Adverse Drug Reactions and Pharmacogenomics: Recent Advances

Ana Alfirevic; Munir Pirmohamed

Personalized Medicine. 2008;5(1):11-23.

Nephrotoxicity

The short-term benefits of the calcineurin inhibitors cyclosporine and tacrolimus are unquestionable in transplant patients. Long-term use, however, has been associated with nephrotoxicity and cardiovascular disease. The prevalence of renal failure in heart transplant recipients varies in different studies and the incidence of end-stage renal disease requiring dialysis has reached 3.9%.^[40] Identification of patients at risk for renal failure and adjustment of therapy has the potential to prevent this complication. Several studies have now shown that renal failure after heart transplantation is associated with TGF-ß polymorphisms.^[41,42] Nephrotoxicity after kidney transplantation, however, has been associated with polymorphisms in the ABCB1 gene (encoding the drug transporter P-glycoprotein) of the donor kidney, but not of the recipient.^[43] Tacrolimus pharmacokinetics are highly correlated with polymorphic expression of enzymes involved in its metabolism, mainly CYP3A4 and CYP3A5, and modulated by P-glycoprotein.^[44] In particular, CYP3A5 genotype seems to be predictive of the tacrolimus dose and nephrotoxicity.^[45]

Several antiretroviral drugs have been associated with significant nephrotoxicity in clinical practice.^[46] Although tenofovir nephrotoxicity was not detected in premarketing clinical trials, proximal tubular dysfunction and acute tubular necrosis have been reported in retrospective cohort studies and prospective clinical trials.^[47] Izzedine et al. recently reported an association between tenofovir-induced proximal tubulopathy and variants in the ABCC2 gene, which encodes multidrug resistance associated protein MRP2.^[48] Tenofovir is a substrate for MRP2 providing some biological plausibility that changes in disposition of tenofovir may represent a risk factor for nephrotoxicity. However, this study was undertaken in a small number of patients (13 with tenofovir-induced renal proximal tubulopathy and 17 patients who were tenofovir tolerant) and needs to be replicated in an independent cohort.

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Cite this: Adverse Drug Reactions and Pharmacogenomics: Recent Advances - Medscape - Jan 01, 2008.

Abstract and Introduction
Drug Hypersensitivity
Cardiotoxicity
Nephrotoxicity
Clinical Application of Pharmacogenetics
Sidebar: Executive Summary
References

Table 1. Associations Between HLA Alleles and Drug-Induced Idiosyncratic, Allegedly Immune-Mediated Reactions
Drug	Group of drugs	Adverse reaction	HLA association	Ref.
Abacavir	Antiretroviral	Hypersensitivity	B5701*	[6]
Allopurinol	Antigout agent	Hypersensitivity	B5801*	[82]
Amoxicillin–clavulanate	Antibiotic	Hepatitis	DRB11501*	[16]
Carbamazepine	Anti-epileptic	Hypersensitivity	B1502*	[9]
Clometacin	Antirheumatic	Hepatitis	B8	[83]
Clozapine	Antipsychotic	Agranulocytosis	B38, DR4 and DQ3	[84]
Dipyrone	Antipyretic	Agranulocytosis	A24, B7 and DQ1	[85]
Gold	Antirheumatic	Proteinuria, dermatological reactions and thrombocytopenia	DR3	[86]
Hydralazine	Antihypertensive	Systemic lupus erythematosus	DR4	[87]
Levamisole	Immunotherapy	Agranulocytosis	B27	[88]
Oxicam	Nonsteroidal anti-inflammatory drug	Toxic epidermal necrolysis	A2 and B12	[89]
Penicillamine	Antirheumatic	Proteinuria	DR3	[90]
Sulphonamides	Antibacterial	Toxic epidermal necrolysis	A29, B12 and DR7	[89]

This table represents some key examples. However, it is important to note that although some findings have been well documented in multiple studies, others have only been reported in a single study and replication has never been achieved. Furthermore, although an association with an HLA allele implies an immune-mediated pathogenesis, direct evidence for this in some reactions, for example, clozapine agranulocytosis, is lacking.

Table 2. Examples of Genetic Associations with Drug-Induced Hepatotoxicity
Drug-induced hepatotoxicity	Group of drugs	Genetic association	Ref.
Amoxicillin–clavulanate	Antibiotic	HLA-DRB11501* haplotype	[16]
Carbamazepine	Anti-epileptic	GSTM1	[91]
Diclofenac	Nonsteroidal anti-inflammatory	UGT2B7 and ABCC2	[92]
Isoniazid	Antituberculotic	NAT2 and CYP2E1	[93]
Methotrexate	Anticancer	GSTM1 and RFC	[94]
Nevirapine	Antiretroviral	ABCB1	[95]
Perhexiline	Anti-angina	CYP2D6	[96]
Tacrine	Anti-Alzheimer’s disease	GSTM1 and GSTT1	[97]
Ticlopidine	Antiplatelet	HLA-A3303*	[17]
Tolcapone	Anti-Parkinson’s disease	UGT1A6	[98]
Troglitazone	Antidiabetic	GSTM1 and GSTT1	[99]
Ximelagatran	Anticoagulant	HLA-DRB107, HLA-DQA102	[115]

ABCB1: ATP-binding casette, subfamily B, member 1 or P-glycoprotein; ABCC2: ATP-binding casette, subfamily C, member 2; CYP2E1: Cytochrome P450 2E1; GSTM1: Glutathione-S-transferase mu; GSTT1: Glutathione-S-transferase theta; NAT2: N-acetyltransferase 2; RFC1: Reduced folate carrier 1; UGT1A6: UDP-glycosyltransferase 1 family, polypeptide 6.

Table 3. HLA-Alleles Associated with Susceptibility to Immune-Mediated Diseases Vary Considerably in Patients from Different Ethnic Groups
Population	HLA-alleles associated with disease	Prevalence in patients	Ref.
Coeliac disease
Caucasians	DQA103* DQB10201* DQA105*	0.32 0.97 0.94	[26] [27] [100]
South Asians	DQA103* DQB10201*	0 0.83	[26]
Bedouin	DRB10301* DQA10501* DQB10201*	Haplotype 0.97 - -	[101]
African–Americans	DQ2 serology DQ8 serology	4/4 assessed 1/4 assessed	[102]
Saharawi (North Africa)	DQA0501* DQB10201*	0.95 0.98	[103]
Argentinians	DR3, DR7 DQw2	0.95 -	[104]
Type I diabetes mellitus
Caucasians Non-hispanics	DRB103 or 04 DQB10302* DRB10401*	0.93 0.93 0.64	[105] [29] [25]
Hispanics	DRB10401* DRB10405*	0.13 0.32	[25]
Brazil non-White	DRB103 or 04 Non-DRB103 or 04	0.70 0.30	[105]
Jewish Ethiopian	DRB10301* DQA105* DQB102* Absence of DRB10402*	Haplotype 0.85 - 1	[106]
Lebanese Arabs	DRB11307* DRB10301* DQB10201*	0.07 0.40 0.49	[24]
Bahraini Arabs	DRB10401* DRB10301* DQB10201*	0.06 0.40 0.44	[24]
Multiple sclerosis
Caucasians	DRB11501* DQA10102* DQB10602* DPB10301*	Haplotype 0.39 - 0.50	[107] [108] [109]
Italians	DQB10602* DQA10301* DRB10401*	0.32	[110] [111]
Palestinians	DRB102*	0.35	[112]
Jordanians	DRB102*	0.50	[112]
Cantonese	DQB10602*	-	[108]
Japanese	No association with HLA	-	[113]
French–Canadians	No association with DPB1	-	[114]

Table 3. HLA-Alleles Associated with Susceptibility to Immune-Mediated Diseases Vary Considerably in Patients from Different Ethnic Groups
Population	HLA-alleles associated with disease	Prevalence in patients	Ref.
Coeliac disease
Caucasians	DQA103* DQB10201* DQA105*	0.32 0.97 0.94	[26] [27] [100]
South Asians	DQA103* DQB10201*	0 0.83	[26]
Bedouin	DRB10301* DQA10501* DQB10201*	Haplotype 0.97 - -	[101]
African–Americans	DQ2 serology DQ8 serology	4/4 assessed 1/4 assessed	[102]
Saharawi (North Africa)	DQA0501* DQB10201*	0.95 0.98	[103]
Argentinians	DR3, DR7 DQw2	0.95 -	[104]
Type I diabetes mellitus
Caucasians Non-hispanics	DRB103 or 04 DQB10302* DRB10401*	0.93 0.93 0.64	[105] [29] [25]
Hispanics	DRB10401* DRB10405*	0.13 0.32	[25]
Brazil non-White	DRB103 or 04 Non-DRB103 or 04	0.70 0.30	[105]
Jewish Ethiopian	DRB10301* DQA105* DQB102* Absence of DRB10402*	Haplotype 0.85 - 1	[106]
Lebanese Arabs	DRB11307* DRB10301* DQB10201*	0.07 0.40 0.49	[24]
Bahraini Arabs	DRB10401* DRB10301* DQB10201*	0.06 0.40 0.44	[24]
Multiple sclerosis
Caucasians	DRB11501* DQA10102* DQB10602* DPB10301*	Haplotype 0.39 - 0.50	[107] [108] [109]
Italians	DQB10602* DQA10301* DRB10401*	0.32	[110] [111]
Palestinians	DRB102*	0.35	[112]
Jordanians	DRB102*	0.50	[112]
Cantonese	DQB10602*	-	[108]
Japanese	No association with HLA	-	[113]
French–Canadians	No association with DPB1	-	[114]

Table 4. Factors that May Potentially Contribute to Future Progress in Pharmacogenetics
Consideration	Brief explanation
Well-defined clinical phenotypes	To include quantifiable and reproducible end points when possible
High-throughput genotyping technologies	Decreased cost, high resolution single nucleotide polymorphism mapping and short time from sampling to genotyping results
Regulatory agencies	Drug labeling to include genetic data and instructions on the use of genetic tests
Global networks	Exchange of knowledge and patient materials
Pharmacogenetics knowledge databases	Integration of genetic knowledge with drugs and diseases
Biobanking	Large cohorts of individuals with good data not only on disease phenotype but also on drug prescribing
Pharmacological research	Improved understanding of mechanisms of action of drugs both with respect to efficacy and toxicity
Education on pharmacogenomics	Improved knowledge base and understanding in healthcare professionals and the general public
Proof of utility of pharmacogenetic testing	Demonstration that drug responses (efficacy or toxicity) can be predicted by pretreatment genotyping; importantly, this makes a difference to clinical outcome

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