{"id":{"repo_id":"dundee","oai_identifier":"oai:discovery.dundee.ac.uk:studenttheses/eb4972a3-eb33-4047-9840-07ab875f4e20"},"canonical_url":"https://search.dev.ndltd.org/etd/dundee/oai:discovery.dundee.ac.uk:studenttheses/eb4972a3-eb33-4047-9840-07ab875f4e20","repository":{"repo_id":"dundee","name":"University of Dundee","base_url":"https://discovery.dundee.ac.uk/ws/oai"},"display":{"title":"Clinical Drug-Gene and Drug-Drug-Gene Interactions for the Most Commonly Used Chronic Drugs in the UK","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.","abstract_html":"<b>Objectives</b>: 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.<b><br/></b><b><br/></b><b>Methods</b>: 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.<b><br/></b><b><br/></b><b>Results</b>: 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)).<br/><br/>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.<br/><br/>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.<b><br/></b><b><br/></b><b>Conclusion</b>: 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.","abstract_has_math":false,"creators":["Malki, Mustafa Adnan"],"institution":"University of Dundee","degree_name":"Doctor of Medicine","degree_level":"Doctoral Thesis","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Pearson, Ewan","Brown, Andrew"],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021","date_published":"2021","updated_at":"2026-07-24T02:08:59Z","subjects":["Pharmacogenomics","Pharmacokinetics","Clinical pharmacology","Drug-gene interactions","Commonly used drug"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["oai:discovery.dundee.ac.uk:studenttheses/eb4972a3-eb33-4047-9840-07ab875f4e20"],"render_values":[{"text":"oai:discovery.dundee.ac.uk:studenttheses/eb4972a3-eb33-4047-9840-07ab875f4e20","href":null,"code":true}]}]},"links":{"outbound_url":"https://discovery.dundee.ac.uk/en/studentTheses/eb4972a3-eb33-4047-9840-07ab875f4e20","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Pearson, Ewan","Brown, Andrew"]},{"key":"dc:contributor.sponsor","label":"Sponsor","values":["Kingdom of Saudi Arabia"]},{"key":"dc:creator","label":"Author","values":["Malki, Mustafa Adnan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2021"]},{"key":"dc:date.issued","label":"Date","values":["2021"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Population Health and Genomics"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Dundee"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://discovery.dundee.ac.uk/en/studentTheses/eb4972a3-eb33-4047-9840-07ab875f4e20"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Doctoral Thesis"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["Doctor of Medicine"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Pharmacogenomics","Pharmacokinetics","Clinical pharmacology","Drug-gene interactions","Commonly used drug"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["oai:discovery.dundee.ac.uk:studenttheses/eb4972a3-eb33-4047-9840-07ab875f4e20","https://discovery.dundee.ac.uk/en/studentTheses/eb4972a3-eb33-4047-9840-07ab875f4e20"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://discovery.dundee.ac.uk/files/57075052/1.2_Final_PhD_Thesis_DGIs_and_DDGIs_for_commonly_used_drugs.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["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."]},{"key":"dc:title","label":"Title","values":["Clinical Drug-Gene and Drug-Drug-Gene Interactions for the Most Commonly Used Chronic Drugs in the UK"]}]}],"canonical_facts":{"dc:contributor.advisor":["Pearson, Ewan","Brown, Andrew"],"dc:contributor.sponsor":["Kingdom of Saudi Arabia"],"dc:creator":["Malki, Mustafa Adnan"],"dc:date":["2021"],"dc:date.issued":["2021"],"dc:description.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."],"dc:identifier":["oai:discovery.dundee.ac.uk:studenttheses/eb4972a3-eb33-4047-9840-07ab875f4e20","https://discovery.dundee.ac.uk/en/studentTheses/eb4972a3-eb33-4047-9840-07ab875f4e20"],"dc:identifier.uri":["https://discovery.dundee.ac.uk/files/57075052/1.2_Final_PhD_Thesis_DGIs_and_DDGIs_for_commonly_used_drugs.pdf"],"dc:language":["eng"],"dc:publisher.department":["Population Health and Genomics"],"dc:publisher.institution":["University of Dundee"],"dc:relation.isreferencedby":["https://discovery.dundee.ac.uk/en/studentTheses/eb4972a3-eb33-4047-9840-07ab875f4e20"],"dc:subject":["Pharmacogenomics","Pharmacokinetics","Clinical pharmacology","Drug-gene interactions","Commonly used drug"],"dc:title":["Clinical Drug-Gene and Drug-Drug-Gene Interactions for the Most Commonly Used Chronic Drugs in the UK"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["Doctoral Thesis"],"dc:type.qualificationname":["Doctor of Medicine"]},"updated_at":"2026-07-24T02:08:59Z"}