Genetic variants of <i><scp>PLA</scp>2G6</i> are associated with Type 2 diabetes mellitus and triglyceride levels in a Chinese population
Bibliographic record
Abstract
AIM: To test the association of PLA2G6 variants with Type 2 diabetes and clinical characteristics in large Chinese population-based samples. METHODS: A total of 6822 people were recruited. In the first stage, 15 single nucleotide polymorphisms within the PLA2G6 region were selected and genotyped in 3700 Chinese Han people. In the second stage, the single nucleotide polymorphisms that showed a significant association were genotyped in an additional 3122 samples for replication. Genotype-phenotype association studies and meta-analyses were performed after combining data from the two stages. RESULTS: In the first stage, we detected rs132984 and rs2284060 as significantly associated with Type 2 diabetes with odds ratios of 1.247 (95% CI 1.074-1.449, P = 0.004, empirical P = 0.047) and 1.173 (95% CI 1.059-1.299, P = 0.002, empirical P = 0.029), respectively. In the second stage, a similar effect of rs132984 on Type 2 diabetes was observed (odds ratio 1.280, 95% CI 1.094-1.497, P = 0.002). The meta-analysis showed a significant effect of the two single nucleotide polymorphisms on Type 2 diabetes (odds ratio 1.254, 95% CI 1.104-1.451, P = 4.85 × 10⁻⁵ for rs132984; odds ratio 1.120, 95% CI 1.046-1.195, P = 0.003 for rs2284060). Moreover, genotype-phenotype association analysis showed that rs132984 was associated with triglyceride levels (P = 0.022, empirical P = 0.044) and area under the curve for glucose (P = 0.015, empirical P = 0.030). CONCLUSIONS: Our data imply that common single nucleotide polymorphisms within the PLA2G6 region are associated with Type 2 diabetes and triglyceride levels in the Chinese population.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".