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Article

Associations between Suspected Adverse Drug Reactions of HMG-CoA Reductase Inhibitors and Polypharmacology Using a National Registry Approach

by
Hasan Yousaf
and
Alan M. Jones
*
School of Pharmacy, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
*
Author to whom correspondence should be addressed.
Pharmacoepidemiology 2024, 3(3), 241-251; https://doi.org/10.3390/pharma3030016
Submission received: 20 April 2024 / Revised: 13 June 2024 / Accepted: 28 June 2024 / Published: 3 July 2024
Versions Notes

Abstract

:
Aims: The aim of this study was to explore the suspected adverse drug reaction (ADR) data of five licensed statins in the UK: atorvastatin, fluvastatin, pravastatin, rosuvastatin, and simvastatin. A secondary aim was to determine if there are any associations between the polypharmacological properties of the statins and their associated muscle-related side effects. Methods: The chemical database of bioactive molecules with drug-like properties, European Molecular Biology Laboratory (ChEMBL), was used to obtain data on the pharmacological interactions of statins with human proteins. The Medicines and Healthcare Products Regulatory Agency’s (MHRA) Yellow Card scheme was used to obtain reports of suspected ADRs from 2018 to 2022. The OpenPrescribing database was used to obtain the prescribing rates for statistical interpretation. Results: The study found no significant difference between the statins association with suspected ADRs across all organ classes (X2, p > 0.05). Fluvastatin was found to have a higher incidence of ADRs/100,000 Rx across multiple system organ classes. Conclusions: No significant difference was found between the suspected ADR incidence of the statins across all system organ classes.

1. Introduction

Statins are a group of lipid-lowering drugs that act by inhibiting 3-hydroxy-3-methylglutaryl (HMG)-coenzyme A reductase, the rate-limiting enzyme for the synthesis of mevalonic acid from HMG-coenzyme A [1]. Mevalonic acid is converted via precursor molecules into cholesterol. By inhibiting cholesterol synthesis, the body upregulates low-density lipoprotein (LDL) receptors, causing a decrease in plasma LDL-cholesterol [2]. Elevated LDL cholesterol is associated with an increased risk of myocardial infarction (MI) and atherosclerotic cardiovascular disease (CVD), which further increases with age [3,4]. Statins are proven to reduce plasma LDL cholesterol and mortality, including in the Scandinavian Simvastatin Survival Study (4S), where simvastatin caused a 35% mean reduction in plasma LDL and 30% reduction in fatal outcomes compared to a placebo [5]. Statins have also proved to be effective in multiple large-scale trials [6].
This study focuses on five statins licensed in the United Kingdom: atorvastatin, fluvastatin, pravastatin, rosuvastatin, and simvastatin [7].
An adverse drug reaction (ADR) is an unintended harmful reaction to the use of a drug [8]. The degree of harm may range from a mild effect through to permanent or fatal outcomes. Statins, like all drugs, have their own unique ADRs, with muscle-related ADRs such as muscle pain (myalgia) being the most reported ADR [9].
Mechanisms have been proposed for statin-induced myopathy; however, there is no singular agreed pathway. A mechanism involving the dissociation of the FKBP12 binding protein, from sarcoplasmic reticulum Ca2+ channels in myocytes, causing pro-apoptotic signaling; but these effects were also present in patients who had not experienced myalgia, so may only affect individuals susceptible due to genetics/other factors [10,11]. Higher-intensity statins, which cause a ≥50% reduction in LDL cholesterol [12], have been associated with increased risk of myopathy, which also brings the pharmacokinetic parameters of the statins into consideration [13,14].
We herein report an approach to identifying patterns between the statin structures, their unique pharmacology, and suspected ADR signals [15,16,17,18,19].

2. Aims

The primary aim of this research is to explore suspected ADR data of atorvastatin, fluvastatin, pravastatin, rosuvastatin, and simvastatin using a national registry approach. A secondary aim is to determine whether there is a link between the physicochemical and pharmacological properties of these statins and their associated side effects.

3. Results

3.1. Physicochemical Properties and Pharmacokinetics

Table 1 shows the properties of the statins. Rosuvastatin and pravastatin were predicted to be less likely than other statins to cause toxicity based on the LLE, with both being > 5; atorvastatin had the smallest LLE (2.67), suggesting it may have more off-target effects compared to other statins.
Fluvastatin was predicted to be the most likely to cross the BBB, followed by simvastatin, pravastatin, rosuvastatin, and atorvastatin, based on the physicochemical properties that they possess: <450 Da MW, tPSA < 90Å, molecule is basic or neutral, a log10D7.4 of 1–3, <2 HBA and <6 HBD, and not being a substrate for P-glycoprotein transporter. Atorvastatin was found to be the most lipophilic (cLog10P = 5.39), which is reflected in its high volume of distribution (Vd = 381 L/kg).

3.2. Target Affinity

Table 2 shows the pharmacological interactions of the five statins as median IC50 values. Interactions with a respective IC50 >> Cmax were excluded from further analysis as it is unlikely that the statins would reach these clinically relevant concentrations in the body.
Fluvastatin (n = 2) was found to have the most potential off-target interactions that were at clinically achievable concentrations (cytochrome P450 2C9 and photoreceptor-specific nuclear receptor (NR2E3)). Rosuvastatin, pravastatin, atorvastatin, and simvastatin had no relevant off-target interactions (n = 0).
Atorvastatin, pravastatin, and simvastatin showed activity at OATP1B1, with atorvastatin having the most potent action with an IC50 of 0.81 µM (Cmax = 0.12 µM); atorvastatin also showed activity at OATP1B3 (3.4 µM).
Atorvastatin, fluvastatin, and simvastatin showed activity at several CYP450 enzymes involved in their metabolism; CYP3A4 for atorvastatin with an IC50 of 5.1 µM, CYP2C9 for fluvastatin with an IC50 of 0.4 µM, and CYP2C8 for simvastatin with an IC50 of 3.7 µM. Fluvastatin was more potent than simvastatin when acting on NR2E3 (IC50 = 0.53 µM); and pravastatin was the only statin to inhibit squalene monooxygenase, with an IC50 of 10 µM.

3.3. Adverse Drug Reactions

The total prescribing of each statin in the UK, the number of suspected ADRs, and their incidence rates for the selected system organ classes from January 2018 to August 2022, alongside chi-squared statistical analysis results are presented in Table 3.
Atorvastatin was the most prescribed statin (226,846,930), followed by simvastatin (94,630,298), rosuvastatin (13,173,853), pravastatin (11,536,965), and fluvastatin with the least prescriptions (496,892) (see Figure S1).
Fluvastatin had the most reported suspected ADRs per 100,000 prescriptions (5.64), followed by rosuvastatin (4.89), pravastatin (3.54), atorvastatin (2.11), and simvastatin (1.41). Statistical summaries can be found in Table S1 of the Supporting Materials. Fatality incidence was similar across the statins with rates ranging between 0.00–0.03 per 100,000 Rx (see Table S2).
There was no significant difference between the suspected ADRs per 100,000 Rx for the statins (X2 analysis), in any of the system organ classes. However, for the musculoskeletal and connective tissue class there was a noticeably different p-value (0.58) compared to all other system organ classes. Within the musculoskeletal and connective tissue organ class, fluvastatin had the highest incidence of ADRs (2.415), followed by rosuvastatin (1.465), pravastatin (0.667), atorvastatin (0.466), and lastly, simvastatin (0.323) see Figure S2. Atorvastatin and simvastatin had a 0.001 incidence rate per 100,000 Rx for fatalities while the other three statins had no reports within this time frame. Further chi-squared statistical analysis was performed within the musculoskeletal and connective tissue organ class (Table 4).
There was no statistically significant difference between any pair of statins for p < 0.05; however, the p-values for fluvastatin were noticeably lower compared to the other statins studied.

4. Discussion

The majority of the polypharmacological interactions identified in Table 2 are unlikely to occur clinically because of the concentrations needed for an effect based on the Cmax of the statins (Table 1). Without accumulation of the statin, it is unlikely that plasma concentrations of the statin will reach these values. It is possible for fluvastatin to accumulate in patients with hepatic impairment [20] due to it being primarily excreted via the bile, with extensive pre-systemic metabolism; this may contribute to fluvastatin having the highest incidence of ADRs per 100,000 Rx (Table 3). Fluvastatin had the highest ADR incidence in multiple organ classes; however, it was prescribed over twenty-fold less than the next least prescribed statin, pravastatin. As two independent sets of data were used for frequency of prescriptions and frequency of reported suspected ADRs, neither dataset enables the interpretation of comorbidity and co-prescription confounders, for example. This limits the assessment of causality and identification and adjustment for these confounding factors. Furthermore, the prescriber’s choice of statin may be influenced by known interactions (and contraindications) with drugs co-prescribed for comorbidities, i.e., there may be a significant bias by indication (or contraindication) as these comorbidities may affect sensitivity for ADRs. This study cannot adjust for these confounders. There is also a statin dose versus risk of association with an ADR that cannot be described within these datasets due to absence of data in reporting. Patient frailty is another factor that may have a bearing on the association of ADRs beyond the discussed kidney and liver confounders. The data on the potential lower safety profile of fluvastatin are unusual and it may be the case that prescribers have decided to use fluvastatin in more frail patients, and consequently, that the risk of adverse events is higher, because the target patients were a priori more at risk.

4.1. ADR Incidence

Overall, no significant difference was found between the statins and any organ class p < 0.05 (Table 3). This suggests that the statins could have a similar class effect not individually differing in their off-target pharmacological mechanism.
For the musculoskeletal and connective tissue organ class (p = 0.58) there was no statistically significant difference between the statins; however, when compared to the p-values for other organ classes, a difference in risk appears. Further analysis within the musculoskeletal and connective tissue organ class showed no statistically significant difference (Table 4); however, fluvastatin compared to other statin pairs had lower p-values and had the highest suspected ADR incidence across multiple organ classes—which was unexpected.
Fluvastatin is a low–medium-intensity statin [21]. The National Institute for Health and Care Excellence (NICE) guidelines recommend a high-intensity statin as first line treatment for patients at risk of cardiovascular disease [22]. Another contributing factor is that fluvastatin is the only statin indicated for use after percutaneous coronary intervention, a procedure which can cause post-operative pain [23]. The low prescribing rate, potential for accumulation, and patient comorbidities could explain the unexpectedly high suspected ADR incidence of fluvastatin.
Chi-squared analysis showed that there was no significant difference between the statins in the musculoskeletal and connective tissue organ class and among the remaining ADR organ classes. These findings confirm a recent meta-analysis [14] that reported that there was no unambiguous evidence that the risk ratios for musculoskeletal symptoms differed between statins; it did however find that higher-intensity statins caused an increased risk of muscle pain or weakness compared to moderate-intensity statins. There is no sequential change in intensity between the statins when looking at the suspected musculoskeletal and connective tissue disorders ADR incidence (Table 3); rosuvastatin is classed as a moderate–high-intensity statin; it had the next highest suspected musculoskeletal and connective tissue disorders ADR incidence, followed by pravastatin, which is classed as a low–moderate-intensity statin.
These findings also align with another large-scale meta-analysis [24], which found that patients were less likely to experience myalgia with simvastatin than with atorvastatin in a pairwise meta-analysis; it also found no significant difference between the statins when collectively comparing n = 1986 myalgia events in a drug-level network meta-analysis.

4.2. Physicochemical Properties

There does not appear to be a clear relationship between the physicochemical properties (Table 1) and the suspected ADR incidence. Rosuvastatin and pravastatin are the most hydrophilic compared to the remaining statins based on their negative log10D7.4 values. This prevents them from passively diffusing through tissue and requires the use of carriers to facilitate their uptake into the liver [25]. This should in theory increase selectivity, and so, reduce uptake into other tissues such as muscle tissue; however, this is not reflected in the suspected muscle ADR incidence, as the lipophilic atorvastatin and simvastatin had smaller suspected incidence values compared to the two hydrophilic statins (rosuvastatin and pravastatin).
Based on the physicochemical properties, fluvastatin was predicted as most likely to cross the BBB, followed by simvastatin, pravastatin, rosuvastatin, and atorvastatin. Earlier studies have found that the lipophilic statins such as atorvastatin, fluvastatin, and simvastatin can easily cross the BBB while hydrophilic statins are less likely to achieve this at clinically used concentrations [26]. There does not appear to be a relationship between the statins which were predicted as more likely to cross the BBB and ADR incidence in the nervous system and psychiatric disorder categories. It is unclear based on current research whether there are any correlations between statins and these types of disorders or whether certain individuals are predisposed to these conditions and are affected by them concomitantly during their treatment with statin(s) [27].

4.3. Pharmacological Interactions

Atorvastatin, pravastatin, and simvastatin showed modest activity at OATP1B1 transporter while atorvastatin also showed activity at OATP1B3. Statins are known to be substrates of these organic anion transporter polypeptides which facilitate their uptake into the liver [28]. Mutations in the SLCO1B1 gene, which encodes for OATP1B1, have been linked to decreased hepatic uptake of statins and increased systemic exposure [29], increasing the risk of myopathy. Patients taking inhibitors of these transporters such as ciclosporin [30] are recommended to reduce their statin dose to prevent ADRs because of increased statin exposure.
Fluvastatin showed activity at CYP2C9, atorvastatin at CYP3A4, and simvastatin at CYP2C8. These are enzymes that take part in the metabolism of these statins and are unlikely to have a role in ADRs unless the statins are taken concomitantly with inhibitors of these enzymes, in turn increasing systemic exposure to the statin. Inhibitors of cytochrome P450 enzymes are less likely to affect rosuvastatin and pravastatin as these are metabolised via other pathways [25].
Pravastatin showed inhibition of squalene monooxygenase, a rate-limiting enzyme in the cholesterol synthesis pathway, acting downstream of HMG-CoA reductase [31]. Little evidence is available for the clinical relevance of squalene monooxygenase inhibition, with animal studies showing symptoms of dermatitis and neuropathy due to squalene monooxygenase modulation [32].
Fluvastatin and simvastatin showed activity at the photoreceptor-specific nuclear receptor (NR2E3). Mutations of its gene have been shown to cause retinal degeneration and other eye disorders in animal studies [33]. It is unclear whether this interaction has any significance for statins in causing ADRs, as no studies of clinical relevance about this interaction were identified.

4.4. Limitations

Prescribing data were available from November 2017 until August 2022. However, due to the format in which the ADR data were available from the MHRA Yellow Card scheme, data were extracted from January 2018 (excluding the data available from 2017). However, this ensured that the suspected ADR incidence per 100,000 Rx for 2017 was not inflated due to ADRs being included for the two months in 2017 where prescribing data were not available.
Two independent sets of data were used for frequency of prescriptions and frequency of reported suspected ADRs; neither dataset enables the interpretation of comorbidity and co-prescription confounders, for example. This limits the assessment of causality and identification and adjustment for these confounding factors.
Reports from the Yellow Card scheme are suspected reports, and therefore, no causal relationship must be proved before submitting a report. Therefore, reported ADRs in any registry may have no defined relationship to the pharmacology of the statins. Comparison of the ADR incidence for a statin against an average incidence was used to ensure relevant ADRs were highlighted. Under-reporting of ADRs is also a common issue with pharmacovigilance schemes, leading to ADRs going unreported [34]. Information such as other drug use and health conditions are not available from the Yellow Card scheme and so it is not possible to prove causality through these data alone.
Furthermore, the prescriber’s choice of statin may be influenced by known interactions (and contraindications) with drugs co-prescribed for comorbidities, i.e., there may be a significant bias by indication (or contraindication) as these comorbidities may affect sensitivity for ADRs. The study cannot adjust for these confounders. There is also a statin dose versus risk of association with an ADR that cannot be described within these datasets. Patient frailty is another factor that may have a bearing on the association of ADRs. The data on the potential lower safety profile of fluvastatin are unusual and it may be the case that prescribers have decided to use fluvastatin in more frail patients, and consequently, that it appeared that the risk of adverse events is higher, because the target patients were a priori more at risk [35].
The musculoskeletal and connective tissue disorders organ class was analysed as a whole, and so, included connective tissue disorders in the statistical analysis. Interactions with human proteins were extracted from the ChEMBL database, which necessarily does not contain every possible interaction which the statin(s) could have in the human body. Furthermore, multiple IC50 values were available for each protein, and so, a median value was used.

5. Methods

5.1. Chemical Properties and Pharmacology

The chemical database of bioactive molecules with drug-like properties, European Molecular Biology Laboratory (ChEMBL) [36], and the Electronic Medicines Compendium (EMC) [37] were used to obtain the experimentally validated physicochemical properties and pharmacokinetic parameters for atorvastatin, fluvastatin, pravastatin, rosuvastatin, and simvastatin.
Physicochemical properties included pKa, cLog10P, cLog10D7.4, topological polar surface area (tPSA), and the number of hydrogen bond donors (HBDs) and acceptors (HBAs) [36]. Certain properties increase the propensity of a molecule to penetrate the blood–brain barrier (BBB) [38,39], as follows: a molecular weight of <450 Da, a neutral or basic drug molecule, the molecule not being a substrate of P-glycoprotein, <6 HBD and <2 HBA, a tPSA of <90 Å2, and a log10D of 1–3 at pH = 7.4. Penetration of the BBB can lead to potential neurological side effects.
Lipophilic ligand efficiency (LLE) was calculated, where LLE = pIC50 − cLog10P. pIC50 is the negative log10 of the IC50, which is the concentration of a drug needed to inhibit 50% of the activity of a process or response at a receptor; the median IC50 values for each statin acting on HMG-CoA reductase were used. cLog10P is the calculated partition coefficient of a substance in its neutral form between an aqueous and organic phase. The LLE is a measure of the specificity of a molecule for its target, accounting for its partitioning in the organic phase [40]. An LLE of >5 is associated with a significantly smaller risk of toxicity [41].
Pharmacokinetic properties were obtained from the EMC and included the bioavailability, half-life, CYP450 inhibitory activity, and the degree of plasma-protein binding (PPB). Experimental Cmax values were obtained from literature databases by systematically searching the drug name and Cmax [42,43,44,45,46]. The volume of distribution was obtained from the EMC, Drugbank [47], and from a trial for simvastatin [48]. Systematic literature searches also determined if the statins were P-glycoprotein substrates [49]. Solely cLog10P, Log10D7.4, pKa, MW, tPSA, HBs, and LLE were calculated from ChemDraw version 22.2.0 from ChemOffice. All remaining pharmacokinetic (Cmax, Vd, PPB, t1/2, %F, Cmax, P-gp, CYP450) and pharmacological interaction data were curated from ChEMBL and EMC experimentally validated databases.

5.2. Pharmacological Interactions

The ChEMBL database was used to identify interactions between each statin and homosapien proteins/targets. Median IC50 values were used to select a representative value from multiple laboratories and assays. A cut-off of IC50 > 10 µM was used to remove interactions that were unlikely to occur in a clinical setting, due to the inability of the statin(s) to reach such concentrations in the body.

5.3. Suspected Adverse Drug Reaction (ADR) Data

Suspected ADR data were obtained from the Medicines and Healthcare Products Regulatory Agency’s (MHRA) Yellow Card interactive Drug Analysis Profiles (iDAPs) [50]. Suspected ADR reports from January 2018 to August 2022 were collected for each statin. This data included the number of ADRs reported to the Yellow Card scheme, with reports being categorised based on the MedDRA organ classification. Organ classes of interest were identified using percentages of the total number of ADRs for that drug; a system organ class was used if it had ≥10% of the total ADRs for at least one of the five statins.

5.4. Prescribing Data

Prescribing data were obtained from the OpenPrescribing database [51] for the January 2018 to August 2022 period. Standardisation was performed by calculating the number of ADRs per 100,000 Rx for each statin.

5.5. Statistical Analysis

A chi-squared analysis was performed on the standardised ADRs per 100,000 Rx using Microsoft Excel for Mac (version 16.67) to determine the statistical significance of the suspected ADR signals (p-value < 0.05).

5.6. Ethical Approval

No ethical approval was required as the study used publicly available open-source data that was fully anonymised.

6. Conclusions

The study found that there was no significant difference between the statins across the selected system organ classes investigated, and specifically, in the musculoskeletal and connective tissue disorder category. Fluvastatin was found to have an unexpectedly high suspected ADR incidence across multiple system organ classes, which initially could be attributed to lower prescribing rates than the other statins but was corrected for in this study based on prescribing levels.
Pharmacological interactions of the statins included the cytochrome P450 enzymes and the organic anion transporters. New interactions with NR2E3 and squalene monooxygenase were found. However, the relationship to suspected statin ADRs was not clear.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/pharma3030016/s1, Figure S1: The number of prescriptions dispensed per statin between January 2018 and August 2022. (Fluvastatin; 496,892), Table S1: Non-fatal ADRs per 100,000 prescriptions of the statins and chi-squared results for all organ classes (selected organ classes are highlighted), Table S2: Fatal ADRs per 100,000 prescriptions of the statins and chi-squared results for all organ classes (selected organ classes are highlighted), and Figure S2: The total number of suspected ADRs per 100,000 prescriptions for the statins between 2018 and 2022 for the selected organ classes.

Author Contributions

Conceptualization, A.M.J.; methodology, H.Y.; validation, A.M.J. and H.Y., formal analysis, H.Y.; investigation, H.Y.; resources, A.M.J.; data curation, H.Y.; writing—original draft preparation, H.Y.; writing—review and editing, A.M.J.; visualization, H.Y.; supervision, A.M.J.; project administration, A.M.J. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Reviewed by School of Pharmacy ethics sub-committee and deemed not applicable.

Informed Consent Statement

Not applicable as above.

Data Availability Statement

The data that support the findings of this study are openly available in the Supplementary Materials file.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Rang, H.P. Drugs affecting major organ systems. In Rang and Dale’s Pharmacology, 9th ed.; Churchill Livingstone: Edinburgh, UK, 2020; pp. 314–315. [Google Scholar]
  2. Brown, M.S.; Goldstein, J.L. A receptor-mediated pathway for cholesterol homeostasis. Science 1986, 232, 34–47. [Google Scholar] [CrossRef]
  3. Mortensen, M.B.; Nordestgaard, B.G. Elevated LDL cholesterol and increased risk of myocardial infarction and atherosclerotic cardiovascular disease in individuals aged 70–100 Years: A contemporary primary prevention cohort. Lancet 2020, 396, 1644–1652. [Google Scholar] [CrossRef] [PubMed]
  4. Abdullah, S.M.; Defina, L.F.; Leonard, D.; Barlow, C.E.; Radford, N.B.; Willis, B.L.; Rohatgi, A.; McGuire, D.K.; de Lemos, J.A.; Grundy, S.M.; et al. Long-term association of low-density lipoprotein cholesterol with cardiovascular mortality in individuals at low 10-year risk of atherosclerotic cardiovascular disease. Circulation 2018, 138, 2315–2325. [Google Scholar] [CrossRef]
  5. Scandinavian Simvastatin Survival Study Group. Randomised trial of cholesterol lowering in 4444 patients with coronary heart disease: The Scandinavian simvastatin survival study (4S). Lancet 1994, 344, 1383–1389. [CrossRef]
  6. Cholesterol Treatment Trialists’ (CTT) Collaborators. The effects of lowering LDL cholesterol with statin therapy in people at low risk of vascular disease: Meta-analysis of individual data from 27 randomised trials. Lancet 2012, 380, 581–590. [Google Scholar] [CrossRef]
  7. NHS. Statins. Available online: https://www.nhs.uk/conditions/statins/ (accessed on 15 December 2022).
  8. Edwards, I.R.; Aronson, J.K. Adverse drug reactions: Definitions, diagnosis, and management. Lancet 2000, 356, 1255–1259. [Google Scholar] [CrossRef] [PubMed]
  9. Pedro-Botet, J.; Núñez-Cortés, J.M.; Flores, J.A.; Rius, J. Muscle symptoms related with statin therapy in general practice. Atherosclerosis 2015, 241, e197. [Google Scholar] [CrossRef]
  10. Lotteau, S.; Ivarsson, N.; Yang, Z.; Restagno, D.; Colyer, J.; Hopkins, P.; Weightman, A.; Himori, K.; Yamada, T.; Bruton, J.; et al. A mechanism for statin-induced susceptibility to myopathy. JACC Basic Transl. Sci. 2019, 4, 509–523. [Google Scholar] [CrossRef]
  11. Isackson, P.J.; Wang, J.; Zia, M.; Spurgeon, P.; Levesque, A.; Bard, J.; James, S.; Nowak, N.; Lee, T.K.; Vladutiu, G.D. RYR1 and CACNA1S genetic variants identified with statin-associated muscle symptoms. Pharmacogenomics 2018, 19, 1235–1249. [Google Scholar] [CrossRef]
  12. Chou, R.; Cantor, A.; Dana, T. Statin Use for the Primary Prevention of Cardiovascular Disease in Adults: A Systematic Review for the U.S. Preventive Services Task Force. National Center for Biotechnology Information. Available online: https://www.ncbi.nlm.nih.gov/books (accessed on 7 January 2023).
  13. Omar, M.A.; Wilson, J.P. FDA adverse event reports on statin-associated rhabdomyolysis. Ann. Pharmacother. 2002, 36, 288–295. [Google Scholar] [CrossRef]
  14. Reith, C.; Reith, C.; Reith, C.; Baigent, C.; Baigent, C.; Baigent, C.; Blackwell, L.; Blackwell, L.; Blackwell, L.; Emberson, J.; et al. Effect of statin therapy on muscle symptoms: An individual participant data meta-analysis of large-scale, randomised, double-blind trials. Lancet 2022, 400, 832–845. [Google Scholar] [CrossRef]
  15. Jones, L.; Jones, A.M. Suspected Adverse Drug Reactions of the Type 2 Antidiabetic Drug class Dipeptidy-Peptidase IV inhbitors (DPP4i): Can polypharmacology help explain? Pharmacol. Res. Perspect. 2022, 10, e01029. [Google Scholar] [CrossRef] [PubMed]
  16. Salim, H.; Jones, A.M. Angiotensin II Receptor Blockers (ARBs) and Manufacturing Contamination: A Retrospective National Register Study into suspected associated adverse drug reactions. Brit. J. Clin. Pharmacol. 2022, 88, 4812–4827. [Google Scholar] [CrossRef] [PubMed]
  17. Sandhu, D.; Antolin, A.A.; Cox, A.R.; Jones, A.M. Identification of different side effects between PARP inhibitors and their polypharmacological multi-target rationale. Brit. J. Clin. Pharmacol. 2022, 88, 742–752. [Google Scholar] [CrossRef] [PubMed]
  18. Matharu, K.; Chana, K.; Ferro, C.; Jones, A.M. Polypharmacology of clinical sodium glucose co-transport protein 2 inhibitors and relationship to suspected adverse drug reactions. Pharmacol. Res. Perspect. 2021, 9, e00867. [Google Scholar] [CrossRef] [PubMed]
  19. Ferro, C.J.; Solkhon, F.; Jalal, Z.; Al-Hamid, A.M.; Jones, A.M. Relevance of physicochemical properties and functional pharmacology data to predict the clinical safety profile of direct oral anticoagulants. Pharmacol. Res. Perspect. 2020, 8, e00603. [Google Scholar] [CrossRef] [PubMed]
  20. Averbukh, L.D.; Turshudzhyan, A.; Wu, D.C.; Wu, G.Y. Statin-induced Liver Injury Patterns: A Clinical Review. J. Clin. Transl. Hepatol. 2022, 28, 543–552. [Google Scholar] [CrossRef] [PubMed]
  21. National Institute for Health and Care Excellence. 1.9 Optimising treatment for people on statins: Grouping of Statins: Cardiovascular Disease: Risk Assessment and Reduction, Including Lipid Modification: Guidance. Available online: https://www.nice.org.uk/guidance/ng238/chapter/recommendations#optimising-treatment-for-people-on-statins-4 (accessed on 1 January 2023).
  22. National Institute for Health and Care Excellence. Recommendations: Cardiovascular Disease: Risk Assessment and Reduction, Including Lipid Modification: Guidance. Available online: https://www.nice.org.uk/guidance/cg181/chapter/Recommendations#lipid-modification-therapy-for-the-primary-and-secondary-prevention-of-cvd-2 (accessed on 1 January 2023).
  23. Mansour, M.; Carrozza, J.P.; Kuntz, R.E.; Fishman, R.F.; Pomerantz, R.M.; Senerchia, C.C.; Safian, R.D.; Diver, D.J.; Baim, D.S. Frequency and outcome of chest pain after two new coronary interventions (atherectomy and stenting). Am. J. Cardiol. 1992, 69, 1379–1382. [Google Scholar] [CrossRef] [PubMed]
  24. Naci, H.; Brugts, J.; Ades, T. Comparative tolerability and harms of individual statins. Circ. Cardiovasc. Qual. Outcomes 2013, 6, 390–399. [Google Scholar] [CrossRef]
  25. Schachter, M. Chemical, pharmacokinetic and pharmacodynamic properties of statins: An update. Fundam. Clin. Pharmacol. 2005, 19, 117–125. [Google Scholar] [CrossRef]
  26. Wood, W.G.; Eckert, G.P.; Igbavboa, U.; Müller, W.E. Statins and neuroprotection. Ann. N. Y. Acad. Sci. 2010, 1199, 69–76. [Google Scholar] [CrossRef]
  27. McFarland, A.J.; Anoopkumar-Dukie, S.; Arora, D.S.; Grant, G.D.; McDermott, C.M.; Perkins, A.V.; Davey, A.K. Molecular mechanisms underlying the effects of statins in the Central Nervous System. Int. J. Mol. Sci. 2014, 15, 20607–20637. [Google Scholar] [CrossRef] [PubMed]
  28. Shitara, Y. Clinical importance of OATP1B1 and OATP1B3 in drug drug interactions. Drug Metab. Pharmacokinet. 2011, 26, 220–227. [Google Scholar] [CrossRef] [PubMed]
  29. Niemi, M. Transporter pharmacogenetics and statin toxicity. Clin. Pharmacol. Ther. 2009, 87, 130–133. [Google Scholar] [CrossRef] [PubMed]
  30. Shitara, Y.; Takeuchi, K.; Nagamatsu, Y.; Wada, S.; Sugiyama, Y.; Horie, T. Long-lasting inhibitory effects of cyclosporin A, but not tacrolimus, on OATP1B1- and OATP1B3-mediated uptake. Drug Metab. Pharmacokinet. 2012, 27, 368–378. [Google Scholar] [CrossRef] [PubMed]
  31. Matzno, S.; Yamauchi, T.; Gohda, M.; Ishida, N.; Katsuura, K.; Hanasaki, Y.; Tokunaga, T.; Itoh, H.; Nakamura, N. Inhibition of cholesterol biosynthesis by squalene epoxidase inhibitor avoids apoptotic cell death in L6 myoblasts. J. Lipid Res. 1997, 38, 1639–1648. [Google Scholar] [CrossRef] [PubMed]
  32. Chugh, A. Squalene epoxidase as hypocholesterolemic drug target revisited. Prog. Lipid Res. 2003, 42, 37–50. [Google Scholar] [CrossRef] [PubMed]
  33. Cheng, H. Photoreceptor-specific nuclear receptor NR2E3 functions as a transcriptional activator in rod photoreceptors. Hum. Mol. Genet. 2004, 13, 1563–1575. [Google Scholar] [CrossRef]
  34. Hazell, L.; Shakir, S.A. Under-reporting of Adverse Drug Reactions. Drug Saf. 2006, 29, 385–396. [Google Scholar] [CrossRef] [PubMed]
  35. Chong, P.H.; Seeger, J.D.; Franklin, C. Clinically relevant differences between the statins: Implications for therapeutic selection. Am. J. Med. 2001, 111, 390–400. [Google Scholar] [CrossRef]
  36. European Molecular Biology Laboratory. Chembl Database. EMBL-EBI Homepage. Available online: https://www.ebi.ac.uk/chembl/ (accessed on 30 November 2022).
  37. Electronic Medicines Compendium. Home—Electronic Medicines Compendium (EMC). Available online: https://www.medicines.org.uk/emc (accessed on 30 November 2022).
  38. Van de Waterbeemd, H.; Camenisch, G.; Folkers, G.; Chretien, J.R.; Raevsky, O.A. Estimation of blood-brain barrier crossing of drugs using molecular size and shape, and H-bonding descriptors. J. Drug Target. 1998, 6, 151–165. [Google Scholar] [CrossRef]
  39. Pajouhesh, H.; Lenz, G.R. Medicinal chemical properties of successful Central Nervous System Drugs. Neurotherapeutics 2005, 2, 541–553. [Google Scholar] [CrossRef] [PubMed]
  40. Hopkins, A.L.; Keserü, G.M.; Leeson, P.D.; Rees, D.C.; Reynolds, C.H. The role of ligand efficiency metrics in drug discovery. Nat. Rev. Drug Discov. 2014, 13, 105–121. [Google Scholar] [CrossRef] [PubMed]
  41. Hann, M.M. Molecular obesity, potency and other addictions in Drug Discovery. MedChemComm 2011, 2, 349–355. [Google Scholar] [CrossRef]
  42. Lins, R.L.; Matthys, K.E.; Verpooten, G.A.; Peeters, P.C.; Dratwa, M.; Stolear, J.-C.; Lameire, N.H. Pharmacokinetics of atorvastatin and its metabolites after single and multiple dosing in hypercholesterolaemic haemodialysis patients. Nephrol. Dial. Transplant. 2003, 18, 967–976. [Google Scholar] [CrossRef] [PubMed]
  43. Xu, H.R.; Chen, W.L.; Chu, N.N.; Li, X.N.; Zhu, J.R. The difference in pharmacokinetics and pharmacodynamics between extended-release fluvastatin and immediate-release fluvastatin in healthy Chinese subjects. J. Biomed. Biotechnol. 2012, 2012, 386230. [Google Scholar] [CrossRef] [PubMed]
  44. Deng, M.; Xue, H.; Liu, H.; Cao, L. Study on bioequivalence of pravastatin sodium tablets in healthy volunteers. Chin. Pharm. Sci. 2005, 40, 451–453. [Google Scholar]
  45. Martin, P.D.; Warwick, M.J.; Dane, A.L.; Hill, S.J.; Giles, P.B.; Phillips, P.J.; Lenz, E. Metabolism, excretion, and pharmacokinetics of rosuvastatin in healthy adult male volunteers. Clin. Ther. 2003, 25, 2822–2835. [Google Scholar] [CrossRef] [PubMed]
  46. FDA: Center for Drug Evaluation and Research. Drug approval package. Clinical Pharmacology and Biopharmaceutics Review(s). Available online: https://www.accessdata.fda.gov/drugsatfda_docs/nda/2016/206679Orig1s000ClinPharmR.pdf (accessed on 16 December 2022).
  47. DrugBank Online: Database for Drug and Drug Target Info. Available online: https://go.drugbank.com/ (accessed on 18 December 2022).
  48. Alakhali, K. Pharmacokinetic of simvastatin study in Malaysian subjects. IOSR J. Pharm. 2013, 3, 46–51. [Google Scholar] [CrossRef]
  49. Goard, C.A.; Mather, R.G.; Vinepal, B.; Clendening, J.W.; Martirosyan, A.; Boutros, P.C.; Sharom, F.J.; Penn, L.Z. Differential interactions between statins and P-glycoprotein: Implications for exploiting statins as Anticancer Agents. Int. J. Cancer 2010, 127, 2936–2948. [Google Scholar] [CrossRef]
  50. Medicines and Healthcare Products Regulatory Agency. What is Being Reported. YellowCard. Available online: https://yellowcard.mhra.gov.uk/idaps (accessed on 30 November 2022).
  51. Bennett Institute for Applied Data Science, Department of Primary Care Health Sciences, University of Oxford. All Chemicals. OpenPrescribing. Available online: https://openprescribing.net/chemical/ (accessed on 5 December 2022).
Table 1. In silico physicochemical and experimental pharmacokinetic properties of the five statin tablet formulations.
Table 1. In silico physicochemical and experimental pharmacokinetic properties of the five statin tablet formulations.
Property vs. DrugAtorvastatinFluvastatinPravastatin Rosuvastatin Simvastatin
cLog10P5.393.831.651.924.46
pIC508.067.857.528.357.59
LLE2.674.025.876.433.13
Log10D7.42.431.05−1.38−1.244.46
MW (Da)558.65411.47424.53481.55418.57
pKa4.314.544.214Neutral
tPSA (Å)111.7982.69124.29140.9272.83
HB acceptors54675
HB donors43431
Bioavailability (F, %)12241720<5
Cmax (nM)118.5687.78189.5739.04130.71
Half-life (h)142.31.5–2191.9
Vd (L/kg)3813300.5134233
PPB≥98%>98%50%90%>95%
P-Glycoprotein substrateYesNoNoNoLikely
Liver CYP450 metabolism3A42C9, 3A4, 2C8MinimalMinimal3A4, 3A5, 2C8, 2C9
Dosing regime10–80 mg OD20–80 mg OD/BID10–40 mg OD5–20 mg OD10–80 mg OD
Key: cLog10P, calculated partition coefficient; LLE, lipophilic ligand efficiency; Log10D7.4, partition coefficient at pH 7.4; MW, molecular weight; pKa, acid dissociation constant; tPSA, topological polar surface area; HB, hydrogen bond; Cmax, peak serum concentration; Vd, volume of distribution; PPB, plasma protein binding. cLog10P, Log10D7.4, pKa, MW, tPSA, HBs, and LLE were calculated from ChemDraw version 22.2.0 from ChemOffice. Cmax, Vd, PPB, t1/2, %F, Cmax, P-gp, and CYP450 data were extracted from ChEMBL and EMC databases.
Table 2. Pharmacological interactions of the statins studied.
Table 2. Pharmacological interactions of the statins studied.
Target vs. DrugAtorvastatin (µM)Fluvastatin (µM)Pravastatin (µM)Rosuvastatin (µM) Simvastatin (µM)
HMG-CoA Reductase0.0090.0140.030.0050.026
OATP1B10.81 n.r.3.6 n.r.7.9
OATP1B33.4 n.r.62 n.r. n.r.
OATP2B1 n.r. n.r.190 n.r. n.r.
CYP P450 2C9 n.r.0.4n.r. n.r.30
CYP P450 3A45.1 n.r.n.r. n.r.30
CYP P450 2C8 n.r. n.r.n.r. n.r.3.7
CYP P450 2D6 n.r. n.r.n.r. n.r.30
CYP P450 2C19 n.r. n.r.n.r. n.r.30
CYP P450 1A2 n.r. n.r.n.r. n.r.30
HDAC111.4 n.r.n.r. n.r. n.r.
HDAC614.3 n.r.n.r. n.r. n.r.
HDAC222.5 n.r.n.r. n.r. n.r.
BSEP41336.113313324.7
MDRAP488.513313326.8133
CMOAT1133 n.r.13313379
CMOAT214.25712558.3133
P-glycoprotein 1289 26.1
NR2E3n.r. 0.53 n.r. n.r.1.2
SMO n.r. n.r.10 n.r. n.r.
hOAT1 n.r.n.r. 408 n.r. n.r.
hOAT2 n.r. n.r.352 n.r. n.r.
hOAT3 n.r.n.r.13.7 n.r.n.r.
hOAT4 n.r. n.r.591 n.r. n.r.
Cmax0.120.690.190.040.13
OATP = solute carrier organic anion transporter family member; CYP = cytochrome; HDAC = histone deacetylase; BSEP = bile salt export pump; MDRAP = multidrug resistance-associated protein; CMOAT = canalicular multispecific organic anion transporter; NR2E3 = photoreceptor-specific nuclear receptor; SMO = squalene monooxygenase; hOAT = solute carrier family 22 member; n.r. = data not reported.
Table 3. Summary of the selected Yellow Card ADR reporting data for the five statins in the UK. The numbers in parentheses are ADRs/100,000 Rx.
Table 3. Summary of the selected Yellow Card ADR reporting data for the five statins in the UK. The numbers in parentheses are ADRs/100,000 Rx.
AtorvastatinFluvastatinPravastatinRosuvastatinSimvastatinp-Values
Total Prescriptions226,846,930496,89211,536,96513,173,85394,630,298-
Total ADRs4782 (2.11)28 (5.64)408 (3.54)644 (4.89)1331 (1.41)0.46
Total Fatalities20 (0.01)0 (0.00)3 (0.03)1 (0.01)6 (0.01)-
Gastrointestinal disorders
Total ADRs549 (0.242)2 (0.403)42 (0.364)73 (0.554)130 (0.137)0.99
Total Fatalities3 (0.001)0 (0)0 (0)0 (0)0 (0)-
General disorders and administration site conditions
Total ADRs555 (0.245)4 (0.805)56 (0.485)65 (0.493)150 (0.159)0.96
Total Fatalities5 (0.002)0 (0)2 (0.017)0 (0)2 (0.002)-
Injury, poisoning and procedural complications
Total ADRs161 (0.071)0 (0)25 (0.217)8 (0.061)93 (0.098)0.99
Total Fatalities0 (0)0 (0)0 (0)0 (0)1 (0.001)-
Investigations
Total ADRs279 (0.123)1 (0.201)8 (0.069)18 (0.137)75 (0.079)-
Total Fatalities0 (0)0 (0)1 (0.009)0 (0)0 (0)-
Musculoskeletal and connective tissue disorders
Total ADRs1057 (0.466)12 (2.415)77 (0.667)193 (1.465)306 (0.323)0.58
Total Fatalities3 (0.001)0 (0)0 (0)0 (0)1 (0.001)-
Nervous system disorders
Total ADRs533 (0.235)4 (0.805)45 (0.390)93 (0.706)113 (0.119)0.94
Total Fatalities1 (0.0004)0 (0)0 (0)0 (0)0 (0)-
Psychiatric disorders
Total ADRs259 (0.114)1 (0.201)33 (0.286)40 (0.304)76 (0.080)1
Total Fatalities0 (0)0 (0)0 (0)0 (0)1 (0.001)-
Skin and subcutaneous tissue disorders
Total ADRs367 (0.162)1 (0.201)41 (0.355)59 (0.448)100 (0.106)0.99
Total Fatalities0 (0)0 (0)0 (0)0 (0)0 (0)-
Table 4. Chi-squared analysis results from comparing the statin-suspected ADR reports per 100,000 Rx within the musculoskeletal and connective tissue organ class.
Table 4. Chi-squared analysis results from comparing the statin-suspected ADR reports per 100,000 Rx within the musculoskeletal and connective tissue organ class.
Statinsp-Value
fluvastatin vs. atorvastatin0.15
fluvastatin vs. pravastatin0.17
fluvastatin vs. rosuvastatin0.17
fluvastatin vs. simvastatin0.14
atorvastatin vs. simvastatin0.35
atorvastatin vs. pravastatin0.48
atorvastatin vs. rosuvastatin0.49
pravastatin vs. rosuvastatin0.59
pravastatin vs. simvastatin0.41
rosuvastatin vs. simvastatin0.41
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Yousaf, H.; Jones, A.M. Associations between Suspected Adverse Drug Reactions of HMG-CoA Reductase Inhibitors and Polypharmacology Using a National Registry Approach. Pharmacoepidemiology 2024, 3, 241-251. https://doi.org/10.3390/pharma3030016

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Yousaf H, Jones AM. Associations between Suspected Adverse Drug Reactions of HMG-CoA Reductase Inhibitors and Polypharmacology Using a National Registry Approach. Pharmacoepidemiology. 2024; 3(3):241-251. https://doi.org/10.3390/pharma3030016

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Yousaf, Hasan, and Alan M. Jones. 2024. "Associations between Suspected Adverse Drug Reactions of HMG-CoA Reductase Inhibitors and Polypharmacology Using a National Registry Approach" Pharmacoepidemiology 3, no. 3: 241-251. https://doi.org/10.3390/pharma3030016

APA Style

Yousaf, H., & Jones, A. M. (2024). Associations between Suspected Adverse Drug Reactions of HMG-CoA Reductase Inhibitors and Polypharmacology Using a National Registry Approach. Pharmacoepidemiology, 3(3), 241-251. https://doi.org/10.3390/pharma3030016

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