Differential expression of plasma proteins and pathway enrichments in pediatric diabetic ketoacidosis
Bibliographic record
Abstract
BACKGROUND: In children with type 1 diabetes (T1D), diabetic ketoacidosis (DKA) triggers a significant inflammatory response; however, the specific effector proteins and signaling pathways involved remain largely unexplored. This pediatric case-control study utilized plasma proteomics to explore protein alterations associated with severe DKA and to identify signaling pathways that associate with clinical variables. METHODS: We conducted a proteome analysis of plasma samples from 17 matched pairs of pediatric patients with T1D; one cohort with severe DKA and another with insulin-controlled diabetes. Proximity extension assays were used to quantify 3072 plasma proteins. Data analysis was performed using multivariate statistics, machine learning, and bioinformatics. RESULTS: This study identified 214 differentially expressed proteins (162 upregulated, 52 downregulated; adj P < 0.05 and a fold change > 2), reflecting cellular dysfunction and metabolic stress in severe DKA. We characterized protein expression across various organ systems and cell types, with notable alterations observed in white blood cells. Elevated inflammatory pathways suggest an enhanced inflammatory response, which may contribute to the complications of severe DKA. Additionally, upregulated pathways related to hormone signaling and nitrogen metabolism were identified, consistent with increased hormone release and associated metabolic processes, such as glycogenolysis and lipolysis. Changes in lipid and fatty acid metabolism were also observed, aligning with the lipolysis and ketosis characteristic of severe DKA. Finally, several signaling pathways were associated with clinical biochemical variables. CONCLUSIONS: Our findings highlight differentially expressed plasma proteins and enriched signaling pathways that were associated with clinical features, offering insights into the pathophysiology of severe DKA.
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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 | 0.000 | 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".