Seeding activity of human superoxide dismutase 1 aggregates in familial and sporadic amyotrophic lateral sclerosis postmortem neural tissues by real-time quaking-induced conversion
Bibliographic record
Abstract
Abstract Amyotrophic lateral sclerosis (ALS) is a rapidly progressive neurodegenerative disease with average lifespan of 2–5 years after diagnosis. The identification of novel prognostic and pharmacodynamic biomarkers are needed to facilitate therapeutic development. Metalloprotein human superoxide dismutase 1 (SOD1) is known to accumulate and form aggregates in patient neural tissue with familial ALS linked to mutations in their SOD1 gene. Aggregates of SOD1 have also been detected in other forms of ALS, including the sporadic form and the most common familial form linked to abnormal hexanucleotide repeat expansions in the Chromosome 9 open reading frame 72 (C9ORF72) gene. Here, we report the development of a real-time quaking-induced conversion (RT-QuIC) seed amplification assay using a recombinant human SOD1 substrate to measure SOD1 seeding activity in postmortem spinal cord and motor cortex tissue from persons with different ALS etiologies. Our SOD1 RT-QuIC assay detected SOD1 seeds in motor cortex and spinal cord dilutions down to 10–5. Importantly, we detected SOD1 seeding activity in specimens from both sporadic and familial ALS cases, with the latter having mutations in either their SOD1 or C9ORF72 genes. Analyses of RT-QuIC parameters indicated similar lag phases in spinal cords of sporadic and familial ALS patients, but higher ThT fluorescence maxima by SOD1 familial ALS specimens and sporadic ALS thoracic cord specimens. For a subset of sporadic ALS patients, motor cortex and spinal cords were examined, with seeding activity in both anatomical regions. Our results suggest SOD1 seeds are in ALS patient neural tissues not linked to SOD1 mutation, suggesting that SOD1 seeding activity may be a promising biomarker, particularly in sporadic ALS cases for whom genetic testing is uninformative.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".