Multimodal predictors of disability progression and processing speed decline in relapsing-remitting multiple sclerosis

Abstract The underlying mechanisms for neurodegeneration in multiple sclerosis are complex and incompletely understood. Multivariate and multimodal investigations integrating demographic, clinical, multi-omics, and neuroimaging data provide opportunities for nuanced analyses, aimed to define disease progression markers. We used data from a 12-year longitudinal multicenter cohort of 88 people with multiple sclerosis, to test the predictive value of multi-omics, T1-weighted MRI (lesion count and volume, lesion-filled brain-predicted age), clinical examinations, self-reports on quality of life, demographics, and general health-related variables for future functional and cognitive disability. Systematic increases in Expanded Disability Status Scale (EDSS) scores were used to stratify a progressive disability group (PDG) from relatively stabile disability. A processing speed decline group (PSDG) was defined by a ≥20% decrease from the maximum (cognitive) Paced Auditory Serial Addition Test score. We used a multiverse approach to identify which baseline variables were most predictive for PDG and PSDG memberships, considering multiple analysis paths. Future disability (median area under the curve: mAUC=0.83±0.04, median Brier score: mBS=0.16±0.02) and the loss of processing speed (mAUC=0.89±0.05, mBS=0.10±0.03) could be successfully classified across models. Varibles significantly (median p-values<0.05) predicting stable disability included receiving disease modifying treatment at 12-year follow-up (median Odds Ratio: mORPDG=7.44±4.07, pmedian=0.013, proportion of the OR’s directionality: PORSD=100%), lower baseline EDSS for each 1-unit (mORPDG=0.25±0.11, pmedian=0.013, PORSD=100%), and counter-intuitively every year increase in baseline age (mORPDG=1.12±0.04, pmedian=0.020, PORSD=100%), and lower vitamin A per 1 umol/L (mORPDG=0.10±0.05, pmedian=0.016, PORSD=99.7%) and D levels per 1 nmol/L (mORPDG=0.95±0.02, pmedian=0.025, PORSD=100%). Variables significantly predicting stable processing speed were receiving disease modifying treatment at 12-year follow-up (mORPSDG=0.10±0.08, pmedian=0.013, PORSD=100%) and baseline PASAT score (mORPSDG=0.86±0.03, pmedian=0.005, PORSD=99.73%). These findings were supported by an additional simulation study. Concordant with the literature, disease modifying treatments influence disability progression, as well as a higher EDSS and PASAT scores at measurement start. Experimental and counterintuitive findings on vitamin A and D levels require further validation. The large variability across models suggests a strong influence of analytic flexibility, such as the selection of covariates. Competing Interest Statement OAA has received a speaker's honorarium from Lundbeck, Janssen, Otsuka and Lilly, and is a consultant to Coretechs.ai and Precision Health. LTW is a minor shareholder of baba.vision. KMM has served on scientific advisory board for Alexion, received speaker honoraria from Biogen, Novartis, Roche and Sanofi, and has participated in clinical trials organized by Biogen, Merck, Novartis, Otivio, Roche and Sanofi. EAH received honoraria for advisory board activity from Sanofi-Genzyme, and his department has received honoraria for lecturing from Biogen and Merck. OT received speaker honoraria from and served on scientific advisory boards of Biogen, Sanofi-Aventis, Merck, and Novartis, and has participated in clinical trials organized by Merck, Novartis, Roche and Sanofi. The remaining authors declare no other competing interests. Funding Statement This project was funded by the Norwegian MS-union (no reference). Model training was performed on the Service for Sensitive Data (TSD) platform, owned by the University of Oslo, operated and developed by the TSD service group at the University of Oslo IT-Department (USIT). Computations were performed using resources provided by UNINETT Sigma2 (#NS9666S) - the National Infrastructure for High Performance Computing and Data Storage in Norway, supported by the Norwegian Research Council (#223273). 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 study was approved by the Norwegian Regional Committees for Medical and Health Research Ethics (REK, 814351). The OFAMS-study and the 10-year follow-up were previously approved by REK (2016/1906) and registered as clinical trial (clinicaltrials.gov identifier: NCT00360906). Ethical approval for the different brain age training datasets was obtained (REK 567301, PVO 17/21624), as well as for the longitudinal validation set (Bergen Breakfast Scanning Club, REK 238310), and the cross-sectional MS data (REK 2011/1846, REK 2016/102). All participants gave their written informed consent according to the Declaration of Helsinki. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. 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, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Footnotes Revisions based on peer-review. Additional model evaluation metrics added, new stratification criteria, updated results and discussion section. Data Availability Brain age model training data are available from the respective websites of the databases either openly or after application (see supplemental material). The main study data (OFAMS data) can be shared after receiving a new ethics approval upon reasonable request to the authors. Brain age models and analysis code are freely available at https://github.com/MaxKorbmacher/OFAMS_Brain_Age.