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Genome-wide association analysis of common genetic variants of resistant hypertension

The Pharmacogenomics Journal volume 19, pages 295–304 (2019)Cite this article

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Abstract

Resistant hypertension (RHTN), defined as uncontrolled blood pressure (BP) ≥ 140/90 using three or more drugs or controlled BP (<140/90) using four or more drugs, is associated with adverse outcomes, including decline in kidney function. We conducted a genome-wide association analysis in 1194 White and Hispanic participants with hypertension and coronary artery disease from the INternational VErapamil-SR Trandolapril STudy—GENEtic Substudy (INVEST-GENES). Top variants associated with RHTN at p < 10−4 were tested for replication in 585 White and Hispanic participants with hypertension and subcortical strokes from the Secondary Prevention of Subcortical Strokes GENEtic Substudy (SPS3-GENES). A genetic risk score for RHTN was created by summing the risk alleles of replicated RHTN signals. rs11749255 in MSX2 was associated with RHTN in INVEST (odds ratio (OR) (95% CI) = 1.50 (1.2–1.8), p = 7.3 × 10−5) and replicated in SPS3 (OR = 2.0 (1.4–2.8), p = 4.3 × 10−5), with genome-wide significance in meta-analysis (OR = 1.60 (1.3–1.9), p = 3.8 × 10−8). Other replicated signals were in IFLTD1 and PTPRD. IFLTD1 rs6487504 was associated with RHTN in INVEST (OR = 1.90 (1.4–2.5), p = 1.1 × 10−5) and SPS3 (OR = 1.70 (1.2–2.5), p = 4 × 10−3). PTPRD rs324498, a previously reported RHTN signal, was among the top signals in INVEST (OR = 1.60 (1.3–2.0), p = 3.4 × 10−5) and replicated in SPS3 (OR = 1.60 (1.1–2.4), one-sided p = 0.005). Participants with the highest number of risk alleles were at increased risk of RHTN compared to participants with a lower number (p-trend = 1.8 × 10−15). Overall, we identified and replicated associations with RHTN in the MSX2, IFLTD1, and PTPRD regions, and combined these associations to create a genetic risk score.

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Funding

INVEST was supported by grants from the University of Florida Opportunity Fund and Abbott Pharmaceuticals. INVEST-GENES was supported by NIH grants U01-GM074492, NIH R01 HL074730. The SPS3 trial was funded by the National Institute of Health and Neurological Disorders and Stroke Grant No. U01NS38529-04A1. The SPS3-GENES was funded by R01 NS073346 and U01-GM074492-05S109. Dr. El Rouby is supported by NIH grant T32HL083810 and Dr. McDonough is supported by NIH Grant 1 KL2 TR001429. The eMERGE Network is funded by NHGRI, with additional funding from NIGMS through the following grants: U01HG04599 and U01HG006379 to Mayo Clinic; U01HG004610 and U01HG006375 to Group Health Cooperative and University of Washington, Seattle; U01HG004608 to Marshfield Clinic; U01HG006389 to Essentia Institute of Rural Health; U01HG004609 and U01HG006388 to Northwestern University; U01HG04603 and U01HG006378 to Vanderbilt University; U01HG006385 to the Coordinating Center; U01HG006382 to Geisinger Clinic; U01HG006380 to Mount Sinai School of Medicine. A portion of the dataset(s) used for the analyses described were obtained from Vanderbilt University Medical Center’s BioVU, supported by institutional funding and by the Vanderbilt CTSA grant UL1 TR000445 from NCATS/NIH, and the Mayo Clinic Biobank supported by the Mayo Clinic Center for Individualized Medicine.

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Authors and Affiliations

  1. Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL, USA

    Nihal El Rouby, Caitrin W. McDonough, Yan Gong, Rhonda M. Cooper-DeHoff & Julie A. Johnson

  2. Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA

    Leslie A. McClure

  3. Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA

    Braxton D. Mitchell, Richard B. Horenstein & Alan R. Shuldiner

  4. Geriatric Research and Education Clinical Center, Veterans Administration Medical Center, Baltimore, MD, USA

    Braxton D. Mitchell & Alan R. Shuldiner

  5. Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA

    Richard B. Horenstein & Alan R. Shuldiner

  6. College of Pharmacy, University of Texas at Austin, Austin, TX, USA

    Robert L. Talbert

  7. Epidemiology and Biostatistics, Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA

    Dana C. Crawford

  8. Department of Biology, University of Florida, Gainesville, FL, USA

    Matthew A. Gitzendanner

  9. RIKEN Center for Integrative Medical Sciences, Yokohama, Japan

    Atsushi Takahashi, Toshihiro Tanaka & Michiaki Kubo

  10. Division of Cardiovascular Medicine, Department of Medicine, University of Florida, Gainesville, FL, USA

    Carl J. Pepine, Rhonda M. Cooper-DeHoff & Julie A. Johnson

  11. Department of Neurology, University of British Columbia, Vancouver, BC, Canada

    Oscar R. Benavente

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  1. Nihal El Rouby
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Correspondence to Julie A. Johnson.

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Dr. Shuldiner is employed by Regeneron Pharmaceuticals, Inc. The remaining authors declare that they have no conflict of interest.

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El Rouby, N., McDonough, C.W., Gong, Y. et al. Genome-wide association analysis of common genetic variants of resistant hypertension. Pharmacogenomics J 19, 295–304 (2019). https://doi.org/10.1038/s41397-018-0049-x

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