Clinical Drug-Gene and Drug-Drug-Gene Interactions for the Most Commonly Used Chronic Drugs in the UK

  • Mustafa Adnan Malki

Student thesis: Doctoral ThesisDoctor of Medicine

Abstract

Objectives: In the present project, I attempted to uncover novel and clinically important drug-gene interactions (DGIs) and drug-drug-gene interactions (DDGIs) among 50 commonly used chronic drugs and 50 commonly used chronic drug combinations in the UK.

Methods: Using the UK Biobank (cross-sectional) cohort and 3 other Scottish cohorts (longitudinal), I have studied the association of 162 genetic variants in important genes with three drug response phenotypes for the 50 selected drugs/combinations. This has generated a total of 48,600 findings divided equally between the two studies (DGIs and DDGIs), which I have made accessible via two online databases. I then undertook further replication for our top findings utilizing the UK Biobank primary care data.

Results: We identify 8 novel associations after Bonferroni correction, 3 of which are replicated or validated in the UK biobank or have other supporting results: The C-allele at rs4918758 in CYP2C9 was associated with a 25% (15-44%) lower odds of dose reduction of quinine, p=1.6×10-5; the A-allele at rs9895420 in ABCC3 was associated with a 46% (24-62%) reduction in odds of dose reduction with doxazosin, p=1.2×10-4, and altered blood pressure response in the UK Biobank; the CYP2D6*2 variant was associated with a 30% (18 %- 40%) reduction in odds of stopping ramipril treatment, p=1.01×10-5, with similar results seen for enalapril and lisinopril and with other CYP2D6 variants.I have also detected two other novel findings with directionally consistent results in the replication cohort with p-values close to significance levels (amlodipine- rs868853 (ABCC4)-lower odds for daily dose reduction and clopidogrel-rs12353214 (PTGS1)-decreased drug stopping risk)).

In addition, out of 3 novel DDGIs, one association was validated using an alternative phenotype in UK Biobank. In the discovery cohort, carrying the G allele at rs9516519 (T>G) variant in ABCC4 transporter was linked with a 4.72 (2.44-9.13) times increased risk of stopping bisoprolol or atorvastatin treatments when they were used concomitantly (p=1.48 × 10-5). In the replication cohort, this drug combination was associated with a great SBP reduction (~ 8 mmHg drop in mean SBP (p < 2 × 10-16)) and the presence of the rs9516519 (T>G) variant increased this effect.

Finally, 19 DG associations were identified that replicated previous study findings including but not limited to the association of CYP2C9*3 with increased gliclazide side effects and the association of CYP2C8*3 with reduced pioglitazone efficacy. We also report some other novel and potentially important associations from both the DG and DDG interaction studies.

Conclusion: The work in this thesis highlights the value of using large population datasets for pharmacogenomic discovery and has identified novel findings that may impact on clinical care.
Date of Award2021
Original languageEnglish
SupervisorEwan Pearson (Supervisor) & Andrew Brown (Supervisor)

Keywords

  • Pharmacogenomics
  • Pharmacokinetics
  • Clinical pharmacology
  • Drug-gene interactions
  • Commonly used drug

Cite this

'