Non-targeted metabolomics for the identification of plasma metabolites associated with organic anion transporting polypeptide 1B1 function

Our aim was to evaluate biomarkers for organic anion transporting polypeptide 1B1 (OATP1B1) function using a hypothesis-free metabolomics approach. We analyzed fasting plasma samples from 356 healthy volunteers using non-targeted metabolite profiling by liquid chromatography high-resolution mass spectrometry. Based on SLCO1B1 genotypes, we stratified the volunteers to poor, decreased, normal, increased, and highly increased OATP1B1 function groups. Linear regression analysis, and random forest (RF) and gradient boosted decision tree (GBDT) regressors were used to investigate associations of plasma metabolite features with OATP1B1 function. Of the 9152 molecular features found, 39 associated with OATP1B1 function either in the linear regression analysis (p < 10-5) or the RF or GBDT regressors (Gini impurity decrease > 0.01). Linear regression analysis showed the strongest associations with two features identified as glycodeoxycholate 3-O-glucuronide (GDCA-3G; p = 1.2 × 10-20 for negative and p = 1.7 × 10-19 for positive electrospray ionization) and one identified as glycochenodeoxycholate 3-O-glucuronide (GCDCA-3G; p = 2.7 × 10-16). In both the RF and GBDT models, the GCDCA-3G feature showed the strongest association with OATP1B1 function, with Gini impurity decreases of 0.40 and 0.17. In RF, this was followed by one GDCA-3G feature, an unidentified feature with a molecular weight of 809.3521, and the second GDCA-3G feature. In GBDT, the second and third strongest associations were observed with the GDCA-3G features. Of the other associated features, we identified with confidence two representing lysophosphatidylethanolamine 22:5. In addition, one feature was putatively identified as pregnanolone sulfate and one as pregnenolone sulfate. These results confirm GCDCA-3G and GDCA-3G as robust OATP1B1 biomarkers in human plasma.

Solanidine is a sensitive and specific dietary biomarker for CYP2D6 activity

BACKGROUND

Individual assessment of CYP enzyme activities can be challenging. Recently, the potato alkaloid solanidine was suggested as a biomarker for CYP2D6 activity. Here, we aimed to characterize the sensitivity and specificity of solanidine as a CYP2D6 biomarker among Finnish volunteers with known CYP2D6 genotypes.

RESULTS

Using non-targeted metabolomics analysis, we identified 9152 metabolite features in the fasting plasma samples of 356 healthy volunteers. Machine learning models suggested strong association between CYP2D6 genotype-based phenotype classes with a metabolite feature identified as solanidine. Plasma solanidine concentration was 1887% higher in genetically poor CYP2D6 metabolizers (gPM) (n = 9; 95% confidence interval 755%, 4515%; P = 1.88 × 10-11), 74% higher in intermediate CYP2D6 metabolizers (gIM) (n = 89; 27%, 138%; P = 6.40 × 10-4), and 35% lower in ultrarapid CYP2D6 metabolizers (gUM) (n = 20; 64%, - 17%; P = 0.151) than in genetically normal CYP2D6 metabolizers (gNM; n = 196). The solanidine metabolites m/z 444 and 430 to solanidine concentration ratios showed even stronger associations with CYP2D6 phenotypes. Furthermore, the areas under the receiver operating characteristic and precision-recall curves for these metabolic ratios showed equal or better performances for identifying the gPM, gIM, and gUM phenotype groups than the other metabolites, their ratios to solanidine, or solanidine alone. In vitro studies with human recombinant CYP enzymes showed that solanidine was metabolized mainly by CYP2D6, with a minor contribution from CYP3A4/5. In human liver microsomes, the CYP2D6 inhibitor paroxetine nearly completely (95%) inhibited the metabolism of solanidine. In a genome-wide association study, several variants near the CYP2D6 gene associated with plasma solanidine metabolite ratios.

CONCLUSIONS

These results are in line with earlier studies and further indicate that solanidine and its metabolites are sensitive and specific biomarkers for measuring CYP2D6 activity. Since potato consumption is common worldwide, this biomarker could be useful for evaluating CYP2D6-mediated drug-drug interactions and to improve prediction of CYP2D6 activity in addition to genotyping.

Real-world pharmacogenetics of statin intolerance: effects of SLCO1B1, ABCG2 , and CYP2C9 variants

OBJECTIVE

The association of SLCO1B1 c.521T>C with simvastatin-induced muscle toxicity is well characterized. However, different statins are subject to metabolism and transport also by other proteins exhibiting clinically meaningful genetic variation. Our aim was to investigate associations of SLCO1B1 c.521T>C with intolerance to atorvastatin, fluvastatin, pravastatin, rosuvastatin, or simvastatin, those of ABCG2 c.421C>A with intolerance to atorvastatin, fluvastatin, or rosuvastatin, and that of CYP2C9*2 and *3 alleles with intolerance to fluvastatin.

METHODS

We studied the associations of these variants with statin intolerance in 2042 patients initiating statin therapy by combining genetic data from samples from the Helsinki Biobank to clinical chemistry and statin purchase data.

RESULTS

We confirmed the association of SLCO1B1 c.521C/C genotype with simvastatin intolerance both by using phenotype of switching initial statin to another as a marker of statin intolerance [hazard ratio (HR) 1.88, 95% confidence interval (CI) 1.08-3.25, P  = 0.025] and statin switching along with creatine kinase measurement (HR 5.44, 95% CI 1.49-19.9, P  = 0.011). No significant association was observed with atorvastatin and rosuvastatin. The sample sizes for fluvastatin and pravastatin were relatively small, but SLCO1B1 c.521T>C carriers had an increased risk of pravastatin intolerance defined by statin switching when compared to homozygous reference T/T genotype (HR 2.11, 95% CI 1.01-4.39, P  = 0.047).

CONCLUSION

The current results can inform pharmacogenetic statin prescribing guidelines and show feasibility for the methodology to be used in larger future studies.

Pharmacogenomics of celiprolol - evidence for a role of P-glycoprotein and organic anion transporting polypeptide 1A2 in celiprolol pharmacokinetics

The aim of this study was to search for associations of genetic variants with celiprolol pharmacokinetics in a large set of pharmacokinetic genes, and, more specifically, in a set of previously identified candidate genes ABCB1, SLCO1A2, and SLCO2B1. To this end, we determined celiprolol single‐dose (200 mg) pharmacokinetics and sequenced 379 pharmacokinetic genes in 195 healthy volunteers. Analysis with 46,064 common sequence variants in the 379 genes did not identify any novel genes associated with celiprolol exposure. The candidate gene analysis showed that the ABCB1 c.3435T>C and c.2677T/G>A, and the SLCO1A2 c.516A>C variants were associated with reduced celiprolol area under the plasma concentration‐time curve (AUC_0–∞). An alternative analysis with ABCB1 haplotypes showed that, in addition to SLCO1A2 c.516A>C, three ABCB1 haplotypes were associated with reduced celiprolol AUC_0–∞. A genotype scoring system was developed based on these variants and applied to stratify the participants to low and high celiprolol exposure genotype groups. The mean AUC_0–∞ of celiprolol in the low exposure genotype group was 55% of the mean AUC_0–∞ in the high exposure group (p = 1.08 × 10⁻¹¹). In addition, the results showed gene‐gene interactions in the effects of SLCO1A2 and ABCB1 variants on celiprolol AUC_0–∞ (p < 5 × 10⁻⁶) suggesting an interplay between organic anion transporting polypeptide 1A2 and P‐glycoprotein in celiprolol absorption. Taken together, these data indicate that P‐glycoprotein and organic anion transporting polypeptide 1A2 play a role in celiprolol pharmacokinetics. Furthermore, patients with ABCB1 and SLCO1A2 genotypes associated with low celiprolol exposure may have an increased risk of poor blood‐pressure lowering response to celiprolol.

Performance of Plasma Coproporphyrin I and III as OATP1B1 Biomarkers in Humans

A previous study in 356 healthy Finnish volunteers showed that glycochenodeoxycholate 3‐O‐glucuronide (GCDCA‐3G) and glycodeoxycholate 3‐O‐glucuronide (GDCA‐3G) are promising biomarkers of organic anion transporting polypeptide 1B1 (OATP1B1). In the same cohort, we now evaluated the performances of two other OATP1B1 biomarkers, coproporphyrin I (CPI) and III (CPIII), and compared them with GCDCA‐3G and GDCA‐3G. Based on decreased (*5 and *15) and increased (*14 and *20) function SLCO1B1 haplotypes, we stratified the participants to poor, decreased, normal, increased, and highly increased OATP1B1 function groups. Fasting plasma CPI concentration was 68% higher in the poor (95% confidence interval, 44%, 97%; P = 1.74 × 10⁻¹⁰), 7% higher in the decreased (0%, 15%; P = 0.0385), 10% lower in the increased (3%, 18%; P = 0.0087), and 23% lower in the highly increased (1%, 40%; P = 0.0387) function group than in the normal function group. CPIII concentration was 27% higher (7%, 51%; P = 0.0071) in the poor function group than in the normal function group. CPI and CPIII detected poor OATP1B1 function with areas under the precision‐recall curve (AUPRC) of 0.388 (95% confidence interval, 0.197, 0.689) and 0.0798 (0.0485, 0.203), and receiver operating characteristic curve (AUROC) of 0.888 (0.851, 0.919) and 0.731 (0.682, 0.776). The AUPRC and AUROC of GCDCA‐3G were, however, 0.389 (0.258, 0.563) and 0.100 (−0.0046, 0.204; P = 0.0610) larger than those of CPI, and 0.697 (0.555, 0.831) and 0.257 (0.141, 0.373; P < 0.0001) larger than those of CPIII. In conclusion, these data indicate that plasma CPI outperforms CPIII in detecting altered OATP1B1 function, but GCDCA‐3G is an even more sensitive OATP1B1 biomarker than CPI.

Comparative Hepatic and Intestinal Efflux Transport of Statins

Previous studies have shown that lipid-lowering statins are transported by various ATP-binding cassette (ABC) transporters. However, because of varying methods, it is difficult to compare the transport profiles of statins. Therefore, we investigated the transport of 10 statins or statin metabolites by six ABC transporters using human embryonic kidney cell-derived membrane vesicles. The transporter protein expression levels in the vesicles were quantified with liquid chromatography-tandem mass spectrometry and used to scale the measured clearances to tissue levels. In our study, apically expressed breast cancer resistance protein (BCRP) and P-glycoprotein (P-gp) transported atorvastatin, fluvastatin, pitavastatin, and rosuvastatin. Multidrug resistance-associated protein 3 (MRP3) transported atorvastatin, fluvastatin, pitavastatin, and, to a smaller extent, pravastatin. MRP4 transported fluvastatin and rosuvastatin. The scaled clearances suggest that BCRP contributes to 87%-91% and 84% of the total active efflux of rosuvastatin in the small intestine and the liver, respectively. For atorvastatin, the corresponding values for P-gp-mediated efflux were 43%-79% and 66%, respectively. MRP3, on the other hand, may contribute to 23%-26% and 25%-37% of total active efflux of atorvastatin, fluvastatin, and pitavastatin in jejunal enterocytes and liver hepatocytes, respectively. These data indicate that BCRP may play an important role in limiting the intestinal absorption and facilitating the biliary excretion of rosuvastatin and that P-gp may restrict the intestinal absorption and mediate the biliary excretion of atorvastatin. Moreover, the basolateral MRP3 may enhance the intestinal absorption and sinusoidal hepatic efflux of several statins. Taken together, the data show that statins differ considerably in their efflux transport profiles. SIGNIFICANCE STATEMENT: This study characterized and compared the transport of atorvastatin, fluvastatin, pitavastatin, pravastatin, rosuvastatin, and simvastatin acid and four atorvastatin metabolites by six ABC transporters (BCRP, MRP2, MRP3, MRP4, MRP8, P-gp). Based on in vitro findings and protein abundance data, the study concludes that BCRP, MRP3, and P-gp have a major impact in the efflux of various statins. Together with in vitro metabolism, uptake transport, and clinical data, our findings are applicable for use in comparative systems pharmacology modeling of statins.

Comparative Hepatic and Intestinal Metabolism and Pharmacodynamics of Statins

This study aimed to comprehensively investigate the in vitro metabolism of statins. The metabolism of clinically relevant concentrations of atorvastatin, fluvastatin, pitavastatin, pravastatin, rosuvastatin, simvastatin, and their metabolites were investigated using human liver microsomes (HLMs), human intestine microsomes (HIMs), liver cytosol, and recombinant cytochrome P450 enzymes. We also determined the inhibitory effects of statin acids on their pharmacological target, 3-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase. In HLMs, statin lactones were metabolized to a much higher extent than their acid forms. Atorvastatin lactone and simvastatin (lactone) showed extensive metabolism [intrinsic clearance (CL_int) values of 3700 and 7400 µl/min per milligram], whereas the metabolism of the lactones of 2-hydroxyatorvastatin, 4-hydroxyatorvastatin, and pitavastatin was slower (CL_int 20-840 µl/min per milligram). The acids had CL_int values in the range <0.1-80 µl/min per milligram. In HIMs, only atorvastatin lactone and simvastatin (lactone) exhibited notable metabolism, with CL_int values corresponding to 20% of those observed in HLMs. CYP3A4/5 and CYP2C9 were the main statin-metabolizing enzymes. The majority of the acids inhibited HMG-CoA reductase, with 50% inhibitory concentrations of 4-20 nM. The present comparison of the metabolism and pharmacodynamics of the various statins using identical methods provides a strong basis for further application, e.g., comparative systems pharmacology modeling. SIGNIFICANCE STATEMENT: The present comparison of the in vitro metabolic and pharmacodynamic properties of atorvastatin, fluvastatin, pitavastatin, pravastatin, rosuvastatin, and simvastatin and their metabolites using unified methodology provides a strong basis for further application. Together with in vitro drug transporter and clinical data, the present findings are applicable for use in comparative systems pharmacology modeling to predict the pharmacokinetics and pharmacological effects of statins at different dosages.

Identification of Glycochenodeoxycholate 3-O-Glucuronide and Glycodeoxycholate 3-O-Glucuronide as Highly Sensitive and Specific OATP1B1 Biomarkers

The aim of this study was to investigate the sensitivity and specificity of endogenous glycochenodeoxycholate and glycodeoxycholate 3-O-glucuronides (GCDCA-3G and GDCA-3G) as substrates for organic anion transporting polypeptide 1B1 (OATP1B1) in humans. We measured fasting levels of plasma GCDCA-3G and GDCA-3G using liquid chromatography-tandem mass spectrometry in 356 healthy volunteers. The mean plasma levels of both compounds were ~ 50% lower in women than in men (P = 2.25 × 10^-18 and P = 4.73 × 10^-9 ). In a microarray-based genome-wide association study, the SLCO1B1 rs4149056 (c.521T>C, p.Val174Ala) variation showed the strongest association with the plasma GCDCA-3G (P = 3.09 × 10^-30 ) and GDCA-3G (P = 1.60 × 10^-17 ) concentrations. The mean plasma concentration of GCDCA-3G was 9.2-fold (P = 8.77 × 10^-31 ) and that of GDCA-3G was 6.4-fold (P = 2.45x10^-13 ) higher in individuals with the SLCO1B1 c.521C/C genotype than in those with the c.521T/T genotype. No other variants showed independent genome-wide significant associations with GCDCA-3G or GDCA-3G. GCDCA-3G was highly efficacious in detecting the SLCO1B1 c.521C/C genotype with an area under the receiver operating characteristic curve of 0.996 (P < 0.0001). The sensitivity (98-99%) and specificity (100%) peaked at a cutoff value of 180 ng/mL for men and 90 ng/mL for women. In a haplotype-based analysis, SLCO1B1*5 and *15 were associated with reduced, and SLCO1B1*1B, *14, and *35 with increased OATP1B1 function. In vitro, both GCDCA-3G and GDCA-3G showed at least 6 times higher uptake by OATP1B1 than OATP1B3 or OATP2B1. These data indicate that the hepatic uptake of GCDCA-3G and GDCA-3G is predominantly mediated by OATP1B1. GCDCA-3G, in particular, is a highly sensitive and specific OATP1B1 biomarker in humans.

Enantiospecific Pharmacogenomics of Fluvastatin

The aim of this study was to investigate how variability in multiple genes related to pharmacokinetics affects fluvastatin exposure. We determined fluvastatin enantiomer pharmacokinetics and sequenced 379 pharmacokinetic genes in 200 healthy volunteers. CYP2C9*3 associated with significantly increased area under the plasma concentration-time curve (AUC) of both 3R,5S-fluvastatin and 3S,5R-fluvastatin (by 67% and 94% per variant allele copy, P = 3.77 × 10^-9 and P = 3.19 × 10^-12 ). In contrast, SLCO1B1 c.521T>C associated with increased AUC of active 3R,5S-fluvastatin only (by 34% per variant allele copy; P = 8.15 × 10^-8 ). A candidate gene analysis suggested that CYP2C9*2 also affects the AUC of both fluvastatin enantiomers and that SLCO2B1 single-nucleotide variations may affect the AUC of 3S,5R-fluvastatin. Thus, SLCO transporters have enantiospecific effects on fluvastatin pharmacokinetics in humans. Genotyping of both CYP2C9 and SLCO1B1 may be useful in predicting fluvastatin efficacy and myotoxicity.

Comprehensive Pharmacogenomic Study Reveals an Important Role of UGT1A3 in Montelukast Pharmacokinetics

To identify the genetic basis of interindividual variability in montelukast exposure, we determined its pharmacokinetics and sequenced 379 pharmacokinetic genes in 191 healthy volunteers. An intronic single nucleotide variation (SNV), strongly linked with UGT1A3*2, associated with reduced area under the plasma concentration–time curve (AUC_0‐∞) of montelukast (by 18% per copy of the minor allele; P = 1.83 × 10⁻¹⁰). UGT1A3*2 was associated with increased AUC_0‐∞ of montelukast acyl‐glucuronide M1 and decreased AUC_0‐∞ of hydroxymetabolites M5R, M5S, and M6 (P < 10⁻⁹). Furthermore, SNVs in SLCO1B1 and ABCC9 were associated with the AUC_0‐∞ of M1 and M5R, respectively. In addition, a candidate gene analysis suggested that CYP2C8 and ABCC9 SNVs also affect the AUC_0‐∞ of montelukast. The found UGT1A3 and ABCC9 variants associated with increased expression of the respective genes in human liver samples. Montelukast and its hydroxymetabolites were glucuronidated by UGT1A3 in vitro. These results indicate that UGT1A3 plays an important role in montelukast pharmacokinetics, especially in UGT1A3*2 carriers.