Systematic, Genome-Wide, Sex-Specific Linkage of Cardiovascular Traits in French Canadians
Bibliographic record
Abstract
The sexual dimorphism of cardiovascular traits, as well as susceptibility to a variety of related diseases, has long been recognized, yet their sex-specific genomic determinants are largely unknown. We systematically assessed the sex-specific heritability and linkage of 539 hemodynamic, metabolic, anthropometric, and humoral traits in 120 French-Canadian families from the Saguenay-Lac-St-Jean region of Quebec, Canada. We performed multipoint linkage analysis using microsatellite markers followed by peak-wide linkage scan based on Affymetrix Human Mapping 50K Array Xba240 single nucleotide polymorphism genotypes in 3 settings, including the entire sample and then separately in men and women. Nearly one half of the traits were age and sex independent, one quarter were both age and sex dependent, and one eighth were exclusively age or sex dependent. Sex-specific phenotypes are most frequent in heart rate and blood pressure categories, whereas sex- and age-independent determinants are predominant among humoral and biochemical parameters. Twenty sex-specific loci passing multiple testing criteria were corroborated by 2-point single nucleotide polymorphism linkage. Several resting systolic blood pressure measurements showed significant genotype-by-sex interaction, eg, male-specific locus at chromosome 12 (male-female logarithm of odds difference: 4.16; interaction P=0.0002), which was undetectable in the entire population, even after adjustment for sex. Detailed interrogation of this locus revealed a 220-kb block overlapping parts of TAO-kinase 3 and SUDS3 genes. In summary, a large number of complex cardiovascular traits display significant sexual dimorphism, for which we have demonstrated genomic determinants at the haplotype level. Many of these would have been missed in a traditional, sex-adjusted setting.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".