Additional file 1 of Polygenic risk for coronary heart disease acts through atherosclerosis in type 2 diabetes
Bibliographic record
Abstract
Additional file 1: Table S1. Characteristics of patients recruited at the Jewish General Hospital. Table S2. Characteristics of patients recruited at the Royal Victoria Hospital. Table S3. Effect of CHD PRS on CHD adjusted for traditional clinical risk factors in the diabetic UK Biobank cohort. Table S4. Associations of CHD PRS with clinical risk factors among all 352 individuals in MCCD. Table S5. Association between CHD PRS and continuous clinical risk factors in the diabetic UK Biobank cohort and the MCCD cohort. Table S6. Effect of non-European ancestry in MCCD. Table S7. Effect of CHD PRS by hospital among European descendants in the MCCD cohort. Table S8. Effects of type 2 diabetes duration and age of onset on atherosclerotic burden among European descendants in the MCCD cohort. Figure S1. Ethnicity decomposition of local population. 162,811 representative LDpruned SNPs were used to examine similarity of each individual with the Eastern Asian (EAS), African (AFR) and European (EUR) populations from the 1000 Genomes Project (G1000 cohort). Samples residing in the shaded area were regarded as European descendants. Samples residing in the middle of two super populations may have an unlisted ancestry or a mixed ancestry, and were thus not regarded as European descendants Samples recruited at the two different hospitals were shaped differently. AFR: the African super population; EAS: The East Asian super population; EUR: The European super population; MCCD: The McGill Cardiac Complications in Diabetes cohort. Figure S2. Sex-specific associations of CHD PRS with CHD and clinical risk factors among individuals with type 2 diabetes. (a) Female-specific associations based on 8092 women in the diabetic UK Biobank cohort and 65 women of a European ancestry in the MCCD cohort. (b) Male-specific associations based on 13,010 men in the diabetic UK Biobank cohort and 245 men of a European ancestry in the MCCD cohort. All results were based on logistic regression models as presented in Fig. 1 without adjusting for sex. Figure S3. Meta-analyses of ORs based on (a) logistic regression models using multivessel stenosis as the outcome and (b) ordinal logistic regression models using the number of atherosclerotic lesions as the outcome. Regressions were performed separately by hospital on samples with a 0putative European ancestry in the MCCD cohort. Estimated ORs are represented by squares where the area is proportional to the corresponding sample size at each hospital. Metaanalytic ORs are represented by diamonds. For all ORs, the corresponding CIs are indicated inside brackets. JGH: The Jewish General Hospital; RVH: The Royal Victoria Hospital.
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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 | 0.002 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.839 | 0.097 |
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".