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Original Investigation |

Magnetic Resonance Spectroscopy Markers of Disease Progression in Multiple Sclerosis

Sara Llufriu, MD, PhD1,4; John Kornak, PhD3; Helene Ratiney, PhD1; Joonmi Oh, PhD2; Don Brenneman, BA1; Bruce A. Cree, MD1; Mehul Sampat, PhD1; Stephen L. Hauser, MD1; Sarah J. Nelson, PhD2; Daniel Pelletier, MD1,2,5,6
[+] Author Affiliations
1Department of Neurology, University of California–San Francisco
2Department of Radiology, University of California–San Francisco
3Department of Epidemiology and Biostatistics, University of California–San Francisco
4Center for Neuroimmunology, Service of Neurology, Hospital Clinic and Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
5Department of Neurology, Yale University, New Haven, Connecticut
6Department of Diagnostic Radiology, Yale University, New Haven, Connecticut
JAMA Neurol. 2014;71(7):840-847. doi:10.1001/jamaneurol.2014.895.
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Importance  Predicting disease evolution is becoming essential for optimizing treatment decision making in multiple sclerosis (MS). Multiple sclerosis pathologic damage typically includes demyelination, neuro-axonal loss, and astrogliosis.

Objective  To evaluate the potential of magnetic resonance markers of central nervous system injury to predict brain-volume loss and clinical disability in multiple sclerosis.

Design, Setting, and Participants  Participants were selected from the Multiple Sclerosis Center at the University of California–San Francisco. The preliminary data set included 59 patients with MS and 43 healthy control individuals. The confirmatory data set included 220 patients from an independent, large genotype-phenotype research project.

Main Outcomes and Measures  Baseline N-acetylaspartate (NAA) level, myo-inositol (mI) in normal-appearing white and gray matter, myelin water fraction in normal-appearing white matter, markers of axonal damage, astrogliosis, and demyelination were evaluated as predictors in a preliminary data set. Potential predictors were subsequently tested for replication in a confirmatory data set. Clinical scores and percentage of brain-volume change were obtained annually over 4 years as outcomes. Predictors of outcomes were assessed using linear models, linear mixed-effects models, and logistic regression.

Results  N-acetylaspartate and mI both had statistically significant effects on brain volume, prompting the use of the mI:NAA ratio in normal-appearing white matter as a predictor. The ratio was a predictor of brain-volume change in both cohorts (annual slope in the percentage of brain-volume change/unit of increase in the ratio: −1.68; 95% CI, −3.05 to −0.30; P = .02 in the preliminary study cohort and −1.08; 95% CI, −1.95 to −0.20; P = .02 in the confirmatory study cohort). Furthermore, the mI:NAA ratio predicted clinical disability (Multiple Sclerosis Functional Composite evolution: −0.52 points annually, P < .001; Multiple Sclerosis Functional Composite sustained progression: odds ratio, 2.76/SD increase in the ratio; 95% CI, 1.32 to 6.47; P = .01) in the preliminary data set and predicted Multiple Sclerosis Functional Composite evolution (−0.23 points annually; P = .01), Expanded Disability Status Scale evolution (0.57 points annually; P = .04), and Expanded Disability Status Scale sustained progression (odds ratio, 1.46; 95% CI, 1.10 to 1.94; P = .009) in the confirmatory data set. Myelin water fraction did not show predictive value.

Conclusions and Relevance  The mI:NAA ratio in normal-appearing white matter has consistent predictive power on brain atrophy and neurological disability evolution. The combined presence of astrogliosis and axonal damage in white matter has cardinal importance in disease severity.

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