Serum proteomic analysis of a pre‐symptomatic multiple sclerosis cohort
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Susceptibility to multiple sclerosis (MS) is determined by environmental and genetic factors, but the cause remains unknown. Changes to the proteome prior to first symptom onset may reflect the underlying pathophysiology of the disease. METHODS: This preliminary study utilized pre-symptomatic and post-symptomatic serum from a sample of 100 incident population-based US military veterans with MS along with 100 matched healthy controls. All samples were obtained from the Department of Defense Serum Repository. Multidimensional protein identification technology tandem mass spectrometry analysis was performed on tryptic peptides of lectin-captured glycosylated serum proteins following albumin/immunoglobulin G depletion. Identified proteins were analyzed with the Ingenuity Pathway Analysis program. RESULTS: The mean intervals between first symptom onset and the collection of pre-symptomatic and post-symptomatic sera were -6.0 and +1.1 years, respectively. Pre-symptomatic proteins from the MS group were differentially regulated compared with both control groups indicating that proteomic changes are detected prior to symptom onset. Pathway analysis showed that proteins involved in the complement and coagulation pathways and lipid transport are significantly altered in the serum of subjects with MS compared with healthy donors. CONCLUSIONS: Compared with healthy controls, differential proteomic changes were noted in the serum of patients with MS that preceded the onset of symptomatic disease. Further work is in progress to confirm or refute these findings.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".