Pretreatment fasting plasma glucose and insulin modify dietary weight loss success results from 3 randomized clinical trials

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Pretreatment fasting plasma glucose and insulin modify dietary weight
loss success: results from 3 randomized clinical trials
Mads F Hjorth,1 Christian Ritz,1 Ellen E Blaak,4 Wim HM Saris,4 Dominique Langin,5–8 Sanne Kellebjerg Poulsen,1,9
Thomas Meinert Larsen,1 Thorkild IA Sørensen,2,3,10 Yishai Zohar,11 and Arne Astrup1
1Department of Nutrition, Exercise and Sports, Faculty of Sciences, 2Novo Nordisk Foundation Center for Basic Metabolic Research (Section on Metabolic
Genetics), 3Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; 4Department of Human
Biology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, Maastricht, Netherlands;
5INSERM, UMR1048, Obesity Research Laboratory, Institute of Metabolic and Cardiovascular Diseases, Toulouse, France; 6University of Toulouse,
UMR1048, Paul Sabatier University, Toulouse, France; 7Toulouse University Hospitals, Laboratory of Clinical Biochemistry, Toulouse, France; 8Institut
Universitaire de France, Paris, France; 9Steno Diabetes Center Copenhagen, Gentofte, Denmark; 10Department of Clinical Epidemiology (formerly Institute of
Preventive Medicine), Bispebjerg and Frederiksberg Hospitals, the Capital Region, Copenhagen, Denmark; and 11Gelesis Inc., Boston, MA
ABSTRACT
Background: Which diet is optimal for weight loss and mainte-
nance remains controversial and implies that no diet fits all patients.
Objective: We studied concentrations of fasting plasma glucose
(FPG) and fasting insulin (FI) as prognostic markers for successful
weight loss and maintenance through diets with different glycemic
loads or different fiber and whole-grain content, assessed in 3 ran-
domized trials of overweight participants.
Design: After an 8-wk weight loss, participants in the DiOGenes
(Diet, Obesity, and Genes) trial consumed ad libitum for 26 wk a
diet with either a high or a low glycemic load. Participants in the
Optimal well-being, development and health for Danish children
through a healthy New Nordic Diet (OPUS) Supermarket interven-
tion (SHOPUS) trial consumed ad libitum for 26 wk the New Nor-
dic Diet, which is high in fiber and whole grains, or a control diet.
Participants in the NUGENOB (Nutrient-Gene Interactions in Hu-
man Obesity) trial consumed a hypocaloric low-fat and high-
carbohydrate or a high-fat and low-carbohydrate diet for 10 wk.
On the basis of FPG before treatment, participants were categorized
as normoglycemic (FPG ,5.6 mmol/L), prediabetic (FPG 5.6–
6.9 mmol/L), or diabetic (FPG $7.0 mmol/L). Modifications of
the dietary effects of FPG and FI before treatment were examined
with linear mixed models.
Results: In the DiOGenes trial, prediabetic individuals regained a
mean of 5.83 kg (95% CI: 3.34, 8.32 kg; P , 0.001) more on the
high– than on the low–glycemic load diet, whereas normoglycemic
individuals regained a mean of 1.44 kg (95% CI: 0.48, 2.41 kg;
P = 0.003) more [mean group difference: 4.39 kg (95% CI: 1.76,
7.02 kg); P = 0.001]. In SHOPUS, prediabetic individuals lost a
mean of 6.04 kg (95% CI: 4.05, 8.02 kg; P , 0.001) more on the
New Nordic Diet than on the control diet, whereas normoglycemic
individuals lost a mean of 2.20 kg (95% CI: 1.21, 3.18 kg; P , 0.001)
more [mean group difference: 3.84 kg (95% CI: 1.62, 6.06 kg);
P = 0.001]. In NUGENOB, diabetic individuals lost a mean of
2.04 kg (95% CI: 20.20, 4.28 kg; P = 0.07) more on the high-fat
and low-carbohydrate diet than on the low-fat and high-carbohydrate
diet, whereas normoglycemic individuals lost a mean of 0.43 kg
(95% CI: 0.03, 0.83 kg; P = 0.03) more on the low-fat and high-
carbohydrate diet [mean group difference: 2.47 kg (95% CI: 0.20,
4.75 kg); P = 0.03]. The addition of FI strengthened these associations.
Conclusion: Elevated FPG before treatment indicates success with
dietary weight loss and maintenance among overweight patients con-
suming diets with a low glycemic load or with large amounts of fiber
and whole grains. These trials were registered at clinicaltrials.gov as
NCT00390637 (DiOGenes) and NCT01195610 (SHOPUS), and
at ISRNCT.com as ISRCTN25867281 (NUGENOB). Am J
Clin Nutr doi: https://doi.org/10.3945/ajcn.117.155200.
Keywords: glucose, insulin, precisionmedicine, personalized nutrition,
weight, glycemic load, glycemic index, fiber, prediabetes, diabetes
INTRODUCTION
In most countries, current interventions and policies have failed
to stop increases in overweight and obesity, resulting in the need
for more effective and affordable preventive and management
Supported by the European Commission Food Quality and Safety Priority of
the Sixth Framework Program [for the Diet, Obesity, and Genes (DiOGenes)
project; contract FP6-2005-513946]. The Optimal well-being, development and
health for Danish children through a healthy New Nordic Diet (OPUS) Su-
permarket intervention (SHOPUS) study was supported by the Nordea Foun-
dation (grant 02-2010-0389) and by sponsors who provided foods to the shop. A
full list of food sponsors is available at the study website (www.foodoflife.
dk/shopus). The Nutrient-Gene Interactions in Human Obesity (NUGENOB)
study was supported by the European Community (contract QLK1-CT-2000-
00618). The work reported in this article was funded by grants from Gelesis Inc.
Supplemental Figures 1–4 and Supplemental Tables 1–4 are available from
the “Online Supporting Material” link in the online posting of the article and
from the same link in the online table of contents at http://ajcn.nutrition.org.
Address correspondence to MFH (e-mail: madsfiil@nexs.ku.dk).
Abbreviations used: DiOGenes, Diet, Obesity, and Genes; FI, fasting in-
sulin; FPG, fasting plasma glucose; NND, New Nordic Diet; NUGENOB,
Nutrient-Gene Interactions in Human Obesity; OPUS, Optimal well-being,
development and health for Danish children through a healthy New Nordic
Diet; SHOPUS, OPUS Supermarket intervention.
Received March 3, 2017. Accepted for publication June 9, 2017.
doi: https://doi.org/10.3945/ajcn.117.155200.
Am J Clin Nutr doi: https://doi.org/10.3945/ajcn.117.155200. Printed in USA. � 2017 American Society for Nutrition 1 of 7
 AJCN. First published ahead of print July 5, 2017 as doi: 10.3945/ajcn.117.155200.
Copyright (C) 2017 by the American Society for Nutrition 
https://doi.org/10.3945/ajcn.117.155200
https://doi.org/10.3945/ajcn.117.155200
https://doi.org/10.3945/ajcn.117.155200
options. Advice to eat less and exercise more, or to count and
limit calorie intake, seems reasonable, but it has not been ef-
fective in reversing the obesity epidemic. The struggle to find the
best diet for weight management has largely failed, giving rise
to an endless number of fad diets (1); this failure has merely
taught us that amounts of specific macronutrients are of minor
importance as long as a diet is taught with the enthusiasm and
persistence to make individuals adhere to it (2, 3). This failure
also may imply that no diet fits all needs, which justifies a search
for biomarkers that can predict success in losing weight and
maintaining weight loss, and can allow the most efficient diet to
be selected on an individual basis.
Few relatively small dietary intervention studies (n = 21–81)
have compared weight loss success while consuming low-
carbohydrate diets (low glycemic load) and low-fat diets (high
glycemic load) while stratifying by fasting insulin (FI) (4, 5) and
insulin secretion measures (6–8). Cornier et al. (4) found that
obese participants with FI .15 mIU/mL lost more weight by
consuming a low-carbohydrate, high-fat diet than a low-fat,
high-carbohydrate, whereas the result was opposite among
participants with FI ,10 mIU/mL. Furthermore, overweight or
obese participants with an insulin concentration above the me-
dian 30 min after an oral-glucose-tolerance test have been found
to lose more weight while consuming ad libitum a low–glycemic
load diet than a low-fat diet (high glycemic load), whereas no
differencewas observed among participants with insulin con-
centrations below the median (7, 8). Two other studies failed to
replicate this result (5, 6). None of these studies investigated
glycemic status before treatment as a prognostic marker of di-
etary weight loss and maintenance of weight loss with different
diets. However, subjects with higher fasting plasma glucose
(FPG) have been found to lose more weight when consuming a
fibrous hydrogel and a hypocaloric diet for 12 wk (Arne Astrup,
unpublished results, 2014).
The purpose of this study was to investigate FPG and FI as
prognostic markers for weight loss and weight loss maintenance
when allocated to pairs of diets with varying macronutrient
content, glycemic load, and fiber and whole-grain content from 3
randomized clinical trials. This was done to find the best weight
loss and weight loss maintenance diet for patients with different
glycemic and insulinemic statuses.
METHODS
We reanalyzed 3 randomized clinical trials—the DiOGenes
(Diet, Obesity, and Genes) study conducted in 8 European coun-
tries (9, 10); the Optimal well-being, development and health for
Danish children through a healthy New Nordic Diet (OPUS) Su-
permarket intervention (SHOPUS) conducted in Denmark (11);
and the NUGENOB (Nutrient-Gene Interactions in Human Obe-
sity) trial conducted in 7 European countries (12). A diagram
showing the participant flow through the 3 studies can be found in
Supplemental Figures 1–3. The research protocols were ap-
proved by the appropriate ethics committees, and all human par-
ticipants gave written informed consent.
As part of the larger dietary weight maintenance trial DiOGenes, a
total of 316 overweight or obese participants (Table 1) were
randomly assigned, after successfully losing $8% body mass
during an 8-wk low-calorie weight loss phase, to an ad libitum
low–glycemic load (low carbohydrate and low glycemic index)
or high–glycemic load (high carbohydrate and high glycemic
index) weight-maintenance diet for 26 wk (3 other dietary reg-
imens from the study are described in Supplemental Figure 4).
Dietary fat content was held constant (w30% of energy) be-
tween the 2 diets. Before the initial weight loss phase, blood
samples were drawn from participants in the fasted state, from
which FPG and FI were analyzed. Furthermore, study partici-
pants completed diaries recording amounts of weighed food for
3 consecutive days at the end of the intervention. Height and
weight were measured before the initial weight loss phase.
During the weight-maintenance period, body weight was
measured at randomization and at weeks 2, 4, 6, 10, 14, 18, 22,
and 26.
In the SHOPUS, a total of 181 centrally obese men and women
(Table 1) were randomly assigned to receive ad libitum for 26 wk the
New Nordic Diet (NND) or a control diet. The macronutrient
composition of the NND was based on Nordic Nutrition Recom-
mendations (13) but contained slightlymore protein content, whereas
the control diet was designed to match the macronutrient compo-
sition of the average diet consumed in Denmark (14), meaning a
slightly higher fat content. The NND is a whole-food approach
characterized by very large amounts of dietary fiber, whole grains,
fruits, berries, and vegetables (11). The glycemic index of the diets
was not assessed. For both groups, food and beverages were provided
free from a study shop throughout the intervention period (11).
Fasting blood samples were drawn at screening and at baseline,
respectively, from which FPG and FI were analyzed. Height was
measured at baseline, and body weight was measured at randomi-
zation and at weeks 2, 4, 8, 12, 16, 20, 24, and 26.
In the NUGENOB study, a total of 771 primarily obese par-
ticipants (Table 1) were randomly assigned to receive a low-fat and
high-carbohydrate or a high-fat and low-carbohydrate hypocaloric
diet (2600 kcal/d) for 10 wk. Dietary protein content was held
constant (aiming at 15% of energy and achieving w17% of en-
ergy) between the 2 diets. The glycemic index of the diets was not
assessed. Blood samples were drawn at baseline, from which FPG
and FI were analyzed. Dietary intake during the intervention was
calculated from 6 d of dietary recordings of weighed food intake
during the intervention. Height was measured at baseline, and
body weight was measured weekly throughout the intervention.
Based on the FPG before treatment, participants were catego-
rized as normoglycemic (FPG ,5.6 mmol/L), prediabetic (FPG
5.6–6.9 mmol/L), or diabetic (FPG $7.0 mmol/L) through the
use of the FPG cutoffs published by the American Diabetes As-
sociation (15). Only the NUGENOB trial included diabetic par-
ticipants consuming both diets; the DiOGenes and SHOPUS trials
do not include analysis of diabetic participants. No similar cate-
gorization of individuals exists based on absolute concentrations
of FI. Previous studies have categorized these differently and have
not included intermediate values (4, 5). However, previous studies
using measures of insulin secretion used median split (6–8). We
used the median values among the prediabetic participants as the
cutoffs (in each of the 3 studies separately) to categorize partic-
ipants as having low or high FI. Finally, the dichotomized cate-
gorization of FPG and FI was also combined to allocate 4 groups
of individuals. Because the number of diabetic participants was
small in the NUGENOB trial, we reduced the FPG cutoff to
6.4 mmol/L when combined with FI.
Baseline characteristics of the 3 studies were summarized as
means 6 SDs, medians (IQRs), or proportions. Differences in
2 of 7 HJORTH ET AL.
the baseline characteristics between glycemic groups were as-
sessed through the use of 2-sample t tests or 1-factor ANOVA
(variables possibly transformed before analysis), or Pearson chi-
square tests. Pearson correlations were calculated between FPG
and FI, and between FPG and weight change.
In each of the 3 studies separately, the differences in weight
change from baseline between glycemic and insulinemic groups
(and the combination of the 2) were analyzed by means of linear
mixed models, with the use of all available weight measurements
(including those from noncompleters). The linear mixed models
included the 3-way interaction diet 3 time 3 glycemic or in-
sulinemic strata, as well as all nested 2-way interactions and the
main effects; the models comprised additional fixed effects in-
cluding age, sex, BMI, and initial weight loss (for the DiOGenes
trial only) and random effects for subjects and sites (except for
SHOPUS). Results are shown as the mean weight changes from
baseline with 95% CIs. At the end of the study, differences in
weight change from baseline between diets were compared within
and between each blood marker group through the use of pairwise
comparisons with post hoc t tests. The level of significance was set
at P, 0.05, and statistical analyses were conducted with the use of
STATA/SE software version 14.1 (StataCorp LLC).
RESULTS
In all 3 trials, individuals with prediabetes were older and had a
higher bodyweight or BMI at baseline than did the normoglycemic
individuals (P , 0.05) (Table 1). The dietary intakes are described
TABLE 1
Baseline characteristics of the study populations stratified by fasting plasma glucose1
FPG ,5.6 mmol/L FPG 5.6–6.9 mmol/L FPG $7.0 mmol/L
DiOGenes (n = 225) (n = 41) —
Age 41.0 6 6.1a 43.3 6 7.0b —
Sex, %
Female 65.3 65.9 —
Male 34.7 34.2 —
Body weight, kg 96.6 (87.7, 109.3) 98.9 (88.7, 115.6) —
Weight loss during an 8-wk LCD, kg 10.3 (8.7, 12.4) 10.3 (8.2, 12.8) —
BMI, kg/m2 33.1 (30.7, 36.8)a 35.3 (32.0, 40.9)b —
BMI category, %
Normal 0.0 0.0 —
Overweight 20.4 9.8 —
Obese 79.6 90.2 —
Fasting glucose, mmol/L 4.9 (4.6, 5.2) 5.9 (5.7, 6.2) —
Fasting insulin, pmol/L 60 (42, 90)a 89 (62, 108)b —
SHOPUS (n = 139) (n = 37) —
Age 37.2 (29.2, 49.8)a 51.5 (44.9, 57.8)b —
Sex,2 %
Female 74.1 54.1 —
Male 25.9 46.0 —
Body weight, kg 85.0 (75.3, 100.6)a 94.9 (86.8, 101.6)b —
BMI, kg/m2 28.9 (26.4, 31.9) 30.7 (28.9,33.9) —
BMI category, %
Normal 13.0 5.4 —
Overweight 45.3 32.4 —
Obese 41.7 62.2 —
Fasting glucose, mmol/L 5.1 (4.8, 5.3) 5.8 (5.6, 6.0) —
Fasting insulin, pmol/L 64 (41, 90) 73 (46, 116) —
NUGENOB (n = 529) (n = 197) (n = 17)
Age 36 (29, 42)a 42 (36, 46)b 41 (37, 47)b
Sex,2 %
Female 83.7 53.8 52.9
Male 16.3 46.2 47.1
Body weight, kg 96.5 (88.1, 107.8)a 103.0 (93.8, 111.0)b 103.6 (92.6, 120.4)c
BMI, kg/m2 34.6 (31.8, 38.0)a 34.7 (31.9, 37.9)a 34.9 (34.0, 40.4)b
BMI category, %
Normal 0.0 0.0 0.0
Overweight 6.1 2.5 0.0
Obese 94.0 97.5 100.0
Fasting glucose, mmol/L 5.1 (4.9, 5.3) 5.8 (5.7, 6.1) 7.4 (7.1, 9.2)
Fasting insulin, pmol/L 57 (40, 81)a 80 (60, 112)b 122 (69, 176)c
1 Values are means6 SDs or medians (IQRs). Different superscript letters within a row indicate significant differences,
P, 0.05. DiOGenes, Diet, Obesity, and Genes; FPG, fasting plasma glucose; LCD, low-calorie diet; NUGENOB, Nutrient-
Gene Interactions in Human Obesity; OPUS, Optimal well-being, development and health for Danish children through
a healthy New Nordic Diet; SHOPUS, OPUS Supermarket intervention.
2 Overall difference between groups tested by chi-square, P , 0.001.
BASELINE GLUCOSE AND INSULIN MODIFY WEIGHT LOSS 3 of 7
in Supplemental Table 1. The correlations between FPG and FI in
the 3 trials were low but significant (r2 = 0.04–0.08; P # 0.005).
After a median weight loss of 10.3 kg in the DiOGenes study,
prediabetic participants consuming ad libitum the high–glycemic
load diet for 26 wk regained 5.83 kg (95% CI: 3.34, 8.32 kg;
P , 0.001) more than the group consuming the low–glycemic
load diet, whereas normoglycemic participants regained only
1.44 kg (95% CI: 0.48, 2.41 kg; P = 0.003) more (Figure 1 and
Supplemental Table 2). Consequently, a 4.39-kg (95% CI: 1.76,
7.02 kg; P = 0.001) difference in responsiveness to the diets was
found between normoglycemic and prediabetic participants.
Participants with low FI regained 2.27 kg (95% CI: 1.22,
3.32 kg; P , 0.001) more consuming the high– compared with
the low–glycemic load diet, whereas no difference was observed
for participants with high FI (P = 0.24). Consequently, no dif-
ference in responsiveness to the diets were found between par-
ticipants with high and low FI (P = 0.14) (Figure 2 and
Supplemental Table 3). Prediabetic participants with low FI
consuming the high–glycemic load diet regained 7.78 kg
(95% CI: 4.39, 11.18 kg; P, 0.001) more than those consuming
the low–glycemic load diet, whereas no difference was observed
for normoglycemic participants with high FI [1.17 kg (95% CI:
FIGURE 1 Relative changes in body weight in participants consuming diets within each of the 3 studies when stratified by FPG (millimoles per liter)
before treatment. Data are presented as estimated mean weight changes from baseline for each combination of the diet 3 time 3 FPG strata interaction in the
linear mixed models, which were also adjusted for age, sex, BMI, and weight loss on the low-calorie diet (for the DiOGenes trial only), subjects, and sites
(except for SHOPUS). Differences in weight change from baseline between diets at the end of the study were compared within and between FPG groups with
pairwise comparisons through the use of post hoc t tests and are presented as mean weight changes from baseline with 95% CIs. The zero line indicates no
difference between diets. Data points above the zero line favor the low–glycemic load diet (DiOGenes), the New Nordic Diet (SHOPUS), and the high-fat and
low-carbohydrate diet (NUGENOB). The 95% CI for prediabetic participants in the NUGENOB trial is omitted from the figure. USignificant difference
between the glycemic groups, P , 0.05. xSignificant difference from zero, P , 0.05. DiOGenes, Diet, Obesity, and Genes; FPG, fasting plasma glucose;
NUGENOB, Nutrient-Gene Interactions in Human Obesity; OPUS, Optimal well-being, development and health for Danish children through a healthy New
Nordic Diet; SHOPUS, OPUS Supermarket intervention.
FIGURE 2 Relative changes in body weight between diets within each of the 3 studies when stratified by FI before treatment. Data are presented as the
estimated mean weight changes from baseline for each combination of the diet 3 time 3 FI strata interaction in the linear mixed models, which were also
adjusted for age, sex, BMI, and weight loss on the low-calorie diet (for DiOGenes only), subjects, and sites (except for SHOPUS). At the end of each study,
differences in weight change from baseline between diets were compared within and between FI groups with pairwise comparisons through the use of post hoc
t tests and are presented as mean weight changes from baseline with 95% CIs. The zero line indicates no difference between diets. Data points above the zero
line favor the low–glycemic load diet (DiOGenes), the New Nordic Diet (SHOPUS), and the high-fat and low-carbohydrate diet (NUGENOB). Cutoffs were
90.3 (DiOGenes), 72.9 (SHOPUS), and 79.2 pmol/L (NUGENOB), representing the median FI of prediabetic participants within each study. USignificant
difference between the insulinemic groups, P , 0.05. xSignificant difference from zero, P , 0.05. DiOGenes, Diet, Obesity, and Genes; FI, fasting insulin;
NUGENOB, Nutrient-Gene Interactions in Human Obesity; OPUS, Optimal well-being, development and health for Danish children through a healthy New
Nordic Diet; SHOPUS, OPUS Supermarket intervention.
4 of 7 HJORTH ET AL.
20.59, 2.93 kg); P = 0.19] (Figure 3 and Supplemental Table
4). The correlation between FPG and weight gain during the
intervention was 20.14 (P = 0.14) with the low–glycemic load
diet and 0.22 (P = 0.028) with the high–glycemic load diet.
In SHOPUS, prediabetic participants lost 6.04 kg (95% CI:
4.05, 8.02 kg; P , 0.001) more consuming the 26-wk ad libitum
NND than the control diet, whereas normoglycemic participants
lost only 2.20 kg (95% CI: 1.21, 3.18 kg; P , 0.001) more.
Consequently, a 3.84-kg (95% CI: 1.62, 6.06 kg; P = 0.001)
difference in responsiveness to the diets was found between
normoglycemic and prediabetic participants (Figure 1 and
Supplemental Table 2). Participants with low FI lost 4.09 kg
(95% CI: 2.91, 5.27 kg; P , 0.001) more consuming the NND
than the control diet, whereas participants with high FI lost only
1.61 kg (95% CI: 0.28, 2.94 kg; P = 0.02) more. Consequently, a
2.48-kg (95% CI: 0.70, 4.26 kg; P = 0.006) difference in re-
sponsiveness to the diets was found between participants with
high and low FI (Figure 2 and Supplemental Table 3). Pre-
diabetic participants with low FI lost 6.27 kg (95% CI: 3.51,
9.02 kg; P , 0.001) more consuming the NND than the control
diet, whereas no difference was observed for normoglycemic
participants with high FI [0.10 kg (95% CI: 21.37, 1.57 kg;
P = 0.89)] (Figure 3 and Supplemental Table 4). The correlation
between FPG and weight gain was 20.29 (P = 0.005) on the
NND and 0.01 (P = 0.92) on the control diet.
In the NUGENOB study, normoglycemic participants lost
0.43 kg (95% CI: 0.03, 0.83 kg; P = 0.03) more consuming the
10-wk hypocaloric low-fat and high-carbohydrate than the hy-
pocaloric high-fat and low-carbohydrate diet, whereas no dif-
ference was observed for prediabetic participants (P = 0.41).
Diabetic participants tended to lose 2.04 kg (95% CI: 20.20,
4.28 kg; P = 0.07) more consuming the high-fat and low-
carbohydrate diet. Consequently, a 2.47-kg (95% CI: 0.20-,
4.75-kg; P = 0.03) difference in responsiveness to the diets was
found between normoglycemic and diabetic participants (Figure
1 and Supplemental Table 2). Participants with low FI lost
0.42 kg (95% CI: 0.01, 0.83 kg; P = 0.046) more consuming the
low-fat and high-carbohydrate diet than the high-fat and low
carbohydrate diet, whereas no difference was observed for par-
ticipants with high FI (P = 0.84). Consequently, no difference in
responsiveness to the diets was found between participants with
high FI and those with low FI (P = 0.33) (Figure 2 and Sup-
plemental Table 3). Participants with FPG $6.4 mmol/L and low
FI lost3.06 kg (95% CI: 0.40, 5.71 kg; P = 0.02) more consuming
the high-fat and low-carbohydrate diet than the low-fat and high-
carbohydrate diet. Participants with FPG ,6.4 mmol/L and low
FI lost 0.49 kg (95% CI: 0.08, 0.91 kg; P = 0.02) more consuming
the low-fat and high-carbohydrate diet (Figure 3 and Supple-
mental Table 4). The correlation between FPG and weight gain
was 0.06 (P = 0.30) with the low-fat and high-carbohydrate diet
and20.03 (P = 0.55) with the high-fat and low-carbohydrate diet.
DISCUSSION
We identified FPG as an important biomarker associated with
successful dietary weight loss and weight loss maintenance while
consuming a range of different hypocaloric and ad libitum diets.
Thus, overweight or obese participants with elevated FPG
(i.e., prediabetic individuals) are extremely susceptible to weight
gain (regain) when consuming a high–glycemic load diet. On the
other hand, these individuals can achieve substantial weight loss
when consuming a diet with a low glycemic load or a diet high
in fiber and whole grains, even without restricting calories.
We previously reported a relative modest difference in weight
regain (2.0 kg) between the high– and low–glycemic load diets
after 26 wk of weight maintenance in the DiOGenes trial (9).
However, we now report that this difference in weight mainte-
nance between the diets was .4 times larger in prediabetic than
FIGURE 3 Relative change in body weight between diets within each of the 3 studies when stratified by FPG and FI before treatment. Data are presented
as estimated mean weight changes from baseline for each combination of the diet 3 time 3 FPG strata 3 FI strata interaction in the linear mixed models,
which were also adjusted for age, sex, BMI, and weight loss on the low-calorie diet (for DiOGenes only), subjects, and sites (except for SHOPUS). At the end
of each study, differences in weight change from baseline between diets were compared within and between blood marker groups with pairwise comparisons
through the use of post hoc t tests and are presented as mean weight changes from baseline with 95% CIs. The zero line indicates no difference between diets.
Data points above the zero line favor the low–glycemic load diet (DiOGenes), the New Nordic Diet (SHOPUS), and the high-fat and low-carbohydrate diet
(NUGENOB). The 95% CI for the high-FI groups in the NUGENOB trial is omitted from the figure. Cutoffs for FPG and FI were 5.6 mmol/L and 90.3 pmol/L
(DiOGenes), 5.6 mmol/L and 72.9 pmol/L (SHOPUS), and 6.4 mmol/L and 79.2 pmol/L (NUGENOB). USignificant difference between the glycemic or
insulinemic groups, P , 0.05. xSignificant difference from zero, P , 0.05. DiOGenes, Diet, Obesity, and Genes; FI, fasting insulin; FPG, fasting plasma
glucose; NUGENOB, Nutrient-Gene Interactions in Human Obesity; OPUS, Optimal well-being, development and health for Danish children through
a healthy New Nordic Diet; SHOPUS, OPUS Supermarket intervention.
BASELINE GLUCOSE AND INSULIN MODIFY WEIGHT LOSS 5 of 7
in normoglycemic participants (5.8 compared with 1.4 kg).
Likewise, we previously reported the overall difference between
the NND and control diets to be 3.2 kg (11). This difference was
almost 3 times larger in prediabetic than in normoglycemic
participants (6.0 compared with 2.2 kg). Furthermore, we previously
reported a nonsignificant difference of 0.3 kg between 10-wk low-
fat and high-carbohydrate and high-fat and low-carbohydrate hy-
pocaloric (2600 kcal/d) diets (12). Stratifying by FPG revealed a
2.5-kg difference in response between the 2 diets among normo-
glycemic and diabetic participants, resulting in a small but sig-
nificantly larger weight loss among normoglycemic participants
consuming the low-fat and high-carbohydrate diet and a border-
line larger weight loss among diabetic participants consuming the
high-fat and low-carbohydrate diet.
FI before treatment was a modest biomarker on its own; how-
ever, combining FI as a biomarker with FPG further strengthened
the associations and revealed interesting phenotypes. Participants
with low FPG and high FI responded equally on all 3 pairs of diets,
whereas participants with high FPG and low FI did better on diets
with a lower glycemic load and more fiber and whole grains.
Furthermore, individuals with low FPG and low FI did better on a
calorie-restricted low-fat and high-carbohydrate diet.
The dietary interventions were carefully controlled to avoid
undesirable differences in the dietary composition within each of
the studies. This resulted in a percentage of energy from fat
within the targeted interval in the NUGENOB trial (12) and a diet
fully in accordance with the NND principles in SHOPUS (11).
However, the glycemic index was not registered in SHOPUS or in
the NUGENOB trial, and we cannot rule out that differences in
glycemic load could be partly responsible for the differences
observed in weight change in these analyses. However, the large
difference in the carbohydrate content of the diets in the
NUGENOB trial could be used as a proxy for glycemic load. The
targeted differences of 12% of energy from protein (at the ex-
pense of carbohydrates) and 15 glycemic index units in the
DiOGenes trial were not fully achieved; instead, these values
were 5.4% of energy and 4.7 glycemic index units, respectively
(9). Nevertheless, the differences in dietary intake obtained here
were large enough to detect differences in weight management
when stratifying by glycemic status.
From these results we cannot conclude whether FPG is re-
sponsible for the different effects of the diets or is simply a marker
for something else that we did not measure. A mechanistic ex-
planation for a direct role of FPG is plausible, as an increased FPG
reflects insulin resistance that is not overcome by enhanced insulin
secretion. To act as a satiety signal, glucose needs to be taken up by
cells in the liver, muscle, adipose tissue, and brain—tissues that are
supposed to deliver feedback to the brain centers that control
appetite and energy intake. We hypothesize that elevated FPG
concentrations indicate that less glucose is taken up by the cells
as a result of the impaired glucose metabolism, and that this can
be partly responsible for a weaker satiating effect of carbohy-
drates in prediabetic individuals, contrasted against insulin-
sensitive, normoglycemic obese individuals. However, no matter
the mechanisms, FPG may serve as a unique and easily accessible
biomarker that could be used to predict future successful weight
loss with different diets.
Over the past several decades, numerous randomized con-
trolled trials have compared various diets for the treatment of
obesity based on the assumption that one diet fits all, without
being able to provide strong evidence for one or the other (2, 3, 9, 11,
12). From our results, it seems that failure to stratify by glycemic
status is likely to underestimate (9, 11) or overlook (12) specific
effects among prediabetic and diabetic individuals, whereas it may
mask (12) or overestimate (9, 11) the effects of a specific diet among
normoglycemic individuals. Therefore, we strongly encourage the
investigation of FPG as amodifier of weight loss andmaintenance in
other large dietary clinical trials in order to help find the most
appropriate diet for individuals with differing glycemic statuses.
Generating evidence to support precision medicine is challeng-
ing, but in randomized clinical trials, interaction testing of in-
tervention effectiveness provides a potentially efficient means to do
so, especially when the results are replicated in other studies (16).
We used the most widely accepted FPG cutoffs advised by the
American Diabetes Association to present the most transparent
results (15).When stratifying by FPG, the randomized study designs
that should balance out known and unknown confounders are
weakened; we therefore adjusted for age, sex, and initial BMI,
because these differed or tended to differ between the glycemic
groups. A weakness is that the 3 studieswere not designed to
examine differences in responsiveness between normoglycemic and
prediabetic obese individuals; it is a matter of chance that we had
enough participants in each group to provide statistical power for our
analyses. However, the post hoc approach can also be considered a
strength, as all 3 studies were double-blinded with respect to the
glycemic status of the participants; the identified difference in di-
etary responsiveness cannot have been influenced by knowledge of
the participants or investigators. Moreover, although some of the
analyses—especially those for diabetic individuals—are based on
relatively small numbers, our findings seem to be consistent across
3 different studies, which suggests robustness of the findings.
In conclusion, elevated FPG before treatment predicts success in
dietary weight loss and weight loss maintenance among over-
weight patients consuming hypocaloric and ad libitum diets with a
low glycemic load or with high fiber and whole grains. This easily
accessible biomarker could potentially magnify weight loss and
optimize weight maintenance by stratifying patients to provide
personalized dietary guidance for overweight and obesity.
The authors’ responsibilities were as follows—AA, YZ, and MFH: de-
signed the research; MFH: performed the statistical analysis; MFH and AA:
wrote the manuscript; and all authors: contributed to the discussion of anal-
yses, critically reviewed the manuscript, and approved the final manuscript.
MFH, YZ, CR, and AA are co-inventors on a pending provisional patent
application on the use of biomarkers for prediction of weight loss responses
based on fasting plasma glucose and insulin. The remaining authors reported
no conflicts of interest.
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