Genome Screen to Detect Linkage to Intracranial Aneurysm Susceptibility Genes
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Evidence supports a substantial genetic contribution to the risk of intracranial aneurysm (IA). The purpose of this study was to identify chromosomal regions likely to harbor genes that contribute to the risk of IA. METHODS: Multiplex families having at least 2 individuals with "definite" or "probable" IA were ascertained through an international consortium. First-degree relatives of individuals with IA who were at increased risk of an IA because of a history of hypertension or present smoking were offered cerebral magnetic resonance angiography. A genome screen was completed using the Illumina 6K SNP system, and the resulting data from 192 families, containing 1155 genotyped individuals, were analyzed. Narrow and broad disease definitions were used when testing for linkage using multipoint model-independent methods. Ordered subset analysis was performed to test for a gene x smoking (pack-years) interaction. RESULTS: The greatest evidence of linkage was found on chromosomes 4 (LOD=2.5; 156 cM), 7 (LOD=1.7; 183 cM), 8 (LOD=1.9; 70 cM), and 12 (LOD=1.6; 102 cM) using the broad disease definition. Using the average pack-years for the affected individuals in each family, the genes on chromosomes 4 (LOD=3.5; P=0.03), 7 (LOD=4.1; P=0.01) and 12 (LOD=3.6; P=0.02) all appear to be modulated by the degree of smoking in the affected members of the family. On chromosome 8, inclusion of smoking as a covariate did not significantly strengthen the linkage evidence, suggesting no interaction between the loci in this region and smoking. CONCLUSIONS: We have detected possible evidence of linkage to 4 chromosomal regions. There is potential evidence for a gene x smoking interaction with 3 of the loci.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.004 | 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".