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days 21 and 1, respectively, and peak at 6 months of age before declining with advanced age [75]. Interestingly, older rats (~18 months) have heightened susceptibility to the nephrotoxicity of the Mate1 substrate, cisplatin [76]. This increased susceptibility is likely due to the reduced expression of Mate1 protein as expression of other cisplatin transporters were unchanged in 18‐month‐old rats [76].

Sex differences in Mate transporters have been observed in mice, but not in humans, and may reflect differential regulation by hormones across species. Expression of mMate1 mRNA is slightly higher in the livers of female mice compared with males. However, within female kidneys, mMate1 mRNA levels are lower than that observed in male mice [14]. Interestingly, expression of mMate2 mRNA in the kidneys can be reduced by removal of the ovaries in female mice [77]; supplementation with 17ß‐estradiol restores mMate2 expression. By comparison, there is no change in mMate1 mRNA in ovariectomized mice. Treatment of mice with testosterone for 7 days increases the protein expression of mMate1 and mMate2 [78]. These findings provide initial insights into the hormonal regulation of Mate transporters in mice.

      3.5.4 Pregnancy

      Pregnancy is accompanied by a number of physiologic changes, including increased cardiac output, as well as hepatic and renal blood flow. There has been much interest into adaptive changes in expression of drug transporters within the mother, placenta, and fetus. Pregnant mice exhibit reduced expression of renal mOct1 and 2, as well as mMate1 mRNA and protein [79, 80]. Within the livers of pregnant mice, there is a downregulation of Oct1 with no change in mMate1 levels compared with virgin mice [79]. These data stand in contrast to a study performed in pregnant women prescribed metformin. Notably, the renal clearance of metformin, as well as the endogenous Mate substrate NMN, was markedly increased during mid‐ and late‐pregnancy compared with early pregnancy or the postpartum period [81]. While a significant increase in glomerular filtration rate contributes to enhanced metformin and NMN elimination from the kidneys, the data also suggest enhanced tubular secretion. The mechanism(s) responsible for divergent regulation of the organic cation transport systems during pregnancy (reduced in mice, increased in humans) are unclear and warrant consideration.

      3.5.5 Disease Models

       3.5.5.1 Kidney Disease and Injury

      Acute and chronic renal disease is a significant cause of morbidity and mortality and have been associated with the altered clearance of drugs and toxicants. In rodents, acute and chronic kidney disease can be recapitulated experimentally using surgical nephrectomy, ischemia‐reperfusion injury, and toxicant‐induced damage. Nephrectomy, or 5/6 removal of kidney tissue, mirrors clinical features of chronic renal disease including elevated circulating creatinine and BUN levels. In rats that have undergone 5/6 nephrectomy, the secretion of cimetidine is markedly reduced, which coincided with lower expression of rMate1 [82]. Similarly, ischemic injury can be accomplished within rats by clamping pedicles for a short period of time and then releasing the clamps and re‐establishing blood flow to the kidneys. This results in ischemic‐reperfusion injury as evidenced by elevations in BUN and serum creatinine levels. In rats that have undergone ischemia‐reperfusion injury, the plasma clearance of the antihistamine famotidine and the probe cation TEA are markedly reduced [83]. Compared with sham‐operated rats, expression of Oct2 and Mate1 proteins were decreased by more than 50% in rats with ischemia‐reperfusion injury [83]. As a result, the impaired clearance is likely due to both diminished uptake by Oct1 and 2 transporters and disrupted efflux by MATE transporters, as well as change in filtration.

      Acute kidney injury caused by the cancer drug cisplatin increases BUN and serum creatinine levels and leads to loss of proximal tubules. In rats treated with a toxic dose of cisplatin, there is downregulation of rOct2 and rMate1 protein [84]. Interestingly, the uremic toxin indoxyl sulfate appears to play a role in the reduced levels of both cation transporters as treatment with AST‐120, an adsorbent, partially restored expression of rOct2 and rMate1 protein, as well as improved renal function indicators [84].

       3.5.5.2 Liver Disease and Injury

      Nonalcoholic fatty liver disease is a prevalent disease in the US patients with advanced disease, or steatohepatitis, often have comorbidities such as type II diabetes and chronic kidney disease. Pathologic features of nonalcoholic steatohepatitis can be recapitulated by feeding rodents a diet deficient in methionine and choline (MCD) or in mice with a genetic predisposition for obesity (known as ob/ob mice). Expression of mOct2 and mMate1 mRNA is reduced in the kidneys of ob/ob mice [85]. Feeding ob/ob mice a MCD diet further lowered expression of mOct2 and mMate1 in the kidneys, which was associated with impaired clearance of metformin. Interestingly, changes in mOct1 or mMate1 mRNA expression were observed in the livers of ob/ob mice regardless of diet [85]. Emerging data from humans with nonalcoholic steatohepatitis or untreated type II diabetes demonstrate hypermethylation of the SLC47A1 gene in liver [86, 87]. These data would tend to support decreased hMATE1 expression as methylation status is a contributor to the interindividual regulation of hMATE1 [88].

3.6 DRUG EFFICACY AND TOXICITY

      3.6.1 Clinical Substrates, Probes, and Inhibitors

Several US Food and Drug Administration (FDA) approved drugs have been identified as MATE1 and MATE2‐K substrates. Of those, only metformin is considered a well‐established in vivo MATE substrate for use in clinical interaction studies [89]. By comparison, several inhibitors of MATE1 and MATE2‐K have been recommended for clinical interaction studies, including cimetidine, dolutegravir, isavuconazole, ranolazine, trimethoprim, and vandetanib [89]. An increase in the exposure (area under the plasma concentration‐time curve) in the presence versus absence of a transport inhibitor defines the interaction as strong if ≥5‐fold increase is observed and moderate if a 2‐ to 5‐fold increase is noted [90]. While the FDA does not consider metformin (substrate) or any of the inhibitors as index drugs for prospective drug–drug interaction studies (due to the promiscuity for multiple transporters), clinical interaction studies are advocated to inform about potential interactions during concomitant usage of two drugs. The FDA specifies that if renal secretion accounts for ≥25% of systemic clearance for an investigational drug that has been identified as a MATE substrate from in vitro studies or if there are concerns about kidney toxicity, then a clinical transporter drug–drug interaction study is warranted [90]. Additionally, if an investigational drug is identified as a MATE inhibitor from in vitro studies, then a clinical drug interaction study would incorporate a known substrate that represents the MATE pathway. However, the criteria of the substrate being a likely concomitant drug may not be met in many circumstances.

The drug development process, through preclinical studies, identifies compounds where renal clearance accounts for a significant percentage of the total body clearance. However, since renal clearance can occur through both filtration and secretion, it is important to distinguish the percentage that is accounted for by secretion, in this case by MATE1 or MATE2‐K. The FDA recommends a 25% threshold systemic clearance due to secretion clearance for further evaluation. Additionally, if there is potential nephrotoxicity of a transporter substrate, then drug–drug interactions should be considered since reduced MATE activity could potentiate cellular toxicity. Table 3.3 has collated clearance and exposure data for compounds that are MATE1 and MATE2‐K substrates in humans. Inhibitors of MATE transporters can reduce renal secretory clearance pathway through the relationship of CL_secretion = CL_total − CL_Filtration. The filtration clearance can be estimated by the glomerular filtration rate multiplied by the unbound fraction of the substrate. Highly relevant in Table 3.3 is the expected area under the plasma concentration data for the substrates, as reductions in renal clearance will lead to increased exposures for the substrates and potential toxicities.

      3.6.2 Pharmacokinetic Drug Interactions

According

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