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Sadée, Wolfgang

0000-0003-1894-6374

Mayo Clinic

The Ohio State University

Citations 3

Abstract 13621: Integrating Metabolomics and Genomics Uncovers Novel Pathways and Genetic Signatures Influencing Hydrochlorothiazide Blood Pressure Response: A Genetic Response Score for Hydrochlorothiazide Use
Shahin, Mohamed H. , Gong, Yan , Beitelshees, Amber L. , Chapman, Arlene B. , Boerwinkle, Eric , Scherer, Steven E. , Rotroff, Daniel M. , Webb, Amy , Langaee, Taimour , McDonough, Caitrin W. , Garrett, Timothy J. , Gums, John G. , Motsinger‐Reif, Alison A. , Chapman, Arlene B. , Turner, Stephen T. , Frye, Reginald F. , Sadée, Wolfgang , Fiehn, Oliver , Cooper‐DeHoff, Rhonda M. , Kaddurah‐Daouk, Rima , Johnson, Julie A.

Circulation | April 23, 2024 | Volume: 132 | Issue: suppl_3 | Pages: No page available

10.1161/circ.132.suppl_3.13621 Get It

Introduction: Hydrochlorothiazide (HCTZ) is among the most commonly prescribed antihypertensives in the US, yet <50% of HCTZ treated patients achieve blood pressure (BP) control. Hypothesis: Integrating metabolomic and genomic profiles of HCTZ treated patients could identify novel pathways/biomarkers for optimizing the use of HCTZ. Methods: Primary analysis included 228 white hypertensives treated with HCTZ from the Pharmacogenomic Evaluation of Antihypertensive Response (PEAR) study. Genotyping was determined via Illumina Omni 1M-Quad Chip and untargeted metabolomics was performed on baseline fasting plasma samples using a GC-TOF MS platform. Pathway analysis was used to integrate metabolites significantly associated with HCTZ BP response (FDR<.05) and genetic signals at p<5x10-5 from HCTZ BP genome-wide analysis. Replication was conducted in another 212 white HCTZ treated patients. Replicated genetic signals were used to create a BP response score by summing their BP lowering alleles. We validated this score by testing it in 196 white HCTZ treated patients in the Genetic Epidemiology of Responses to Antihypertensives (GERA) study. Results: Thirteen metabolites were significantly associated with HCTZ systolic BP (SBP) and diastolic BP (DBP) responses (FDR<.05). Metabolomics-genomics integration revealed significant metabolites along with rs2727563 PRKAG2, rs12604940 DCC, and rs13262930 EPHX2, in the netrin signalling pathway (p=1x10-5), as potential markers significantly influencing HCTZ BP response. We successfully replicated those 3 genetic signals and added their alleles to create a response score which explained 11.3% and 11.9% of the variability to HCTZ SBP and DBP responses, respectively. We found that patients carrying one “response” allele had a significantly worse response than carriers of six alleles (ΔSBP/ΔDBP: -1.5/1.2 vs -16.3/-10.4 mmHg, respectively, SBP score p=1x10-8 and DBP score p=3x10-9). We further validated this response score by testing it in the GERA (DBP score p=0.03, SBP score p=0.07). Conclusion: This study highlights the power of using different omics to identify novel pathways/biomarkers of drug response, and suggests that PRKAG2, DCC and EPHX2 might be important determinants of HCTZ BP response.
The Pharmacogenomics Research Network Translational Pharmacogenetics Program: Outcomes and Metrics of Pharmacogenetic Implementations Across Diverse Healthcare Systems
Luzum, Jasmine A. , Pakyz, R E, Elsey, AR, Haidar, Cyrine E. , Peterson, JF, Whirl‐Carrillo, Michelle , Handelman, SK, Palmer, Kathleen , Pulley, JM, Beller, Michael, Schildcrout, JS, Field, JR, Weitzel, KW, Cooper‐DeHoff, RM, Cavallari, Larisa H. , O'Donnell, PH, Altman, Russ B. , Pereira, Naveen L. , Ratain, MJ, Roden, DM, Embi, PJ, Klein, Teri E. , Johnson, JA, Relling, MV, Wang, L, Weinshilboum, RM, Freimuth, Robert R. , Johnson, Julie A. , Peterson, Josh F. , Schildcrout, Jonathan S. , Elsey, Amanda R., Peterson, JF, Weitzel, KW, Cooper-DeHoff, RM, Ratain, Mark J. , Roden, DM, Sadée, Wolfgang , Relling, Mary V. , Shuldiner, Alan R. , Schildcrout, Jonathan S , Whirl-Carrillo, Michelle , Freimuth, Robert R , Peterson, Josh F , Cavallari, Larisa H , Luzum, Jasmine A , Klein, Teri E

Clinical Pharmacology & Therapeutics | January 16, 2017 | Volume: 102 | Issue: 3 | Pages: 502-510

10.1002/cpt.630 Get It

Numerous pharmacogenetic clinical guidelines and recommendations have been published, but barriers have hindered the clinical implementation of pharmacogenetics. The Translational Pharmacogenetics Program (TPP) of the National Institutes of Health (NIH) Pharmacogenomics Research Network was established in 2011 to catalog and contribute to the development of pharmacogenetic implementations at eight US healthcare systems, with the goal to disseminate real‐world solutions for the barriers to clinical pharmacogenetic implementation. The TPP collected and normalized pharmacogenetic implementation metrics through June 2015, including gene–drug pairs implemented, interpretations of alleles and diplotypes, numbers of tests performed and actionable results, and workflow diagrams. TPP participant institutions developed diverse solutions to overcome many barriers, but the use of Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines provided some consistency among the institutions. The TPP also collected some pharmacogenetic implementation outcomes (scientific, educational, financial, and informatics), which may inform healthcare systems seeking to implement their own pharmacogenetic testing programs.
Conference Scene: Lessons Learned from the 5th Statistical Analysis Workshop of the Pharmacogenetics Research Network
Atkinson, Elizabeth J. , McDonnell, Shannon K. , Witte, John S. , Crawford, Dana C. , Fan, Yiping , Li, Lang , Rodin, Andréi S. , Speed, Terry, Yerges, Laura, Schaid, Daniel J. , Fridley, Brooke L. , Li, Dalin , Sadée, Wolfgang , Speed, Terry, Weiss, Scott T. , Yang, Jun J.J. , McDonnell, Shannon K

Pharmacogenomics | March 17, 2010 | Volume: 11 | Issue: 3 | Pages: 297-303

10.2217/pgs.10.5 Get It