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The role of incretins in gestational diabetes: a case-control study on the impact of obesity

Diabetology & Metabolic Syndrome volume 16, Article number: 248 (2024) Cite this article

Abstract

Background

This study aimed to evaluate the role of serum Glucagon-Like Peptide-1 (GLP-1), Glucagon-Like Peptide-2 (GLP-2), and Glucose-Dependent Insulinotropic Polypeptide (GIP) levels in relation to obesity and gestational diabetes mellitus (GDM) in pregnancy.

Methods

A case-control study was conducted, including 96 pregnant women with singleton pregnancies who underwent the Oral Glucose Tolerance Test (OGTT) for GDM diagnosis during the 24th–28th weeks of gestation. Blood samples were collected for measuring GLP-1, GLP-2, GIP, and fasting glucose. Statistical analyses included receiver operating characteristic (ROC) curves and correlation analysis.

Results

Among the 96 women, no significant difference in age was observed between the groups, but Body Mass Index (BMI) was significantly higher in GDM-O (Gestational Diabetes Mellitus-Obese) and non-GDM-O groups (p < 0.001). GLP-1 had an area under the curve (AUC) of 0.666 (95% CI: 0.553–0.778, p = 0.005) for diagnosing GDM. The optimal GLP-1 cutoff was 815.86 ng/mL, with 65% sensitivity and 77% specificity. A significant correlation was found between GLP-2 and GIP (r = 0.289, p = 0.004), but no significant correlations were observed between GLP-1 and other peptides or gestational age (p > 0.05).

Conclusions

Impaired secretion of GLP-1, GLP-2, and GIP likely contributes to the pathogenesis of GDM. GLP-1 may serve as a potential biomarker for diagnosing GDM.

Introduction

The gastrointestinal tract is the largest endocrine organ in the body, producing hormones that regulate body weight and have important signaling and sensitizing roles in energy metabolism [1]. GIP (glucose-dependent insulinotropic polypeptide), GLP-1 (glucagon-like polypeptide-1), and GLP-2 (glucagon-like polypeptide-2) are secreted from the gut and are known as incretin peptides, which together regulate insulin secretion in response to food intake in hyperglycemia. GLP-1 and GIP play an important role in postprandial insulin secretion in healthy subjects. GLP-1 and GLP-2 are degraded by the enzyme dipeptyl peptidase-4 (DPP-4). GLP-1 and DPP-4-based therapies are now widely used in the treatment of type 2 diabetes mellitus [2, 3]. In addition to their effects on insulin hormone, incretins also have effects on glucagon hormone, reduce gastric emptying, and have neuro- and cardioprotective effects [4]. Incretin-based peptide combination therapies are used in the treatment of type 2 diabetes mellitus and are promising in the treatment of obesity. In phase 1 and preclinical studies, GLP-1 multi-agonists have been shown to reduce appetite, eating, and weight gain [5].

Fasting GLP-1 levels are similar in lean and obese subjects [6]. Most of the data show a decrease in postprandial GLP-1 after a meal in obese patients. GLP-1 release is higher in response to carbohydrates than fats in healthy adults. Similar GLP-1 response to fat and carbohydrate has been shown in obesity [4, 7]. DPP-4 activity is responsible for GLP-1 degradation and is higher in obese people, which may cause a decrease in GLP-1 activity leading to a decreased feeling of satiety in obese people [8]. Incretin defects have been shown in the pathogenesis of type 2 diabetes mellitus, the pathophysiology of type 2 DM and gestational diabetes mellitus are similar [9]. Incretins including GLP-1 and GIP may contribute to the mechanisms that compensate for insulin resistance and associated increased blood glucose levels observed in pregnant women, but evidence is conflicting [9, 10]. A study evaluating the role of incretin peptides in islet adaptation during pregnancy, using incretin receptor knockout mice, demonstrated the important role of GLP-1 in pregnancy-induced \(\:\beta\:\)-cell mass expansion, primarily mediated by local GLP-1 production in \(\:\alpha\:\)-cells [11]. However, the study also found that GIP derived from islet or K-cells is not essential for pregnancy-related \(\:\beta\:\)-cell mass expansion. Cypryk et al. [12] observed higher fasting GLP-1 levels in patients with gestational diabetes mellitus (GDM) compared to pregnant women with normal glucose tolerance, while Lencioni et al. reported lower, but not significantly different, GLP-1 levels in women with GDM [13]. Therefore, we plan to evaluate the association of fasting GIP, GLP-1, and GLP-2 with gestational diabetes in obese and non-obese pregnant women.

There are a limited number of studies in the literature on the effects of incretins on the pathophysiology of gestational diabetes [14, 15]. This study aimed to investigate the effect of incretin, which is involved in the etiopathogenesis of gestational diabetes mellitus, which causes many adverse obstetric and neonatal outcomes in pregnancy, and to determine whether obesity has additive effects [16]. According to our literature review, this study is the first study to examine the relationship between incretins and gestational diabetes and to group obese and non-obese patients separately.

Materials and methods

This case-control bi-center study was conducted between 2021 and 2022 in the departments of Obstetrics and Gynecology of Duzce University and Ankara Bilkent City Hospital of Health Sciences University. The protocol of this study was approved by the Duzce University Faculty of Medicine Ethics Committee (Ethics Committee Reference Number:2021/161) and written informed consent was obtained from all the participants. The study included pregnant women with singleton pregnancies aged between 18 and 40 years at the time of GDM diagnosis (24–28 weeks of gestation). Unwillingness or inability to provide written informed consent, medications that can affect glucose metabolism (metformin, glucocorticoids, immunosuppressants, antipsychotics), severe systemic disease (e.g., diabetes mellitus, chronic hypertension, and chronic kidney failure), chronic inflammation, infectious disease, and multi-fetal pregnancy were excluded from this study. Patients were selected among those who agreed to undergo an Oral Glucose Tolerance Test (OGTT) for the diagnosis of GDM. GDM was diagnosed based on a 75-g oral glucose tolerance test (OGTT). Threshold values for diagnosis of GDM recommended by the International Association of Diabetes and Pregnancy Study Group are fasting plasma glucose ≥ 92 mg/dL, 1-h plasma glucose after a 75 g oral glucose load ≥ 180 mg/dL or 2-h plasma glucose after a 75 g oral glucose load ≥ 153 mg/dL. One or more of these values from a 75-g OGTT must be equaled or exceeded for the diagnosis of GDM [17]. Body mass index (BMI) (weight (kg)/height (m2)) was measured at the time of GDM screening. Blood samples for incretin levels (GLP-1, GLP-2, GIP) were collected during the oral glucose tolerance test (OGTT), which was performed between the 24th and 28th weeks of pregnancy. The clinical data collected included maternal age, smoking status, gestational age, height, weight, body mass index (BMI), gestational weight gain, gravidity, parity, live births, miscarriages, systolic and diastolic blood pressure, glucose levels (fasting, 1st hour, and 2nd hour), preterm labor, neonatal weight, APGAR scores (1 and 5 min), intrauterine growth restriction (IUGR), oligohydramnios, polyhydramnios, NICU admissions, insulin use, diet, hypothyroidism, and route of delivery. These parameters were evaluated primarily during the second trimester when the OGTT and incretin measurements were taken and at delivery for neonatal outcomes.

The treatment for women with GDM aimed to achieve optimal glucose levels as per the American Diabetes Association guidelines [18]. Glycemic targets were set at fasting plasma glucose below 95 mg/dL, 1-hour postprandial glucose below 140 mg/dl, or 2-hour postprandial glucose below 120 mg/dl. Nutritional therapy was tailored to increase maternal and fetal health while meeting glycemic goals and appropriate weight gain based on the guidelines. The diet included at least 175 g of carbohydrates, 71 g of protein, and 28 g of fiber, with low saturated fat intake. Weight gain recommendations were 7–12 kg for overweight women and 5–10 kg for obese women. Insulin therapy was started if glycemic targets were not achieved by dietary and lifestyle changes. For women with hypertension, blood pressure management aimed to maintain values below 135/85 mmHg but not lower than 120/80 mmHg to avoid impairing fetal growth. Similar recommendations were made for healthy pregnant women regarding nutrition, weight gain, and blood pressure targets.

Pregnant women were divided into two groups according to the results of OGTT diagnostic tests: pregnant women with gestational diabetes mellitus and pregnant women without glucose tolerance during pregnancy. Pregnant women who were divided into two groups GDM and non-GDM were again divided into 2 groups according to their BMI.

Pregnant women with a BMI above 30 kg/m² were included in the obese group and pregnant women with a BMI of 30 kg/m² were included in the non-obese group. Patients were divided into four groups according to OGTT results and body mass indexes Group 1: obese with gestational diabetes, Group 2: nonobese with gestational diabetes, Group 3: obese pregnant women without glucose tolerance during pregnancy, and Group 4: non-obese pregnant women without glucose tolerance during pregnancy. Fasting GLP-1, GLP-2, and GIP values of pregnant women divided into these 4 groups were compared between the groups.

586 pregnant women were included in the study, 23 of whom did not meet the inclusion criteria. Of the 563 pregnant women who met the inclusion criteria, 13.6% (n = 77) were in the obese GDM group, 4.2% (n = 24) in the non-obese GDM group, 16.3% (n = 92) in the obese non-GDM group and 65.7% (n = 370) in the non-obese non-GDM group. The number of individuals in the groups was randomly generated by the simple random method in accordance with the minimum required sample size and in a balanced manner (Fig. 1).

Fig. 1
figure 1

Flow diagram of study participants

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Serum was obtained by allowing the blood to clot for 30 min, followed by centrifugation at 2000×g for 10 min. Serum samples were immediately aliquoted into single-use tubes and biobanked at − 80 °C. Repeated freeze–thaw cycles were avoided. GLP-1 levels studied using the Human GLP-1 ELISA kit (Sunred Biological Technology, catalog no: 201-12-0023, Shanghai, China), GLP-2 levels studied using (Sunred Biological Technology, catalog no: 201-12-5322, Shanghai, China) and GIP levels studies using Human GIP ELISA kit (Sunred Biological Technology, catalog no: 201-12-0018, Shanghai, China) in accordance with the study procedures specified in the kit catalog. Absorbance measurements were performed on a Multiscan FC Microplate Photometer (Thermo Fisher Scientific, MA, USA) device. The minimum detection limits of GLP-1, GLP-2, and GIP were 0.055 ng/mL, 52.1 ng/mL, and 23.9 ng/mL, respectively. The intra-assay and inter-assay coefficient of variation for GLP-1, GLP-2, and GIP were < 8% and < 10%, respectively.

Statistical analysis

Data were analyzed using SPSS statistics on Windows 21.0 (IBM Corp, Armonk, NY). Quantitative data were expressed as mean +\- standard deviation and median (minimum-maximum) and categorized data were expressed as number (n) and percentage (%). One-way ANOVA test and Kruskal Wallis test were used to compare independent groups, Pearson chi-square test was used to compare categorized variables. Correlation analysis was performed using the Pearson test and Spearman’s rho where appropriate. Data were defined at a 95% confidence level and were considered statistically significant when p < 0.05. Since this was an initial study comparing four groups, the sample size and statistical power calculations were not performed prior to starting the investigation. However, a post-hoc analysis of the data from 24 patients in each group showed that the study had a statistical power of 0.80. This was calculated using an effect size of 0.75 and an alpha significance level of 0.05.

Results

Demographic and clinical data of the groups are given in Table 1.

Table 1 Demographic and clinical data of the groups
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The mean age was 30.8, 30.5, 27, 28.3 in the groups respectively. There was no difference between the groups in terms of age. BMI was significantly higher in GDM-O and non-GDM-O groups (p < 0.001). Weight gain during pregnancy was similar between the groups Gravidity, Parity, Live-birth, Miscarriage, D&C, and systolic blood pressure were similar between the groups (p > 0.05). Diastolic blood pressure was significantly higher in obese groups compared to non-obese groups. Fasting glucose, first and second-hour glucose levels were significantly higher in GDM-O and GDM-Non-O groups compared to non-GDM groups. There was no significant difference between the groups in terms of GLP-2 and GIP. GLP-1 levels were significantly higher in GDM-O and GDM-non-O groups compared to non-GDM groups (Fig. 2).

Fig. 2
figure 2

Serum GLP-1 levels in all groups

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We compared obstetric and neonatal outcomes across the four groups. The use of insulin and diet modification was significantly higher in the Obese GDM group (p < 0.001). Cesarean rates were comparable across groups (p = 0.340), but indications for cesarean varied significantly, with higher rates of gestational hypertension and macrosomia in the Obese GDM group (p = 0.012). Preterm labor occurred more frequently in the Obese GDM group however no statistical difference was found(p = 0.080). Neonatal outcomes showed significant differences in APGAR scores at 1 and 5 min (p = 0.001 and p = 0.003, respectively), with higher NICU admissions in both GDM groups (p = 0.002). Polyhydramnios was more common in the Obese GDM group (p = 0.038), while other complications like IUGR and oligohydramnios were not significantly different between groups. Neonatal weight was comparable across all groups (p = 0.685) Obstetric and neonatal outcomes of patients are given on Table 2).

Table 2 Obstetric and neonatal outcomes of the groups
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Table 3 Diagnostic performance of GLP 1 for diagnosing gestational diabetes mellitus
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ROC analysis revealed that GLP-1 had high sensitivity and specificity to define GDM (area under the curve (AUC):0.666 and 95% confidence interval (CI): 0.553–0.778) (p = 0.005). However, GLP-2 and GIP had low sensitivity for GDM. ROC analysis is shown in Fig. 3.

Fig. 3
figure 3

Receiver operating characteristic (ROC) curve for GLP-1 in predicting gestational diabetes mellitus

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The optimal cut off level of maternal GLP-1 was 815.86 with 65% sensitivity and 77% specificity. The diagnostic performance of GLP-1 for diagnosing gestational diabetes mellitus (GDM) is detailed in the Table 3. The overall fraction correct, often referred to as “accuracy,” stands at 0.708, indicating a moderately accurate diagnostic capability. The mis-classification rate is noted at 0.292, suggesting that approximately 29.2% of cases are incorrectly classified. Sensitivity, which measures the ability to identify true positives, is 0.646, indicating that 64.6% of actual GDM cases are correctly identified. Specificity, measuring the ability to identify true negatives, is 0.771, indicating that 77.1% of non-GDM cases are correctly identified. The diagnostic odds ratio, a measure of the effectiveness of a diagnostic test, is calculated as 6.134, showing that GLP-1 has a moderately favorable diagnostic performance for GDM when considering both sensitivity and specificity.

Correlation analysis revealed that there was a significant association between GLP2 and GIP (r:0,289 p:0,004). The correlation between serum GLP-2 and GIP concentrations was shown in Fig. 4. No association was found between GLP1-GPL2, GLP1-gestational age, GLP2-gestational age and GLP1-GIP (p > 0.05).

Fig. 4
figure 4

The correlation between serum GLP-2 and GIP concentrations

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Discussion

In the current study, we found that fasting GLP-1 levels were higher in GDM patients compared to those with normal glucose tolerance. However, this conclusion is based on a single measurement and may not reflect changes throughout pregnancy. Furthermore, GLP-2 and GIP levels showed a significant correlation in the study population investigated.

Following the demonstration for nearly five decades that oral glucose ingestion releases more insulin than intravenous glucose ingestion, efforts to identify incretin peptides began [19]. The discovery of GIP was the first to show that glucose-stimulated insulin release was markedly potentiated. However, as the evidence increased, it was shown that the incretin effect was partially attenuated even after immunoneutralization of GIP, indicating that GIP is not the only intestinal-derived incretin [20, 21].

Incretins have gained importance after the favorable effects of procedures in bariatric surgery on glucose homeostasis and the development of metabolic syndrome [22, 23]. The incretin effect is of great importance for normal glucose tolerance [23]. However, the exact roles and importance of gut-derived peptides under physiological conditions are still controversial. Initial studies focused only on GIP and GLP-1, but nowadays the effects of other derivative peptides are also of interest.

Decreased fasting GIP and GLP-1 levels have been associated with worsening fasting glucose levels in patients with type 2 DM and it has been suggested that basal GIP and GLP-1 may be useful in the early diagnosis of type 2 DM [24]. Although the pathophysiology of decreased GLP-1 release is still controversial, long-term type 2 diabetes and inadequate glycemic control seem to be associated with low GLP-1 responses, while studies evaluating the effects of GIP and GLP-1 in the development of gestational diabetes mellitus present conflicting results [25, 26].

In the literature, some studies indicate that fasting levels of both GLP-1 and GIP are lower in patients with gestational diabetes mellitus (GDM), with low GLP-1 levels being associated with a higher risk of developing GDM [13, 27]. Specifically, research has shown that Asian-Indian women with GDM exhibit high insulin resistance, islet cell dysfunction, and low fasting GLP-1 levels. Incretin axis dysfunction may contribute to this islet cell dysfunction [28]. Early diagnosis, multidisciplinary care, and tailored management with optimal glycemic control are linked to a significant reduction in pregnancy complications as well as long-term consequences for both the mother and the offspring [29].

However, while some studies have reported increased GLP-1 and GIP secretion during oral glucose tolerance tests (OGTT) in women with GDM [15], other research suggests that GLP-1 and GIP levels are not impaired during OGTT in these patients [12]. The discrepancy in results has been attributed to differences in sample sizes used in these studies [12, 13, 30]. In our study, basal GLP-1 levels were found to be elevated in patients with GDM. GLP-1 demonstrated high sensitivity (70%) and specificity (56%) in identifying GDM.

Some human studies on obesity have shown increased levels of GLP-1 and to a lesser degree GIP after diet-induced weight loss, but not all studies showed this effect [23, 31]. GDM and obesity are associated with poor postprandial gut hormone response, impaired satiety, and weight gain [32]; GLP-1 has been implicated in the regulation of blood glucose elevation and insulin resistance in pregnancy, suggesting a role in maternal metabolism and weight gain [27].

In the literature, a study conducted in non-pregnant obese diabetic patients showed impaired insulinotropic effect of GIP and suggested that this impairment may be an important factor in the pathophysiology of GDM [33]. In our study, we think that GLP-1, GLP-2, and GIP are associated with the pathophysiology of GDM.

Based on the available data, changes in incretin levels may play a role in the compensation of insulin resistance in pregnancy. Assessing GLP-1 function in GDM may be an early detection parameter that can be used to plan appropriate follow-up and treatment timing. However, there is only one recent study by Krystynik et al. (2023), no significant differences were found in fasting GLP-1 and GIP concentrations or their AUC between pregnant women with impaired fasting plasma glucose, despite significant variations in BMI values among the groups [34]. Our study showed that basal GLP-1 concentrations were higher in GDM patients especially in obese group. We believe that our study, being the first in its field to differentiate between obese and non-obese pregnant women in terms of GDM presence, is more valuable and will guide future research.

The great interest attracted by GLP-1 and GIP as potent incretins has partially overshadowed efforts to understand the importance of other proglucagon-derived peptides. In contrast to the insulinotropic effects of GLP-1, GLP-2 increases glucagon levels in fasting and postprandial states [35], the main effect of GLP-2 is to reduce intestinal permeability, enhance barrier function, and improve digestion and absorption of nutrients by inhibiting gastrointestinal motility [36].

In the literature, it has been shown that there is a correlation between insulin resistance and GLP-2 secretion in obese individuals [37], while later studies have suggested that it may be the cause of insulin resistance in healthy and diabetic individuals due to its glucagonotropic effect [38, 39]. In addition, animal studies have shown that GLP-2 secretion in the ileum decreases under diabetic conditions [40]. Therefore, it is thought that decreased GLP-2 production may lead to the development of diabetes. The fact that plasma GLP-2 concentrations are higher in obese patients without type 2 diabetes compared to healthy people suggests that GLP-2 functions as a protective factor against glucose metabolism disorder that develops in obesity [21].

The fact that plasma GLP-2 concentrations are higher in obese patients without type 2 diabetes compared to healthy people suggests that GLP-2 functions as a protective factor against glucose metabolism disorder that develops in obesity [21]. In a single and recent study examining the relationship between GLP-2 and GDM, it was suggested that GLP-2 may be associated with weight gain during pregnancy [41], while in our study, GLP-2 was found to be significantly associated with the development of GDM risk. However, the sensitivity and specificity of GLP-2 in the development of GDM were found to be low.

Incretin test results can be influenced by fasting conditions. In a study during the second trimester, postprandial GLP-1 and GIP concentrations were compared between women with gestational diabetes mellitus (GDM) and normal glucose tolerance. Women with GDM had approximately 20% higher postload GLP-1 and GIP concentrations, independent of age, BMI, and gestational age [15]. The increase in GLP-1 was specifically associated with insulin secretion only in women with GDM. Postprandial GLP-1 levels were negatively correlated with birth weight. These findings suggest that women with GDM have elevated postprandial GLP-1 and GIP concentrations, potentially related to insulin secretion. Furthermore, there is a potential role of GLP-1 in fetal growth regulation [15]. When O’Malley et al. compared fasting GLP-1 and GIP measurements in the second trimester according to the presence of obesity, they found that GLP-1 was significantly higher in those with obesity at the first visit, but this difference was not observed in the GDM groups [42]. However, in the study of Bonde et al., which involved participants in the second trimester and postpartum period, the researchers compared postprandial GLP-1 responses between patients with gestational diabetes mellitus (GDM) and their postpartum levels. The results showed that pregnancy was associated with decreased postprandial GLP-1 responses, and patients with GDM had even lower GLP-1 responses compared to their postpartum levels [43]. Another study comparing fasting and postprandial GLP-1 concentrations with plasma insulin and glucose levels found that fasting GLP-1 concentrations were associated with insulin levels, but not with glucose levels. During the oral glucose tolerance test (OGTT), GLP-1 concentrations were associated with insulin levels, but not with glucose levels. No significant associations were found between GIP concentrations and insulin or glucose levels. Additionally, BMI at the time of the OGTT was positively correlated with fasting GLP-1 concentrations. These findings highlight the relationship between GLP-1, insulin, and BMI in glucose metabolism during the second trimester of pregnancy [11].

Overall, the studies provide insights into the concentrations of GLP-1 and GIP in pregnant women with impaired glucose metabolism. While some studies observed significant differences in GLP-1 concentrations between GDM and non-GDM groups, others did not find significant differences. The association between GLP-1 concentrations and insulin or glucose levels varied across studies. Additionally, BMI was found to be associated with GLP-1 concentrations in some studies. However, further research is needed to establish the exact mechanisms and clinical implications of these associations.

An important advantage of our study is that neither the pregnant women nor the research team were aware of GDM status at the time of serum sampling, which minimizes selection bias. Another strength of the study is that very careful sampling was performed to accurately optimize the concentrations of GLP-1,2 and GIP and the results are potentially reproducible.

This study highlights the potential significance of incretin hormones, particularly GLP-1, in the pathophysiology of gestational diabetes mellitus (GDM). Our findings suggest that GLP-1 could be used as a potential biomarker for the diagnosis of GDM. The observed increase in GLP-1 levels in pregnant women with GDM indicate that this hormone may serve as a clinical tool for early diagnosis or management of the condition. Furthermore, investigating GLP-1-targeted therapies in women with GDM may open new avenues for disease management.

This study has some limitations that need to be taken into account. First, the patient population is small, primarily due to the high costs of the tests used. In addition, population matching in terms of age, sex, and BMI is not perfect. Since our study was conducted in the mid-trimester when insulin resistance becomes evident, the lack of evaluation of incretin in the postpartum period limits the power of the study. Another limitation is that there was no measurement of incretin hormones earlier in the pregnancy, which might also affect individual levels as pregnancy progresses. In this study, GLP-1,2 and GIP responses after oral glucose loading were not evaluated when comparing normal glucose tolerance and GDM in pregnant women. The baseline measurement of incretin concentrations may not be the optimal time to assess incretin function, which limits this study. Incretin hormones are also more expensive to use as a screenin/diagnostic tool than the OGTT test, but the test may become cheaper in the future and could be used in patients who do not want or cannot tolerate the test.

Incretins play an important role in glucose homeostasis by reducing insulin resistance and increasing insulin release. New evidence emphasizes the importance of incretins in improving glycemic control and insulin sensitivity, especially in conditions associated with obesity. To date, results from human studies are conflicting.

Conclusion

This study the potential role of GLP-1 as a biomarker in diagnosing gestational diabetes mellitus (GDM), with higher levels observed in GDM patients. The findings suggest that GLP-1 may also serve as a target for future therapeutic interventions in the management of GDM.

These findings contribute to our understanding of the role of these hormones in pregnancy and may have implications for future research in this area.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Abbreviations

GLP-1:

Glucagon-Like Peptide-1

GLP-2:

Glucagon-Like Peptide-2

GIP:

Glucose-Dependent Insulinotropic Polypeptide

OGTT:

Oral Glucose Tolerance Test

GDM:

Gestational Diabetes Mellitus

ROC:

Receiver Operating Characteristic

AUC:

Area Under the Curve

DM:

Diabetes Mellitus

DPP-4:

Dipeptyl Peptidase-4

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Acknowledgements

The authors are grateful for all the participants in the study.

Funding

The funding for this study has been provided by the Scientific Research Projects Coordination Office of Duzce University (grant No. 2021.04.02.1261).

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Authors and Affiliations

  1. Department of Gynecology and Obstetrics, Faculty of Medicine, Duzce University, Merkez/Düzce, 81620, Turkey

    Engin Yurtcu, Betul Keyif, Gamze Yilmaz & Selcuk Erkilinc

  2. Department of Gynecology and Obstetrics, Ankara Bilkent City Hospital, Ankara, Turkey

    Betul Keyif, Gamze Yilmaz & Selcuk Erkilinc

  3. Department of Gynecology and Obstetrics, Faculty of Medicine, Izmir Demokrasi University, İzmir, Turkey

    Betul Keyif, Gamze Yilmaz & Selcuk Erkilinc

  4. Department of Obstetrics and Gynecology, University of Health Sciences, Ankara Bilkent City Hospital, Ankara, Turkey

    Hatice Akkaya & A. Seval Ozgu-Erdinc

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  1. Engin Yurtcu
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Contributions

Conceptualization, E.Y. and B.K.; methodology, E.Y. and A.S.O.E.; formal analysis, E.Y. investigation, G.Y.; data curation, E.Y. and B.K.; writing—original draft preparation, E.Y., B.K. and H.A.; writing—review and editing, E.Y., A.S.O.E.; visualization, S.E.; supervision, E.Y. and B.K.; project administration, E.Y. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Engin Yurtcu.

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Ethical approval

The protocol of this study was approved by the Duzce University Faculty of Medicine Ethics Committee (Ethics Committee Reference Number:2021/161) and written informed consent was obtained from all the participants.

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Not applicable.

Competing interests

The authors declare no competing interests.

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Yurtcu, E., Keyif, B., Yilmaz, G. et al. The role of incretins in gestational diabetes: a case-control study on the impact of obesity. Diabetol Metab Syndr 16, 248 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13098-024-01483-w

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Keywords

Diabetology & Metabolic Syndrome

ISSN: 1758-5996

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