Predicting Disability Progression And Cognitive Worsening In Multiple Sclerosis With Gray Matter Network Measures

Objective In multiple sclerosis (MS), magnetic resonance imaging (MRI) measures at the whole brain or regional level are only modestly associated with disability, while network-based measures are emerging as promising prognostic markers. We sought to demonstrate whether data-driven network-based measures of regional grey matter (GM) volumes predict future disability in secondary progressive MS (SPMS). We used cross-sectional structural MRI, and baseline and longitudinal data of Expanded Disability Status Scale [EDSS], 9-Hole Peg Test [9HPT], and Symbol Digit Modalities Test [SDMT], from a clinical trial in 988 people with progressive MS. We processed T1-weighted scans to obtain GM probability maps and applied spatial independent component analysis (ICA) to identify co-varying patterns of GM volume change. We used survival models to determine whether baseline GM network measures predict cognitive and motor worsening. Results We identified 15 networks of regionally co-varying GM features. Compared with whole brain GM, deep GM, and lesion volumes, ICA-components correlated more closely with clinical outcomes. A mainly basal ganglia component had the highest correlations at baseline with the SDMT and was associated with cognitive worsening (HR= 1.29, 95% CI [1.09-1.52], p< 0.005). Two ICA-components were associated with 9HPT worsening (HR=1.30, 95% CI [1.06:1.60], p<0.01; and HR= 1.21, 95%CI [1.01:1.45], p<0.05). Post-hoc analyses revealed that for 9HPT and SDMT survival models including network-based measures reported a higher discrimination power (respectively, C-index= 0.69, se= 0.03; C-index= 0.71, se= 0.02) compared to models including only whole and regional MRI measures (respectively, C-index= 0.65, se= 0.03; C-index= 0.69, se= 0.02). Conclusions The disability progression was better predicted by networks of covarying GM regions, rather than by single regional or whole-brain measures. Network analysis can be applied in future clinical trials and may play a role in stratifying participants who have the most potential to show a treatment effect. ### Competing Interest Statement The authors have declared no competing interest. ### Clinical Trial NCT01416181 ### Funding Statement This study was supported by the International Progressive MS Alliance (IPMSA, award reference number PA-1603-08175). We are grateful to all the IPMSA investigators who have contributed trial data to this study as part of EPITOME: Enhancing Power of Intervention Trials Through Optimized MRI Endpoints network. DC, FB and OC are supported by the NIHR biomedical research centre at UCLH ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The Institutional Review Board at the Montreal Neurological Institute (MNI), Quebec, Canada approved this study under the auspices of International Progressive MS Alliance (Reference number: IRB00010120). All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes Processed data and codes used in this study are available upon request from qualified investigators. * ### Abbreviations 9HPT : 9-Hole Peg Test C-index : Concordance Index CDP : Confirmed Disability Progression CNS : Central Nervous System CSF : Cerebro-Spinal Fluid DGM : Deep Grey Matter EDSS : Expanded Disability Status Scale FWHM : ull Width At Half Maximum GM : Grey matter HR : Hazard Ratio ICA : Independent Component Analysis MRI : Magnetic Resonance Imaging MS : Multiple Sclerosis SDMT : Symbol Digit Modalities Test SPMS : Secondary Progressive Multiple Sclerosis WM : White Matter