Effect of plasma MicroRNA on antihypertensive response to beta blockers in the Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR) studies
β-blockers show variable efficacy as antihypertensives. Herein, we evaluated plasma miRNAs as biomarkers for defining antihypertensive response to β-blockers. Expression of 22 β-blocker pharmacodynamics-related miRNAs was assessed in baseline plasma samples from 30 responders and 30 non-responders t...
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| Published in | European journal of pharmaceutical sciences Vol. 131; pp. 93 - 98 |
|---|---|
| Main Authors | , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Netherlands
Elsevier B.V
01.04.2019
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0928-0987 1879-0720 1879-0720 |
| DOI | 10.1016/j.ejps.2019.02.013 |
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| Abstract | β-blockers show variable efficacy as antihypertensives. Herein, we evaluated plasma miRNAs as biomarkers for defining antihypertensive response to β-blockers. Expression of 22 β-blocker pharmacodynamics-related miRNAs was assessed in baseline plasma samples from 30 responders and 30 non-responders to metoprolol from the PEAR-2 study (Discovery). Logistic regression was performed to identify miRNAs significantly associated with metoprolol response. Those miRNAs were profiled in baseline plasma samples from 25 responders and 25 non-responders to atenolol from the PEAR study (validation). In discovery, miR-101, miR-27a, miR-22, miR-19a, and let-7e were significantly associated with metoprolol response (P = 0.01, 0.017, 0.025, 0.025, and 0.04, respectively). In validation, miR-19a was significantly associated with atenolol response (P = 0.038). Meta-analysis between PEAR-2 and PEAR revealed significant association between miR-19a (P = 0.004), miR-101 (P = 0.006), and let-7e (P = 0.012) and β-blocker response. Hence, miR-19a, miR-101, and let-7e, which regulate β1-adrenergic receptor and other β-blocker pharmacodynamics-related genes, may be biomarkers for antihypertensive response to β-blockers.
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| AbstractList | β-blockers show variable efficacy as antihypertensives. Herein, we evaluated plasma miRNAs as biomarkers for defining antihypertensive response to β-blockers. Expression of 22 β-blocker pharmacodynamics-related miRNAs was assessed in baseline plasma samples from 30 responders and 30 non-responders to metoprolol from the PEAR-2 study (Discovery). Logistic regression was performed to identify miRNAs significantly associated with metoprolol response. Those miRNAs were profiled in baseline plasma samples from 25 responders and 25 non-responders to atenolol from the PEAR study (validation). In discovery, miR-101, miR-27a, miR-22, miR-19a, and let-7e were significantly associated with metoprolol response (P = 0.01, 0.017, 0.025, 0.025, and 0.04, respectively). In validation, miR-19a was significantly associated with atenolol response (P = 0.038). Meta-analysis between PEAR-2 and PEAR revealed significant association between miR-19a (P = 0.004), miR-101 (P = 0.006), and let-7e (P = 0.012) and β-blocker response. Hence, miR-19a, miR-101, and let-7e, which regulate β1-adrenergic receptor and other β-blocker pharmacodynamics-related genes, may be biomarkers for antihypertensive response to β-blockers.
[Display omitted] β-blockers show variable efficacy as antihypertensives. Herein, we evaluated plasma miRNAs as biomarkers for defining antihypertensive response to β-blockers. Expression of 22 β-blocker pharmacodynamics-related miRNAs was assessed in baseline plasma samples from 30 responders and 30 non-responders to metoprolol from the PEAR-2 study (Discovery). Logistic regression was performed to identify miRNAs significantly associated with metoprolol response. Those miRNAs were profiled in baseline plasma samples from 25 responders and 25 non-responders to atenolol from the PEAR study (validation). In discovery, miR-101, miR-27a, miR-22, miR-19a, and let-7e were significantly associated with metoprolol response (P = 0.01, 0.017, 0.025, 0.025, and 0.04, respectively). In validation, miR-19a was significantly associated with atenolol response (P = 0.038). Met-aanalysis between PEAR-2 and PEAR revealed significant association between miR-19a (P = 0.004), miR-101 (P = 0.006), and let-7e (P = 0.012) and β-blocker response. Hence, miR-19a, miR-101, and let-7e, which regulate β1-adrenergic receptor and other β-blocker pharmacodynamics-related genes, may be biomarkers for antihypertensive response to β-blockers. β-blockers show variable efficacy as antihypertensives. Herein, we evaluated plasma miRNAs as biomarkers for defining antihypertensive response to β-blockers. Expression of 22 β-blocker pharmacodynamics-related miRNAs was assessed in baseline plasma samples from 30 responders and 30 non-responders to metoprolol from the PEAR-2 study (Discovery). Logistic regression was performed to identify miRNAs significantly associated with metoprolol response. Those miRNAs were profiled in baseline plasma samples from 25 responders and 25 non-responders to atenolol from the PEAR study (validation). In discovery, miR-101, miR-27a, miR-22, miR-19a, and let-7e were significantly associated with metoprolol response (P = 0.01, 0.017, 0.025, 0.025, and 0.04, respectively). In validation, miR-19a was significantly associated with atenolol response (P = 0.038). Meta-analysis between PEAR-2 and PEAR revealed significant association between miR-19a (P = 0.004), miR-101 (P = 0.006), and let-7e (P = 0.012) and β-blocker response. Hence, miR-19a, miR-101, and let-7e, which regulate β1-adrenergic receptor and other β-blocker pharmacodynamics-related genes, may be biomarkers for antihypertensive response to β-blockers.β-blockers show variable efficacy as antihypertensives. Herein, we evaluated plasma miRNAs as biomarkers for defining antihypertensive response to β-blockers. Expression of 22 β-blocker pharmacodynamics-related miRNAs was assessed in baseline plasma samples from 30 responders and 30 non-responders to metoprolol from the PEAR-2 study (Discovery). Logistic regression was performed to identify miRNAs significantly associated with metoprolol response. Those miRNAs were profiled in baseline plasma samples from 25 responders and 25 non-responders to atenolol from the PEAR study (validation). In discovery, miR-101, miR-27a, miR-22, miR-19a, and let-7e were significantly associated with metoprolol response (P = 0.01, 0.017, 0.025, 0.025, and 0.04, respectively). In validation, miR-19a was significantly associated with atenolol response (P = 0.038). Meta-analysis between PEAR-2 and PEAR revealed significant association between miR-19a (P = 0.004), miR-101 (P = 0.006), and let-7e (P = 0.012) and β-blocker response. Hence, miR-19a, miR-101, and let-7e, which regulate β1-adrenergic receptor and other β-blocker pharmacodynamics-related genes, may be biomarkers for antihypertensive response to β-blockers. β-blockers show variable efficacy as antihypertensives. Herein, we evaluated plasma miRNAs as biomarkers for defining antihypertensive response to β-blockers. Expression of 22 β-blocker pharmacodynamics-related miRNAs was assessed in baseline plasma samples from 30 responders and 30 non-responders to metoprolol from the PEAR-2 study (Discovery). Logistic regression was performed to identify miRNAs significantly associated with metoprolol response. Those miRNAs were profiled in baseline plasma samples from 25 responders and 25 non-responders to atenolol from the PEAR study (validation). In discovery, miR-101, miR-27a, miR-22, miR-19a, and let-7e were significantly associated with metoprolol response (P = 0.01, 0.017, 0.025, 0.025, and 0.04, respectively). In validation, miR-19a was significantly associated with atenolol response (P = 0.038). Meta-analysis between PEAR-2 and PEAR revealed significant association between miR-19a (P = 0.004), miR-101 (P = 0.006), and let-7e (P = 0.012) and β-blocker response. Hence, miR-19a, miR-101, and let-7e, which regulate β1-adrenergic receptor and other β-blocker pharmacodynamics-related genes, may be biomarkers for antihypertensive response to β-blockers. |
| Author | Turner, Stephen T. Johnson, Julie A. Gums, John G. Chapman, Arlene B. El-Wakeel, Lamia El-Hamamsy, Manal Solayman, Mohamed H. Cooper-DeHoff, Rhonda M. Boerwinkle, Eric Langaee, Taimour Y. Badary, Osama A. Gong, Yan Shahin, Mohamed H. Beitelshees, Amber L. |
| AuthorAffiliation | f Human Genetics Center and Institute of Molecular Medicine, University of Texas Health Science Center, Houston, TX, USA a Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL, USA d Department of Medicine, The University of Chicago, Chicago, IL, USA e Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA g Division of Endocrinology, Diabetes and Nutrition, School of Medicine, University of Maryland Baltimore, MD, USA c Division of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic College of Medicine, Rochester, MN, USA b Department of Clinical Pharmacy, Faculty of Pharmacy, Ain Shams University, Cairo, Egypt |
| AuthorAffiliation_xml | – name: g Division of Endocrinology, Diabetes and Nutrition, School of Medicine, University of Maryland Baltimore, MD, USA – name: e Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA – name: a Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL, USA – name: b Department of Clinical Pharmacy, Faculty of Pharmacy, Ain Shams University, Cairo, Egypt – name: d Department of Medicine, The University of Chicago, Chicago, IL, USA – name: c Division of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic College of Medicine, Rochester, MN, USA – name: f Human Genetics Center and Institute of Molecular Medicine, University of Texas Health Science Center, Houston, TX, USA |
| Author_xml | – sequence: 1 givenname: Mohamed H. surname: Solayman fullname: Solayman, Mohamed H. organization: Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL, USA – sequence: 2 givenname: Taimour Y. surname: Langaee fullname: Langaee, Taimour Y. organization: Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL, USA – sequence: 3 givenname: Yan surname: Gong fullname: Gong, Yan organization: Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL, USA – sequence: 4 givenname: Mohamed H. surname: Shahin fullname: Shahin, Mohamed H. organization: Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL, USA – sequence: 5 givenname: Stephen T. surname: Turner fullname: Turner, Stephen T. organization: Division of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic College of Medicine, Rochester, MN, USA – sequence: 6 givenname: Arlene B. surname: Chapman fullname: Chapman, Arlene B. organization: Department of Medicine, The University of Chicago, Chicago, IL, USA – sequence: 7 givenname: John G. surname: Gums fullname: Gums, John G. organization: Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA – sequence: 8 givenname: Eric surname: Boerwinkle fullname: Boerwinkle, Eric organization: Human Genetics Center and Institute of Molecular Medicine, University of Texas Health Science Center, Houston, TX, USA – sequence: 9 givenname: Amber L. surname: Beitelshees fullname: Beitelshees, Amber L. organization: Division of Endocrinology, Diabetes and Nutrition, School of Medicine, University of Maryland Baltimore, MD, USA – sequence: 10 givenname: Manal surname: El-Hamamsy fullname: El-Hamamsy, Manal organization: Department of Clinical Pharmacy, Faculty of Pharmacy, Ain Shams University, Cairo, Egypt – sequence: 11 givenname: Lamia surname: El-Wakeel fullname: El-Wakeel, Lamia organization: Department of Clinical Pharmacy, Faculty of Pharmacy, Ain Shams University, Cairo, Egypt – sequence: 12 givenname: Rhonda M. surname: Cooper-DeHoff fullname: Cooper-DeHoff, Rhonda M. organization: Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL, USA – sequence: 13 givenname: Osama A. surname: Badary fullname: Badary, Osama A. organization: Department of Clinical Pharmacy, Faculty of Pharmacy, Ain Shams University, Cairo, Egypt – sequence: 14 givenname: Julie A. surname: Johnson fullname: Johnson, Julie A. email: johnson@cop.ufl.edu organization: Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL, USA |
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| Keywords | Antihypertensive response Hypertension microRNA Biomarker Beta-blocker |
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| SubjectTerms | Adrenergic beta-Antagonists - pharmacology Adult Antihypertensive Agents - pharmacology Antihypertensive response Atenolol - pharmacology Beta-blocker Biomarker Female Humans Hypertension Hypertension - blood Hypertension - genetics Male Metoprolol - pharmacology microRNA MicroRNAs - blood Middle Aged |
| Title | Effect of plasma MicroRNA on antihypertensive response to beta blockers in the Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR) studies |
| URI | https://dx.doi.org/10.1016/j.ejps.2019.02.013 https://www.ncbi.nlm.nih.gov/pubmed/30753892 https://www.proquest.com/docview/2183181805 https://pubmed.ncbi.nlm.nih.gov/PMC6467266 |
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