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. Author manuscript; available in PMC: 2015 Jun 1.
Published in final edited form as: Med Sci Sports Exerc. 2014 Jun;46(6):1098–1103. doi: 10.1249/MSS.0000000000000204

Postprandial Plasma Incretin Hormones in Exercise-Trained versus Untrained Subjects

Edward P Weiss 1,2, Nathaniel K Royer 3, Jonathan S Fisher 3, John O Holloszy 2, Luigi Fontana 2,4,5
PMCID: PMC4029861  NIHMSID: NIHMS542359  PMID: 24576859

Abstract

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, non-obese, 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-hr,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·min·1000, 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/L·100, p=0.61) or GIP AUC (19.2±1.4 vs. 18.0±1.4 pg·min/mL·1000; p=0.56). In CON, insulin AUC was correlated with AUCs 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).

Conclusion

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.

Key terms: glucagon-like peptide-1, glucose-dependent insulinotropic polypeptide, insulin sensitivity, glucose tolerance

INTRODUCTION

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 three 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 non-obese 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 in obese individuals. Additionally, 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 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 untrained states.

SUBJECTS AND METHODS

Study Design, Setting, and Participants

The study was a cross-sectional, observational comparison of middle-aged to older individuals who were long term endurance athletes (runners) and age- and sex-matched non-obese 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 (see reference (6) for the first report from the larger study). 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 additional 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, aged ≥40 yr) who performed a minimum of 7 hr/wk of structured vigorous endurance exercise were recruited from the Saint Louis Metropolitan area. These participants averaged 77 km/wk (48 miles/wk) running and had been training for an average of 21 years. 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 US 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. Non-obese (BMI<30 kg/m2), age- and sex-matched individuals who had low levels of physical activity (<1 hr/wk for a minimum of 2 years prior to the study) and were following a typical US 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 mos), 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.

Height, weight, and body composition

Fasted morning height and weight were measured and used to calculate BMI (kg/m2). Body composition was measured by using dual energy X-ray absorptiometry (QDR 1000/w, Hologic, Waltham, MA).

Energy intake

Total energy intake was assessed by the study dietitian using 7-day 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.

Aerobic capacity

Maximal oxygen uptake (VO2max) 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 a heart rate 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 minutes until the subject could no longer continue due to exhaustion. Additional details about this protocol have been published previously (25).

Oral glucose tolerance test

Oral-glucose-tolerance tests (OGTT, 75 g, 2 hr) were performed in the morning after an overnight fast. Subjects habitually consumed ≥150 g/day carbohydrate prior to 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 −80º 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., Saint Charles, MO). 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 (ISI) 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).

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·min·1000 (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 had an effect on incretin hormones.

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 above). Analyses were performed using SAS Enterprise Guide (version 4.3, SAS Institute Inc., Cary, NC).

RESULTS

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 in EX (Table 1). VO2max 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-hr glucose concentrations were well within the optimal ranges (i.e. below 100 and 140 mg/dL, respectively) for both groups (Table 1 and Figure 1), fasting glucose, insulin, and HOMA-IR were lower, and ISI was higher in the EX group than in CON, indicating better glucoregulatory function in the EX group (Table 1).

Table 1.

Characteristics of the study participants.

EX Group CON Group Among group p-value
Sex, n (M/F) 13/1 13/1 1.00
Age, yr 56 ± 9 57 ± 9 0.73
Weight, kg 70.0 ± 7.3 80.9 ± 12.9 0.01
Body mass index, kg/m2 23.1 ± 1.6 25.3 ± 2.3 0.006
Body fat, % 14.6 ± 4.1 23.3 ± 5.9 0.0002
Fat mass, kg 10.2 ± 3.2 18.3 ± 5.0 <0.0001
Fat free mass, kg 59.8 ± 7.0 60.4 ± 9.8 0.87
Energy intake, kcal/d 2911 ± 586 2466 ± 201 0.01
VO2max, L/min 3.74 ± 0.80 2.75 ± 0.69 0.002
VO2max, mL/kg/min 53 ± 8 34 ± 6 <0.0001
Fasting glucose, mg/dL 80 ± 8 94 ± 8 0.07
Fasting insulin, μU/mL* 1.8 ± 0.4 4.2 ± 0.8 0.01
HOMA-IR 0.51 ± 0.20 1.38 ± 0.20 0.02
ISI 18.1 ± 1.8 9.1 ± 1.8 0.001
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Values represent means ± standard deviation or n (for sex). P-values for quantitative data are from independent t-tests. P-value for sex is from a Fisher’s exact test.

*

Fasting insulin data were log transformed for statistical analyses and were back transformed for presentation in this table. VO2max, maximal oxygen uptake; HOMA-IR, homeostasis model assessment of insulin resistance; ISI, insulin sensitivity index.

Figure 1.

Figure 1

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Circulating glucose, insulin and incretin hormone concentrations in response to a 75 g oral glucose load in lean exercise-trained subjects (n=14) and age- and sex-matched sedentary control subjects (n=14). * p≤0.05 for comparisons of means for positive incremental area under the curve (AUC). Units for area under the curve (AUC) data are mg/dL·min for glucose (panel A inset), μU/mL·min for insulin (panel B inset), pmol/L·min for glucagon-like peptide (GLP)-1 (panel C inset), and pg/mL·min for glucose-dependent insulinotropic polypeptide (GIP) (panel D inset).

OGTT glucose AUC did not differ between groups (p=0.20, Figure 1). Insulin AUC was 40% lower in the EX group than in CON (p=0.04). No differences between EX and CON were observed for GLP-1 (p=0.82) or GIP AUCs (p=0.59) (Figure 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 AUCs (vs. incremental AUCs) did not differ between groups (not shown).

GLP-1 and insulin AUCs were not correlated in the EX group (Figure 2). However, in the CON group, moderate to strong correlations were observed between the AUCs for GLP-1 and insulin (r=0.53, p=0.05) and GIP and insulin (r=0.71, p=0.004) (Figure 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 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 VO2max in either the EX group (p-value range, 0.29 – 0.97), the CON group (p-value range, 0.38 – 0.98), or in both groups combined (p-value range, 0.61 – 0.95).

Figure 2.

Figure 2

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Associations between circulating incretin hormones (GLP-1 and GIP AUCs) and insulin AUC in lean exercise-trained subjects (n=14) and age- and sex-matched sedentary control subjects (n=14). Associations were evaluated by using Spearman correlation analyses. The magnitude of correlation between GLP-1 and insulin did not differ between groups (p=0.26, based on fisher’s r-to-z transformation); however, the correlation between GIP and insulin was significantly greater in the CON group than in the EX group (p=0.04).

DISCUSSION

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, non-obese 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 utilizing 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. Additionally, 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); while 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 which 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 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 non-significant (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, non- obese 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 appears as though exercise training may attenuate the dependency of insulin secretion on incretin hormones. While 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. Additionally, future studies are needed to directly evaluate the effect exercise training on pancreatic β cell sensitivity to incretin hormones.

Acknowledgments

We 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; 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. This work was supported by the Saint Louis University Beaumont Faculty Development Fund, the Longer Life Foundation, NIH grants UL1 RR024992 and K01 DK080886. Istituto Superiore di Sanità/NIH Collaboration Program Grant, and the Scott and Annie Appleby Charitable Trust. Results of the present study do not constitute endorsement by ACSM.

Funding/Support: This work was supported by the Saint Louis University Beaumont Faculty Development Fund, the Longer Life Foundation, NIH grants UL1 RR024992 and K01 DK080886. Istituto Superiore di Sanità/NIH Collaboration Program Grant, and the Scott and Annie Appleby Charitable Trust

Footnotes

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

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