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

Over 2 years, patients with MS showed changes in vocabulary range (β = 0.53, p = 0.008, q = 0.02) and phrase repetition (β = 0.56, p = 0.007, q = 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.