Dynamics and Predictors of Cognitive Impairment along the Disease Course in Multiple Sclerosis

(1) Background: The evolution and predictors of cognitive impairment (CI) in multiple sclerosis (MS) are poorly understood. We aimed to define the temporal dynamics of cognition throughout the disease course and identify clinical and neuroimaging measures that predict CI. (2) Methods: This paper fea...

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Published inJournal of personalized medicine Vol. 11; no. 11; p. 1107
Main Authors Lopez-Soley, Elisabet, Martinez-Heras, Eloy, Andorra, Magi, Solanes, Aleix, Radua, Joaquim, Montejo, Carmen, Alba-Arbalat, Salut, Sola-Valls, Nuria, Pulido-Valdeolivas, Irene, Sepulveda, Maria, Romero-Pinel, Lucia, Munteis, Elvira, Martínez-Rodríguez, Jose E., Blanco, Yolanda, Martinez-Lapiscina, Elena H., Villoslada, Pablo, Saiz, Albert, Solana, Elisabeth, Llufriu, Sara
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 28.10.2021
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Abstract (1) Background: The evolution and predictors of cognitive impairment (CI) in multiple sclerosis (MS) are poorly understood. We aimed to define the temporal dynamics of cognition throughout the disease course and identify clinical and neuroimaging measures that predict CI. (2) Methods: This paper features a longitudinal study with 212 patients who underwent several cognitive examinations at different time points. Dynamics of cognition were assessed using mixed-effects linear spline models. Machine learning techniques were used to identify which baseline demographic, clinical, and neuroimaging measures best predicted CI. (3) Results: In the first 5 years of MS, we detected an increase in the z-scores of global cognition, verbal memory, and information processing speed, which was followed by a decline in global cognition and memory (p < 0.05) between years 5 and 15. From 15 to 30 years of disease onset, cognitive decline continued, affecting global cognition and verbal memory. The baseline measures that best predicted CI were education, disease severity, lesion burden, and hippocampus and anterior cingulate cortex volume. (4) Conclusions: In MS, cognition deteriorates 5 years after disease onset, declining steadily over the next 25 years and more markedly affecting verbal memory. Education, disease severity, lesion burden, and volume of limbic structures predict future CI and may be helpful when identifying at-risk patients.
AbstractList (1) Background: The evolution and predictors of cognitive impairment (CI) in multiple sclerosis (MS) are poorly understood. We aimed to define the temporal dynamics of cognition throughout the disease course and identify clinical and neuroimaging measures that predict CI. (2) Methods: This paper features a longitudinal study with 212 patients who underwent several cognitive examinations at different time points. Dynamics of cognition were assessed using mixed-effects linear spline models. Machine learning techniques were used to identify which baseline demographic, clinical, and neuroimaging measures best predicted CI. (3) Results: In the first 5 years of MS, we detected an increase in the z-scores of global cognition, verbal memory, and information processing speed, which was followed by a decline in global cognition and memory (p < 0.05) between years 5 and 15. From 15 to 30 years of disease onset, cognitive decline continued, affecting global cognition and verbal memory. The baseline measures that best predicted CI were education, disease severity, lesion burden, and hippocampus and anterior cingulate cortex volume. (4) Conclusions: In MS, cognition deteriorates 5 years after disease onset, declining steadily over the next 25 years and more markedly affecting verbal memory. Education, disease severity, lesion burden, and volume of limbic structures predict future CI and may be helpful when identifying at-risk patients.
(1) Background: The evolution and predictors of cognitive impairment (CI) in multiple sclerosis (MS) are poorly understood. We aimed to define the temporal dynamics of cognition throughout the disease course and identify clinical and neuroimaging measures that predict CI. (2) Methods: This paper features a longitudinal study with 212 patients who underwent several cognitive examinations at different time points. Dynamics of cognition were assessed using mixed-effects linear spline models. Machine learning techniques were used to identify which baseline demographic, clinical, and neuroimaging measures best predicted CI. (3) Results: In the first 5 years of MS, we detected an increase in the z-scores of global cognition, verbal memory, and information processing speed, which was followed by a decline in global cognition and memory ( p < 0.05) between years 5 and 15. From 15 to 30 years of disease onset, cognitive decline continued, affecting global cognition and verbal memory. The baseline measures that best predicted CI were education, disease severity, lesion burden, and hippocampus and anterior cingulate cortex volume. (4) Conclusions: In MS, cognition deteriorates 5 years after disease onset, declining steadily over the next 25 years and more markedly affecting verbal memory. Education, disease severity, lesion burden, and volume of limbic structures predict future CI and may be helpful when identifying at-risk patients.
Author Sepulveda, Maria
Alba-Arbalat, Salut
Saiz, Albert
Solana, Elisabeth
Blanco, Yolanda
Romero-Pinel, Lucia
Solanes, Aleix
Andorra, Magi
Martínez-Rodríguez, Jose E.
Llufriu, Sara
Villoslada, Pablo
Radua, Joaquim
Pulido-Valdeolivas, Irene
Montejo, Carmen
Martinez-Lapiscina, Elena H.
Lopez-Soley, Elisabet
Sola-Valls, Nuria
Munteis, Elvira
Martinez-Heras, Eloy
AuthorAffiliation 4 Early Psychosis: Interventions and Clinical-Detection (EPIC) Laboratory, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London WC2R 2LS, UK
5 Multiple Sclerosis Unit, Neurology Department, Hospital Universitari de Bellvitge, IDIBELL, 08907 Barcelona, Spain; lromeropinel@gmail.com
3 Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Solna, 171 77 Stockholm, Sweden
2 Imaging of Mood- and Anxiety-Related Disorders (IMARD) Group, IDIBAPS and CIBERSAM, 08036 Barcelona, Spain; solanes@clinic.cat (A.S.); radua@clinic.cat (J.R.)
1 Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d’Investigacions Biomediques August Pi i Sunyer (IDIBAPS) and Universitat de Barcelona, 08036 Barcelona, Spain; elopez2@clinic.cat (E.L.-S.); emartind@clinic.cat (E.M.-H.); magiandorra@gmail.com (M.A.); c.montejo.gonzalez@gmail.com (C.M.); sal
AuthorAffiliation_xml – name: 6 Neurology Department: Hospital del Mar Medical Research Institute (IMIM), 08003 Barcelona, Spain; emunteis@parcdesalutmar.cat (E.M.); jemartinezrguez@gmail.com (J.E.M.-R.)
– name: 5 Multiple Sclerosis Unit, Neurology Department, Hospital Universitari de Bellvitge, IDIBELL, 08907 Barcelona, Spain; lromeropinel@gmail.com
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– name: 1 Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d’Investigacions Biomediques August Pi i Sunyer (IDIBAPS) and Universitat de Barcelona, 08036 Barcelona, Spain; elopez2@clinic.cat (E.L.-S.); emartind@clinic.cat (E.M.-H.); magiandorra@gmail.com (M.A.); c.montejo.gonzalez@gmail.com (C.M.); salba@clinic.cat (S.A.-A.); nuria.sola@grupsagessa.com (N.S.-V.); irenepulidovaldeolivas@gmail.com (I.P.-V.); msepulve@clinic.cat (M.S.); yblanco@clinic.cat (Y.B.); elenahmlapiscina@gmail.com (E.H.M.-L.); pvillos@stanford.edu (P.V.); asaiz@clinic.cat (A.S.)
– name: 2 Imaging of Mood- and Anxiety-Related Disorders (IMARD) Group, IDIBAPS and CIBERSAM, 08036 Barcelona, Spain; solanes@clinic.cat (A.S.); radua@clinic.cat (J.R.)
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Snippet (1) Background: The evolution and predictors of cognitive impairment (CI) in multiple sclerosis (MS) are poorly understood. We aimed to define the temporal...
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SubjectTerms Age
Cognition & reasoning
Cognitive ability
Cortex (cingulate)
Cortex (temporal)
Datasets
Information processing
Learning algorithms
Machine learning
Magnetic resonance imaging
Medicin och hälsovetenskap
Memory
Multiple sclerosis
Neuroimaging
Patients
Precision medicine
Semantics
Software
Variables
Volumetric analysis
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Title Dynamics and Predictors of Cognitive Impairment along the Disease Course in Multiple Sclerosis
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Volume 11
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