Design and rationale for the SIB trial: a randomized parallel comparison of semaglutide versus placebo on intestinal barrier function in type 2 diabetes mellitus

Abstract

Objective:

To describe the rationale and design of the SIB trial, an interventional clinical trial testing the hypothesis that subcutaneous (s.c.) once-weekly semaglutide can improve intestinal permeability and reduce systemic inflammation in participants with type 2 diabetes (T2D) and obesity.

Methods:

SIB (NCT04979130) is an investigator-initiated, single-center randomized, double-blinded, placebo-controlled clinical study being conducted at the University of Colorado Anschutz Medical Campus. The primary objective of this novel trial is to test the hypothesis that subcutaneous (s.c.) once-weekly semaglutide could improve intestinal permeability and reduce systemic inflammation in participants with T2D and obesity. Eligible participants had a diagnosis of type 2 diabetes, elevated body mass index, and evidence of systemic inflammation. Participants were randomized 1:1 to s.c. semaglutide or placebo. Participants were assessed for intestinal permeability and markers of inflammation at baseline, mid-study, and at the end of the study. Efficacy assessments were based on the analysis of the following: lactulose:mannitol ratio test, serum lipopolysaccharide-binding protein (LBP), fecal calprotectin, inflammatory biomarkers (IL-6, TNF, IL-1, IL-8, hs-CRP), and HbA1c. All participants who enrolled in the trial provided written informed consent after having received written and oral information on the trial. The risks of semaglutide use were minimized by administration according to FDA-labeled use and close monitoring for adverse events.

Discussion:

SIB is the first study to examine the effects of GLP-1 receptor agonists on intestinal permeability in humans and will provide important data on their impact on systemic inflammation and intestinal permeability in the setting of T2D and obesity.

Keywords

diabetes mellitus type 2 intestinal permeability semaglutide systemic inflammation

Introduction

Type 2 diabetes (T2D) and obesity are associated with chronic, subclinical systemic inflammation.^1–3 Additionally, patients with T2D have a two-fold increased risk of cardiovascular disease (CVD, i.e. myocardial infarction, stroke, and peripheral vascular disease) compared to the general population.⁴ It is thought that this chronic inflammation may be responsible for cardiovascular events in people with diabetes.⁵ It is important to identify the cause of this inflammation in order to better direct clinical interventions for T2D and the prevention and treatment of associated cardiovascular complications.

It has been proposed that increased intestinal permeability, or ‘leaky gut’, may contribute to inflammation by allowing the passage of undesirable luminal contents such as toxins, food, and bacterial antigens through the intestinal barrier into the circulation, thus activating the immune system.⁶ The intestinal barrier primarily consists of the epithelial cell layer, along with immunoglobulins, mucous, and defensins, with the purpose of preventing unwanted luminal products from entering the body.⁷

Animal studies have suggested that impaired intestinal barrier function and shifts in intestinal microbiota may result in inflammation and insulin resistance in obesity.^8–10 In murine studies, mice that lack functional lipopolysaccharide (LPS) receptors (CD14 knockout mice) are resistant to diet-induced obesity and related disorders. LPS binds to toll-like receptor 4 (TLR-4) on macrophages and adipocytes with the help of CD14 and LPS-binding protein (LBP), resulting in the release of pro-inflammatory cytokines and ultimately leading to insulin resistance.^11,12 Furthermore, chronic subcutaneous infusion of LPS (mimicking metabolic endotoxemia) induces significant inflammation and insulin resistance to a similar extent as observed following high-fat feeding.⁸ Murine studies also suggest a regulatory role for the intestinal microbiota. Significant shifts in bacterial populations in the gut are associated with increased intestinal permeability and insulin resistance in high-fat diet fed mice, while antibiotics can ameliorate these changes.^9,10

There are limited data on intestinal permeability in diabetes and metabolic disorders in humans. Increased intestinal permeability has been reported in individuals with metabolic syndrome, obesity, non-alcoholic fatty liver disease (NAFLD), and diabetes.^13,14 Intestinal permeability decreased by approximately 50% after weight loss in morbidly obese subjects with NAFLD.¹³ Impaired intestinal function also has been seen in type 1 diabetes and is believed to facilitate increased exposure to antigens that can trigger autoimmune destruction of beta cells.¹⁴

Assessment of intestinal barrier function can be conducted with the use of orally administered probes as well as blood and fecal markers of impaired intestinal permeability. Small saccharide probes, which are not supposed to cross the intestinal barrier, have been used to evaluate intestinal permeability.¹⁵ The lactulose:mannitol ratio (LMR) in recovered urine is the most common assessment of intestinal permeability. Lactulose is a relatively large molecule that is poorly absorbed across a healthy intestinal epithelium. Of note, different probes measure the permeability of different regions of the gastrointestinal tract (Figure 1). Lactulose measures small intestine permeability. In the setting of epithelial damage, there is increased paracellular movement of lactulose across the intestinal epithelium.^14,16,17 Thus, it is considered a marker of intestinal barrier integrity. Mannitol, which is a smaller molecule, crosses via the pore pathway, which allows for passage of sodium ions, water, and small solutes.^18,19 The LMR recovered in urine collected within 6 h after the ingestion of the dual sugar predominantly reflects small intestine permeability. Urine lactulose levels increase with intestinal epithelial damage while urine mannitol should remain the same, thus an increased LMR is correlated with increased intestinal permeability.^7,20

Figure 1.

Zones of absorption along the gastrointestinal tract for commonly used intestinal permeability probes: sucrose, lactulose mannitol, sucralose and Cr-EDTA.

In a study of 48 males with diabetes mellitus who were administered an oral sugar solution containing lactulose and L-rhamnose, a monosaccharide substituted for mannitol, after an overnight fast, Mooradian et al. demonstrated a significant increase in urine lactulose and L-rhamnose excretion in diabetes compared to healthy controls suggesting increase passive movement of sugars across the intestinal barrier.²¹ Although this indicates impaired intestinal permeability, it is of note the LMR between diabetic subjects and healthy controls in this study showed no difference likely as a result of the increased passive movement of both sugars across the intestinal mucosa altering LMR values.²¹

Blood and fecal biomarkers have also been used to measure intestinal permeability. Zonulin is a protein that modulates the intercellular tight junctions of the intestinal epithelium and has been determined to be a marker of impaired intestinal barrier function.^22,23 Serum zonulin levels were revealed to be increased in correlation with obesity and insulin intolerance in a study of Caucasian males.²³ Zonulin is released from multiple tissue types and is one of more than 50 proteins involved in the regulation of the intercellular tight junctions.²⁴ Furthermore, calprotectin is produced by neutrophils and crosses the intestinal barrier into the gut during the inflammatory process and can be utilized as a marker of gut inflammation.²⁵ Fecal calprotectin levels positively correlated with markers of intestinal permeability in individuals with inflammatory bowel diseases (IBDs).^26–28 Several studies have reported increased blood levels of gut microbiota-derived LPS in individuals with diabetes, referred to as metabolic endotoxemia.²⁹ LBP binds to LPS and leads to activation of the body’s immune system and release of proinflammatory cytokines.³⁰ LBP has a longer half-life than LPS in blood; therefore, the serum LBP concentration is a stable indicator of exposure to LPS and intestinal permeability.³⁰ In a cross-sectional study of subjects with T2D, mean serum LBP was significantly elevated and correlated with body mass index (BMI), insulin resistance, triglyceride and C-reactive protein (CRP) levels suggesting that T2D might cause altered intestinal permeability.³¹ Additionally, elevated LBP levels correlated with arterial stiffness independent of obesity and traditional cardiovascular risk factors.³² These studies suggest that metabolic endotoxemia may contribute to the pathogenesis of insulin resistance and CVD through chronic, low-grade systemic inflammation.

Rationale for use of GLP-1 agonists

Interventions that could improve intestinal barrier integrity may decrease chronic inflammation and the risk for diabetes and its complications, including CVD. Glucagon-like peptide 1 (GLP-1) receptor agonists cause weight loss and reduce inflammatory markers, in addition to their glucose-lowering effects.³³ The anti-inflammatory effects of GLP-1 receptor agonists seem to extend beyond their weight loss properties. Mechanisms, such as inhibiting macrophage infiltration and decreasing cytokine secretion, have been proposed as direct effects of GLP-1 receptor agonists on the immune system.^34,35 GLP-1 has been shown to improve intestinal barrier function by decreasing intestinal inflammation and expediting mucosal healing in vitro and in animal models.³⁶ Additionally, GLP-1 receptor agonists have been shown to modulate the gut microbiota in a metabolically favorable way.³⁷ It was shown for the first time in humans that fasting GLP-1 increased after chemotherapy and the level correlated with CRP levels suggesting that GLP-1 may play a role in regulation of mucosal defenses.³⁸ The direct effect of GLP-1 receptor agonists on intestinal barrier function may be the mechanism for their anti-inflammatory effects. There are no data on the effects of GLP-1 receptor agonists on intestinal permeability in humans. Investigating the influence of GLP-1 receptor agonists on intestinal barrier function could shed light on the protective mechanism of action of GLP-1 receptor agonists and their anti-inflammatory and cardioprotective properties. If successful, this work may also support the feasibility of other interventions to improve intestinal barrier function, resulting in reduced chronic inflammation and decreasing the risk for T2D and CVD.

The SIB trial is a randomized controlled trial designed to evaluate the effects of a GLP-1 receptor agonist on intestinal barrier function. We investigated the effects of subcutaneous (s.c.) once weekly semaglutide as compared to placebo on intestinal permeability and chronic inflammation in patients with T2D treated only with metformin. The trial is a randomized, double-blinded, placebo-controlled trial to minimize bias. Participants with moderately controlled glycemia (HbA1c <8.5%) were enrolled to minimize the need for rescue medication in the placebo arm and to reduce the possible confounding effect of a dramatic improvement in glycemic control.

Materials and methods

Study design and population

The SIB trial (NCT04979130) is an investigator-initiated study. The study design and protocol were developed by the principal investigator’s team and funded by Novo Nordisk. It is a single-center randomized, double-blinded, placebo-controlled clinical trial conducted at the University of Colorado Anschutz Medical Campus. Participants were randomized to once-weekly s.c. semaglutide or matching placebo.

Overweight or obese individuals with T2D on metformin monotherapy were recruited in the study. To enrich the population at risk for impaired intestinal permeability, only those with hs-CRP >1 mg/L, as a marker of chronic inflammation, were included.³⁹ Subjects with signs of acute inflammation (i.e. hs-CRP > 10) or those taking any medication or supplements affecting intestinal permeability were excluded. Participants with poor glycemic control (A1c > 8.5%) were not randomized to minimize the need for rescue medication for hyperglycemia during the trial which might interfere with the outcomes of the study (Table 1).

Table 1.

Inclusion and exclusion criteria for the SIB trial.

Inclusion criteria:

1. Male or female, age above or equal to 18 years at the time of signing informed consent.
2. Diagnosed with T2D mellitus on metformin monotherapy
3. Hemoglobin A1c <8.0% (<64 mmol/mol) on screening day
4. Body mass index ⩾28 kg/m²
5. Low-grade inflammation, defined as elevated high sensitivity C-reactive protein (hs-I CRP >1.0 and ⩽10 mg/L).

Exclusion criteria:

1. Known or suspected hypersensitivity to trial product or related products
2. Female who is pregnant, breast-feeding or intends to become pregnant or is of child-bearing potential and not using a highly effective contraceptive method
3. Participation in any clinical trial of an approved or non-approved investigational medicinal product within 30 days before screening
4. Any disorder, which in the investigator’s opinion might jeopardize patient’s safety or compliance with the protocol
5. Any of the following: myocardial infarction, stroke, hospitalization for unstable angina pectoris or transient ischemic attack within the past 60 days prior to the day of screening
6. Second anti-diabetic agent use within 3 months of screening
7. Chronic kidney disease defined as eGFR <30 mL/min/1.73 m²
8. C-reactive protein (hs-CRP >10.0 mg/L) to eliminate patients with acute inflammatory process at the time of screening
9. Any recent infection or antibiotic use within 3 weeks
10. Regular use (more than a week duration) of anti-inflammatory medication (steroid or NSAIDs) within 3 months of screening
11. Regular use (more than a week duration) of any digestive health supplements, such as probiotics or prebiotics within 3 months screening
12. Diagnosis of chronic intestinal inflammatory disease such as Crohn’s disease, ulcerative colitis or irritable bowel syndrome
13. Prior bariatric or bowel surgery
14. Heart failure presently classified as being in New York Heart Association Class IV
15. Presence or history of malignant neoplasm within 5 years prior to the day of screening. Basal and squamous cell skin cancer and any carcinoma in situ is allowed
16. Personal or family history of multiple endocrine neoplasia type 2 or medullary thyroid carcinoma
17. History of chronic pancreatitis or history of acute pancreatitis within 6 months of screening
18. Chronic consumption of >2 alcoholic standard drinks per day

Eligible individuals who provided informed consent were entered to a screening period of not more than 4 weeks. Individuals were randomized in a 1:1 ratio to either semaglutide 0.5 mg or matching placebo once weekly for 16 weeks. A 16-week time period was adapted from the rapid reduction in HbA1c observed in the SUSTAIN 6 trial and is thought to provide sufficient time observe the effects of semaglutide.⁴⁰ Patients were expected to start study medication on the day of randomization. Participants were instructed to up-titrate study medication to 1 mg weekly in accordance with FDA-labeled use. Titration were adjusted based on the individual participant’s tolerance and PI’s discretion. To maximize retention and compliance and to optimize treatment and safety, participants in both treatment groups were met with study staff every 4 weeks post-randomization for 16 weeks to assess tolerance and compliance to study medication and adverse events. Markers of intestinal permeability and inflammation were collected at baseline, 8 weeks, and 16 weeks after randomization. A summary of events occurring at each study visit are summarized in Table 2. The trial used a commercially available LMR test kit (Genova Diagnostics, Asheville, NC, USA) which included a concentrate containing 5 g lactulose, 1 g mannitol, 8 mL glycerin, and water, and tubes for urine collection. Measurements of fecal calprotectin, serum zonulin, LBP, and biomarkers of inflammation were conducted by the University of Colorado. Patients remained in the study for observation for 4 weeks until the final dose of study medication or 16 total weeks, whichever is longer.

Table 2.

Visit summary.

Visits	Screening at visit 1	Randomization at visit 2	Visit 3	Visit 4	Visit 5 (Phone)	Visit 6	Visit 7 (Phone)
Week (visit window)	−2 (+/-1 week)	0 (+/-3 days)	4 (+/-3 days)	8 (+/-3 days)	12 (+/-3 days)	16 (+/-3 days)	20 (+/-3 days)
Informed consent	X
Medical history	X
AE evaluation		X	X	X	X	X	X
Concomitant medication	X	X	X	X	X	X	X
A1C	X
hs-CRP	X			X		X
CMP	X
Lipid profile		X				X
Urine pregnancy test	X
Lactulose/mannitol test		X		X		X
Serum zonulin		X				X
Fecal calprotectin*		X				X
LBP		X				X
IL-6		X				X
Stool sample collection for biobanking*		X				X
Blood sample for biobanking		X		X		X
Dispense medication		X	X	X
Dose up-titration			X	X

Fecal collection kit will be given to subjects at the prior visit to bring collected sample to the visit.

Study objectives and endpoints

The primary objective is to investigate the effects of short-term treatment (16 weeks) of semaglutide as compared to placebo on intestinal permeability in subjects with T2D. The study additionally investigated the effects of short-term treatment of semaglutide as compared to placebo on chronic inflammation, and the interaction of changes in intestinal permeability with chronic inflammation, weight loss, and glycemic control. The primary endpoint is comparing the difference in the LMR between treatment groups at 16 weeks. Secondary endpoints include comparing differences between treatment groups in other markers of intestinal permeability, such as LBP, serum zonulin, and fecal calprotectin, and differences in markers of chronic inflammation at 16 weeks. Additionally, we compared differences between treatment groups in intestinal permeability and inflammation markers at the midpoint of intervention (8 weeks).

Statistical considerations

Sample size and power calculations

There is no previous study evaluating intestinal permeability using LMR in patients with T2D. All studies that have used LMR to evaluate intestinal permeability in a similar population to T2D have been summarized in Table 3. We assumed subjects with T2D on metformin monotherapy have similar LMR values to morbidly obese patients without metabolic syndrome. Morbidly obese subjects with metabolic syndrome or subjects with NAFLD had higher LMR (i.e. worse intestinal barrier function). Therefore, we chose a more conservative value for our baseline estimate. Based on previous studies, we assumed the mean LMR = 0.062 with standard deviation = 0.0208 for both groups at baseline.¹³ Then, we assume the placebo group mean does not change (still equals 0.062) at 16 weeks, and the standard deviation of LMR was 0.0208 for both groups. With 80% power and significance level α = 0.05, a sample size of N = 21 per group was needed to detect a 30% difference (0.062 versus 0.0434) in mean LMR between the two groups at 16 weeks (Table 4).

Table 3.

Summary of studies evaluating intestinal permeability using LMR in patients with T1D, obesity, and NAFLD.

Ref	Design	Cohort	Results	% diff
de La Serre et al.⁹	Weight loss (23 kg) BMI = 43	Obese and NAFLD n = 13	0.080 (0.073, 0.093)–0.027 (0.024, 0.034)	Decreased by 66%
de La Serre et al.⁹	Cross sectional	Steatosis grade 2 (n = 13) versus no steatosis (n = 6)	0.080 (0.070, 0.091) versus 0.035 (0.029, 0.038)	Higher by 56%
de La Serre et al.⁹	Cross sectional	With MS (n = 18) versus no MS (n = 9)	0.079 (0.064, 0.088) versus 0.062 (0.042, 0.074)	Higher by 22%
Lam et al.¹⁰	Cross sectional	T1D (n = 46) versus control (n = 23)	0.038 (0.005−0.176) versus 0.014 (0.004−0.027)	Higher by 63%

BMI, Body mass index; LMR, lactulose:mannitol ratio; MS, multiple sclerosis; NAFLD, non-alcoholic fatty liver disease; T1D, Type 1 diabetes.

Table 4.

Required sample size for comparing mean LMR between both treatment groups at 16 weeks, 2-sample independent t-test with 80% power, significance level α = 0.05, standard deviation = 0.0208 for both groups, control mean = 0.062.

LMR, lactulose:mannitol ratio.

Color shade of green shows the sample size of 21 participants per group required to detect a 30% difference in mean LMR at 16 weeks with 80% power. Our study plans for a minimum 21 participants each for treatment arm and placebo.

A prior study was used for estimating the baseline mean (0.062) and standard deviation (0.0208) of LMR in the sample size and power analysis.¹³ However, it is possible that these assumptions may be inaccurate for the current study population. To address this, we used the blinded interim sample size re-estimation procedure of Kieser and Friede.⁴¹ When 50% of subjects completed the study (N = 21), we re-estimated the baseline mean and standard deviation of LMR on the entire sample blinded to treatment assignment. The previous sample size estimation was then repeated using these new estimates of the baseline mean and standard deviation of LMR. Importantly, this interim sample size re-estimation procedure maintains blinding to treatment assignment, and does not require any adjustment to the final p-values computed at the end of the study.

Statistical plan

The primary outcome was the difference in mean LMR between the semaglutide and placebo groups at 16 weeks. As recommended by Senn 2006, ANCOVA was used to assess differences in LMR between the two groups at 16 weeks while adjusting for baseline LMR.⁴² Paired t-tests was used to assess the within group change (from baseline to 16 weeks) in mean LMR for each treatment group. Lastly, a linear mixed effect model was used to model LMR at all three time points (baseline, 8 weeks, 16 weeks). We tested both the main effect for treatment and the treatment × time interaction.

Secondary outcomes

The above analyses (paired t-tests for within group change, ANCOVA for between group changes) were repeated with the following secondary outcomes: serum LBP, zonulin, fecal calprotectin and proinflammatory marker levels. In all analyses, validation of the distributional and parameterization assumptions was checked, and alternative approaches were implemented if needed (e.g. data transformations or non-parametric methods). All primary analyses were evaluated at a two-sided significance level of 0.05. All secondary analyses reported both unadjusted and multiple-testing adjusted p-values, using the Benjamini–Hochberg method to control the false-discovery rate at level 0.05.⁴³ Given that the treatments were randomly assigned, the two treatment groups were expected to be balanced at baseline with regard to other possible variables. Nevertheless, we tested whether the treatment groups differ by various demographic variables and analyses adjusted for any variables whose p-values were <0.05. To address the problem of missing data, a sensitivity analysis was conducted using multiple imputation via the mice R package.⁴⁴ Power analysis was conducted using PASS software, and statistical analyses were conducted using R.^45,46 Both ‘Intention to Treat’ and ‘Per Protocol’ analyses were conducted.

Ethical considerations

The risks of semaglutide use were minimized by administration according to FDA-labeled use and close monitoring for adverse events. There was a slight risk of diarrhea with the administration of the lactulose-mannitol drink. Risks to the patient were minimized through the design of the inclusion and exclusion criteria, and a safety lab panel consisting of HbA1c, hs-CRP, CMP, and urine pregnancy test in females of childbearing potential prior to randomization. Investigators monitored patients for adverse events throughout the study and managed glucose levels according to American Diabetes Association 2022 guidelines.

Discussion

The root cause of the chronic low-grade systemic inflammation associated with T2D is still the subject of investigation. It is suggested the chronic inflammation is associated with increased intestinal permeability.⁶ In a human trial investigating small intestine permeability changes with age, intestinal permeability was significantly increased in participants with low-grade inflammation and T2D when compared to those with low-grade inflammation or T2D alone.⁴⁷ Animal studies suggest a dysfunctional intestinal barrier can lead to chronic inflammation and insulin resistance.^8–10 In humans, the inflammatory biomarker CRP is not only elevated in individuals with T2D when compared to healthy controls but also elevated CRP in non-diabetics increases the risk of developing T2D.⁴⁸ The role of increased intestinal permeability in mediating intestinal mucosal inflammation and pathogenesis in IBD is becoming more prevalent.^49–51 The data backing the association between chronic inflammation and intestinal permeability in patients with T2D is limited, but some human studies suggest increased intestinal permeability is present in T2D.^15,21,23,31

The SIB trial is a single-center, randomized, double-blinded, placebo-controlled clinical trial designed to evaluate the effects of the GLP-1 receptor agonist semaglutide on intestinal barrier function in individuals with T2D. To our knowledge, this trial is the first study to examine the effects of GLP-1 receptor agonists on intestinal permeability in humans. We speculate that by improving intestinal barrier function in individuals with T2D, the associated chronic inflammation and related comorbidities could subsequently be reduced. Treatment of inflammation associated with T2D can improve insulin secretion and can provide protection to organ systems and reduce micro- and macrovascular complications in diabetes.⁵² This is important because CVDCVD is the most common comorbidity associated with T2D.⁵³

Chronic, low-grade inflammation is associated with dyslipidemia and atherosclerosis.⁵⁴ Lowe et al. demonstrated that elevated levels of proinflammatory markers, such as IL-6, and to a lesser degree hs-CRP and fibrinogen, are predictors of macrovascular events and death in a cohort of individuals with T2D.⁵⁵ The prevalence of obesity in T2D is well-established and is associated with low-grade inflammation and increased risk of CVD.^56,57 In a systematic review, Einarson et al. demonstrated the global prevalence of CVD in T2D to be 32.2%.⁵⁷ Carnethon et al. determined mortality in individuals with CVD and T2D is more likely than those without CVD or T2D with an odds ratio of 4.56 (95% CI 3.53–5.89).⁵⁸ GLP-1 receptor agonists, including semaglutide, are commercially used anti-diabetes drugs for treatment of T2D. GLP-1 receptor agonists have been proven to reduce proinflammatory markers, cause weight loss, and reduce composite cardiovascular outcomes in both animal and human studies.^33,59

In animal studies, administration of GLP-1 therapies in obese and diabetic mice resulted in improved intestinal barrier function by decreasing intestinal inflammation and expediting mucosal healing, in addition to lowering blood glucose.^33,36 In one murine study, use of GLP-1 receptor agonists was shown to improve gut homeostasis and reduce colonic inflammation.⁶⁰ The study displayed improved disease in mice colitis models treated with liraglutide (a GLP-1 receptor agonist) and reduced colonic inflammation through regulation of IL-33, CCL20, and mucin 5b, markers that have been shown to be dysregulated in mice colitis models. Bang-Berthelson et al. speculated liraglutide increased intestinal barrier function and promoted mucosal healing through the regulation of IL-33, CCL20, and mucin 5b, thus improving disease in the mice colitis models.⁶⁰ Yusta et al. demonstrated expression and activation of the GLP-1 receptor in intestinal intraepithelial lymphocytes of mice by GLP-1 receptor agonists attenuated inflammation and reduced gut injury leading to improved intestinal barrier function.⁶¹ In animal models, improvement of intestinal inflammation and barrier function by use of a GLP-1 receptor agonist is evident. Currently, there are no data on the effects of GLP-1 receptor agonists on intestinal permeability in humans.

LMR is an inexpensive and non-invasive assessment on intestinal permeability, but there is variability in the LMR and in the urine collection times across clinical trials that use the test. The SIB trial will be using a commercially available LMR test kit provided by Genova Diagnostics to assess intestinal permeability. The sugar drink in the test kit contains 5 g of lactulose and 1 g of mannitol, and the urine collection will be performed 6 h post-ingestion. A recent meta-analysis assessing LMR in Crohn’s and celiac disease found there were larger mean differences in LMR between healthy controls and participants with Crohn’s or celiac disease using a 2:1 LMR when compared with studies that use a 5:2 LMR.⁶² This may suggest a lower LMR may be more sensitive to an impaired intestinal barrier in the setting of inflammation. Musa et al. found that urine collection after 5 h versus 2 h yielded no statistically significant differences in LMR.⁶³ Akram et al. found no significant differences in LMR when comparing 2-h and 6-h urine collection times in adults with IBD and other gastrointestinal diseases.⁶⁴ The Genova Diagnostics LMR kit used in this study instructs urine be collected at 6 h post-ingestion, but in the future a 2-h collection may yield similar results. Furthermore, Rao et at. concluded that the majority of mannitol is absorbed across the small intestine, but there is also some absorption in the large intestine.⁶⁵ It is speculated that prolonged urine collection times (i.e. 6 h) can potentially cause the LMR measures to be falsely lowered due to both small and large intestine absorption of mannitol.⁶⁵ It is assumed that lactulose movement across the intestinal barrier is more specific for increased permeability and should compensate for any extra mannitol absorption in the large intestine.

The quantities of lactulose and mannitol collected at 6 h post-ingestion of the sugar drink is expressed as a percentage recovery of the ingested dose.²⁹ Typically, analytes are measured using high-performance liquid chromatography (HPLC). HPLC is considered a highly accurate and exceptionally reproducible method for measuring analytes in a solution.⁶⁶ Genova Diagnostics uses an automated spectrophotometric technique for measurements of urinary mannitol and lactulose.^67,68 Camilleri et al. found that HPLC and Genova’s method of analysis for urinary sugars had similar results with a correlation coefficient for mannitol and lactulose of 0.997 and 0.662, respectively (both p < 0.001).⁶⁹ Additionally, Genova Diagnostics acknowledges that the calculation of LMR via their test is dependent on renal function. It is stated that mannitol concentration variability is corrected by relating the urinary creatinine concentrations to the mannitol determinations in the pre- and post-challenge urine collections. However, it is not stated if corrections for lactulose are completed. Additionally, if urinary creatinine concentrations are too low, suggesting significant renal insufficiency, the relation of urinary creatinine to mannitol cannot be calculated. As this trial’s participants have type 2 diabetes, which has a well-known relationship with nephropathy and renal insufficiency, we have excluded participants with chronic kidney disease defined as EGFR <30 mL/min/1.73 m². Nonetheless, care needs to be taken when interpreting the LMR results.

Serum zonulin is another non-invasive and inexpensive assessment of intestinal permeability. Zonulin levels have been shown to be significantly increased in individuals with obesity and insulin resistance, suggesting an altered intestinal barrier in those populations.²³ Zonulin has been shown to be upregulated in multiple autoimmune (i.e. ankylosing spondylitis and rheumatoid arthritis) and nervous system diseases (i.e. multiple sclerosis).⁷⁰ This study does not exclude participants with these conditions and potentiates the possibility of participants with these underlying conditions to have elevated zonulin that is not a direct reflection of intestinal permeability. Additionally, more than 70 peer-reviewed publications have used ELISA assays by two companies (CUSABIO assay, Wuhan, China and immunodiagnostik GA, Bensheim, Germany). Recent studies reported that antibodies in these assays might not be specific to zonulin, and could identify a variety of proteins structurally and possibly functionally related to zonulin.⁷¹ Care will need to be taken when analyzing serum zonulin results.

LBP is used as a measure of intestinal permeability because the presence of elevated LBP in the blood without evidence of infection suggests LPS is leaking across the intestinal barrier. LBP has a longer half-life and is a more stable indicator of exposure to LPS and intestinal permeability.³⁰ When using LBP as a marker of intestinal permeability, the presence of an underlying bacterial infection in participants would show an elevated LBP that does not reflect intestinal permeability.³⁰ Thus, we exclude participants that have had an infection or antibiotic use within 3 weeks prior to enrollment in the trial. Additionally, the data on LBP as a marker of intestinal permeability is mixed. Kuzma et al. showed that there was no correlation between LBP levels and LMR in normal weight to obese adults.⁷² However, Vogt et al. demonstrated that LBP positively correlates with LMR in a cohort of patients with liver cirrhosis.⁷³ LBP is believed to be a more accurate marker of intestinal permeability than LPS, but conflicting data on LBP’s correlation to LMR suggests LBP may not be as accurate as previously suspected.

The effect of GLP-1 receptor agonists on satiety with resultant weight loss is one of the reasons why the drug has gained popularity as a diabetes treatment and a weight loss adjunct.⁷⁴ There is data suggesting weight loss is associated with improvement in intestinal permeability. A meta-analysis of 47 clinical trials reported a statistically significant improvement in intestinal permeability, as evidenced by markers of intestinal permeability including serum zonulin, LPS/LBP, and LMR, with weight loss [SMD: −0.7 (95% CI: −0.9, −0.4), p < 0.0001, I 2 = 83%, n = 17 studies].⁷⁵ Furthermore, there is evidence that GLP-1 receptor agonists statistically significantly decrease hs-CRP in individuals with T2D and obesity; however, when adjusted for change in body weight, statistical significance was lost.⁷⁶ This suggests that weight loss associated with GLP-1 receptor agonist use is a major contributor toward the drug’s reduction in inflammatory markers. Our analysis was required to adjust for changes in BMI when assessing intestinal permeability.

The SIB trial provided valuable data on the effects of a GLP-1 receptor agonist on intestinal permeability. This provided insights into the potential for GLP-1 receptor agonists to improve intestinal barrier function and prevent the negative consequences associated with chronic inflammation.

Footnotes

Acknowledgements

We thank the CUDECT team for their continued contributions and coordination of the SIB Trial.

Declarations

ORCID iDs

Steven Rella

Chelsea Baker

References

Olefsky

Glass

CK.

Macrophages, inflammation, and insulin resistance. Ann Rev Physiol 2010; 72: 219–246.

Esser

Legrand-Poels

Piette

, et al. Inflammation as a link between obesity, metabolic syndrome and type 2 diabetes. Diabetes Res Clin Pract 2014; 105: 141–150.

Cruz

Sousa

, et al. The linkage between inflammation and Type 2 diabetes mellitus. Diabetes Res Clin Pract 2013; 99: 85–92.

Emerging Risk Factors Collaboration, Sarwar

Gao

, et al. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies. Lancet 2010; 375: 2215–2222.

Haffner

SM.

Pre-diabetes, insulin resistance, inflammation and CVD risk. Diabetes Res Clin Pract. 2003; 61(Suppl. 1): S9–S18.

Genser

Aguanno

Soula

, et al. Increased jejunal permeability in human obesity is revealed by a lipid challenge and is linked to inflammation and type 2 diabetes. J Pathol 2018; 246: 217–230.

Arrieta

Bistritz

Meddings

JB.

Alterations in intestinal permeability. Gut 2006; 55: 1512–1520.

Cani

Amar

Iglesias

, et al. Metabolic endotoxemia initiates obesity and insulin resistance. Diabetes 2007; 56: 1761–172.

de La Serre

Ellis

Lee

, et al. Propensity to high-fat diet-induced obesity in rats is associated with changes in the gut microbiota and gut inflammation. AmJ Physiol GastrointLiver Physiol 2010; 299: G440–G448.

10.

Lam

CWY

Hoffmann

JMA

, et al. Effects of dietary fat profile on gut permeability and microbiota and their relationships with metabolic changes in mice. Obesity 2015; 23: 1429–1439.

11.

Tremaroli

Bäckhed

Functional interactions between the gut microbiota and host metabolism. Nature 2012; 489: 242–249.

12.

Ciesielska

Matyjek

Kwiatkowska

TLR4 and CD14 trafficking and its influence on LPS-induced pro-inflammatory signaling. Cell Mol Life Sci 2021; 78: 1233–1261.

13.

Damms-Machado

Louis

Schnitzer

, et al. Gut permeability is related to body weight, fatty liver disease, and insulin resistance in obese individuals undergoing weight reduction. Am J Clin Nutr 2016; 105: 127–135.

14.

Bosi

Molteni

Radaelli

, et al. Increased intestinal permeability precedes clinical onset of type 1 diabetes. Diabetologia 2006; 49: 2824–2827.

15.

Horton

Wright

Smith

, et al. Increased intestinal permeability to oral chromium (51Cr)-EDTA in human type 2 diabetes. Diabet Med 2014; 31: 559–563.

16.

Nathavitharana

Lloyd

Raafat

, et al. Urinary mannitol: lactulose excretion ratios and jejunal mucosal structure. Arch Dis Child 1988; 63: 1054–1059.

17.

Sukkar

Schenone

Foppiani

, et al. Experimental assessment of chemotherapy-induced early intestinal damage in colon cancer the lactulose-mannitol permeability test. Tumori 2004; 90: 461–463.

18.

Wegh

CAM

de Roos

Hovenier

, et al. Intestinal permeability measured by urinary sucrose excretion correlates with serum zonulin and faecal calprotectin concentrations in UC patients in remission. J Nutr Metab 2019; 2019: 2472754.

19.

von Martels

JZH

Bourgonje

Harmsen

HJM

, et al. Assessing intestinal permeability in Crohn’s disease patients using orally administered 52Cr-EDTA. PLoS One 2019; 14: e0211973.

20.

Dastych

Jr Novotná

, et al. Lactulose/mannitol test and specificity, sensitivity, and area under curve of intestinal permeability parameters in patients with liver cirrhosis and Crohn’s disease. Dig Dis Sci 2008; 53: 2789–2792.

21.

Mooradian

Morley

Levine

, et al. Abnormal intestinal permeability to sugars in diabetes mellitus. Diabetologia 1986; 29: 221–224.

22.

Fasano

Regulation of intercellular tight junctions by zonula occludens toxin and its eukaryotic analogue zonulin. Ann N Y Acad Sci 2000; 915: 214–222.

23.

Moreno-Navarrete

Sabater

Ortega

, et al. Circulating zonulin, a marker of intestinal permeability, is increased in association with obesity-associated insulin resistance. PLoS One 2012; 7: e37160.

24.

Ohlsson

Orho-Melander

Nilsson

PM.

Higher levels of serum zonulin may rather be associated with increased risk of obesity and hyperlipidemia, than with gastrointestinal symptoms or disease manifestations. Int J Mol Sci 2017; 18: 582.

25.

Sequeira

Lentle

Kruger

, et al. Standardising the lactulose mannitol test of gut permeability to minimise error and promote comparability. PLoS One 2014; 9: e99256.

26.

Konikoff

Denson

LA.

Role of fecal calprotectin as a biomarker of intestinal inflammation in inflammatory bowel disease. Inflamm Bowel Dis 2006; 12: 524–534.

27.

Berstad

Arslan

Folvik

Relationship between intestinal permeability and calprotectin concentration in gut lavage fluid. Scand J Gastroenterol 2000; 35: 64–69.

28.

Tibble

Sigthorsson

Foster

, et al. Use of surrogate markers of inflammation and Rome criteria to distinguish organic from nonorganic intestinal disease. Gastroenterology 2002; 123: 450–460.

29.

Gomes

JMG

de Assis Costa

and de Cássia Gonçalves Alfenas. Metabolic endotoxemia and diabetes mellitus: a systematic review. Metabolism 2017; 68: 133–144.

30.

Schumann Ralf

. Old and new findings on lipopolysaccharide-binding protein: a soluble pattern-recognition molecule. Biochem Soc Trans 2011; 39: 989–993.

31.

Cox

Zhang

Bowden

, et al. Increased intestinal permeability as a risk factor for type 2 diabetes. Diabetes Metab 2017; 43: 163–166.

32.

Sakura

Morioka

Shioi

, et al. Lipopolysaccharide-binding protein is associated with arterial stiffness in patients with type 2 diabetes: a cross-sectional study. Cardiovasc Diabetol 2017; 16: 62.

33.

Lee

Jun

HS.

Anti-inflammatory effects of GLP-1-based therapies beyond glucose control. Mediators Inflamm 2016; 2016: 3094642.

34.

Guo

Huang

Chen

, et al. Glucagon-like peptide 1 improves insulin resistance in vitro through anti-inflammation of macrophages. Braz J Med Biol Res 2016; 49: e5826-e.

35.

Rakipovski

Rolin

Nøhr

, et al. The GLP-1 analogs liraglutide and semaglutide reduce atherosclerosis in ApoE−/− and LDLr−/− mice by a mechanism that includes inflammatory pathways. JACC Basic Transl Sci 2018; 3: 844–857.

36.

Koehler

J A

Baggio

Yusta

, et al. GLP-1R agonists promote normal and neoplastic intestinal growth through mechanisms requiring Fgf7. Cell Metabolism 2015; 21: 379–391.

37.

Zhao

Chen

Xia

, et al. A glucagon- like peptide-1 receptor agonist lowers weight by modulating the structure of gut microbiota. Front Endocrinol 2018; 9: 233.

38.

Ebbesen

Kissow

Hartmann

, et al. Glucagon-like peptide-1 is a marker of systemic inflammation in patients treated with high-dose chemotherapy and autologous stem cell transplantation. Biol Blood Marrow Transplant 2019; 25: 1085–1091.

39.

Leech

McIntyre

Steel

, et al. Risk factors associated with intestinal permeability in an adult population: a systematic review. Int J Clin Pract 2019; 73: e13385.

40.

Vilsbøll

Bain

Leiter

, et al. Semaglutide, reduction in glycated haemoglobin and the risk of diabetic retinopathy. Diabetes Obes Metab 2018; 20: 889–897.

41.

Kieser

Friede

Simple procedures for blinded sample size adjustment that do not affect the type I error rate. Statist Med 2003; 22: 3571–3581.

42.

Senn

SJ.

Change from baseline and analysis of covariance revisited. Stat Med 2006; 25: 4334–444.

43.

Benjamini

Hochberg

Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc B (Methodological) 1995; 57: 289–300.

44.

van Buuren

Groothuis-Oudshoorn

. Mice: multivariate imputation by chained equations in R. J Stat Softw 2011; 45: 67.

45.

NCSS L. ncss.com/software/pass (2019, accessed 14 May 2020).

46.

Team RC. R Foundation for Statistical Computing, https://www.R-project.org/(2018, accessed 14 May 2020).

47.

Valentini

Ramminger

Haas

, et al. Small intestinal permeability in older adults. Physiological reports. 2014; 2(4):e00281.

48.

Pradhan

Manson

Rifai

, et al. C-reactive protein, interleukin 6, and risk of developing type 2 diabetes mellitus. JAMA 2001; 286: 327–334.

49.

Turpin

Lee

Raygoza Garay

, et al. Increased intestinal permeability is associated with later development of Crohn’s disease. Gastroenterology 2020; 159: 2092–2100.e5.

50.

Chang

Leong

Wasinger

, et al. Impaired intestinal permeability contributes to ongoing bowel symptoms in patients with inflammatory bowel disease and mucosal healing. Gastroenterology 2017; 153: 723–731.e1.

51.

Michielan

D’Incà

Intestinal permeability in inflammatory bowel disease: pathogenesis, clinical evaluation, and therapy of leaky gut. Mediators Inflamm 2015; 5: 1–10

52.

Donath

MY.

Multiple benefits of targeting inflammation in the treatment of type 2 diabetes. Diabetologia 2016; 59: 679–682.

53.

Iglay

Hannachi

Joseph Howie

, et al. Prevalence and co-prevalence of comorbidities among patients with type 2 diabetes mellitus. Curr Med Res Opin 2016; 32: 1243–1252.

54.

Pickup

JC.

Inflammation and activated innate immunity in the pathogenesis of type 2 diabetes. Diabetes Care 2004; 27: 813–823.

55.

Lowe

Woodward

Hillis

, et al. Circulating inflammatory markers and the risk of vascular complications and mortality in people with type 2 diabetes and cardiovascular disease or risk factors: the ADVANCE study. Diabetes 2014; 63: 1115–1123.

56.

Einarson

Acs

Ludwig

, et al. Prevalence of cardiovascular disease in type 2 diabetes: a systematic literature review of scientific evidence from across the world in 2007–2017. Cardiovasc Diabetol 2018; 17: 83.

57.

Leon

Maddox

TM.

Diabetes and cardiovascular disease: epidemiology, biological mechanisms, treatment recommendations and future research. World J Diabetes 2015; 6: 1246–1258.

58.

Carnethon

Biggs

Barzilay

, et al. Diabetes and coronary heart disease as risk factors for mortality in older adults. Am J Med 2010; 123: 556.e1–556.e5569.

59.

Sheahan

Wahlberg

Gilbert

MP.

An overview of GLP-1 agonists and recent cardiovascular outcomes trials. Postgrad Med J 2020; 96: 156–161.

60.

Bang-Berthelsen

Holm

Pyke

, et al. GLP-1 induces barrier protective expression in Brunner’s glands and regulates colonic inflammation. Inflamm Bowel Dis 2016; 22: 2078–2097.

61.

Yusta

Baggio

Koehler

, et al. GLP-1R Agonists modulate enteric immune responses through the intestinal intraepithelial lymphocyte GLP-1R. Diabetes 2015; 64(7): 2537–2549.

62.

Gan

Nazarian

Teare

, et al. A case for improved assessment of gut permeability: a meta-analysis quantifying the lactulose:mannitol ratio in coeliac and Crohn’s disease. BMC Gastroenterol 2022; 22: 16.

63.

Musa

Kabir

Hossain

, et al. Measurement of intestinal permeability using lactulose and mannitol with conventional five hours and shortened two hours urine collection by two different methods: HPAE-PAD and LC-MSMS. PLoS One 2019; 14: e0220397.

64.

Akram

Mourani

, et al. Assessment of intestinal permeability with a two-hour urine collection. Dig Dis Sci 1998; 43: 1946–1950.

65.

Rao

Camilleri

Eckert

, et al. Urine sugars for in vivo gut permeability: validation and comparisons in irritable bowel syndrome-diarrhea and controls. Am J Physiol Gastrointest Liver Physiol 2011; 301: G919–G928.

66.

Timchenko

YV.

Advantages and disadvantages of high-performance liquid chromatography (HPCL). J Environ Anal Chem 2021; 8: 335.

67.

Lunn

Northrop

. Automated enzymatic assays for the determination of intestinal permeability probes in urine. 2. Mannitol. Clin Chim Acta 1989; 183: 163–170.

68.

Behrens

Docherty

Elia

, et al. A simple enzymatic method for the assay of urinary lactulose. Clin Chim Acta 1984; 137: 361–367.

69.

Camilleri

Nadeau

Lamsam

, et al. Understanding measurements of intestinal permeability in healthy humans with urine lactulose and mannitol excretion. Neurogastroenterol Motil 2010; 22: e15–e26.

70.

Fasano

Intestinal permeability and its regulation by zonulin: diagnostic and therapeutic implications. Clin Gastroenterol Hepatol 2012; 10: 1096–1100.

71.

Ajamian

Steer

Rosella

, et al. Serum zonulin as a marker of intestinal mucosal barrier function: May not be what it seems. PLoS One 2019; 4: e0210728.

72.

Kuzma

Cromer

Hagman

, et al. No differential effect of beverages sweetened with fructose, high-fructose corn syrup, or glucose on systemic or adipose tissue inflammation in normal-weight to obese adults: a randomized controlled trial. Am J Clin Nutr 2016; 104: 306–314.

73.

Vogt

Reuken

Stengel

, et al. Dual-sugar tests of small intestinal permeability are poor predictors of bacterial infections and mortality in cirrhosis: a prospective study. World J Gastroenterol 2016; 22: 3275–3284.

74.

Shah

Vella

Effects of GLP-1 on appetite and weight. Rev Endocr Metab Disord 2014; 15: 181–187.

75.

Koutoukidis

Jebb

Zimmerman

, et al. The association of weight loss with changes in the gut microbiota diversity, composition, and intestinal permeability: a systematic review and meta-analysis. Gut Microbes 2022; 14: 2020068.

76.

Newsome

Francque

Harrison

, et al. Effect of semaglutide on liver enzymes and markers of inflammation in subjects with type 2 diabetes and/or obesity. Aliment Pharmacol Ther 2019; 50: 193–203.