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Am J Physiol Endocrinol Metab 284: E695-E707, 2003. First published December 27, 2002; doi:10.1152/ajpendo.00308.2002
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Vol. 284, Issue 4, E695-E707, April 2003

Interaction of glucagon and epinephrine in the control of hepatic glucose production in the conscious dog

Stephanie M. Gustavson, Chang An Chu, Makoto Nishizawa, Ben Farmer, Doss Neal, Ying Yang, E. Patrick Donahue, Paul Flakoll, and Alan D. Cherrington

Department of Molecular Physiology and Biophysics and Diabetes Research and Training Center, Vanderbilt University, Nashville, Tennessee 37232


    ABSTRACT
TOP
ABSTRACT
INTRODUCTION
RESEARCH DESIGN AND METHODS
RESULTS
DISCUSSION
REFERENCES

Epinephrine increases net hepatic glucose output (NHGO) mainly via increased gluconeogenesis, whereas glucagon increases NHGO mainly via increased glycogenolysis. The aim of the present study was to determine how the two hormones interact in controlling glucose production. In 18-h-fasted conscious dogs, a pancreatic clamp initially fixed insulin and glucagon at basal levels, following which one of four protocols was instituted. In G + E, glucagon (1.5 ng · kg-1 · min-1; portally) and epinephrine (50 ng · kg-1 · min-1; peripherally) were increased; in G, glucagon was increased alone; in E, epinephrine was increased alone; and in C, neither was increased. In G, E, and C, glucose was infused to match the hyperglycemia seen in G + E (~250 mg/dl). The areas under the curve for the increase in NHGO, after the change in C was subtracted, were as follows: G = 661 ± 185, E = 424 ± 158, G + E = 1,178 ± 57 mg/kg. Therefore, the overall effects of the two hormones on NHGO were additive. Additionally, glucagon exerted its full glycogenolytic effect, whereas epinephrine exerted its full gluconeogenic effect, such that both processes increased significantly during concurrent hormone administration.

canine; gluconeogenesis; glycogenolysis; counterregulatory hormones


    INTRODUCTION
TOP
ABSTRACT
INTRODUCTION
RESEARCH DESIGN AND METHODS
RESULTS
DISCUSSION
REFERENCES

GLUCAGON AND EPINEPHRINE, the two primary counterregulatory hormones, are secreted in response to physiological stresses such as hypoglycemia, exercise, and infection. The individual actions of these two hormones on glucose production have been well defined, yet it remains unclear how they interact acutely in a physiological setting to stimulate glucose production. Glucagon has been shown to have rapid effects on hepatic glucose production, with half-maximal activation occurring in ~4.5 min (19). In conscious dogs, administration of glucagon at a fourfold basal rate in the presence of a pancreatic clamp and fixed basal insulin resulted in a rapid increase (180%) in glucose production that waned with time, such that after 3 h it was increased by only 41% (7). This effect of glucagon on glucose production has been shown to result primarily from a rapid, potent, time-dependent effect on glycogenolysis and to a lesser extent from a less potent, slower effect on gluconeogenesis (7). Studies in humans have also shown that glucagon can increase glucose production in a rapid, time-dependent manner primarily by increasing glycogenolysis (8, 41).

The mild effect of glucagon on gluconeogenesis is somewhat surprising when it is considered that the hormone is known to stimulate both transcription and activation of hepatic gluconeogenic enzymes (22, 39, 49, 50). In fact, glucagon has been shown to increase hepatic gluconeogenic efficiency in vivo both acutely (67) and chronically (43), yet the contribution of the rise in gluconeogenesis to the increase in glucose production was small. This paradox may be explained by the fact that glucagon has little effect on gluconeogenic substrate mobilization from muscle or fat. Thus any enhancement of gluconeogenic flux would initially increase gluconeogenesis, but then the gluconeogenic substrate levels in blood would fall and the gluconeogenic contribution to glucose production would return toward its basal rate.

Epinephrine has also been shown to increase glucose production in a rapid, time-dependent manner, albeit with a decreased sensitivity on a molar basis compared with glucagon (6, 56, 59, 66). The effect of epinephrine on glucose production results from a stimulation of both gluconeogenesis and glycogenolysis. Chu and colleagues (10-12) showed that the former is due to the indirect action of the hormone on peripheral substrate release, whereas the latter is due to the direct action of epinephrine on the liver. Chu et al. (10) also showed that when the hormone increased gluconeogenesis, it caused a compensatory decrease in its glycogenolytic action, implying a reciprocal relationship between the two processes. Support for a reciprocal relationship between gluconeogenesis and glycogenolysis can be found in several other previous studies in both humans (33, 34, 74) and dogs (15, 18). In those experiments, increasing the gluconeogenic precursor supply to the liver increased gluconeogenesis but did not increase total glucose production, thereby implying a decrease in glycogenolysis. On the other hand, inhibiting glycogen breakdown has not been uniformly shown to stimulate gluconeogenesis (23, 64), perhaps because gluconeogenic precursor supply was limiting.

The interaction of glucagon and epinephrine in regulating hepatic glucose production has not been extensively characterized. Two previous studies found that administration of glucagon and epinephrine concurrently resulted in an additive increase in glucose production in the dog (21) and human (62). However, insulin and glucose levels were not controlled in those studies, making interpretation of the data difficult. In addition, glucose production was not separated into its gluconeogenic and glycogenolytic components. Thus the aim of the present study was to analyze the interaction of glucagon and epinephrine in controlling hepatic glucose production at a time when plasma insulin was basal and fixed. Specifically, we wanted to determine whether glucagon, when elevated in the presence of an epinephrine-induced increase in gluconeogenic precursor supply to the liver, would have an increased effect on gluconeogenesis and as a result a decreased effect on glycogenolysis.


    RESEARCH DESIGN AND METHODS
TOP
ABSTRACT
INTRODUCTION
RESEARCH DESIGN AND METHODS
RESULTS
DISCUSSION
REFERENCES

Animals and surgical procedures. Studies were performed on 23 overnight-fasted, conscious mongrel dogs of either sex (19-26.9 kg, mean = 23.2 kg). Animals were fed once daily a diet of meat (Kal-Kan, Vernon, CA) and chow (Purina Lab Canine Diet no. 5006; Purina Mills, St. Louis, MO) comprised of 46% carbohydrate, 34% protein, 14% fat, and 6% fiber based on dry weight. The animals were housed in a facility that met American Association for the Accreditation of Laboratory Animal Care guidelines, and the protocols were approved by the Vanderbilt University Medical Center Animal Care Committee.

Approximately 16 days before the study, a laparotomy was performed under general anesthesia (15 mg/kg body wt sodium pentothal before surgery; 1.0% isoflurane as an inhalation anesthetic during surgery). In all dogs, ultrasonic flow probes (Transonic Systems, Ithaca, NY) were positioned around the portal vein and a hepatic artery, as previously described (10). Silastic catheters (Dow Corning, Midline, MI) were inserted into a femoral artery, the portal vein, and the left common hepatic vein for blood sampling and into the splenic and jejunal veins for intraportal hormone delivery, as previously described (47). The catheters were filled with heparinized saline (200 U/ml; Abbott Laboratories, North Chicago, IL), and their free ends were knotted. The free ends of the catheters and the flow probe leads were placed in subcutaneous pockets until the study day. Animals were studied only if the following criteria were met before the study: 1) leukocyte count <18,000/mm3, 2) hematocrit >35%, 3) good appetite, and 4) normal stools. As a side note, in all dogs an ultrasonic flow probe was positioned around a renal artery, and a Silastic catheter was inserted into a renal vein. The renal glucose production data form the basis of a separate study.

On the morning of a study, the Transonic leads and the catheters were exteriorized under local anesthesia (2% lidocaine; Abbott Laboratories). The dog was placed in a Pavlov harness, and the contents of the catheters were aspirated, after which the catheters were flushed with saline and subsequently used for blood sampling or infusion. Angiocaths (20 gauge; Becton Dickinson, Sandy, UT) were inserted into the right and left cephalic veins for infusion of [3-3H]glucose (New England Nuclear, Boston, MA) and glucose (20% dextrose, Baxter Healthcare, Deerfield, IL; or 50% dextrose, Abbott Laboratories) respectively. An angiocath was also placed in the left saphenous vein for indocyanine green dye (ICG; Sigma Chemical, St. Louis, MO) and somatostatin (Bachem, Torrance, CA) infusion. If required according to the protocol, an angiocath was placed in the right saphenous vein for peripheral epinephrine (Sigma Chemical) infusion.

Experimental design. Each experiment consisted of a 100-min tracer equilibration and hormone adjustment period (-140 to -40 min) followed by a 40-min control period (-40 to 0 min). During these periods, [3-3H]glucose (~50 µCi prime; ~0.50 µCi/min) and ICG (0.07 mg/min) were infused. In addition, a pancreatic clamp was performed. This involved infusion of somatostatin (0.8 µg · kg-1 · min-1) through a peripheral vein to inhibit endogenous insulin and glucagon secretion and replacement of insulin (~250 µU · kg-1 · min-1; Eli Lilly, Indianapolis, IN) and glucagon (0.5 ng · kg-1 · min-1; Bedford Laboratories, Bedford, OH) intraportally. The insulin infusion rate was varied if necessary during the equilibration period to maintain euglycemia. The control period was followed by a 4-h experimental period (0-240 min) during which basal insulin was maintained. Each dog underwent one of four experimental protocols. In the G + E group (n = 6), glucagon (1.5 ng · kg-1 · min-1; portally) and epinephrine (50 ng · kg-1 · min-1; peripherally) were elevated; in the G group (n = 6), glucagon (1.5 ng · kg-1 · min-1; portally) alone was increased; in the E group (n = 6), epinephrine (50 ng · kg-1 · min-1; peripherally) alone was raised; and in the C group (n = 5), basal glucagon and epinephrine (no epinephrine infusion) were maintained. In the G, E, and C protocols, glucose was infused peripherally to match the plasma glucose seen in G + E (~250 mg/dl). The [3-3H]glucose infusion rate was also varied throughout the experimental period to clamp the glucose specific activity and thereby minimize errors in glucose turnover calculation. In addition, to prevent a slow decline in glucagon levels, the glucagon infusion rate was increased slightly each hour. In dogs receiving basal glucagon, glucagon infusion was increased from 0.50 to 0.54, 0.58, and 0.62 ng · kg-1 · min-1 at times 60, 120, and 180 min, respectively. In dogs receiving threefold basal glucagon, glucagon infusion was increased from 1.5 to 1.62, 1.74, and 1.86 at times 60, 120, and 180 min, respectively. In all dogs, mean arterial blood pressure and heart rate were determined throughout the experiment at each sampling time point by use of either a chart recorder with blood pressure transducer (Gould RS3200) or a Digi-Med Blood Pressure Analyzer (Micro-Med, Louisville, KY).

Analytical procedures. The immediate processing of the samples and the measurement of whole blood glucose, glutamine, glutamate, acetoacetate, individual amino acids (serine, threonine, glycine), and metabolites [lactate, alanine, glycerol, beta -hydroxybutyrate (BOHB)] were described previously (10, 63). In addition, plasma levels of glucose, [3-3H]glucose, ICG, catecholamines, insulin, glucagon, cortisol, and nonesterified fatty acids (NEFA) were measured as previously described (10, 63). C-peptide [in plasma to which 500 kallikrein inhibitor units/ml Trasylol had been added (FBA Pharmaceuticals, New York NY)] was determined via disequilibrium double-antibody radioimmunoassay (Linco Research, St. Charles, MO) with an interassay coefficient of variation of 5%.

Calculations. Both ICG and Transonic flow probes were used to estimate total hepatic blood flow in these studies. The net hepatic balances and net hepatic fractional extractions of the measured substrates were calculated using both Transonic-determined and ICG-determined flow. The data shown are those calculated using Transonic-determined flow, as this flow does not require an assumption about the distribution of arterial vs. portal flow. Note that the same conclusions were drawn when ICG-determined flow was used to calculate the data. Equations used were as follows
net hepatic balance = H · HF − [(A · AF) + (P · PF)]

net hepatic fractional extraction =

<FR><NU>H · HF − [(A · AF) + (P · PF)]</NU><DE>[(A · AF) + (P · PF)]</DE></FR>

hepatic sinusoidal level = A · (AF/HF) + P · (PF/HF)
where A, P, and H are arterial, portal vein, and hepatic vein concentrations (blood or plasma); AF and PF are the arterial and portal vein flow (blood or plasma) measured by the Transonic flow probes; and HF (total liver flow; blood or plasma) = AF + PF. Positive numbers for net hepatic balance indicate net production, and negative numbers indicate net uptake. In some cases, uptake is presented rather than balance, and when such is the case positive values are used. Note that, because the liver is supplied by blood from both the hepatic artery and the portal vein, neither represents the true inflowing hepatic blood supply. For this reason, we calculated hepatic sinusoidal hormone levels, which provide an estimate of the average inflowing hormone concentration at the confluence of the two inputs, with the assumption that it occurs early in the sinusoid.

Tracer-determined total glucose production (Ra) and utilization (Rd) were calculated according to the isotope dilution method outlined by Wall et al. (72), as simplified by DeBodo et al. (17), and using the two-compartment model described by Mari (42) and canine parameters established by Dobbins et al. (20). Endogenous Ra was then calculated by subtracting the glucose infusion rate from the total glucose production rate. Note that endogenous glucose production represents both hepatic and renal glucose production and thus slightly overestimates hepatic glucose production.

Gluconeogenesis, as classically defined, is the synthesis and subsequent release of glucose from noncarbohydrate precursors. Carbon produced from flux through the gluconeogenic pathway does not necessarily have to be released as glucose; it can also be stored as glycogen, oxidized, or released as lactate. Therefore, there is a distinction between gluconeogenic flux to glucose 6-phosphate (G-6-P) (conversion of precursors to G-6-P, also called G-6-P-neogenesis) and gluconeogenesis (release of glucose derived from gluconeogenic flux). In the present studies, we estimated hepatic gluconeogenic (GNG) flux to G-6-P, net hepatic GNG flux, and net hepatic glycogenolytic (GLY) flux.

Hepatic GNG flux to G-6-P was obtained by summing net hepatic uptake rates of the gluconeogenic precursors (alanine, serine, glycine, threonine, glutamine, glutamate, glycerol, lactate, pyruvate) and then dividing by two to transform the data into glucose equivalents (by accounting for incorporation of three-carbon precursor molecules into six-carbon glucose molecules). Net hepatic pyruvate uptake was assumed to be 10% of net hepatic lactate uptake (71). When net hepatic output of any precursor occurred, rather than uptake, the precursor was considered to be a product of the liver, and thus net uptake was set to zero. However, note that the net hepatic balance data of the precursors represent the entire database, regardless of net output or net uptake.

Net hepatic GNG flux was determined by subtracting the summed net hepatic output rates (when such occurred) of the substrates noted above (in glucose equivalents) and glucose oxidation from the GNG flux to G-6-P. A positive number represents net gluconeogenic flux to G-6-P, whereas a negative number indicates net glycolytic flux from G-6-P. Glucose oxidation was assumed to be 0.3 mg · kg-1 · min-1 throughout each experiment, similar to the basal period of earlier studies in 18-h-fasted (28) and 24-h-fasted (0.3 ± 0.1 mg · kg-1 · min-1; Moore MC, Pagliassotti MJ, Swift LL, Asher J, Murrell J, Neal D, and Cherrington AD, unpublished observations) conscious dogs. Although use of this value may slightly overestimate or underestimate the true glucose oxidation rate, it is unlikely to differ by >0.1 mg · kg-1 · min-1 from the actual oxidation rate. Our earlier studies (60) showed that hyperglycemia (in the presence of euinsulinemia) did not appreciably change the hepatic glucose oxidation rate (0.4 ± 0.2 mg ·kg-1 · min-1). It also seems unlikely that glucagon and epinephrine would change hepatic glucose oxidation significantly. Although both have been shown to inhibit pyruvate dehydrogenase, and thus pyruvate oxidation (24, 54, 55), the basal oxidation rate is so low that any effect would have been difficult, if not impossible, to detect.

Net hepatic GLY flux was determined by subtracting net hepatic GNG flux from net hepatic glucose balance (NHGB). A positive number therefore represents net glycogen breakdown, whereas a negative number indicates net glycogen synthesis.

Ideally, GNG flux to G-6-P would be calculated using unidirectional hepatic uptake rates for each substrate, but this would be difficult, as it would require the simultaneous use of multiple stable isotopes that could themselves induce a mild perturbation of the metabolic state. Therefore, net hepatic balance was used instead, necessitating consideration of the limits of this approach. There is little or no net production of gluconeogenic amino acids or glycerol by the liver, so in their case the compromise is of little consequence (26, 46). However, such is not the case for lactate. Our estimate of the rate of GNG flux to G-6-P will be quantitatively accurate only if we assume that lactate flux is unidirectional at a given moment (i.e., either into or out of the liver). In a given cell, this does not seem like an unreasonable assumption in light of the reciprocal control of gluconeogenesis or glycogenolysis (50). Jungermann and Katz (35) and Radziuk and Pye (53) have suggested, however, that there is spatial separation of metabolic pathways. Specifically, gluconeogenic periportal hepatocytes primarily consume lactate and other noncarbohydrate precursors for the synthesis of glucose and glycogen, whereas glycolytic perivenous hepatocytes predominantly consume plasma glucose, which can then be incorporated into glycogen, oxidized, or released as lactate or other glycolytic substrates (35, 53). Therefore, it is possible that, under normal nutritional conditions, hepatic GNG and GLY flux occur in a net sense simultaneously with lactate output or uptake occurring in different cells. To the extent that flux occurs in both directions simultaneously, use of net hepatic balance will cause an underestimation of GNG flux to G-6-P. Note that net hepatic GNG flux and net hepatic GLY flux can be calculated accurately without concern for the assumptions related to whether or not simultaneous GNG and GLY substrate flux occur.

The approach we used to estimate GNG flux to G-6-P is based on several assumptions. First, it is assumed that there is minimal net contribution of gluconeogenic precursors from intrahepatic proteolysis and lipolysis. To the extent that there is a small contribution of intrahepatic gluconeogenic precursors, we would tend to underestimate GNG flux (and overestimate GLY flux). However, we have found that, in the normal dog, there are negligible hepatic triglyceride stores after an overnight fast (Moore MC, Pagliassotti MJ, Swift LL, Asher J, Murrell J, Neal D, and Cherrington AD, unpublished observations). This observation of low hepatic triglyceride stores in the dog was supported by another group (70). Furthermore, we recently estimated that intrahepatic proteolysis after an overnight fast in the dog was only 0.2 mg · kg-1 · min-1, thus contributing minimally to gluconeogenic flux (26). We also showed that, in the 36-h-fasted dog, alanine specific activity exiting the liver was identical to that entering the liver under basal hormonal conditions, suggesting that there was minimal intrahepatic proteolysis (65). Although glucagon, cAMP, and epinephrine have been shown to stimulate hepatic proteolysis in vitro, pharmacological levels were required for a modest effect (45, 46, 48, 57, 61, 75), whereas physiological levels similar to those in the present study stimulated proteolysis only minimally (<0.5%) (30) or not at all (48). A second assumption of the method is that all of the gluconeogenic carbon taken up in a net sense is converted to G-6-P. We verified this assumption in a recent study which showed that GNG flux measured directly was actually larger than the estimate obtained using the current method, presumably due to the addition of intrahepatic amino acid precursors (26). A third assumption is that transient variations in the intrahepatic pool of gluconeogenic substrates have minimal impact on our estimates of GNG flux.

The area under the curve (AUC) for hepatic GNG flux to G-6-P, net hepatic GNG flux, and net hepatic GLY flux in each group was calculated for the entire experimental period (4 h) by use of the trapezoidal rule. The AUC was calculated using change from basal data points, thus accounting for any baseline differences among groups. The mean AUC of the control group was then subtracted from that of each individual dog in every group. The mean ± SE for the Delta AUC for each of the three experimental groups was then reported.

Statistical analysis. Data are expressed as means ± SE. Statistical comparisons were made by one- and two-way analysis of variance (ANOVA) with repeated-measures design (except for the blood pressure and heart rate data: paired t-test) run on Sigma Stat (SPSS Science, Chicago, IL). Analysis of AUC data was made with one-way ANOVA. Post hoc analysis was performed with Tukey's test. Statistical significance was accepted at P < 0.05.


    RESULTS
TOP
ABSTRACT
INTRODUCTION
RESEARCH DESIGN AND METHODS
RESULTS
DISCUSSION
REFERENCES

Glucose and hormone levels. In all four groups, plasma glucose levels rose from ~110 to ~250 mg/dl (Table 1). To achieve similar glucose levels in all groups, different glucose infusion rates (GIR) were required, as depicted in Table 1. The plasma insulin levels remained essentially unchanged and basal and were not significantly different from group to group (Table 1). Arterial plasma C-peptide levels, measured as an index of endogenous insulin secretion, were low and did not change in any group (data not shown), thereby confirming continued inhibition of insulin release even in the presence of hyperglycemia. Arterial and hepatic sinusoidal plasma glucagon levels rose similarly in the protocols in which the glucagon infusion was increased (G and G + E) but remained basal in the other protocols (Table 1 and Fig. 1). Arterial and hepatic sinusoidal plasma epinephrine levels rose similarly in the protocols in which epinephrine was infused (E and G + E), but remained basal when the catecholamine was not infused (Table 1 and Fig. 1). Arterial cortisol levels as well as arterial and portal norepinephrine levels remained basal in all groups throughout the studies (data not shown).

                              
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  		Table 1.   Arterial plasma glucose, GIR, arterial plasma insulin, hepatic sinusoidal plasma insulin, and arterial plasma glucagon and epinephrine



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  		Fig. 1.   Hepatic sinusoidal plasma glucagon (A) and epinephrine levels (B) in control (-40 to 0 min) and experimental (0-240 min) periods in the hyperglycemic control (C), glucagon-alone (G), epinephrine-alone (E), and the 2 hormones combined (G + E) 18-h-fasted conscious dogs. Data are expressed as means ± SE. Statistical comparisons were made by 2-way ANOVA with repeated measures; n = 5 for C, n = 6 each for G, E, and G + E. For sinusoidal glucagon, P < 0.05 for C vs. G and G + E and for E vs. G and G + E. G and G + E changed significantly from basal (P < 0.05), whereas C and E did not. For sinusoidal epinephrine, P < 0.05 for C vs. E and G + E and for G vs. E and G + E. E and G + E changed significantly from basal (P < 0.05), whereas C and G did not.

Arterial blood pressure and heart rate. Mean arterial blood pressure (mmHg) was initially similar in all groups (basal period: C = 106 ± 5, G = 121 ± 11, E = 112 ± 9, G + E = 129 ± 9) and remained stable in all but the E group, in which it fell modestly (average of experimental period: C = 106 ± 5, G = 121 ± 8, E = 96 ± 11, G + E = 130 ± 11, P < 0.05 for the change in E; paired t-test). As expected, heart rate rose modestly in both E and G + E (P < 0.05; paired t-test) as a result of epinephrine administration (C = 96 ± 12 to 94 ± 6, G = 92 ± 17 to 82 ± 11, E = 104 ± 13 to 134 ± 8, G + E = 70 ± 9 to 95 ± 9).

Glucose metabolism. In all groups, basal NHGB (mg · kg-1 · min-1) was similar (C = 1.2 ± 0.2, G = 1.7 ± 0.3, E = 1.8 ± 0.3, G + E = 1.4 ± 0.2; Fig. 2). In response to hyperglycemia (C), NHGB changed from output to uptake (-2.5 ± 0.3 at 240 min). In response to glucagon (G), NHGB rose to 4.6 ± 0.8 at 15 min and waned with time (0.5 ± 0.8 at 240 min). The effect of glucagon per se is represented in the inset to Fig. 2 as the difference between the changes in G and C. In response to epinephrine (E), NHGB rose (3.3 ± 0.9 at 15 min) but also waned with time, falling to a rate significantly lower than basal (0.0 ± 1.0 at 240 min). The effect of epinephrine per se is represented in the inset of Fig. 2 as the difference between the changes in E and C. Finally, in the presence of both hormones (G + E), NHGB rose to 7.3 ± 1.0 at 15 min, which was greater than with either individual hormone. Once again, the response waned with time (2.0 ± 0.5 at 240 min). The data in the inset of Fig. 2 indicate that the effects of glucagon and epinephrine on net hepatic glucose production (Delta AUC) were additive. Changes in tracer-determined endogenous glucose Ra paralleled the changes in NHGB (Table 2).


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  		Fig. 2.   Net hepatic glucose balance in control (-40 to 0 min) and experimental (0-240 min) periods in C, G, E, and G + E 18-h-fasted conscious dogs. Data are expressed as means ± SE. Statistical comparisons were made by 1- and 2-way ANOVA with repeated measures; n = 5 for C, n = 6 each for G, E, and G + E. P < 0.05 for C vs. G, E and G + E, G vs. C and G + E, and E vs. C and G + E. All groups changed from basal (P < 0.05; C and E fell significantly by the end of the study, and G and G + E rose significantly and then returned to basal levels). Inset: area under the curves (AUC) of net hepatic glucose balance (change from basal after subtracting change from basal of C, over 4 h). P < 0.05 for G + E vs. G and E.


                              
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  		Table 2.   Tracer-determined whole body glucose Ra and Rd

Tracer-determined, whole body glucose Rd (mg · kg-1 · min-1; Table 2) increased markedly in C (2.3 ± 0.2 to 6.0 ± 0.5 at 240 min). In G and E, glucose Rd rose less than in the control group (2.7 ± 0.2 to 4.2 ± 1.0 with G and 2.9 ± 0.2 to 4.0 ± 0.9 with E at 240 min). Finally, when both hormones were given together, glucose Rd did not rise significantly (2.8 ± 0.4 to 3.4 ± 0.8 at 240 min).

Lactate: arterial levels and net hepatic balance. In the control group, arterial blood lactate levels rose modestly due to an increase in net hepatic lactate output during hyperglycemia (Fig. 3). When glucagon was increased, the arterial blood lactate level rose as in the control group, also due to an increase in net hepatic lactate production. However, with glucagon, the rise in net hepatic lactate output and the lactate level occurred more quickly, presumably resulting from the hormone's effect on glycogenolysis. When epinephrine was increased, arterial lactate levels rose to a markedly greater extent than in C or G despite the fact that net hepatic output essentially ceased within 30 min. This indicates that the catecholamine stimulated the net release of lactate from nonhepatic tissues (most likely muscle). Finally, when both hormones were increased concurrently, there was a brief increase in net hepatic lactate output and a resulting rise in the blood lactate level, followed by a fall in net hepatic lactate output to zero and a continued rise in the lactate level to almost 2.5 mmol/l.


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  		Fig. 3.   Arterial blood lactate levels (A) and net hepatic lactate balance (B) in control (-40 to 0 min) and experimental (0-240 min) periods in C, G, E, and G + E 18-h-fasted conscious dogs. Data are expressed as means ± SE. Statistical comparisons were made by 2-way ANOVA with repeated measures; n = 5 for C, n = 6 each for G, E, and G + E. For arterial lactate levels, P < 0.05 for E vs. C, G, and G + E. Although there was no overall significant difference of G + E vs. C and G, the last 2 time points were significantly different (P < 0.05). All groups increased significantly from basal (P < 0.05). For net hepatic lactate balance, P < 0.05 for G vs. E. All groups changed significantly from basal (P < 0.05; C and G rose significantly, whereas E and G + E fell significantly).

Glycerol, NEFA, and ketones: arterial levels, net hepatic balance, and net hepatic fractional extraction. In both the hyperglycemic control protocol and the glucagon protocol, arterial glycerol levels and net hepatic glycerol uptake drifted down (significantly in G, nonsignificantly in C; Table 3). Epinephrine caused a rise in both arterial glycerol levels and net hepatic glycerol uptake, both of which waned with time. Finally, the combination of glucagon and epinephrine resulted in changes that were similar to those seen with epinephrine alone. Net hepatic glycerol fractional extraction did not change over time in any group and was not different among the groups (data not shown).

                              
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  		Table 3.   Arterial blood levels of glycerol and ketones and arterial plasma levels of NEFA in addition to NH glycerol U, NH NEFA U, and NH ketone P

The NEFA data closely resemble the glycerol data. In the C and G groups, both arterial NEFA levels and net hepatic NEFA uptake fell significantly (Table 3). In the E and G + E groups, there was an early rise in both arterial NEFA levels and net hepatic NEFA uptake, both of which waned with time. Notably, when both hormones were administered concurrently, NEFA levels and uptake tended to remain elevated for a more prolonged period before falling. Net hepatic NEFA fractional extraction did not change in any group and was not different among the groups (data not shown).

Ketone (BOHB and acetoacetate) metabolism tended to mirror changes in NEFA, although statistical significance was not achieved. Arterial blood ketone levels and net hepatic production tended to fall in both C and G (Table 3). In E, blood ketone levels tended to rise and then fall, as did net hepatic production. Finally, in G + E, ketone levels and net hepatic production also tended to rise and fall, although the increase appeared more sustained.

Alanine: arterial levels, net hepatic uptake, and net hepatic fractional extraction. In the hyperglycemic control group, arterial alanine levels rose, net hepatic alanine uptake did not change, and net hepatic fractional extraction of alanine tended to fall (Table 4). In the epinephrine infusion group, both the arterial level and net hepatic uptake of alanine increased, whereas net hepatic fractional extraction was sustained. In the two groups involving glucagon infusion, the arterial alanine levels did not change, but net hepatic alanine uptake increased and net hepatic alanine fractional extraction tended to increase. Although only the alanine data are portrayed, as it is the most important gluconeogenic amino acid, the calculations to determine GNG and GLY flux incorporated the net hepatic balance of the other gluconeogenic amino acids as well (serine, threonine, glycine, glutamine, and glutamate).

                              
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  		Table 4.   Arterial blood levels, net hepatic uptake, and net hepatic fractional extraction of alanine

Gluconeogenesis and glycogenolysis. In response to hyperglycemia (Fig. 4), hepatic GNG flux to G-6-P (mg · kg-1 · min-1) did not change, whereas net hepatic GNG flux fell (-0.5 ± 0.2 to -1.3 ± 0.3 at 240 min, P < 0.05). Net hepatic GLY flux (mg · kg-1 · min-1) also fell when hyperglycemia occurred (1.6 ± 0.3 to -1.4 ± 0.1 at 240 min, P < 0.05). In response to glucagon (Fig. 4), GNG flux to G-6-P did not change significantly, whereas net hepatic GNG flux fell quickly (by 15 min; P < 0.05) and remained modestly suppressed relative to its basal value. Net hepatic GLY flux increased initially (1.9 ± 0.4 to 5.9 ± 1.0 at 15 min) and then waned with time (1.0 ± 0.7 at 240 min). In response to epinephrine (Fig. 5), hepatic GNG flux to G-6-P almost tripled by 240 min (P < 0.05). Net hepatic GNG flux also increased significantly (-0.8 ± 0.4 to 0.7 ± 0.6 at 240 min, P < 0.05). In contrast, there was a nonsignificant rise in net hepatic GLY flux (2.5 ± 0.6 to 3.2 ± 1.2 at 15 min) that waned with time, eventually reaching a rate significantly below basal (-1.0 ± 0.8 at 240 min). Finally, in response to both hormones (Fig. 6), hepatic GNG flux to G-6-P increased significantly, albeit to a slightly lesser extent than with epinephrine alone. Net hepatic GNG flux also increased in a similar manner (P < 0.05). In contrast, net hepatic GLY flux increased significantly (1.7 ± 0.6 to 8.1 ± 1.6 at 15 min) and to a greater extent than with either hormone alone, after which it waned with time (1.5 ± 0.6 at 240 min).


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  		Fig. 4.   Hepatic gluconeogenic (GNG) flux to glucose 6-phosphate (G-6-P; A), net hepatic GNG flux (B), and net hepatic glycogenolytic (GLY) flux (C) in control (-40 to 0 min) and experimental (0-240 min) periods in C and G 18-h-fasted conscious dogs. Data are expressed as means ± SE. Statistical comparisons were made by 2-way ANOVA with repeated measures (significance accepted at P < 0.05); n = 5 for C and n = 6 for G. In C, GNG flux to G-6-P did not change, net hepatic GNG flux fell (P < 0.05), and net hepatic GLY flux fell (P < 0.05). In G, GNG flux to G-6-P did not change, net hepatic GNG flux fell (P < 0.05), and net hepatic GLY flux rose (P < 0.05) and then returned to basal levels. Among groups, for GNG flux to G-6-P, P < 0.05 for C vs. E; for net hepatic GNG flux, there were no significant differences; and for net hepatic GLY flux, P < 0.05 for C vs. G and G + E and for E vs. G + E.



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  		Fig. 5.   Hepatic GNG flux to G-6-P (A), net hepatic GNG flux (B), and net hepatic GLY flux (C) in control (-40 to 0 min) and experimental (0-240 min) periods in C and E 18-h-fasted conscious dogs. Data are expressed as means ± SE. Statistical comparisons were made by 2-way ANOVA with repeated measures (significance accepted at P < 0.05); n = 5 for C and n = 6 for E. In C, GNG flux to G-6-P did not change, net hepatic GNG flux fell (P < 0.05), and net hepatic GLY flux fell (P < 0.05). In E, GNG flux to G-6-P and net hepatic GNG flux rose (P < 0.05), and net hepatic GLY flux fell (P < 0.05). Among groups, for GNG flux to G-6-P, P < 0.05 for C vs. E; for net hepatic GNG flux, there were no significant differences; and for net hepatic GLY flux, P < 0.05 for C vs. G and G + E and for E vs. G + E.



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  		Fig. 6.   Hepatic GNG flux (A), net hepatic GNG flux to G-6-P (B), and net hepatic GLY (C) in control (-40 to 0 min) and experimental (0-240 min) periods in C and G + E 18-h-fasted conscious dogs. Data are expressed as means ± SE. Statistical comparisons were made by 2-way ANOVA with repeated measures (significance accepted at P < 0.05); n = 5 for C and n = 6 for G + E. In C, GNG flux to G-6-P did not change, net hepatic GNG flux fell (P < 0.05), and net hepatic GLY flux fell (P < 0.05). In G + E, GNG flux to G-6-P and net hepatic GNG flux rose (P < 0.05), and net hepatic GLY flux rose (P < 0.05) and then returned to basal levels. Among groups, for GNG flux to G-6-P, P < 0.05 for C vs. E; for net hepatic GNG flux, there were no significant differences; and for net hepatic GLY flux, P < 0.05 for C vs. G and G + E and for E vs. G + E.

The Delta AUC revealed that glucagon and epinephrine do not have a synergistic effect on hepatic GNG flux to G-6-P or net hepatic GNG flux (Fig. 7). In fact, their effects on both parameters, as well as on net hepatic GLY flux, appear to be additive (Fig. 7). Whereas independently each could only increase one process significantly over the 4-h period, together they could simultaneously augment both gluconeogenesis and glycogenolysis.


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  		Fig. 7.   AUCs of hepatic GNG flux to G-6-P (A), net hepatic GNG flux (B), and net hepatic GLY flux (C). All AUCs are shown as change from basal (Delta C), after subtraction of change from basal of C, over 4 h. Data are expressed as means ± SE. Statistical comparisons were made by 1-way ANOVA (significance accepted at P < 0.05); n = 5 for C, n = 6 each for G, E, and G + E. For GNG flux to G-6-P, P < 0.05 for G vs. E; for net GNG flux, P < 0.05 for G vs. E and G + E; and for net GLY flux, P < 0.05 for E vs. G and G + E.


    DISCUSSION
TOP
ABSTRACT
INTRODUCTION
RESEARCH DESIGN AND METHODS
RESULTS
DISCUSSION
REFERENCES

The aim of the present study was to determine whether epinephrine could modify the action of glucagon on hepatic glucose production. We hypothesized that total hepatic production would be additive in the presence of both hormones but that glucagon's effect on gluconeogenesis would be augmented whereas its effect on glycogenolysis would be inhibited. The hormones were indeed found to have additive effects on hepatic glucose production regardless of the technique used to assess the process (NHGB or tracer-determined endogenous Ra). The present study confirmed previous findings that, over a 4-h period, glucagon's action is primarily glycogenolytic whereas epinephrine's action is primarily gluconeogenic. Contrary to our hypothesis, however, the results showed no synergistic effect of the two hormones on gluconeogenesis. Likewise, the glycogenolytic response to the two hormones was not less than the sum of their individual responses. In short, epinephrine did not alter the action of glucagon on hepatic glucose production; instead, the effects of the two hormones were additive, such that a simultaneous rise in both augmented both gluconeogenesis and glycogenolysis markedly.

These studies looked at the effects of physiological increments in glucagon and epinephrine on glucose production by the liver in the absence of changes in insulin and in the presence of matched hyperglycemia. The glucagon levels achieved were approximately one-half those needed for the hormone's maximal effect on glucose production (67). The epinephrine levels were such that they had a small but significant effect on glucose production and a marked effect on gluconeogenesis. In essence, we chose physiological levels of the two hormones that would produce large enough effects on glucose production to be significant alone but small enough to allow the detection of synergism if it occurred.

Our results confirm previous data that found additive effects of glucagon and epinephrine on tracer-determined glucose production (21, 62). However, in both previous studies the additive rise in the presence of both hormones was accompanied by an approximately twofold greater rise in peripheral insulin levels, in addition to an approximately twofold greater rise in the plasma glucose level, compared with the increments that occurred with either individual hormone (21). Therefore, it was possible that additive effects were observed in the previous studies only because hyperinsulinemia and hyperglycemia obscured the synergistic effects of the hormones. Unlike the previous studies, the present study controlled for insulin levels by use of a pancreatic clamp and glucose levels by use of a hyperglycemic clamp. Additionally, the present study separated glucose production into its gluconeogenic and glycogenolytic components. Despite the improved design, however, the conclusions remained the same.

Hepatic GNG flux to G-6-P changed as expected for the control group and for the individual-hormone treatment groups. Changes in net hepatic GNG flux closely resembled changes in GNG flux to G-6-P, even though absolute flux rates were lower. Glucagon treatment did not significantly increase either parameter, whereas epinephrine treatment increased both markedly. Combination of the two hormones did not result in a synergistic effect on gluconeogenesis. There are several possible reasons why synergism did not occur. First, both hyperglycemia and the increased glycogen breakdown that occurred when both hormones were coadministered would be expected to increase flux through the glycolytic pathway. This would, in turn, raise fructose-2,6-bisphosphate levels, making flux through G-6-P in the gluconeogenic direction less likely to occur (31, 50). Second, the gluconeogenic substrates lactate and alanine did not rise as high in the G + E group as in the E group (see below). The reduced availability of lactate and alanine may have limited the gluconeogenic response when the hormones were coadministered. Third, it is possible that there was a synergistic effect on GNG flux but it was too small to detect given the assumptions of the method used to estimate gluconeogenesis.

Net hepatic GLY flux also changed as expected in the control group and the individual hormone treatment groups. Net glycogen breakdown ceased in response to hyperglycemia; in fact, net glycogen synthesis occurred by the end of the study. The increase in glucagon resulted in a large increase in net glycogenolysis, whereas the increment in epinephrine did not increase net glycogenolysis significantly over the 4-h period. Net glycogenolysis increased to a similar extent during combined hormone infusion as during glucagon-alone administration. It is likely that the lack of synergism with regard to gluconeogenesis explains the lack of inhibition of glycogenolysis by the combination of the two hormones.

Glucose utilization increased in the control group due to hyperglycemia. However, glucose utilization tended to increase less in both the glucagon group [probably due to decreased glucose uptake by liver (7, 40, 51, 65)] and the epinephrine group [probably due to decreased glucose uptake by muscle (10)] than in the control group. When both hormones were combined, glucose utilization was significantly less than in the control (hyperglycemia alone) group. In fact, the increase in glucose utilization when both hormones were administered concurrently was not significant. This is important physiologically, because these hormones decrease glucose clearance individually by different mechanisms and thus together can increase glucose availability for the brain during times of stress.

Lactate levels rose in the hyperglycemic control group, as seen previously (65), likely due to increased glucose uptake by the liver and subsequent release of the carbon as lactate. Glucagon administration resulted in a small, quick rise in lactate production that waned with time, most likely the consequence of glucagon's rapid effect on glycogen breakdown, as reported previously (7, 8). This effect was short-lived, and after 1 h the glucagon group resembled the control group in both lactate levels and net hepatic balance. Lactate levels rose markedly with epinephrine treatment, as shown previously (6, 10, 14, 59), presumably due to increased lactate production from muscle glycogenolysis. Notably, lactate levels were significantly lower in the presence of both hormones than in the presence of epinephrine alone, even though both hormones stimulate lactate production by different organs. There are three possible explanations for this finding. The first relates to a known action of glucagon, which is to increase the efficiency of hepatic gluconeogenic precursor uptake (43, 67). In the combined-treatment group, the liver removed lactate at the same rate as in the epinephrine group, even though the arterial lactate level was much lower. Thus the liver was more efficient at removing lactate in the presence of both glucagon and epinephrine, probably because of stimulation of gluconeogenic enzyme activity by glucagon. This increased efficiency of uptake would likely allow steady state to be achieved earlier and thus result in a lower arterial lactate level. A second possible explanation for the lower lactate levels in the presence of both hormones is that lactate disappearance increased in response to glucagon at a site other than the liver. The third possible explanation is that glucagon decreased lactate appearance in the combined group. Because skeletal muscle has not been shown to possess glucagon receptors (4) and the kidney is not responsive to glucagon (25, 69), it seems unlikely that the effect on the lactate level was due to either of the latter possibilities.

Arterial alanine levels rose as expected in the control group due to hyperglycemia (65). Alanine levels remained unchanged in the presence of glucagon (67), the reason being that glucagon increases hepatic alanine fractional extraction by increasing alanine transport into the liver (36-38). As expected, alanine levels did not differ as a result of epinephrine treatment (10). However, when both hormones were administered together, the rise in alanine was less than with epinephrine alone. The possible explanations for this are the same as for lactate, with one additional possibility: the different lactate levels. Lactate administration increased alanine release from perfused rat skeletal muscle (58), and peripheral lactate infusion in the conscious dog increased the plasma alanine level (15). Thus alanine may have been lower in the combined group in part because lactate levels were lower.

Glycerol concentrations decreased in the control group, reflecting decreased lipolysis probably due to both hyperglycemia (16) and the infusion of somatostatin for an extended period of time (29). Glucagon is known to have little effect on lipolysis in vivo, and glucagon treatment had no demonstrable effect on glycerol levels in this study (2, 27). Epinephrine increased glycerol levels but only for a brief period, as expected (10, 16). Combined hormone treatment logically resembled epinephrine treatment, and glycerol levels increased and waned to similar values. For all groups, net hepatic glycerol uptake paralleled changes in arterial levels. In general, NEFA levels and net hepatic uptake tended to follow the same patterns as glycerol. Note that in both groups receiving epinephrine infusion, NEFA levels and uptake rates increased and waned, as expected. However, the elevations in both the level and net hepatic uptake in the combined hormone group were sustained for a longer period than in the epinephrine-alone group. This was perhaps due to the higher lactate level in the epinephrine group, as lactate has been shown to cause a fall in NEFA levels in vitro (3) and in vivo in dogs (15, 32, 44) and humans (1). Interestingly, NEFA increases gluconeogenesis in vivo (5, 9, 13, 52, 68, 73), and during the period (time 60-90 min) in which NEFA tended to be elevated in the combined group, there was a tendency for the GNG flux rate to be increased.

In summary, glucagon and epinephrine had additive effects on glucose production and perhaps glucose utilization. Furthermore, these hormones had additive effects on hepatic glycogenolysis. There was no synergism with regard to gluconeogenesis, probably due to the fact that glucagon increased the efficiency of hepatic gluconeogenesis without increasing the delivery of gluconeogenic precursors to the liver from muscle and adipose tissue. Regardless, it can be concluded that epinephrine did not modify glucagon's effect on either glycogenolysis or gluconeogenesis. When raised concurrently, glucagon and epinephrine do what neither can do alone, namely increase both components of hepatic glucose production. Under stress conditions, such changes in glucagon and epinephrine would undoubtedly be accompanied by changes in insulin, and it remains to be seen whether, in the presence of hyperinsulinemia, their interaction would be altered.


    ACKNOWLEDGEMENTS

We thank Margaret Converse, Wanda Snead, Eric Allen, Angela Penaloza, and Jon Hastings for excellent technical support. Additionally, we express gratitude to Dr. Mary Moore for careful reading of the manuscript.


    FOOTNOTES

This research was supported by a National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) grant for the Diabetes Research and Training Center at Vanderbilt University, P60-DK-20593, by an NIDDK grant for the Clinical Nutrition Research Unit at Vanderbilt University, P30-DK-26657, by an NIDDK grant for the Molecular Endocrinology Training Program, T32-DK-07563, and by another NIDDK grant, R37-DK-18243.

This work was presented in part at the 60th Annual Meeting of the American Diabetes Association, San Antonio, TX, June 2000.

Address for reprint requests and other correspondence: S. M. Gustavson, Vanderbilt Univ. Medical Center, Div. of Diabetes, Endocrinology, and Metabolism, 715 Preston Research Bldg., Nashville, TN 37232-6303 (E-mail: stephanie.m.gustavson{at}vanderbilt.edu).

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

First published December 27, 2002;10.1152/ajpendo.00308.2002

Received 11 July 2002; accepted in final form 19 December 2002.


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RESULTS
DISCUSSION
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