Abstract
Purpose: The Mayo-Baylor RIGHT 10K Study enabled preemptive, sequence-based pharmacogenomics (PGx)-driven drug prescribing practices in routine clinical care within a large cohort. We also generated the tools and resources necessary for clinical PGx implementation and identified challenges that need to be overcome. Furthermore, we measured the frequency of both common genetic variation for which clinical guidelines already exist and rare variation that could be detected by DNA sequencing, rather than genotyping. Methods: Targeted oligonucleotide-capture sequencing of 77 pharmacogenes was performed using DNA from 10,077 consented Mayo Clinic Biobank volunteers. The resulting predicted drug response–related phenotypes for 13 genes, including CYP2D6 and HLA, affecting 21 drug–gene pairs, were deposited preemptively in the Mayo electronic health record. Results: For the 13 pharmacogenes of interest, the genomes of 79% of participants carried clinically actionable variants in 3 or more genes, and DNA sequencing identified an average of 3.3 additional conservatively predicted deleterious variants that would not have been evident using genotyping. Conclusion: Implementation of preemptive rather than reactive and sequence-based rather than genotype-based PGx prescribing revealed nearly universal patient applicability and required integrated institution-wide resources to fully realize individualized drug therapy and to show more efficient use of health care resources.
Original language | English (US) |
---|---|
Pages (from-to) | 1062-1072 |
Number of pages | 11 |
Journal | Genetics in Medicine |
Volume | 24 |
Issue number | 5 |
DOIs | |
State | Published - May 2022 |
Keywords
- Clinical translation
- Implementation
- Individualized medicine
- Pharmacogenomics
- Pre-emptive clinical DNA sequencing
ASJC Scopus subject areas
- Genetics(clinical)
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Implementation of preemptive DNA sequence–based pharmacogenomics testing across a large academic medical center : The Mayo-Baylor RIGHT 10K Study. / Wang, Liewei; Scherer, Steven E.; Bielinski, Suzette J. et al.
In: Genetics in Medicine, Vol. 24, No. 5, 05.2022, p. 1062-1072.Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - Implementation of preemptive DNA sequence–based pharmacogenomics testing across a large academic medical center
T2 - The Mayo-Baylor RIGHT 10K Study
AU - Wang, Liewei
AU - Scherer, Steven E.
AU - Bielinski, Suzette J.
AU - Muzny, Donna M.
AU - Jones, Leila A.
AU - Black, John Logan
AU - Moyer, Ann M.
AU - Giri, Jyothsna
AU - Sharp, Richard R.
AU - Matey, Eric T.
AU - Wright, Jessica A.
AU - Oyen, Lance J.
AU - Nicholson, Wayne T.
AU - Wiepert, Mathieu
AU - Sullard, Terri
AU - Curry, Timothy B.
AU - Rohrer Vitek, Carolyn R.
AU - McAllister, Tammy M.
AU - St. Sauver, Jennifer L.
AU - Caraballo, Pedro J.
AU - Lazaridis, Konstantinos N.
AU - Venner, Eric
AU - Qin, Xiang
AU - Hu, Jianhong
AU - Kovar, Christie L.
AU - Korchina, Viktoriya
AU - Walker, Kimberly
AU - Doddapaneni, Harsha Vardhan
AU - Wu, Tsung Jung
AU - Raj, Ritika
AU - Denson, Shawn
AU - Liu, Wen
AU - Chandanavelli, Gauthami
AU - Zhang, Lan
AU - Wang, Qiaoyan
AU - Kalra, Divya
AU - Karow, Mary Beth
AU - Harris, Kimberley J.
AU - Sicotte, Hugues
AU - Peterson, Sandra E.
AU - Barthel, Amy E.
AU - Moore, Brenda E.
AU - Skierka, Jennifer M.
AU - Kluge, Michelle L.
AU - Kotzer, Katrina E.
AU - Kloke, Karen
AU - Vander Pol, Jessica M.
AU - Marker, Heather
AU - Sutton, Joseph A.
AU - Kekic, Adrijana
AU - Ebenhoh, Ashley
AU - Bierle, Dennis M.
AU - Schuh, Michael J.
AU - Grilli, Christopher
AU - Erickson, Sara
AU - Umbreit, Audrey
AU - Ward, Leah
AU - Crosby, Sheena
AU - Nelson, Eric A.
AU - Levey, Sharon
AU - Elliott, Michelle
AU - Peters, Steve G.
AU - Pereira, Naveen
AU - Frye, Mark
AU - Shamoun, Fadi
AU - Goetz, Matthew P.
AU - Kullo, Iftikhar J.
AU - Wermers, Robert
AU - Anderson, Jan A.
AU - Formea, Christine M.
AU - El Melik, Razan M.
AU - Zeuli, John D.
AU - Herges, Joseph R.
AU - Krieger, Carrie A.
AU - Hoel, Robert W.
AU - Taraba, Jodi L.
AU - St. Thomas, Scott R.
AU - Absah, Imad
AU - Bernard, Matthew E.
AU - Fink, Stephanie R.
AU - Gossard, Andrea
AU - Grubbs, Pamela L.
AU - Jacobson, Therese M.
AU - Takahashi, Paul
AU - Zehe, Sharon C.
AU - Buckles, Susan
AU - Bumgardner, Michelle
AU - Gallagher, Colette
AU - Fee-Schroeder, Kelliann
AU - Nicholas, Nichole R.
AU - Powers, Melody L.
AU - Ragab, Ahmed K.
AU - Richardson, Darcy M.
AU - Stai, Anthony
AU - Wilson, Jaymi
AU - Pacyna, Joel E.
AU - Olson, Janet E.
AU - Sutton, Erica J.
AU - Beck, Annika T.
AU - Horrow, Caroline
AU - Kalari, Krishna R.
AU - Larson, Nicholas B.
AU - Liu, Hongfang
AU - Wang, Liwei
AU - Lopes, Guilherme S.
AU - Borah, Bijan J.
AU - Freimuth, Robert R.
AU - Zhu, Ye
AU - Jacobson, Debra J.
AU - Hathcock, Matthew A.
AU - Armasu, Sebastian M.
AU - McGree, Michaela E.
AU - Jiang, Ruoxiang
AU - Koep, Tyler H.
AU - Ross, Jason L.
AU - Hilden, Matthew G.
AU - Bosse, Kathleen
AU - Ramey, Bronwyn
AU - Searcy, Isabelle
AU - Boerwinkle, Eric
AU - Gibbs, Richard A.
AU - Weinshilboum, Richard M.
N1 - Funding Information: This work was supported by the Mayo Clinic Center for Individualized Medicine; the Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery; Mayo Clinic Pharmacy Services; the Augeo Foundation; the; Satter Foundation; Bernard E. and Edith B. Waterman; William G. Little; Roche Diagnostics Corporation; National Science Foundation 2041339; National Institutes of Health grants U19 GM61388 (The Pharmacogenomics Research Network), R01 GM28157, U01 HG005137, R01 GM125633, R01 AG034676 (The Rochester Epidemiology Project), and U01 HG06379 and U01 HG06379 Supplements (The Electronic Medical Record and Genomics [eMERGE] Network). The funders/sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or the decision to submit the manuscript for publication. We wish to thank Duan Liu (Mayo Clinic) for his assistance with the preparation of this manuscript, and Michele J. Swift (Mayo Clinic) for her administrative assistance. Compensation was not received for their contributions. Conceptualization: Lie.W. S.J.B. R.M.W. R.A.G. E.B. S.E.S; Data Curation: E.V. X.Q. J.M.V.P. C.M.F. A.S.; Formal Analysis: Lie.W. S.J.B. D.M.M. S.E.S. X.Q. K.W. T.-J.W. Q.W. D.K. J.L.BIII. A.M.M. M.B.K. K.J.H. H.S. S.E.P. J.E.O. K.R.K. N.B.L. H.L. Liw.W. G.S.L. B.J.B. R.R.F. Y.Z. D.J.J. M.A.H. S.M.A. M.E.M. R.J.; Funding Acquisition: R.M.W. R.A.G.; Investigation: S.J.B. R.M.W. D.M.M. S.E.S. J.L.BIII. A.M.M. T.B.C.; Methodology: Lie.W. S.J.B. M.W. J.L.S. R.M.W. E.B. D.M.M. S.E.S. E.V. X.Q. J.H. C.L.K. K.W. J.L.BIII. A.M.M. A.E.B. B.E.M. J.M.S. M.L.K. K.E.K. K.K. W.T.N. J.G. H.M. P.J.C. A.K. A.E. D.B. M.J.S. Ch.G. S.E. A.U. Le.W. S.C. E.A.N. S.L. M.E. S.G.P. N.P. M.F. F.S. M.P.G. I.J.K. K.N.L. R.W. J.A.A. E.T.M. J.A.W. C.M.F. R.M.E.M, J.D.Z. J.R.H. C.A.K. R.W.H. J.L.T. T.B.C. T.M.M. C.R.R.V. S.R.S.T, I.A. M.E.B. S.R.F. A.G. P.L.G. T.M.J. P.T. M.B. K.F.-S. N.R.N. A.K.R. D.M.R. J.W. R.R.S.; Project Administration: Lie.W. S.J.B. L.A.J. M.W. T.S. J.L.S. R.M.W. R.A.G. E.B. D.M.M. S.E.S. C.L.K. V.K. J.L.BIII. A.M.M. W.T.N. J.G. P.J.C. S.E. K.N.L. L.J.O. E.T.M. J.A.W. T.B.C. T.M.M. C.R.R.V. R.R.S.; Resources: S.J.B. H.D. R.R. S.D. W.L. G.C. L.Z. A.E.B. J.M.V.P. S.C.Z. S.B. Co.G. M.L.P. J.E.P. J.E.O. E.J.S. A.T.B. C.H.; Software: M.W. E.V. X.Q. K.W. T.-J.W. J.L.BIII. K.J.H. H.S. S.E.P. J.M.V.P. J.S. A.S. T.H.K. J.L.R. M.G.H. K.B. B.R. I.S.; Supervision: Lie.W. S.J.B. L.A.J. M.W. T.S. J.L.S. R.M.W. R.A.G. E.B. D.M.M. S.E.S. E.V. J.H. K.W. H.D. R.R. W.L. J.L.BIII. A.E.B. K.K. W.T.N. H.M. P.J.C. M.E. S.G.P. N.P. M.F. F.S. M.P.G. I.J.K. K.N.L. R.W. L.J.O. T.B.C. T.M.M. C.R.R.V. I.A. M.E.B. R.R.S. N.B.L.; Validation: D.M.M. S.E.S. E.V. X.Q. J.H. C.L.K. V.K. K.W. T.-J.W. R.R. S.D. W.L. G.C. L.Z. Q.W. D.K. J.L.BIII. M.B.K.; Writing-original draft: Lie.W. S.J.B. R.M.W. R.A.G. S.E.S. E.V. X.Q. J.H. V.K.; Writing-review and editing: Lie.W. S.E.S. S.J.B. D.M.M. L.A.J. J.L.BIII. A.M.M. J.G. R.R.S. E.T.M. J.A.W. L.J.O. W.T.N. M.W. T.S. T.B.C. C.R.R.V. T.M.M. J.L.S.S. P.J.C. K.N.L. E.V. X.Q. J.H. C.L.K. V.K. K.W. H.D. T.-J.W. R.R. S.D. W.L. G.C. L.Z. Q.W. D.K. M.B.K. K.J.H. H.S. S.E.P. A.E.B. B.E.M. J.M.S. M.L.K. K.E.K. K.K. J.M.V.P. H.M. J.A.S. A.K. A.E. D.M.B. M.J.S. Ch.G. S.E. A.U. Le.W. S.C. E.A.N. S.L. M.E. S.G.P. N.P. M.F. F.S. M.P.G. I.J.K. R.W. J.A.A. C.M.F. R.M.E.M. J.D.Z. J.R.H. C.A.K. R.W.H. J.L.T. S.R.S.T. I.A. M.E.B. S.R.F. A.G. P.L.G. T.M.J. P.T. S.C.Z. S.B. M.B. Co.G. K.F.-S. N.R.N. M.L.P. A.K.R. D.M.R. A.S. J.W. J.E.P. J.E.O. E.J.S. A.T.B. C.H. K.R.K. N.B.L. H.L. Liw. W. G.S.L. B.J.B. R.R.F. Y.Z. D.J.J. M.A.H. S.M.A. M.E.M. R.J. T.H.K. J.L.R. M.H. K.B. B.R. I.S. E.B. R.A.G. R.M.W. All participants in this study were recruited from the Mayo Clinic Biobank and informed consent was obtained under Mayo Clinic Institutional Review Board approval. Participants agreed to the use of their stored Biobank samples for clinical pharmacogenomic testing, deposit of pharmacogenomic results into their electronic health record for clinical use, and use of de-identified pharmacogenomic data for research. For more information on both the Biobank (https://www.mayo.edu/research/centers-programs/mayo-clinic-biobank/about/governance-oversight) and the RIGHT cohort, please see Bielinski et al.15 Funding Information: This work was supported by the Mayo Clinic Center for Individualized Medicine; the Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery; Mayo Clinic Pharmacy Services; the Augeo Foundation; the; Satter Foundation; Bernard E. and Edith B. Waterman; William G. Little; Roche Diagnostics Corporation; National Science Foundation 2041339; National Institutes of Health grants U19 GM61388 ( The Pharmacogenomics Research Network ), R01 GM28157 , U01 HG005137 , R01 GM125633 , R01 AG034676 ( The Rochester Epidemiology Project ), and U01 HG06379 and U01 HG06379 Supplements ( The Electronic Medical Record and Genomics [eMERGE] Network). Publisher Copyright: © 2022 American College of Medical Genetics and Genomics
PY - 2022/5
Y1 - 2022/5
N2 - Purpose: The Mayo-Baylor RIGHT 10K Study enabled preemptive, sequence-based pharmacogenomics (PGx)-driven drug prescribing practices in routine clinical care within a large cohort. We also generated the tools and resources necessary for clinical PGx implementation and identified challenges that need to be overcome. Furthermore, we measured the frequency of both common genetic variation for which clinical guidelines already exist and rare variation that could be detected by DNA sequencing, rather than genotyping. Methods: Targeted oligonucleotide-capture sequencing of 77 pharmacogenes was performed using DNA from 10,077 consented Mayo Clinic Biobank volunteers. The resulting predicted drug response–related phenotypes for 13 genes, including CYP2D6 and HLA, affecting 21 drug–gene pairs, were deposited preemptively in the Mayo electronic health record. Results: For the 13 pharmacogenes of interest, the genomes of 79% of participants carried clinically actionable variants in 3 or more genes, and DNA sequencing identified an average of 3.3 additional conservatively predicted deleterious variants that would not have been evident using genotyping. Conclusion: Implementation of preemptive rather than reactive and sequence-based rather than genotype-based PGx prescribing revealed nearly universal patient applicability and required integrated institution-wide resources to fully realize individualized drug therapy and to show more efficient use of health care resources.
AB - Purpose: The Mayo-Baylor RIGHT 10K Study enabled preemptive, sequence-based pharmacogenomics (PGx)-driven drug prescribing practices in routine clinical care within a large cohort. We also generated the tools and resources necessary for clinical PGx implementation and identified challenges that need to be overcome. Furthermore, we measured the frequency of both common genetic variation for which clinical guidelines already exist and rare variation that could be detected by DNA sequencing, rather than genotyping. Methods: Targeted oligonucleotide-capture sequencing of 77 pharmacogenes was performed using DNA from 10,077 consented Mayo Clinic Biobank volunteers. The resulting predicted drug response–related phenotypes for 13 genes, including CYP2D6 and HLA, affecting 21 drug–gene pairs, were deposited preemptively in the Mayo electronic health record. Results: For the 13 pharmacogenes of interest, the genomes of 79% of participants carried clinically actionable variants in 3 or more genes, and DNA sequencing identified an average of 3.3 additional conservatively predicted deleterious variants that would not have been evident using genotyping. Conclusion: Implementation of preemptive rather than reactive and sequence-based rather than genotype-based PGx prescribing revealed nearly universal patient applicability and required integrated institution-wide resources to fully realize individualized drug therapy and to show more efficient use of health care resources.
KW - Clinical translation
KW - Implementation
KW - Individualized medicine
KW - Pharmacogenomics
KW - Pre-emptive clinical DNA sequencing
UR - http://www.scopus.com/inward/record.url?scp=85127847512&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85127847512&partnerID=8YFLogxK
U2 - 10.1016/j.gim.2022.01.022
DO - 10.1016/j.gim.2022.01.022
M3 - Article
C2 - 35331649
AN - SCOPUS:85127847512
VL - 24
SP - 1062
EP - 1072
JO - Genetics in Medicine
JF - Genetics in Medicine
SN - 1098-3600
IS - 5
ER -