Discovery and Verification of Sjögren’s Syndrome Protein Biomarkers in Tears by Targeted LC-MRM
Bibliographic record
Abstract
Sjögren's syndrome (SS) is an autoimmune rheumatic disorder characterized by exocrine gland dysfunction, mainly from the lacrimal and salivary glands. The disease causes severe aqueous dry eye syndrome (DED) and is associated with high rates of complications, including corneal ulceration, scaring, and perforation. Systemic complications may occur as well as a higher risk of developing lymphoma. Diagnosis of SS-DED is often delayed and difficult to establish. With the aim of discovering biomarkers to help discriminate SS-DED patients, a combination of untargeted and targeted LC-MS/MS analyses were performed on tear samples collected on Schirmer strips and subjected to tryptic digestion. Following the analysis of three cohorts and the development of two targeted LC-sMRM methods for the verification of putative biomarkers found in the first cohort of samples, 64 proteins could be linked to Sjögren's syndrome, in the hopes of helping to confirm diagnoses as well as potentially stratifying the severity of disease in these patients. Proteins that were increased in SS-DED showed activation of the immune system and alterations in homeostasis. Several proteases and protease inhibitors were found to be significantly changing in SS-DED, as well as a consistent decrease in specific proteins known to be secreted by the lacrimal gland.
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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 | 0.003 | 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".