Postprandial and fasting hepatic glucose fluxes in long-standing type 1 diabetes

Abstract

Objective: Intravenous insulin infusion partly improves liver glucose fluxes in type 1 diabetes (T1D). This study tests the hypothesis that continuous subcutaneous insulin infusion (CSII) normalizes hepatic glycogen metabolism.

Research design and methods: T1D with poor glycemic control (T1Dp; HbA(1c): 8.5 ± 0.4%), T1D with improved glycemic control on CSII (T1Di; 7.0 ± 0.3%), and healthy humans (control subjects [CON]; 5.2 ± 0.4%) were studied. Net hepatic glycogen synthesis and glycogenolysis were measured with in vivo (13)C magnetic resonance spectroscopy. Endogenous glucose production (EGP) and gluconeogenesis (GNG) were assessed with [6,6-(2)H(2)]glucose, glycogen phosphorylase (GP) flux, and gluconeogenic fluxes with (2)H(2)O/paracetamol.

Results: When compared with CON, net glycogen synthesis was 70% lower in T1Dp (P = 0.038) but not different in T1Di. During fasting, T1Dp had 25 and 42% higher EGP than T1Di (P = 0.004) and CON (P < 0.001; T1Di vs. CON: P = NS). GNG was 74 and 67% higher in T1Dp than in T1Di (P = 0.002) and CON (P = 0.001). In T1Dp, GP flux (7.0 ± 1.6 μmol ⋅ kg(-1) ⋅ min(-1)) was twofold higher than net glycogenolysis, but comparable in T1Di and CON (3.7 ± 0.8 and 4.9 ± 1.0 μmol ⋅ kg(-1) ⋅ min(-1)). Thus T1Dp exhibited glycogen cycling (3.5 ± 2.0 μmol ⋅ kg(-1) ⋅ min(-1)), which accounted for 47% of GP flux.

Conclusions: Poorly controlled T1D not only exhibits augmented fasting gluconeogenesis but also increased glycogen cycling. Intensified subcutaneous insulin treatment restores these abnormalities, indicating that hepatic glucose metabolism is not irreversibly altered even in long-standing T1D.

FIG. 1.

Metabolic model representing fluxes between G6P, glycogen, glucose, and the parameters of glycogenolytic flux derived by ²H₂O and ¹³C MR methods. Component fluxes include GS flux, GP, GNG, and EGP. The in vivo ¹³C MRS assay measures the net loss of hexose from the pool of glycogen metabolites (i.e., net glycogenolysis), and GNG is calculated as EGP − net glycogenolysis. Net glycogenolysis represents the difference between GP and GS, hence the fraction of EGP derived from net glycogenolytic flux is equal to (GP − GS)/EGP. The ²H₂O method measures the fractional contribution of GP to EGP flux. When GS is zero, net glycogenolysis and GP are equal. During glycogen cycling, where GS is active, GP is higher than net glycogenolysis.

FIG. 2.

²H NMR spectra of urinary glucuronides following derivatization to MAG from a healthy control subject, a diabetic patient with poor glycemic control (T1Dp), and a diabetic patient with good glycemic control (T1Di). The number above each signal represents its positional origin in the MAG molecule. The ratio of signal 5 and signal 2 areas (H5-to-H2) is also shown.

FIG. 3.

Plasma concentrations of glucose (A), FFA (B), insulin (C), and glucagon (D) in CON (▲), T1Dp (●), and T1Di (○). Mean plasma glucose from 6:30 p.m. until 5:30 a.m. is shown. *T1Dp vs. CON P < 0.001; **T1Dp vs. T1Di P = 0.017; †CON vs. T1Di P < 0.001; plasma insulin concentration at 1:30 a.m. ‡CON vs. T1Di P = 0.036. Data are presented as means ± SEM.

FIG. 4.

GNG, GP, glycogen cycling, and GLYnet in healthy CON (white bars), T1Di (hatched bars), and T1Dp (black bars). *CON vs. T1Dp P = 0.001; **T1Di vs. T1Dp P = 0.002; †T1Di vs. T1Dp P = 0.021; ‡T1Di vs. T1Dp P = 0.02. Data are presented as means ± SEM.

FIG. 5.

Relationship between EGP and glycogen cycling (A) and HbA_1c (B) across all groups: patients with poorly controlled type 1 diabetes (●), improved glycemic control (○), and nondiabetic CON (▲).