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Original Article |
Department of Physiology and Biophysics (G.W.V.C., M.K., S.P.K., S.D.M., M.K.D., R.N.B.), Keck School of Medicine, University of Southern California, Los Angeles, California 90089-9142; and Department of Physiology (P.L.B.), University of Toronto, Toronto, Ontario, M5S 1A8 Canada
Address all correspondence and requests for reprints to: Richard N. Bergman, Ph.D., Department of Physiology and Biophysics, University of Southern California, Keck School of Medicine, 1333 San Pablo Street, MMR 626, Los Angeles, California 90089-9142. E-mail: rbergman{at}usc.edu.
Abstract
We previously developed a canine model of central obesity and insulin resistance by supplementing the normal chow diet with 2 g cooked bacon grease/kg body weight. Dogs fed this fatty diet maintained glucose tolerance with compensatory hyperinsulinemia. The signal(s) responsible for this up-regulation of plasma insulin is unknown. We hypothesized that meal-derived factors such as glucose, fatty acids, or incretin hormones may signal ß-cell compensation in the fat-fed dog. We fed the same fat-supplemented diet for 12 wk to six dogs and compared metabolic responses with seven control dogs fed a normal diet. Fasting and stimulated fatty acid and glucose-dependent insulinotropic peptide concentrations were not increased by fat feeding, whereas glucose was paradoxically decreased, ruling out those three factors as signals for compensatory hyperinsulinemia. Fasting plasma glucagon-like peptide-1 (GLP-1) concentration was 2.5-fold higher in the fat-fed animals, compared with controls, and 3.4-fold higher after a mixed meal. Additionally, expression of the GLP-1 receptor in whole pancreas was increased 2.3-fold in the fat-fed dogs. The increase in both circulating GLP-1 and its target receptor may have increased ß-cell responsiveness to lower glucose. Glucose is not the primary cause of hyperinsulinemia in the fat-fed dog. Corequisite meal-related signals may be permissive for development of hyperinsulinemia.
ALTHOUGH INSULIN RESISTANCE is associated with obesity (1) and type 2 diabetes (2, 3), frank diabetes develops only when the ß-cells fail to compensate appropriately for insulin resistance (4). Hyperinsulinemia is the physiological response that maintains glucose homeostasis in the insulin-resistant organism. However, the precise mechanisms by which the normal organism detects insulin resistance and compensates with hyperinsulinemia are not known. It is important to identify the signal or signals that mediate ß-cell compensation because compensatory failure is a first step to diabetes. The ß-cell requires a rise in ambient glucose concentration to stimulate insulin secretion (5). Many endogenous substances augment glucose-stimulated insulin secretion (GSIS) and may play a role in ß-cell compensation for insulin resistance. Among these are fatty acids (6) and/or the intestinally derived incretin hormones glucose-dependent insulinotropic peptide (GIP) and glucagon-like peptide-1 (GLP-1) (7). Each of these substances has been associated with hyperinsulinemia in obesity and diabetes (6, 8, 9, 10). Although we recently described a longitudinal fat-fed canine model of central obesity, insulin resistance, and hyperinsulinemic compensation (11), we did not examine the roles of these potential signals in compensation for insulin resistance.
Hyperglycemia and hyperinsulinemia develop during the progression from normal glucose tolerance to type 2 diabetes (12). Glucose is perhaps the most likely candidate for mediating hyperinsulinemia in the face of insulin resistance. However, first-degree relatives of patients with type 2 diabetes and members of ethnic groups at high risk for developing diabetes (13) are hyperinsulinemic but not hyper-glycemic, suggesting that hyperinsulinemia can precede hyperglycemia. Therefore, glucose may not be the primary signal to compensate for insulin resistance.
Dyslipidemia, of which elevated fatty acid concentration is a component, is a feature of obesity and type 2 diabetes. Fatty acids may be more available in the insulin-resistant state of obesity when insulinemia is insufficient to appropriately suppress lipolysis (14), particularly if the adipocyte is also resistant to the hormone. Because fatty acids can augment GSIS in vivo (6, 15, 16) and in vitro (17, 18), failure to adequately suppress fatty acid release from adipose tissue could synergize insulin release to a given glucose stimulus. Fatty acids also suppress hepatic insulin clearance (19, 20, 21). Thus, elevated fasting or stimulated fatty acid concentration could contribute to the development of hyperinsulinemia of obesity and diabetes. However, first-degree relatives of patients with type 2 diabetes are hyperinsulinemic with normal plasma fatty acid concentrations (9, 22, 23). Furthermore, pharmacological lowering of fatty acid concentrations in this setting increases rather than decreases the insulin response to glucose challenges (24). Therefore, fatty acid concentration may not be a requisite signal to the pancreatic ß-cell to compensate for insulin resistance.
Exaggerated incretin response to a meal may also explain hyperinsulinemia. Incretin hormones released by the intestine in response to oral nutrients augment GSIS and glucose disposition (25, 26). Meal-derived glucose and fatty acids in the gastrointestinal lumen are potent stimulators of incretin release (27, 28, 29). Thus, elevated fasting or stimulated incretin hormone concentrations could play a role contributing to hyperinsulinemia. Increasing GLP-1 concentration by inhibiting its degradation (30) or feeding a high-fat meal (10) increases insulin secretion and improves glucose tolerance in hyperinsulinemic obese rats. Digestion and absorption of a fatty meal requires several hours (31), depending on the magnitude of the fat load imposed by the meal. GLP-1 release in this situation could occur over a prolonged period and contribute to elevated fasting GLP-1 levels. Therefore, exaggerated GLP-1 response to chronic fat consumption could be a primary mediator for compensatory hyperinsulinemia. In this study, we examined the roles of glucose, fatty acids, and incretin hormones as potential signals for hyperinsulinemia in response to fat feeding in the dog.
Materials and Methods
Animals
The experimental protocol was approved by the University of Southern California (USC) Institutional Animal Care and Use Committee. Healthy male mongrel dogs (n = 13) were housed under controlled kennel conditions (12-h light:12-h dark cycle) in the USC Keck School of Medicine vivarium. Dogs were fed either only a control diet for 3 wk (control group, n = 7) or the control diet supplemented with fat (fat-fed group, n = 6) for 12 wk. In our experience, dogs fed the control diet for several months remain stable, so a 3-wk period was selected to verify maintenance of weight and metabolic parameters. The control diet consisted of a half can (
200 g) of Hill’s Prescription Diet (27.3% protein, 8.3% fat, 44.3% carbohydrate, 7.6% fiber; Hill’s Pet Nutrition, Inc., Topeka, KS) and dry chow ad libitum (up to 900 g daily; 26.4% protein, 14.7% fat, 39.6% carbohydrate, 17% fiber; Wayne Dog Food, Alfred Mills, Chicago, IL). The control diet consisted of approximately 3424 kcal/d, 44% from carbohydrates, 28% from protein, and 28% from fat. The modest fat supplementation consisted of 2 g cooked bacon grease per kilogram initial body weight (obtained from the USC Keck School of Medicine cafeteria). The addition of fat to the diet increased total energy to approximately 3900 kcal/d and calories from fat to approximately 38%.
Magnetic resonance imaging (MRI) scans
MRIs of the control dogs were taken after approximately 3 wk on the control diet and of the fat-fed dogs after approximately 12 wk on the fat-supplemented diet. To do this, anesthesia was induced immediately before the MRI scan by sc injection of a mixture of acepromazine (0.1 mg/kg body weight; Bio-ceutic, St. Joseph, MO) and atropine sulfate (0.04 mg/kg, 1/120 grain; Western Medical Supply, Inc., Arcadia, CA), followed by iv injection of a mixture of ketamine HCl (10 mg/kg; Phoenix Pharmaceutical, Inc., St. Joseph, MO) and diazepam (0.2–0.5 mg/kg; Abbott Laboratories, North Chicago, IL). Adipose tissue in sc and ip depots was quantified from 1 of 30 axial abdominal images (1-cm T1 slices, TR:500, TE:14, 1.5 Tesla Horizon magnet, version 5.7 software; General Electric) using ScionImage software (Windows 95, version ß3b; Scion Corp., Frederick, MD), as described previously (11).
Frequently sampled iv glucose tolerance tests (FSIGTs)
Insulin-modified FSIGTs were performed as described previously (11) within 10 d of the MRIs. Glucose and insulin doses were determined for both groups from the body weight before special diets began. Animals were familiarized with a Pavlov sling at least 1 wk before experimental procedures. At approximately 0700 h on the day of the FSIGT following a 16-h fast, animals were brought to the laboratory and placed in the Pavlov sling. A 19-gauge iv catheter was placed in a saphenous vein and secured. Sampling began approximately 20 min after catheter placement. After baseline fasting samples at -20, -10, and -1 min, 300 mg glucose/kg body weight (50% dextrose, 454 mg/ml) were injected into the saphenous vein (t = 0). Porcine insulin (30 mU/kg; Novo Nordisk, Copenhagen, Denmark) was injected at 20 min. Twenty-eight additional blood samples were collected at t = 2, 3, 4, 5, 6, 8, 10, 12, 14, 16, 19, 22, 23, 24, 25, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 140, 160, and 180 min into chilled tubes, immediately centrifuged, and plasma was separated. Samples for assay of glucose, lactate, and insulin were placed in tubes coated with lithium fluoride and heparin containing 50 µl EDTA; samples for assay of lipids were placed into tubes coated with the lipoprotein lipase antagonist paraoxon (Sigma, St. Louis, MO) and containing 75 µl EDTA. Samples for assay of protease-sensitive peptides were collected into tubes containing 25 µl 2% EDTA/ml blood plus 25 µl aprotinin/ml blood (10,000 KIU/ml; Serologicals Corp., Clarkston, GA).
Meal tolerance tests (MTTs)
MTTs were performed within 1 wk of the FSIGTs. At approximately 0700 h on the day of the MTT, animals were brought to the laboratory and placed in the Pavlov sling. A 19-gauge iv catheter was placed in each saphenous vein and secured. Sampling began approximately 20 min after catheter placement. After one baseline sample at -90 min, a constant infusion of [9,10]-3H-palmitate (1.6 µCi/min, Sigma) was initiated. A mixed meal containing approximately 200 g canned dog food (Hill’s Prescription Diet), approximately 200 g dry dog chow (Wayne Dog Food), 4 µCi 1-14C-palmitate/kg body weight homogenized with 2 g cooked bacon grease/kg body weight, and approximately 50 ml warm water were offered at t = 0 min and removed at t = 10 min. Meals were consumed (79.2 ± 10.0% eaten) within 7.4 ± 1.0 min. There were no significant differences in meal composition, percentage consumption, or consumption time within or between groups (data not shown). Twenty-one additional blood samples were collected into chilled tubes, immediately centrifuged, and plasma was separated at t = -90, -30, -20, -10, -1, 5, 10, 20, 30, 40, 50, 60, 75, 90, 105, 120, 150, 180, 210, 220, 230, and 240 min. Sample collection tubes were prepared as described above.
Assays
Glucose and lactate were measured with a YSI 2700 autoanalyzer (Yellow Springs Instrument Co., Yellow Springs, OH) and the remaining plasma stored at -20 C for insulin analysis. Free fatty acids (FFAs) were measured with the NEFA C kit (Wako Pure Chemical Industries, Richmond, VA) colorometric assay based on coenzyme-A acylation. Glycerol was measured with the GPO-Trinder colorometric triglyceride kit (Sigma) based on glycerol kinase and glycerol phosphate oxidase. Both assays were modified for microvolume samples as previously described (11). Insulin was measured with an ELISA (Novo-Nordisk) originally developed for human serum or plasma and adapted for dog plasma. The method is based on two murine monoclonal antibodies that bind to different epitopes on insulin but not to proinsulin. Materials for the insulin assay, including the dog standard, were kindly provided by Novo-Nordisk. The intraassay variance was 2.9%; the interassay variance was 6%. C-peptide was measured RIA (kit CCP-24HK; Linco Research, Inc., St. Charles, MO) with an intraassay variance of 6.9% and an interassay variance of 6.7%. Active GLP-1 (7–37 and 7–36 amide) was measured to 2 pM by ELISA, a two-site noncompetitive immunoassay based on enzyme-labeled quantification of GLP-1 detected by a fluorogenic substrate that does not detect GLP-1 degradation product (9–36 amide), GLP-2, or glucagon (kit EGLP-35K; Linco). Our assay variance (intraassay, 4.5%; interassay, 12.9%) was comparable with that of RIA measures of active GLP-1 (6–18%) (32, 33, 34). GIP was measured by RIA (kit RIK-7192; Peninsula Laboratories, Inc., San Carlos, CA) after plasma extraction on a C18 Sep-Pak (Waters Corp., Milford, MA). Incretin hormones were measured in six control and five fat-fed dogs.
RNA isolation
At the end of the diet, dogs were killed and tissue samples obtained from pancreas for assessment of gene expression. Similar biopsies were obtained from dogs that consumed a standard diet. Tissue samples were stored at -80 C until analysis. Total RNA was extracted from frozen pancreas using the Tri-reagent kit (Molecular Research Center, Inc., Cincinnati, OH). RNA samples were treated with DNase and quantified by spectrophotometry. Integrity of pancreatic RNA samples was assessed by agarose gel electrophoresis and ethidium bromide staining. RNA samples were then diluted as appropriate to equalize concentrations and stored at -80 C.
Preparation of cDNA probe by RT-PCR
Dog GLP-1 receptor cDNA was synthesized from 2 mg total RNA in 50 µl final incubation volume by using the Advantage one-step RT-PCR kit (CLONTECH Laboratories, Inc., Palo Alto, CA). The sequence of the upstream primer was 5'-ATCCTCCGAGCGCTGTCCGTCTTC-3' and downstream primer was 5'-CTTGTTCATCCATCACGAAGGCAA-3' as previously published (35). Briefly the reverse transcription was carried out under the following conditions: 50 C for 1 h, 90 C for 5 min, and PCR amplification of cDNA was performed in 35 cycles (94 C for 30 sec, 60 C for 30 sec, 68 C for 1 min) and one cycle at 72 C for 2 min, yielding a 562-bp product. PCR products were analyzed by gel electrophoresis using 2% agarose. Appropriate PCR products were purified by gel extraction (QIAquick gel extraction kit, QIAGEN, Valencia, CA), and both strands were sequenced in duplicate using an automated ABI Prism 377 DNA sequencer (USC/Norris Cancer Center, Microchemical Core Facility). The sequenced region showed 91% homology with human GLP-1 receptor as described previously (35).
Northern blot analysis
Equal amounts (20 mg) of total RNA were fractionated on 1% agarose gel (NorthernMax, Ambion, Inc., Austin, TX). Total RNA was transferred overnight through capillary action onto a Hybond-XL nylon membrane (Amersham Pharmacia Biotech, Buckinghamshire, UK). Dog GLP-1 receptor cDNA was labeled with [
-32P] dCTP by using a multiprime DNA labeling system kit (DECAprime II, Ambion, Inc.). Membranes were prehybridized (2 h at 42 C) and hybridized overnight at 42 C (Ultrahyb, Ambion, Inc.). Membranes were washed in 1 x saline sodium citrate/0.1% SDS twice for 20 min at 42 C and exposed on BioMax MS double-emulsion photographic film (Eastman Kodak Co., Rochester, NY) for 7 h at -80 C, using intensifying screens. Radioactivity in each band was quantified, and the fold change in each mRNA was calculated after correction for loading differences by measuring the amount of 18S rRNA.
Calculations
Insulin sensitivity (SI), the acute insulin response to glucose [AIRG(0–10)], glucose tolerance measured from 10–19 min after glucose injection, and glucose effectiveness were calculated from the FSIGT glucose profiles with MinMod software (version 3.0, 1994; USC). The disposition index, which represents insulin responsiveness corrected for changes in insulin sensitivity (36), was calculated as the mathematical product of SI and AIRG (0–10). Homeostasis model assessment (HOMA) values were calculated for insulin resistance and ß-cell function from fasting plasma insulin and glucose values by linear approximation (37, 38). Insulin clearance was estimated from the insulin decay during the FSIGT (11) and by the ratio of insulin to C-peptide during the first 10 min of the FSIGT and the MTT. Areas under time course curves were computed using the trapezoidal rule. Mann-Whitney two-sample rank tests performed with Minitab version 12.23 (Minitab, Inc., State College, PA) were used to compare outcomes between groups. Numeric results are presented as mean ± SEM.
Results
There was no difference in the initial weight of the control dogs, compared with the fat-fed dogs. After the diet period, the fat-fed dogs weighed significantly more than the control dogs (P < 0.01), although the apparent differences between groups in abdominal adiposity did not achieve significance (Table 1
). Despite fat feeding, dogs were not glucose intolerant, compared with controls (control, 2.22 ± 0.27 kg; fat-fed, 2.42 ± 0.44 kg; P = NS), and glucose effectiveness was not different between the groups (Table 2). Both HOMA values for insulin resistance (control, 19.0 ± 1.7 pM/mM; fat-fed, 23.0 ± 1.7 pM/mM; P < 0.05, Table 2) and fasting insulin concentration were higher in the fat-fed animals (77.6 ± 6.2 vs. 104.9 ± 7.6 pM, P < 0.01, Table 3), suggestive of insulin resistance. Similarly, there was a tendency toward impaired insulin action in the fat-fed dogs by minimal model analysis of FSIGT data (SI, -39%, P = 0.07, Table 2). Enhanced ß-cell responsiveness appeared to contribute to the hyperinsulinemia because the HOMA value calculated for ß-cell function was 91% greater in the fat-fed animals (817.9 ± 60.5 vs. 1563.2 ± 116.4 pM/mM-1, P < 0.0001). Paradoxically, mean fasting plasma glucose concentration was a highly significant 9% lower in the fat-fed vs. the control animals (5.4 ± 0.1 vs. 4.9 ± 0.1 mM, P < 0.0001) and fasting FFA, glycerol, and GIP concentrations were not higher in the fat-fed group (Table 3). In striking contrast, fasting GLP-1 concentration was amplified 2.5-fold in the fat-fed animals (5.5 ± 0.6 vs. 13.9 ± 1.5 pM, P < 0.05). This was paralleled by a 2.3-fold increase in pancreatic GLP-1 receptor expression in the fat-fed dogs (Fig. 1).
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). The fractional insulin clearance rate (0.43 ± 0.05 vs. 0.43 ± 0.04 min-1, P = NS) and the insulin to C-peptide ratio during the FSIGT (1.38 + 0.14 vs. 1.47 ± 0.21, P = NS) were also similar between groups. The insulin to C-peptide ratio during the meal tended to be greater in the fat-fed dogs (0.79 ± 0.10 vs. 1.28 ± 0.19, P = 0.051), suggesting impaired insulin clearance in response to oral nutrients.
Integrated glucose, FFA, insulin, and GLP-1 responses during the meal are shown in Fig. 2. The 1-h integrated insulin response to the meal was unaffected by 12 wk of fat feeding (Fig. 2c); however, FFA suppression was slower and the integrated response was greater in fat-fed dogs (Fig. 2b, P < 0.01), suggesting insulin resistance of adipose tissue. The integrated glucose response was significantly lower in the fat-fed dogs (Fig. 2a, P < 0.05). Consistent with the fasting data, the integrated GLP-1 response was greatly magnified (3.4-fold) by fat feeding (Fig. 2d, P < 0.05), but the integrated GIP response was unaffected.
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Our data show that glucose is not the primary signal for hyperinsulinemia in response to a moderately fatty diet (Fig. 2). Neither dynamic nor steady state FFAs or GIP was different between groups and thus did not play a role in this model of diet-induced hyperinsulinemia and insulin resistance. If glucose were the primary signal for hyperinsulinemia, plasma glucose concentration would have to be higher at fasting, after a meal, or both in the hyperinsulinemic animals. Paradoxically, both meal and fasting plasma glucose were significantly lower in the fat-fed animals. Lower glucose is consistent with the concept that hyperinsulinemia was driven by a compensatory signal other than glucose itself.
We expected that dogs fed a moderate fat diet for 12 wk would develop a similar degree of adiposity and insulin resistance as the dogs we previously studied longitudinally (65% lower SI at 12 wk vs. baseline) (11). However, the difference in SI in these fat-fed dogs studied cross-sectionally, compared with the controls, was less than in our previous longitudinal report. These animals weighed more than the control dogs, although we did not detect any difference in adiposity. It is possible that muscle mass increased in the setting of hyperinsulinemia, although the scant muscle viewed in an abdominal cross-sectional image permitted neither quantification nor extrapolation to whole-body muscle mass. The fat-fed dogs also showed a tendency toward insulin resistance by minimal model analysis (39% lower SI with fat feeding). Although this failure to definitively detect differences in insulin sensitivity probably resulted from increased variance associated with the cross-sectional design, there were other indicators suggestive of insulin resistance, including fasting hyperinsulinemia, steady state insulin resistance, and the FFA-insulin responses to the meal.
An increase in glycemia has long been considered the primary stimulus for a homeostatic rise in insulinemia (5). Hyperinsulinemia and insulin resistance coexist in the prediabetic state (13, 39). An increase in plasma glucose in response to inadequate insulin action would signal a compensatory increase in insulin release. As insulin sensitivity declines, glycemia may tend to creep higher, resulting in glucotoxicity and ß-cell failure (40) and eventually type 2 diabetes. Paradoxically, in the fat-fed dogs, fasting plasma glucose was unquestionably decreased despite fasting hyperinsulinemia and meal glucose response was lower despite similar insulin response. By the traditional paradigm, glucose would have to be elevated to stimulate insulin release. Therefore, elevated plasma glucose was not the primary signal inducing fasting hyperinsulinemia in the fat-fed dogs.
FFAs could augment ß-cell response as a compensatory mechanism for insulin resistance and play a later toxic role in ß-cell failure during the shift from impaired glucose tolerance to frank diabetes. FFAs have been associated with potentiated glucose-stimulated insulin secretion in vitro (6, 41) and in vivo (42, 43). Chronic exposure of ß-cells to elevated FFAs may induce ß-cell failure from lipotoxicity (44). Adipocytes in our fat-fed dogs were insulin resistant, as indicated by fasting hyperinsulinemia in the absence of lower fasting FFAs and reduction in FFA suppression during the meal. The lack of measurable change in fasting plasma FFAs suggests that fatty acids were not an important early signal to the ß-cell to provoke hyperinsulinemia. By the end of the MTT, FFA response was not different between groups (data not shown), so prandial fatty acids are an unlikely signal for fasting hyperinsulinemia.
Plasma insulin response to oral glucose is exaggerated, compared with iv glucose (25). This incretin effect (45) involves communication between the digestive tract and the pancreas via humoral factors that potentiate insulin secretion (46). Although many hormones released by the gut in response to a nutrient load have been tested, only GIP and GLP-1 are gastrointestinal factors today considered to be incretins (47). Although GIP is a substantial and important component of the incretin effect stimulated by oral glucose (48), GIP is inconsequential in the incretin response to a mixed meal (49) in man. Our GIP data confirm these results in the dog. Furthermore, GIP receptor antibodies do not affect fasting or glucose-stimulated insulinemia in mice lacking the GLP-1 receptor (50), suggesting a dominant role for GLP-1 vs. GIP in regulation of glycemia. GLP-1 is a more potent insulin secretagogue than GIP (51) and is responsible for up to 70% of the incretin effect (52), compared with 20–50% for GIP (53, 54). Hyperinsulinemic type 2 diabetic patients have higher basal GLP-1 than healthy controls (51, 55). The higher basal and prandial GLP-1 concentrations in the fat-fed dogs mirrors this pattern and suggests increased production or decreased degradation of active GLP-1 in response to chronic exposure of intestinal L cells to fat. A 24-h study in humans consuming a normal mixed diet showed that plasma GLP-1 remained elevated throughout the day, returning to basal only overnight (56). Chronic consumption of fatty meals may sustain this elevation of GLP-1 overnight.
The ELISA kit we used to quantify plasma GLP-1 was elegantly validated by Persson et al. (57). The fasting plasma GLP-1 concentration in the control dogs (5.5 ± 0.6 pM) is within the normal range for humans (34, 58) and dogs (35, 59); fasting GLP-1 concentration in the fat-fed dogs is slightly greater than the normal range. Furthermore, the increase in plasma GLP-1 we observed during the test meal in both groups of dogs was similar in magnitude to the increase observed by Jeppesen et al. (58) during a mixed meal in humans. These data from other investigators reinforce our observations.
The dog model is a robust model for studying L cell physiology and has been for years (60, 61). Although the canine stomach contains glucagon-producing A cells, it does not contain GLP-1-producing L cells. Thus, one would not expect to find any GLP-1 produced by the canine gastric A cell because the peptide splice patterns in the two cell types are distinct (62). Furthermore, glucagon secretion by the A cell, whether gastric or pancreatic, could not play any role in producing the putative GLP-1 and metabolic responses detected in this model. First, the assay used to detect GLP-1 is an ELISA with 0% cross-reactivity with glucagon, GLP-1(9–36-amide), or GLP-2 (www.lincoresearch.com). Second, glucagon secretion in the dog is determined by sympathetic nervous system activation, not pancreatic hyperglycemia. Because the sympathetic nervous system would be quiescent during feeding, any rise in glucagonlike immunoreactivity could not be derived from the pancreas or stomach in the fed state (in which we detected a 3.4-fold larger GLP-1 response in the fat-fed animals, compared with controls). Third, glucagon would cause an increase in plasma glucose, and we in fact observed lower plasma glucose in both the fasting and fed states.
For GLP-1 to stimulate insulin secretion, ambient glucose must be at normal or slightly elevated concentrations (63, 64, 65). Insulin secretion requires activation of a cAMP-dependent pathway for the ß-cell to be glucose competent, i.e. sensitive to glucose as a signal for insulin secretion (66). GLP-1, as a stimulator of cAMP production, has been shown to restore glucose competence in ß-cells (67). The enhanced insulin secretion during a meal (25) results from both incretin-stimulated cAMP production and metabolism of meal-derived glucose in the ß-cell. Thus, significant elevation of GLP-1 increases ß-cell gain such that insulin secretion could be normalized even at lower ambient glucose. In addition, the increased GLP-1 receptor expression we observed may be a second pathway to increased ß-cell gain.
We did not observe greater insulin secretion in the fat-fed dogs, compared with controls in response to either iv glucose or a mixed meal. When we previously fed fat to dogs for 12 wk and monitored insulin sensitivity, secretion, and clearance, we noted a phasic response producing compensatory hyperinsulinemia (11). The dogs became severely insulin resistant without hyperinsulinemic compensation for 2 wk, followed by increased acute insulin secretion peaking at 6 wk, followed by a decrease in secretion and impaired insulin clearance. Because these dogs were studied only at 12 wk, we did not expect to see significantly greater insulin secretion. Alternatively, these data suggest the possibility of a ß-cell defect that failed to produce a compensatory increase in insulin secretion in response to worsening insulin sensitivity. A tendency toward increased glucose effectiveness (33% greater in the fat-fed dogs) (Table 2) may represent a strategy to normalize glucose disposal in an insulin-independent fashion, thus sparing the ß-cell.
Insulin extraction by the liver is impaired by oral, compared with iv, glucose in rats (68) and healthy humans but not type 2 diabetic subjects (69) and may be related to incretins or other meal-derived factors. This suggests that impaired insulin clearance, an important compensation mechanism (48, 68, 70), is lost in diabetes. Our previous findings showed that impaired insulin clearance dominated the hyperinsulinemia from 9 to 12 wk as insulin secretion normalized, although the effect was not significant at 12 wk. Consistent with this previous report, we did not observe a significant decline in insulin clearance in the 12-wk fat-fed animals in the current study when measured by the insulin and C-peptide responses to iv glucose. However, insulin clearance early during a meal tended to be impaired, compared with iv glucose, in line with previous observations (71). Kjems et al. (72) have recently demonstrated in a swine model of islet dysfunction that reduced ß-cell mass is associated with impaired postprandial insulin clearance. Although we did not measure ß-cell mass, it is possible that 12 wk of chronic exposure to a high-fat diet may have been lipotoxic to ß-cells (41). Postprandial impairment of insulin clearance may compensate for the diminished ß-cell secretory capacity we observed.
We may have failed to detect truly significant differences in SI, AIRG, and glucose effectiveness because of the cross-sectional nature of the study design. Differences in these dynamic parameters were not evident at the 12-wk time point but may have manifested earlier or later during the course of fat feeding. We did, however, observe evidence of significant insulin resistance and hyperinsulinemic compensation by several static measures (plasma insulin, HOMA). It is thus possible that significant divergences in dynamic response occurred outside our brief 4-h window of observation but remained evident 16 h after food withdrawal.
In summary, glucose was not a primary signal for hyperinsulinemia in the fat-fed dog. We hypothesize that increased GLP-1 release in response to chronic stimulation by lumenal fat, coupled with increased GLP-1 receptor expression in the pancreas, enhances ß-cell glucose competence, permitting fasting hyperinsulinemia. In conclusion, our data do not support a role for elevated plasma glucose in the development of hyperinsulinemia in response to fat feeding in this canine model.
Acknowledgments
Footnotes
This work was supported by NIH Research Grants DK27619 and DK29867 (to R.N.B.), a NIH grant supplement (to G.W.V.C.), and a Tier 1 Canada Research Chair (to P.L.B.). S.D.M. performed this work while he was a predoctoral trainee supported by the National Institute on Aging (T32-AG-00093) and a postdoctoral fellow supported by a mentor-based grant from the American Diabetes Association. S.P.K. and M.K.D. performed this work while they were predoctoral trainees supported by the National Institute on Aging (T32-AG-00093).
Abbreviations: AIRG, Acute insulin response to glucose; FFA, free fatty acid; FSIGT, frequently sampled iv glucose tolerance test; GIP, glucose-dependent insulinotropic peptide; GLP-1, glucagon-like peptide-1; GSIS, glucose-stimulated insulin secretion; HOMA, homeostasis model assessment; MRI, magnetic resonance imaging; MTT, meal tolerance test; SI, insulin sensitivity.
Received January 7, 2002.
Accepted August 8, 2002.
References
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) and dogs fed a fat-supplemented diet (
) for 12 wk (a). Chronic dietary fat supplementation produced hyperinsulinemia in dogs in the absence of hyperglycemia or hyperlipacidemia. In stark contrast, the 2.5-fold increase of plasma GLP-1 was associated with fasting hyperinsulinemia. Further supporting the role of GLP-1 in up-regulating glucose responsiveness was the 2.3-fold higher GLP-1 receptor expression in fat-fed dog pancreas, compared with control (a and b). *, P < 0.01, compared with controls; 
, P < 0.0001, compared with controls; 
, P < 0.05, compared with controls.