Abstract 18116: Genetic Associations With Atherosclerotic Abdominal Aortic Calcification
Bibliographic record
Abstract
Background: There is limited information regarding genetic contributions to atherosclerotic aortic calcification, an important predictor of cardiovascular disease. Methods: We conducted a genome-wide association study (GWAS) meta-analysis with subsequent replication analysis to define single nucleotide polymorphisms (SNPs) associated with abdominal (AAC) or thoracic aortic calcification (TAC). AAC and TAC were quantified using multi-detector computed tomography. SNPs were assayed by Illumina or Affymetrix arrays and imputation at the cohort level was performed using data from the 1000 Genomes project. Results: 9417 individuals of European descent from four cohorts of the Cohorts for Heart and Aging Research in Genome Epidemiology (CHARGE) consortium were included in the AAC discovery analysis and 8422 individuals from five cohorts in the TAC discovery analysis. SNPs achieving genome-wide significance were tested for replication in four additional cohorts with Hispanic-American (HA) and African-American (AA) participants. Two regions contained SNPs associated at a genome-wide level for AAC (p<5.0x10 -8 , Table), the HDAC9 (chromosome 7, 6 SNPs) and RAP1GAP (chromosome 1, 2 SNPs) genetic loci. All six HDAC9 SNPs were associated with AAC in HA. Among these, rs2107595 was associated with AAC both in HA (p=2.8x10 -6 ) and in AA (p=0.01). SNPs in RAP1GAP were not associated with AAC in the replication analysis. No SNPs were associated with TAC at the genome-wide threshold. SNPs in the HDAC9 locus were associated with other forms of calcification (coronary artery calcification) as well as clinically apparent coronary heart disease (p<0.05). Conclusions: SNPs in the HDAC9 locus are associated with the presence of AAC in participants of European descent. This association was replicated in other ethnic groups in the United States. These findings suggest a novel role for HDAC9 in the development of abdominal aortic calcification.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".