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Medicine & Science in Sports & Exercise:
doi: 10.1249/MSS.0000000000000204
Basic Sciences

Postprandial Plasma Incretin Hormones in Exercise-Trained versus Untrained Subjects


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1Department of Nutrition and Dietetics, Saint Louis University, St. Louis, MO; 2Division of Geriatrics and Nutritional Science, Department of Medicine, Washington University School of Medicine, St. Louis, MO; 3Department of Biology, Saint Louis University, St. Louis, MO; 4Department of Medicine, Salerno University Medical School, Salerno, ITALY; and 5CEINGE Biotecnologie Avanzate, Napoli, ITALY

Address for correspondence: Edward P. Weiss, Ph.D., Department of Nutrition and Dietetics, Saint Louis University, 3437 Caroline Street, St. Louis, MO 63104; E-mail:

Submitted for publication May 2013.

Accepted for publication October 2013.

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Introduction: After food ingestion, the incretin hormones, glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP), are secreted by the intestines into circulation where they act on the pancreas to promote insulin secretion. We evaluated the hypothesis that low postprandial plasma insulin levels in lean exercise-trained individuals are associated with low concentrations of incretin hormones.

Methods: A cross-sectional study was performed to compare postprandial incretin hormone levels in lean endurance exercise-trained individuals (EX; n = 14, ≥40 yr) and age- and sex-matched, nonobese, sedentary control subjects (CON, n = 14). The main outcome measures were GLP-1, GIP, insulin, and glucose incremental areas under the curve (AUC) as measured in plasma samples collected during a 2-h,75-g oral glucose tolerance test (OGTT).

Results: The EX group had lower body fat percentage (14.6% ± 1.1% vs 23.3% ± 1.7%, P = 0.0002) and higher maximal oxygen uptake (53 ± 2 vs 34 ± 2, P < 0.0001) than CON. Glucose AUC did not differ between groups (P = 0.20). Insulin AUC was lower in EX (2.5 ± 0.5 vs 4.2 ± 1.2 μU·mL−1·1000 min−1, P = 0.02). No differences were observed between groups (EX and CON, respectively) for GLP-1 AUC (3.5 ± 0.7 vs 4.1 ± 1.1 pmol·min−1·100 L−1, P = 0.61) or GIP AUC (19.2 ± 1.4 vs 18.0 ± 1.4 pg·min−1·1000 mL−1; P = 0.56). In CON, insulin AUC was correlated with AUC for GLP-1 (r = 0.53, P = 0.05) and GIP (r = 0.71, P = 0.004), but no such correlations were observed in EX (both P ≥ 0.67).

Conclusions: Low postprandial insulin levels in lean exercise-trained individuals are not attributable to lower incretin hormone concentrations. However, exercise may decrease the dependency of postprandial insulin levels on incretin hormones.

The incretin hormones, glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP), are secreted into circulation by the intestine after food ingestion. In the presence of hyperglycemia, these hormones stimulate the β cells of the pancreas to secrete insulin (12) and are responsible for ∼50% of the postprandial rise in insulin concentrations. Long-term vigorous endurance training results in high cardiovascular fitness and low levels of body fat, both of which are independent determinants (18) of low postprandial insulin concentrations (23) and high insulin sensitivity (8). It is conceivable that these effects might be partly attributable to lower postprandial incretin hormone concentrations.

There is a paucity of research on the effect of endurance exercise training on postprandial incretin hormone concentrations. One study demonstrated that 3 months of exercise training (without weight loss) in obese women reduced postprandial insulin and GIP levels (13). Similar effects of exercise training on insulin and GIP were observed in two studies on older obese subjects; however, the intervention in these studies also included dietary restriction, which may have had its own effect on GIP (10,20). In another intervention group in one of these studies, subjects underwent exercise training without dietary restriction. While GIP concentrations did not change; this is not surprising because insulin levels were also unaffected (10). No studies could be found that evaluated the effect of longer-term training (i.e., ≥ 1 yr) on postprandial GIP levels or training effects in nonobese individuals. Furthermore, to our knowledge, no studies have evaluated the effect of exercise training on the bioactive form of GIP (the aforementioned studies evaluated total GIP) or on total or active GLP-1. However, it is noteworthy that exercise training (with dietary restriction) was recently shown to decrease circulating concentrations of dipeptidyl peptidase-4, which is the enzyme that rapidly degrades GIP and GLP-1 into their inactive forms; this effect would be expected to increase the serum concentrations of the bioactive forms of GIP and GLP-1 (14).

It is possible that long-term vigorous exercise training might alter postprandial incretin hormone concentrations through effects on body weight or adiposity. However, studies on the effects of body weight and adiposity on postprandial incretin hormones have produced conflicting results. Cross-sectional data indicate that postprandial serum concentrations of total and bioactive GIP are lower (7,9,22) in lean subjects than that in obese individuals. In addition, intervention studies have shown that postprandial total GIP levels decrease with weight loss (21,26). However, other cross-sectional (21) and intervention study data (9) indicate that body weight does not affect GIP levels. With respect to GLP-1, cross-sectional studies indicate that postprandial GLP-1 levels are higher in lean subjects than that in obese subjects (1,21); furthermore, one intervention study demonstrated increases in GLP-1 levels with weight loss (21). However, these findings are contradicted by a cross-sectional study which showed that lean subjects have lower GLP-1 levels than obese individuals (7) and intervention studies in which active GLP-1 decreased with weight loss (1) or did not change (2). Taken together, the effects of body weight and/or weight loss on postprandial incretin hormone concentrations are not clear.

The purpose of the present study was to evaluate the hypothesis that the lower postprandial insulin levels in lean endurance athletes are partly attributable to lower postprandial incretin hormone concentrations. We performed a cross-sectional study to compare the oral glucose tolerance test (OGTT) plasma insulin and incretin hormone concentrations in lean endurance athletes and healthy age- and sex-matched sedentary control subjects. A secondary objective was to determine the degree of association between postprandial incretin hormone concentrations and postprandial insulin levels to gain insights about the role of incretin hormones in modulating postprandial insulin levels in the exercise-trained and exercise-untrained states.

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Study design, setting, and participants

The study was a cross-sectional, observational comparison of middle-age to older individuals who were long-term endurance athletes (runners) and age- and sex-matched nonobese healthy control subjects. The subjects in the present study were a subset of those involved in a larger observational study (5) that had been ongoing, including follow-up visits, since 2002 and consisted mostly of men (for the first report from the larger study, see Fontana et al. [6] ). Research activities were performed in a university-based medical center in Saint Louis, Missouri. Data collection for the present ancillary study started in January 2007 and ended in December 2012. In addition to all testing for the primary study, the ancillary study included special blood collection and processing procedures for the measurement of incretin hormone concentrations. Although the larger study included a separate group of subjects who were undergoing self-imposed chronic calorie restriction, incretin hormone data were not available from these subjects.

Master athlete runners (EX, age ≥40 yr) who performed a minimum of 7 h·wk−1 of structured vigorous endurance exercise were recruited from the Saint Louis Metropolitan area. These participants averaged 77 km·wk−1 (48 miles·wk−1) running and had been training for an average of 21 yr. Exercise-trained volunteers were queried by the study dietitian and excluded if they followed a specific diet for the treatment of a medical condition (e.g., a gluten-free diet for gluten intolerance or a low sodium diet for blood pressure management) or any other diet in which a major food category is avoided (e.g., a “vegan” diet containing no animal products would be exclusionary). The diets of the enrolled exercise-trained participants were generally consistent with a typical U.S. diet (e.g., regular consumption of restaurant meals, fast food, sweets and fried foods, etc.), although this was based on a qualitative evaluation by the study dietitian, not formal criteria. Nonobese (BMI < 30 kg·m−2), age- and sex-matched individuals who had low levels of physical activity (<1 h·wk−1 for a minimum of 2 yr before the study) and were following a typical U.S. diet were recruited to serve as healthy control group (CON). All subjects underwent a medical history, physical examination, and standard clinical chemistries (blood and urine). Exclusion criteria included recent weight change (≥5% in 6 months), tobacco use, medication use, and a history or clinical evidence of disease. Written consent was obtained from all participants, and the study was approved by the university’s institutional review board.

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Height, weight, and body composition

Fasted morning height and weight were measured and used to calculate BMI (kg·m−2). Body composition was measured by using dual energy x-ray absorptiometry (QDR 1000/w; Hologic, Waltham, MA).

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Energy intake

Total energy intake was assessed by the study dietitian using 7-d food dairies. Participants received detailed instructions from the dietitian before recording in the diary; after the diary period, they were queried to clarify any information that was unclear. Computerized nutrient analysis (Nutrition Data System for Research, version 4.03; Nutrition Coordination Center, University of Minnesota, Minneapolis, MN) was used to analyze the diaries.

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Aerobic capacity

Maximal oxygen uptake (V˙O2max) was measured by indirect calorimetry (TrueMax 2400; ParvoMedics, Salt Lake City, UT) during a progressive incremental treadmill exercise test to exhaustion. A modified Balke treadmill test protocol was used in which the initial speed was adjusted for each subject to elicit an HR of ∼70% of age-predicted maximal HR, and the initial grade was 0%; thereafter, the speed remained constant, and the grade was increased 1%–2% every 1–2 min until the subject could no longer continue due to exhaustion. Additional details about this protocol have been published previously (25).

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Oral glucose tolerance test

OGTT (75 g, 2 h) was performed in the morning after an overnight fast. Subjects habitually consumed ≥150 g·d−1 carbohydrate before the OGTT and were instructed to refrain from exercise for ≥48 h. Venous blood was collected into EDTA containing tubes before and every 30 min after the oral glucose load. Samples to be analyzed for GLP-1 were collected into tubes that also contained dipeptidyl peptidase-4 inhibitor (DPP4; Millipore Corp., Saint Charles, MO) to prevent the degradation of active GLP-1. Plasma was isolated and frozen at −80°C for later analysis.

Plasma glucose was measured by using the glucose oxidase method (Stat Plus; YSI Corp., Yellow Springs, OH). Insulin was measured with a double-antibody radioimmunoassay (17). Total GIP and active GLP-1 (7–36 and 7–37 amides) were measured with ELISA assays (EZHGIP-54K and EGLP-35K, respectively; Millipore Corp.). All plasma analytes were measured by personnel who were blinded to subject identities and study groups. Positive incremental area under the curve (AUC) was calculated by using the trapezoidal method (3). Insulin sensitivity index was calculated from OGTT glucose and insulin data (15). Homeostasis model assessment of insulin resistance (HOMA-IR) was calculated from fasting glucose and insulin (16).

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Sample size determination

Sample size of 14 subjects per group was calculated based on the number of subjects that would be required to detect a typical exercise training effect on insulin AUC (i.e., 30% reduction [23,24]), a standard deviation of duplicate insulin AUC assessments of 2.5 μU·mL−1·1000 min−1 (24), an alpha error rate of 0.05, and a desired statistical power of 0.80. It was assumed that this would also have been sufficient to detect physiologically meaningful changes in incretin hormones, if exercise training affected incretin hormones.

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Statistical analyses

Between-group means comparisons were performed with independent t-tests. Because the residuals distributions for insulin and GLP-1 were skewed, these insulin and GLP-1 data were log transformed before analysis; results were back-transformed for data presentation. Spearman correlations were used to evaluate associations between variables. Fisher’s r-to-z transformations were used to evaluate the between-group equality of correlation coefficients. Multiple stepwise regression analyses were used to evaluate the determinants of insulin AUC, with P ≤ 0.15 being used as the criterion for including predictors in the model. Significance was accepted at P ≤ 0.05 (except for in multiple regression, as noted previously). Analyses were performed using SAS Enterprise Guide (version 4.3, SAS Institute Inc., Cary, NC).

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Participants who were enrolled in the present study were a subset of individuals from a larger study (5) who consented to undergo additional testing. The larger study included 28 subjects in each group (24 men and 4 women in each group). The individuals who were part of the larger study but did not participate in the present study had completed all testing for the larger study before the ancillary study started; therefore, they did not have the opportunity to participate. Therefore, the sample for the present study represents half of that for the larger study.

As expected, based on the recruitment of age- and sex-matched subjects for the two groups, mean age and sex were similar in the two groups (Table 1). Body weight, BMI, and body fat levels were higher in CON than that in EX (Table 1). V˙O2max was greater in the EX group, reflecting their exercise-trained status. Despite their leaner phenotype, the EX group had 18% higher habitual energy intake than the CON group. Although fasting and 2-h glucose concentrations were well within the optimal ranges (i.e., <100 and 140 mg·dL−1, respectively) for both groups (Table 1 and Fig. 1), fasting glucose, insulin, and HOMA-IR were lower, and insulin sensitivity index was higher in the EX group than that in CON, indicating better glucoregulatory function in the EX group (Table 1).

Table 1
Table 1
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Figure 1
Figure 1
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OGTT glucose AUC did not differ between groups (P = 0.20, Fig. 1). Insulin AUC was 40% lower in the EX group than that in CON (P = 0.04). No differences between EX and CON were observed for GLP-1 (P = 0.82) or GIP AUC (P = 0.59) (Fig. 1). To explore the possibility that other measures of incretin hormone responses differed between groups, we evaluated the peak postprandial incretin hormone responses, the baseline to peak deltas, and several combinations of postprandial time frames; however, none of these differed between groups (data not shown). Furthermore, the total AUC (vs incremental AUC) did not differ between groups (not shown).

Incretin hormones and insulin AUC were not correlated in the EX group (Fig. 2). However, in the CON group, moderate to strong correlations were observed between the AUC for GLP-1 and insulin (r = 0.53, P = 0.05) and GIP and insulin (r = 0.71, P = 0.004) (Fig. 2). Although the strength of correlation between GLP-1 and insulin in the CON group was not significantly greater (P = 0.26) than that in the EX group, the correlation between GIP and insulin was stronger in the CON group than that in the EX group (P = 0.04). Multiple regression analysis indicated that in the CON group, GIP AUC was a stronger predictor of insulin AUC (partial r2 = 0.49, P = 0.005) than GIP AUC (partial r2 = 0.11, P = 0.11) and that together, GLP-1 and GIP accounted for 60% of the variance in insulin AUC (P = 0.006). As was true for simple correlations, multiple regression indicated that neither GIP AUC nor GLP-1 AUC was a significant predictor of insulin AUC in the EX group. Postprandial GLP-1 and GIP responses were not correlated with body fat percentage or V˙O2max in the EX group (P = 0.29 – 0.97), the CON group (P = 0.38 – 0.98), or both groups combined (P = 0.61 – 0.95).

Figure 2
Figure 2
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Results from the present study show that postprandial incretin hormone levels do not differ between lean exercise-trained individuals with low postprandial insulin levels and inactive, nonobese control subjects who had higher insulin levels. This finding suggests that that the lower insulin levels in lean exercise-trained individuals are not mediated by reductions in circulating incretin hormone concentrations. A secondary finding was that postprandial GLP-1 and GIP levels correlated with postprandial insulin levels in sedentary, control group subjects but not in the exercise-trained individuals. This finding provides preliminary evidence that that exercise training may attenuate the dependency of postprandial insulin secretion on incretin hormones.

Numerous factors other than lower postprandial incretin levels could contribute to the lower insulin levels observed in exercise-trained subjects. First, lower blood glucose concentrations might provide less β-cell stimulus for insulin secretion; however, postprandial glucose levels were not significantly lower in the exercise group in our study. Alternatively, β-cell sensitivity to incretin hormones might be reduced in exercise-trained individuals. To our knowledge, the effect of exercise training on β-cell sensitivity to incretin hormones has not been evaluated; however, the notable lack of correlation between postprandial incretin hormones and postprandial insulin levels in the EX group in our study suggests that the dependency of insulin secretion on incretin hormones may be attenuated by exercise training. Another possible explanation for lower insulin levels in exercise-trained subjects is that β-cell sensitivity to glucose might be reduced. In support of this possibility, studies using a hyperglycemic clamp (11) and a bolus infusion of glucose (19) have shown that insulin secretion during standardized glycemia is lower in exercise-trained subjects. Finally, exercise might also reduce postprandial insulin levels by increasing hepatic insulin clearance; indeed, some research supports this possibility (4).

A key limitation of the present study is that this was a cross-sectional observational study; therefore, unknown factors might have confounded the results. Accordingly, we are currently performing a randomized controlled exercise training trial with more in-depth measures of incretin hormones and incretin effects, which will provide much more definitive evidence. In addition, as part of our current randomized trial, we increased the blood sampling frequency during the early part of the OGTT (i.e., sampling at 0, 10, 20, and 30 min) in case exercise training alters early postprandial incretin hormone responses. Another limitation is that the study groups differed in terms of training status, body composition, and energy intake, which makes it difficult to know which of these factors is responsible for the different correlations that were observed in the two groups. However, because these factors are interdependent, it is not possible to match on all factors simultaneously. For example, matching on body composition would have required control group to have an even lower energy intake relative to the exercise group (i.e., to maintain a lean phenotype in the absence of regular exercise); although this would eliminate between-group differences in body composition, it would exacerbate the mismatch in energy intake. Another limitation is the underrepresentation of women in the study sample. The rationale for this was that subjects were recruited from an existing study that consisted primarily of men. However, the reductions in postprandial insulin levels that result from exercise training are similar in men and women, thus making this sampling issue of lesser concern. Furthermore, although the removal of the women from the statistical analyses reduced the marginally significant correlation (r = 0.53, P = 0.05) between GLP-1 and insulin in the control group to nonsignificant (r = 0.42, P = 0.16), none of the other findings of this study were affected. Finally, although results from our correlation analyses suggest that exercise training might alter the effects of incretin hormones on pancreatic insulin secretion, this evidence is very preliminary, and infusion studies are needed to evaluate the insulin secretory response to “clamped” levels of circulating incretin hormones.

In conclusion, results from the present study suggest that in healthy, nonobese individuals, the insulin-lowering effect of endurance exercise training is not attributable to lower postprandial GLP-1 or GIP concentrations. However, based on the lack of association between postprandial incretin hormone concentrations and insulin in exercise-trained individuals, while moderate to strong associations were observed in the sedentary control group, it seems as though exercise training may attenuate the dependency of insulin secretion on incretin hormones. Although we targeted healthy individuals for the present study to avoid the potentially confounding effects that disease might have on the study outcomes, it is important to note that the results from this study may not apply to individuals with metabolic disease or frank obesity. In addition, future studies are needed to directly evaluate the effect exercise training on pancreatic β-cell sensitivity to incretin hormones.

None of the authors have professional relationships with companies or manufacturers who will benefit from the results of the present study.

This work was supported by the Saint Louis University Beaumont Faculty Development Fund, the Longer Life Foundation, the National Institutes of Health (grant nos. UL1 RR024992 and K01 DK080886), the Istituto Superiore di Sanità/National Institutes of Health Collaboration Program Grant, and the Scott and Annie Appleby Charitable Trust.

The authors are grateful to the study participants for their cooperation and to the staff of the Applied Physiology Laboratory and Nurses of the Clinical Research Unit at Washington University Medical School for their skilled assistance. The study design was developed by EPW, JOH, and LF; data collection was performed and supervised by NKR, JSF, and LF; data analyses and interpretation were performed by EPW, NKR JSF, JOH, and LF; and writing was performed by EPW. All authors provided critical intellectual input on the article and approved of the article in its final form.

None of the authors had conflicts of interest.

Results of the present study do not constitute endorsement by the American College of Sports Medicine.

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