NAA is a Marker of Disability in Secondary-Progressive MS: A Proton MR Spectroscopic Imaging Study

Abstract

BACKGROUND AND PURPOSE: The secondary progressive phase of multiple sclerosis is characterised by disability progression due to processes that lead to neurodegeneration. Surrogate markers such as those derived from MRI are beneficial in understanding the pathophysiology that drives disease progression and its relationship to clinical disability. We undertook a 1H-MRS imaging study in a large secondary progressive MS (SPMS) cohort, to examine whether metabolic markers of brain injury are associated with measures of disability, both physical and cognitive. MATERIALS AND METHODS: A cross-sectional analysis of individuals with secondary-progressive MS was performed in 119 participants. They underwent 1 H-MR spectroscopy to obtain estimated concentrations and ratios to total Cr for total NAA, mIns, Glx, and total Cho in normal-appearing WM and GM. Clinical outcome measures chosen were the following: Paced Auditory Serial Addition Test, Symbol Digit Modalities Test, Nine-Hole Peg Test, Timed 25-foot Walk Test, and the Expanded Disability Status Scale. The relationship between these neurometabolites and clinical disability measures was initially examined using Spearman rank correlations. Significant associations were then further analyzed in multiple regression models adjusting for age, sex, disease duration, T2 lesion load, normalized brain volume, and occurrence of relapses in 2 years preceding study entry. RESULTS: Significant associations, which were then confirmed by multiple linear regression, were found in normal-appearing WM for total NAA (tNAA)/total Cr (tCr) and the Nine-Hole Peg Test (r = 0.23; 95% CI, 0.06-0.40); tNAA and tNAA/tCr and the Paced Auditory Serial Addition Test (r = 0.21; 95% CI, 0.03-0.38) (r = 0.19; 95% CI, 0.01-0.36); mIns/tCr and the Paced Auditory Serial Addition Test, (r = À0.23; 95% CI, À0.39 to À0.05); and in GM for tCho and the Paced Auditory Serial Addition Test (r = À0.24; 95% CI, À0.40 to À0.06). No other GM or normal-appearing WM relationships were found with any metabolite, with associations found during initial correlation testing losing significance after multiple linear regression analysis. CONCLUSIONS: This study suggests that metabolic markers of neuroaxonal integrity and astrogliosis in normal-appearing WM and membrane turnover in GM may act as markers of disability in secondary-progressive MS.

A systematic review of resting state functional MRI connectivity changes and cognitive impairment in multiple sclerosis

“…Future multimodal studies using DWI and rs-fMRI can test the predictions of the ‘network collapse’ model further and to develop this or new models as needed to better characterise progression and the influence of pathology in MS brains, in order to develop clinically useful disease markers. In addition, there is evidence of physiological abnormalities in MS that are associated with cognitive dysfunction, such as cerebral hypoperfusion and sodium accumulation in the grey and white matter (86–88), and additional proton spectroscopic changes (89). Considering how these are related to network changes can help us understand the mechanisms of network abnormalities and aid in the search for a biomarker of cognitive impairment.…”

ORYX‐MRSI: A fully‐automated open‐source software for proton magnetic resonance spectroscopic imaging data analysis

“…1,[4][5][6]37 There have been several multivoxel 1 H-MRSI studies that have employed data analysis pipelines including automatic and manual data quality control, chemical shift correction, tissue fraction calculation, metabolite map generation and registration onto common brain atlases, and ROI analysis. 18,[38][39][40][41][42][43][44] However, a standardized data analysis software has not yet been developed that can execute all these steps for the analysis of 3D 1 H-MRSI data. This study presents Oryx-MRSI, which is an open-source MATLAB-based end-toend pipeline for complementary MRSI data analysis after data quantification.…”

“…1 H‐MRSI is a clinically useful technique that provides metabolic information useful for the diagnosis, treatment decision making, and follow‐up for several diseases including brain disorders 1,4–6,37 . There have been several multivoxel 1 H‐MRSI studies that have employed data analysis pipelines including automatic and manual data quality control, chemical shift correction, tissue fraction calculation, metabolite map generation and registration onto common brain atlases, and ROI analysis 18,38–44 . However, a standardized data analysis software has not yet been developed that can execute all these steps for the analysis of 3D 1 H‐MRSI data.…”

ORYX-MRSI: A Fully-Automated Open-Source Software for Three-Dimensional Proton Magnetic Resonance Spectroscopic Imaging Data Analysis

“…1 H-MRSI is a clinically useful technique that provides metabolic information useful for the diagnosis, treatment decision making, and follow-up for several diseases including brain disorders (Chang et al, 2013;Kantarci et al, 2000;Nelson, 2003Nelson, , 2011. There have been several multivoxel 1 H-MRSI studies that have employed data analysis pipelines including chemical shift correction, tissue fraction calculation, metabolite map generation and registration onto common brain atlases, and ROI analysis (Andronesi et al, 2020;Hangel et al, 2018;Hingerl et al, 2020;Malaspina et al, 2021;Maudsley et al, 2010;Parikh et al, 2015;Solanky et al, 2020). However, a standardized data analysis software has not yet been developed that can execute all these steps for the analysis of 3D 1 H-MRSI data.…”