Use of systems pharmacology modeling to elucidate the operating characteristics of SGLT1 and SGLT2 in renal glucose reabsorption in humans

Abstract

In the kidney, glucose in glomerular filtrate is reabsorbed primarily by sodium-glucose cotransporters 1 (SGLT1) and 2 (SGLT2) along the proximal tubules. SGLT2 has been characterized as a high capacity, low affinity pathway responsible for reabsorption of the majority of filtered glucose in the early part of proximal tubules, and SGLT1 reabsorbs the residual glucose in the distal part. Inhibition of SGLT2 is a viable mechanism for removing glucose from the body and improving glycemic control in patients with diabetes. Despite demonstrating high levels (in excess of 80%) of inhibition of glucose transport by SGLT2 in vitro, potent SGLT2 inhibitors, e.g., dapagliflozin and canagliflozin, inhibit renal glucose reabsorption by only 30-50% in clinical studies. Hypotheses for this apparent paradox are mostly focused on the compensatory effect of SGLT1. The paradox has been explained and the role of SGLT1 demonstrated in the mouse, but direct data in humans are lacking. To further explore the roles of SGLT1/2 in renal glucose reabsorption in humans, we developed a systems pharmacology model with emphasis on SGLT1/2 mediated glucose reabsorption and the effects of SGLT2 inhibition. The model was calibrated using robust clinical data in the absence or presence of dapagliflozin (DeFronzo et al., 2013), and evaluated against clinical data from the literature (Mogensen, 1971; Wolf et al., 2009; Polidori et al., 2013). The model adequately described all four data sets. Simulations using the model clarified the operating characteristics of SGLT1/2 in humans in the healthy and diabetic state with or without SGLT2 inhibition. The modeling and simulations support our proposition that the apparent moderate, 30-50% inhibition of renal glucose reabsorption observed with potent SGLT2 inhibitors is a combined result of two physiological determinants: SGLT1 compensation and residual SGLT2 activity. This model will enable in silico inferences and predictions related to SGLT1/2 modulation.

Keywords: SGLT; dapagliflozin; diabetes mellitus; glucosuria; renal glucose reabsorption; systems pharmacology model.

Figure 1

Structure of the systems pharmacology model for describing renal glucose reabsorption and the inhibitory effect of an SGLTs inhibitor. PCT1-6: sub-segments 1–6 of proximal convoluted tubules; PST1-3: sub-segments 1–3 of proximal straight tubules; UB, urinary bladder.

Figure 2

Model description of cumulative (A,B) and step-wise (C,D) urinary glucose excretion (UGE) in the healthy (A,C) and T2DM (B,D) subjects at baseline and after 7 daily doses of 10 mg dapagliflozin in the DeFronzo et al. study (2013), where an stepwise hyperglycemic clamp procedure was employed. The symbols represent observations and the curves are model predictions. Pglu, plasma glucose concentration.

Figure 3

Evaluation of model predictivity against three separate clinical data sets. (A) Polidori et al. (2013) urinary glucose excretion (UGE) data in T2DM subjects at baseline and after 8 daily doses of 100 mg canagliflozin. The symbols represent the observed data and the curves are model predictions. (B) Wolf et al. (2009) renal glucose reabsorption rate in T2DM patients who were subjected to a stepwise hyperglycemic clamp procedure. (C) Mogensen (1971) renal glucose reabsorption rate in healthy and diabetic subjects with plasma glucose levels elevated to over 650 mg/dL.

Figure 4

Model calculated step-wise amount of glucose reabsorbed (A,B) and relative contributions to the reabsorption (C–F) by renal SGLT1 and SGLT2 at baseline and after dapagliflozin treatment in healthy subjects and patients with diabetes under the SHC procedure in DeFronzo et al. (2013). (A,C) healthy, baseline; (B,D) healthy, after treatment; (E) patient, baseline; and (F) patient, after treatment. Cp,dapa, total plasma concentration of dapagliflozin.

Figure 5

Model derived operation efficiency (defined as glucose reabsorption rate/V_max × 100% for either SGLT1 or SGLT2) for both SGLTs at baseline and after dapagliflozin treatment in the healthy subjects (A) and patients with diabetes (B) under the stepwise hyperglycemic clamp procedure in DeFronzo et al. (2013).

Figure 6

Simulation of the relationships between loss of function (i.e., reduction in V_max) and renal glucose reabsorption (% filtered) as well as urinary glucose excretion (UGE) for SGLT2 (A) and SGLT1 (B) in an otherwise healthy subject with normoglycemia.

Figure 7

Sensitivity of urinary glucose excretion (UGE) to SGLT1 capacity (V_max1) (A) and inhibitor affinity to SGLT1 (K_i1) (B) in a T2DM patient subjected to the same study procedure as in DeFronzo et al. (2013) with target plasma glucose from 100 to 350 mg/dL with increments of 50 mg/dL. For the analysis on V_max1, all other parameters were held constant and V_max1 was varied to 10, 14, 17, or 20 mmole/h (corresponding to a 50, 30, 15%, or 0% reduction of SGLT1 capacity). For the analysis on K_i1, the K_i1 value of an SGLT2 inhibitor which was otherwise identical to dapagliflozin was varied from 6 to 10,000 nM, representing a selectivity for SGLT2 from 20× to 33,333×.