A Genome‐Wide Association Study of Plasma α <sub>2</sub> ‐Macroglobulin Concentrations in Young Adults
Bibliographic record
Abstract
Background Gluten intake has been shown to be associated with circulating levels of α 2 ‐macroglobulin in young adults without celiac disease. Gluten‐free foods have increased in popularity over the past decade despite a poor understanding of the physiological effects of gluten intake in those without celiac disease. Plasma α 2 ‐macroglobulin represents a physiologically important molecule involved in inflammation and cytokine release, but the contribution of common genetic variation to the observed variation in circulating concentrations of α 2 ‐macroglobulin remains unclear. Objective The objective was to identify genetic variants that are associated with α 2 ‐macroglobulin in a population of young adults using a genome‐wide approach. Methods A genome‐wide association study (GWAS) was conducted on circulating levels of α 2 ‐macroglobulin in a population of young Caucasians without clinically diagnosed celiac disease from the Toronto Nutrigenomics and Health Study (n=488). Concentrations of α 2 ‐macroglobulin were measured in plasma using a multiple reaction monitoring HPLC‐MS/MS assay. Genome‐wide genotyping was conducted for 822,000 single nucleotide polymorphisms (SNPs) using the Affymetrix 6.0 chip. The association between genome‐wide genetic variants and plasma α 2 ‐macroglobulin was explored using linear regression with an additive mode of inheritance. Results Circulating α 2 ‐macroglobulin was associated with variation in ICOSGL (p = 3.9×10 −7 ), a T‐cell stimulatory gene involved in cytokine release and various immune‐related disorders including celiac disease. Conclusion These results suggest that the physiological effects of gluten intake may be mediated by genes involved in T‐cell proliferation and cytokine release. Support or Funding Information 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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".