Amyotrophic lateral sclerosis (ALS) is a devastating disease of motor neurons with unknown etiology. Evidence suggests that the brain undergoes degenerative changes in ALS, particularly within areas of the descending motor pathway. Identifying robust and non-invasive biomarkers that are sensitive to neurodegeneration in ALS is essential for improving clinical trial design and assessment of treatment effectiveness. This study evaluated 1H-MRS-measured metabolite levels as biomarkers of disease severity. Ultra-high field (7 tesla) 1H-MRS revealed metabolic abnormalities in the motor cortex and brainstem of humans with ALS that are dependent on disease stage.
Nineteen subjects with ALS and 17 age- and gender-matched healthy controls participated in the study. Subjects with ALS were determined to have either possible, probable, or definite ALS based on revised El Escorial diagnostic criteria.6 Scores on the validated ALS Functional Rating Scale-Revised (ALSFRS-R),7 site of onset, most affected side of the body, and disease duration were recorded.
Single-voxel 1H-MRS was performed using a 16-channel transceiver coil8 on a 7 T scanner (Siemens Erlangen). Spectra from the motor cortex (2.2 x 2.2 x 2.2 cm3, placed contralaterally to the most affected side) and pontine brainstem (1.6 x 1.6 x 1.6 cm3) were acquired using semi-LASER9 (TR = 5 s, TE = 26 ms, 64 averages) (Fig. 1). GSH in the motor cortex was quantified by spectral editing at 3 T in the same subjects using MEGA-PRESS10 (TR = 2 s, TE = 68 ms, 512 averages; VOI: 3.5 x 2.5 x 2.3 cm3) (Fig. 2).
Metabolite concentrations were determined by LCModel11 with water-scaling, as described previously.12,13 Only metabolites quantified with mean Cramer-Rao Lower Bounds less than 20% were reported (Fig. 3). Pairs of metabolites with strong cross-correlations (r<-0.7) were reported as sums. Neurochemical levels were compared using ANCOVA adjusted for hemisphere scanned. Pearson’s correlation coefficients were calculated to estimate correlations between neurochemical levels and clinical status measures.
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