Drug–Drug–Gene Interactions in Cardiovascular Medicine

Figures & data

Table 1 Example Categories of Cardiovascular Medicines/Drugs

Categories	Drug Classes and/or Examples	Main Uses
Anti-arrhythmic drugs	Class I (membrane stabilizing drugs like lidocaine, flecainide and propafenone), class II (beta blockers like esmolol, see below), class III (eg amiodarone and dronedarone) and class IV (calcium-channel blockers that are not dihydropyridines eg verapamil).	To control the ventricular rate and/or restore and maintain sinus rhythm for atrial fibrillation, ectopic beats, atrial flutter, paroxysmal supraventricular tachycardia, ventricular tachycardia or arrhythmias after myocardial infarction.
Beta-adrenoceptor blocking drugs	Propranolol, atenolol, carvedilol, metoprolol, esmolol, sotalol, nebivolol etc.	Angina, hypertension, myocardial infarction, arrhythmias, heart failure and others (thyrotoxicosis, anxiety, migraine prophylaxis, glaucoma etc).
Positive inotropic drugs	Cardiac glycosides (eg digoxin) and phosphodiesterase type-3 inhibitors (eg enoximone and milrinone).	To increase the force of myocardial contraction in conditions such as heart failure and atrial fibrillation
Anti-anginal drugs	Nitrates (eg glyceryl trinitrate and ranolazine), calcium-channel blockers (eg verapamil and dihydropyridines like nifedipine), potassium channel activators (eg nicorandil), peripheral vasodilators (eg cilostazol) and others (eg ivabradine).	Cause coronary vasodilation and/or reduce venous return/left ventricular work hence managing angina (and other conditions such as hypertension, arrhythmias and peripheral vascular disease).
Antifibrinolytics	Eg tranexamic acid.	Impair fibrin dissolution to prevent or treat bleeding associated with excessive fibrinolysis (eg thrombolytic overdose, dental extraction, surgery, traumatic hyphaemia and obstetric disorders).
Blood-related products	Includes dried human prothrombin complex (contains clotting factors IX, II, VII and X) and specific coagulation factors (eg recombinant factor VIIa/activated eptacog alfa, dried factor IX fraction and protein C concentrate).	Treatment/perioperative prophylaxis of haemorrhage in patients with congenital or acquired (including anticoagulant overdose) deficiencies of specific coagulation factors.
Calcium-channel blockers	Dihydropyridines (eg felodipine, nifedipine and amlodipine) and non-dihydropyridines (eg diltiazem and verapamil).	Angina, hypertension, subarachnoid haemorrhage and arrhythmias (verapamil).
Anticoagulants	Parenteral (eg heparin, low molecular weight heparins such as enoxaparin, heparinoids such as danaparoid and hirudins such as bivalirudin) and oral anticoagulants that include Vitamin K antagonists (eg warfarin, acenocoumarol) and direct oral anticoagulants (eg apixaban, rivaroxaban and dabigatran).	Prevent thrombus formation or extension eg in venous thromboembolism and prevention of clots due to atrial arrhythmias and prosthetic cardiac valves.
Antiplatelets	Include aspirin, clopidogrel, ticagrelor, cilostazol and others.	Prophylaxis of myocardial infarctions, reduction of thrombosis after angioplasty and coronary stenting and stroke prophylaxis after prosthetic valve replacement or in cerebrovascular ischemia
Fibrinolytics/thrombolytic agents	Human tissue plasminogen activators (alteplase), reteplase, tenecteplase, streptokinase and urokinase.	Clot resolution during myocardial infarction, thromboembolism or cerebral stroke.
Drugs affecting the renin-angiotensin system	Angiotensin-converting enzyme inhibitors like captopril, angiotensin II receptor antagonists like losartan and renin-inhibitors like aliskiren.	Used in heart failure, hypertension, diabetic nephropathy and prophylaxis of cardiovascular events.
Diuretics	Thiazides (eg bendroflumethiazide), loop diuretics (eg furosemide and torsemide), potassium-sparing diuretics and aldosterone antagonists (eg amiloride, triamterene, eplerenone and spironolactone), osmotic diuretics (eg mannitol), and carbonic anhydrase inhibitors (eg acetazolamide).	To relieve cardiovascular disease-related oedema (eg oedema due to chronic heart failure) and blood pressure (usually in lower doses).
Lipid-modifying drugs	Statins (eg atorvastatin, lovastatin, simvastatin), fibrates (eg bezafibrate, gemfibrozil), bile acid sequestrants (eg colestipol and cholestyramine) and others (eg lomitapide, nicotinic acid and omega-3 fatty acid compounds).	Altering the balance between low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides in hyperlipidaemias and prevention of cardiovascular events.

Figure 1 Continued.

Figure 1 Drug-drug, drug-gene, and drug-drug-gene interactions.^13,52 (A) Normal metabolism: expected drug exposure (black dotted line in plasma drug concentration–time curve, single exposure) for a drug/substrate that is metabolized by two cytochrome P450 (CYP) enzymes. (B) Drug–drug interaction (DDI): inhibition (eg null activity) or induction (eg increased enzyme copies) of CYP A by co-medications resulting in increased (red line in plasma drug concentration–time curve) or decreased (green line in plasma drug concentration–time curve) drug exposures, respectively. (C) Drug–gene interaction (DGI): genetic variation inactivates/reduces (loss-of-function/LoF variant) or increases (gain-of-function/GoF variant) CYP B activity resulting in increased or decreased drug exposures, respectively. (D) Drug-drug-gene interaction (DDGI): cumulative effects of comedications (DDIs) and genetic variations (DGIs). In a category 1 DDGI, a DDI and DGI on the same pathway (eg CYP A) and direction (eg inhibitor with a LOF variant) interact to significantly increase (or decrease) drug exposure while in a category 2 DDGI, the DDI and DGI act on different pathways but still in the same direction to also increase (or decrease) drug exposure. Lastly, category 3 comprises DDIs and DGIs with opposing effects (eg inhibitor with a GOF variant) that leads to increased (inhibitor effects greater than GOF variant effects), decreased (inhibitor effects lower than GOF variant effects) or unchanged (inhibitor effects similar to GOF variant effects) drug exposure. The above interactions also apply to bioactivation of prodrugs (in which decreased metabolism results in decreased systemic exposure) and other pathways (eg drug- and/or gene-mediated changes to drug transporters or drug targets). If a drug has a comparable clinical effect with its metabolites, the effects of metabolism-based DDIs, DGIs and DDGIs may not be apparent. Any compensation by CYP A for the loss (or increase) in CYP B’s activity, and vice-versa, is not depicted/accounted for in this over-simplified schematic.

Table 2 Examples of Substrates, Inducers and Inhibitors for Cytochrome P450 Isoenzymes and Transporters^a (Data from Turner et al²⁷)

Enzymes	Subtrates^b,c	Inducers^d,e	Inhibitors^f,g
CYP isoenzymes
CYP1A2	Sensitive (alosetron, caffeine, duloxetine, melatonin, ramelteon, tasimelteon, theophylline, tizanidine) Moderate sensitive (clozapine, pirfenidone, ramosetron) Other (cyclobenzaprine, fluvoxamine, haloperidol, imipramine, mexiletine, nabumetone, naproxen, olanzapine, riluzole, tacrine, triamterene, zileuton, zolmitriptan)	Moderate (phenytoin, rifampicin, ritonavir, tobacco, teriflunomide) Other (carbamazepine)	Strong (ciprofloxacin, enoxacin, fluvoxamine, zafirlukast) Moderate (methoxsalen, mexiletine, oral contraceptives) Weak (acyclovir, allopurinol, cimetidine, peginterferon 2a, piperine, zileuton) Other (amiodarone, efavirenz, ticlopidine, levofloxacin)
CYP3A4/5	Sensitive (alfentanil, avanafil, budesonide, buspirone, conivaptan, darifenacin, darunavir, dasatinib, dronedarone, ebastine, eletriptan, eplerenone, everolimus, felodipine, ibrutinib, indinavir, lomitapide, lovastatin, lurasidone, maraviroc, midazolam, naloxegol, nisoldipine, quetiapine, saquinavir, sildenafil, simvastatin, sirolimus, tacrolimus, ticagrelor, tipranavir, tolvaptan, triazolam, vardenafil) Moderate sensitive (alprazolam, aprepitant, atorvastatin, colchicine, eliglustat, pimozide, rilpivirine, rivaroxaban, tadalafil) Other (astemizole, chlorphenamine, ciclosporin, cisapride, clarithromycin, diazepam, erythromycin, nevirapine, quinidine, ritonavir, telithromycin)	Strong (carbamazepine, enzalutamide, mitotane, phenytoin, rifampicin, St. John’s wort) Moderate (bosentan, efavirenz, etravirine, modafinil) Weak (armodafinil, rufinamide) Other (nevirapine, phenobarbital, pioglitazone, rifabutin, troglitazone)	Strong (boceprevir, clarithromycin, cobicistat, conivaptan, diltiazem, grapefruit juice, idelalisib, indinavir, itraconazole, ketoconazole, nefazodone, nelfinavir, posaconazole, ritonavir, troleandomycin, voriconazole) Moderate (aprepitant, cimetidine, ciprofloxacin, clotrimazole, crizotinib, ciclosporin, dronedarone, erythromycin, fluconazole, fluvoxamine, imatinib, tofisopam, verapamil) Weak (chlorzoxazone, cilostazol, fosaprepitant, istradefylline, ivacaftor, lomitapide, ranitidine, ranolazine, tacrolimus, ticagrelor) Other (amiodarone, suboxone)
CYP2B6	Sensitive (bupropion) Moderate sensitive (efavirenz) Other (artemisinin, cyclophosphamide, ifosfamide, ketamine, meperidine, methadone, nevirapine, propofol, selegiline)	Strong (carbamazepine) Moderate (efavirenz, rifampicin, ritonavir) Weak (nevirapine) Other (artemisinin, phenobarbital, phenytoin)	Weak (clopidogrel, tenofovir, ticlopidine, voriconazole) Other (thiotepa)
CYP2C8	Sensitive (repaglinide) Moderate sensitive (montelukast, pioglitazone, rosiglitazone) Other (amodiaquine, paclitaxel, torsemide)	Moderate (rifampicin)	Strong (clopidogrel, gemfibrozil) Moderate (deferasirox, teriflunomide) Weak (telithromycin, trimethoprim) Other (montelukast)
CYP2C9	Sensitive (celecoxib) Moderate sensitive (glimepiride, phenytoin, tolbutamide, warfarin) Other (diclofenac, fluvastatin, glibenclamide, glipizide, ibuprofen, irbesartan, losartan, naproxen, piroxicam, rosiglitazone, torsemide, valproic acid, zafirlukast)	Moderate (aprepitant, carbamazepine, enzalutamide, rifampicin, ritonavir) Other (nevirapine, phenobarbital, St. John’s wort)	Moderate (amiodarone, felbamate, fluconazole, miconazole, piperine) Weak (diosmin, disulfiram, fluvastatin, fluvoxamine, voriconazole) Other (efavirenz, isoniazid, metronidazole, paroxetine, sulfamethoxazole)
CYP2C19	Sensitive (omeprazole, mephenytoin) Moderate sensitive (diazepam, lansoprazole, rabeprazole, voriconazole) Other (amitriptyline, carisoprodol, citalopram, clomipramine, clopidogrel, cyclophosphamide, esomeprazole, imipramine, labetalol, pantoprazole, phenobarbital, phenytoin, proguanil)	Strong (rifampicin, ritonavir) Moderate (efavirenz, enzalutamide, phenytoin) Other (St. John’s Wort)	Strong (esomeprazole, fluconazole, fluoxetine, fluvoxamine, omeprazole, ticlopidine) Weak (voriconazole) Other (cimetidine, felbamate, isoniazid, ketoconazole, lansoprazole, oral contraceptives, pantoprazole)
CYP2D6	Sensitive (atomoxetine, desipramine, dextromethorphan, eliglustat, nebivolol, nortriptyline, perphenazine, tolterodine, venlafaxine) Moderate sensitive (amitriptyline, encainide, imipramine, metoprolol, propafenone, propranolol, tramadol, trimipramine) Other (aripiprazole, carvedilol, clomipramine, codeine, desipramine, doxepin, duloxetine, flecainide, fluoxetine, haloperidol, mexiletine, ondansetron, oxycodone, paroxetine, risperidone, tamoxifen, thioridazine, timolol)	–	Strong (bupropion, fluoxetine, paroxetine, quinidine, terbinafine) Moderate (cinacalcet, duloxetine, fluvoxamine, mirabegron) Weak (abiraterone, amiodarone, celecoxib, cimetidine, clobazam, cobicistat, desvenlafaxine, escitalopram, labetalol, lorcaserin, ritonavir, sertraline, vemurafenib) Other (aripiprazole, chlorphenamine, clomipramine, diphenhydramine, doxepin, haloperidol, methadone)
Transporters
ABCB1 (P-gp)	Actinomycin D, aliskiren, ambrisentan, apixaban, atorvastatin, bepridil, berberine, celiprolol, ciclosporin, cimetidine, ciprofloxacin, clopidogrel, colchicine, dabigatran, daunorubicin, digoxin, diltiazem, domperidone, doxorubicin, edoxaban, erythromycin, etoposide, everolimus, fexofenadine, imatinib, irinotecan, ivermectin, labetalol, lapatinib, lidocaine, loperamide, losartan, lovastatin, maraviroc, methotrexate, mitomycin c, nadolol, nilotinib, ondansetron, paclitaxel, posaconazole, propranolol, quinine sulfate, rifampicin, rivaroxaban, saxagliptin, tacrolimus, talinolol, taxol, terfenadine, ticagrelor, timolol, tolvaptan, topotecan, verapamil, vinblastine, vincristine, warfarin	Strong (carbamazepine, dexamethasone, doxorubicin, phenytoin, rifampicin, St. John’s wort) Others (ciclosporin, tipranavir, venlafaxine)	Strong (amiodarone, carvedilol, dronedarone, itraconazole, lopinavir and ritonavir, quinidine, ritonavir, saquinavir, verapamil) Others (clarithromycin, lapatinib, propafenone, ranolazine, telaprevir, tipranavir)
SLCO1B1	Asunaprevir, atorvastatin, bosentan, danoprevir, docetaxel, fexofenadine, glibenclamide, nateglinide, paclitaxel, pitavastatin, pravastatin, repaglinide, rosuvastatin, simvastatin	-	Strong (atazanavir and ritonavir, ciclosporin, lopinavir and ritonavir, rifampicin) Others (clarithromycin, erythromycin, gemfibrozil, simeprevir)

Notes: ^aDrugs in bold are cardiovascular medicines. ^bSensitive and moderate-sensitive substrates are taken from the Food and Drug Administration (FDA) table of substrates, inhibitors and inducers.⁴⁴ Sensitive and moderate-sensitive substrates experience areas under the concentration–time curve (AUC) increments of ≥5 and ≥2 to <5-fold with strong index inhibitors of a given metabolic pathway, respectively. The substrates that are not present in the FDA table but are listed in the Indiana Flockhart Table TM⁴⁵ are categorized under “Other”. ^cSubstrates for transporters taken from the FDA tables,⁴⁴ and Wessler et al⁴⁶ d Strong, moderate and weak inducers, taken from the FDA tables,⁴⁴ decrease the AUC of sensitive index substrates of a given metabolic pathway by ≥80%, ≥50% to <80%, and ≥20% to <50%, respectively. “Other” inducers are those not present in the FDA table but are listed in the Indiana Flockhart Table^{TM. e}P-gp inducers from Wessler et al⁴⁶ with the assessment of strength of P-gp inducers from Appendix A of the British Columbia guidelines on Potential NOAC Drug Interactions.⁴⁷ Strong, moderate and weak inhibitors increase the AUC of sensitive index substrates of a given metabolic pathway by ≥5-fold, ≥2 to <5-fold, and ≥1.25 to <2-fold, respectively. They were all taken from the FDA tables,⁴⁴ except for (es)omeprazole designated as strong CYP2C19 inhibitors based on the Indiana Flockhart Table TM⁴⁵ and Modak et al⁴⁸ “Other” inhibitors are those not present in the FDA table but are listed in the Indiana Flockhart Table^TM, and whose inhibitory strength is not yet confirmed. ^gTransporter inhibitors taken from the FDA tables,⁴⁴ with strength assessment taken from Wessler et al⁴⁶ and Appendix A of the British Columbia guidelines on Potential NOAC Drug Interactions.⁴⁷

Abbreviations: ABCB1 (P-gp), ATP Binding Cassette Subfamily B Member 1 (P-glycoprotein 1); AUC, area under the concentration–time curve; CYP, Cytochrome P450; SLCO1B1, Solute Carrier Organic Anion Transporter Family Member 1B1.

Figure 2 Commonly used medications influenced by pharmacogenes. The bar chart shows the total number of prescriptions (top panel) or patients receiving the prescriptions (bottom panel) in 2019 in the United States. Corresponding ranks are shown in parentheses. Data from the ClinCalc DrugStats Database⁴⁰ that used the Medical Expenditure Panel Survey 2013–2019 (Agency for Healthcare Research and Quality) as a prescription data source.

Table 3 A Summary of Clinical Implementation Pharmacogenetic Guidelines for Cardiovascular Drugs (Data from Abdullah-Koolmees^a et al)³⁰

Drug Class	Drug	Guidelines	Genes/Genetic Variants	Recommendation (Evidence Classification^b)
Anticoagulants	Acenocoumarol	DPWG	VKORC1 −1639G>A	AA: reduce dose by 50% and check INR more frequently. Initial and maintenance doses can be calculated using an algorithm (4F). AG: no action required (4C).
	Phenprocoumon	DPWG	VKORC1 −1639G>A	AA: reduce dose by 50% and check INR more frequently. For patients younger than 75 years, initial and maintenance doses can be calculated using an algorithm, as done by EUPACT (4D). AG: no action required (4D).
	Warfarin	CPIC	Non-Africans: CYP2C9*2, CYP2C9*3, VKORC1 −1639G>A	Use Gage and IWPC dosing algorithms (Strong/Moderate).
			African: CYP2C9*2, CYP2C9*3, VKORC1 −1639G>A
			African carriers of CYP2C9*5, *6, *8 or *11	Decrease calculated dose by 15–30%; 20–40% in variant homozygotes (Moderate).
			African carriers of the CYP2C rs12777823 A allele	Decrease calculated dose by 10–25% (Moderate).
			CYP4F2*3	Increase calculated dose by 5–10% (Optional).
		CPNDS	CYP2C9*2, CYP2C9*3, VKORC1 −1639G>A	Calculate dose based on www.warfarindosing.org (++++, Moderate).
		DPWG	CYP2C9	*1*3, *2*2, *2*3, *3*3: use 20–65% of the standard initial dose. Initial and maintenance doses can be calculated using an algorithm, as done by EUPACT (4A-D).
			VKORC1 −1639G>A	AA: use 60% of the standard initial dose. Initial and maintenance doses can be calculated using an algorithm, as done by EUPACT (4A). AG: no action required (4A).
		RNPGx	CYP2C9*2, CYP2C9*3, VKORC1 −1639G>A	As per dosing table (Advisable).
Antiplatelets	Clopidogrel	CPIC	CYP2C19	PM/IM: Use alternative antiplatelet non-contraindicated drug such as prasugrel or ticagrelor (Strong/Moderate). UM: Dosage and administration as per drug label (Strong).
		DPWG	CYP2C19	PM: for PCI, stroke or TIA, avoid clopidogrel and consider alternatives such as prasugrel, ticagrelor and aspirin/dipyridamole while for other indications, determine the level of inhibition of platelet aggregation and consider alternatives in poor responders (4F). IM: for PCI, stroke or TIA, choose an alternative or double the dose to 150 mg/day (600 mg loading dose) while for other indications, no action required (4F). UM: no action required (4A).
		RNPGx	CYP2C19	PM/IM: Use alternative drug, not metabolized by CYP2C19 (Essential). UM: Use as per standard of care ie 75mg/day (Essential).
Anti-arrhythmics (class I, membrane stabilizing drugs)	Flecainide	DPWG	CYP2D6	PM: reduce dose by 50%, record ECG, and monitor plasma concentrations (4F). IM: for the diagnosis of Brugada syndrome, no action required; otherwise reduce dose by 25%, record ECG, and monitor plasma concentrations (3A). UM: record ECG and monitor plasma concentration or select alternative drug eg, amiodarone, disopyramide, quinidine, and sotalol (not available).
	Propafenone	DPWG	CYP2D6	PM: reduce dose by 70%, record ECG, and monitor plasma concentrations (4C). IM/UM: adjust dose based on plasma concentrations and record ECG or select alternative drug eg, amiodarone, disopyramide, quinidine, sotalol (3A/3D).
Beta-blockers	Metoprolol	DPWG	CYP2D6	PM: if a gradual heart rate reduction is required or if there is symptomatic bradycardia, gradually increase dose up to 25% of the standard dose (4C). IM: if a gradual heart rate reduction is required or if there is symptomatic bradycardia, gradually increase dose up to 50% of the standard dose (4A). UM: use the maximum dose for the relevant indication or titrate dose up to 250% of normal dose or use alternative drugs eg bisoprolol or carvedilol for heart failure, and atenolol or bisoprolol for other indications (4D).
HMG-CoA reductase inhibitors (statins)	Eg atorvastatin, simvastatin	CPIC	SLCO1B1	Low/intermediate function: for simvastatin, prescribe a lower dose, consider an alternative statin like pravastatin/rosuvastatin and consider routine creatine kinase surveillance (Strong).
		DPWG	SLCO1B1	*1*5, *5*5 (atorvastatin): If patient has additional risk factors for statin-induced myopathy, choose alternative drugs fluvastatin. If patient has no additional risk factors or an alternative is not an option, then advise the patient to contact their doctor when muscle symptoms occur (4C). *1*5, *5*5 (simvastatin): consider additional risk factors for statin-induced myopathy to choose an alternative. If an alternative is not an option, avoid doses exceeding 40mg/day and advise the patient to contact their doctor when muscle symptoms occur (4D).
		RNPGx	SLCO1B1	*1*5: High dose statins and OATP1B1/CYP3A4 inhibitors should be avoided (Possibly helpful). *5*5: High dose statins and OATP1B1/CYP3A4 inhibitors should be avoided. Lower simvastatin dose to 20 mg/day with creatine phosphokinase assay or use another statin (Possibly helpful).

Notes: ^aThese guidelines were accurate as of 1 July 2020, and some may have been updated. For instance, the CPIC Clopidogrel⁷⁸ guideline now considers additional phenotypes such as CYP2C19 likely intermediate metabolizer and CYP2C19 likely poor metabolizer while the statin guideline⁸⁰ now considers ABCG2 and CYP2C9 genotypes. ^bCPIC has three recommendation levels for genotype/phenotype-drug pairs (strong, moderate, and optional); CPNDS has four levels of evidence (+ to ++++), and three levels for genotyping recommendations (strong, moderate, and optional); DPWG has five (0–4) levels of evidence and eight for clinical relevance (AA to F); and RNPGx has three levels for genotyping recommendations (essential, advisable, and possibly helpful).

Abbreviations: ABCB1 (P-gp), ATP Binding Cassette Subfamily B Member 1 (P-glycoprotein 1); CPIC, Clinical Pharmacogenetics Implementation Consortium; CPNDS, Canadian Pharmacogenomics Network for Drug Safety; CYP, Cytochrome P450; DPWG, Dutch Pharmacogenetics Working Group; EU-PACT, European Pharmacogenetics of Anticoagulant Therapy; HMG-CoA, β-Hydroxy β-methylglutaryl-Coenzyme A; IM, intermediate metabolizer; IWPC, International Warfarin Pharmacogenetics Consortium; PCI, percutaneous coronary intervention; PM, poor metabolizer; RM, rapid metabolizer; RNPGx, French National Network (Réseau) of Pharmacogenetics; SLCO1B1, Solute Carrier Organic Anion Transporter Family Member 1B1; TIA, Transient Ischaemic Attack; UM, ultra-rapid metabolizer; VKORC1, Vitamin K epOxide Reductase Complex 1.

Table 4 Examples of Drug–Drug–Gene Interactions Involving Cardiovascular medicines^15,31,83

Victim Drugs/Substrates	Perpetrator Drugs (Inhibitors^a/Inducers)	Relevant Genotype	Effects	References
Category 1 (similar effects, same pathway eg CYP2C9 inhibitor with CYP2C9 RoF/LoF mutation)
CYP2C9-mediated
Fluvastatin	Telmisartan	CYP2C9*1/*3	Myotoxicity.	[84]
Losartan	Phenytoin, valproic acid	CYP2C9*2/*3	Inhibition of the conversion of losartan to its active metabolite E3174.	[85,86]
Vitamin-k antagonists (eg acenocoumarol, warfarin)	Amiodarone, clopidogrel, pantoprazole, losartan, fluconazole, fluoxetine, irbesartan, fluvastatin, metronidazole, NSAIDs, simvastatin	CYP2C9*2/*3	Over-anticoagulation, decreased dose requirements, increased bleeding risks.	[82,87–92]
CYP2C19-mediated
Clopidogrel	Proton-pump inhibitors	CYP2C19*2/*3	Reduction of antiplatelet effect/increased clopidogrel resistance in poor metabolizers.	[93–95]
Omeprazole	Antiplatelets (clopidogrel, ticlopidine)	CYP2C19*2/*3	Increased AUC, especially for *1*1^b.	[96,97]
Warfarin	Proton-pump inhibitors (lansoprazole, omeprazole)	CYP2C19*2/*3	Warfarin potentiation and increased bleeding risks, increased AUC (especially for *1*1)^b for R- but not S-warfarin.	[98,99]
CYP2D6-mediated^c
Brofaromine, dextromethorphan, encainide, methoxyphenamine, mexiletine, procainamide, propafenone, R-flecainide, venlafaxine	Quinidine	CYP2D6 poor and/or intermediate metabolizers	Increased AUC and/or decreased clearance, especially for normal metabolizers^b.	[100–112]
Flecainide	Amiodarone, paroxetine	CYP2D6 poor and/or intermediate metabolizers	Increased AUC, increased QT interval corrected using the Fridericia formula, or increased flecainide-induced QRS prolongation, especially for normal metabolizers^b.	[113–115]
Lidocaine, mexiletine	Propafenone	CYP2D6 poor and/or intermediate metabolizers	Increased AUC and/or decreased clearance, especially for normal metabolizers^b.	[116,117]
Metoprolol	Amiodarone, celecoxib, diphenhydramine, dronedarone, hydroxychloroquine, imatinib, propafenone, terbinafine.	CYP2D6 poor and/or intermediate metabolizers	Increased AUC and/or decreased clearance, especially for normal metabolizers^b and/or increased clinical and adverse effects (eg sinus bradycardia, confusion, falls, tiredness and dyspnea on exertion).	[118–127]
CYP3A-mediated
Simvastatin	Cyclosporine, diltiazem	CYP3A5*3/*3 and CYP3AP1*3/*3	Myopathy.	[128,129]
SLCO1B1-mediated
Pravastatin	Cyclosporine	SLCO1B1 c.521 T>C	Increased AUC, especially for the TT genotype^b.	[130]
Category 2 (similar effects, multiple pathways eg CYP3A4 inhibitor with CYP2C19 LoF mutation)
Atorvastatin	Pantoprazole (CYP2C19 and CYP3A4/5 inhibitor)	CYP2C19*2*2	Rhabdomyolysis and acute renal failure.	[131]
Diazepam	Diltiazem (CYP3A4 inhibitor)	CYP2C19*2/*3	Increased AUC and prolonged elimination diazepam half-life in all genotypes.	[132]
Caffeine	Propafenone (CYP2D6 and CYP1A2 inhibitor)	CYP2D6 poor metabolizers	Decreased clearance (increase in caffeine plasma concentrations) especially in poor metabolizers.	[133]
Category 3 (opposing effects)
Clopidogrel	Proton-pump inhibitors (CYP2C19 inhibitors)	CYP2C19*17 (GoF)	Higher rates of cardiac rehospitalization due to decreased clopidogrel efficacy (in this case, the effects of the inhibitors were stronger than the genetic influence).	[95]
Propafenone	Rifampicin (CYP3A4/1A2 inducer)	CYP2D6 poor metabolizers (LoF)	Decreased AUC for all genotypes (effects of the inducer stronger than those of the genetic mutation), with the percentage decrease more pronounced in normal metabolizers (no genetic mutation to offset some of the effects of the inducer).	[134]
Warfarin	Rifampicin (CYP2C9 inducer)	CYP2C9*2/*3 (RoF)	Higher changes in S-warfarin clearance for *2*3 and *3*3 subjects (effects of the inducer more pronounced in poor metabolizers).	[92]

Notes: Data from references^15,31,83. ^aInhibitors include other substrates (competitive inhibitors). ^bMutant-type genotypes or poor/intermediate metabolizers have high drug exposure (high AUC or low clearance) to start with, so the effect of adding inhibitors (increase in AUC or decrease in clearance) is less pronounced compared to wild-type genotypes or normal/extensive metabolizers. In terms of the absolute effects, poor/intermediate metabolizers have the highest drug exposures, with or without the inhibitors. When normal/extensive metabolizers are given strong inhibitors, the actual/observed phenotype is that of a poor/intermediate metabolizer resulting into phenocopies or phenoconversion. ^cFor CYP2D6, normal metabolizers included two normal function alleles (eg CYP2D6*1/*1, CYP2D6*1/*2, CYP2D6*2/*2), or a normal function allele combined with a decreased function allele (eg CYP2D6*1/*10, CYP2D6*1/*41, CYP2D6*2/*10, CYP2D6*2/*41); intermediate metabolizers consisted of one normal function allele combined with no function allele (eg CYP2D6*1/*3, CYP2D6*1/*4, CYP2D6*1/*5, CYP2D6*1/*6, CYP2D6*1/*21, CYP2D6*2/*3, CYP2D6*2/*4, CYP2D6*2/*5), or two decreased function alleles (eg CYP2D6*10/*41, CYP2D6*10/*10) or one decreased function allele combined with no function allele (eg CYP2D6*3/*41, CYP2D6*4/*41, CYP2D6*5/*10, CYP2D6*6/*10, CYP2D6*6/*41, CYP2D6*10/*21, CYP2D6*10/*30); poor metabolizers consisted of two no function alleles (eg CYP2D6*3/*4, CYP2D6*4/*4, CYP2D6*4/*5, CYP2D6*4/*6, CYP2D6*5/*5, CYP2D6*5/*16, CYP2D6*7/*7); while ultra-rapid metabolizers consisted of two increased function alleles or more than two normal function alleles (eg CYP2D6*1/*1xN, CYP2D6*1/*2xN, CYP2D6*1/*4xN, CYP2D6*1/*41xN, CYP2D6*2/*2xN).

Abbreviations: AUC, area under the concentration–time curve; GoF, Gain-of-Function; CYP, Cytochrome P450; LoF, Loss-of-Function; RoF, Reduction-of-Function; SLCO1B1, Solute Carrier Organic Anion Transporter Family Member 1B1.

Box 1 Minimizing Drug–Drug Interactions (DDIs)¹⁸

Be aware of DDIs and how to detect them, especially those that are clinically relevant. Avoid unnecessary polypharmacy with tools such as STOPP/START,^Citation178 ensure an accurate drug history to identify all drugs (including over-the-counter medicines, some dietary elements and herbal therapies)^Citation179 and deprescribe if necessary. Use appropriate reference sources (eg the British National Formulary) and available decision support systems. Appropriately monitor drug therapy eg conduct therapeutic drug monitoring for high-risk drugs like those with a low therapeutic index. Conduct pharmacogenetic testing for clinically actionable variants like those in Table 3. Take advice from clinical pharmacists. Report DDI-implicated adverse drug reactions to regulatory authorities, since continual surveillance of approved drugs helps to discover safety concerns that may have been missed before marketing approval.

Table 5 Proposed Solutions to Clinical Practice Challenges

Challenges Related to	Proposed Solutions
Drug information compendia, interaction databases and clinical implementation guidelines	These resources should expand their scope to include DDGIs and other complex interactions. Existing and future guidance should work towards harmonization to, among other things, reduce clinician fatigue. Since these resources require a solid evidence-base to be clinically impactful, more studies exploring and quantifying DDGIs and other complex interactions are urgently required.
Electronic decision support tools	More research should help to identify clinically relevant interactions, which should enable the prioritization of DDIs/DGIs/DDGIs to include in electronic decision support tools and hopefully decrease alert fatigue (irrelevant interactions not included, fewer discrepancies between predicted and actual interactions). To reduce on the overriding of DDI/DGI/DDGI alerts, clinicians should be educated on the importance and cost-effectiveness of using electronic decision support tools as reduced hospitalizations and substantial savings due to a reduction in interaction-mediated adverse drug events is beneficial to all stakeholders.
DGI (and consequently DDGI) implementation	The Royal College of Physicians and British Pharmacological Society, among others, recommended:^Citation161 Clinical service designs that consider current healthcare system and staffing challenges, Establishment of national standardized consenting recommendations/guidelines, Panel-based pharmacogenetic testing with consideration of point-of-care testing, Tailored clinical pharmacogenomics guidance, Centralized funding, Upskilling of healthcare prescribers in pharmacogenomics and personalized medicine, Improving clinical governance and oversight, Involvement of all stakeholders, including patients, and, Conducting collaborative, inclusive and multidisciplinary research.
Real-world evidence and “big data”	Follow current guidance with regard to how to best use real-world evidence. For example, the REporting of studies Conducted using Observational Routinely collected health Data (RECORD) statement can help researchers streamline the design, conduct and reporting of routinely collected real-world data, which should minimize bias and improve the accuracy/validity and completeness of reported findings.^Citation163,Citation164 Resources such as the HDR UK Phenotype Library (https://phenotypes.healthdatagateway.org/) are providing validated phenotyping algorithms that can be used to more accurately extract data from medical records using clinical codes such as the International Classification of Diseases, while existing techniques such as physiological-based pharmacokinetic modelling and simulation can be employed to predict DDGIs in these studies. For instance, one predictor tool (https://www.ddi-predictor.org/) can incorporate DDIs and DGIs mediated by CYP3A4, CYP2D6, CYP2C9, CYP2C19 and CYP1A2 as well as hepatic function (cirrhosis) to predict DDGIs that can be compared with actual patient outcomes, including adverse drug events.^Citation15,Citation180–182 For polygenic interactions, where multiple genes contribute to a DGI or DDGI, polygenic risk scores that sum up the influence of several genetic factors on drug-related outcomes into a single score can also be employed.^Citation183 Any signals obtained from such studies will need to be replicated in external cohorts and/or be examined further in clinical trials and/or mechanistic studies.^Citation18
Clinically-relevant endpoints	To overcome the issue of incompleteness of electronic health records when it comes to clinically relevant endpoints, validated phenotyping algorithms that extract information from multiple sources can be used. For instance, the CALIBER Bleeding phenotype (https://www.caliberresearch.org/portal/phenotypes/bleeding)^Citation184 uses clinical codes from multiple-sources including primary care (Clinical Practice Research Datalink), secondary care (Hospital Episode Statistics/hospital admission data) and the national death registry to identify patients who suffered a bleeding event. Where clinically relevant endpoints cannot be used (for example, when a drug is relatively novel and its adverse effect profile is not well known), surrogate/alternative endpoints such as prescribing behaviour or maintenance dose can be used. For example, Malki et al used three Scottish cohorts and the UK Biobank (with linked electronic healthcare records) to identify novel DGIs for 50 most commonly used drugs and 162 variants in 35 genes involved in drug pharmacokinetics.^Citation185 In addition to an efficacy endpoint (systolic blood pressure reduction), they used two phenotypes based on prescribing behaviour (drug-stop and dose-decrease, which are proxies for altered efficacy or tolerability), which enabled them to replicate 11 known DGIs and identify eight novel ones. On the other hand, McInnes and Altman searched the UK Biobank for DGIs among 200 drugs and 9 genes using maintenance dose (the average milligrams of drug per day for the last five prescriptions of each drug) and differential drug response phenotypes (diagnosis codes in primary care data, eg risk of developing a specific side effect).^Citation186
Pre-emptive genotyping	It is recommended to use existing pharmacogenetic implementation guidelines and/or prescribing information from regulatory agencies to choose the genetic variants to include on a panel to use for pre-emptive genotyping,^Citation161 as was recently demonstrated.^Citation167 Specifically, Van der Wouden et al based on actionable DPWG guidelines to include 58 genetic variants located within 14 genes (CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A5, DPYD, F5, HLA-A, HLA-B, NUDT15, SLCO1B1, TPMT, UGT1A1, and VKORC1) on a panel they called a pharmacogenetics passport. This panel can be used to optimize drug prescribing for 49 commonly prescribed drugs, including nine (18.4%) cardiovascular medicines (namely acenocoumarol, atorvastatin, clopidogrel, flecainide, metoprolol, phenprocoumon, propafenone, simvastatin, and warfarin).^Citation167 The cost-effectiveness of pre-emptive genotyping for cardiovascular medicines is an area that requires further research.
Ethnic diversity	Interaction studies should ensure that the different races/ethnicities are adequately represented, which should decrease the discordance in clinical utility studies, improve translation to the clinic and reduce health inequalities.^Citation169 Underrepresented populations may be exposed to different drugs or DDIs. For instance, some of the underrepresented populations are more reliant on herbal treatment due to easier availability and cheaper cost, which increases the prevalence of herb–drug interactions, including those in the cardiovascular field, in these populations,^Citation187 which further emphasizes the importance of conducting trials in these underserved populations and/or ensuring that they are well represented in future trials.

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