First Trimester Protein Biomarkers for Risk of Spontaneous Preterm Birth: Identifying a Critical Need for More Rigorous Approaches to Biomarker Identification and Validation
Bibliographic record
Abstract
BACKGROUND: Spontaneous preterm birth is the leading cause of perinatal morbidity and mortality worldwide and continues to present a major clinical dilemma. We previously reported that a number of protein species were dysregulated in maternal serum collected at 11-13+6 weeks' gestation from pregnancies that continued to labour spontaneously and deliver preterm. OBJECTIVES AND METHODS: In this study, we aimed to validate changes seen in 4 candidate protein species: alpha-1-antitrypsin, vitamin D-binding protein (VDBP), alpha-1beta-glycoprotein and apolipoprotein A-1 in a larger cohort of women using a western blot approach. RESULTS: Serum levels of all 4 proteins were reduced in women who laboured spontaneously and delivered preterm. This reduction was significant for VDBP (p = 0.04), which has been shown to be involved in a plethora of essential biological functions, including actin scavenging, fatty acid transport, macrophage activation and chemotaxis. CONCLUSIONS: The decrease in select proteoforms of VDBP may result in an imbalance in the optimal intrauterine environment for the developing foetus as well as to a successful uncomplicated pregnancy. Thus, certain (phosphorylated) species of VDBP may be of value in developing a targeted approach to the early prediction of spontaneous preterm labour. Importantly, this study raises the importance of a focus on proteoforms and the need for any biomarker validation process to most effectively take these into account rather than the more widespread practice of simply focussing on the primary amino acid sequence of a protein.
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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 | 0.043 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".