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The Journal of Clinical Endocrinology & Metabolism 89(8):3914 –3921
Copyright © 2004 by The Endocrine Society
doi: 10.1210/jc.2003-031941
Separate Contribution of Diabetes, Total Fat Mass, and
Fat Topography to Glucose Production, Gluconeogenesis,
and Glycogenolysis
AMALIA GASTALDELLI, YOSHINORI MIYAZAKI, MAURA PETTITI, EMMA BUZZIGOLI,
SRIKANTH MAHANKALI, ELE FERRANNINI, AND RALPH A. DEFRONZO
Metabolism Unit (A.G., M.P., E.B., E.F.), C.N.R. Institute of Clinical Physiology and Department of Internal Medicine,
University of Pisa School of Medicine, 56100 Pisa, Italy; and Diabetes Division (A.G., Y.M., S.M., E.F., R.A.D.), University
of Texas Health Science Center, San Antonio, Texas 78229-3900
The contribution of increased gluconeogenesis (GNG) to the
excessive rate of endogenous glucose production (EGP) in
type 2 diabetes (T2DM) is well established. However, the separate effects of obesity (total body fat), visceral adiposity, and
T2DM have not been investigated. We measured GNG (by the
2
H2O technique) and EGP (with 3-3H-glucose) after an overnight fast in 44 type 2 diabetic and 29 gender/ethnic-matched
controls. Subjects were classified as obese (body mass index 30
kg/m2 or greater) or nonobese (body mass index < 30 kg/m2);
diabetic subjects were further subdivided according to the
severity of fasting hyperglycemia [fasting plasma glucose
(FPG) < 9 mM or > 9 mM]. EGP was similar in nondiabetic
controls and T2DM with FPG less than 9 mM but was increased
in T2DM with FPG > 9 mM (P < 0.001). Within the diabetic
groups, obesity had an independent effect to further increase
I
T IS WELL established that basal endogenous (primarily
hepatic) glucose production (EGP) is increased in type 2
diabetes (T2DM) in proportion to the elevation in fasting
plasma glucose concentration (FPG) (1–3). There is controversy, however, as to whether changes in gluconeogenesis
(GNG) or glycogenolysis are responsible for the increase in
EGP. We recently demonstrated that both total EGP and the
fraction of plasma glucose derived from GNG were increased
in both obesity and diabetes and contributed to their fasting
hyperglycemia (3). Similar results have been reported by
others (4), whereas Boden et al. (5) found that only T2DM
patients with severe fasting hyperglycemia (⬎10 mm) had an
increased basal rate of EGP and GNG. However, in that study
the T2DM patients were obese [average body mass index
(BMI) 31.0 kg/m2], whereas the control group was nonobese
(BMI 26.8 kg/m2). We have previously shown that basal
GNG is increased in obese subjects with normal glucose
tolerance (3), but total EGP is normal, most likely due to
inhibition of glycogenolysis by the concomitant hyperinsuAbbreviations: BMI, Body mass index; C5, carbon 5; 2DM, type 2
diabetes; EGP, endogenous glucose production; FFA, free fatty acid;
FFM, fat-free mass; FM, fat mass; FPG, fasting plasma glucose; GNG,
gluconeogenesis; HbA1c, glycosylated hemoglobin; MRI, magnetic response imaging; Rd, glucose disappearance; T2DM, type 2 diabetes; VF,
visceral fat.
JCEM is published monthly by The Endocrine Society (http://www.
endo-society.org), the foremost professional society serving the endocrine community.
basal EGP (P < 0.01). In both nonobese diabetic groups, both
the percent GNG and gluconeogenic flux were increased, compared with nonobese nondiabetic controls. In both diabetic
groups, obesity further increased both percent GNG and gluconeogenic flux. In obese and nonobese T2DM, the increase in
gluconeogenic flux was not accompanied by a reciprocal decrease in glycogenolysis, indicating a loss of hepatic autoregulation. By multivariate analysis, gluconeogenic flux was positively correlated with percent body fat, visceral fat, and the
fasting plasma free fatty acid and glucose concentrations (all
P < 0.02). We conclude that obesity per se, and visceral fat
accumulation in particular, as well as poorly controlled diabetes are potent stimuli to augment gluconeogenic flux.
(J Clin Endocrinol Metab 89: 3914 –3921, 2004)
linemia. This hepatic autoregulation (6) appears to be lost in
T2DM subjects who, despite elevated basal plasma insulin
levels, are unable to suppress appropriately glycogenolysis
to maintain a normal basal rate of EGP (3). Thus, at present,
the separate effects of obesity and T2DM on GNG and hepatic autoregulation remain unclear.
A role for elevated plasma free fatty acid (FFA) levels has
been implicated in the accelerated rate of GNG and total EGP
in T2DM patients (7, 8). Increased FFA concentrations promote GNG in rat liver (9); similar observations have been
made in humans (10, 11). In the postabsorptive state, circulating FFAs are derived from lipolysis, and the fat cell has
been shown to be resistant to the antilipolytic effect of insulin
in both T2DM and nondiabetic obese individuals (7, 12, 13).
Because of these associations, one might expect that excess
total body fat or altered fat distribution would be related to
the accelerated rate of GNG and EGP in diabetic and obese
individuals. With regard to this, increased visceral fat (VF)
has been associated with resistance to the antilipolytic effect
of insulin in adipocytes (14, 15), reduced rate of FFA reesterification (16), and decreased insulin-stimulated glucose
disposal as measured by the euglycemic insulin clamp technique (17). It has been postulated that accelerated release of
FFAs (18, 19) and/or other adipocytokines (20) by visceral
adipocytes into the portal circulation can induce or augment
hepatic insulin resistance and enhance GNG.
The goal of this study was to examine the relationships
among the rate of GNG, hepatic insulin resistance, and fat
3914
Gastaldelli et al. • Obesity Is a Major Stimulus for Gluconeogenesis
accumulation in normal glucose tolerant and T2DM individuals. Because visceral fat is related strongly to total adiposity (21), it is mandatory to account for influence of obesity when attempting to establish an independent role for
visceral fat in glycemic control and the regulation of hepatic
glucose metabolism. In the present study, we measured in
the same individual total body fat content (by tracer), abdominal fat distribution [by magnetic response imaging
(MRI)], EGP (by 3-3H-glucose infusion), and GNG (by the
2
H2O method) in a large group of diabetic and nondiabetic
subjects spanning a wide range of adiposity.
Subjects and Methods
Subjects
Forty-four T2DM patients (16 females, 28 males; 30 Mexican-Americans, 14 Caucasians) and 29 age-matched nondiabetic control subjects
(12 females, 17 males; 16 Mexican-Americans, 13 Caucasians) participated in the study. Fifteen T2DM patients previously were studied (22).
Based on World Health Organization criteria (23), subjects with a BMI
greater than 30 kg/m2 were classified as obese. None of the diabetics had
ever been treated with insulin or thiazolidinediones. For subjects who
were taking metformin or sulfonylureas, the medication was stopped 2
wk before the study. Other than sulfonylureas or metformin, subjects
were not taking any other drugs known to affect glucose tolerance. All
control subjects had a normal 75-g oral glucose tolerance test (24). Body
weight was stable in all subjects for at least 3 months before study. All
studies were carried out at the Clinical Research Center of the University
of Texas Health Science Center at San Antonio. The study protocol was
approved by the Institutional Review Board of the University of Texas
Health Science Center at San Antonio, and informed written consent was
obtained from each subject before participation.
J Clin Endocrinol Metab, August 2004, 89(8):3914 –3921 3915
sample was obtained. The subjects were asked not to change their
habitual dietary regimen, eat the last meal between 1800 and 1900 h on
the night before study, and not eat or drink anything after the last meal.
At 2200 h on the evening before study, all subjects drank 2H2O [5 g /kg
of fat-free mass (FFM)] (Isotech, Williston, VT). A blood sample for the
determination of baseline 2H2O enrichment was taken at 0800 h on the
morning of the day before the study. Upon arrival, a polyethylene
cannula was inserted into an antecubital vein for the infusion of all test
substances. A second catheter was inserted retrogradely into an ipsilateral wrist vein on the dorsum of the hand for blood sampling, and the
hand was kept in a heated box at 65 C. At 0700 h, blood was drawn for
the determination of FPG. Then a primed (20 ␮Ci ⫻ FPG per 5 mmol/
liter) continuous (0.20 ␮Ci/min) infusion of 3-3H-glucose (DuPont NEN
Life Science Products, Boston, MA) was initiated and continued until the
end of the study. During the last 30 min of the basal equilibration period
(90 –120 min after the start of 3-3H-glucose in nondiabetic subjects and
150 –180 min for diabetic subjects), plasma samples were drawn at 5- to
10-min intervals for the determination of plasma glucose and insulin
concentration and plasma tritiated glucose-specific activity. At the end
of the basal equilibration period, a urine sample was obtained. After the
basal equilibration period, insulin was administered as a prime-continuous (40 mU/m⫺2䡠min⫺1) infusion for 120 min as previously described
(27). The plasma glucose concentration was measured every 5 min after
the start of the insulin infusion, and a variable infusion of 20% glucose
was adjusted based on the negative feedback principle to maintain the
plasma glucose level at 5 mm with a coefficient of variation less than 5%.
In diabetic subjects the plasma glucose concentration was allowed to
drop to 5 mm, at which level it was clamped. Plasma samples were
collected every 15 min from 0 to 90 min and every 5–10 min from 90 to
120 min for the determination of plasma glucose and insulin concentrations and plasma tritiated glucose-specific activity. Plasma samples
for the determination of deuterated glucose and water enrichment were
taken before starting the tritiated glucose infusion and at the end of the
basal equilibration period.
Study design
Analytical methods
Within a 5- to 7-d interval, all subjects received: 1) measurement of
lean body mass and fat mass (FM) using an iv bolus of 3H2O; 2) a
euglycemic hyperinsulinemic clamp study in combination with 3-3Hglucose to measure basal EGP and hepatic and peripheral tissue sensitivity to insulin; 3) 2H2O given on the evening before the insulin clamp
study to measure the contribution of GNG and glycogenolysis to EGP;
and 4) in a subgroup of subjects (16 controls and 28 diabetics), quantitation of sc and intraabdominal visceral fat content at L4-L5 using
nuclear MRI.
Plasma glucose concentration was determined by the glucose oxidase
method (Beckman II glucose analyzer, Fullerton, CA). Plasma insulin
concentration was measured by RIA (Diagnostic Products Corp., Los
Angeles, CA). Glycosylated hemoglobin (HbA1c) concentration was
measured by affinity chromatography (biochemical methodology,
Drower 4350; Isolab, Akron, OH). Plasma FFA concentration was measured spectrophotometrically (Wako Chemicals GmbH, Neuss, Germany). Plasma tritiated glucose-specific activity was determined on
barium hydroxide/zinc sulfate deproteinized samples (Somogyi’s
procedure).
The pattern of 2H incorporation into plasma glucose after 2H2O ingestion was determined according to the method developed by Landau
(28), as modified (22, 29). Briefly, the fraction of glucose produced via
GNG from all precursors can be quantified from the ratio of 2H enrichment of carbon 5 (C5) to that of water. Because during glycogen breakdown there is no binding of hydrogen from body water to C5 of the
glucose formed, enrichment at C5 in blood glucose vs. water reflects the
fractional contribution of GNG to total EGP, i.e. from both phosphoenolpyruvate precursors and glycerol. Precision and accuracy of C5 have
been reported previously (3). Water enrichment in the body water pool
was monitored by reacting a sample of plasma or urine with calcium
carbide (CaC2) to form acetylene (C2H2). The enrichment of acetylene
was then determined by gas chromatography-mass spectrometry by
monitoring peaks of mass 26 and 27 (30). All samples were run through
the gas chromatography-mass spectrometry processing in duplicate or
triplicate.
Lean and fat body mass
Subjects were admitted to the Clinical Research Center at 0800 h after
a 10-h overnight fast. A catheter was placed into an antecubital vein and,
after the withdrawal of a baseline blood sample, a 100-␮Ci iv bolus of
3
H2O was administered. Blood samples were drawn for the determination of plasma 3H2O radioactivity after 90, 105, and 120 min. Lean and
fat body mass were calculated as described previously (25).
Abdominal fat distribution
Intraabdominal visceral and sc fat depots were measured in a subgroup of subjects by MRI, using imaging procedures that have been
published previously (22, 26). Briefly, images were acquired on a 1.9 T
Elscint Prestige MRI system (GE Medical System, Milwaukee WI). A
sagittal localizing image was used to center transverse sections on the
line through the space between L4 and L5, and the field of view was
adjusted for body size to ensure a 2-mm pixel spacing. Signal averaging
(four signals averaged) was used to reduce the effect of motion-related
artifacts. Additionally, respiratory gating was used to combat motioninduced artifacts and reduce the blurring of fat boundaries in the anterior region of the abdomen.
Euglycemic hyperinsulinemic clamp
Subjects were admitted to the Clinical Research Center at 0700 h, after
an approximately 13-h overnight fast, and a spontaneously voided urine
Data analysis
Total body water was calculated from the mean plasma 3H2O radioactivity measured at 90, 105, and 120 min after the iv bolus of 3H2O.
Plasma 3H2O-specific activity was calculated assuming that plasma water represents 93% of total plasma volume and FFM was calculated by
dividing total body water by 0.73 (31). FM was calculated as the difference between body weight and FFM.
Subcutaneous and VF areas were quantitated by magnetic resonance
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J Clin Endocrinol Metab, August 2004, 89(8):3914 –3921
Gastaldelli et al. • Obesity Is a Major Stimulus for Gluconeogenesis
imaging at L4-L5 level as previously described (26). Briefly, images were
processed using Alice software (Perceptive Systems Inc., Boulder, CO)
to determine abdominal sc and intraabdominal visceral fat areas. The sc
fat area was analyzed by selecting the outer and inner margins of sc
adipose tissue as region of interest from the cross-sectional images and
counting the number of pixels between the outer and inner margins of
sc adipose tissue. The VF (intraabdominal) area was determined using
histograms specific to the visceral regions. The histograms were
summed over the range of pixel values designated as fat by fitting two
normal analysis distribution curves to them.
All glucose fluxes were expressed per FFM (in micromoles per minute
per kilogramffm) because this has been shown to best account for differences due to sex, obesity, and age (32). During the last 30 min of the
basal equilibration period, both plasma glucose concentration and 3-3Hglucose-specific activity were in steady-state in all subjects, and total
EGP was calculated as the ratio of the 3-3H-glucose infusion rate to the
plasma 3-3H-glucose-specific activity (mean of five determinations).
During the euglycemic insulin clamp, non-steady-state conditions prevail and total glucose rate of appearance was calculated using Steele’s
equation. EGP during the last 30 min of the insulin clamp was obtained
as the difference between rate of appearance and the exogenous glucose
infusion rate. The insulin-stimulated rate of glucose disappearance (Rd)
during the last 30 min of the insulin clamp was calculated from Steele’s
equation. The hepatic insulin resistance index was calculated as the
product of EGP ⫻ fasting plasma insulin. Over the range of insulin
concentrations from 30 to 150 pmol/liter, i.e. those that exist under
fasting conditions in T2DM and control subjects, the relationship between plasma insulin and EGP is linear (r ⫽ ⫺0.92, P ⬍ 0.0001) (7).
Data are given as the mean ⫾ se. Proportions were compared by ␹2
analysis; comparison of mean group values was performed by two-way
ANOVA, with obesity and diabetes as the factors. Partial correlation
analyses were used to estimate associations among continuous variables
in the whole data set.
Results
Anthropometric and metabolic data (Table 1)
In addition to subgrouping by obesity, individuals with
T2DM were further classified according to severity of fasting
hyperglycemia: FPG less than 9 mm (range 5.5– 8.95 mm) or
FPG 9 mm or more (range 9.1–14.4 mm). There were no
significant differences between groups with respect to sex or
ethnicity, but diabetics were older and heavier than nondiabetic subjects regardless of whether they were lean or obese.
HbA1c and known duration of diabetes were not significantly
different between obese and nonobese diabetics. Obesity, but
not diabetes, was associated with an increase in plasma triglyceride concentration and decrease in plasma high-density
lipoprotein-cholesterol concentration. The fasting plasma
FFA concentration was increased modestly in both type 2
diabetic groups, and this increase was further enhanced by
the presence of obesity (without reaching statistical significance). Fasting plasma insulin levels were significantly increased in diabetics and further increased by obesity in both
diabetic and nondiabetic groups.
With regard to body composition, FFM and VF area were
increased in association with obesity alone, whereas percent
FM and sc fat area were also independently increased in
association with diabetes.
FPG did not change significantly in nondiabetic subjects
over the 2 h of tracer glucose infusion (5.4 ⫾ 0.1 to 5.3 ⫾ 0.1
mm, P ⫽ ns). In contrast, in both diabetic groups, the fasting
plasma glucose concentration decreased over the 3-h period
of tritiated glucose infusion: from 8.7 ⫾ 0.3 to 7.4 ⫾ 0.3 mm
(by 8%) in diabetics with FPG less than 9 mm and from 12.1 ⫾
0.4 to 11.2 ⫾ 0.5 mm (by 15%) in diabetics with FPG 9 mm or
more (both P ⬍ 0.01).
Metabolic data (Table 2)
In the basal state, EGP was similar in nondiabetic controls
and diabetics with FPG less than 9 mm, whereas it was
significantly increased in diabetics with FPG 9 mm or more.
Within the diabetic groups, obesity had an independent effect to further increase basal EGP. The hepatic insulin resistance index increased progressively, and the basal glucose
clearance decreased progressively, from groups of nondiabetic control to diabetic with FPG less than 9 mm to diabetic
with FPG 9 mm or more (P ⬍ 0.01 for both the effect of obesity
and diabetes) (Fig. 1).
In the nonobese, nondiabetic control subjects, the fraction
of GNG derived from all precursors after an overnight fast
averaged 57%, and was not influenced by age, sex, or ethnicity. In both nonobese diabetic groups, the percent GNG
was increased, compared with the nonobese control group.
Across all groups, obesity had a further significant effect to
TABLE 1. Anthropometric and clinical characteristics
Control
No.
Age (yr)
HbA1c (%)
Duration of diabetes (yr)
FPG (mM)
Fasting plasma insulin (pmol/liter)
Fasting plasma FFA (mM)
Triglycerides (mg/dl)
HDL-cholesterol (mg/dl)
LDL-cholesterol (mg/dl)
Mean blood pressure (mm Hg)
BMI (kg/m2)
FFM (kg)
FM (%)
VF area (cm2)
Subcutaneous area (cm2)
T2DM-FPG (⬍9 mM)
T2DM-FPG (ⱖ9 mM)
Nonobese
Obese
Nonobese
Obese
Nonobese
Obese
21
41 ⫾ 2
5.2 ⫾ 0.1
8
49 ⫾ 3
5.2 ⫾ 0.1
14
56 ⫾ 3
7.4 ⫾ 0.3
3.0 ⫾ 1.1
7.4 ⫾ 0.3
59 ⫾ 7
0.69 ⫾ 0.06
127 ⫾ 16
39 ⫾ 3
103 ⫾ 9
105 ⫾ 3
26.8 ⫾ 0.6
53 ⫾ 2
33 ⫾ 1
121 ⫾ 9
272 ⫾ 32
7
53 ⫾ 3
7.4 ⫾ 0.4
3.6 ⫾ 1.8
7.4 ⫾ 0.4
121 ⫾ 20
0.73 ⫾ 0.08
242 ⫾ 53
34 ⫾ 2
104 ⫾ 16
105 ⫾ 12
34.4 ⫾ 0.9
55 ⫾ 4
42 ⫾ 2
184 ⫾ 36
505 ⫾ 16
14
52 ⫾ 2
9.5 ⫾ 0.3
4.0 ⫾ 1.3
11.2 ⫾ 0.5
61 ⫾ 5
0.66 ⫾ 0.03
150 ⫾ 16
41 ⫾ 4
114 ⫾ 7
101 ⫾ 2
26.5 ⫾ 0.6
52 ⫾ 2
32 ⫾ 1
118 ⫾ 7
244 ⫾ 31
9
54 ⫾ 4
8.4 ⫾ 0.5
4.3 ⫾ 1.3
11.2 ⫾ 0.5
103 ⫾ 18
0.71 ⫾ 0.06
184 ⫾ 18
30 ⫾ 1
114 ⫾ 11
106 ⫾ 5
33.9 ⫾ 0.6
54 ⫾ 4
42 ⫾ 1
181 ⫾ 40
467 ⫾ 70
5.3 ⫾ 0.1
43 ⫾ 4
0.59 ⫾ 0.03
130 ⫾ 30
42 ⫾ 3
91 ⫾ 6
100 ⫾ 3
24.4 ⫾ 0.6
50 ⫾ 2
29 ⫾ 1
97 ⫾ 12
197 ⫾ 18
5.5 ⫾ 0.1
75 ⫾ 9
0.71 ⫾ 0.05
183 ⫾ 55
38 ⫾ 5
96 ⫾ 13
97 ⫾ 6
31.6 ⫾ 0.5
56 ⫾ 3
38 ⫾ 1
158 ⫾ 32
346 ⫾ 62
HDL, High-density lipoprotein; LDL, low-density lipoprotein; ns, not significant.
a
P ⬍ 0.05 or less for effect of diabetes and bP ⬍ 0.05 or less for the effect of obesity by two-way ANOVA.
P
a
a
ns
a
a,b
ns
b
b
ns
b
a,b
b
a,b
b
a,b
Gastaldelli et al. • Obesity Is a Major Stimulus for Gluconeogenesis
J Clin Endocrinol Metab, August 2004, 89(8):3914 –3921 3917
TABLE 2. Metabolic characteristics
Control
Basal EGP (␮mol/min䡠kgffm)
Percent GNG (%)
GNG flux (␮mol/min䡠kgffm)
GLY flux (␮mol/min䡠kgffm)
Clamp plasma insulin (pmol/liter)
Clamp plasma FFA (mM)
Rd (␮mol/min䡠kgffm)
Clamp EGP (␮mol/min䡠kgffm)
a
T2DM-FPG (⬍9 mM)
T2DM-FPG (ⱖ9 mM)
Nonobese
Obese
Nonobese
Obese
Nonobese
Obese
16.3 ⫾ 0.3
56.5 ⫾ 1.6
9.1 ⫾ 0.3
7.0 ⫾ 0.3
299 ⫾ 18
0.16 ⫾ 0.02
31.7 ⫾ 3.1
4.5 ⫾ 1.0
17.7 ⫾ 0.3
66.2 ⫾ 1.8
11.7 ⫾ 0.5
6.0 ⫾ 0.3
368 ⫾ 31
0.29 ⫾ 0.04
31.8 ⫾ 4.5
4.8 ⫾ 0.8
15.5 ⫾ 0.6
64.4 ⫾ 3.0
10.0 ⫾ 0.6
5.5 ⫾ 0.5
362 ⫾ 27
0.22 ⫾ 0.02
20.3 ⫾ 2.2
5.5 ⫾ 0.9
17.1 ⫾ 0.8
72.5 ⫾ 4.6
12.2 ⫾ 0.6
4.9 ⫾ 1.0
458 ⫾ 47
0.31 ⫾ 0.03
16.1 ⫾ 0.7
7.1 ⫾ 0.7
17.7 ⫾ 0.8
63.9 ⫾ 4.3
11.3 ⫾ 0.9
6.4 ⫾ 0.8
364 ⫾ 24
0.20 ⫾ 0.01
17.3 ⫾ 0.7
8.4 ⫾ 1.0
19.2 ⫾ 0.8
69.0 ⫾ 3.7
13.3 ⫾ 0.9
5.9 ⫾ 0.6
446 ⫾ 50
0.26 ⫾ 0.02
15.9 ⫾ 1.1
8.8 ⫾ 1.4
P ⬍ 0.05 or less for effect of diabetes and
b
P
a,b
b
a,b
ns
a,b
b
a,b
a
P ⬍ 0.05 or less for the effect of obesity by two-way ANOVA; ns, not significant.
FIG. 2. Relationship between the fasting plasma glucose concentration and gluconeogenic and glycogenolytic flux in obese (dashed lines)
and nonobese (solid lines) individuals. See text for statistical analysis.
nonobese individuals. Clamp plasma FFA levels were less
suppressed in obese than in nonobese subjects, the effect of
diabetes per se not reaching statistical significance (Table 2).
Correlations
FIG. 1. Hepatic insulin resistance index (EGP ⫻ FPI) (top) and basal
glucose clearance (bottom) in nonobese (BMI ⬍ 30 kg/m2) and obese
(BMI ⱖ 30 kg/m2) individuals. Nondiabetic control subjects are shown
by the open bars. Diabetic subjects with mild or severe fasting hyperglycemia are represented by the cross-hatched and solid bars,
respectively. See text for statistical analysis.
increase the percent GNG. Gluconeogenic flux was markedly
increased by obesity and diabetes independently of one another (Fig. 2); the bivariate model predicted an increase in
flux of 2.6 ⫾ 0.6 ␮mol/min⫺1䡠kgffm⫺1 in obese subjects (P ⬍
0.0001), one of 0.7 ⫾ 0.7 ␮mol/min⫺1䡠kgffm⫺1 in diabetics
with FPG 9 mm or less (P ⫽ ns), and one of 2.2 ⫾ 0.7 in
diabetics with FPG greater than 9 mm (P ⫽ 0.001 vs. nonobese, nondiabetic controls). Glycogenolytic flux was reduced
slightly, although not significantly, in nonobese and obese
type 2 diabetics with FPG less than 9 mm, compared with the
other groups.
Insulin-mediated Rd was significantly decreased in association with both obesity and diabetes (Table 2). EGP was
suppressed by 75 ⫾ 4% in the control group, 61 ⫾ 5% in
diabetics with FPG less than 9 mm, and 55 ⫾ 4% in diabetics
with FPG 9 mm or more (P ⬍ 0.005) similarly in obese and
In the whole data set, FPG was strongly and positively
correlated with both the rates of EGP (r ⫽ 0.42 and P ⬍
0.0001) and GNG (Fig. 3), whereas there was no significant
relationship between FPG and glycogenolysis. None of the
measured glucose parameters (EGP, percent GNG, GNG
flux, glycogenolytic flux, hepatic insulin resistance index)
was significantly associated with the plasma insulin concentration. Both percent GNG and gluconeogenic flux were
strongly and positively related to the plasma FFA concentration (partial r ⫽ 0.36, P ⬍ 0.003 and partial r ⫽ 0.31, P ⫽
0.01, respectively, after adjusting for sex, age, ethnicity, and
BMI), whereas glycogenolysis was related to the plasma FFA
concentration inversely (partial r ⫽ ⫺0.31, P ⬍ 0.02). This
result explained why no correlation was observed between
plasma FFAs and EGP.
Neither EGP nor glycogenolysis was related to VF or sc fat.
In contrast, GNG, expressed as both the fractional contribution to GNG and total flux, was significantly and positively
related to VF (but not sc fat), even after adjusting for percent
FM (partial r ⫽ 0.30 and P ⬍ 0.05 for both). In a multivariate
regression model, we correlated glucose fluxes with fasting
plasma glucose, FFAs, and percent body fat, accounting also
for age, gender, and ethnicity. GNG flux was independently
related to percent body fat (partial r ⫽ 0.30, P ⫽ 0.01), fasting
3918
J Clin Endocrinol Metab, August 2004, 89(8):3914 –3921
Gastaldelli et al. • Obesity Is a Major Stimulus for Gluconeogenesis
FIG. 3. Relationship between gluconeogenic flux and FPG concentration, fasting plasma FFA concentration, percent body fat, and VF in
nondiabetic control subjects (solid circles) and diabetic subjects (open circles).
plasma glucose (partial r ⫽ 0.33, P ⫽ 0.006), and FFA concentrations (partial r ⫽ 0.29, P ⬍ 0.02); in this model, glycogenolysis was negatively related only to plasma FFA concentration. The same relationships held by replacing percent
body fat with VF area.
Discussion
Elevated basal EGP (2, 33) and impaired suppression of
EGP by physiologic hyperinsulinemia (33, 34) are characteristic features of T2DM. The increase in EGP is the major
determinant of fasting hyperglycemia, at least in poorly controlled diabetic patients (2, 33). The fraction of plasma glucose that is derived from GNG in T2DM patients has been
reported to be increased (3, 4, 35, 36) or normal (5). However,
in these previous studies, the number of subjects studied was
small, and glycemic control and degree of obesity were not
separately taken into account. Although Boden et al. (5)
found a difference in GNG flux between mildly and severely
hyperglycemic patients, the diabetic and control subjects
were not matched for obesity (seven controls with BMI of
26.8 kg/m2 vs. 14 T2DM with FPG ⬍ 10 mm with BMI of 29.2
kg/m2 and 13 T2DM with FPG ⬎ 10 mm with BMI of 32.9
kg/m2). Mismatch for adiposity is important because we
have shown an independent effect of obesity on GNG when
expressed both as percent contribution as well as total flux
in normoglycemic subjects (3) and an effect of VF accumulation in T2DM subjects (22).
Whereas the preponderance of evidence supports enhanced GNG as the cause of increased basal EGP in human
T2DM (3, 4), there is some evidence to suggest that glycogenolysis also may be increased (36, 37). Most importantly,
the separate impact of factors such as degree of obesity and
fat distribution on GNG has not been examined. In the
present study, we found that the fraction of EGP that is
Gastaldelli et al. • Obesity Is a Major Stimulus for Gluconeogenesis
derived from GNG was increased in obese patients at each
degree of fasting hyperglycemia, whereas glycogenolytic
flux tended to be decreased (although not significantly) in
T2DM patients with mild fasting hyperglycemia and was
unchanged in severely hyperglycemic diabetic subjects (Fig.
2). It is especially noteworthy that in our data a difference in
BMI of only approximately 4 kg/m2 was associated with an
increment in GNG flux similar to that associated with an
increase in FPG of 6 mmol/liter. These results emphasize the
quantitative effect of obesity to augment GNG flux, namely
the impact of hyperglycemia, and the need to closely match
diabetic and control subjects for adiposity when evaluating
GNG. In addition to fasting plasma glucose and FFA levels,
increased GNG flux was simultaneously related to percent
body fat and VF area (independently of age, gender, BMI,
and ethnicity).
In nondiabetic subjects an increase in GNG flux is counterbalanced by a reduction in glycogenolysis and total EGP
remains unchanged (6). In mildly diabetic subjects, there was
a tendency (although not significant) for glycogenolysis to
decrease as GNG increased (Fig. 2). However, in severely
diabetic individuals, hepatic autoregulation clearly was lost
and the marked increase in GNG flux was not associated with
any compensatory decrease in glycogenolysis. Thus, these
findings support the results of Boden et al. (10), who failed
to observe the normal compensatory glycogenolytic response to stimulation (with lipid infusion) or inhibition (with
nicotinic acid) of GNG in diabetic subjects.
The hepatic insulin resistance index was influenced by
both obesity and diabetes (i.e. severity of fasting hyperglycemia). Thus, for any level of glycemia, obesity approximately doubled the hepatic insulin resistance index,
whereas, for any given level of obesity, diabetes increased the
hepatic insulin resistance index by approximately 50% (Fig.
1). It is noteworthy that in both nonobese and obese diabetic
individuals with severe fasting hyperglycemia (FPG 11.2 ⫾
0.5 mmol/liter), the marked increase in both EGP and FPG,
compared with the diabetic group with mild fasting hyperglycemia (FPG 7.4 ⫾ 0.3 mmol/liter and normal basal EGP),
was associated with a failure of the fasting plasma insulin
concentration to increase further to offset the worsening hepatic insulin resistance (Table 1). Moreover, during the clamp
EGP was progressively less suppressed moving from control
to diabetics with FPG less than 9 mm to diabetics with FPG
9 mm or greater (P ⬍ 0.005) (Table 2). Consistent with previous results from our laboratory (33), these observations
stress the role that ␤-cell incompetence plays in determining
when EGP begins to increase in absolute terms and how the
liver is sensitive to the effect of insulin.
In both nonobese and obese type 2 diabetic subjects, progressive increases in FPG were associated with a progressive
decline in the basal glucose clearance (Fig. 1). This relation
was observed, even after changes in the fasting plasma insulin concentration were taken into account. Likewise, Rd
was reciprocally related to both obesity and diabetes. These
observations confirm the inhibitory effect of hyperglycemia
and obesity on glucose use and are consistent with previous
publications from several laboratories (1, 39, 40).
J Clin Endocrinol Metab, August 2004, 89(8):3914 –3921 3919
Fat distribution and GNG
A significant body of evidence has accumulated to indicate
that visceral, as contrasted with sc, adiposity is associated
with hepatic and peripheral insulin resistance (41). Several
hypotheses have been proposed to explain this association.
One hypothesis proposes that increased FFA flux into the
portal vein renders the liver resistant to the restraining effect
of insulin on EGP (42). This hypothesis is based on the fact
that visceral adipocytes are more resistant to the antilipolytic
effect of insulin (18) than are sc fat cells. Several lines of
evidence (10, 18, 20, 43, 44) support the concept that FFAs are
an important regulator of EGP. In vitro studies have demonstrated that plasma FFAs increase the activity of pyruvate
carboxylase and phosphoenolpyruvate carboxylase, the ratelimiting enzymes for GNG (9, 45, 46), and augment the activity of glucose-6-phosphatase, the enzyme that ultimately
controls the release of glucose by the liver (47). In contrast,
a decrease in plasma FFAs has been shown to inhibit glucose6-phosphatase, leading to a reduction in GNG, an effect also
seen in man (48). In normal subjects, an increase in plasma
FFA concentration stimulates GNG (10, 49, 50), whereas a
decrease reduces it (10, 49, 50). With regard to the latter, it has
been shown that a significant portion of the suppressive
effect of insulin on hepatic glucose production is mediated
via inhibition of lipolysis and a reduction in circulating FFA
concentrations (44, 51, 52). Moreover, FFA infusion in normal
humans under conditions that simulate the diabetic state (43)
and in obese insulin-resistant subjects (53) enhances EGP,
most likely secondarily to stimulation of GNG.
In the present study, we found a strong linear relationship
between GNG and the plasma FFA concentration. A strong
correlation also was found between VF and both percent
GNG and absolute gluconeogenic flux. These results are
consistent with the possibility that increased release of FFAs
by VF into the portal circulation may contribute to the stimulation of hepatic GNG. However, whether this stimulation
results in overproduction of glucose by the liver (VF was not
correlated with EGP) depends on the concomitant adjustment (or lack thereof) of the glycogenolytic rate. Because
GNG is less sensitive to insulin inhibition than is glycogenolysis (34, 54), the increased fasting plasma insulin concentration in mildly hyperglycemic diabetic patients (Table 2)
tends to down-regulate glycogenolysis, thereby maintaining
EGP within normal limits. In the more hyperglycemic subjects, the ambient plasma insulin concentration is insufficient
to restrain EGP, which consequently rises to levels that are
elevated in absolute terms (Table 2). Thus, the combination
of visceral adipose mass/visceral lipolytic activity, ␤-cell
incompetence, and insulin resistance could be viewed as a
regulatory axis that controls EGP by independently regulating the individual components of EGP, GNG and glycogenolysis. The contribution of VF cell-derived adipocytokines to
this visceral-portal-hepatic axis remains to be defined. This
is in agreement with a recent paper (55), which observed that
an increase in FM, primarily in the abdominal area, was
associated with hepatic insulin resistance and inhibition of
suppression of EGP during the clamp.
In conclusion, in diabetic subjects obesity per se and VF
accumulation in particular induce hepatic insulin resistance
3920
J Clin Endocrinol Metab, August 2004, 89(8):3914 –3921
and are potent stimuli to augment gluconeogenic flux. Poorly
controlled diabetes and abdominal obesity are independent
determinants of severe fasting hyperglycemia.
Gastaldelli et al. • Obesity Is a Major Stimulus for Gluconeogenesis
18.
19.
Acknowledgments
The authors thank Magda Ortiz, Dianne Frantz, Socorro Mejorado,
Janet Shapiro, John Kincaid, John King, Norma Diaz, and Patricia Wolf
for their assistance in performing the insulin clamp studies and S. Frascerra, Ph.D.; S. Baldi, Ph.D.; D. Ciociaro; and N. Pecori for their technical
assistance in the measurement of GNG.
Received December 16, 2003. Accepted May 6, 2004.
Address all correspondence and requests for reprints to: Ralph A.
DeFronzo, M.D., Diabetes Division, University of Texas Health Science
Center, 7703 Floyd Curl Drive MS 7886, San Antonio, Texas 78229-3900.
E-mail: [email protected].
This work was supported by National Institutes of Health Grant
DK-24092, General Clinical Research Center Grant M01-RR-01346, a
Veterans Affairs Merit Award, and funds from the Veterans Administration Medical Research Service.
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