Abstract
Background
Elderly patients with type 2 diabetes (T2DM) experience a significantly raised risk of cardiovascular disease. We aimed to determine the effect of the multi-species synbiotic supplementation in elderly patients with T2DM and high cardiovascular risk.
Methods
Ninety-six patients with T2DM, aged ≥65 years with high cardiovascular risk, were enrolled between January 2022 and May 2023 and randomly allocated to receive a synbiotic supplement, containing a multi-species probiotic, and fructooligosaccharide as a prebiotic, or placebo supplements for 4 months. The primary outcome was the mean difference in weight change between synbiotics and placebo. The secondary outcomes were the mean difference in modifications in the body fat mass (BFM), lean body mass (LBM), and biochemical parameters, including glucose metabolism indices, lipid profile, and adhesion molecules between the two groups due to the intervention.
Results
Eighty-five participants completed the study. The mean weight [−1.16 kg (−1.36 to −0.97)], body mass index (BMI) [−0.44 kg/m2 (−0.36 to −0.51)], and BFM [−0.99 kg (−1.05 to −0.93)] decreased significantly in the synbiotic group compared to the placebo group in the linear mixed analysis of covariance analysis (all p < 0.001). The mean serum Low-density-Lipoprotein (LDL-C) [−10.83 mg/dl (−14.78 to −6.88)], and total cholesterol [−11.78 mg/dl (−16.44 to −7.11)], vascular cell adhesion molecule 1 (VCAM-1) [−85.70 ng/L (−150.14 to −21.26)], fasting plasma glucose (FPG) [−22.83 mg/dl (−31.30 to −14.36)], and homeostatic model assessment for insulin resistance (HOMA-IR.) [−1.31 (−1.75 to −0.86)] improved in the synbiotic group significantly compared to the placebo group (p = 0.002, p = 0.012, p = 0.017, p < 0.001, p = 0.003 and p = 0.001, respectively). No serious adverse events were detected.
Conclusion
A multi-species synbiotic preparation benefits elderly patients with T2DM and high cardiovascular risk and improves weight, BMI, BFM, and plasma levels of total cholesterol, LDL-C, VCAM-1, FPG, and HOMA-IR. These findings suggest synbiotics may have health-promoting impacts in older patients with diabetes.
Subject terms: Randomized controlled trials, Type 2 diabetes
Introduction
Type 2 diabetes mellitus (T2DM) is the most prevalent and clinically significant metabolic disorder worldwide [1]. Due to the progression in the management of T2DM and its comorbidities, life expectancy in patients with T2DM has been extended, increasing the number of older people with T2DM [2]. Diabetes significantly increases the cardiovascular disease (CVD) risk [3, 4]. This is due to a combination of traditional risk factors such as hypertension (HTN), dyslipidemia, and obesity, as well as nontraditional factors such as oxidative stress, low-grade inflammation, and endothelial dysfunction [5, 6]. Consequently, close monitoring and treatment of patients with diabetes is crucial to prevent CVD [3].
The gut microbiota (GM) plays a significant role in the development and progression of diabetes, and dysbiosis is a common feature in patients with T2DM [7]. Dysbiosis has an important effect on gut barrier integrity, resulting in a leaky gut with increased permeability that stimulates the translocation of inflammatory mediators, such as lipopolysaccharide (LPS), the cell wall element of gram-negative bacteria, to the blood, which activates inflammatory responses and insulin resistance [8]. LPS disturbs cardiovascular health and raises CVD risk [93]. It is important to consider that the GM of older people with T2DM differs from that of healthy elderly people, with specific differences in taxonomic variety and functional path [9].
The potential for reconstructing GM as a therapeutic approach for diabetes is an encouraging area of research, with investigations proposing that interventions such as probiotics, prebiotics, and fecal microbial transplantation may be beneficial [7, 10–12]. Probiotics are live microorganisms that provide health benefits to the host when consumed in adequate amounts and can help reestablish this balance [13]. Prebiotics, which are nondigestible ingredients, selectively stimulate the growth of advantageous bacteria [14]. Synbiotics refer to a combination of prebiotics and probiotics to enhance human or animal health [15].
Existing literature on synbiotic use in diabetes in older adults, focusing on the potential benefits of synbiotics in improving GM in this population, is limited [16–18]. Shen et al. [19] showed that non-food probiotics, prebiotics, and synbiotics reduced the all-cause and CVD mortality risk in older adults. Kassaian [20] and Naseri [21] reported that synbiotic supplementation improved lipid profiles and other CVD risk factors in individuals at risk for T2DM. Recently, it has been informed that the short-term use of the synbiotic formula has significantly diminished fasting insulin, improved lipid profile, and decreased high-sensitivity C-reactive protein (hs-CRP) and tumor necrosis factor-alpha (TNF-alpha) serum levels in older patients [22]. Although these studies provide valuable insights into the potential mechanisms and benefits of synbiotics, there is a need for more research, specifically regarding their safety and efficacy in diabetes management in older individuals with high CVD risk.
On the other hand, existing T2DM management approaches are still mainly based on evidence from younger populations. Tight control of dyslipidemia, HTN, and blood glucose levels is critical in dealing with these risk factors and preventing cardiovascular complications in older patients with diabetes [23]. Nevertheless, the impact of obesity on CVD in the elderly may differ from that in younger people, and the correlation between blood glucose control and cardiovascular events in older patients with diabetes is complex [24]. To our knowledge, there have been no studies regarding the effect of synbiotic supplements on older adults with T2DM and a high CVD risk. Therefore, this study aimed to investigate the impact of 4 months of ingestion of synbiotics or placebo on anthropometric indices, body composition, lipid profile, glucose metabolism indices, and serum levels of atherosclerosis-dependent indices through a triple-blind, randomized, placebo-controlled clinical trial (RCT) in this population.
Material and methods
Study design
This parallel-group triple-blind RCT was conducted in two endocrinology outpatient clinics of Tabriz University of Medical Sciences according to the Consolidated Standards of Reporting Trials SPIRIT 2013 guidelines. This RCT comprised a 2-week wash-out and a 4-month intervention period. During the wash-out period, participants were asked to avoid probiotic supplements and foods, dietary supplements, antibiotics, and oral nonsteroidal anti-inflammatory drugs. The flowchart of the participants is shown in Fig. 1.
Fig. 1. CONSORT 2010 Flow Diagram.
The study participant flow chart.
Ethical considerations
This RCT was conducted following the Declaration of Helsinki. The patients were informed regarding the study objectives and design, and signed a written informed consent before enrollment. The trial protocol was approved by the Institutional Review Board (No. 67033) and the Ethics Committee of the Research Vice-Chancellor of Tabriz University of Medical Sciences (IR.TBZMED.REC.1399.917) and registered on the Iranian clinical trial website (http://www.irct.ir: IRCT20161022030424N6). Patients’ data were conserved in a secure database to keep patients’ security.
Participants
Participants were recruited via convenience sampling from the outpatient clinics of the Emam Reza and Sina hospitals (Tabriz University of Medical Sciences, Iran). Enrollment was conducted between January 2022 and May 2023. Demographic information and medical history were obtained at the first appointment.
The inclusion criteria were: (1) men and women aged 65 years or older on the day of signing the informed consent form; (2) T2DM hemoglobin A1C (HbA1C) ≥ 6.5% or fasting blood glucose (FBG) ≥ 126 mg/dL [25]; (3) body mass index (BMI) ranging from 18 to 40 kg/m2; (4) under constant antidiabetic treatment (without daily change) at least 8 weeks before randomization (if the patient uses insulin, the daily dose of insulin should not change more than 10% from 8 weeks before randomization); and (5) high risk of cardiovascular events: albuminuria in two out of three random urine samples in the last 24 h and a positive history of macrovascular events (proven history of myocardial infarction or advanced coronary artery disease involving a high-risk vessel, history of ischemic or hemorrhagic stroke, or proven carotid artery disease or peripheral blood vessel disease). Exclusion criteria were: (1) smoking and alcohol consumption; (2) severe uncontrolled diabetes; (3) use of dietary supplements, other probiotic supplements or food diuretics, laxatives, any drugs that affect weight, and antibiotics during the washout and intervention period; (4) acute digestive problems; and (5) unusual stressful events during the study.
Sample size
One-way analysis of covariance (ANCOVA) was used to analyze the primary outcome, with baseline weight as a covariate. The mean difference and common standard deviation (SD) from baseline to 4 months in body weight in the synbiotic group compared to the placebo group were presumed to be 2% and 4%, respectively [26]. Accounting for a 2-sided significance level of α = 0.05, and a power of 1−β = 0.8, 40 participants were calculated for each group. Considering a 20% loss to follow-up rate, 48 subjects were estimated as necessary for inclusion in each group.
Randomization, treatment allocation, and blinding
Participants were randomized in a 1:1 ratio to receive a synbiotic or placebo via block randomization using Random Allocation Software version 1.0, stratified by baseline BMI (20–24.9, 25–29.9, 30–34.9 and 35–39.9 kg/m2) and fasting plasma glucose (FPG) (100-199, 200–299, and ≥300 mg/dl). Unaware of the research protocol, a statistician allocated the participants to the study groups and created an allocation list with sealed and consecutively numbered opaque envelopes. Each envelope contained a card, that was representative of either “Synbiotic” or “Placebo”. The probiotic and placebo capsules were identical regarding their physical characteristics, including size, color, and odor. Investigators, site staff, clinical monitors, and participants remained blinded to the assigned intervention until the trial was complete.
Study intervention
The treatment group received a synbiotic supplement containing probiotic bacterial strains and 250 mg short-chain fructooligosaccharide (FOS) as a prebiotic (Familacte® capsules, ZistTakhmir, Tehran, Iran) twice daily in addition to their standard drug regimen. The strains used in this product included Lactobacillus rhamnosus, Lactobacillus helveticus, Lactobacillus casei, Bifidobacterium lactis, Lactobacillus acidophilus, Bifidobacterium breve, Lactobacillus bulgaricus, Bifidobacterium longum, Lactobacillus plantarum, Bifidobacterium bifidum, Lactobacillus geseri, and Streptococcus thermophilus. Familacte ® was provided in capsules comprising 1 × 109 colony-forming units (CFU) reserved in the refrigerator below 4 °C.
Placebo capsules containing maltodextrin were similar in smell, flavor, color, texture, and appearance. The supplements and placebo were manufactured by ZistTakhmir Co., Tehran, Iran, and were provided by the company.
Participants were instructed to consume one capsule of the test product twice daily, in the morning and evening, after the meal.
Outcomes
Primary outcome
The primary outcome was weight change, measured at baseline and after the intervention. The estimand was the mean difference between synbiotic and placebo for this outcome.
Secondary outcome
The secondary outcomes were the mean difference in modifications in the body fat mass (BFM), lean body mass (LBM), and biochemical parameters, including glucose metabolism indices (i.e., FPG, fasting insulin, HbA1c, and homeostasis model assessment-estimated insulin resistance (HOMA-IR)), lipid profile [i.e., triglycerides (TG), total cholesterol, high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein-cholesterol (LDL-C)], and adhesion molecules (intracellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1)) between the two groups due to the intervention.
Measurements
Demographics
Clinical and demographic variables such as personal and socioeconomic data, medications, and the existence of other diseases were documented through a face-to-face interview during the first evaluation.
Dietary intakes
Three 24-h dietary records, planned to capture comprehensive information about food and drink intakes, were completed for three nonconsecutive days (two weekdays and one weekend), once at the baseline and then at the end of the study. To obtain the dietary intake of patients, we used Nutritionist IV software (First Databank, San Bruno, Calif., USA) modified for Iranian foods.
Anthropometrics and body composition
Height was measured using a wall tape measure with a wall-mounted stadiometer (Seca 206, Hamburg, Germany). Weight and body composition indices, including BFM, LBM, and BMI, were measured employing a bioelectric impedance device (Body composition analyzer, In Body 270, Korea).
Laboratory measures
At baseline and the end of the study, 10 ml of fasting venous blood was taken after a 12-h fasting state from the forearm vein by trained and experienced laboratory technicians between 7 and 10 AM. The blood samples were centrifuged at room temperature to separate the serum (4000 rpm for 20 min), which was then stored at −75 °C for future measurements.
Biochemical indices
FBG levels were measured by the glucose oxidase method on an auto-analyzer (Cobas c 311, Roche Diagnostics, Risch-Rotkreuz, Switzerland). Serum insulin was measured by using an ELISA kit (Monobind Inc. Lake Forest, California, USA). HbA1C levels were measured by a high-performance liquid chromatography analyzer (Tosoh, Tokyo, Japan). HOMA-IR score was used to determine the insulin resistance using the following formula: HOMA-IR = fasting insulin (μU/mL) × FPG (mmol/L)/22.5.
Lipid profile tests (TG, Total Cholesterol, and HDL-C) were conducted by an enzymatic method (colorimetry) using Pars Azmoon kits (Pars-Azmoon, Karaj, Iran) and an autoanalyzer (Selectra ProXL, Vital Scientific, Spankeren, The Netherlands). LDL-C level was calculated using the Friedwald formula.
The serum levels of sVCAM-1 and sICAM-1 were detected using a human ELISA kit (Diaclone SAS Biotech Co., Ltd, France).
All laboratory measurements of each parameter were analyzed together (baseline and end-of-study samples) to minimize inter-assay variation.
Compliance and safety
At each visit, compliance was evaluated by counting consumed products. Additionally, patients were requested to record a diary comprising the daily intake of treatments. The main investigator monitored all patients for adverse events through phone calls and monthly in-person appointments. The participants were invited to contact the investigators when they experienced adverse reactions.
Statistical analysis
We analyzed the collected data using SPSS version 22 software (SPSS Inc., Chicago, Illinois). Kolmogorov–Smirnov and Shapiro–Wilk tests for normality were used for all variables. The baseline categorical variables were presented as frequency (percentage), and continuous variables were presented as mean ± SD. The Chi-square test and independent samples t-test were applied to compare the essential characteristics and basic measurements of biochemical variables of patients between the two groups. A modified intention-to-treat analysis was performed. To compare the changes of quantitative variables before and after intervention in each study group, paired Wilcoxon tests and paired samples t-tests were used. A linear mixed ANCOVA model was applied for the main analysis. Treatment (probiotic or placebo), and baseline values for the variables were included as fixed effects and subject as random effects. Age, sex, and BMI were considered potential confounders and were included as covariates. However, none of these variables showed any confounding effects (β-estimate of ≥10%) and were not included in the main model. In this study, a two-tailed p value of less than 0.05 was considered statistically significant.
Results
Patient enrollment began on 11 January 2022 and continued over 12 May 2023. One hundred and twenty-one patients were evaluated for eligibility, from which 25 patients were excluded (16 didn’t meet the inclusion criteria and 9 refused to participate). Ninety-six participants contributed to the trial and were randomly assigned to the intervention arms. Of the participants who started to participate in the trial, one discontinued because of disruptions related to severe flu-like symptoms, and ten participants discontinued for unknown reasons. Finally, 85 patients (43 in the synbiotic group and 42 in the placebo group) completed the 4-month intervention.
Participants’ baseline sociodemographic, anthropometric, and metabolic characteristics
The baseline sociodemographic, anthropometric, and metabolic characteristics of the participants, including age, sex, marital status, education, disease duration (years), family history of diabetes, and antidiabetes medications, are shown in Table 1. There was no significant difference between the two groups in this regard. The mean body weight was 77.28 ± 7.16 kg, the mean BMI was 29.19 ± 3.41 kg/m2, the mean waist circumference was 93.60 ± 6.19 cm, and the mean hip circumference was 107.25 ± 2.98 cm. The reported energy intake was 2449.44 ± 308.24 kcal. It was observed that 19 (22.35%) patients had a history of MI, 57 (67.05%) had a history of advanced coronary artery disease, and 9 (10.58%) had a history of ischemic stroke.
Table 1.
Baseline characteristics of the study patients.
| Characteristics | Synbiotic group n = 43 | Placebo group n = 42 | p* | |
|---|---|---|---|---|
| Age (years), mean ± SD | 69.79 ± 2.85 | 71.52 ± 3.55 | 0.306 | |
| Sex, n (%) | Male | 23 (53.5) | 19 (34.3) | 0.450 |
| Female | 20 (46.5) | 23 (65.7) | ||
| Education, n (%) | Primary school | 26 (60.5) | 29 (69.1) | 0.616 |
| Secondary school | 12 (27.9) | 8 (19.0) | ||
| College | 5 (11.6) | 5 (11.9) | ||
| Occupation, n (%) | Unemployed | 16 (37.2) | 17 (40.5) | 0.896 |
| Employed | 11 (25.6) | 5 (11.9) | ||
| Housewife | 9 (20.9) | 12 (28.6) | ||
| Retired | 7 (16.3) | 8 (19.0) | ||
| Marriage status, n (%) | Single | 7 (16.3) | 5 (11.9) | 0.952 |
| Married | 22 (51.2) | 25 (59.5) | ||
| Divorced | 3 (7.0) | 4 (9.5) | ||
| Widowed | 11 (25.6) | 8 (19.0) | ||
| Family history (%) | Yes | 22 (51.2) | 27 (64.3) | 0.224 |
| No | 21 (48.8) | 15 (35.7) | ||
| Duration of diabetes (years), mean ± SD | 7.37 ± 3.49 | 7.0 ± 2.11 | 0.553 | |
| Antidiabetic medications, n (%) | Metformin | 15 (34.9) | 11 (26.2) | 0.474 |
| Sulfonylureas | 9 (20.9) | 11 (26.2) | ||
| Thiazolidinediones | 2 (4.6) | 3 (7.1) | ||
| Insulin injection | 11 (25.6) | 8 (19.0) | ||
| Insulin injection + oral drug | 6 (14.0) | 9 (21.5) | ||
| Other medications, n (%) | ACE inhibitors | 30 (69.8) | 32 (76.2) | 0.531 |
| Antiplatelet agents | 32 (74.4) | 35 (83.3) | ||
| β-Blockers | 38 (88.3) | 37 (88.1) | ||
| statin | 29 (67.4) | 25 (59.5) | ||
| Fibrates | 11 (25.6) | 5 (11.9) | ||
| Diabetic nephropathy | Yes | 2 (4.6) | 4 (9.5) | 0.784 |
| No | 41 (95.4) | 38 (90.5) | ||
| Hepatic steatosis | Yes | 5 (11.7) | 8 (19.0) | 0.415 |
| No | 38 (88.3) | 34 (81.0) | ||
| Physical activity level, n (%) | Light | 38 (88.3) | 40 (95.2) | 0.891 |
| Moderate | 5 (11.7) | 2 (4.8) | ||
| Body mass index (kg/m2) | 20–24.9 | 6 (14.0) | 5 (12.0) | - |
| 25–29.9 | 23 (53.5) | 23 (54.8) | ||
| 30–34.9 | 10 (23.2) | 10 (23.8) | ||
| 35–39.9 | 4 (9.3) | 4 (9.4) | ||
| Fasting blood glucose (mg/dl) | 100–199 | 26 (60.5) | 25 (59.5) | - |
| 200–299 | 11 (25.6) | 11 (26.2) | ||
| ≥300 | 6 (14.0) | 6 (14.3) | ||
| Waist circumference (cm), mean ± SD | 93.30 ± 6.81 | 92.40 ± 5.56 | 0.661 | |
| Hip circumference (cm), mean ± SD | 106.94 ± 3.49 | 105.58 ± 2.35 | 0.324 | |
| Energy (kcal), mean ± SD | 2403.67 ± 302.16 | 2496.29 ± 310.95 | 0.168 | |
| Carbohydrate (g), mean ± SD | 378.25 ± 51.13 | 321.07 ± 44.33 | 0.198 | |
| Protein (g), mean ± SD | 62.57 ± 15.15 | 64.17 ± 20.13 | 0.498 | |
| Total fat (g), mean ± SD | 70.13 ± 20.12 | 75.11 ± 11.54 | 0.298 | |
| Systolic blood pressure (mmHg), mean ± SD | 141.04 ± 11.10 | 143.21 ± 9.55 | 0.337 | |
| Diastolic blood pressure (mmHg), mean ± SD | 87.90 ± 11.96 | 89.40 ± 12.45 | 0.573 | |
*independent t-test or Chi-square and ± Fisher’s exact test.
Dietary intakes
No statistically significant differences were seen concerning the mean energy and macro and micronutrient intakes between the two groups at baseline and end of the intervention. The calorie consumption by patients in the synbiotic group before the trial was 2403.67 ± 302.16 kcal/d, with no statistically significant variation during the study period [MD = 75.88 kcal/day (95% CI, −77.62 to 229.32), p = 0.327]. Such a result was seen in the placebo group [MD = 120.66 kcal/day (95% CI, −7.95 to 249.28), p = 0.065].
Primary and secondary outcomes
Weight and body composition
As seen in Table 2, over the 4 months, the mean body weight significantly reduced in the synbiotic group, compared to the placebo group, even after adjusting for weight baseline values and energy intakes of participants (p < 0.001). The mean BMI significantly decreased in the synbiotic group compared to the placebo group after adjusting for BMI baseline values and differences in calorie intakes of participants (p < 0.001). The mean BFM significantly decreased in the synbiotic group compared to the placebo group after adjusting for BFM baseline values and differences in calorie intakes of participants (p < 0.001). There were not any within- and between-group differences in the LBM values of participants due to the interventions (all p > 0.05).
Table 2.
Comparison of anthropometric and body composition indices between synbiotic and placebo groups before and after intervention.
| Variable | Synbiotic group n = 43 | Placebo group n = 42 | P* | P** | |
|---|---|---|---|---|---|
| Weight, mean ± SD | Before intervention | 78.28 ± 6.53 | 76.25 ± 7.69 | <0.001 | <0.001 |
| After intervention | 77.12 ± 6.48 | 76.03 ± 7.79 | |||
| Change±, MD (95% CI)a | −1.16 (−1.36, −0.97) | −0.21 (−0.47, +0.03) | |||
| BMI, mean ± SD | Before intervention | 29.52 ± 3.63 | 28.80 ± 3.17 | <0.001 | <0.001 |
| After intervention | 29.08 ± 3.58 | 28.71 ± 3.18 | |||
| Change±, MD (95% CI)a | −0.44 (−0.36, −0.51) | −0.08 (−0.17, +0.00) | |||
| BFM, mean ± SD | Before Intervention | 33.80 ± 5.37 | 32.92 ± 5.17 | <0.001 | <0.001 |
| After Intervention | 32.80 ± 5.12 | 32.86 ± 5.22 | |||
| Change±, MD (95% CI)a | −0.99 (−1.05, −0.93) | −0.06 (−0.13, +0.01) | |||
| LBM, Mean ± SD | Before intervention | 49.99 ± 5.14 | 50.60 ± 4.91 | 0.204 | 0.221 |
| After intervention | 49.81 ± 5.31 | 50.58 ± 5.14 | |||
| Change±, MD (95% CI)a | −0.17 (−0.39, 0.03) | −0.02 (−0.08, +0.03) |
The bold values indicate the statistical significance.
BFM body fat mass, BMI body mass index, LBM lean body mass, MD (95% CI) Mean difference (95% confidence interval).
*Analyzed by use of a linear mixed model with treatment as fixed effects and subject as random effect, and baseline value as covariate.
**Analyzed by use of a linear mixed model with treatment as fixed effects and subject as random effect, and baseline value and differences in calori intake as covariate.
aPaired t tests for normally distributed variables or paired Wilcoxon tests for abnormally distributed variables.
Lipid profile
As seen in Table 3, the mean serum TG levels decreased significantly in the synbiotic group, but not in the placebo group. However, there were no significant between-group differences even after adjusting for TG baseline values (p = 0.416) (Fig. 2A). The mean serum LDL-C levels decreased significantly in the synbiotic group, but not in the placebo group. Synbiotic supplements were better than placebo in decreasing the LDL-C after adjusting for LDL baseline values (p = 0.002) (Fig. 2B). The mean serum total cholesterol levels decreased significantly in the synbiotic group, but not in the placebo group. Synbiotic supplements were better than placebo in decreasing the serum total cholesterol after adjusting for baseline values (p = 0.012) (Fig. 2D).
Table 3.
Comparison of Lipid profile between synbiotic and placebo groups before and after intervention.
| Variable | Synbiotic group n = 43 | Placebo group n = 42 | P* | |
|---|---|---|---|---|
| TG (mg/dl), mean ± SD | Before intervention | 285.44 ± 125.06 | 301.42 ± 115.50 | 0.416 |
| After intervention | 270.95 ± 116.08 | 291.11 ± 97.14 | ||
| Change±, MD (95% CI)a | −14.48 (−22.85, −6.12) | −10.30 (−27.68, 7.06) | ||
| LDL-C (mg/dl), mean ± SD | Before intervention | 138.90 ± 19.23 | 135.35 ± 19.52 | 0.002 |
| After intervention | 128.06 ± 18.51 | 136.03 ± 18.69 | ||
| Change±, MD (95% CI)a | −10.83 (−14.78, −6.88) | 0.67 (−5.57, 6.92) | ||
| HDL-C (mg/dl), mean ± SD | Before intervention | 43.90 ± 9.35 | 49.30 ± 7.20 | 0.109 |
| After intervention | 45.86 ± 8.02 | 47.90 ± 8.23 | ||
| Change±, MD (95% CI)a | 1.95 (−0.05, 3.95) | −1.40 (−2.86, 0.05) | ||
| Total Cholesterol, mean ± SD | Before intervention | 239.90 ± 32.55 | 244.95 ± 29.93 | 0.012 |
| After intervention | 228.12 ± 31.49 | 242.16 ± 26.90 | ||
| Change±, MD (95% CI)a | −11.78 (−16.44, −7.11) | −2.79 (−10.32, 4.74) |
HDL-C high-density lipoprotein cholesterol, LDL-C low-density lipoprotein cholesterol, MD (95% CI) mean difference (95% confidence interval), TG triglycerides.
The bold values indicate the statistical significance.
*Analyzed by use of a linear mixed model with treatment as fixed effects and subject as random effect, and baseline value as covariate.
aPaired samples t-test.
Fig. 2. Effect of a Multi-Species Synbiotic Preparation on Lipid Profile in Older Patients with Type 2 Diabetes and High Cardiovascular Risk.
This figure shows the impact of a synbiotic preparation on various serum lipid parameters. A Serum Triglyceride Level, B Serum LDL (Low-Density Lipoprotein) Cholesterol Level, C Serum HDL (high-density lipoprotein) cholesterol level, and D Serum total cholesterol level. Data are expressed as mean ± standard error of the mean (SEM). Statistical significance is denoted as *p < 0.05 vs. baseline and **p < 0.01 vs. placebo.
Adhesion molecules
As seen in Table 4, the mean serum VCAM-1 level decreased significantly in the synbiotic group, compared to the placebo group after adjusting for VCAM-1 baseline values (p < 0.001) (Fig. 3A). The mean serum ICAM-1 levels decreased significantly in the synbiotic group, but not in the placebo group. However, there were no significant differences between synbiotics and placebo even after adjusting for ICAM-1 baseline values (p = 0.787) (Fig. 3B).
Table 4.
Comparison of adhesion molecules between synbiotic and placebo groups before and after intervention.
| Variable | Synbiotic group n = 43 | Placebo group n = 42 | P* | |
|---|---|---|---|---|
| VCAM-1 (ng/L), mean ± SD | Before intervention | 1650.03 ± 221.15 | 1706.94 ± 190.50 | <0.001 |
| After intervention | 1564.32 ± 203.20 | 1751.90 ± 218.31 | ||
| Change±, MD (95% CI)a | −85.70 (−150.14, −21.26) | 44.95 (−21.64, 111.55) | ||
| ICAM-1 (ng/L), mean ± SD | Before intervention | 543.06 ± 88.72 | 531.20 ± 73.56 | 0.787 |
| After intervention | 518.37 ± 60.38 | 519.41 ± 63.88 | ||
| Change±, MD (95% CI)a | −24.69 (−48.92, −0.46) | −11.79 (−41.75, 18.17) |
The bold values indicate the statistical significance.
ICAM-1 intracellular adhesion molecule-1, MD (95% CI) Mean difference (95% confidence interval), VCAM-1 vascular cell adhesion molecule-1.
*Analyzed by use of a linear mixed model with treatment as fixed effects and subject as random effect, and baseline value as covariate.
aPaired samples t-test.
Fig. 3. Effect of a multi-species synbiotic preparation on adhesion molecules in older patients with type 2 diabetes and high cardiovascular risk.
This figure shows the impact of a synbiotic preparation on serum adhesion molecule levels. A VCAM-1 (vascular cell adhesion molecule-1) and B ICAM-1 (intercellular adhesion molecule-1). Data are expressed as mean ± standard error of the mean (SEM). Statistical significance is denoted as *p < 0.05 vs. baseline and **p < 0.001 vs. placebo.
Glucose metabolism indices
As seen in Table 5, over the study period, the mean serum FPG levels decreased significantly in the synbiotic group, but not in the placebo group. There was a significant difference between the synbiotic and placebo groups after adjusting for FPG baseline values and weight changes due to the treatment (p = 0.003). The mean serum insulin levels decreased significantly in the synbiotic group, but not in the placebo group. However, there was no significant difference between the synbiotic and placebo groups after adjusting for insulin baseline values and weight changes (p = 0.060). The mean HOMA-IR levels decreased significantly in the synbiotic group, but not in the placebo group. There was a significant difference between the synbiotic and placebo groups after adjusting for HOMA-IR baseline values and weight changes (p = 0.001). There were no significant within- or between-group differences regarding HbA1C over the study period (all p > 0.05).
Table 5.
Comparison of glucose metabolism indices between synbiotic and placebo groups before and after intervention.
| Variable | Synbiotic group n = 43 | Placebo group n = 42 | P* | |
|---|---|---|---|---|
| FPG (mg/dl), mean ± SD | Before intervention | 173.52 ± 37.10 | 169.10 ± 36.70 | 0.015 |
| After intervention | 150.68 ± 28.47 | 166.79 ± 24.40 | ||
| Change±, MD (95% CI)a | −22.83 (−31.30, −14.36) | -2.31 (-11.60, 6.97) | ||
| Insulin (μIU/ml), mean ± SD | Before intervention | 15.12 ± 2.74 | 15.51 ± 2.68 | 0.008 |
| After intervention | 14.17 ± 2.71 | 15.38 ± 2.10 | ||
| Change±, MD (95% CI)a | −0.94 (−1.48, −0.39) | −0.13 (−0.69, 0.43) | ||
| HbA1C | Before intervention | 7.35 ± 1.02 | 7.45 ± 0.87 | 0.313 |
| After intervention | 7.19 ± 1.01 | 7.38 ± 0.91 | ||
| Change±, MD (95% CI)a | −0.16 (−0.34, 0.02) | −0.06 (−0.16, 0.02) | ||
| HOMA-IR | Before intervention | 6.66 ± 2.49 | 6.64 ± 2.32 | 0.001 |
| After intervention | 5.34 ± 1.66 | 6.39 ± 1.51 | ||
| Change±, MD (95% CI)a | −1.31 (−1.75, −0.86) | −0.24 (−0.74, 0.25) |
The bold values indicate the statistical significance.
FPG fasting plasma glucose, HbA1C hemoglobin A1C, HOMA-IR homeostasis model assessment-estimated insulin resistance, MD (95% CI) Mean difference (95% confidence interval).
*Analyzed by use of a linear mixed model with treatment as fixed effects and subject as random effect, and baseline value as covariate.
aPaired samples t-test.
Safety and adverse events
The synbiotic was well tolerated. There were no statistically significant differences between the studied groups in this regard. Three patients from the synbiotic group and one from the placebo group reported nausea that resolved in both groups in a few days, spontaneously.
Taken all together, these results suggest benefits of multi-strain synbiotic preparation in decreasing weight, BMI, and BFM, and improving plasma levels of total cholesterol, LDL-C, VCAM-1, FPG, and HOMA-IR in older patients with T2DM and high cardiovascular risk (Fig. 4).
Fig. 4. Effect of a multi-species synbiotic preparation in older patients with type 2 diabetes and high cardiovascular risk.
This figure illustrates the impact of the multi-species synbiotic preparation on key health indicators in older patients with Type 2 Diabetes and high cardiovascular risk. Specifically, it presents changes in body composition, including A weight, B body mass index (BMI), and C body fat mass (BFM); cardiovascular risk markers such as D plasma total cholesterol, E plasma low-density lipoprotein cholesterol (LDL-C), and F plasma vascular cell adhesion molecule-1 (VCAM-1); and measures of glucose metabolism and insulin sensitivity, namely, G fasting plasma glucose (FPG) and H homeostatic model assessment for insulin resistance (HOMA-IR).
Discussion
This randomized, triple-blind, placebo-controlled study involving older adults with T2DM and high CVD risk indicates that multi-strain synbiotic preparation including L. rhamnosus, L. helveticus, L. casei, B. lactis, L. acidophilus, B. breve, L. bulgaricus, B. longum, L. plantarum, B. bifidum, L. geseri, and S. thermophilus, and FOS for 4 months can significantly decrease weight and improve FPG, fasting insulin, and HOMA-IR compared to the placebo. The intervention was well tolerated.
Increasing age combined with diabetes exerts a synergistic consequence on the vascular system, increasing the atherosclerosis load in older adults with T2DM and significantly increasing the risk of death [23, 27]. Additionally, current socioeconomic variations have led to an upsurge in obesity, which is now seen as sarcopenic obesity in older adults with T2DM [28]. Nutritional approaches targeting weight management, blood lipids, and blood pressure are confirmed to reduce atherosclerotic disease risk in this population [29].
Probiotics and synbiotics have been confirmed to expand gut commensal diversity and adjust the immune system in older adults [30]. Many investigations have proposed that the efficacy of multi-strain probiotic supplements may be better than mono-strain ones, representing synergy between strains [31]. The mechanism of these synergistic properties is not understood clearly and is supposed to comprise complex networks of cell-cell communications [32]. The co-supplementation of lactose-based probiotics and FOS is extensively accepted to help increase lactobacilli survival under stress conditions [33, 34]. FOSs, a widely used prebiotic, are an energy source and a crucial nutrient for GM [35]. FOSs can be fermented by the GM and help the establishment and activities of beneficial bacteria, including Lactobacillus and Bifidobacterium, enhance the metabolism of the GM, reduce inflammation, and improve host immunity [36]. This is well tolerated and safe since FOS has not been related to a greater risk of intestinal discomfort in older individuals in previous studies [37]. Nonetheless, the literature contains only a few data and information on the effect of probiotics and prebiotics in older adults with T2DM and high CVD risk.
Recent investigations propose that probiotics and synbiotics may help weight loss and improve metabolic health in people with overweight/obesity. Sudha et al. [38] studied the efficacy of multi-strain synbiotic capsules in adult participants. In line with our findings, a 12-week supplementation significantly reduced BMI and body weight compared to a placebo. Similarly, Chen et al. [39] performed a 12-week RCT on children. Treatment with a three-strain probiotic resulted in a significant decrease in BMI, serum LDL-C, and total cholesterol and an increase in serum HDL-C. In runners, a multi-strain probiotic supplementation for 3 months improved LBM in men and reduced BFM in women [40]. However, Park and Bae [41] concluded that probiotics have limited efficacy in managing body weight. These inconsistent findings propose that the effects of probiotics on body weight may depend on issues such as probiotic strain, treatment duration, and baseline characteristics of the patients.
Weight management in older adults with T2DM and high CVD risk is multifaceted. While obesity is a significant risk factor for CVD in this population [24], an “obesity paradox” occurs where a higher BMI correlates with lower mortality in older patients with CVD [42]. However, body composition measures are more important than BMI alone in older individuals [42]. Intentional weight loss in older adults with obesity can improve CVD risk profiles, but must be seen cautiously because of the risks of sarcopenia and hip fractures [43].
According to our findings, synbiotic supplementation for 4 months led to a significant decrease in BFM with no statistically significant changes in the LBM of participants. In this line, recent investigations suggest that probiotics and synbiotics may benefit osteoporosis and sarcopenia. The gut-muscle axis plays a central role in muscle health, with microbial metabolites like short-chain fatty acids (SCFA) modulating age-related variations through several paths [44]. Additionally, prebiotics, probiotics, and synbiotics had beneficial impacts on bone mineral content and bone structure in animal and human investigations [45]. Therefore, probiotics and their compounds with prebiotics can be a logical approach to weight management in older patients with T2DM.
According to our findings, the multi-strain synbiotic preparation for 4 months significantly improved FPG, serum insulin, and HOMA-IR index with no significant changes in HbA1C in older patients with T2DM. Impaired glucose tolerance is an important risk factor for T2DM and CVD. Therefore, preserving good blood glucose response is critical for avoiding and managing metabolic disorders [46]. Several Investigations have demonstrated that probiotics can reduce FPG, fasting plasma insulin, and HOMA-IR, with effects fluctuating based on treatment duration, probiotic formulation, and dosage [47]. Our observations parallel those of Kordowski et al., that a synbiotic combination of Bacillus subtilis DSM 32315 and L-alanyl-L-glutamine for two weeks significantly decreased FPG, predominantly in those with raised baseline values [48]. In the study by Tajabadi–Ebrahimi et al. [49], synbiotic supplements containing 3 probiotic bacteria species, L. acidophilus, L. casei, and B. bifidum plus inulin for 12 weeks in patients with T2DM, overweight, and CVD significantly reduced FPG, serum insulin levels, and increased insulin sensitivity compared to placebo. This is while, in the study by Horvath et al. [50], the supplementation with a multispecies synbiotic in patients with diabetes for 6 months had no significant effect on glucose metabolism compared to the placebo.
The effects of probiotics are related to their capability to adjust GM composition, improve gut barrier integrity, decrease intestinal permeability, and lessen the circulating endotoxins because of increased mucin expression and tight-junction firmness that defends the epithelial barrier [51, 52]. Probiotics are supposed to attach to gut epithelial cells, avoiding the expansion of harmful microorganisms by creating anti-bacterial agents such as bacteriocins and organic acids. SCFAs are produced by probiotics and play a critical role in glucose homeostasis through several mechanisms, including the increase of protective glucagon-like peptide-1 (GLP-1) release and enhanced insulin sensitivity [53]. SCFAs might adjust hepatic glucose homeostasis by activating AMP-activated protein kinase, involving peroxisome proliferator-activated receptor (PPAR)-γ-mediated impacts on gluconeogenesis [54]. Additionally, SCFAs increase anorectic hormone release, peptide YY, which may improve glucose disposal and insulin resistance [55]. Probiotics can alleviate the destructive effects of pro-inflammatory cytokines on the gut barrier by decreasing pro-inflammatory and improving anti-inflammatory reactions.
We revealed that synbiotics supplementation resulted in the serum LDL-C, total cholesterol, and VCAM-1 decreases compared to the placebo. Several studies have confirmed that synbiotic and probiotic supplements can reduce serum TG [20, 56–58] and increase HDL cholesterol levels [56–58]. However, we did not find evidence of this in our study. A recent study showed that synbiotic supplementation significantly increased HDL-C levels and the abundance of beneficial gut bacteria, including Firmicutes, Bacteroidetes, Lactobacillus, and Bifidobacterium in adults with dyslipidemia [59]. Similarly, in healthy young volunteers, both probiotic and synbiotic supplementations decreased total cholesterol, LDL-C, and TG while increasing HDL-C, with synbiotics showing more obvious effects [60]. In another study, synbiotic bread consumption in patients with T2DM led to diminished serum TG and very low-density lipoprotein (VLDL)-C and increased HDL-C compared to probiotic and control bread [56].
ICAM-1 and VCAM-1 are known as inflammatory factors, which elevate their secretion levels in various inflammatory conditions. ICAM-1 and VCAM-1 have a great role in modulating homeostasis in disorders such as cancer, atherosclerosis, MI, stroke, and many more [61]. Obesity is a low-grade chronic inflammatory procedure related to several disorders that elevate VCAM-1 levels, such as high lipoprotein levels, hyperglycemia, and hyperinsulinemia [62, 63]. Blood concentration of cell adhesion molecule VCAM-1 correlates with the upcoming development of microvascular complications such as diabetic neuropathy [64]. Given the substantial in diabetic vasculopathy, adhesion molecules provide potential beneficial targets for inhibiting and managing chronic complications of T2DM.
Experimental and clinical investigations have shown the controversial properties of GM-modifying agents on endothelial function. Malik et al. [65] showed a drink containing 20 billion CFU per day of L. plantarum 299 v (Lp299v) for 6 weeks improved vascular endothelial function in men with stable coronary artery disease. In this experiment, twenty men with stable coronary artery disease consumed a drink containing 20 billion CFU of Lp299v per day for 6 weeks. Tenorio-Jimenez et al. [66] showed administration of Lactobacillus reuteri V3401 capsules for 3 months correlated with lower levels of soluble ICAM-1, in adults with obesity and metabolic syndrome. Rezazadeh et al. [67] showed that consumption of probiotic yogurt containing L. acidophilus La5 and B. lactis Bb12 for 2 months led to a significant decrease in the level VCAM-1 compared to regular yogurt in patients with metabolic syndrome. Szulinska et al. [68] revealed that multispecies probiotics altered the functional and biochemical indices of vascular dysfunction in postmenopausal women with obesity.
Five mechanisms have been proposed to have a role in the decrease of cholesterol concentrations by lactic bacteria, such as inhibition of cholesterol reabsorption, facilitation of cholesterol elimination, inhibition of the cholesterol enzymatic synthesis by the SCFAs, interfering with the bile salt reprocessing, and simplifying their removal [69, 70]. Probiotics may provide cholesterol-lowering properties through bile salt hydrolase (an enzyme of probiotics that hydrolyzes bile salts into amino acid residues and free bile salts) [71].
On the other hand, FOS affects macronutrient absorption, delaying gastric emptying, and diminution small-bowel transit time. Gluconeogenesis induced by FOS may be facilitated by SCFAs, particularly propionate [70]. SCFAs are potential precursors for cholesterol and fatty acid formation in the gastrointestinal tract. Probiotics and SCFAs stimulate cholesterol internalization into bacterial cells, and dilute intestinal cholesterol and excretion in feces. SCFAs would attenuate proatherogenic mediators including LDL-C and VLDL synthesis, lipogenesis, and formation of fats in adipocytes and enterocytes.
The effects of dietary modifications and supplements on the GM are highly individualized. Managing diabetes in elderly patients with high CVD risk requires an individualized approach based on the patient’s age, disease duration, risk of hypoglycemia, cardiovascular complication risk, and life expectancy [72]. While constricted glycemic control may benefit younger patients, it can be dangerous for older patients with longer disease duration [73].
Our study has some limitations. We did not evaluate the participants’ compliance by measuring SCFAs or fecal bacterial loads. Additionally, we did not assess gut barrier function or plasma LPS levels. We used a synbiotic containing multi-bacterial species plus FOS. So, it is unclear if the intervention effects in this study were due to which component of the supplements. We did not collect stool samples, so we did not know whether any probiotics endured in the colon. Moreover, although our findings showed that the benefit of the 4-month duration of synbiotic treatment was obvious, there were no significant improvements in some of the variables, and we suggest that the trial length was not enough to screen for the variations.
Conclusion
In conclusion, multi-species synbiotic supplementation for 4 months among elderly patients with T2DM and high CVD risk had beneficial effects on weight, BMI, BFM, and plasma levels of total cholesterol, LDL-C, VCAM-1, FPG, and HOMA-IR; however, it did not have any effect on the HbA1c, TG, HDL-C, and ICAM-1 levels. These findings suggest synbiotic supplementation may provide beneficial potential for elderly patients with T2DM and high CVD risk. These findings suggest synbiotics may have health-promoting impacts as part of a healthy diet in older patients with diabetes and high CVD risk.
Acknowledgements
We thank all patients and personnel of the Physical Medicine and Rehabilitation Research Center for helping us in this study. We specifically thank Prof. Seyed Kazem Shakouri for his assistance in conducting this project.
Author contributions
The authors’ responsibilities were as follows—ND, EN, and NA designed and conducted research; ND and SY performed the statistical analysis, and analyzed the data; and ND, SY, and MH wrote the paper. ND, SY, and FE revised the first draft of the manuscript; ND was the primary one responsible for the final content. All authors read and approved the final manuscript.
Funding
Funding was received from the Deputy of Research, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran (NO. 67033). The study funders had no role in the study design; in the collection, analysis, and interpretation of data; in the report’s writing; or in the decision to submit the article for publication.
Data availability
The data support the findings of this study are available from the corresponding author, upon reasonable request.
Competing interests
All authors declare that they have no competing interests regarding the research conducted and reported in this article.
Declaration of generative AI and AI-assisted technologies in the writing process
No AI-assisted technologies were employed during the preparation of this work.
Footnotes
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data support the findings of this study are available from the corresponding author, upon reasonable request.