SGLT2 Inhibition and Uric Acid Excretion in Patients with Type 2 Diabetes and Normal Kidney Function.

BACKGROUND AND OBJECTIVES: Sodium-glucose transporter 2 (SGLT2) inhibitor-induced uric acid lowering may contribute to kidney-protective effects of the drug class in people with type 2 diabetes. This study investigates mechanisms of plasma uric acid lowering by SGLT2 inhibitors in people with type 2 diabetes with a focus on urate transporter 1. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We conducted an analysis of two randomized clinical trials. First, in the Renoprotective Effects of Dapagliflozin in Type 2 Diabetes study, 44 people with type 2 diabetes were randomized to dapagliflozin or gliclazide for 12 weeks. Plasma uric acid, fractional uric acid excretion, and hemodynamic kidney function were measured in the fasted state and during clamped euglycemia or hyperglycemia. Second, in the Uric Acid Excretion study, ten people with type 2 diabetes received 1 week of empagliflozin, urate transporter 1 blocker benzbromarone, or their combination in a crossover design, and effects on plasma uric acid, fractional uric acid excretion, and 24-hour uric acid excretion were measured. RESULTS: In the Renoprotective Effects of Dapagliflozin in Type 2 Diabetes study, compared with the fasted state (5.3±1.1 mg/dl), acute hyperinsulinemia and hyperglycemia significantly reduced plasma uric acid by 0.2±0.3 and 0.4±0.3 mg/dl (both P<0.001) while increasing fractional uric acid excretion (by 3.2%±3.1% and 8.9%±4.5%, respectively; both P<0.001). Dapagliflozin reduced plasma uric acid by 0.8±0.8 during fasting, 1.0±1.0 in hyperinsulinemic-euglycemic state, and 0.8±0.7 mg/dl during hyperglycemic conditions (P<0.001), respectively, whereas fractional uric acid excretion in 24-hour urine increased by 3.0%±2.1% (P<0.001) and 2.6%±4.5% during hyperinsulinemic-euglycemic conditions (P=0.003). Fractional uric acid excretion strongly correlated to fractional glucose excretion (r=0.35; P=0.02). In the Uric Acid Excretion study, empagliflozin and benzbromarone both significantly reduced plasma uric acid and increased fractional uric acid excretion. Effects of combination therapy did not differ from benzbromarone monotherapy. CONCLUSIONS: In conclusion, SGLT2 inhibitors induce uric acid excretion, which is strongly linked to urinary glucose excretion and is attenuated during concomitant pharmacologic blockade of urate transporter 1. CLINICAL TRIAL REGISTRY NAME AND REGISTRATION NUMBER: Renoprotective Effects of Dapagliflozin in Type 2 Diabetes (RED), NCT02682563; SGLT2 Inhibition: Uric Acid Excretion Study (UREX), NCT05210517.

A neural mass model to predict electrical stimulation evoked responses in human and non-human primate brain.

OBJECTIVE: Deep brain stimulation (DBS) is a valuable tool for ameliorating drug resistant pathologies such as movement disorders and epilepsy. DBS is also being considered for complex neuro-psychiatric disorders, which are characterized by high variability in symptoms and slow responses that hinder DBS setting optimization. The objective of this work was to develop an in silico platform to examine the effects of electrical stimulation in regions neighboring a stimulated brain region. APPROACH: We used the Jansen-Rit neural mass model of single and coupled nodes to simulate the response to a train of electrical current pulses at different frequencies (10-160 Hz) of the local field potential recorded in the amygdala and cortical structures in human subjects and a non-human primate. RESULTS: We found that using a single node model, the evoked responses could be accurately modeled following a narrow range of stimulation frequencies. Including a second coupled node increased the range of stimulation frequencies whose evoked responses could be efficiently modeled. Furthermore, in a chronic recording from a non-human primate, features of the in vivo evoked response remained consistent for several weeks, suggesting that model re-parameterization for chronic stimulation protocols would be infrequent. SIGNIFICANCE: Using a model of neural population activity, we reproduced the evoked response to cortical and subcortical stimulation in human and non-human primate. This modeling framework provides an environment to explore, safely and rapidly, a wide range of stimulation settings not possible in human brain stimulation studies. The model can be trained on a limited dataset of stimulation responses to develop an optimal stimulation strategy for an individual patient.