IMPACT OF ABCC8 AND TRPM4 GENETIC VARIATION IN CENTRAL NERVOUS SYSTEM DYSFUNCTION ASSOCIATED WITH PEDIATRIC SEPSIS
Bibliographic record
Abstract
ABSTRACT: Background: Sepsis-associated brain injury is associated with deterioration of mental status, persistent cognitive impairment, and morbidity. The SUR1/TRPM4 channel is a nonselective cation channel that is transcriptionally upregulated in the central nervous system with injury, allowing sodium influx, depolarization, cellular swelling, and secondary injury. We hypothesized that genetic variation in ABCC8 (SUR1 gene) and TRPM4 would associate with central nervous system dysfunction in severe pediatric sepsis. Methods: 326 children with severe sepsis underwent whole exome sequencing in an observational cohort. We compared children with and without central nervous system dysfunction (Glasgow Coma Scale <12) to assess for associations with clinical characteristics and pooled rare variants in ABCC8 and TRPM4. Sites of variation were mapped onto protein structure and assessed for phenotypic impact. Results: Pooled rare variants in either ABCC8 or TRPM4 associated with decreased odds of central nervous system dysfunction in severe pediatric sepsis (OR 0.14, 95% CI 0.003-0.87), P = 0.025). This association persisted following adjustment for race, organ failure, viral infection, and continuous renal replacement therapy (aOR 0.11, 95% CI 0.01-0.59, P = 0.038). Structural mapping showed that rare variants concentrated in the nucleotide-binding domains of ABCC8 and N-terminal melastatin homology region of TRPM4 . Conclusion : This study suggests a role for the ABCC8/TRPM4 channel in central nervous system dysfunction in severe pediatric sepsis. Although exploratory, the lack of therapies to prevent or mitigate central nervous system dysfunction in pediatric sepsis warrants further studies to clarify the mechanism and confirm the potential protective effect of these rare ABCC8/TRPM4 variants.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".