Placental proteomic signatures of preterm birth, gestational age, and birthweight
Bibliographic record
Abstract
BACKGROUND: Preterm birth and low birthweight are leading contributors to infant morbidity and mortality, yet underlying mechanisms remain poorly understood. Proteomics can provide insights into biological pathways that may be targets for prevention and reveal predictive markers of at-risk pregnancies. The placenta plays a critical role in parturition, yet few studies have investigated proteomic signatures in the placenta associated with birth outcomes. METHODS: Using untargeted, mass spectrometry-based label-free proteomics, 1,221 proteins were quantified in placental samples from 99 participants in the Conditions Affecting Neurocognitive Development and Learning in Early Childhood (CANDLE) study. Associations of placental proteomics with binary spontaneous preterm birth, continuous gestational age at birth, and birthweight-for-gestational age z-scores were evaluated via differential abundance analysis, pathway enrichment, and principal component analysis (PCA) adjusting for numerous potential confounders. Sparse partial least squares discriminant analysis (sPLS-DA) was employed in a classification analysis to predict preterm versus term birth using the placental proteomics data. RESULTS: Preterm birth was associated with expression of 295 proteins and 15 molecular pathways, while gestational age was associated with expression of 367 proteins and 28 molecular pathways. Among the proteins significantly associated with either outcome, 264 (72%) overlapped. Proteins most strongly associated with both birth timing measures included Steryl-sulfatase (STS; preterm birth: LogFC = 2.08, FDR < 0.0001; gestational age at birth: LogFC= -0.57, FDR < 0.000001) and Collagen alpha-2(I) chain (COL1A2; preterm birth: LogFC= -2.11, FDR < 0.001; gestational age at birth: LogFC = 0.49, FDR < 0.0001). No associations were identified with birthweight z-scores. Proteins with the strongest links to preterm birth were major contributors to variance explained in PCA, and four of ten retained PCs were significantly associated with preterm birth. The top component in sPLS-DA classified preterm birth with 86.9% accuracy using 30 proteins, while the optimal sPLS-DA solution retaining three components classified preterm birth with 87.7% accuracy using 120 proteins. CONCLUSIONS: Many of the top proteins and molecular pathways associated with birth timing measures have been previously implicated in birth outcomes and pregnancy complications, and point to mechanisms including energy production, inflammation, and oxidative stress that may drive these risks. These proteins may serve as targets in future mechanistic and therapeutic research. Proteins identified through sPLS-DA demonstrated high accuracy in distinguishing preterm from term birth, pointing to potential targets for clinical screening tools, but necessitating validation in independent studies and more accessible biospecimens.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".