Genome-wide linkage scan for exercise stroke volume and cardiac output in the HERITAGE Family Study
Bibliographic record
Abstract
A genome-wide linkage scan was performed for genes affecting submaximal exercise cardiac output (Q) and stroke volume (SV) in the sedentary state and their responses to a standardized 20-wk endurance training program. A total of 509 polymorphic markers were used, and 328 pairs of siblings from 99 white nuclear families and 102 sibling pairs from 105 black family units were available. Q and SV were measured in relative steady state during exercise at 50 W (Q50 and SV50, respectively). Baseline phenotypes were adjusted for age, sex, and body surface area (BSA), and the training responses (post-training - baseline, Delta) were adjusted for age, sex, baseline BSA, and baseline value of the phenotype. Three analytical strategies were used: a multipoint variance components linkage analysis using all the family data, and regression-based single- and multipoint linkage analyses using pairs of siblings. In whites, baseline SV50 and DeltaSV50 showed promising linkages (P < 0.0023) with markers on chromosomes 14q31.1 and 10p11.2, respectively. Suggestive evidence of linkage (0.01 > P > 0.0023) for DeltaSV50 and Delta Q50 was detected on chromosome 2q31.1 and for baseline SV50 and Q50 on chromosome 9q32-q33. In blacks, markers on 18q11.2 showed promising linkages with baseline Q50. Suggestive evidence of linkage was found in three regions for baseline SV50 (1p21.3, 3q13.3, 12q13.2) and one for baseline SV50 and Q50 (10p14). All these chromosomal regions include several potential candidate genes and therefore warrant further studies in the HERITAGE cohort and other studies.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".