Influence of Genetic Risk Factors on Coronary Heart Disease Occurrence in Afro-Caribbeans
Bibliographic record
Abstract
BACKGROUND: Despite excessive rates of cardiovascular risk factors such as hypertension, diabetes, and obesity, Afro-Caribbeans have lower mortality rates from coronary heart disease (CHD) than do whites. This study evaluated the association of genetic risk markers previously identified in whites and CHD in Afro-Caribbeans. METHODS: We studied 537 Afro-Caribbean individuals (178 CHD cases and 359 controls) who were genotyped for 19 CHD-related single-nucleotide polymorphisms (SNPs). A genetic risk score (GRS) incorporating the 19 SNPs was calculated. These participants were compared with 1360 white individuals from the Second Northwick Park Heart Study. RESULTS: In Afro-Caribbeans, patients with CHD had higher rates of hypertension (78.7% vs 30.1%), hypercholesterolemia (52.8% vs 15.0%), and diabetes (53.9% vs 14.8%) and were more often men (64.0% vs 43.7%) and smokers (27.5% vs 13.4%) compared with non-CHD controls (all P < 0.001). The GRS was higher in Afro-Caribbeans with CHD than in those without CHD (13.90 vs 13.17; P < 0.001) and was significantly associated with CHD after adjustment for cardiovascular risk factors, with an odds ratio of 1.40 (95% confidence interval, 1.09-1.80) per standard deviation change. There were significant differences in allelic distributions between the 2 ethnic groups for 14 of the 19 SNPs. The GRS was substantially lower in Afro-Caribbean controls compared with white controls (13.17 vs 16.59; P < 0.001). CONCLUSIONS: This study demonstrates that a multilocus GRS composed of 19 SNPs associated with CHD in whites is a strong predictor of the disease in Afro-Caribbeans. The differences in CHD occurrence between Afro-Caribbeans and whites might be a result of significant discrepancies in common gene variant distribution.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".