Multimorbidity, polypharmacy, and drug-drug-gene interactions following a non-ST elevation acute coronary syndrome: analysis of a multicentre observational study

Abstract

Background The number of patients living with co-existing diseases is growing. This study aimed to assess the extent of multimorbidity, medication use, and drug- and gene-based interactions in patients following a non-ST elevation acute coronary syndrome (NSTE-ACS). Methods In 1456 patients discharged from hospital for a NSTE-ACS, comorbidities and multimorbidity (≥ 2 chronic conditions) were assessed. Of these, 698 had complete drug use recorded at discharge, and 652 (the ‘interaction’ cohort) had drug use and actionable genotypes available for CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A5, DPYD, F5, SLCO1B1, TPMT, UGT1A1, and VKORC1. The following drug interactions were investigated: pharmacokinetic drug-drug (DDIs) involving CYPs (CYPs above, plus CYP1A2, CYP2C8, CYP3A4), SLCO1B1, and P-glycoprotein; drug-gene (DGIs); drug-drug-gene (DDGIs); and drug-gene-gene (DGGIs). Interactions predicted to be ‘substantial’ were defined as follows: DDIs due to strong inhibitors/inducers, DGIs due to variant homozygous/compound heterozygous genotypes, and DDGIs/DGGIs where the constituent DDI/DGI(s) both influenced the victim drug in the same direction. Results In the whole cohort, 727 (49.9%) patients had multimorbidity. Non-linear relationships between age and increasing comorbidities and decreasing coronary intervention were observed. There were 98.1% and 39.8% patients on ≥ 5 and ≥ 10 drugs, respectively (from n = 698); women received more non-cardiovascular drugs than men (median (IQR) 3 (1–5) vs 2 (1–4), p = 0.014). Overall, 98.7% patients had at least one actionable genotype. Within the interaction cohort, 882 interactions were identified in 503 patients (77.1%), of which 346 in 252 patients (38.7%) were substantial: 59.2%, 11.6%, 26.3%, and 2.9% substantial interactions were DDIs, DGIs, DDGIs, and DGGIs, respectively. CYP2C19 (49.5% of all interactions) and SLCO1B1 (18.4%) were involved in the largest number of interactions. Multimorbidity (p = 0.019) and number of drugs (p = 9.8 × 10−10) were both associated with patients having ≥ 1 substantial interaction. Multimorbidity (HR 1.76, 95% CI 1.10–2.82, p = 0.019), number of drugs (HR 1.10, 95% CI 1.04–1.16, p = 1.2 × 10−3), and age (HR 1.05, 95% CI 1.03–1.07, p = 8.9 × 10−7), but not drug interactions, were associated with increased subsequent major adverse cardiovascular events. Conclusions Multimorbidity, polypharmacy, and drug interactions are common after a NSTE-ACS. Replication of results is required; however, the high prevalence of DDGIs suggests integrating co-medications with genetic data will improve medicines optimisation.

Pharmacogenomics and circadian rhythms as mediators of cardiovascular drug-drug interactions

“…Several medications prescribed for the prevention and treatment of diseases of the cardiovascular system are highly interactive ( Table 1 ). Moreover, multi-morbidity is linked with the high prevalence of polypharmacy ( Turner et al., 2020 ). Accordingly, it is not unusual for older patients with atherosclerosis-associated ischemic heart failure to receive a sizeable combination of cardiovascular therapeutics, e.g., heart failure drugs like digoxin, a cholesterol-lowering drug like simvastatin, one or more blood pressure (BP)-lowering drugs like an angiotensin-converting enzyme inhibitor (ACEI), angiotensin II receptor blocker (ARB), beta blocker, and/or diuretic, and an antiplatelet like aspirin and an anti-coagulant such as warfarin or clopidogrel ( Turner et al., 2020 ).…”

“…Genetic factors may contribute to the vulnerability to and impacts of DDI in patients with one or multiple diseases, largely through the regulation of the DDI biological responses. Genetic polymorphisms have been demonstrated in genes coding for drug metabolizing processes, including cytochrome P450 ( Turner et al., 2020 ), or transporting proteins, such as p-glycoprotein ( Holtzman et al., 2006 ) and organic cation transporter (OCT) ( Zhou et al., 2021 ).…”

“…Pathogenic insults promote phenotypic contractile, synthetic, proliferative, and apoptotic changes of the arterial and heart tissues ( Geng, 1997 , 2001 , 2003 ; Geng and Libby, 2002 ). Drug-drug, drug-food/food supplement, or drug-genetic/epigenetic factor interactions may result in adverse impacts on the cardiovascular system ( Turner et al., 2020 ). In 1995, Leape et al.…”

Pharmacogenomics of NSAID-Induced Upper Gastrointestinal Toxicity

“…Another factor to consider is that as our population continues to age, the prevalence of multimorbidity will increase ( Uijen and van de Lisdonk, 2008 ), which will be accompanied by polypharmacy. Multimorbidity and polypharmacy increase the likelihood of drug- and gene-based interactions ( Turner and et al, 2020 ). The elderly are liable to be prescribed NSAIDs, including LDA, because of the high prevalence of cardiovascular disease and arthritis.…”

The Influence of Pharmacogenetics on the Clinical Relevance of Pharmacokinetic Drug–Drug Interactions: Drug–Gene, Drug–Gene–Gene and Drug–Drug–Gene Interactions

“…In pediatric patients, for example, the annual prescribing prevalence of at least one level A drug (recommendations for drugs available with high evidence regarding a particular genotype) ranges from 7987 to 10,629 per 100,000 patients [6]. Turner analyzed the data from non-ST elevation myocardial infarction patients (n = 1456) and found that 98.7% of the patients had at least one actionable genotype [7]. Within the interaction cohort (drug use and actionable genotypes available), 882 interactions were identified in 503 patients (77.1%), of which 346 interactions in 252 patients (38.7%) were substantial: 59.2%, 11.6%, 26.3%, and 2.9% substantial interactions were DDIs, DGIs, Drug-Drug-Gene-Interactions (DDGIs) and Drug-Gene-Gene-Interactions (DGGIs), respectively (see Table 1 for definitions).…”