Low-frequency variants in genes involved in glutamic acid metabolism and γ-glutamyl cycle and risk of coronary artery disease in type 2 diabetes
Bibliographic record
Abstract
A common genetic variant at the glutamate-ammonia ligase (GLUL) locus has been previously associated with an increased risk of coronary artery disease (CAD) as well as alterations of glutamic acid metabolism and the γ-glutamyl cycle in individuals with type 2 diabetes (T2D). Here we investigated whether less frequent variants in GLUL and 15 additional genes in these pathways are associated with differences in CAD risk in T2D. Coding sequences and regulatory elements of these genes were sequenced in 2,394 individuals with T2D from three CAD case/control sets. Ninety-six variants with minor allele frequency [MAF]< 0.05 were identified as being nominally associated with CAD status. One of these variants (rs62447457, MAF 0.025), placed in a non-coding region flanking the γ-glutamylcyclotransferase (GGCT) gene, showed nominal evidence of replication in two other cases-control sets (n = 1,132), with summary OR of 0.54 (p = 2.5 × 10–4). Another variant (rs145322388, MAF = 0.039), flanking the dipeptidase 2 (DPEP2) gene, showed association with CAD status across discovery and replications sets (summary OR 0.61, p = 2.5 × 10–4). A third variant (rs1238275622, MAF 0.004), flanking the GLUL gene, was associated with increased risk of CAD (summary OR 1.84, p-value 2.1 × 10–3). Based on their Regulome scores (2b, 2a, and 3a, respectively), all three variants are very likely to have regulatory functions. In summary, we have identified low-frequency variants associated with CAD in T2D at two loci involved in glutamic acid metabolism and the γ-glutamyl cycle. These findings provide further evidence for a role of these pathways in the link between T2D and CAD.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| 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".