Immune cells and the trajectories of depression, anxiety, and cognitive function among people with amyotrophic lateral sclerosis
Bibliographic record
Abstract
Amyotrophic lateral sclerosis (ALS) represents a complex syndrome characterized by motor, psychiatric, and cognitive symptoms, where associations between cellular immune features and non-motor manifestations remain unknown. In this cohort study, we enrolled 250 incident people with ALS (pwALS) assessed with the Hospital Anxiety and Depression Scale, and 226 pwALS with the Montreal Cognitive Assessment, including 218 overlapping pwALS. All individuals were diagnosed between January 2015 and January 2023 in Stockholm, Sweden. We applied joint latent class models to delineate distinct trajectories of anxiety, depression, and cognition, incorporating survival outcomes. A majority of the pwALS had data on leukocyte counts and flow cytometric analyses using a comprehensive T cell panel. We then used immune cell subtypes measured at diagnosis to predict trajectories of these outcomes following ALS diagnosis. We identified two distinct trajectories for anxiety, depression, and cognitive function following ALS diagnosis. PwALS with longer survival displayed more stable trajectories, while those with shorter survival showed decreasing anxiety symptom, increasing depressive symptom, and declining cognitive function. Higher count of leukocytes at the time of ALS diagnosis tended to associate with anxiety and depression trajectories related to shorter survival. Among T cell subpopulations, several CD8 + T cell subsets were associated with a stable trajectory of depressive symptom, and, in turn, better survival. ALS-associated psychiatric and cognitive trajectories vary significantly between pwALS with different prognosis. Certain T cell subsets measured at diagnosis might be indicative of depression trajectories post-diagnosis. • People with ALS who survive longer tend to have stable mental states. • Higher leukocyte counts are correlated with unstable psychiatric states. • Some CD8 + T cell subsets are correlated with better depressive outcomes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".