Baseline biomarkers of connectome disruption and atrophy predict future processing speed in early multiple sclerosis

NeuroImage. Clinical
Amy KuceyeskiS A Gauthier

Abstract

The development of accurate prognoses in multiple sclerosis is difficult, as the disease is characterized by heterogeneous patterns of brain abnormalities that relate in an unclear way to future impairments. Here, we use a statistical modeling approach to determine if the baseline pattern of connectome disruption due to T2-FLAIR lesions could predict a patient's future processing speed, as measured using the Symbol Digits Modality Test scores. Imaging data, demographics and Symbol Digits Modality Test scores were collected from 61 early relapsing remitting multiple sclerosis patients. The Network Modification Tool was used to estimate damage to the connectome by quantifying white matter abnormalities' effects on 1) global network properties, 2) regional connectivity and 3) connectivity between pairs of regions. MS subjects showed significant improvement of processing speed between baseline and follow-up (t = -2.6, p = 0.0096); however, both baseline (t = -4.01, p = 0.00012) and follow-up (t = -2.10, p = 0.038) processing speed were significantly lower than age-matched healthy controls. Partial Least Squares Regression was used to create models that predict future processing speed from between baseline imaging metrics and demogr...Continue Reading

Software Mentioned

Network Modification ( NeMo ) Tool
FreeSurfer
SPM8
NeMo Tool
NeMo
Brainography
PLSR

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