Literature DB >> 24694233

Human leukocyte antigen (HLA) pharmacogenomic tests: potential and pitfalls.

Ann K Daly1.   

Abstract

Adverse drug reactions involving a range of prescribed drugs and affecting the skin, liver and other organs show strong associations with particular HLA alleles. For some reactions, HLA typing prior to prescription, so that those positive for the risk allele are not given the drug associated with the reaction, shows high positive and negative predictive values. The best example of clinical implementation relates to the hypersensitivity reaction induced by the anti-HIV drug abacavir. When this reaction is phenotyped accurately, 100% of those who develop it are positive for HLA-B*57:01. Drug regulators worldwide now recommend genotyping for HLA-B*57:01 before abacavir is prescribed. Serious skin rashes including Stevens-Johnson syndrome and toxic epidermal necrosis can be induced by carbamazepine and other anticonvulsant drugs. In certain East Asians, these reactions are significantly associated with HLA-B*15:02, and typing for this allele is now recommended prior to carbamazepine prescription in these populations. Other HLA associations have been described for skin rash induced by carbamazepine, allopurinol and nevirapine and for liver injury induced by flucloxacillin, amoxicillin-clavulanate, lapatanib, lumiracoxib and ticlopidine. However, the predictive values for typing HLA alleles associated with these adverse reactions are lower. Clinical implementation therefore seems unlikely. Performing HLA typing is relatively complex compared with genotyping assays for single nucleotide polymorphisms. With emphasis on HLA-B*57:01, the approaches used commonly, including use of sequence-specific oligonucleotide PCR primers and DNA sequencing are considered, together with their successful implementation. Genotyping single nucleotide polymorphisms tagging HLA alleles is a simpler alternative to HLA typing but appears insufficiently accurate for clinical use.

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Year:  2014        PMID: 24694233     DOI: 10.2174/138920021502140327180733

Source DB:  PubMed          Journal:  Curr Drug Metab        ISSN: 1389-2002            Impact factor:   3.731


  6 in total

Review 1.  Personalized medicine: Genetic risk prediction of drug response.

Authors:  Ge Zhang; Daniel W Nebert
Journal:  Pharmacol Ther       Date:  2017-02-14       Impact factor: 12.310

2.  HLA-B (*) 58:01 for Allopurinol-Induced Cutaneous Adverse Drug Reactions: Implication for Clinical Interpretation in Thailand.

Authors:  Chonlaphat Sukasem; Thawinee Jantararoungtong; Parnrat Kuntawong; Apichaya Puangpetch; Napatrupron Koomdee; Patompong Satapornpong; Patcharin Supapsophon; Jettanong Klaewsongkram; Ticha Rerkpattanapipat
Journal:  Front Pharmacol       Date:  2016-07-18       Impact factor: 5.810

3.  Adverse drug reactions triggered by the common HLA-B*57:01 variant: a molecular docking study.

Authors:  George Van Den Driessche; Denis Fourches
Journal:  J Cheminform       Date:  2017-03-04       Impact factor: 5.514

4.  Genome-Wide Association Study of Metamizole-Induced Agranulocytosis in European Populations.

Authors:  Anca Liliana Cismaru; Deborah Rudin; Luisa Ibañez; Evangelia Liakoni; Nicolas Bonadies; Reinhold Kreutz; Alfonso Carvajal; Maria Isabel Lucena; Javier Martin; Esther Sancho Ponce; Mariam Molokhia; Niclas Eriksson; Stephan Krähenbühl; Carlo R Largiadèr; Manuel Haschke; Pär Hallberg; Mia Wadelius; Ursula Amstutz
Journal:  Genes (Basel)       Date:  2020-10-29       Impact factor: 4.096

Review 5.  Genetic Determinants in HLA and Cytochrome P450 Genes in the Risk of Aromatic Antiepileptic-Induced Severe Cutaneous Adverse Reactions.

Authors:  Ali Fadhel Ahmed; Chonlaphat Sukasem; Majeed Arsheed Sabbah; Nur Fadhlina Musa; Dzul Azri Mohamed Noor; Nur Aizati Athirah Daud
Journal:  J Pers Med       Date:  2021-05-07

6.  Adverse drug reactions triggered by the common HLA-B*57:01 variant: virtual screening of DrugBank using 3D molecular docking.

Authors:  George Van Den Driessche; Denis Fourches
Journal:  J Cheminform       Date:  2018-01-30       Impact factor: 5.514

  6 in total

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