Site-Specific IGFBP-1 Hyper-Phosphorylation in Fetal Growth Restriction: Clinical and Functional Relevance
Bibliographic record
Abstract
Phosphorylation enhances IGFBP-1 binding to IGF-I, thereby limiting the bioavailability of IGF-I that may be important in fetal growth. Our goal in this study was to determine whether changes in site-specific IGFBP-1 phosphorylation were unique to fetal growth restriction. To establish a link, we compared IGFBP-1 phosphorylation (sites and degree) in amniotic fluid from FGR (N = 10) and controls (N = 12). The concentration of serine phosphorylated IGFBP-1 showed a negative correlation with birth weight in FGR (P = 0.049). LC-MS/MS analysis revealed all four previously identified phosphorylation sites (Ser98, Ser101, Ser119, and Ser169) to be common to FGR and control groups. Relative phosphopeptide intensities (LC-MS) between FGR and controls demonstrated 4-fold higher intensity for Ser101 (P = 0.026), 7-fold for Ser98/Ser101 (P = 0.02), and 23-fold for Ser169 (P = 0.002) in the FGR group. Preliminary BIAcore data revealed 4-fold higher association and 1.7-fold lower dissociation constants for IGFBP-1/IGF-I in FGR. A structural model of IGFBP-1 bound to IGF-I indicates that all the phosphorylation sites are on relatively mobile regions of the IGFBP-1 sequence. Residues Ser98, Ser101, and Ser169 are close to structured regions that are involved in IGF-I binding and, therefore, could potentially make direct contact with IGF-I. On the other hand, residue Ser119 is in the middle of the unstructured linker that connects the N- and C-terminal domains of IGFBP-1. The model is consistent with the assumption that residues Ser98, Ser101, and Ser169 could directly interact with IGF-I, and therefore phosphorylation at these sites could change IGF-I interactions. We suggest that site-specific increase in IGFBP-1 phosphorylation limits IGF-I bioavailability, which directly contributes to the development of FGR. This study delineates the potential role of higher phosphorylation of IGFBP-1 in FGR and provides the basis to substantiate these findings with larger sample size.
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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 | 0.005 | 0.003 |
| 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 | 0.004 |
| 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".