Effects of the timing of acute mulberry leaf extract intake on postprandial glucose metabolism in healthy adults: a randomised, placebo-controlled, double-blind study

Subjects

Participants were recruited from Tokyo Institute of Technology and Waseda University via word of mouth and study posters on display on the campus. Twelve (male; n = 8, female; n = 4) healthy young adults (aged 21–39 years) participated in this study. The exclusion criteria were as follows: (1) diagnosed with diabetes or dyslipidaemia; (2) taking any antioxidant, anti-obesity, or antidiabetic medication or supplements; (3) taking depression, sleeping, or steroid medications; (4) obese (body mass index [BMI] > 35 kg/m2) or suffering from sleep apnoea; (5) smoker; (6) set pacemaker or metal in the body (excluding dental fillings); and (7) engaged in shift-work or travel with jetlag within the previous 2 weeks. To rule out the presence of any of these exclusion criteria, all participants completed a health-related questionnaire about dietary intake and physical activity, including exercise, prior to the study (Fig. S1). This study was conducted in accordance with the guidelines of the Declaration of Helsinki and was approved by the ethics committee of the Tokyo Institute of Technology (Approval No. 2021080). All participants provided informed consent prior to enroling in the study. This clinical trial was registered under the local institutional board of the University Hospital Medical Information Network, Japan (Clinical Trial reference: UMIN 000045301).

Study design and procedure

The trials were performed at the Tokyo Institute of Technology between August and November 2021. A randomised, placebo-controlled, double-blind, counterbalanced crossover design was used. Each participant participated in four trials in a randomised order: (1) morning placebo trial (08:00; MP trial), (2) evening placebo trial (18:00; EP trial), (3) morning MLE trial (08:00; MM trial), and (4) evening MLE trial (18:00; EM trial; Fig. 1). Randomisation was achieved using computer-generated random numbers using Excel software. An independent researcher who was not involved in this study generated the sequence. The interval between trials was at least 1 week. In all the trials, we asked the participants to maintain their usual daily sleep and wake cycle. For the MP and MM trials, all participants were required to visit the laboratory at 08:00 h after a minimum of 10-h overnight fast (no intake of any food or beverage, except water). The dinner on the previous day was provided in both morning trials. For the EP and EM trials, all participants were required to visit the laboratory at 18:00 after a minimum 10-h fast (no intake of any food or beverage, except water) maintaining a resting state. Breakfast on the day of the experiment was provided in both evening trials. In this study, fasting duration was almost the same as in previous studies, which have reported that fasting duration influences glucose tolerance and metabolism [8, 21]. After a 10 min rest, a fasting venous blood sample was collected by venipuncture while the participants were in a seated position. Venous blood samples were collected 30, 60, 120, and 180 min after the initiation of the test meal for each trial.

Fig. 1: Protocols for the morning and evening trials.figure 1

Gray box: fasting duration, Diagonal box: resting duration, Black box: meal and placebo or MLE intake, Up arrow: blood sampling.

Test meals

The test meals used in all the trials were purchased as a set meal. Although we did not evaluate the amount of ingredients in each meal, these meals were almost identical. In addition, the test meals were provided as mixed meals consisting of rice, tofu, onions, cheese, mushrooms, bacon, Chinese cabbage, pork ham, carrots, potatoes, tomatoes, macaroni, and celery. The mixed meal was prepared according to body mass (average: 60 kJ/kg body mass) by a registered dietitian. The energy content of the meal was 15% from fats, 70% from carbohydrates, and 15% from proteins. Previous studies have reported that this macronutrient composition increases postprandial glucose in healthy adults [22, 23]. All participants were asked to consume the test meal within 20 min. The time taken to consume the mean in the first trial was recorded and replicated in subsequent trials. The participants consumed either a placebo (cellulose, 6 tablets, 1 mg per tablet, total 6 mg, no DNJ) or MLE supplements (DNJ, 6 tablets, 1 mg per tablet, total 6 mg) with breakfast or dinner. It has been reported that this amount of DNJ decreases postprandial blood glucose levels [17]. During each trial, subjects sat in a chair (reading, writing, or using an electronic device such as PC or smart phone) except when eating the mixed test meal. In addition, they did not eat other food or drink except water after eating the mixed test meal.

MLE and placebo content

The placebo (cellulose, 1 mg per tablet, no DNJ) and MLE (DNJ, 1 mg per tablet) tablets used in this study were provided by FANCL Corporation (Yokohama, Japan). Each tablet contained 1% calcium stearate to fill the tablets.

Baseline measurements of body mass, body fat, and muscle mass

For all participants, body mass, body fat, fat-free mass, and muscle mass were measured to the nearest 0.1 kg using a digital scale (Inbody 230, Inbody Inc., Tokyo Japan) in a fasting state. We used the data taken at the first trial as the baseline measurement. BMI was calculated as weight in kilograms divided by the square of height in metres.

Blood sampling and biochemical assays

To measure serum blood markers such as insulin, triacylglycerol (TAG), and non-esterified fatty acids (NEFAs), samples were allowed to clot for 30 min at room temperature and then centrifuged at 3000 rpm for 10 min. The serum sample was dispensed into plain microtubes and stored at −80 °C until the assay was performed. For plasma glucose measurements, venous blood samples were collected in tubes containing sodium fluoride-ethylenediaminetetraacetic acid. For the measurement of plasma gastric inhibitory polypeptide (GIP) and glucagon-like peptide 1 (GLP-1), venous blood samples were collected in tubes containing a DPP-4 inhibitor and protease inhibitor cocktail (BD, Tokyo, Japan). Thereafter, both samples were immediately centrifuged and stored at −80 °C until analysis. Enzymatic colorimetric assays were used to measure the plasma concentrations of glucose (GLU-HK (M); Shino-test Corporation, Kanagawa, Japan), serum TAG (Pure Auto S TAG-N; Sekisui Medical Company Limited, Tokyo, Japan), and serum NEFAs (Wako Pure Chemical Industries Limited). Enzyme-linked immunosorbent assays were used to measure plasma concentrations of insulin (Mercodia Insulin ELISA; Mercodia AB, Uppsala, Sweden), active GIP, and active GLP-1 (Yanaihara Institute, Inc. ELISA; Yanaihara Institute, Inc. Shizuoka, Japan).

Statistical analysis

Data were analysed using Predictive Analytics Software, version 28.0 for Windows (SPSS, Inc., IBM, Tokyo, Japan). The primary outcome measure was the incremental area under the blood glucose curve (iAUC) of plasma glucose, and the secondary outcome measure was postprandial glucose concentrations. The sample size was estimated using G*Power 3.1 and data from previous studies on the effects of timing of meals on postprandial glucose [22, 23]. A sample size of 11 was determined to have approximately 80% power to detect changes in glucose-lowering effects at a significance level of 0.05. The Kolmogorov–Smirnov test was used to check for the normality of the distribution of all blood parameters. Paired t-tests were used to compare between the MP and EP trials on the iAUC of blood biomarkers. To compare the effects of the timing of diet (morning and evening) on postprandial blood parameters, a two-factor ANOVA with repeated measures was used to determine the effect of meal timing (morning or evening) and postprandial interval time (0–180 min) on blood markers. Moreover, a two-factor ANOVA with repeated measures was used to determine the effect of the trial (placebo or MLE) and intake timing (morning or evening) on the iAUC of blood markers, which was calculated using the trapezoidal rule. To evaluate the effects of timing of acute MLE intake on postprandial blood markers, a three-factor ANOVA with repeated measures was used to determine the effect of the trial (placebo or MLE), meal intake timing (morning or evening), and postprandial interval time (0–180 min) on the blood marker concentrations. When significant main or interaction effects were detected, the Bonferroni method was used for post-hoc comparisons. The P-values reported for the comparisons of postprandial blood parameters at each time are subsequent to the Bonferroni correction. Statistical significance was set at P < 0.05. Results were presented as means with standard errors.

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