Multi-Ethnic Analysis of Lipid-Associated Loci: The NHLBI CARe Project
Bibliographic record
Abstract
BACKGROUND: Whereas it is well established that plasma lipid levels have substantial heritability within populations, it remains unclear how many of the genetic determinants reported in previous studies (largely performed in European American cohorts) are relevant in different ethnicities. METHODOLOGY/PRINCIPAL FINDINGS: We tested a set of ∼50,000 polymorphisms from ∼2,000 candidate genes and genetic loci from genome-wide association studies (GWAS) for association with low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG) in 25,000 European Americans and 9,000 African Americans in the National Heart, Lung, and Blood Institute (NHLBI) Candidate Gene Association Resource (CARe). We replicated associations for a number of genes in one or both ethnicities and identified a novel lipid-associated variant in a locus harboring ICAM1. We compared the architecture of genetic loci associated with lipids in both African Americans and European Americans and found that the same genes were relevant across ethnic groups but the specific associated variants at each gene often differed. CONCLUSIONS/SIGNIFICANCE: We identify or provide further evidence for a number of genetic determinants of plasma lipid levels through population association studies. In many loci the determinants appear to differ substantially between African Americans and European Americans.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".