Screening study for genetic polymorphisms affecting pharmacokinetics of talniflumate

Talniflumate is a phthalidyl ester of niflumic acid, which has potent analgesic and anti-inflammatory effects and is widely used to treat inflammatory disorders, such as rheumatoid arthritis. To screen the possible genetic factors affecting the pharmacokinetics (PK) of talniflumate, 23 male Korean volunteers were enrolled from two separate bioequivalence studies. All subjects received 740 mg (two tablets) talniflumate in a standard 2×2 cross-over model in a randomized order. For the genetic study, PK parameters of the reference drug were used. We used Illumina Human610Quad v1.0 DNA Analysis BeadChip for whole genome single nucleotide polymorphism (SNP) analysis and whole genome genotyping data were processed by linear regression analysis for PK parameters. Whole genome analysis revealed 1498 significant SNPs (P < 0.0001) for Cmax, 65 significant SNPs (P < 0.0001) for T(max), and 1491 significant SNPs (P < 0.0001) for AUC(inf). For clinical pharmacological purposes, we selected SNPs from drug metabolizing enzymes and transporters, and analyzed the PK parameters of various genotypes. Two SNPs (rs11165069 from ABCA4 (p=0.00002); rs17847036 from CYP2C9 (p=0.000001)) showed significant associations with talniflumate C(max). In the T(max) group, two SNPs (rs3787555 from CYP24A1 (p=0.00035); rs2275034 from ABCA4 (p=0.000587)) showed significant associations with talniflumate T(max). In the AUC(inf) group, two SNPs (rs11165069 from ABCA4 (p=0.00002); rs12461006 from SLC1A6 (p=0.00008)) exhibited significant associations with talniflumate absorption. These results show that genetic factors could affect the PK parameters, and provide information that may be used in the development of personalized talniflumate therapy.

Screening study for genetic polymorphisms affecting pharmacokinetics of simvastatin

Simvastatin reduces plasma cholesterol by inhibiting HMG-CoA reductase (HMGR) and is widely used in the treatment of hypercholesterolemia. To screening the possible genetic factors affecting the pharmacokinetics (PK) of simvastatin, 35 male Korean volunteers were enrolled from two separate bioequivalence studies. Each subject was administered 20 mg simvastatin and reference drug PK parameters were used. We used Illumina Human610Quad v1.0 DNA Analysis BeadChip for whole genome SNPs analysis and whole genome genotyping data was processed by linear regression analysis for PK parameters of drug metabolizing enzymes and transporters. We found 145 significant SNPs (P < 0.01) in C(max), 135 significant SNPs (P < 0.01) in T(max) and 85 significant SNPs (P < 0.01) in AUC(inf) from whole genome analysis. In particular, we found that the ABCC2 gene had a significant effect on C(max) and AUC(inf). These results could provide information of possible candidate genes for personalized simvastatin therapy.

Screening study for genetic polymorphisms affecting pharmacokinetics of pioglitazone

Pioglitazone is known to have antidiabetic effects through decreasing peripheral, hepatic and vascular insulin resistance by the stimulation of PPAR gamma. To address the possible genetic factors affecting the pharmacokinetics (PK) of pioglitazone, 27 male Korean volunteers were enrolled from two separate bioequivalence studies. Each subject was administered 15 mg pioglitazone and reference drug PK parameters were used. We used Illumina Human610 Quad v1.0 DNA Analysis BeadChip for whole genome SNPs analysis and whole genome genotyping data was processed by linear regression analysis for PK parameters. We found 35 significant SNPs (P < 0.0001) in C(max), 1,118 significant SNPs (P < 0.0001) in T(max) and 1,259 significant SNPs (P < 0.0001) in AUC(inf) from whole genome analysis. For clinical pharmacological purpose, we selected SNPs from several phase I and II drug metabolizing enzyme and analyzed PK parameters with genotypes. Four SNPs (rs7761731 and rs3799872 from CYP39A1; rs156697 from GSTO2; rs1558139 from CYP4F2) showed significant associations with pioglitazone C(max). In the T(max) group, seven SNPs from 3 genes (rs3766198 from CYP4B1; rs2270422 from GSTZ1; rs2054675, rs10500282, rs3745274, rs8192719, and rs11673270 from CYP2B6) had significant associations. In the AUC(inf) group, seven SNPs from 4 genes (rs11572204 from CYP2J2; rs4148280 from UGT2A1, rs4646422 from CYP1A1; rs3745274, rs8192719, rs11673270, and rs707265 from CYP2B6) showed significant associations with pioglitazone absorption. These results showed that genetic makeup could affect the PK parameters and these informations could be provide information for personalized pioglitazone therapy.