Abstract 15465: Precision Medicine Approach to Resistant Hypertension: Genetic Markers of Resistant Hypertension Through a Genome-wide Association Study (GWAS) in the Secondary Prevention of Subcortical Strokes (SPS3)
Bibliographic record
Abstract
Introduction: Resistant hypertension (RHTN), a blood pressure (BP) ≥140/90 mm Hg despite ≥ 3 antihypertensive drugs or BP < 140/90 mm Hg using ≥ 4 drugs, is associated with increased incidence of adverse cardiovascular outcomes, especially stroke. Hypothesis and objective: We hypothesize common variants exist in the genes regulating BP response and may lead to RHTN in some patients. Methods: A discovery cohort of hypertensive participants were included as cases (as defined above) or controls (N=719; 263 whites, 322 Hispanics, and 134 African Americans) from SPS3-GENES. They were genotyped on the Illumina Omni 5 Exome chip. Multiple logistic regression analysis was conducted separately in each race using an additive genetic model, adjusting for predictors for RHTN, principle components for ancestry and BP target treatment arms. Results from the 3 racial groups were combined using meta-analysis with inverse-variance weighting, with the hypothesis that functional variants are consistent across races. The associations of seven SNPs that met the suggestive level of association (p <1 x10-5) in the SPS3 meta-analysis were tested for replication in 1,194 participants (657 whites, and 537 Hispanics) from the INternational VErapamil-SR trandolapril STudy GENEtic Substudy (INVEST-GENES). Bonferroni adjusted p was set at 0.007 to correct for multiple comparisons. Combined meta-analysis between INVEST and SPS3 was conducted for replicated SNPs or SNPs that had consistent association in the two cohorts with a nominal significance. Results: A missense SNP (rs3766160; Asp114Asn) in CELA2B was associated with increased risk of RHTN in SPS3 (Combined OR=1.8, p=6x10-6)). The same SNP replicated in INVEST (Combined OR=1.3, p=0.004; INVEST/SPS3 meta-p=4.5x10-7). An intronic SNP rs3789592 in strong linkage disequilibrium (r2=0.98) with a missense SNP (rs1049434; Asp490Glu) in SLC16A1 was associated with RHTN in SPS3 (Combined OR=2.0, p=7.6x10-7) and had a consistent association in INVEST (Combined OR=1.2, p=0.048; INVEST/SPS3 meta-p=7.6x10-7). Conclusion: Genetic loci in CELA2B, SLC16A1 were identified and confirmed for association in two cohorts. These associations, if further validated may help identify those patients at risk for RHTN.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".