AbstractObjectives: 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 Award||2021|
|Supervisor||Ewan Pearson (Supervisor) & Andrew Brown (Supervisor)|
- Clinical pharmacology
- Drug-gene interactions
- Commonly used drug