Utility of the ALSFRS‐R for predicting ALS and comorbid disease neuropathology: The Veterans Affairs Biorepository Brain Bank. Issue 2 (4th June 2022) - Colvin, Leigh E.; Foster, Zachariah W.; Stein, Thor D.; Thakore‐James, Manisha; Salajegheh, Mohammad Kian; Carr, Kendall; Spencer, Keith R.; Abdul Rauf, Nazifa; Adams, Latease; Averill, James G.; Walker, Sean E.; Robey, Ian; et al.
Abstract: Introduction/Aims: The amyotrophic lateral sclerosis (ALS) functional rating scale‐revised (ALSFRS‐R) is commonly used to track ALS disease progression; however, there are gaps in the literature regarding the extent to which the ALSFRS‐R relates to underlying central nervous system (CNS) pathology. The current study explored the association between ALSFRS‐R (total and subdomain) scores and postmortem neuropathology (both ALS‐specific and comorbid disease). Methods: Within our sample of 93 military veterans with autopsy‐confirmed ALS, we utilized hierarchical cluster analysis (HCA) to identify discrete profiles of motor dysfunction based on ALSFRS‐R subdomain scores. We examined whether emergent clusters were associated with neuropathology. Separate analyses of variance and covariance with post‐hoc comparisons were performed to examine relevant cluster differences. Results: Analyses revealed significant correlations between ALSFRS‐R total and subdomain scores with some, but not all, neuropathological variables. The HCA illustrated three groups: Cluster 1—predominantly diffuse functional impairment; Cluster 2—spared respiratory/bulbar and impaired motor function; and Cluster 3—spared bulbar and impaired respiratory, and fine and gross motor function. Individuals in Cluster 1 (and to a lesser degree, Cluster 3) exhibited greater accumulation of ALS‐specific neuropathology and less comorbid neuropathology than those in Cluster 2. Discussion: These results suggest that discrete patterns of motor dysfunction based on ALSFRS‐R subdomain scores are related to postmortem neuropathology. Findings support use of ALSFRS‐R subdomain scores to capture the heterogeneity of clinical presentation and disease progression in ALS, and may assist researchers in identifying endophenotypes for separate assessment in clinical trials.