
Contributions
Abstract: P1117
Type: Poster
Abstract Category: Pathology and pathogenesis of MS - Neuropsychology
Cognitive impairment affects more than half of all individuals with multiple sclerosis (MS), although its cause remains unclear. Cognitive processing speed is the earliest and most common area to be affected. Recent technological advances have allowed for the development of computer-based assessments of cognitive processing speed that are sensitive, reliable, and resistant to practice effects. We sought to identify the physiological mechanism underlying cognitive processing speed impairment in MS using these advanced measurement approaches, in combination with neuroimaging measures. Relapsing-Remitting MS (RRMS) (n=20, 19.3±2.7 years of age, 55% female) and healthy control (n=26, 20.0±3.9 years of age, 69% female) participants completed the Cogstate Brief Battery information processing tasks and an MRI scan. MRI sequences included a T1-weighted anatomical scan and 64-direction diffusion tensor imaging (DTI). Regions of interest delineation and cortical thickness estimations were automatically performed using Freesurfer analysis software. Regional labels were also used to calculate region-wise mean DTI fractional anisotropy (FA), a measure of white matter integrity The Cogstate information processing measures successfully differentiated between RRMS and HC cohorts, with a z score of -0.93±1.01 for MS and -0.35±0.61 for HC, p=0.03. Further, information processing speed was differentially associated with frontal lobe FA (r=-0.550, P=0.02) in the RRMS sample and insular cortical thickness (r=-0.481, p=0.02) in the HC sample. Studies looking at both region-wise and tractography-based FA have reported frontal lobe FA reductions to be associated with cognitive impairment in RRMS. We have shown that computer-based information assessments of cognitive processing speed are not only sensitive in RRMS samples, but are also able to predict variability in frontal lobe FA in the RRMS brain.
Disclosure: Michael Shaw: Nothing to dislcose
Elizabeth Bartlett: Nothing to disclose
Colleen Schwarz: Nothing to disclose
Margaret Kasschau: Nothing to disclose
Laraib Ijaz: Nothing to disclose
Lauren Krupp: received consulting fees from Novartis, Biogen, Redhill science, served on the DSMB for Pfizer, Sanofi, on the steering committee of Novartis, received royalties from Janseen, Eisai, Abbvie, Amicus, and received research support from the Department of Defense, Biogen, Novartis, National Multiple Sclerosis Society, and the Lourie Foundation.
Christine DeLorenzo: Nothing to disclose
Leight Charvet: Consultant for Biogen
Abstract: P1117
Type: Poster
Abstract Category: Pathology and pathogenesis of MS - Neuropsychology
Cognitive impairment affects more than half of all individuals with multiple sclerosis (MS), although its cause remains unclear. Cognitive processing speed is the earliest and most common area to be affected. Recent technological advances have allowed for the development of computer-based assessments of cognitive processing speed that are sensitive, reliable, and resistant to practice effects. We sought to identify the physiological mechanism underlying cognitive processing speed impairment in MS using these advanced measurement approaches, in combination with neuroimaging measures. Relapsing-Remitting MS (RRMS) (n=20, 19.3±2.7 years of age, 55% female) and healthy control (n=26, 20.0±3.9 years of age, 69% female) participants completed the Cogstate Brief Battery information processing tasks and an MRI scan. MRI sequences included a T1-weighted anatomical scan and 64-direction diffusion tensor imaging (DTI). Regions of interest delineation and cortical thickness estimations were automatically performed using Freesurfer analysis software. Regional labels were also used to calculate region-wise mean DTI fractional anisotropy (FA), a measure of white matter integrity The Cogstate information processing measures successfully differentiated between RRMS and HC cohorts, with a z score of -0.93±1.01 for MS and -0.35±0.61 for HC, p=0.03. Further, information processing speed was differentially associated with frontal lobe FA (r=-0.550, P=0.02) in the RRMS sample and insular cortical thickness (r=-0.481, p=0.02) in the HC sample. Studies looking at both region-wise and tractography-based FA have reported frontal lobe FA reductions to be associated with cognitive impairment in RRMS. We have shown that computer-based information assessments of cognitive processing speed are not only sensitive in RRMS samples, but are also able to predict variability in frontal lobe FA in the RRMS brain.
Disclosure: Michael Shaw: Nothing to dislcose
Elizabeth Bartlett: Nothing to disclose
Colleen Schwarz: Nothing to disclose
Margaret Kasschau: Nothing to disclose
Laraib Ijaz: Nothing to disclose
Lauren Krupp: received consulting fees from Novartis, Biogen, Redhill science, served on the DSMB for Pfizer, Sanofi, on the steering committee of Novartis, received royalties from Janseen, Eisai, Abbvie, Amicus, and received research support from the Department of Defense, Biogen, Novartis, National Multiple Sclerosis Society, and the Lourie Foundation.
Christine DeLorenzo: Nothing to disclose
Leight Charvet: Consultant for Biogen