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American Heart Association

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Final ID: 075

Blood pressure polygenic score predicts long-term blood pressure control and treatment-resistant hypertension

Abstract Body: Introduction Suboptimal blood pressure (BP) control remains a major cardiovascular disease risk factor globally. Whether genetic contributors to elevated BP independently predict long-term BP control and treatment-resistant hypertension is unknown.

Objectives We examined the associations of BP polygenic score (PGS) with long-term BP control and treatment-resistant hypertension among patients with hypertension.

Methods Using Mass General Brigham Biobank nested within the U.S. healthcare system, we identified 22,466 individuals aged 18-64 years with established hypertension between January 2018 and May 2019. Multiancestral BP PGS was fine-tuned using the external UK Biobank cohort. Longitudinal BP control was defined as cumulative duration above target systolic BP (SBP) ≥130 mmHg or diastolic BP (DBP) ≥80 mmHg in percentage over a 5-year follow-up. Treatment-resistant hypertension was defined as SBP ≥140 or DBP ≥90 mmHg despite the concurrent use of 3 antihypertensive classes, use of ≥4 antihypertensive classes at any BP level, or physician adjudication. Using multivariable regression, we assessed the associations of BP PRS with 5-year BP control and lifetime resistant hypertension incidence adjusting for traditional cardiometabolic risk factors and comorbidities. Incremental prognostic utility of BP PRS was assessed based on improvement in discrimination C-index or the likelihood ratio test.

Results The mean SBP/DBP (standard deviation) at index date was 132(18) / 75(11) mmHg, and 4126 (18.4%) developed resistant hypertension over a lifetime. In reference to the low (<20th percentile) PGS group, the high (≥80th percentile) genetic risk group was associated with 8.01 [6.68-9.34]% longer duration lived with above-target SBP and 6.19 [5.05-7.33]% longer with high DBP. In parallel, the high SBP genetic risk group had a 2.36 [2.07-2.68]-folds higher odds of developing treatment-resistant hypertension. Adding BP PGSs to traditional risk factors improved discrimination C-index [95% CI] for predicting resistant hypertension from 0.74 [0.73-0.75] to 0.78 [0.77-0.79] (P <0.001). BP PGS consistently predicted longitudinal BP management in the validation population-based UK Biobank cohort in adherence to the UK clinical guideline.
Conclusions BP PGS predicts long-term BP control and treatment-resistant hypertension. Harnessing BP PGS may inform anticipated trends in long-term BP control to better enable optimal hypertension management.
  • Cho, So Mi  ( Massachusetts General Hospital , Boston , Massachusetts , United States )
  • Honigberg, Michael  ( Massachusetts General Hospital , Boston , Massachusetts , United States )
  • Fahed, Akl  ( Massachusetts General Hospital , Boston , Massachusetts , United States )
  • Patel, Aniruddh  ( Massachusetts General Hospital , Boston , Massachusetts , United States )
  • Hornsby, Whitney  ( Massachusetts General Hospital , Boston , Massachusetts , United States )
  • Natarajan, Pradeep  ( Massachusetts General Hospital , Boston , Massachusetts , United States )
  • Ruan, Yunfeng  ( Massachusetts General Hospital , Boston , Massachusetts , United States )
  • Lee, Hyeok-hee  ( Beth Israel Deaconess Medical Center , Boston , Massachusetts , United States )
  • Koyama, Satoshi  ( Massachusetts General Hospital , Boston , Massachusetts , United States )
  • Juraschek, Stephen  ( Beth Israel Deaconess Medical Center , Boston , Massachusetts , United States )
  • Allen, Norrina  ( NORTHWESTERN UNIVERSITY , Chicago , Illinois , United States )
  • Yang, Eugene  ( University of Washington , Seattle , Washington , United States )
  • Mcevoy, John  ( University of Galway , Galway , Ireland )
  • Secemsky, Eric  ( Beth Israel Deaconess Medical Center , Boston , Massachusetts , United States )
  • Author Disclosures:
    So Mi Cho: DO NOT have relevant financial relationships | Michael Honigberg: DO have relevant financial relationships ; Research Funding (PI or named investigator):Genentech:Active (exists now) ; Advisor:Miga Health:Past (completed) ; Consultant:Comanche Biopharma:Past (completed) ; Research Funding (PI or named investigator):Novartis:Active (exists now) | Akl Fahed: No Answer | Aniruddh Patel: No Answer | Whitney Hornsby: No Answer | Pradeep Natarajan: DO have relevant financial relationships ; Researcher:Allelica:Past (completed) ; Ownership Interest:TenSixteen Bio:Active (exists now) ; Ownership Interest:Candela:Active (exists now) ; Consultant:BMS:Past (completed) ; Ownership Interest:MyOme:Active (exists now) ; Ownership Interest:Parameter Health:Active (exists now) ; Consultant:Foresite Capital:Active (exists now) ; Consultant:Foresite Labs:Active (exists now) ; Consultant:Tourmaline Bio:Active (exists now) ; Consultant:TenSixteen Bio:Past (completed) ; Consultant:Eli Lilly & Co:Past (completed) ; Consultant:Novo Nordisk:Past (completed) ; Consultant:Genentech:Past (completed) ; Consultant:Allelica:Past (completed) ; Researcher:Genentech:Active (exists now) | Yunfeng Ruan: No Answer | Hyeok-Hee Lee: DO NOT have relevant financial relationships | Satoshi Koyama: No Answer | Stephen Juraschek: DO NOT have relevant financial relationships | Norrina Allen: No Answer | Eugene Yang: DO have relevant financial relationships ; Advisor:SkyLabs:Active (exists now) ; Advisor:Qure.ai:Past (completed) ; Advisor:Mineralys:Past (completed) ; Advisor:Idorsia:Past (completed) | John McEvoy: No Answer | Eric Secemsky: No Answer
Meeting Info:
Session Info:

Concurrent A: Genetics, Proteomics, and Metabolomics

Saturday, 09/06/2025 , 01:30PM - 03:00PM

Oral Abstract Session

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