A common haplotype and the Pro582Ser polymorphism of the hypoxia-inducible factor-1α (<i>HIF1A</i>) gene in elite endurance athletes
Bibliographic record
Abstract
Hypoxia-inducible factor-1alpha (HIF1A) is a transcription factor regulating several genes in response to hypoxic stimuli. HIF1A target genes code for proteins involved in oxygen transport, glycolytic enzymes, and glucose transporters. We investigated whether single-nucleotide polymorphisms and haplotypes in the HIF1A gene are associated with endurance performance in the Genathlete cohort, which includes 316 Caucasian male elite endurance athletes (EEA) with a maximal oxygen uptake of 79.0+/-3.5 ml.kg(-1).min(-1) (mean+/-SD) and 304 Caucasian male sedentary controls with a maximal oxygen uptake of 40.1+/-7.0 ml.kg(-1).min(-1). Six single-nucleotide polymorphisms (rs1951795, rs11158358, rs2301113, rs11549465, rs115494657, rs17099207) were genotyped with the TaqMan system. We found a nominal significant tendency for a difference between the two groups for HIF1A Pro582Ser (rs11549465) genotype distributions (Pchi2=0.017). Homozygotes of the Pro genotype were slightly more frequent in athletes than in controls (84 vs. 75%). Compared with Ser carriers, the odds ratio (OR) of being an EEA in Pro/Pro homozygotes was 1.77 [95% confidence interval (CI): 1.18-2.67, P=0.006] compared with the other genotypes. A common HIF1A haplotype (frequency: 15%), including the rs11549465 Pro allele and the minor A allele of rs17099207 in the 3' flanking region of the gene, showed a significant association with EEA status (OR: 2.37, 95% CI: 1.21-4.66, P=0.012), whereas the most prevalent haplotype (frequency: 59%) comprising the rs11549465 Pro allele and the major G allele of rs1709920 showed no association with EEA status (OR: 0.93, 95% CI: 0.58-1.50, P=0.769). We found preliminary evidence that the HIF1A Pro582Ser polymorphism and a common haplotype of the HIF1A gene may be associated with EEA status in Caucasian men.
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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 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".