AUTHOR=Høgestøl Einar A. , Kaufmann Tobias , Nygaard Gro O. , Beyer Mona K. , Sowa Piotr , Nordvik Jan E. , Kolskår Knut , Richard Geneviève , Andreassen Ole A. , Harbo Hanne F. , Westlye Lars T. TITLE=Cross-Sectional and Longitudinal MRI Brain Scans Reveal Accelerated Brain Aging in Multiple Sclerosis JOURNAL=Frontiers in Neurology VOLUME=10 YEAR=2019 URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2019.00450 DOI=10.3389/fneur.2019.00450 ISSN=1664-2295 ABSTRACT=
Multiple sclerosis (MS) is an inflammatory disorder of the central nervous system. By combining longitudinal MRI-based brain morphometry and brain age estimation using machine learning, we tested the hypothesis that MS patients have higher brain age relative to chronological age than healthy controls (HC) and that longitudinal rate of brain aging in MS patients is associated with clinical course and severity. Seventy-six MS patients [71% females, mean age 34.8 years (range 21–49) at inclusion] were examined with brain MRI at three time points with a mean total follow up period of 4.4 years (±0.4 years). We used additional cross-sectional MRI data from 235 HC for case-control comparison. We applied a machine learning model trained on an independent set of 3,208 HC to estimate individual brain age and to calculate the difference between estimated and chronological age, termed brain age gap (BAG). We also assessed the longitudinal change rate in BAG in individuals with MS. MS patients showed significantly higher BAG (4.4 ± 6.6 years) compared to HC (Cohen's D = 0.69,