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Transcript
OMB No. 0925-0001/0002 (Rev. 08/12 Approved Through 8/31/2015)
BIOGRAPHICAL SKETCH
Provide the following information for the Senior/key personnel and other significant contributors.
Follow this format for each person. DO NOT EXCEED FIVE PAGES.
NAME: Teri E. Klein
eRA COMMONS USER NAME (credential, e.g., agency login): TERI.KLEIN
POSITION TITLE: Co-PI & Director, PharmGKB; Co-PI, CPIC
INSTITUTION AND LOCATION
DEGREE
(if
applicable)
University of California, San Diego
University of California, Santa Cruz
University of California, San Francisco
Completion
Date
MM/YYYY
FIELD OF STUDY
06/1977
BA
06/1980
Chemistry/Biology
PhD
06/1987
Medical Information
Sciences
A. Personal Statement
I am the Co-PI & Director of the Pharmacogenomics Knowledgebase (PharmGKB) and the Co-PI of the
Clinical Pharmacogenetics Implementation Consortium (CPIC). My area of professional expertise extends over
clinical and research pharmacogenomics, the study of how variation in human genetics impacts drug response
phenotypes. The PharmGKB resource is the premier repository of curated information about how human
genetic variation impacts drug-response phenotypes. We use the contents of PharmGKB to create drug dosing
guidelines (CPIC) and new applications in data mining, drug discovery and personal genomics.
I have taught, advised and mentored graduate level (masters, doctoral and post-doctoral) biomedical
informatics students since my initial faculty position at the University of California San Francisco (Department
of Pharmaceutical Chemistry) and at Stanford University (Biomedical Informatics).
B. Positions and Honors
Research and/or Professional Experience
2015–
Co-PI, Clinical Pharmacogenetics Implementation Consortium (CPIC), Stanford University
2014–
Co-PI & Director, PharmGKB, Stanford University
2009–
Co-leader, Clinical Pharmacogenetics Implementation Consortium (CPIC)
2002
National Institutes of Health (NIH), Study Section Reviewer
2000-2014
Director, PharmGKB, Stanford University
2000–
Faculty Member and Executive Committee Member, Biomedical Informatics, Stanford University
2000-2002
Treasurer, International Society for Computational Biology
1996–
Co-founder and Co-chair, Pacific Symposium on Biocomputing
1994-2000
Faculty, Department of Pharmaceutical Chemistry, University of California San Francisco
1998
National Institute of Environmental Health Sciences (NIEHS), Site Visit Reviewer
Honors and Awards
2001 Fellow, American College of Medical Informatics
2015 Fellow, American College of Medical Genetics and Genomics
C. Contribution to Science
My bibliography of 124 papers on PubMED (as of 4/13/2015) is present on “My Bibliography” at NCBI at
http://www.ncbi.nlm.nih.gov/sites/myncbi/1X_VflkeIyBQm/bibliography/47842419/public/?sort=date&direction=
ascending
Five key areas of contribution over the last decade include:
1. I have served as the original Director and now Co-PI and Director, of the Pharmacogenomics
Knowledgebase (PharmGKB, http://www.pharmgkb.org/) Resource. This is a premier human-curated
knowledge base of how human genetic variation impacts drug response phenotypes. It gets 25,00035,000 unique IP hits each month, publishes review articles on drug pathways and genes of
significance to pharmacogenomics (and thus precision medicine), and is the basis for several clinical
implementation research efforts. We have over 110 papers published as part of the PharmGKB project.
a. McDonagh Em, Whirl-Carrillo M, Altman RB, Klein TE. Enabling the curation of your
pharmacogenetic study. Clin Pharmacol Ther. 2015 Feb;97(2):116-9. PMC4352230.
b. Mazaleuskaya LL, Theken KN, Gong L, Thorn CF, FitzGerald GA, et al. PharmGKB summary:
ibuprofen pathways. Pharmacogenetics and genomics. 2015; 25(2):96-106. PMCID:
PMC4355401.
c. McDonagh EM, Clancy JP, Altman RB, Klein TE. PharmGKB summary: very important
pharmacogene information for CFTR. Pharmacogenetics and genomics. 2015; 25(3):149-56.
PMCID: PMC4336773.
d. Whirl-Carrillo M, McDonagh EM, Hebert JM, Gong L, Sangkuhl K, Thorn CF, Altman RB, Klein
TE. Pharmacogenomics knowledge for personalized medicine. Clin Pharmacol Ther. 2012
Oct;92(4):414-7. PMCID: PMC3660037.
2. I am the co-apiof the Clinical Pharmacogenetics Implementation Consortium. The Clinical
Pharmacogenetics Implementation Consortium (CPIC) was formed in late 2009, as a shared project
between PharmGKB and the Pharmacogenomics Research Network. CPIC guidelines are peerreviewed and published in a leading journal (in partnership with Clinical Pharmacology and
Therapeutics) with simultaneous posting to PharmGKB with supplemental information/data and
updates. CPIC's goal is to address some of the barriers to implementation of pharmacogenetic tests
into clinical practice. We have published clinical dosing guidelines for 29 drug-gene pairs.
a. Relling MV, Klein TE. CPIC: Clinical Pharmacogenetics Implementation Consortium of the
Pharmacogenomics Research Network. Clin Pharmacol Ther. 2011 Mar;89(3):464-7. PMCID:
PMC3098762.
b. Johnson JA, Klein TE, Relling MV. Clinical implementation of pharmacogenetics: more than one
gene at a time. Clin Pharmacol Ther. 2013 May;93(5):384-5. PMCID: PMC3716458.
c. Caudle KE, Klein TE, Hoffman JM, Muller DJ, Whirl-Carrillo M, Gong L, McDonagh EM,
Sangkuhl K, Thorn CF, Schwab M, Agundez JA, Freimuth RR, Huser V, Lee MT, Iwuchukwu
OF, Crews KR, Scott SA, Wadelius M, Swen JJ, Tyndale RF, Stein CM, Roden D, Relling MV,
Williams MS, Johnson SG. Incorporation of pharmacogenomics into routine clinical practice: the
Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline development process.
Curr Drug Metab. 2014 Feb;15(2):209-17. PMCID: PMC3977533.
d. Hicks JK, Bishop JR, Sangkuhl K, Müller DJ, Ji Y, Leckband SG, Leeder JS, Graham RL, Chiulli
DL, LLerena A, Skaar TC, Scott SA, Stingl JC, Klein TE, Caudle KE, Gaedigk A. Clinical
Pharmacogenetics Implementation Consortium (CPIC) Guideline for CYP2D6 and CYP2C19
Genotypes and Dosing of Selective Serotonin Reuptake Inhibitors. Clin Pharmacol Ther. 2015
May 13. PubMed PMID: 25974703. NIHMSID 689584.
3. We have helped demonstrate how whole human genomes can be annotated, and the issues of genome
annotation in the context of next generation sequencing. This leadership has been through highly
collaborative papers showing the first clinical analysis of a whole human genome, the analysis of a
family quartet of genomes, an analysis of a series of genomes with an analysis of accuracy, and papers
on the appropriate interpretation and triage of variations discovered in genome sequencing
applications, both for pharmacogenomics and more broadly. We have 14 papers published as part of
these efforts.
a. Daneshjou R, Zappala Z, Kukurba K, Boyle SM, Ormond KE, Klein TE, Snyder M, Bustamante
CD, Altman RB, Montgomery SB. PATH-SCAN: a reporting tool for identifying clinically
actionable variants. Pac Symp Biocomput. 2014:229-40. PMCID: PMC4008882.
b. Altman RB, Whirl-Carrillo M, Klein TE. Challenges in the pharmacogenomic annotation of whole
genomes. Clin Pharmacol Ther. 2013 Aug;94(2):211-3. PMCID: PMC4058909.
c. Dewey FE, Chen R, Cordero SP, Ormond KE, Caleshu C, Karczewski KJ, Whirl-Carrillo M,
Wheeler MT, Dudley JT, Byrnes JK, Cornejo OE, Knowles JW, Woon M, Sangkuhl K, Gong L,
Thorn CF, Hebert JM, Capriotti E, David SP, Pavlovic A, West A, Thakuria JV, Ball MP, Zaranek
AW, Rehm HL, Church GM, West JS, Bustamante CD, Snyder M, Altman RB, Klein TE, Butte
AJ, Ashley EA. Phased whole-genome genetic risk in a family quartet using a major allele
reference sequence. PLoS Genet. 2011 Sep;7(9):e1002280. PMCID: PMC3174201.
d. Ashley EA, Butte AJ, Wheeler MT, Chen R, Klein TE, Dewey FE, Dudley JT, Ormond KE,
Pavlovic A, Morgan AA, Pushkarev D, Neff NF, Hudgins L, Gong L, Hodges LM, Berlin DS,
Thorn CF, Sangkuhl K, Hebert JM, Woon M, Sagreiya H, Whaley R, Knowles JW, Chou MF,
Thakuria JV, Rosenbaum AM, Zaranek AW, Church GM, Greely HT, Quake SR, Altman RB.
Clinical assessment incorporating a personal genome. Lancet. 2010 May 1;375(9725):1525-35.
PMCID: PMC2937184.
4. I have led international pharmacogenomics data consortia for warfarin, tamoxifen, clopidogrel, and
selective serotonin reuptake inhibitors. The goal for each consortium was to determine the role of
pharmacogenomics for each of these drugs with respect to possible efficacy and adverse events. We
have published our results in peer-reviewed journals including New England Journal of Medicine,
Lancet and Clinical Pharmacology and Therapeutics.
a. International Warfarin Pharmacogenetics Consortium, Klein T E, Altman R B, Eriksson N, Gage
B F, Kimmel S E, Lee M-T M, Limdi N A, Page D, Roden D M, Wagner M J, Caldwell M D,
Johnson J A. Estimation of the warfarin dose with clinical and pharmacogenetic data. N Engl J
Med. 2009 Feb 19;360(8):753-64. PMCID: PMC2722908.
b. Perera MA, Cavallari LH, Limdi NA, Gamazon ER, Konkashbaev A, Daneshjou R, Pluzhnikov A,
Crawford DC, Wang J, Liu N, Tatonetti N, Bourgeois S, Takahashi H, Bradford Y, Burkley BM,
Desnick RJ, Halperin JL, Khalifa SI, Langaee TY, Lubitz SA, Nutescu EA, Oetjens M, Shahin
MH, Patel SR, Sagreiya H, Tector M, Weck KE, Rieder MJ, Scott SA, Wu AH, Burmester JK,
Wadelius M, Deloukas P, Wagner MJ, Mushiroda T, Kubo M, Roden DM, Cox NJ, Altman RB,
Klein TE, Nakamura Y, Johnson JA. Genetic variants associated with warfarin dose in AfricanAmerican individuals: a genome-wide association study. Lancet. 2013; 382(9894):790-6.
PMCID: PMC3759580.
c. Province MA, Goetz MP, Brauch H, Flockhart DA, Hebert JM, Whaley R, Suman VJ, Schroth W,
Winter S, Zembutsu H, Mushiroda T, Newman WG, Lee MT, Ambrosone CB, Beckmann MW,
Choi JY, Dieudonné AS, Fasching PA, Ferraldeschi R, Gong L, Haschke-Becher E, Howell A,
Jordan LB, Hamann U, Kiyotani K, Krippl P, Lambrechts D, Latif A, Langsenlehner U, Lorizio W,
Neven P, Nguyen AT, Park BW, Purdie CA, Quinlan P, Renner W, Schmidt M, Schwab M, Shin
JG, Stingl JC, Wegman P, Wingren S, Wu AH, Ziv E, Zirpoli G, Thompson AM, Jordan VC,
Nakamura Y, Altman RB, Ames MM, Weinshilboum RM, Eichelbaum M, Ingle JN, Klein TE;
International Tamoxifen Pharmacogenomics Consortium. CYP2D6 genotype and adjuvant
tamoxifen: meta-analysis of heterogeneous study populations. Clin Pharmacol Ther. 2014
Feb;95(2):216-27. PMCID: PMC3904554.
d. Province MA, Altman RB, Klein TE. Interpreting the CYP2D6 results from the International
Tamoxifen Pharmacogenetics Consortium. Clin Pharmacol Ther. 2014 Aug;96(2):144-6.
Review. PMCID: PMC4147833.
5. I led research efforts designed to construct a robust and relevant predictive model of the disease
Osteogenesis Imperfecta based on genomic, structural, functional and clinical data, and knowledge.
We worked towards identifying the common elements that result from mutations in genes that lead to
OI phenotypes and affect response to treatments. Increased knowledge of collagen structure and
genes involved in the OI disease process could benefit the study of other genetic collagenous disorders
and diseases such as chondrodysplasis, aneurysms and Ehlers-Danlos syndrome where alteration of
collagen structure is the primary determinant of phenotype.
a. Bodian DL, Chan TF, Poon A, Schwarze U, Yang K, Byers PH, Kwok PY, Klein TE. Mutation
and polymorphism spectrum in osteogenesis imperfecta type II: implications for genotypephenotype relationships. Hum Mol Genet. 2009 Feb 1;18(3):463-71. doi: 10.1093/hmg/ddn374.
Epub 2008 Nov 7. Erratum in: Hum Mol Genet. 2009 May 15;18(10):1893-5. PMCID:
PMC2638801.
b. Chan TF, Poon A, Basu A, Addleman NR, Chen J, Phong A, Byers PH, Klein TE, Kwok PY
Natural variation in four human collagen genes across an ethnically diverse population.
Genomics. 2008 Apr;91(4):307-14. PMCID: PMC2737816.
c. Radmer RJ, Klein TE. Severity of osteogenesis imperfecta and structure of a collagen-like
peptide modeling a lethal mutation site. Biochemistry. 2004 May 11;43(18):5314-23. PubMed
PMID: 15122897.
d. Mooney SD, Klein TE. Structural models of osteogenesis imperfecta-associated variants in the
COL1A1 gene. Mol Cell Proteomics. 2002 Nov;1(11):868-75. PubMed PMID: 12488462.
D. Research Support
Active
R24 GM061374
04/01/2000-06/30/2019
NIH / NIGMS
PharmGKB: pharmacogenomic knowledge for precision medicine
Since 2000, the Pharmacogenomics Knowledgebase (PharmGKB, http://www.pharmgkb.org/) has become the
premier repository of information about how human genetic variation impacts drug response phenotypes.
Goals: to extend the activities of the PharmGKB by implementing a plan of curation, tool-building and
collaborations that address the key challenges to the field.
Role: Co-PI and Director
NIH 8-UHG0073436A (PI: Bustamante, Carlos)
09/23/2013-07/31/2017
NIH
Clinically Relevant Genome Variation Database
The goal is to create the world’s premier database of genetic variants relevant to clinical care (Clinically
Relevant Genomic Variants or CRGVs). We will provide transparent data synthesis and consensus opinion on
the clinical utility of a given genetic variant across a spectrum of genetic lesions including single nucleotide
changes, small indels, structural variants, and epigenetic changes. We will integrate with ClinVar, PharmGKB,
and OMIM and draw upon NHGRI initiatives including the Genome Sequencing and Analysis and Mendelian
Disorders Sequencing Centers, and the Clinical Sequencing Exploratory Research Centers.
Role: Co-Investigator
R24 GM115264 (PI: Relling, Mary)
07/01/2015-06/30/2018
NIH / St. Jude’s Children’s Research Hospital
Subcontract
Clinical Pharmacogenetics Implementation Consortium (CPIC)
This group is responsible for contributing to the evaluation and writing of the gene-drug guidelines, the
development of the translation tables, the dissemination and integration of the dosing guidelines on the
PharmGKB website, the CPIC working group website and outreach.
Role: PI
Completed
1 R01 AR051582-01 (PI: Klein)
08/05/2000-06/30/2009
NIH NIAMS
Linking Collagen Genotypes to Molecular Phenotypes
The long-term goal of this proposal is to determine the chemical, physical and structural properties of
biopolymers in the context of natural sequence variation. Mutations in type I collagen lead to an array of minor
to lethal disorders. Osteogenesis imperfecta (OI) is the most common clinical result of mutations in the two
type I collagen genes, COL1A1 and COL1A2. As diagnostic strategies for OI move from the clinical picture to
evaluation of mutations in genes, there is a paucity of data on which to base coherent counseling decisions in
that the relationships between genotypes, molecular phenotypes, and clinical phenotypes are unknown and
poorly understood. An understanding of the physiochemical properties of native and mutated collagens will
provide the basis to comprehend the molecular etiology of OI phenotypes. Information that is critical for the
development of useful genetic counseling protocols when only DNA based diagnostic information is available.
Role: PI