Novel Protein Glycan–Derived Markers of Systemic Inflammation and C-Reactive Protein in Relation to Glycemia, Insulin Resistance, and Insulin Secretion
Bibliographic record
Abstract
OBJECTIVE N-acetylglucosamine/galactosamine (GlycA) and sialic acid (GlycB) moieties of glycosylated serum proteins are nonspecific measures of inflammation, but conclusive data on their relationship with insulin resistance or insulin secretion are missing. Therefore, we aimed to examine the relation of GlycA, GlycB, and C-reactive protein (CRP) to direct measures of insulin sensitivity (insulin sensitivity index [SI]) and insulin secretion (acute insulin response [AIR]). RESEARCH DESIGN AND METHODS This study used cross-sectional analyses and included 1,225 participants with and without type 2 diabetes in the Insulin Resistance Atherosclerosis Study (IRAS). SI and AIR were measured using the frequently sampled intravenous glucose tolerance test, and GlycA and GlycB were measured using nuclear magnetic resonance spectroscopy. RESULTS GlycA and GlycB had a strong correlation with CRP (r = 0.60 [P < 0.001] and r = 0.46 [P < 0.001], respectively). In a linear regression model with both GlycA and CRP as independent variables, GlycA (β × 1 SD, −0.04 ± 0.02; P < 0.01) and CRP (−0.06 ± 0.02; P < 0.001) were independently associated with SI even after adjusting for demographics, smoking, physical activity, plasma glucose, and BMI. However, neither CRP nor GlycA had an independent relationship with AIR. CONCLUSIONS GlycA may complement CRP in evaluating the relationship between inflammation, glucose tolerance, and insulin resistance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".