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Biochemical Correlations with Fatigue in Multiple Sclerosis Detected by MR 2D Localized Correlated Spectroscopy
Author(s) -
ARM Jameen,
Aliedani Oun,
Ribbons Karen,
Lea Rod,
LechnerScott Jeannette,
Ramadan Saadallah
Publication year - 2021
Publication title -
journal of neuroimaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.822
H-Index - 64
eISSN - 1552-6569
pISSN - 1051-2284
DOI - 10.1111/jon.12836
Subject(s) - medicine , in vivo magnetic resonance spectroscopy , glutamine , creatine , multiple sclerosis , glutathione , endocrinology , lesion , pathophysiology , gastroenterology , pathology , magnetic resonance imaging , biochemistry , amino acid , chemistry , enzyme , immunology , radiology
BACKGROUND AND PURPOSE Fatigue is the common symptom in patients with multiple sclerosis (MS), yet its pathophysiological mechanism is poorly understood. We investigated the metabolic changes in fatigue in a group of relapsing‐remitting MS (RRMS) patients using MR two‐dimensional localized correlated spectroscopy (2D L‐COSY). METHODS Sixteen RRMS and 16 healthy controls were included in the study. Fatigue impact was assessed with the Modified Fatigue Impact Scale (MFIS). MR 2D L‐COSY data were collected from the posterior cingulate cortex. Nonparametric statistical analysis was used to calculate the changes in creatine scaled metabolic ratios and their correlations with fatigue scores. RESULTS Compared to healthy controls, the RRMS group showed significantly higher fatigue and lower metabolic ratios for tyrosine, glutathione, homocarnosine (GSH+Hca), fucose‐3, glutamine+glutamate (Glx), glycerophosphocholine (GPC), total choline, and N‐acetylaspartate (NAA‐2), while increased levels for isoleucine and glucose ( P ≤ .05). Only GPC showed positive correlation with all fatigue domains ( r = .537, P ≤ .05). On the other hand, Glx‐upper, NAA‐2, GSH+Hca, and fucose‐3 showed negative correlations with all fatigue domains ( r = –.345 to –.580, P ≤ .05). While tyrosine showed positive correlation with MFIS ( r = .499, P ≤ .05), cognitive fatigue was negatively correlated with total GSH ( r = –.530, P ≤ .05). No correlations were found between lesion load or brain volumes with fatigue score. CONCLUSIONS Our results suggest that fatigue in MS is strongly correlated with an imbalance in neurometabolites but not structural brain measurements.

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