Genome Scan for Familial Abdominal Aortic Aneurysm Using Sex and Family History as Covariates Suggests Genetic Heterogeneity and Identifies Linkage to Chromosome 19q13
Bibliographic record
Abstract
BACKGROUND: Abdominal aortic aneurysm (AAA) is a relatively common disease, with 1% to 2% of the population harboring aneurysms. Genetic risk factors are likely to contribute to the development of AAAs, although no such risk factors have been identified. METHODS AND RESULTS: We performed a whole-genome scan of AAA using affected-relative-pair (ARP) linkage analysis that includes covariates to allow for genetic heterogeneity. We found strong evidence of linkage (logarithm of odds [LOD] score=4.64) to a region near marker D19S433 at 51.88 centimorgans (cM) on chromosome 19 with 36 families (75 ARPs) when including sex and the number of affected first-degree relatives of the proband (N(aff)) as covariates. We then genotyped 83 additional families for the same markers and typed additional markers for all families and obtained a LOD score of 4.75 (P=0.00014) with sex, N(aff), and their interaction as covariates near marker D19S416 (58.69 cM). We also identified a region on chromosome 4 with a LOD score of 3.73 (P=0.0012) near marker D4S1644 using the same covariate model as for chromosome 19. CONCLUSIONS: Our results provide evidence for genetic heterogeneity and the presence of susceptibility loci for AAA on chromosomes 19q13 and 4q31.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.005 | 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".