Clinical Pharmacogenetic Testing and Application: Laboratory Medicine Clinical Practice Guidelines Part 2

Sollip Kim; Yeo-Min Yun; In-Suk Kim; Sang Hoon Song; Hye In Woo; Kyung-A Lee; Woochang Lee; Hyun-Jung Cho; Misuk Ji; Hyo-Jin Chae; Soo-Youn Lee; Sail Chun

doi:10.3343/lmo.2016.6.4.193

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Kim, Yun, Kim, Song, Woo, Lee, Lee, Cho, Ji, Chae, Lee, and Chun: Clinical Pharmacogenetic Testing and Application: Laboratory Medicine Clinical Practice Guidelines Part 2

Original Article

Lab Med Online 2016;6(4):193-213.

Published online: 17 October 2016

DOI: https://doi.org/10.3343/lmo.2016.6.4.193

Clinical Pharmacogenetic Testing and Application: Laboratory Medicine Clinical Practice Guidelines Part 2

Sollip Kim, M.D.^1,^†, Yeo-Min Yun, M.D.^2,^†, In-Suk Kim, M.D.³, Sang Hoon Song, M.D.⁴, Hye In Woo, M.D.⁵, Kyung-A Lee, M.D.⁶, Woochang Lee, M.D.⁷, Hyun-Jung Cho, M.D.⁸, Misuk Ji, M.D.⁹, Hyo-Jin Chae, M.D.¹⁰, Soo-Youn Lee, M.D.^11,^∗, Sail Chun, M.D.^7,^∗

¹Department of Laboratory Medicine, Ilsan Paik Hospital, Inje University College of Medicine, Goyang, Korea

²Department of Laboratory Medicine, Konkuk University Medical Center, Konkuk University School of Medicine, Seoul, Korea

³Department of Laboratory Medicine, School of Medicine, Pusan National University, Busan, Korea

⁴Department of Laboratory Medicine, Seoul National University Hospital and College of Medicine, Seoul, Korea

⁵Department of Laboratory Medicine, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon, Korea

⁶Department of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea

⁷Department of Laboratory Medicine, University of Ulsan College of Medicine and Asan Medical Center, Seoul, Korea

⁸Department of Laboratory Medicine, Konyang University Hospital, College of Medicine, Konyang University, Daejeon, Korea

⁹Department of Laboratory Medicine, Veterans Health Service Medical Center, Seoul, Korea

¹⁰Department of Laboratory Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea

¹¹Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea

^† These authors contributed equally to this work.

^∗ These corresponding authors contributed equally to this work.

Corresponding author: Soo-Youn Lee Department of Laboratory Medicine and Genetics, Sungkyunkwan University School of Medicine, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul 06351, Korea Tel: +82-2-3410-1824, Fax: +82-2-3410-2719, E-mail: suddenbz@skku.edu

Corresponding author: Sail Chun Department of Laboratory Medicine, University of Ulsan College of Medicine and Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Korea Tel: +82-2-3010-4513, Fax: +82-2-478-0884, E-mail: sailchun@amc.seoul.kr

Received 1 December 201518 February 2016 Accepted 2 March 2016

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Pharmacogenetics is a rapidly evolving field and the number of pharmacogenetic tests for clinical use is steadily increasing. However, incorrect or inadequate implementation of pharmacogenetic tests in clinical practice may result in a rise in medical costs and adverse outcomes in patients. This document suggests guidelines for the clinical application, interpretation, and reporting of pharmacogenetic test results based on a literature review and the collection of evidence-based expert opinions. The clinical laboratory practice guidelines encompass the clinical pharmacogenetic tests covered by public medical insurance in Korea. Technical, ethical, and regulatory issues related to clinical pharmacogenetic tests have also been addressed. In particular, this document comprises the following pharmacogenetic tests: CYP2C9 and VKORC1 for warfarin, CYP2C19 for clopidogrel, CYP2D6 for tricyclic antidepressants, codeine, tamoxifen, and atomoxetine, NAT2 for isoniazid, UGT1A1 for irinotecan, TPMT for thio-purines, EGFR for tyrosine kinase inhibitors, ERBB2 (HER2) for erb-b2 receptor tyrosine kinase 2-targeted therapy, and KRAS for anti-epidermal growth factor receptor drugs. These guidelines would help improve the usefulness of pharmacogenetic tests in routine clinical settings.

Keywords: Pharmacogenetics, Genetic testing, Practice guidelines, Clinical laboratory services

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Table 1.

CYP2C9 alleles and enzyme activity [11]

Allele	Constituted by genotypes at:	Amino acid changes	Enzymatic activity
∗1	Reference allele		Normal
∗2	C>T at rs1799853	R144C	Decreased
∗3	A>C at rs1057910	I359L	Decreased
∗4	T>C at rs56165452	I359T	Decreased
∗5	C>G at rs28371686	D360E	Decreased
∗6	delA at rs9332131	273 frame shift	Null
∗7	C>A at rs67807361	L19I
∗8	G>A at rs7900194	R150H	Decreased
∗9	A>G at rs2256871	H251R
∗11	C>T at rs28371685	R335W	Decreased
∗12	C>T at rs9332239	P489S	Decreased
∗13	T>C at rs72558187	L90P	Decreased
∗14	G>A at rs72558189	R125H	Decreased
∗15	C>A at rs72558190	S162X	Null
∗16	A>C at rs72558192	T299A	Decreased
∗17	1144C>T	P382S	Decreased
∗18	A>C at rs1057910, A>C at rs72558193, A>T at rs1057911	I359L; D397A	Decreased
∗25	delAGAAATGGAA at rs72558188	118 frame shift	Null
∗33	G>A at rs72558184	R132Q	Decreased

Table 2.

Allele frequencies (%) of CYP2C9 and VKORC1

Allele	White [6]	Asian [6]	Black [6]	Korean [105-110]	Chinese [111-118]	Japanese [119-123]
CYP2C9∗2	13	0	3	0	0	0
CYP2C9∗3	7	4	2	4-5	2-9	2
VKORC1 −1639G_>A (rs9923231) or 1173C>T (rs9934438)	39	91	11	87-94	88-93	86-92

Table 3.

Recommended warfarin doses (mg/day) to achieve a therapeutic international normalized ratio based on CYP2C9 and VKORC1 genotypes using the warfarin product insert approved by the United States Food and Drug Administration

VKORC1 −1639G>A	CYP2C9∗1/∗1	CYP2C9∗1/∗2	CYP2C9∗1/∗3	CYP2C9∗2/∗2	CYP2C9∗2/∗3	CYP2C9∗3/∗3
GG	5-7	5-7	3-4	3-4	3-4	0.5-2
GA	5-7	3-4	3-4	3-4	0.5-2	0.5-2
AA	3-4	3-4	0.5-2	0.5-2	0.5-2	0.5-2

Table 4.

Representative warfarin dosing algorithms

	International Warfarin Pharmacogenetic Consortium (IWPC) algorithm	Gage algorithm
Derivation cohort, total/Asian (n)	4,043/1,229	1,015/NA
Validation cohort, total/Asian (n)	1,009/300	292/NA
Variables in the dosing equation	Age (decades), height (cm), weight (kg), VKORC1 genotype (-1639G_>A), CYP2C9 genotype (∗2, ∗3), race (Asian, black/ African American, missing, or mixed), enzyme inducer (carbamazepine, phenytoin, rifampin, or rifampicin) status, amiodarone status	VKORC1 genotype (-1639G>A), BSA, CYP2C9 genotype (∗2, ∗3), Age (decades), target INR, per 0.5 increase, amiodarone status, current smoker, race (African American), DVT/PE
Output	Square root of weekly warfarin dose	Daily dose
Internet source	http://www.warfarindosing.org, http://www.pharmgkb.org	http://www.warfarindosing.org

Abbreviations: BSA, body surface area in meters; DVT, deep vein thrombosis; INR, international normalized ration; PE, pulmonary embolism.

Table 5.

Frequencies (%) of CYP2C19 alleles

Allele	White [124, 125]	African American [124, 125]	Hispanic [124]	Ashkenazi Jewish [124]	Asian [30]	Korean [40-47]
∗1	84-87.1	75-82	85	83	60-62	60.0-65.3
∗2	12-12.9	12-25.0	10	12	29-35	26.0-30.3
∗3	0	0	-	-	2.4-8.9	6.8-10.1
∗4	0.3	0	0	0.45	0-0.5	0
∗5	-	-	-	-	0-0.6	-
∗6	-	-	-	-	0	0
∗7	-	-	-	-	-	-
∗8	0.4	0.3	0	0.15	0	0
∗17	-	-	-	-	0.3	1.2-1.5

Table 6.

Assigning likely CYP2C19 phenotypes based on genotypes [31]

Likely phenotype	Genotypes	Examples of diplotypes
Ultra-rapid metabolizer: normal or increased activity (~5-30% of patients)	An individual carrying 2 increased-activity alleles (∗17), or 1 functional allele (∗1) plus 1 increased-activity allele (∗17)	∗1/∗17, ∗17/∗17
Extensive metabolizer: homozygous wild-type or	An individual carrying 2 functional (∗1) alleles	∗1/∗1
normal activity (~35-50% of patients)
Intermediate metabolizer: heterozygote or intermediate	An individual carrying 1 functional allele (∗1) plus 1 loss-of-	∗1/∗2, ∗1/∗3
activity (~18-45% of patients)	function allele (∗2-∗8)
Poor metabolizer: homozygous variant, mutant, low, or deficient activity (~2-15% of patients)	An individual carrying 2 loss-of-function alleles (∗2-∗8)	∗2/∗2, ∗2/∗3, ∗3/∗3

Table 7.

Clopidogrel therapy based on CYP2C19 phenotype for ACS/PCI patients initiating antiplatelet therapy [31]

Phenotype (genotype)	Implications for clopidogrel	Therapeutic recommendations
Ultra-rapid metabolizer (UM) (∗1/∗17, ∗17/∗17) and extensive metabolizer (EM) (∗1/∗1)	Normal (EM) or increased (UM) platelet inhibition; normal (EM) or decreased (UM) residual platelet aggregation^a	Clopidogrel label-recommended dosage and administration
Intermediate metabolizer (IM) (∗1/∗2, ∗1/∗3, ∗2/∗17)	Reduced platelet inhibition; increased residual platelet aggrega-	Prasugrel or other alternative therapy (if no
	tion; increased risk for adverse cardiovascular events	contraindication)
Poor metabolizer (PM) (∗2/∗2, ∗2/∗3, ∗3/∗3)	Significantly reduced platelet inhibition; increased residual plate-	Prasugrel or other alternative therapy (if no
	let aggregation; increased risk for adverse cardiovascular events	contraindication)

^a The CYP2C19∗17 allele may be associated with an increased risk of bleeding.

Table 8.

Frequencies of CYP2D6 alleles (%)

Allele	East Asian [50]	Korean [126]	Korean [54]	Europe [50]	African [50]	South/Central Asian [50]	Oceanian [50]
∗1	34.17	33.25	32.32	53.63	39.23	53.70	70.15
∗2	12.82	10.13	10.88	26.91	20.12	31.90	1.20
∗3	0.00	0.00	-	1.32	0.03	0.00	0.00
∗4	0.42	0.25	-	18.50	3.36	6.56	1.13
∗5	5.61	6.13	5.61	2.69	6.07	2.54	4.95
∗10	42.31	45.00	45.58	3.16	6.77	19.76	1.60
∗41	1.97	1.88	2.24	8.56	10.94	10.50	0.00
∗2xN	0.38	0.50	0.99	1.27	1.56	0.50	0.00
∗1xN	0.28	0.13	0.07	0.80	1.47	0.50	11.83

Table 9.

Assignment of likely phenotypes based on diplotypes of CYP2D6 [49, 127]

Likely phenotype	Activity score	Genotypes	Examples of diplotypes
Ultra-rapid metabolizer (~1-2%)	_> 2.0	An individual carrying duplications of functional alleles	(∗1/∗1)xN, (∗1/∗2)xN, (∗2/∗2)xN
Extensive metabolizer (~77-92%)	1.0-2.0	An individual carrying 2 functional alleles or 1 functional and	∗1/∗1, ∗1/∗2, ∗2/∗2, 1/∗9, ∗1/∗41, ∗1/∗5, ∗1/∗4
		1 nonfunctional allele or 1 functional and 1 reduced function allele
Intermediate metabolizer (~2-11%)	0.5	An individual carrying 1 reduced function and 1 nonfunctional allele or	∗4/∗41, ∗5/∗9, ∗4/∗10, ∗41/∗41
		2 reduced function alleles
Poor metabolizer (~5-10%)	0	An individual carrying no functional alleles	∗4/∗4, ∗3/∗4, ∗5/∗5, ∗5/∗6

Table 10.

Dosing recommendations for amitriptyline and nortriptyline based on CYP2D6 phenotype [49]

Phenotype	Implication	Therapeutic recommendation
Ultra-rapid metabolizer	Increased metabolism of tricyclics to less active compounds when compared with extensive metabolizers.	Avoid tricyclic use due to potential lack of efficacy. Consider an alternative drug not metabolized by CYP2D6.
	Lower plasma concentrations will increase the probability	If a tricyclic is warranted, consider increasing the starting dose. Utilize therapeu-
	of pharmacotherapy failure.	tic drug monitoring to guide dose adjustments.
Extensive metabolizer	Normal metabolism of tricyclics.	Initiate therapy with recommended starting dose.
Intermediate metabolizer	Reduced metabolism of tricyclics to less active compounds when compared with extensive metabolizers.	Consider a 25% reduction of the recommended starting dose. Utilize therapeutic drug monitoring to guide dose adjustments.
	Higher plasma concentrations will increase the probability of side effects.
Poor metabolizer (~5-10%)	Greatly reduced metabolism of tricyclics to less active compounds when compared with extensive metabolizers.	Avoid tricyclic use due to the potential for side effects. Consider an alternative drug not metabolized by CYP2D6.
	Higher plasma concentrations will increase the probability of side effects.	If a tricyclic is warranted, consider a 50% reduction of the recommended starting dose. Utilize therapeutic drug monitoring to guide dose adjustments.

Table 11.

Frequencies of NAT2 alleles (%)

Allele	Cambo-	Japanese	Korean	Korean	Korean	Europe-	African
Allele	dian [69]	[71]	[70]	[71]	[72]	an [71]	[71]
∗4	40.1	69.3	65.7	62.4	62.3	-	8.9
∗5	11.3	-	1.6	-	1.9	53.3	71.6
∗6	31.4	22.7	20.1	22.4	21.2	-	-
∗7	17.2	-	11.5	15.2	13.5	-	-
∗11	-	-	-	-	-	44.4	19.4
∗12	-	-	0.8	-	0.5	-	-
∗13	-	8.0	0.1	-	0.7	2.3	-

Table 12.

Assignment of likely phenotypes based on diplotypes of NAT2 [68, 70]

Likely phenotype	Genotype	Examples of diplotypes
Normal/high activity (rapid acetylator)	2 rapid NAT2 alleles (∗4, ∗11, ∗12, ∗13)	∗4/∗4, ∗4/∗12, ∗4/∗13, etc.
Intermediate activity (intermediate acetylator)	1 rapid NAT2 allele and 1 slow NAT2 allele	∗4/∗5, ∗4/∗6, ∗4/∗7, etc.
Low activity (slow acetylator)	2 slow NAT2 alleles (∗5, ∗6, ∗7)	∗6/∗6, ∗7/∗7, ∗6/∗7, ∗5/∗6, ∗5/∗7, etc.

Table 13.

Frequencies of UGT1A1 alleles (%)

Allele	Asian [128]	Korean [129]	Korean [130]	Korean [131]	Korean [132]	Korean [133]	White [128]	Black [128]
∗6	15.7	21.3	18.6	15.5	22.2	19.3	0.7	0.0
∗28	9.7	12.7	10.4	10.3	9.5	11.4	38.8	44.6

Table 14.

Assignment of likely phenotypes based on diplotypes of UGT1A1

Likely phenotype	Genotype	Examples of diplotypes
Homozygous wild (normal/high activity)	Two functional alleles (∗1)	∗1/∗1
Heterozygote (intermediate activity, intermediate metabolizer)	One functional (∗1) and one reduced function allele (∗6, ∗28)	∗1/∗6, ∗1/∗28
Compound heterozygote [134] (low activity, poor metabolizer)	One reduced function allele (∗6) and another reduced function allele (∗28)	∗6/∗28
Homozygous variant (low activity, poor metabolizer)	Two reduced function alleles (∗6, ∗28)	∗6/∗6, ∗28/∗28

Table 15.

Frequencies of TPMT alleles (%)

Allele	Asian [82]	Korean [40]	Korean [41]	Korean [42]	Korean [43]	Korean [44]	Korean [45]	Korean [87]	Caucasian [82]
∗1	98.35	98.88	97.51	98.95	98.78	96.19	96.00	96.44	95.73
∗2	0	0	0	0	0	0	1.00	0	0.19
∗3A	0.01	0	0	0	0	0	0.50	0	3.56
∗3B	0	0	0	0	0	0	0	0	0.05
∗3C	1.57	0.88	1.75	1.05	1.22	2.54	2.50	1.44	0.42
∗6	0.07	0.25	0.73	-	-	1.27	-	0.17	-

Table 16.

Assignment of likely thiopurine S-methyltransferase phenotypes based on genotypes [23]

Likely phenotype	Genotypes	Examples of diplotypes
Homozygous wild-type or normal high activity (constitutes ~86-97% of patients)	An individual carrying two or more functional (∗1) alleles	∗1/∗1
Heterozygote or intermediate activity (~3-14% of patients)	An individual carrying one functional allele (∗1) plus one nonfunctional allele (∗2, ∗3A, ∗3B, ∗3C, or ∗4)	∗1/∗2, ∗1/∗3A, ∗1/∗3B, ∗1/∗3C, ∗1/∗4
Homozygous variant, mutant, low, or deficient activity (~1 in 178 to 1 in 3,736 patients)	An individual carrying two nonfunctional alleles (∗2, ∗3A, ∗3B, ∗3C, or ∗4)	∗3A/∗3A, ∗2/∗3A, ∗3C/∗3A, ∗3C/∗4, ∗3C/∗2, ∗3A/∗4

Table 17.

Drug sensitivity according to genetic variations in EGFR

Major genetic variation	Nomenclature	Phenotype
G719S (exon 18)	NM_005228.3:c.2155G_<A, NP_005219.2:p.Gly719Ser	TKI sensitivity
G719C (exon 18)	NM_005228.3:c.2155G_<T, NP_005219.2:p.Gly719Cys	TKI sensitivity
G719A (exon 18)	NM_005228.3:c.2155G_<C, NP_005219.2:p.Gly719Ala	TKI sensitivity
In-frame deletions (exon 19)	NM_005228.3:c.2235_2249del15, NP_005219.2:p.Glu746_Ala750del	TKI sensitivity
	NM_005228.3:c.2236_2250del15, NP_005219.2:p.Glu746_Ala750del	TKI sensitivity
	NM_005228.3:c.2239_2248delinsC, NP_005219.2:p.Leu747_Ala750delinsPro NM_005228.3:c.2240_2257del18, NP_005219.2:p.Leu747_Pro753delinsSer	TKI sensitivity TKI sensitivity
T790M (exon 20)	NM_005228.3:c.2369C>T, NP_005219.2:p.Thr790Met	TKI resistance
L858R (exon 21)	NM_005228.3:c.2573T>G, NP_005219.2:p.Leu858Arg	TKI sensitivity
L861Q (exon 21)	NM_005228.3: c.2582T>A, NP_005219.2:p.Leu861Gln	TKI sensitivity

Table 18.

Number and type of mutations, affected codons, and corresponding altered amino acids in exon 2, codons 12 and 13 of the KRAS gene, analyzed separately for specimens derived from primary tumors and metastases [104]

Codon	Type of point mutation	Frequency of mutations in primary tumors (n=879)(% of all tumors)	Frequency of mutations in metastases (n =139) (% of all tumors)
12	c.35G>A (p.G12D) c.35G>T (p.G12V)	123 (14.0%) 78 (8.9%)	21 (15.1%) 9 (6.5%)
	c.34G>T (p.G12C)	29 (3.3%)	3 (2.2%)
	c.34G_>A (p.G12S) c.35G>C (p.G12A)	21 (2.4%) 21 (2.4%)	5 (3.6%) 3 (2.2%)
	c.34G>C (p.G12R) c.34G>A, c.35G4T (p.G12I)	4 (0.5%) 1 (0.1%)	1 (0.7%) Not reported
	c.34G>T, c.35G4T (p.G12F)	1 (0.1%)	1 (0.7%)
13	c.38G>A (p.G13D) c.37G_>T (p.G13C)	68 (7.7%) 2 (0.2%)	Not reported 7 (5.0%)
	c.37G>C (p.G13R)	1 (0.1%)	1 (0.7%)
Wild type		530 (60.3%)	88 (63.3%)

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