Identifying markers of insulin resistance in the plasma proteome
Bibliographic record
Abstract
Type 2 diabetes (T2D) represents a significant global health problem. The plasma proteome comprises numerous high‐abundance proteins that may be associated with the development of T2D. The objective was to determine the association between HOMA‐IR, a common measure of insulin resistance, and 54 plasma proteins belonging to disease‐associated pathways in a population of healthy young adults (n=488) from the Toronto Nutrigenomics and Health Study. Protein concentrations were measured by a multiple reaction monitoring HPLC‐MS/MS assay. General linear models were used to assess the association between plasma proteins and HOMA‐IR. Analyses were adjusted for age, sex, ethnicity, waist circumference, physical activity, and contraceptive use among women. Hemopexin, complement factor H, heparin cofactor II, afamin, α 1 ‐anti‐trypsin, α 2 ‐HS‐glycoprotein, apolipoprotein L1, complement C3, serum amyloid P‐component, vitronectin, and transthyretin were significantly ( p <0.0009) positively correlated with HOMA‐IR. Adiponectin, an anti‐inflammatory protein, was inversely correlated with HOMA‐IR. These results suggest that a number of plasma proteins may be useful biomarkers of insulin resistance and T2D risk. Research support from the Advanced Foods and Materials Network.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".