Automated speech analysis reveals progressive linguistic changes associated with subsequent gray matter loss in multiple sclerosis

BACKGROUND: The utility of high-level linguistic analysis for longitudinal monitoring of multiple sclerosis (MS) and its relationship with progressive brain volume loss remains largely unexplored. OBJECTIVE: To characterize longitudinal changes in lexical and syntactic features in MS and determine whether linguistic alterations are associated with subsequent brain volume loss. METHODS: Ninety-seven patients with MS and 80 age- and sex-matched healthy controls completed story narration tasks at baseline and 2-year follow-up. Recordings were automatically transcribed and analyzed to extract five linguistic features. Magnetic resonance imaging (MRI) assessments were performed between the 2- and 7-year follow-ups. Linear mixed-effects models assessed linguistic decline over 2 years and whether these early changes were associated with a subsequent 5-year brain volume loss. RESULTS: = 0.02). Early changes in these lexical features were associated with subsequent 5-year decline in total gray matter volume. Linguistic changes were also related to cortical gray matter and cerebellar volume loss but not to hippocampal or white matter volume loss. CONCLUSION: Automated speech analysis captures progressive linguistic decline in MS. Early linguistic changes were associated with subsequent brain volume loss, supporting speech-derived biomarkers of neurodegeneration.