Download Leptin is influenced both by predisposition to obesity and diet

International Journal of Obesity (2000) 24, 450±459
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Leptin is in¯uenced both by predisposition to
obesity and diet composition
A Raben1* and A Astrup1
1
Research Department of Human Nutrition, Centre for Food Research, The Royal Veterinary and Agricultural University, Frederiksberg,
Denmark
OBJECTIVE: (1) To investigate whether plasma leptin concentrations differ between subjects with and without the
genetic predisposistion to obesity, and (2) to investigate the effect of dietary manipulations on plasma leptin in these
subjects.
DESIGN: Fasting and postprandial plasma leptin concentrations were measured before and after 14 days' ad libitum
intake of a fat-rich (FAT), starch-rich (STARCH) or sucrose-rich (SUCROSE) diet. On day 15 ad libitum breakfast and
lunch were given and blood sampled regularly until 6 p.m.
SUBJECTS: Eight normal-weight, post-obese women and 10 matched controls (body mass index, 23.5 0.5 and
22.9 0.3 kg=m2).
MEASUREMENTS: Leptin, glucose, insulin, appetite ratings, dietary intake, body weight and composition.
RESULTS: Fasting leptin concentration on day 1 or 15 did not differ between post-obese and controls. However, after
meal intake leptin increased in post-obese compared with controls on all three diets. In both groups fasting and
postprandial leptin concentrations were greater after SUCROSE compared with FAT and STARCH.
CONCLUSION: A larger postprandial leptin concentration was observed in post-obese subjects than in controls. This
may be related to greater insulin sensitivity in adipose tissue in the post-obese. Furthermore, increased leptin
concentrations were found after a sucrose-rich diet in both groups, possibly related to larger postprandial insulin
peaks on this diet. Both contentions should, however, be validated by further studies.
International Journal of Obesity (2000) 24, 450±459
Keywords: starch; fat; sucrose; post-obese; glucose; insulin; appetite
Introduction
The OB-protein leptin, secreted from adipose tissue
and ®rst described in 1994,1 may be important in the
development of obesity by in¯uencing both food
intake and energy expenditure. Thus, leptin has been
found to decrease food intake and increase energy
expenditure both in ob=ob mice2 ± 4 and in non-obese
mice.2 In humans, leptin has repeatedly been shown to
be positively associated with body weight, body mass
index and fat mass.5 ± 8 Also, in humans, homozygous
mutation in the genes encoding leptin or the leptin
receptor is associated with early-onset obesity, along
with no pubertal development and other endocrine
de®ciencies.9 Two hypotheses have resulted from
these observations. Either a failure to produce leptin
in the adipose tissue or a resistance to its action in the
central nervous system may result in increased body
weight and obesity. The latter hypothesis has, however, recently been challenged by Arch et al.10 They
stated that, if leptin resistance is a cause rather than a
consequence of obesity, leptin concentrations would
*Correspondence: A Raben, Research Department of Human
Nutrition, Centre for Food Research, The Royal Veterinary and
Agricultural University, 30 Rolighedsvej, DK-1958 Frederiksberg
C, Denmark.
E-mail: [email protected]
Received 29 March 1999; revised 6 September 1999; accepted
4 November 1999
be expected to be raised in subjects who are prone to
obesity but who have slimmed.
Whether low fasting leptin concentrations predispose to obesity has already been investigated in
prospective studies. In one study low leptin concentrations predicted weight gain in 36 very obese,
middle-aged Pima Indians.11 However, in another
study on 180 moderately obese, non-diabetic Mexicans studied after 3.25 y no such connection was
found.8 Likewise, Lindroos et al found that basal,
fasting leptin concentrations were not predictive of 4 y
weight changes in 49 severely obese women with a
familial predisposition to obesity.12 Since the obese
state is in itself a confounding factor when trying to
disclose the reasons for obesity, studies of leptin
concentrations in normal-weight subjects with the
genetic predisposition to obesity (ie pre- or postobese) are, however, more interesting. Furthermore,
fasting leptin concentrations do not represent the
diurnal pattern. Thus differences in leptin concentrations may occur at other times during the day or night.
With regard to food intake, leptin in humans has
been found to increase during acute and chronic
overfeeding,13 and to decrease during fasting and
longer-term energy restriction.14,15 Studies on the
impact of changes in dietary composition (1 week ±
4 months), when energy balance and body weight is
maintained, have in general shown no effect on
fasting leptin of major changes in dietary composition
Leptin, predisposition to obesity and diet
A Raben and A Astrup
(fat content ˆ 14 ± 60 energy%).16 ± 18 One of these
studies found that 8 months' ad libitum low-fat diet
decreased leptin only in those who lost body weight,
indicating that the diet per se had no effect.18 The
decrease in leptin also paralleled a decrease in body
fat, resting energy expenditure and fasting insulin.18
Studies on the in¯uence of acute meal intake on
postprandial leptin show more discordant results.
Thus, some found an effect of meal intake on leptin
concentrations,19 ± 22 while others did not.5,17,23 ± 27
These discrepancies may relate to differences in the
duration of the postprandial measurement period (1 ±
10 h), different types of test meals or types of subjects
used. Especially, a measurement period of at least 8 h
seems to be necessary to discover any diet-induced
differences in plasma leptin concentrations.
The purpose of the present study was two-fold: (1)
to compare fasting and postprandial leptin concentrations in normal-weight, post-obese with never-obese
subjects, (2) to investigate the impact of a fat-rich, a
starch-rich=low-fat (`recommended') or a sucroserich=low-fat diet, on fasting and 8-h postprandial
leptin concentrations after 14 days' ad libitum intake
in the two study groups.
Methods
Subjects
Eighteen healthy, normal-weight women, eight postobese (PO) and 10 controls (C), matched on a groupbasis for age, weight, height, percentage fat mass, and
percentage fat-free mass participated in the study
(Table 1). The post-obese women had a family history
of obesity (at least one obese parent or sibling), had
been more than 10% overweight (average s.e.m.
ˆ 38 9%), and had been weight-stable for at least
2 months. None had undergone surgical operations to
become normal-weight. The study was approved by
the Municipal Ethical Committee of Copenhagen and
Frederiksberg as in accordance with the Helsinki II
declaration. All subjects gave written consent after the
experimental procedure had been explained to them.
Table 1 Subjects characteristicsa
Age (y)
Height (m)
Weight (kg)
Body mass index (kg=m2)
Maximal weight (kg)
Previous overweightb (%)
Fat mass (%)
Fat-free mass (%)
Post-obese
(n ˆ 8 ,)
Controls
(n ˆ10 ,)
40 4
1.67 1.3
65.4 1.2
23.5 0.5
89 4
38 9
28.7 1.1
71.3 1.1
38 3
1.65 1.3
62.1 1.3
22.9 0.3
63 1c
2 6
29.2 0.7
70.8 0.7
Data are means s.e.m.
a
Measured on day 1 of the ®rst of three ad libitum diets. bSee Ref.
46. cPost-obese vs controls, P < 0.05 by unpaired t-test.
451
Experimental design
The experimental design has been described in detail
previously.28 In brief, each subject completed three
14 day ad libitum dietary periods, a sucrose-rich
(SUCROSE), a starch-rich (STARCH) and a fat-rich
(FAT) period. The order of the periods differed, but
subjects in the post-obese and control group were
following similar diet orders. Each subject was measured at the same time in her menstrual cycle. Before
each experimental period subjects were given a standardized, weight-maintenance diet for 3 days (days -2,
-1 and 0). After the standard diet, the experimental
diets were supplied in ad libitum amounts (see below)
to be consumed at home for 14 days. Days 0 and 14
were spent in our respiration chambers. In the morning on day 15 blood samples were taken in the fasted
state and postprandially after breakfast and lunch until
6 p.m. Body weight and composition were measured
in the fasting state on day 1 and 15. At least 2 weeks
and no more than 6 weeks separated the dietary
periods. The subjects were instructed not to change
their physical activity pattern during or between the
three experimental diets.
Data for 20 subjects on ad libitum energy intake,
body weight and composition, 24 h energy expenditure, substrate oxidations, appetite sensations and
habitual food intake, and for 18 subjects (eight PO
and 10 C) on plasma catecholamines, blood lipids
and coagulation factors, have been published
separately.28,29
Diets
The standard weight-maintenance diet given before
each dietary period contributed 13 energy-percentage
(E%) protein, 37 E% fat, 50 E% carbohydrate (9 E%
sucrose), 2.9 g=MJ dietary ®ber and had a P=S-ratio
of 0.4. The diet was prepared according to each
subject individual energy needs adjusted to the nearest
0.5 MJ.30
The average macronutrient compositions of the 14
day ad libitum diets as follows: SUCROSE Ð 59 E%
carbohydrate (23 E% sucrose), 28 E% fat and 13 E%
protein; FAT Ð 46 E% fat, 41 E% carbohydrate (2 E%
sucrose) and 13 E% protein; STARCH Ð 59 E%
carbohydrate (2 E% sucrose), 28 E% fat and 13 E%
protein. Dietary ®ber amounted to a total of 22, 32 and
20 g=d as on FAT, STARCH and SUCROSE, respectively. The ratio between polyunsaturated and saturated fatty acids (P=S-ratio) was 0.4 on the FAT diet
and 0.7 on both the SUCROSE and STARCH diets.
The amount of food given for breakfast and lunch
on day 15 was similar to the ad libitum amounts
consumed on day 14 in the chamber (Table 2). Coffee,
tea and water consumption as well as smoking (two
PO and one C) were allowed, but the amount and time
was copied from the ®rst dietary period.
The computer database of foods from the National
Food Agency of Denmark (Dankost 2.0) was used in
International Journal of Obesity
Leptin, predisposition to obesity and diet
A Raben and A Astrup
452
Table 2 Ad libitum energy intake on day 15
P-value
ANOVA
Breakfast
Energy (kJ)
Lunch
Energy (kJ)
Breakfast ‡ lunch
Energy (kJ)
Fat
Starch
Sucrose
dg
Diet
Group
PO
C
2816 324
2371 192
2141 223A
2307 206
3006 370B
2636 265
0.28
0.03
0.46
PO
C
3948 478
3544 310
3022 356
3148 278
4216 400
3188 176
0.07
0.14
0.22
PO
C
6764 730A
5915 234
5163 519B
5456 326
7222 658A
5823 364
0.07
0.008
0.24
Data are means s.e.m. PO: post-obese (n ˆ 8). C: control (n ˆ 10). d g ˆ diet grop interaction. Results in the
same row with different superscript are signi®cantly different (per diet, n ˆ 18; P < 0.05).
the calculations of energy and nutrient intake of the
diets.31
Anthropometric measurements
Body weight was measured Ð blinded for the subjects Ð in the morning of days 1 and 15 after 10 h of
fasting and after voiding. The same digital scale was
used each time (Seca model 707, Copenhagen). Body
composition was subsequently estimated by electrical
bioimpedance using an Animeter (HTS-Engineering
Inc., Odense, Denmark). Fat mass (FM) and fat-free
mass (FFM) were calculated as previously reported.32.
Blood sampling
On day 15 the subjects left the respiration chamber at
9.00 a.m. After voiding and weighing the subjects lay
on a bed in the supine position and a Ven¯on catheter
(Viggo, Gothenborg, Sweden) was inserted into an
antecubital arm vein. After 10 min rest a fasting blood
sample was taken. Breakfast was eaten at 10.00 a.m.
and lunch at 2.00 p.m. Blood samples were taken after
15, 30, 60, 120 and 240 min from initiation of breakfast and lunch. The subjects rested in the supine
position for 10 min before each blood sample.
During the day the subjects could sit, walk quietly
or go to the toilet. The type of activity during the day
of the ®rst dietary period was noted and repeated
thereafter.
Appetite sensations
Every hour from 9 a.m. (fasting) until 5 p.m. subjects
recorded their sensations of hunger, fullness, desire to
eat and prospective food consumption on 10 cm visual
analog scales (VAS) with words anchored at each end,
expressing the most positive (eg good, pleasant) or the
most negative rating (eg bad, unpleasant).33 This was
done on day 14, while in the respiratory chambers.
However, since food and ¯uid intake was repeated on
day 15, just postponed by 1 h, appetite data (n ˆ 18)
could be compared with blood data (n ˆ 18).
International Journal of Obesity
Laboratory analyses
Blood was sampled without stasis through an indwelling antecubital cannula. Blood for determination of
plasma leptin was sampled in plain tubes, centrifuged
at 3000 G and 4 C and stored at ÿ20 C. Leptin was
analyzed by Radioimmunoassay using a DRG-Human
leptin RIA-kit RIA 1624 from DRG Instruments
GmbH, Marburg, Germany. The intraserial coef®cient
of variation (CV) was 4.4% and the interserial CV
was 4.2%. Blood for glucose analyses was sampled
in EDTA=K3=sodium-¯uoride tubes, centrifuged at
1500 g and 20 C and stored at ÿ20 C. Glucose was
determined on a Cobas Mira (Roche Diagnostic
System), using an end-point analysis with MPR3
Gluco-quant R glucose=HK kinetic 1442457 (Boehringer and Mannheim GmbH Diagnostica) and the
hexokinase=G6P-DH method. Blood for insulin was
sampled in plain tubes, centrifuged at 3000 g for 10
min at 4 C and stored at ÿ20 C. Serum insulin was
determined as a non-competitive sandwich assay with
a DAKO insulin kit, code no. K6219 (DAKO A=S,
Denmark).
Statistical analyses
All results are given as means s.e.m. Initial group
characteristics were compared by an unpaired t-test
(Table 1). The areas under the postprandial curves
were calculated separately for each subject as the
difference between the integrated area of the response
curve and the rectangular area determined by the basal
values. Differences in fasting concentrations and areas
under the curve (AUC) between the three diets and
two groups were tested by parametric analysis of
variance (ANOVA) using the GLM procedure in
SAS. Factors were group, diet, and group diet
using subject (group) as error term for group effects.
In case of signi®cance, a t-test on least squares means
(for unbalanced designs) was used to test for differences between groups or diets. Differences in the
postprandial responses were tested by ANOVA
using GLM in SAS and diet time group,
diet group, time group, diet time, time, diet
Leptin, predisposition to obesity and diet
A Raben and A Astrup
and group as factors and subject (group) as error term
for all group effects.
Simple correlation analyses were performed within
each diet (n ˆ 18). However, in order to explain the
observed differences in leptin between diets, two
types of analyses were performed. One was simple
linear regression analyses using means of groups and
diets (n ˆ 6). The other was an adjustment of leptin for
differences in the relevant parameter (eg body
weight). This was done by including the adjustment
parameter as a factor (covariate) in the ANOVA.
The signi®cance level was set at P < 0.05. Statgraphics Software version 4.2 (Graphic Software
Systems Inc., Rockville, MD) and the Statistical
Analysis Package version 6.12 for Windows (SAS
Institute, Cary, NC) were used in the statistical
calculations.
Results
Energy intake
The 14 day ad libitum energy intake (EI) was lowest
on STARCH (9.1 0.4 MJ=day) compared with both
SUCROSE (10.3 0.5 MJ=day) and FAT (10.3 0.4
MJ=day) (P < 0.05). Compared with the control
group, PO consumed signi®cantly more energy on
FAT (11.0 0.7 vs 9.7 0.4 MJ=day, P < 0.001) and
SUCROSE (11.4 0.7) vs 9.5 0.5 MJ=day,
P < 0.0001).
On average both groups consumed more energy on
SUCROSE than STARCH at breakfast, whereas there
were no differences at lunch (Table 2). Total energy
intake for both breakfast and lunch was signi®cantly
lower for STARCH compared with FAT and
SUCROSE (P < 0.01). There were no group differences over the day (Table 2).
453
Leptin
Fasting leptin concentrations on days 1 and 15 and
changes from day 1 to 15 were similar in PO and C
(Table 3). However, in both groups fasting leptin on
day 15 and change in fasting leptin (day 15ÿday 1)
were higher after SUCROSE compared with the other
two diets (diet effect, P < 0.01). After meal intake
leptin values initially dropped, but then increased
steadily in PO compared with a minor increase in C
(group time effect, P < 0.0001; Figure 1). The differences were most pronounced after lunch and were
independent on the type of diet. Total areas under the
curve (AUC) were higher after SUCROSE than
STARCH, but not different between groups (Figure
1). When data were expressed as areas under the
curves above baseline (d-AUC's), the d-AUC's were
larger in PO on all three diets and only negative values
were observed for C (data not shown). There were no
diet differences in the d-AUCs, indicating that the
higher postprandial concentration and AUC on
SUCROSE were due to the higher fasting concentration on this diet compared with FAT and STARCH.
Glucose
Fasting glucose on days 1 and 15 and the changes
from day 1 to day 15 were not different between
groups or diets (Table 3). After meal intake on day 15,
however, there were signi®cant differences in the
glucose response between both diets and groups
Table 3 Fasting % plasma concentrations in post-obese and controls before (day 1) and after (day 15) 14 days' ad
libitum intake of a diet rich in fat, starch or sucrose
P-value
ANOVA
Fat
Before (day1)
Leptin (ng=ml)
Glucose (mmol=l)
Insulin (pmol=l)
After (day15)
Leptin (ng=ml)
Glucose (mmol=l)
Insulin (pmol=l)
Change (day15ÿday1)
Leptin (mg=ml)
Glucose (mmol=l)
Insulin (pmol=l)
Starch
Sucrose
PO
C
PO
C
PO
C
8.8 1.6
10.9 1.1
4.73 0.10
4.87 0.13
32 7
34 8
9.9 2.0
10.4 0.9
4.77 0.10
4.82 0.11
32 8
33 7
8.7 1.5
9.8 0.8
4.55 0.08
4.85 0.11
33 9
32 6
PO
C
PO
C
PO
C
9.7 2.0
10.3 1.5
4.64 0.17
4.76 0.14
39 7
51 6
9.5 1.8
9.3 0.7
4.58 0.12
4.72 0.10
45 6
56 5
11.1 2.2
11.7 1.6
4.46 0.13
4.80 0.10
42 6
64 9
PO
C
PO
C
PO
C
0.9 0.9a
ÿ0.5 1.0
ÿ0.09 0.11
ÿ0.11 0.08
6 6
7 9
ÿ0.4 0.6a
ÿ1.1 0.7
ÿ0.19 0.08
0.10 0.06
13 11
23 8
2.4 1.0b
1.9 1.2
ÿ0.09 0.08
ÿ0.05 0.09
9 11
32 10
dg
Diet
Group
0.35
0.29
0.50
0.07
0.15
0.28
0.89
0.99
0.97
0.73
0.008
0.88
0.18
0.59
0.23
0.61
0.29
0.06
0.78
0.0007
0.43
0.81
0.69
0.61
0.55
0.34
0.22
Data are means s.e.m. PO: eight post-obese women. C: 10 matched control women. d g ˆ diet group
interaction. Results in the same row with different superscripts are different, P < 0.05 (n ˆ 18).
International Journal of Obesity
Leptin, predisposition to obesity and diet
A Raben and A Astrup
454
Figure 1 Mean plasma leptin concentrations in eight postobese (PO) and 10 controls (C) after 14 days' ad libitum intake of
a fat-rich (FAT), a starch-rich (STARCH) and a sucrose-rich
(SUCROSE) diet. Brkf. ˆ breakfast. Signi®cant by ANOVA,
P < 0.05: group time, diet (SUCROSE > STARCH) and time.
Bottom panel: mean ( s.e.m.) total areas under the curves
(AUC). Diet effect, P < 0.01. Different letter: diets differ, P < 0.01.
(Figure 2). SUCROSE resulted in the lowest AUC
compared with STARCH and FAT and the post-obese
subjects had a lower AUC on all three diets compared
with controls (Figure 2).
International Journal of Obesity
Figure 2 Mean plasma glucose concentrations in eight postobese (PO) and 10 controls (C) after 14 days' ad libitum intake of
a fat-rich (FAT), a starch-rich (STARCH) and a sucrose-rich
(SUCROSE) diet. Brkf. ˆ breakfast. Signi®cant by ANOVA,
P < 0.01: group time, diet time, group (PO < C, all diets), diet
(SUCROSE < STARCH and FAT) and time. Bottom panel: mean
( s.e.m.) total areas under the curves (AUC). Diet effect,
P < 0.0001. Group effect, P < 0.01; ***P < 0.0001 for PO vs C.
Different letters: diets differ, P < 0.0001.
Insulin
Fasting insulin concentration were not signi®cantly
different between diets or groups, although the group
Leptin, predisposition to obesity and diet
A Raben and A Astrup
455
effect was near-signi®cant on day 15 (P ˆ 0.058;
Table 3). There was a signi®cant time diet interaction in postprandial insulin responses with a steeper
rise in insulin after SUCROSE, a slower response
after STARCH, and a ¯atter response after FAT
(Figure 3). A lower AUC was seen in PO compared
with C on all three diets (Figure 3).
Appetite sensations
Comparison of appetite ratings by ANOVA showed
a time group interaction for hunger (P < 0.01).
Furthermore, a group effect was observed (P < 0.05)
with the post-obese subjects feeling more satis®ed
(Figure 4) and less hungry, and having less desire to
eat (prospective consumption) than the controls on all
three diets (P < 0.01). A diet effect was observed for
prospective consumption (P < 0.05), with FAT giving
higher ratings (more desire to eat) than SUCROSE or
STARCH (P < 0.05). The mean ratings (averaged
over the day) showed similar signi®cance levels as
the ANOVAs concerning group and diet effects.
Adjustment of mean ratings for total energy intake
during the day did not change these ®ndings.
Body weight and composition
There were no signi®cant differences between the two
groups in 14 day changes of body weight or composition (Table 4). However, a diet effect was observed
for changes in body weight and fat-free mass
(P < 0.05; Table 4). Thus, body weight was reduced
after STARCH compared with SUCROSE, and fatfree mass was increased after SUCROSE compared
with FAT or STARCH (Table 4). These ®ndings have
been discussed previously.28
Leptin correlations and adjustments
Simple correlation analyses within each diet (n ˆ 18)
showed a positive correlation between change in
fasting leptin (day 15ÿday 1) and change in body
weight on FAT (r ˆ 0.52, P < 0.05) and change in fat
mass (kg) on FAT and SUCROSE (r ˆ 0.47 ± 0.58,
P < 0.05). A positive correlation between fasting
leptin and hunger (day 15) was found on STARCH
(r ˆ 0.53, P < 0.05).
Correlation analyses using the six means of diets
and groups resulted in no signi®cant correlations
between fasting leptin on one hand and glucose,
insulin, appetite scores or noradrenaline concentration
on the other hand. However, the AUC's for leptin
correlated negatively with the AUC's for glucose
(r ˆ ÿ0.84, P < 0.05), respectively. Furthermore,
AUC for leptin correlated positively with AUC for
noradrenaline (r ˆ 0.87, P < 0.05).28
Adjustment analyses, where all 54 data were
included, resulted in the following. The observed
diet differences in fasting leptin from day 1 to 15
did not change signi®cantly after adjusting for
changes in body weight, fat mass, 14 day energy,
Figure 3 Mean plasma insulin concentrations in eight postobese (PO) and 10 controls (C) after 14 days' ad libitum intake of
a fat-rich (FAT), a starch-rich (STARCH) and a sucrose-rich
(SUCROSE) diet. Brkf. ˆ breakfast. Signi®cant by ANOVA,
P < 0.05: time diet, group (PO < C, all diets) and time. Bottom
panel: mean ( s.e.m.) area under the curves (AUC). Group
effect, P < 0.05; *P < 0.05; **P < 0.01 PO vs C.
carbohydrate or fat intake. However, after adjusting
for 14-day sucrose intake, the diet effect became nonsigni®cant (P ˆ 0.36). The diet effect for the areas
under the curve (AUC) was still signi®cant after
International Journal of Obesity
Leptin, predisposition to obesity and diet
A Raben and A Astrup
456
d-AUC glucose, d-AUC insulin or d-AUC noradrenaline or the four factors together.
Discussion
Figure 4 Mean satiety scores for eight post-obese (PO) and 10
controls (C) after 14 days' ad libitum intake of a fat-rich (FAT), a
starch-rich (STARCH) and a sucrose-rich (SUCROSE) diet. Brkf. ˆ
breakfast. Signi®cant by ANOVA, P < 0.05: group (PO < C, all
diets) and time. Bottom panels: mean ratings ( s.e.m.) from
9 a.m. to 5 p.m. Group effect, P < 0.05, ***P < 0.001; **P < 0.01
for PO vs C.
adjusting for energy intake on day 15, AUC glucose,
AUC insulin or AUC noradrenaline or all four factors
together. The group effect for d-AUC leptin did not
change after adjusting for energy intake on day 15,
International Journal of Obesity
Two interesting results were obtained from the present
study. The ®rst was the postprandial increase in leptin
levels observed in post-obese, normal-weight subjects,
but not in matched controls. The second was an
increased fasting and total area under the curve for
leptin after 14 days' ad libitum intake of a sucroserich=low-fat diet compared with a starch-rich=low-fat
or a fat-rich diet.
The increase in postprandial leptin concentration in
our post-obese group was a new ®nding not previously
described in the literature. That it was found consistently on all three diets and not abolished by adjusting
for differences in energy intake, increases the validity
of the observations. It could indicate that these postobese subjects are resistant to leptin and that leptin's
normal feedback mechanism does not work optimally
in this group. Findings from a recent study on cerebral
blood ¯ow in obese support this. Here, a depressed
neural activity of hypothalamus in 11 obese women
was observed during exposure to food, although leptin
concentrations were high at the same time.34 However, it could also be due to an increased insulin
sensitivity, especially in the adipose tissue, as has
been reported before in similar subjects.35 This is
further supported by the previously observed differences in fat metabolism in post-obese subjects. Thus,
after a fat-rich meal a smaller increase in plasma
triglycerides and a greater suppression of plasma
non-esteri®ed fatty acids and fat oxidation was
reported, indicating both depressed lipolysis and
greater lipid storage after the meal.32 It would also
correspond to data from Pima Indians showing that
increased insulin sensitivity was a risk factor for
weight gain.36 The present ®ndings of lower glucose
and insulin concentration in PO than in C on all three
diets, despite similar or higher energy intake in PO,
also points towards increased insulin sensitivity in PO.
Since prolonged hyperinsulinaemia has been found to
stimulate leptin release,37 increased insulin sensitivity
could have caused the higher postprandial leptin
values in the post-obese subjects.
The fact that we found no differences between PO
and C in fasting leptin concentration could have lead
to the assumption that leptin is not a factor predictive
of weight gain in these subjects. Two previous studies
with post-obese subjects have found similar
results.38,39 Thus, no relation between initial fasting
leptin and weight change was found in a 4 y prospective study on 14 post-obese, postmenopausal
women.39 Similarly, a study in which the post-obese
state was obtained by gastroplasty reported no differences between leptin concentration in eight post-obese
Leptin, predisposition to obesity and diet
A Raben and A Astrup
Table 4 Changes % in body weight, fat mass and fat-free mass in post-obese and controls after 14 days' ad libitum
intake of a diet rich in fat, starch of sucrose
457
P-value
ANOVA
Fat
Change in body weight (kg)
Change in fat mass (kg)
Change in fat-free mass
PO
C
PO
C
PO
C
ÿ0.6 0.7
ÿ0.2 0.3
ÿ0.2 0.3
ÿ0.2 0.3
ÿ0.3 0.4A
ÿ0.1 0.2
Starch
Sucrose
A
ÿ0.7 0.6
ÿ0.7 0.2
ÿ0.5 0.3
ÿ0.3 0.2
ÿ0.3 0.5A
ÿ0.4 0.2
B
0.5 0.5
ÿ0.1 0.2
0.1 0.3
ÿ0.3 0.2
0.4 0.3B
0.1 0.2
dg
Diet
Group
0.31
0.02
0.87
0.54
0.49
0.88
0.50
0.03
0.93
Data are means s.e.m. PO: eight post-obese women. C: 10 matched control women. d g ˆ diet group
interaction. Results in the same row with different superscripts are different, P < 0.05 (n ˆ 18).
women (6.4 ng=ml) and eight matched controls (8.9
ng=ml).38 Conversely, eight post-obese subjects (two
males, six females) were recently found to have much
lower fasting leptin concentration (4.6 ng=ml) than
eight controls (11.2 ng=ml, one male, seven
females).40 The reason for the discrepancy between
these studies is not easy to ®nd, but in general it is
dif®cult to rely on a single measurement, especially
when the groups are relatively small (n ˆ 8 ± 10) and
include different sexes. However, with the present
results of increased postprandial leptin concentrations
in post-obese, considerations on the fasting values
may be less relevant.
The second interesting ®nding in the present study
was the increased leptin concentration after
SUCROSE compared with FAT and STARCH. This
was found for fasting values and total areas under the
curves (AUC's). Since the incremental AUC's (dAUC's) were not different, the larger AUC's were
caused by the higher fasting values on SUCROSE.
The reason for the increased fasting leptin cannot be
found in the fasting glucose and insulin levels, since
these were unchanged by the dietary manipulations.
Instead it may be that the greater initial postprandial
insulin peak on SUCROSE had an overall stimulating
effect on leptin secretion on this diet, giving rise to the
higher fasting leptin on SUCROSE. Plasma leptin
levels do not increase acutely after meal intake, but
a slow increase starting 4 h postprandially and reaching a peak 8 h postprandially has been reported.20
Furthermore, the often reported diurnal variation
with highest leptin late at night and lowest during
the day24 was found to be related not to the day=night
factorper se, but to the food intake.20 Thus, meal
intake does have an impact on leptin secretion. Several recent studies also support that carbohydrates per
se have an effect on leptin secretion. Romon et al
reported signi®cant differences in 8 h leptin concentrations between an isoenergetic high-fat and highcarbohydrate meal in 22 non-obese males and
females.22 Furthermore, Coppack et al 19 found that
in vivo tissue leptin production increased 5 h after a
meal with 70 E% carbohydrate, demonstrating both a
slow effect of meal intake and a speci®c effect of
carbohydrate on leptin secretion. Finally, Astrup et al
found that leptin secretion from adipose tissue, mea-
sured by the 133Xe-clearance technique and cannulation of the abdominal fat vein, increased steeply 30
min after intake of a mixed meal and returned towards
baseline from 60 to 120 min postprandially. There
were no observable changes in arterial, venous or
arterial-venous leptin concentrations.41 The increase
in leptin secretion occurred before the absorption of
dietary fat, but simultaneously with the increase in
plasma glucose and insulin. This indicates that leptin
not only acts as a long-term lipostatic agent, but also
as a short-term glucostatic hormone, stimulated
acutely by the intake of dietary carbohydrate. Many
previous test meal studies using only short measurement periods and plasma samples have therefore not
been able to show these changes. In line with the
above is also a recent study by Jenkins et al.14 They
demonstrated a close correlation between changes in
fasting leptin and carbohydrate intake after 4 days of
fasting, whereas no such correlations were seen with
changes in fat or protein intake. They also concluded
that, since these correlations were observed before any
marked loss of fat mass, leptin may have a role in
defending the body's carbohydrate stores and may
therefore be involved in the satiating effects of carbohydrate.
In the present study, leptin was measured on ad
libitum diets, ie under conditions resembling the
subjects' normal life, given these types of diets.
Since diets were given ad libitum and subjects lost
some body weight on the STARCH diet (0.7 kg), data
were adjusted both for differences in energy intake
and changes in body weight and fat mass. This did
not, however, change the conclusions. Instead the
leptin differences could be abolished by adjusting
for 14 day average sucrose intake indicating that
sucrose per se was the reason for the increased
leptin levels. Despite the fact that subjects had a
similar ad libitum energy intake on the FAT and
SUCROSE diet, leptin did not increase on the FAT
diet. The increased leptin on SUCROSE might therefore be one of several mechanisms trying to defend
the body against weight gain on such a diet by
reducing food intake and increasing energy expenditure. That energy intake was not lower on SUCROSE
than on FAT therefore seems puzzling. Maybe the
SUCROSE diet was too palatable28 and=or included
International Journal of Obesity
Leptin, predisposition to obesity and diet
A Raben and A Astrup
458
too many ¯uids42 for leptin to have a reducing effect
on energy intake compared with the FAT diet. Instead,
both in the present and previous studies, sympathetic
nervous system activity, measured by energy expenditure and=or catecholamine concentrations, was
actually increased on a sucrose-rich diet.28,43,44 The
positive relation between AUC leptin and noradrenaline reported here supports this hypothesis.
The association of leptin with food intake or appetite sensations in humans has so far only been investigated in a few studies. In a study on 12 normalweight males, insulin and hunger ratings were found
to differ signi®cantly, whereas leptin levels were
similar 8 h after two different test meals.27 In another
study, however, fasting leptin was found to be positively related to fasting satiety in 22 overweight
women on caloric restriction.45 In the present study,
we saw the opposite on STARCH, ie a positive
correlation between fasting hunger and leptin. The
latter discrepancies can, however, be related to the use
of appetite measurements from single individuals in a
correlation analyses. This may give very different and
probably often erroneous outcomes due to great interand intraindividual variation.33 In the present study,
however, both mean 8 h satiety and leptin concentrations were in general higher in post-obese than in
controls. This could support a relation between leptin
and satiety in humans, although a bias in the registration of subjective appetite in obese and obesity-susceptible individuals may be suspected.
Conclusion
Two important ®ndings were obtained from the present study. The ®rst was a larger postprandial increase
in leptin levels in post-obese, normal-weight subjects
compared with never-obese controls. This might be
explained by increased insulin sensitivity in adipose
tissue in the post-obese group. The second ®nding was
increased leptin levels after 14 days' ad libitum intake
of a sucrose-rich=low-fat diet compared with a starchrich=low-fat or a fat-rich diet. This may have been
caused by higher postprandial insulin peaks and
thereby greater leptin stimulation on the sucrose-rich
diet. Further scienti®c support for these contentions is
still warranted, however.
Acknowledgements
The study was supported by the Danish Research and
Development Programme for Food Technology
1990 ± 1994, Danisco Sugar, and the Danish Medical
Research Council, grant no. 12-9537-3. MasterFoods
a.s. and Toms Chokolade A=S generously sponsored
foods for the study. The authors gratefully thank
International Journal of Obesity
Bente Knap, Inge Timmermann, Jannie Mùller
Larsen, Charlotte Kostecki, Karina Graff Larsen,
Lone Kistrup Larsen, Lis Kristoffersen and Trine
Jessen for expert technical assistance.
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