Abstract 4346945: Pharmacogenomic Profiling Improves Blood Pressure Control in Resistant Hypertension: A Precision Medicine Approach

Background: Resistant hypertension affects approximately 10-20% of hypertensive patients. Emerging evidence suggests genetic variation significantly influences antihypertensive drug response, providing a compelling rationale for pharmacogenomic-guided therapy. Research Question: Does pharmacogenomic testing lead to clinically meaningful improvements in blood pressure control, medication management, and adverse effect profiles in resistant hypertension? Methods: This systematic review synthesizes evidence on pharmacogenomic markers associated with antihypertensive drug response in resistant hypertension. We conducted a comprehensive search of PubMed and PharmGKB for studies published between Jan 2015 to Mar 2025. Two independent reviewers screened 412 articles, with 87 meeting inclusion criteria. Meta-analysis was performed for genetic variants reported in ≥3 studies with comparable outcome measures. Results: CYP2D6 variants (*4, *10) significantly affect metoprolol metabolism (p<0.001), with poor metabolizers experiencing a 2.3-fold increased risk of bradycardia and hypotension (95% CI: 1.7-3.1). ABCB1 C3435T polymorphism impacts verapamil efficacy, with T allele carriers showing a mean 8.4 mmHg greater systolic BP reduction compared to wild-type carriers (p=0.003). NPPA T2238C and NPPB rs198358 variants predict response to aldosterone antagonists with an area under the curve of 0.76 (95% CI: 0.68-0.84). CYP11B2 -344C>T variants demonstrated strong associations with spironolactone efficacy (odds ratio: 2.1; 95% CI: 1.4-3.2). A panel of 12 SNPs in genes including YEATS4, SLC12A3, and WNK1 demonstrated 78% predictive accuracy for thiazide diuretic response in black patients with resistant hypertension. Meta-analysis of implementation studies (n=891 patients across 5 studies) indicates a 17.3% improvement in blood pressure control (95% CI: 12.8-21.9%, p<0.001) compared to standard care, with a 32% reduction in medication changes (p=0.002) and 26% decrease in reported adverse effects (p=0.005). Conclusions: Pharmacogenomics offers a promising strategy to overcome treatment resistance in hypertension by enabling personalized medication selection based on individual genetic profiles. Implementation of pharmacogenomic testing could improve blood pressure control rates, reduce adverse effects, and decrease polypharmacy burden in resistant hypertension. Future prospective studies are needed to validate comprehensive multi-gene panels specific to resistant hypertension.