 0.05). Worse average cognition and executive function were associated with lower lambda values. Impaired information processing speed, working memory, and attention were associated with lower clustering values.
Our findings indicate that MS subjects with a more randomly organized gray matter network show worse cognitive functioning, suggesting that single-subject gray matter graphs may capture neurological dysfunction due to MS. |
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| AbstractList | Coordinated patterns of gray matter morphology can be represented as networks, and network disruptions may explain cognitive dysfunction related to multiple sclerosis (MS).
To investigate whether single-subject gray matter network properties are related to impaired cognition in MS.
We studied 148 MS patients (99 female) and 33 healthy controls (HC, 21 female). Seven network parameters were computed and compared within MS between cognitively normal and impaired subjects, and associated with performance on neuropsychological tests in six cognitive domains with regression models. Analyses were controlled for age, gender, whole-brain gray matter volumes, and education level.
Compared to MS subjects with normal cognition, MS subjects with cognitive impairment showed a more random network organization as indicated by lower lambda values (all p < 0.05). Worse average cognition and executive function were associated with lower lambda values. Impaired information processing speed, working memory, and attention were associated with lower clustering values.
Our findings indicate that MS subjects with a more randomly organized gray matter network show worse cognitive functioning, suggesting that single-subject gray matter graphs may capture neurological dysfunction due to MS. Coordinated patterns of gray matter morphology can be represented as networks, and network disruptions may explain cognitive dysfunction related to multiple sclerosis (MS).BACKGROUNDCoordinated patterns of gray matter morphology can be represented as networks, and network disruptions may explain cognitive dysfunction related to multiple sclerosis (MS).To investigate whether single-subject gray matter network properties are related to impaired cognition in MS.OBJECTIVETo investigate whether single-subject gray matter network properties are related to impaired cognition in MS.We studied 148 MS patients (99 female) and 33 healthy controls (HC, 21 female). Seven network parameters were computed and compared within MS between cognitively normal and impaired subjects, and associated with performance on neuropsychological tests in six cognitive domains with regression models. Analyses were controlled for age, gender, whole-brain gray matter volumes, and education level.METHODSWe studied 148 MS patients (99 female) and 33 healthy controls (HC, 21 female). Seven network parameters were computed and compared within MS between cognitively normal and impaired subjects, and associated with performance on neuropsychological tests in six cognitive domains with regression models. Analyses were controlled for age, gender, whole-brain gray matter volumes, and education level.Compared to MS subjects with normal cognition, MS subjects with cognitive impairment showed a more random network organization as indicated by lower lambda values (all p < 0.05). Worse average cognition and executive function were associated with lower lambda values. Impaired information processing speed, working memory, and attention were associated with lower clustering values.RESULTSCompared to MS subjects with normal cognition, MS subjects with cognitive impairment showed a more random network organization as indicated by lower lambda values (all p < 0.05). Worse average cognition and executive function were associated with lower lambda values. Impaired information processing speed, working memory, and attention were associated with lower clustering values.Our findings indicate that MS subjects with a more randomly organized gray matter network show worse cognitive functioning, suggesting that single-subject gray matter graphs may capture neurological dysfunction due to MS.CONCLUSIONOur findings indicate that MS subjects with a more randomly organized gray matter network show worse cognitive functioning, suggesting that single-subject gray matter graphs may capture neurological dysfunction due to MS. |
| Author | Tijms, Betty M Wattjes, Mike P Killestein, Joep Rimkus, Carolina M Schoonheim, Menno M Eijlers, Anand Jc Vrenken, Hugo Leite, Claudia C Barkhof, Frederik Steenwijk, Martijn D |
| Author_xml | – sequence: 1 givenname: Carolina M surname: Rimkus fullname: Rimkus, Carolina M organization: Department of Radiology and Nuclear Medicine, VUmc MS Center Amsterdam, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands/Department of Radiology, Faculty of Medicine, University of São Paulo, São Paulo, Brazil – sequence: 2 givenname: Menno M surname: Schoonheim fullname: Schoonheim, Menno M organization: Department of Anatomy and Neurosciences, VUmc MS Center Amsterdam, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands – sequence: 3 givenname: Martijn D surname: Steenwijk fullname: Steenwijk, Martijn D organization: Department of Anatomy and Neurosciences, VUmc MS Center Amsterdam, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands/Department of Neurology, VUmc MS Center Amsterdam, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands – sequence: 4 givenname: Hugo surname: Vrenken fullname: Vrenken, Hugo organization: Department of Radiology and Nuclear Medicine, VUmc MS Center Amsterdam, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands – sequence: 5 givenname: Anand Jc surname: Eijlers fullname: Eijlers, Anand Jc organization: Department of Anatomy and Neurosciences, VUmc MS Center Amsterdam, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands – sequence: 6 givenname: Joep surname: Killestein fullname: Killestein, Joep organization: Department of Neurology, VUmc MS Center Amsterdam, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands – sequence: 7 givenname: Mike P surname: Wattjes fullname: Wattjes, Mike P organization: Department of Radiology and Nuclear Medicine, VUmc MS Center Amsterdam, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands – sequence: 8 givenname: Claudia C surname: Leite fullname: Leite, Claudia C organization: Department of Radiology, Faculty of Medicine, University of São Paulo, São Paulo, Brazil – sequence: 9 givenname: Frederik surname: Barkhof fullname: Barkhof, Frederik organization: Department of Radiology and Nuclear Medicine, VUmc MS Center Amsterdam, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands/Institutes of Neurology and Healthcare Engineering, University College London, London, UK – sequence: 10 givenname: Betty M orcidid: 0000-0002-2612-1797 surname: Tijms fullname: Tijms, Betty M organization: Alzheimer Center and Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands |
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| SubjectTerms | Adult Cognitive Dysfunction - etiology Cognitive Dysfunction - physiopathology Executive Function - physiology Female Gray Matter - diagnostic imaging Gray Matter - pathology Humans Magnetic Resonance Imaging Male Middle Aged Multiple Sclerosis - complications Multiple Sclerosis - diagnostic imaging Multiple Sclerosis - pathology Multiple Sclerosis - physiopathology Nerve Net - diagnostic imaging Nerve Net - pathology |
| Title | Gray matter networks and cognitive impairment in multiple sclerosis |
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