Data-driven Subtyping and Staging of ALS: A Multicentre, Longitudinal, Deformation-Based Morphometry Study
Bibliographic record
Abstract
Abstract Amyotrophic lateral sclerosis (ALS) is clinically and biologically heterogeneous, yet data-driven imaging subtyping approaches have rarely been validated longitudinally or linked to clinical and survival outcomes. We aimed to identify and validate distinct ALS subtypes and disease stages using deformation-based morphometry (DBM) and the Subtype and Stage Inference (SuStaIn) model, and to characterize their cross-sectional and longitudinal imaging, clinical, cognitive, and survival profiles. Data from 198 ALS patients and 144 healthy controls in the Canadian ALS Neuroimaging Consortium (CALSNIC) multicenter cohort were analyzed. Baseline regional DBM w-scores from 14 ALS-relevant regions served as input to SuStaIn to infer subtypes and stages. Longitudinal consistency of subtype and stage assignments (e.g. adherence to the expected disease evolution) was assessed using follow-up visits. Imaging and clinical trajectories were compared across subtypes using linear mixed-effects models incorporating stage and elapsed time. Associations between longitudinal variables and SuStaIn stage were estimated using mixed models, while baseline clinical and cognitive differences were assessed with ordinary least squares regression. Survival differences were evaluated using Kaplan–Meier curves and log-rank tests. SuStaIn identified one normal-appearing group (S0) and three ALS atrophy subtypes. S0 showed no baseline atrophy but exhibited longitudinal motor decline and the most favorable survival (log-rank p < 0.05 to p < 0.01). S1 exhibited classical motor/corticospinal tract-dominant degeneration, greater lower motor neuron burden, and intermediate survival. S2 showed limbic-onset atrophy progressing toward motor pathways, with preserved cognition and a milder course. S3 demonstrated extensive fronto-parietal and striatal atrophy, longitudinal motor–thalamic degeneration, and the shortest survival. Subtype and stage assignments demonstrated high longitudinal consistency (>90%). SuStaIn stage was strongly associated with widespread brain atrophy (and ventricular expansion), with the strongest effects in limbic–subcortical regions. Stage also correlated with ALS Functional Rating Scale-Revised (ALSFRS-R) decline and forced vital capacity (FVC) reduction, indicating that stage reflects disease-linked progression. This study establishes a robust, longitudinally validated model of ALS heterogeneity, showing that SuStaIn-derived subtypes define distinct disease trajectories, whereas the normal-appearing group reflects an early, structurally preserved state with a more favorable survival profile. By integrating probabilistic staging with longitudinal modeling, these findings clarify dynamic subtype-specific progression patterns and support the use of SuStaIn for biologically informed patient stratification, prognostication, and clinical trial enrichment in ALS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".