A PILOT STUDY OF PHARMACOGENOMICS IN PATIENTS WITH CHRONIC KIDNEY DISEASE STAGE 5 OF UNCERTAIN CAUSE

Y L CHUNG1, C PATEL2,3, A MALLAWAARACHICHI3,4,5, Z STARK3,6,7,8, C SIMONS3,7, C QUINLAN3,7,8,9, A MALLETT1,3,10

1The University of Queensland, Brisbane, Australia, 2Genetic Health Queensland, Royal Brisbane and Women’s Hospital, Brisbane, Australia, 3KidGen Collaborative, Australian Genomics Health Alliance, Melbourne, Australia, 4Royal Prince Alfred Hospital, Sydney, Australia, 5Garvan Institute of Medical Research, Sydney, Australia, 6Victorian Clinical Genetics Service, Melbourne, Australia, 7Murdoch Children’s Research Institute, Melbourne, Australia, 8Department of Paediatrics, University of Melbourne, Melbourne, Australia, 9Department of Paediatric Nephrology, Royal Children’s Hospital, Melbourne, Australia, 10Department of Renal Medicine, Royal Brisbane and Women’s Hospital, Brisbane, Australia

Aim: This qualitative cross-sectional study aimed to identify genetic variation related to drug-metabolising enzymes, transporters and receptors in patients with end-stage kidney disease of unknown cause (ESKD-UC) and to determine potential gene-drug interactions that could guide medical therapy.
Background: ESKD-UC leads to significant mortality and morbidity. However, inadequate understanding of factors predicting kidney disease progression in this patient population limit options in managing personal and familial genetic risk. Optimisation of pharmacological treatment to alter disease course, complications and management are of critical importance. Whole genome sequencing, primarily used to determine a genetic basis for kidney disease in this group, may concurrently better guide drug therapy through analysis for pharmacogenomic variants.
Methods: Whole genome sequencing for diagnostic purposes was performed on blood samples of enrolled eligible patients with ESKD-UC. A clinical summary of patient-specific predicted gene-drug interactions was subsequently generated by OneOme’s RightMed test, which analyses for presence of known pharmacogenomic polymorphisms.
Results: 11 patients were genotyped, all of which had at least one genomic variant implicating hepatic enzyme activity that deviated from normal, including cytochrome P (CYP) 3A5 and CYP1A2. The median number of prescribed medications per patient was 9 and median pill burden was 16/day. Although none were prescribed drugs that had major predicted gene-drug interactions, most (n=9) had genotypes that predisposed them to potential major gene-drug interactions. While only 4 patients were taking drugs that had moderate gene-drug interactions, all had genotypes that predisposed them to some type of moderate gene-drug interactions.
Conclusions: Most patients in this group have genetic polymorphisms that predispose them to potential major/moderate gene-drug interactions. Understanding their genotype may help guide choice of drug therapy and initial medication dosing.


Biography:
Yue Ling Chung is a third year medical student at the University of Queensland. Prior to studying medicine, she had obtained her Bachelor of Science (Pharmacy) (Honours) from the National University of Singapore and had worked at the National University Hospital of Singapore as a senior pharmacist.

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