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Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network

Genetic variation can affect drug response in multiple ways, although it remains unclear how rare genetic variants affect drug response. The electronic Medical Records and Genomics (eMERGE) Network, collaborating with the Pharmacogenomics Research Network, began eMERGE‐PGx, a targeted sequencing stu...

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Autores principales: Bush, WS, Crosslin, DR, Owusu‐Obeng, A, Wallace, J, Almoguera, B, Basford, MA, Bielinski, SJ, Carrell, DS, Connolly, JJ, Crawford, D, Doheny, KF, Gallego, CJ, Gordon, AS, Keating, B, Kirby, J, Kitchner, T, Manzi, S, Mejia, AR, Pan, V, Perry, CL, Peterson, JF, Prows, CA, Ralston, J, Scott, SA, Scrol, A, Smith, M, Stallings, SC, Veldhuizen, T, Wolf, W, Volpi, S, Wiley, K, Li, R, Manolio, T, Bottinger, E, Brilliant, MH, Carey, D, Chisholm, RL, Chute, CG, Haines, JL, Hakonarson, H, Harley, JB, Holm, IA, Kullo, IJ, Jarvik, GP, Larson, EB, McCarty, CA, Williams, MS, Denny, JC, Rasmussen‐Torvik, LJ, Roden, DM, Ritchie, MD
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5010878/
https://www.ncbi.nlm.nih.gov/pubmed/26857349
http://dx.doi.org/10.1002/cpt.350
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author Bush, WS
Crosslin, DR
Owusu‐Obeng, A
Wallace, J
Almoguera, B
Basford, MA
Bielinski, SJ
Carrell, DS
Connolly, JJ
Crawford, D
Doheny, KF
Gallego, CJ
Gordon, AS
Keating, B
Kirby, J
Kitchner, T
Manzi, S
Mejia, AR
Pan, V
Perry, CL
Peterson, JF
Prows, CA
Ralston, J
Scott, SA
Scrol, A
Smith, M
Stallings, SC
Veldhuizen, T
Wolf, W
Volpi, S
Wiley, K
Li, R
Manolio, T
Bottinger, E
Brilliant, MH
Carey, D
Chisholm, RL
Chute, CG
Haines, JL
Hakonarson, H
Harley, JB
Holm, IA
Kullo, IJ
Jarvik, GP
Larson, EB
McCarty, CA
Williams, MS
Denny, JC
Rasmussen‐Torvik, LJ
Roden, DM
Ritchie, MD
author_facet Bush, WS
Crosslin, DR
Owusu‐Obeng, A
Wallace, J
Almoguera, B
Basford, MA
Bielinski, SJ
Carrell, DS
Connolly, JJ
Crawford, D
Doheny, KF
Gallego, CJ
Gordon, AS
Keating, B
Kirby, J
Kitchner, T
Manzi, S
Mejia, AR
Pan, V
Perry, CL
Peterson, JF
Prows, CA
Ralston, J
Scott, SA
Scrol, A
Smith, M
Stallings, SC
Veldhuizen, T
Wolf, W
Volpi, S
Wiley, K
Li, R
Manolio, T
Bottinger, E
Brilliant, MH
Carey, D
Chisholm, RL
Chute, CG
Haines, JL
Hakonarson, H
Harley, JB
Holm, IA
Kullo, IJ
Jarvik, GP
Larson, EB
McCarty, CA
Williams, MS
Denny, JC
Rasmussen‐Torvik, LJ
Roden, DM
Ritchie, MD
author_sort Bush, WS
collection PubMed
description Genetic variation can affect drug response in multiple ways, although it remains unclear how rare genetic variants affect drug response. The electronic Medical Records and Genomics (eMERGE) Network, collaborating with the Pharmacogenomics Research Network, began eMERGE‐PGx, a targeted sequencing study to assess genetic variation in 82 pharmacogenes critical for implementation of “precision medicine.” The February 2015 eMERGE‐PGx data release includes sequence‐derived data from ∼5,000 clinical subjects. We present the variant frequency spectrum categorized by variant type, ancestry, and predicted function. We found 95.12% of genes have variants with a scaled Combined Annotation‐Dependent Depletion score above 20, and 96.19% of all samples had one or more Clinical Pharmacogenetics Implementation Consortium Level A actionable variants. These data highlight the distribution and scope of genetic variation in relevant pharmacogenes, identifying challenges associated with implementing clinical sequencing for drug treatment at a broader level, underscoring the importance for multifaceted research in the execution of precision medicine.
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spelling pubmed-50108782016-09-04 Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network Bush, WS Crosslin, DR Owusu‐Obeng, A Wallace, J Almoguera, B Basford, MA Bielinski, SJ Carrell, DS Connolly, JJ Crawford, D Doheny, KF Gallego, CJ Gordon, AS Keating, B Kirby, J Kitchner, T Manzi, S Mejia, AR Pan, V Perry, CL Peterson, JF Prows, CA Ralston, J Scott, SA Scrol, A Smith, M Stallings, SC Veldhuizen, T Wolf, W Volpi, S Wiley, K Li, R Manolio, T Bottinger, E Brilliant, MH Carey, D Chisholm, RL Chute, CG Haines, JL Hakonarson, H Harley, JB Holm, IA Kullo, IJ Jarvik, GP Larson, EB McCarty, CA Williams, MS Denny, JC Rasmussen‐Torvik, LJ Roden, DM Ritchie, MD Clin Pharmacol Ther Research Genetic variation can affect drug response in multiple ways, although it remains unclear how rare genetic variants affect drug response. The electronic Medical Records and Genomics (eMERGE) Network, collaborating with the Pharmacogenomics Research Network, began eMERGE‐PGx, a targeted sequencing study to assess genetic variation in 82 pharmacogenes critical for implementation of “precision medicine.” The February 2015 eMERGE‐PGx data release includes sequence‐derived data from ∼5,000 clinical subjects. We present the variant frequency spectrum categorized by variant type, ancestry, and predicted function. We found 95.12% of genes have variants with a scaled Combined Annotation‐Dependent Depletion score above 20, and 96.19% of all samples had one or more Clinical Pharmacogenetics Implementation Consortium Level A actionable variants. These data highlight the distribution and scope of genetic variation in relevant pharmacogenes, identifying challenges associated with implementing clinical sequencing for drug treatment at a broader level, underscoring the importance for multifaceted research in the execution of precision medicine. John Wiley and Sons Inc. 2016-06-01 2016-08 /pmc/articles/PMC5010878/ /pubmed/26857349 http://dx.doi.org/10.1002/cpt.350 Text en © 2016 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs (http://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research
Bush, WS
Crosslin, DR
Owusu‐Obeng, A
Wallace, J
Almoguera, B
Basford, MA
Bielinski, SJ
Carrell, DS
Connolly, JJ
Crawford, D
Doheny, KF
Gallego, CJ
Gordon, AS
Keating, B
Kirby, J
Kitchner, T
Manzi, S
Mejia, AR
Pan, V
Perry, CL
Peterson, JF
Prows, CA
Ralston, J
Scott, SA
Scrol, A
Smith, M
Stallings, SC
Veldhuizen, T
Wolf, W
Volpi, S
Wiley, K
Li, R
Manolio, T
Bottinger, E
Brilliant, MH
Carey, D
Chisholm, RL
Chute, CG
Haines, JL
Hakonarson, H
Harley, JB
Holm, IA
Kullo, IJ
Jarvik, GP
Larson, EB
McCarty, CA
Williams, MS
Denny, JC
Rasmussen‐Torvik, LJ
Roden, DM
Ritchie, MD
Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network
title Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network
title_full Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network
title_fullStr Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network
title_full_unstemmed Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network
title_short Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network
title_sort genetic variation among 82 pharmacogenes: the pgrnseq data from the emerge network
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5010878/
https://www.ncbi.nlm.nih.gov/pubmed/26857349
http://dx.doi.org/10.1002/cpt.350
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