Cathepsin D as biomarker in cerebrospinal fluid of nusinersen‐treated patients with spinal muscular atrophy
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The therapeutic landscape of spinal muscular atrophy (SMA) has changed dramatically during the past 4 years, but treatment responses differ remarkably between individuals, and therapeutic decision-making remains challenging, underlining the persistent need for validated biomarkers. METHODS: We applied untargeted proteomic analyses to determine biomarkers in cerebrospinal fluid (CSF) samples of SMA patients under treatment with nusinersen. Identified candidate proteins were validated in CSF samples of SMA patients by Western blot and enzyme-linked immunosorbent assay. Furthermore, levels of peripheral neurofilament heavy and light chain were determined. RESULTS: Untargeted proteomic analysis of CSF samples of three SMA type 1 patients revealed the lysosomal protease cathepsin D as a candidate biomarker. Subsequent validation analysis in a larger cohort of 31 pediatric SMA patients (type 1, n = 12; type 2, n = 9; type 3, n = 6; presymptomatically treated, n = 4; age = 0-16 years) revealed a significant decline of cathepsin D levels in SMA patients aged ≥2 months at the start of treatment. Although evident in all older age categories, this decline was only significant in the group of patients who showed a positive motor response. Moreover, downregulation of cathepsin D was evident in muscle biopsies of SMA patients. CONCLUSIONS: We identified a decline of cathepsin D levels in CSF samples of SMA patients under nusinersen treatment that was more pronounced in the group of "treatment responders" than in "nonresponders." We believe that our results indicate a suitability of cathepsin D levels as a possible biomarker in SMA also in older patients, in combination with analysis of peripheral neurofilament light chain in adolescents or alone in adult patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".