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Multicenter Study
. 2014 Sep;96(3):370-9.
doi: 10.1038/clpt.2014.109. Epub 2014 May 22.

Genetic Variants in Transcription Factors Are Associated With the Pharmacokinetics and Pharmacodynamics of Metformin

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Free PMC article
Multicenter Study

Genetic Variants in Transcription Factors Are Associated With the Pharmacokinetics and Pharmacodynamics of Metformin

S Goswami et al. Clin Pharmacol Ther. .
Free PMC article

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Abstract

One-third of type 2 diabetes patients do not respond to metformin. Genetic variants in metformin transporters have been extensively studied as a likely contributor to this high failure rate. Here, we investigate, for the first time, the effect of genetic variants in transcription factors on metformin pharmacokinetics (PK) and response. Overall, 546 patients and healthy volunteers contributed their genome-wide, pharmacokinetic (235 subjects), and HbA1c data (440 patients) for this analysis. Five variants in specificity protein 1 (SP1), a transcription factor that modulates the expression of metformin transporters, were associated with changes in treatment HbA1c (P < 0.01) and metformin secretory clearance (P < 0.05). Population pharmacokinetic modeling further confirmed a 24% reduction in apparent clearance in homozygous carriers of one such variant, rs784888. Genetic variants in other transcription factors, peroxisome proliferator-activated receptor-α and hepatocyte nuclear factor 4-α, were significantly associated with HbA1c change only. Overall, our study highlights the importance of genetic variants in transcription factors as modulators of metformin PK and response.

Conflict of interest statement

CONFLICTOF INTEREST

The authors declared no conflict of interest.

Figures

Figure 1
Figure 1
Candidate transcription factors known to modulate gene expression levels of transporters involved in metformin disposition. (a) A cell diagram that depicts a putative network of transcription factors working in concert to modulate gene expression levels of metformin transporters. (b) A high-level gene diagram that highlights a mechanism by which a single-nucleotide polymorphism change in a transcription factor gene may modulate the pharmacological outcome of metformin. PK/PD, pharmacokinetics/pharmacodynamics.
Figure 2
Figure 2
Final metformin population pharmacokinetic model structure and visual predictive check. (a) A two-compartment model with delayed absorption best characterizes the data. All parameters are ratios over the bioavailability of metformin (F). The model structure includes the final model covariates determined by a stepwise covariate analysis (SCM). (b) Visual predictive check of the final population pharmacokinetic model. The shaded regions indicate the 95th and 5th percentiles (ends) and the range of median simulated profiles (center) of simulated predictions from the visual predictive check. Overlaid back points are combined healthy volunteer (n = 102) and type 2 diabetes patient (n = 133) data observations. The solid line indicates the median of the observed data, with red lines indicating the 95th and 5th percentiles of observations. CrCL, creatinine clearance; CL, apparent clearance of metformin; Ka, absorption rate constant; Ktr, transit rate constant, Vc, apparent central volume of distribution; Vp, apparent peripheral volume of distribution.
Figure 3
Figure 3
Predicted effects of demographic and genetic factors on metformin pharmacokinetic parameters. (a) Predicted effects of covariates on apparent clearance (CL/F) with the reference ethnicity identified as European Americans. (b) Predicted effect of covariates on intercompartmental clearance (Q/F). (c) Predicted effects of covariates on central compartment volume (Vc/F). (d, e, and f) Simulations of pharmacokinetic profiles after a single 850-mg dose of metformin with variability on clearance. Simulations are based on the predicted metformin clearance estimates. Predicted clearance estimates are based on the covariates described in Figure 3a. Ethnicity, creatinine clearance (CrCL), and SP1 variant status are shown in each panel. Dashed line at 1 mg/l indicates the lower target of metformin concentration based on therapeutic range. (d) Black solid line = typical value of clearance for a Caucasian with normal creatinine clearance (80–130ml/min) who is homozygous CC for SNP rs784888. Dashed black lines indicate the 97.5 and 2.5 percentiles of the interindividual variability (ETA) distribution for CL/F for this patient. (e) Black solid line = typical value of clearance for a Caucasian with low creatinine clearance (<70ml/min) who is homozygous GG for SNP rs784888. Dashed lines indicate the 97.5 and 2.5 percentiles of the interindividual variability (ETA) distribution for CL/F for this patient. (f) Black solid line = typical value of clearance for an African American with normal creatinine clearance (80–130ml/min) who is homozygous CC for SNP rs784888. Dashed lines indicate the 97.5 and 2.5 percentiles of the interindividual variability (ETA) distribution for CL/F or this patient. CrCL, creatinine clearance; SNP, single-nucleotide polymorphism.
Figure 4
Figure 4
Gene diagram summarizes the chromosome location of top associated single-nucleotide polymorphisms, highlighting both metformin pharmacodynamic and pharmacokinetic associated P values using multiple linear regression analysis, n = 440 patients for pharmacodynamics analysis, and n = 57 healthy subjects for the pharmacokinetic analysis. G, associated allele of rs784892; PD, pharmacodynamics, variant association with treatment HbA1c level, as defined in the text; PK, pharmacokinetics, variant association with measured metformin secretory clearance (ml/min).
Figure 5
Figure 5
A zoomed-in view of genetic polymorphisms in HNF4-α and PPAR-α associated with treatment-HbA1c levels. Circles represent the location and the–log10 P value of the association. Recombination rates are also overlaid on the figure, with each peak representing relatively high recombination rates for that region.

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