Targeted proteomics analysis in type 1 diabetes identifies lower agouti-related protein levels in individuals with impaired hypoglycaemia awareness
Bibliographic record
Abstract
Impaired awareness of hypoglycaemia (IAH) is a complication of diabetes treatment, whereby individuals are no longer able to feel an oncoming hypoglycaemic event. IAH may be a result of central nervous system adaptation to low recurrent hypoglycaemias, however the precise pathways involved remain unknown. This study employed proteomics analysis to explore potential pathophysiological pathways in IAH, using a nested case-control design within the Dutch Type 1 Diabetes Biomarker study. The Olink ® Cardiovascular II panel was used for targeted proteomics, comparing 67 individuals with IAH to 108 age- and sex-matched individuals with normal awareness of hypoglycaemia (NAH). Univariate analysis revealed that agouti-related protein (AGRP) levels were significantly lower in individuals with IAH compared to NAH (6.12 NPX vs. 6.44 NPX, FDR-adjusted P = 0.012). In multivariate models adjusted for sex and diabetes duration, AGRP remained significant before p-value adjustment ( P < 0.001) but not after adjusting for false discovery rate (FDR) ( P = 0.057). AGRP, known for its orexigenic effects and expression in the arcuate nucleus of the hypothalamus, is involved in glucose sensing and hypothalamic-pituitary-adrenal (HPA) axis stimulation, suggesting its potential role in the pathophysiology of IAH. This study highlights the need for further research to clarify AGRP’s role and its possible implications for managing IAH in diabetes.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".