Abstract P229: Genetic Risk Scores are Associated with Chronic Venous Disease Prevalence and Severity in a Multi-Ethnic Cohort: The San Diego Population Study (SDPS)
Bibliographic record
Abstract
Background: Chronic venous disease is common, affecting up to 40% of the population, although estimates vary quite widely due to differing evaluation methods and definitions. Chronic venous disease shares some risk factors with venous thromboembolism (VTE). Several genetic loci have been recently discovered and replicated for VTE, mostly in populations of European descent. We tested associations of these loci, as well as a genetic risk score including these variants, with chronic venous disease prevalence and severity in a multi-ethnic cohort. Methods: The San Diego Population Study (SDPS) is a prospective cohort study that evaluated 2404 ethnically diverse men and women aged 29-91 for venous disease using duplex ultrasound. The current study includes 1229 participants from the baseline exam who were genotyped for 35 variants in 23 loci. Venous disease was defined as moderate or severe, as well as severe only. Logistic regression was used to examine the association of each variant with venous disease, stratified by ethnic group. A weighted genetic risk score, using the top 20% of variants and weighting by the beta coefficients, was generated for each ethnic group. Associations of this risk score with venous disease were examined stratified by ethnic group. Results: The mean ± standard deviation (SD) age was 60±11, with 64% female, and 62% White, 14% Hispanic, 11% African-American, and 12% Asian. The prevalence of moderate and severe venous disease was 41%, and severe venous disease alone was 25%. While some loci overlapped in the ethnic-specific genetic risk scores, others were exclusive to an ethnic group. In models adjusting for known venous disease risk factors, in Whites, Hispanics, African-Americans and Asians, respectively, each SD higher genetic risk score was associated with a 1.42-fold higher odds (95% CI (1.21, 1.66)), 2.06-fold higher odds (95% CI (1.44, 2.95)), a 2.25-fold higher odds (95% CI (1.38, 3.66)), and 2.45-fold higher odds (95% CI (1.57, 3.82)) for moderate or severe disease. The difference in c-statistics was statistically significant between the known venous risk factor model and this model adding the genetic risk factor for Hispanics, African-Americans, and Asians, with 0.67 vs. 0.75 (p=0.03), 0.69 vs. 0.77 (p=0.02), 0.63 vs. 0.74 (p=0.01), respectively. The difference was not significant for Whites, 0.64 vs. 0.66 (p=0.12). All results were similar for severe venous disease only. Conclusions: This ethnic-specific genetic risk score is strongly associated with chronic venous disease, and may be of greater importance for venous disease in those of non-European descent. Future work should focus on examining racial/ethnic group genetic architecture in relation to venous disease.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".