Empirical pathological staging and subtyping of TDP-43 proteinopathies

Background: Pathological aggregation of tar DNA-binding protein 43 (TDP-43) in the brain is the primary cause of many cases of frontotemporal lobar degeneration (FTLD), amyotrophic lateral sclerosis (ALS) and limbic-predominant age-related TDP-43 encephalopathy (LATE). It is therefore imperative to establish empirical staging systems to characterize and distinguish stereotypical patterns and commonplace deviations of different TDP-43 proteinopathies. Method: We use ordinal ratings of TDP-43 burden from 19 brain regions to perform data-driven disease progression modeling (SuStaIn) to find the most likely trajectories for FTLD-TDP (n = 108), ALS (n = 137) and LATE (n = 283) from the CNDR Brain Bank at the University of Pennsylvania. Subtype number was defined using cross-validated information criterion. Each individual was assigned a subtype and stage. Multivariate OLS models tested differences between subtypes. Stages were compared to age and existing staging schemes. Cross-validated logistic regression was used for 3-way classification using SuStaIn information only. Result: SuStaIn provided data-driven staging of TDP-43 proteinopathies complementing previously described human-defined staging schema, further providing additional detail (Fig1A-C; Fig3A-C). SuStaIn also identified two distinct subtypes within FTLD-TDP and a further two within ALS (Fig1D). FTLD-TDP subtypes differed in TDP-43 type and Alzheimer’s disease pathology (Table1); ALS subtypes were differentiated by age (Table 2) and by antemortem clinical characteristics. No subtypes were observed for the LATE group. Progression along data-driven stages was positively associated with age in LATE individuals, but negatively associated with age in individuals with FTLD-TDP (Fig2). Using only regional TDP-43 severity, our data driven model could distinguish individuals diagnosed with ALS, FTD or LATE with a cross-validated balanced precision of 0.93 and balanced recall of 0.92, and these metrics improved to 0.95 and 0.96 when combined with a logistic regression model (Fig3). Very little stage overlap was found between FTLD-TDP and LATE, but stages that did overlap showed subtly different patterns (Fig4). Conclusion: We provide an empirical pathological staging system for ALS, FTLD-TDP and LATE, which is sufficient for staging and accurate classification. We demonstrate that there is substantial heterogeneity amongst ALS and FTLD-TDP progression patterns, whilst LATE exhibits a homogeneous progression pattern.