Large-scale next generation sequencing based analysis of SLCO1B1 pharmacogenetics variants in the Saudi population.

BACKGROUND: SLCO1B1 plays an important role in mediating hepatic clearance of many different drugs including statins, angiotensin-converting enzyme inhibitors, chemotherapeutic agents and antibiotics. Several variants in SLCO1B1 have been shown to have a clinically significant impact, in relation to efficacy of these medications. This study provides a comprehensive overview of SLCO1B1 variation in Saudi individuals, one of the largest Arab populations in the Middle East. METHODS: The dataset of 11,889 (9,961 exomes and 1,928 pharmacogenetic gene panel) Saudi nationals, was used to determine the presence and frequencies of SLCO1B1 variants, as described by the Clinical Pharmacogenetic Implementation Consortium (CPIC). RESULTS: We identified 141 previously described SNPs, of which rs2306283 (50%) and rs4149056 (28%), were the most common. In addition, we observed six alleles [*15 (24.7%) followed by *20 (8.04%), *14 (5.86%), *5 (3.84%), *31 (0.21%) and *9 (0.03%)] predicted to be clinically actionable. Allele diplotype to phenotype conversion revealed 41 OATP1B1 diplotypes. We estimated the burden of rare, and novel predicted deleterious variants, resulting from 17 such alterations. CONCLUSIONS: The data we present, from one of the largest Arab cohorts studied to date, provides the most comprehensive overview of SLCO1B1 variants, and the subsequent OATP1B1 activity of this ethnic group, which thus far remains relatively underrepresented in available international genomic databases. We believe that the presented data provides a basis for further clinical investigations and the application of personalized statin drug therapy guidance in Arabs.

Precision medicine in cardiovascular therapeutics: Evaluating the role of pharmacogenetic analysis prior to drug treatment.

Pharmacogenomics is the examination of how genetic variation influences drug metabolism and response, in terms of both efficacy and safety. In cardiovascular disease, patient-specific diplotypes determine phenotypes, thereby influencing the efficacy and safety of drug treatments, including statins, antiarrhythmics, anticoagulants and antiplatelets. Notably, polymorphisms in key genes, such as CYP2C9, CYP2C19, VKORC1 and SLCO1B1, significantly impact the outcomes of treatment with clopidogrel, warfarin and simvastatin. Furthermore, the CYP2C19 polymorphism influences the pharmacokinetics and safety of the novel hypertrophic cardiomyopathy inhibitor, mavacamten. In this review, we critically assess the clinical application of pharmacogenomics in cardiovascular disease and delineate present and future utilization of pharmacogenomics. This includes insights into identifying missing heritability, the integration of whole genome sequencing and the application of polygenic risk scores to enhance the precision of personalized drug therapy. Our discussion encompasses health economic analyses that underscore the cost benefits associated with pre-emptive genotyping for warfarin and clopidogrel treatments, albeit acknowledging the need for further research in this area. In summary, we contend that cardiovascular pharmacogenomic analyses are underpinned by a wealth of evidence, and implementation is already occurring for some of these gene-drug pairs, but as with any area of medicine, we need to continually gather more information to optimize the use of pharmacogenomics in clinical practice.

Transporter Genes and statin-induced Hepatotoxicity.

PURPOSE: Hepatotoxicity has emerged as a major cause of statin treatment interruption. Although organic anion-transporting polypeptide 1B1 (SLCO1B1), multidrug resistance protein 1 (ABCB1), and breast cancer resistance protein (ABCG2) have been identified as transporters of statins, knowledge of their role in statin-associated hepatotoxicity remains limited. Therefore, we aimed to conduct a comprehensive analysis to elucidate the association between hepatotoxicity and SLCO1B1, ABCB1, and ABCG2 polymorphisms. METHODS: This study retrospectively analyzed prospectively collected samples. We selected 10 single nucleotide polymorphisms (SNPs) of SLCO1B1, 9 SNPs of ABCB1, and 12 SNPs of ABCG2. We developed two models for multivariable analyses (Model I: clinical factors only; Model II: both clinical and genetic factors), and the attributable risk (%) of variables in Model II was determined. RESULTS: Among 851 patients, 66 (7.8%) developed hepatotoxicity. In Model I, lipophilic statins, atrial fibrillation (Afib), and diabetes mellitus showed a significant association with hepatotoxicity. In Model II, lipophilic statins and Afib, SLCO1B1 rs11045818 A allele, SLCO1B1 rs4149035 T allele, and ABCG2 rs2622629 TT genotype were associated with higher hepatotoxicity risk. Among them, the SLCO1B1 rs11045818 A allele exhibited the highest attributable risk (93.2%). The area under the receiver operating characteristic curve in Model I was 0.62 (95% CI: 0.55-0.69), and it was increased to 0.71 in Model II (95% CI: 0.64-0.77). CONCLUSION: This study investigated the correlation between hepatotoxicity and polymorphisms of transporter genes in patients taking statins. The findings could help improve personalized treatments for patients receiving statin therapy.

SLCO1B1 Exome Sequencing and Statin Treatment Response in 64,000 UK Biobank Patients.

The solute carrier organic anion transporter family member 1B1 (SLCO1B1) encodes the organic anion-transporting polypeptide 1B1 (OATP1B1 protein) that transports statins to liver cells. Common genetic variants in SLCO1B1, such as *5, cause altered systemic exposure to statins and therefore affect statin outcomes, with potential pharmacogenetic applications; yet, evidence is inconclusive. We studied common and rare SLCO1B1 variants in up to 64,000 patients from UK Biobank prescribed simvastatin or atorvastatin, combining whole-exome sequencing data with up to 25-year routine clinical records. We studied 51 predicted gain/loss-of-function variants affecting OATP1B1. Both SLCO1B1*5 alone and the SLCO1B1*15 haplotype increased LDL during treatment (beta*5 = 0.08 mmol/L, p = 6 × 10-8; beta*15 = 0.03 mmol/L, p = 3 × 10-4), as did the likelihood of discontinuing statin prescriptions (hazard ratio*5 = 1.12, p = 0.04; HR*15 = 1.05, p = 0.04). SLCO1B1*15 and SLCO1B1*20 increased the risk of General Practice (GP)-diagnosed muscle symptoms (HR*15 = 1.22, p = 0.003; HR*20 = 1.25, p = 0.01). We estimated that genotype-guided prescribing could potentially prevent 18% and 10% of GP-diagnosed muscle symptoms experienced by statin patients, with *15 and *20, respectively. The remaining common variants were not individually significant. Rare variants in SLCO1B1 increased LDL in statin users by up to 1.05 mmol/L, but replication is needed. We conclude that genotype-guided treatment could reduce GP-diagnosed muscle symptoms in statin patients; incorporating further SLCO1B1 variants into clinical prediction scores could improve LDL control and decrease adverse events, including discontinuation.

Do Gene Polymorphisms Play a Role in Newborn Hyperbilirubinemia?

Objectives: Polymorphisms of the uridine-diphospho-glucuronosyltransferase 1A1 (UGT1A1) gene, hepatic solute carrier organic anion transporter 1B1/B3 (SLCO1B1/3) gene, and glutathione S-transferase (GST) gene have been associated with significant hyperbilirubinemia in some populations. This study aims to determine whether the variation of UGT1A1, SLCO1B1/3 and GST genes play an important role in neonatal hyperbilirubinemia in Turkish newborn infants. Methods: The study included 61 idiopathic hyperbilirubinemia cases, 28 prolonged jaundice cases, and 41 controls. Ten common polymorphisms in four genes involved in bilirubin metabolism were examined. Polymerase chain reaction-restriction fragment length polymorphism method was used to detect variants of those genes. Results: No association was found between the variants of UGT1A1 at nt 211, the SLCO1B1 gene at nt 388, 463, 521, 1463, the SLCO1B3 gene at nt 334, 727+118, 1865+19721, and the GST gene at nt 313, 341, and neonatal hyperbilirubinemia. There was no difference between the case and control groups in terms of allele frequencies of these genes (except SLCO1B3 at nt 334) (p>0.05 in all comparisons). The presence of the G allele of the SLCO1B3 at nt 334 variant gene seemed to protect from jaundice in infants with idiopathic hyperbilirubinemia. Conclusion: These gene polymorphisms currently studied do not seem to modulate the risk of hyperbilirubinemia in Turkish newborn infants.

SLCO1B1 and ABCG2 genotype-informed phenotypes are related to variation in ramipril exposure.

Ramipril is an angiotensin-converting enzyme inhibitor used for hypertension and heart failure management. To date, scarce literature is available on pharmacogenetic associations affecting ramipril. The goal of this study was to investigate the effect of 120 genetic variants in 34 pharmacogenes (i.e., genes encoding for enzymes like CYPs or UGTs and transporters like ABC or SLC) on ramipril pharmacokinetic variability and adverse drug reaction (ADR) incidence. Twenty-nine healthy volunteers who had participated in a single-dose bioequivalence clinical trial of two formulations of ramipril were recruited. A univariate and multivariate analysis searching for associations between genetic variants and ramipril pharmacokinetics was performed. SLCO1B1 and ABCG2 genotype-informed phenotypes strongly predicted ramipril exposure. Volunteers with the SLCO1B1 decreased function (DF) phenotype presented around 1.7-fold higher dose/weight-corrected area under the curve (AUC/DW) than volunteers with the normal function (NF) phenotype (univariate p-value [puv] < 0.001, multivariate p-value [pmv] < 0.001, ß = 0.533, R2 = 0.648). Similarly, volunteers with ABCG2 DF + poor function (PF) phenotypes presented around 1.6-fold higher AUC/DW than those with the NF phenotype (puv = 0.011, pmv < 0.001, ß = 0.259, R2 = 0.648). Our results suggest that SLCO1B1 and ABCG2 are important transporters to ramipril pharmacokinetics, and their genetic variation strongly alters its pharmacokinetics. Further studies are required to confirm these associations and their clinical relevance.

Allelic frequencies of polymorphism c.521T>C (rs4149056) favor preemptive SLCO1B1 genotyping in Armenia.

OBJECTIVES: Statins represent an important pharmacological factor for the prevention of cardiovascular diseases but may also cause severe cases of myotoxicity. Numerous studies have described the association of the SLCO1B1 gene variant c.521C with statin-induced myopathy across different populations. This study aimed at evaluating the usefulness of preemptive SLCO1B1 genotyping in Armenia. METHODS: A total of 202 Armenian patients referred to the Center of Medical Genetics and Primary Health Care in Yerevan for upper respiratory tract infection between January and May 2022 were included in this study. Genotyping for SLCO1B1 c.521T>C (rs4149056) was performed using a commercially available real-time PCR assay (RealFast™). RESULTS: In total, 3/202 (1.5 %) samples were C/C homozygotes and 52/202 (25.7 %) were T/C heterozygotes, associated with a high and increased risk for statin-induced myopathy, respectively. The SLCO1B1 c.521C allelic frequency was 14.4 %. CONCLUSIONS: The observed allele frequency of 14.4 % for the c.521C variant is slightly lower than frequencies reported from Europe, but relatively high compared to Asian populations, suggesting that preemptive SLCO1B1 genotyping could be a useful approach for the reduction of statin-induced adverse effects in Armenia.

Utilizing Pharmacogenomic Data for a Safer Use of Statins among the Emirati Population.

BACKGROUND: Statins are the most prescribed lipid-lowering drugs worldwide. The associated adverse events, especially muscle symptoms, have been frequently reported despite their perceived safety. Three pharmacogenes, the solute carrier organic anion transporter family member 1B1 (SLCO1B1), ATP-binding cassette subfamily G member 2 (ABCG2), and cytochrome P450 2C9 (CYP2C9) are suggested as safety biomarkers for statins. The Clinical Pharmacogenomic Implementation Consortium (CPIC) issued clinical guidelines for statin use based on these three genes. OBJECTIVES: The present study aimed to examine variants in these pharmacogenes to predict the safety of statin use among the Emirati population. METHODS: Analyzing 242 whole exome sequencing data at the three genes enabled the determination of the frequencies of the single nucleotide polymorphisms (SNPs), annotating the haplotypes and the predicted functions of their proteins. RESULTS: In our cohort, 29.8% and 5.4% had SLCO1B1 decreased and poor function, respectively. The high frequency warns of the possibility of significant side effects of some statins and the importance of pharmacogenomic testing. We found a low frequency (6%) of the ABCG2:rs2231142 variant, which indicates the low probability of Emirati patients being recommended against higher rosuvastatin doses compared with other populations with higher frequencies of this variant. In contrast, we found high frequencies of the functionally impaired CYP2C9 alleles, which makes fluvastatin a less favorable choice. CONCLUSION: Among the sparse studies available, the present one demonstrates all SLCO1B1 and CYP2C9 function-impairing alleles among Emiratis. We highlighted how population-specific pharmacogenomic data can predict safer choices of statins, especially in understudied populations.

Physiologically based pharmacokinetic (PBPK) modeling of pitavastatin in relation to SLCO1B1 genetic polymorphism.

Pitavastatin, a potent 3-hydroxymethylglutaryl coenzyme A reductase inhibitor, is indicated for the treatment of hypercholesterolemia and mixed dyslipidemia. Hepatic uptake of pitavastatin is predominantly occupied by the organic anion transporting polypeptide 1B1 (OATP1B1) and solute carrier organic anion transporter family member 1B1 (SLCO1B1) gene, which is a polymorphic gene that encodes OATP1B1. SLCO1B1 genetic polymorphism significantly alters the pharmacokinetics of pitavastatin. This study aimed to establish the physiologically based pharmacokinetic (PBPK) model to predict pitavastatin pharmacokinetics according to SLCO1B1 genetic polymorphism. PK-Sim® version 10.0 was used to establish the whole-body PBPK model of pitavastatin. Our pharmacogenomic data and a total of 27 clinical pharmacokinetic data with different dose administration and demographic properties were used to develop and validate the model, respectively. Physicochemical properties and disposition characteristics of pitavastatin were acquired from previously reported data or optimized to capture the plasma concentration-time profiles in different SLCO1B1 diplotypes. Model evaluation was performed by comparing the predicted pharmacokinetic parameters and profiles to the observed data. Predicted plasma concentration-time profiles were visually similar to the observed profiles in the non-genotyped populations and different SLCO1B1 diplotypes. All fold error values for AUC and Cmax were included in the two fold range of observed values. Thus, the PBPK model of pitavastatin in different SLCO1B1 diplotypes was properly established. The present study can be useful to individualize the dose administration strategy of pitavastatin in individuals with various ages, races, and SLCO1B1 diplotypes.

Variability in plasma rifampicin concentrations and role of SLCO1B1, ABCB1, AADAC2 and CES2 genotypes in Ethiopian patients with tuberculosis.

BACKGROUND: Rifampicin, a key drug against tuberculosis (TB), displays wide between-patient pharmacokinetics variability and concentration-dependent antimicrobial effect. We investigated variability in plasma rifampicin concentrations and the role of SLCO1B1, ABCB1, arylacetamide deacetylase (AADAC) and carboxylesterase 2 (CES-2) genotypes in Ethiopian patients with TB. METHODS: We enrolled adult patients with newly diagnosed TB (n = 119) who had received 2 weeks of rifampicin-based anti-TB therapy. Venous blood samples were obtained at three time points post-dose. Genotypes for SLCO1B1 (c.388A > G, c.521T > C), ABCB1 (c.3435C > T, c.4036A > G), AADACc.841G > A and CES-2 (c.269-965A > G) were determined. Rifampicin plasma concentration was quantified using LC-MS/MS. Predictors of rifampicin Cmax and AUC0-7 h were analysed. RESULTS: The median rifampicin Cmax and AUC0-7 were 6.76 µg/mL (IQR 5.37-8.48) and 17.05 µg·h/mL (IQR 13.87-22.26), respectively. Only 30.3% of patients achieved the therapeutic efficacy threshold (Cmax>8 µg/mL). The allele frequency for SLCO1B1*1B (c.388A > G), SLCO1B1*5 (c.521T > C), ABCB1 c.3435C > T, ABCB1c.4036A > G, AADAC c.841G > A and CES-2 c.269-965A > G were 2.2%, 20.2%, 24.4%, 14.6%, 86.1% and 30.6%, respectively. Sex, rifampicin dose and ABCB1c.4036A > G, genotypes were significant predictors of rifampicin Cmax and AUC0-7. AADACc.841G > A genotypes were significant predictors of rifampicin Cmax. There was no significant influence of SLCO1B1 (c.388A > G, c.521T > C), ABCB1c.3435C > T and CES-2 c.269-965A > G on rifampicin plasma exposure variability. CONCLUSIONS: Subtherapeutic rifampicin plasma concentrations occurred in two-thirds of Ethiopian TB patients. Rifampicin exposure varied with sex, dose and genotypes. AADACc.841G/G and ABCB1c.4036A/A genotypes and male patients are at higher risk of lower rifampicin plasma exposure. The impact on TB treatment outcomes and whether high-dose rifampicin is required to improve therapeutic efficacy requires further investigation.

The impact of SLCO1B1 rs4149056 on LDL-C target achievement after lipid lowering therapy optimization in men and women with familial hypercholesterolemia.

Background and aims: FH women are less likely to receive intensive statin treatment and to obtain a 50% reduction of LDL-C from baseline compared to men with FH. SLCO1B1 rs4149056 might influence statin therapy compliance and thus LDL-C target achievement. Our aim was to evaluate the impact of SLCO1B1 rs4149056 on LDL-C target achievement after lipid lowering therapy (LLT) optimization in men and women with FH. Methods: This was a retrospective observational study involving 412 FH subjects with a probable or defined clinical diagnosis of FH who had had genetic analysis from June 2016 to September 2022. Biochemical analysis was obtained from all subjects at baseline and at the last follow-up after LLT optimization. Results: After LLT optimization the percentage of FH subjects on high-intensity statins decreased from the M/SLCO1B1- group to the W/SLCO1B1+ group and the same was found in LDL-C target distribution (for both p for trend < 0.01). The prevalence of SASE fear increased from the M/SLCO1B1- group to the W/SLCO1B1+ group and the same was observed in reported myalgia distribution (for both p for trend < 0.01). Logistic regression analysis showed that the W/SCLO1B1-, M/SCLO1B1+ and W/SCLO1B1+ groups were inversely associated with LDL-C target achievement (p for trend < 0.001) and the W/SCLO1B1+ group exhibited the strongest association. Conclusion: A low prevalence of FH women with SLCO1B1 rs4149056 were on high intensity statins and they rarely achieved LDL-C target. The genotype effect of SLCO1B1 rs4149056 could be more pronounced in FH women than men.

Construction and characterization of a humanized SLCO1B1 rat model with its application in evaluating the uptake of different statins.

Organic anion-transporting polypeptides 1B1 (OATP1B1) plays a crucial role in the transport of statins. However, there are too few animal models related to OATP1B1, especially humanized animal models. In this study, the human SLCO1B1 cDNA was inserted into the second exon of the rat Slco1b2 gene using CRISPR/Cas9 technology. Pharmacokinetic characteristics of statins were conducted in wild-type (WT), humanized OATP1B1 (hOATP1B1), and OATP1B2 knockout (OATP1B2 KO) rats, respectively. The results showed that human OATP1B1 was successfully expressed in rat liver and exhibited transport function. Furthermore, the pharmacokinetic results revealed that OATP1B1 exhibited varying uptake levels of pivastatin, rosuvastatin, and fluvastatin, leading to different levels of exposure within the body. These results were consistent with those obtained from in vitro experiments using overexpressed cell lines. In conclusion, we established a novel humanized SLCO1B1 transgenic rat model to assess the role of human OATP1B1 in the uptake of different statins. The different uptake mediated by OATP1B1 may be an important reason for the different efficacy of statins. The hOATP1B1 rat is a promising model for improving the prediction of human drug transport.

Distinguishing Molecular Properties of OAT, OATP, and MRP Drug Substrates by Machine Learning.

The movement of organic anionic drugs across cell membranes is partly governed by interactions with SLC and ABC transporters in the intestine, liver, kidney, blood-brain barrier, placenta, breast, and other tissues. Major transporters involved include organic anion transporters (OATs, SLC22 family), organic anion transporting polypeptides (OATPs, SLCO family), and multidrug resistance proteins (MRPs, ABCC family). However, the sets of molecular properties of drugs that are necessary for interactions with OATs (OAT1, OAT3) vs. OATPs (OATP1B1, OATP1B3) vs. MRPs (MRP2, MRP4) are not well-understood. Defining these molecular properties is necessary for a better understanding of drug and metabolite handling across the gut-liver-kidney axis, gut-brain axis, and other multi-organ axes. It is also useful for tissue targeting of small molecule drugs and predicting drug-drug interactions and drug-metabolite interactions. Here, we curated a database of drugs shown to interact with these transporters in vitro and used chemoinformatic approaches to describe their molecular properties. We then sought to define sets of molecular properties that distinguish drugs interacting with OATs, OATPs, and MRPs in binary classifications using machine learning and artificial intelligence approaches. We identified sets of key molecular properties (e.g., rotatable bond count, lipophilicity, number of ringed structures) for classifying OATs vs. MRPs and OATs vs. OATPs. However, sets of molecular properties differentiating OATP vs. MRP substrates were less evident, as drugs interacting with MRP2 and MRP4 do not form a tight group owing to differing hydrophobicity and molecular complexity for interactions with the two transporters. If the results also hold for endogenous metabolites, they may deepen our knowledge of organ crosstalk, as described in the Remote Sensing and Signaling Theory. The results also provide a molecular basis for understanding how small organic molecules differentially interact with OATs, OATPs, and MRPs.

Influence of pharmacogenetics on the diversity of response to statins associated with adverse drug reactions.

Background: Statins are one of the most prescribed medications in developed countries as the treatment of choice for reducing cholesterol and preventing cardiovascular diseases. However, a large proportion of patients experience adverse drug reactions, especially myotoxicity. Among the factors that influence the diversity of response, pharmacogenetics emerges as a relevant factor of influence in inter-individual differences in response to statins and can be useful in the prevention of adverse drug effects. Content: A systematic review was performed of current knowledge of the influence of pharmacogenetics on the occurrence and prevention of statin-associated adverse reactions and clinical benefits of preemptive pharmacogenetics testing. Summary: Genetic variants SLCO1B1 (rs4149056) for all statins; ABCG2 (rs2231142) for rosuvastatin; or CYP2C9 (rs1799853 and rs1057910) for fluvastatin are associated with an increase in muscle-related adverse effects and poor treatment adherence. Besides, various inhibitors of these transporters and biotransformation enzymes increase the systemic exposure of statins, thereby favoring the occurrence of adverse drug reactions. Outlook: The clinical preemptive testing of this pharmacogenetic panel would largely prevent the incidence of adverse drug reactions. Standardized methods should be used for the identification of adverse effects and the performance and interpretation of genotyping test results. Standardization would allow to obtain more conclusive results about the association between SLCO1B1, ABCG and CYP2C9 variants and the occurrence of adverse drug reactions. As a result, more personalized recommendations could be established for each statin.

Pharmacogenetic aspects of efficacy and safety of methotrexate treatment in pediatric acute lymphoblastic leukemia.

OBJECTIVES: To evaluate the role of ABCB1 (C3435T rs1045642, rs1128503, rs2032582, rs4148738), SLCO1B1 T521C rs4149056 genetic polymorphisms in the development of major types of methotrexate (MTX) toxicities and the occurrence of a terminal event (death, relapse) in pediatric АLL. METHODS: The study included 124 patients diagnosed with pediatric ALL. All patients treated according to the protocols of the German BFM group (2002/2009) with high-dose (1,000, 2,000 and 5,000 mg/m2) methotrexate. MTX-related toxicities, including hematologic, hepatic and renal, were evaluated according to the common terminology criteria for adverse events version 5.0 (CTCAE v.5.0). Real-time PCR method was used to investigate polymorphisms of ABCB1 and SLCO1B1 genes. The study material was peripheral blood. RESULTS: A competitive analysis demonstrated significant relationships between MTX ADRs. The results of the study support the existence of relationships between some ADRs and MTX kinetics. An associative analysis showed association with the development of AEs to methotrexate indicating their clinical significance from different genetic polymorphisms protein-transporters. The available results confirm the associations of the studied genes with the increased risk of high doses MTX toxic ADRs and terminal events. CONCLUSIONS: Complementing the existing criteria for pediatric ALL risk groups with pharmacogenetic indicators will allow further individualization of therapy.