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Probiotics for the management of type 2 diabetes mellitus: A systematic review and meta-analysis
Accepted Manuscript Probiotics for the Management of Type 2 Diabetes Mellitus: A Systematic Review and Meta-analysis Syamimi Samah, Kalavathy Ramasamy, Siong Meng Lim, Chin Fen Neoh PII: DOI: Reference:
S0168-8227(16)30164-4 http://dx.doi.org/10.1016/j.diabres.2016.06.014 DIAB 6672
To appear in:
Diabetes Research and Clinical Practice
Received Date: Revised Date: Accepted Date:
18 January 2016 23 May 2016 6 June 2016
Please cite this article as: S. Samah, K. Ramasamy, S.M. Lim, C.F. Neoh, Probiotics for the Management of Type 2 Diabetes Mellitus: A Systematic Review and Meta-analysis, Diabetes Research and Clinical Practice (2016), doi: http://dx.doi.org/10.1016/j.diabres.2016.06.014
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Title: Probiotics for the Management of Type 2 Diabetes Mellitus: A Systematic Review and Meta-analysis
Authors: Syamimi Samah1, Kalavathy Ramasamy1,2, Siong Meng Lim1,2, Chin Fen Neoh1,2*
Affiliations: 1
Faculty of Pharmacy, Universiti Teknologi MARA (UiTM), 42300 Bandar Puncak Alam,
Selangor Darul Ehsan, Malaysia. 2
Collaborative Drug Discovery Research (CDDR) Group, Pharmaceutical and Life Sciences
Community of Research, Universiti Teknologi MARA (UiTM), 40450 Shah Alam, Selangor Darul Ehsan, Malaysia.
*Corresponding
author:
Chin
Fen
Neoh,
Phone:
+603-32584708,
E-mail:
[email protected]
Keyword: probiotics; glycaemic; type 2 diabetes mellitus; review Abstract word count: 250 Manuscript word count: 4451
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ABSTRACT Aims: To systematically review evidence of probiotic interventions against type 2 diabetes mellitus (T2DM) and analyse the effects of probiotics on glycaemic control among T2DM patients.
Methods: Electronic search using five electronic databases was performed until October 2015. Relevant studies were identified, extracted and assessed for risk of bias. The primary outcomes of this review were glycated haemoglobin (HbA1c) and fasting blood glucose (FBG). Fasting plasma insulin, Homeostasis Model Assessment-Insulin Resistance, Creactive protein, Interleukin-6 and Malondialdehyde, were identified as the secondary outcomes. Mean differences (MD) between probiotics and control groups for all outcomes were pooled using either Fixed- or Random-Effect Model. Statistical heterogeneity was assessed using I² and Chi² tests.
Results: Six randomised controlled trials (RCTs) were included in the systematic review, whereas only five were included in meta-analysis. Most RCTs were presented with low or unclear risk of bias. When compared to placebo, FBG was significantly lower with probiotic consumption (MD = -0.98 mmol/L; 95% CI: -1.17, 0.78, p < 0.00001), with moderate but insignificant heterogeneity noted. Insignificant changes between the groups were also noted for HbA1c and other secondary outcomes.
Conclusions: A moderate hypoglycaemic effect of probiotics, with a significantly lower FBG was noted. Findings on HbA1c, anti-inflammatory and anti-oxidative effects of probiotics in the clinical setting, however, remain inconsistent. The findings imply the need for well-
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designed clinical studies to further assess the potential beneficial effects of probiotics in management of T2DM.
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1.0 Introduction Type 2 diabetes mellitus (T2DM), a metabolic disease characterised by hyperglycaemia, is associated with either insensitivity of insulin or lack of insulin secretion [1]. It is the leading cause of cardiovascular disorders, blindness, end-stage renal failure, amputations and hospitalisation [2]. The incidence of T2DM is increasing. In 2011, 366 million adults worldwide were estimated to suffer from diabetes mellitus. The number is projected to increase to 592 million by year 2035 [3]. In addition, the management of T2DM is costly. In 2010, the global estimation of diabetes expenditures was USD376 billion; the expenditure is predicted to increase to USD490 billion in the next 20 years [4]. Given its substantial health and socio-economic burden, identifying an optimal therapy for T2DM is important.
The underlying mechanisms of the abnormal rise of blood glucose level are complex and multi-factorial [5]. T2DM associated risk factors that have already been identified include age, genetic predisposition, sedentary lifestyle, diet patterns and stress [6]. Recently, emerging data suggested that gut microbiota may have an important role in progression and development of T2DM. It was reported that when the microbiome balance is shifted in favour of the unhealthy ones, the level of metabolic endotoxin will increase and potentially trigger a chronic, low-grade inflammation [7]. The release of inflammatory cytokines can cause oxidative stress [8], and ultimately, lead to destruction of β-cells in the pancreas. It was found that probiotic consumption could increase the amount of beneficial bacteria (i.e. Bifidobacteria) in the gut, which could in turn reduce intestinal permeability towards lipopolysaccharide (LPS) produced by unhealthy gut microorganisms, and altogether attenuate systemic inflammation responses [9]. As such, modulating gut microbiota through dietary interventions (e.g. probiotic intake) may be useful in the prevention and control of inflammatory metabolic disorders including T2DM.
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Probiotics are live microorganisms that when administered in sufficient amounts can confer health benefit to their host [10]. Lactobacilli and bifidobacteria are the two most common types of probiotics [5]. The global probiotic market was estimated at USD33.19 billion in 2015 and it is projected to reach USD46.55 billion by 2020; dominated by Asia-Pacific market [11]. The applications of probiotics as alternative biotherapeutics have been successfully demonstrated in treatment of respiratory infection [12], inflammatory bowel disease [13], antibiotic associated diarrhoea [14] and ulcerative colitis [15]. In spite of the booming in vitro and in vivo probiotic studies against metabolic diseases such as T2DM, their application at clinical settings remains scarce [16, 17]. In fact, the findings from the very few clinical trials that have been conducted were inconsistent. The most recent systematic review and meta-analysis on probiotic use in glycaemic control comprised of 17 trials, involving a broad range of study populations [i.e. healthy participants, T2DM patients, patients with hypercholesterolaemia,
non-alcoholic steatohepatitis or metabolic syndrome, obese
populations and patients with gestational diabetes mellitus (GDM)]. The findings, however, were limited by substantial inter-study clinical heterogeneity [18]. In addition, the effects of probiotics against vital parameters like glycated haemoglobin (HbA1c), anti-inflammatory and anti-oxidative markers were not assessed [18]. This systematic review and meta-analysis focused mainly on clinical studies that have investigated the efficacy of probiotics in T2DM patients, highlighting areas that were not usually addressed by previous review (Supplementary Table 1): the effect of probiotic on HbA1c and fasting blood glucose (FBG), anti-inflammation and anti-oxidation.
2.0 Material and methods 2.1 Literature Search Strategy
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A search of electronic databases, including EMBASE, PubMed/Medline, SpringerLink, the Cochrane Library and trial registry website (ClinicalTrials.gov) was performed. The final search was carried out in October 2015, using combinations of search terms which included ‘diabetes mellitus’, ‘probiotics’, ‘lactobacilli’, ‘bifidobacter’, ‘streptococcus’, ‘microbiota’, ‘microflora’, ‘microbiome’, ‘gut hormone’, ‘insulin sensitivity’, ‘anti-oxidant’ and ‘antiinflammatory’. In addition, citations in each paper were also used to further identify relevant papers that were not found in electronic databases.
2.2 Study Selection The inclusion criteria for this systematic review and meta-analysis were as follow: (a) randomised controlled trials (RCT), (b) adult T2DM patients (i.e. age of 18 and above), and (c) the use of probiotics (of any form, including capsule, yogurt and kefir) as an intervention. On the other hand, studies presented only as abstracts with no subsequent full report of findings, on-going clinical studies, quasi-randomised study design, in vitro or in vivo studies, review papers, non-English literatures, studies involving patients with GDM, Type 1 diabetes mellitus (T1DM), any other metabolic diseases such as obesity or hypercholesterolaemia, studies with no probiotic genus/strains reported and studies using synbiotics (i.e. probiotics combined with prebiotics) were all excluded. Whilst the primary outcomes for meta-analysis were HbA1c and FBG, the secondary outcomes included fasting plasma insulin, homeostasis model assessment of insulin resistance (HOMA-IR), inflammatory markers [i.e. C-reactive protein (CRP), interleukin-6 (IL-6)] and anti-oxidative or oxidative stress markers [i.e. malondialdehyde (MDA)]. The eligibility of all potential studies identified for inclusion was independently assessed by two review authors (SS and CFN). Discrepancies on study inclusion were resolved through discussion and consensus.
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2.3 Data Extraction and Collection Data (e.g. probiotic strains, dose, duration of intervention, dosage forms, sample size, baseline and post-intervention values for the aforementioned outcome measures) obtained from the included studies were independently extracted by two authors (SS and CFN), using a standardised, electronic abstraction form.
2.4 Assessments of Risk Bias and Publication Bias Risk bias for the included studies were independently assessed (SS and CFN) using criteria as outlined in the Cochrane Handbook for Systematic Reviews of Interventions [19]. The assessment included selection bias (method for random sequence generation and allocation concealment), performance bias (blinding of participants and personnel), detection bias (blinding of outcome assessment), attrition bias (incomplete outcome data), reporting bias (selective reporting) and other sources of bias. In addition, sample size calculation and funding declaration associated with each clinical trial were also assessed. Any disagreement was resolved by discussion. Potential publication bias was assessed using visual inspection of Funnel Plots (if RCTs included in meta-analysis < 10) and Egger’s Test (if RCTs included in meta-analysis > 10).
2.5 Data Analysis Statistical analyses were performed by employing the Review Manager Software version 5.3 (The Nordic Cochrane Centre, Copenhagen, Denmark). Mean differences (MD) between intervention (probiotics) and control group for each aforementioned outcome were first pooled using the Fixed-Effect Model. The statistical heterogeneity in each meta-analysis was assessed using I² and Chi² statistics. Heterogeneity was regarded as substantial if I² > 50% or I² > 25% with a low p value of < 0.10 in the Chi² test. In this case, the Random-Effect Model
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was performed. In order to explore the source of heterogeneity, subgroup analyses were conducted by comparing the mean difference for each outcome measure as follow: (a) probiotic dose [< 10 9 colony forming unit (CFU) versus ≥ 10 9 CFU], (b) duration of probiotic intervention (≤ 6 weeks versus > 6 weeks), (c) probiotic dosage forms (capsule versus yogurt or kefir), and (d) probiotic genus (single versus multiple genus). Also, sensitivity analyses were performed to examine the robustness of meta-analysis findings. This was achieved by excluding studies with small sample size (i.e. < 20 patients) for each intervention and control group.
3.0 Results 3.1 Description of Included Studies Out of the 260 records that have been identified through the search (after removal of duplicates), 254 records were excluded based on the pre-specified criteria (Figure 1). Table 1 outlines the details of all eligible studies and their findings. Whilst a total of six eligible studies that have investigated the use of probiotics in T2DM patients were included in the qualitative synthesis (systematic review) [8, 20-24], only five were included in quantitative synthesis (meta-analysis) [8, 20-23]; all studies were published within the past five years. The study by Andreasen et al. [24] was excluded from the meta-analysis because findings for outcomes of interest exclusive for T2DM patients were not reported. There were two trials that used probiotics in yogurt form [8, 20], one in the form of kefir [23] and the remaining in capsule form [21, 22, 24]. Except for one Denmark-based study [24], all studies [8, 20-23] were conducted in Middle East countries (i.e. Iran). The majority of the trials (n = 4) used blends of various probiotic genera, including lactobacilli and bifidobacteria [8, 20, 22, 23]. No changes in study participants’ diabetic medication regimens (e.g. metformin, glibenclamide, glitazones) was reported in two of the studies trials [8, 23]. Two trials [20, 22]
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were categorised as industry sponsored whereas four studies explicitly stated no competing interests [8, 21, 23, 24].
3.2 Risk Bias and Publication Bias Figures 2(A) and 2(B) summarise the authors’ judgements on each risk of bias item for all six RCTs included in this systematic review. In general, most RCT were presented with either low or unclear risk of bias. Publication bias was not assessed using Egger’s regression given that RCTs included in this meta-analysis were less than 10 studies; the Funnel Plots for all outcome measures were approximately symmetric.
3.3 Hypoglycaemic Effects 3.3.1 HbA1c and FBG Figures 3(A) and 3(B) illustrate the Forest Plots of the pooled estimates of probiotics on HbA1c and FBG, respectively. All six studies [8, 20-24] investigated the hypoglycaemic effects of probiotics; four studies documented significant decrease (p < 0.05) in HbA1c and/ or FBG levels. In the current meta-analysis, no significant difference was noted in HbA1c (MD = -0.11%, 95% CI: -1.00, 0.78, p = 0.81) between the probiotic and control groups [Figure 3(A)]. Significant substantial inter-study heterogeneity was noted (I2 = 91%, p < 0.00001). Subgroup analyses (Table 2) revealed that the extreme inconsistency among four trials in HbA1c (I2 = 91%) was reduced to I2 = 55% when differences in probiotic dose and dosage form are accounted for. A significant increase (p < 0.05) in HbA1c was noted in trials using probiotic dose of ≥ 109 CFU and capsule dosage form. The findings, however, remain inconclusive as the number of trials included in these subgroups was small. No significant difference in HbA1c lowering effect of probiotics was observed in trials with administration
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of probiotics > 6 weeks (p = 0.79). Subgroup analysis for probiotic genus was not performed as all trials included for HbA1c analysis used multiple probiotic genus products.
In contrast, a significantly lower FBG at 0.98 mmol/L (95% CI: -1.17, -0.78, p < 0.00001), but with non-significant moderate inter-study heterogeneity was noted (I2 = 32%, p = 0.21). Further to removal of study with small sample size (i.e. n < 20 for each group) and the use of Random-Effect Model, no change in the significance of the pooled estimates of FBG (MD = 0.98 mmol/L; 95% CI: -1.18, -0.78, p < 0.00001 and MD = -0.95 mmol/L; 95% CI: -1.52, 0.39, p = 0.001) was noted, respectively. Subgroup analysis revealed that a significantly lower FBG was noted in those trials with administration of probiotics > 6 weeks; greater consistency was observed within the subgroups as well (Table 2). The use of probiotic capsules has resulted in a significantly lower FBG with low heterogeneity (I2 = 0%, p = 0.55). Significantly lower FBG was noted in both subgroups receiving probiotic dose < 109 CFU and ≥ 109 CFU. No significant difference in FBG lowering effect of probiotics was observed in trials using single or multiple probiotic genus.
3.3.2 HOMA-IR and Fasting Plasma Insulin Three studies investigated the effects of probiotics against insulin resistance [21, 22, 24] but only one [22] with positive findings. Forest Plot of the pooled estimates of probiotics on HOMA-IR [Supplementary Figure 1(A)] revealed a non-significant difference between the groups (MD = -0.79, 95% CI: -2.71, 1.14, p = 0.42) but with significant substantial interstudy heterogeneity observed (I2 = 85%, p = 0.009). Subgroup analyses was not performed given the number of studies included was small (n = 2).
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There were only three studies that documented the effects of probiotics on fasting insulin concentration [20-22]. There was, however, no significant difference in fasting plasma insulin (MD = 0.13 µIU/mL, 95% CI: -3.02, 3.28, p = 0.93) between the probiotic and control groups. The findings were presented with significant substantial inter-study heterogeneity (I2 = 95%, p < 0.00001) [Supplementary Figure 1(B)]. Subsequent removal of the study with small sample size [21] had led to no change in the significance of the pooled estimates of fasting plasma insulin (MD = -1.04 µIU/mL, 95% CI: -3.62, 1.54, p = 0.43). Subgroup analyses (Table 2) of trials using probiotic dose ≥ 109 CFU and > 6 weeks revealed significant reductions of fasting plasma insulin. Also, significant increase of fasting plasma insulin was noted in the trial using single probiotic genus; the findings, however, remain inconclusive as the number of trials included in these subgroups was small. The extreme inconsistency among three trials in fasting plasma insulin (I2 = 95%) was reduced to I2 = 52% when differences in probiotic dose and duration of trial were accounted for. There was no significant association between the pooled estimates of probiotics on fasting plasma insulin and probiotic dosage form.
3.4 Anti-inflammatory Effects A total of four studies reported on anti-inflammatory effects of probiotics, and all were with mixed responses [8, 21, 22, 24]. Both Forest Plots indicated that there were no significant differences in CRP [Supplementary Figure 2(A)] (MD = -0.47 mg/L, 95% CI: -1.25, 0.32, p = 0.25) and IL-6 [Supplementary Figure 2(B)] (MD = -0.57 pg/mL, 95% CI: -3.26, 2.12, p = 0.68) levels, respectively. Significant inter-study heterogeneity was observed in the overall analyses for CRP (I2 = 76%, p = 0.02) and IL-6 (I2 = 87%, p = 0.005) levels. The removal of a study with small sample size [21], however, led to significant reduction of CRP level (MD = -0.93 mg/L; 95% CI: -1.20, -0.66, p < 0.00001) and low heterogeneity (I2 = 0%, p = 0.34).
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Subgroup analyses of trials (Table 2) revealed significant reductions of CRP in groups using probiotic dose ≥ 10 9 CFU and multiple probiotic genus for > 6 weeks; the findings, however, remain inconclusive as the number of trials included in these subgroups was small. The inconsistency among three trials in CRP (I2 = 75%) was reduced when differences in probiotic dose (I2 = 28%), probiotic genus (I2 = 0%) and duration of trial (I2 = 0%) were accounted for. There was no significant evidence for an association between reduction of CRP level and the probiotic dosage form. Subgroup analyses for IL-6 was not performed given the small number of studies included (n = 2).
3.5 Anti-oxidative Effects There were only three studies that documented the anti-oxidative properties of probiotics [2022]. As there was only one single study that investigated the changes of SOD, GPx, CAT, total antioxidant status [20] and GSH [22] after probiotic consumption, no pooled analysis was performed for the abovementioned parameters. Forest Plot of the pooled estimate of probiotics on MDA (Supplementary Figure 3) revealed non-significant difference between the groups (p = 0.54), with low inter-study heterogeneity noted (I2 = 0%, p = 0.90).
4.0 Discussion The current meta-analysis is the first to examine the pooled estimate of probiotics on HbA1c. The use of HbA1c is a gold standard in clinical management of T2DM [25] and it permits comparability among the published studies. A 1% reduction in HbA1c has been associated with 21% risk reduction of diabetes related-end points and 37% risk reduction for microvascular complications [26]. Hence, a 1% reduction in HbA1c is considered to be clinically relevant. The findings from the current meta-analysis revealed no significant difference in HbA1c between the probiotic and the control groups; substantial heterogeneity,
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however, was noted across the clinical studies. Even though results of the subgroup analyses indicated that there were significant associations between the effects of probiotics on HbA1c and the probiotic dose or capsule dosage form, but not for the duration of probiotic intervention, these findings were limited by the small number of studies included in the subgroup analyses. One of the common limitations in all the studies included in this review is the fact that none investigated the long term effects of probiotics; all these studies were conducted in a period ranging from 4 to 8 weeks. Accordingly, the findings on HbA1c from these studies were doubtful given that the changes in HbA1c could only be detected every three months as per the life cycle of red blood cells [27]. In addition, only one study [23] in this review determined sample sizes based on the reduction in HbA1c between intervention and placebo groups; the other two studies which reported a power calculation were aimed to detect the differences in pro-inflammatory markers [i.e. hypersensitive (hs)-CRP] [22] or anti-oxidative enzymes (i.e. CAT) [20]. Of note, having sample size based on the primary outcome provides a better focus path for trial as well as adding quality to the results obtained [28, 29].
Consistent with Ruan et al. [18], a significantly lower FBG upon probiotic intake when compared to the control group was documented. A strength of the current findings is the fact that insignificant moderate inter-study heterogeneity was noted, as opposed to the findings by Ruan et al. [18]. Of note, the pooled estimate of probiotics on FBG in the current metaanalysis was primarily driven by the findings of Asemi et al. [22], in which the intake of probiotics exerted a preventive effect on the rise of FBG rather than resulting in a lower FBG level, as compared to placebo group. In addition, our subgroup analysis revealed that the lowering effect of FBG was significant in those trials with intervention period > 6 weeks. These clinical findings were consistent with the in vivo studies using diabetic mice and rat
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models, which reported significant reductions of glycaemic parameters (i.e. FBG and 2 hours post prandial glucose), and improvement in glucose tolerance [30-32]. The intervention period in in vivo studies were usually longer (i.e. 8 to 20 weeks) [30-33], in comparison to the clinical studies (i.e. 4 to 8 weeks). The specific mechanisms underlying the hypoglycaemic effects of probiotics, however, remain unclear. Some researchers described these hypoglycaemic effects as the positive consequences of probiotic-mediated decrease in systemic inflammation or oxidative stress [5, 18].
Earlier meta-analysis by Ruan et al. [18] did not examine the pooled anti-inflammatory effects of probiotics. In the current meta-analysis, no significant differences in CRP and IL-6 levels, however, were noted in the probiotic group, from which significant heterogeneity observed. Our findings suggested that high probiotic dose, longer duration of probiotic intervention and the use of multiple probiotic genuses associated significantly with better anti-inflammatory effects of probiotics. Of note, the removal of study with small sample size [21] had led to significant reduction of CRP level and low heterogeneity among those in the probiotic group. The inconsistency of results had also been observed in vivo. Although a significant decrease of TNF-α and IL-6 levels were noted among colitis-induced rats fed with probiotics [34], yet another study revealed a statically indifferent insignificant decrease of IFN-γ [35]. It is important to note that these in vivo studies used different inflammatory markers, probiotic genus/strain and feeding duration, making it difficult to directly compare and assess the anti-inflammatory effects of probiotics.
Similar to systemic inflammation, the levels of free radical and oxidative stress in T2DM patients were also reported to be higher than the healthy subjects [36-38]. It has been postulated that probiotic consumption would increase the level of anti-oxidative enzymes (i.e.
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SOD, GPx, CAT) which are able to rapidly scavenge reactive oxygen species, and therefore, reduce the rate of oxidative stress in T2DM patients [20, 21]. In agreement with the clinical studies [20, 22], the majority of the in vivo studies observed significantly increase antioxidative enzyme activities (i.e. SOD and GSH-Px) in hyperlipidaemic and diabetic rats [39, 40] after consumption of L. casei and L. acidophilus (7.56 x 10 7 to 2 x 1010 CFU/mL) for one to four weeks. The current meta-analysis, however, revealed a non-significant difference in MDA, with low inter-study heterogeneity noted.
Contrary to the findings by Ruan et al. [18], the current study revealed no significant difference in HOMA-IR in groups that have received probiotics. It is interesting to note that Ruan et al. [18] indicated an opposing pooled effect of probiotics on fasting plasma insulin in which a significant reduction was observed, particularly in the hyperglycaemic subgroup. The current study, however, suggested otherwise. The pooled effect of probiotics on fasting plasma insulin in the current meta-analysis was sensitive to the omission of RCT with small sample size. The inconsistencies in the pooled findings of fasting plasma insulin and insulin resistance between the current work and Ruan et al. [18] have hindered meaningful conclusions to be made and these data should be interpreted with caution given the substantial inter-study heterogeneity observed in both meta-analyses.
Also, there remain gaps in the knowledge albeit the increase of number of trials that investigate the efficacy of probiotics in T2DM in clinical settings. Inconsistencies in the findings were noted across the clinical studies included in this meta-analysis [8, 20-22, 24]. The possible reasons underlying this observation remain to be elucidated. It is believed that the beneficial effects of probiotics (i.e. hypoglycaemic, anti-inflammatory or anti-oxidative properties) could be highly strain specific. The use of a single strain, such as L. acidophilus
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NCFM in the study by Andreasen et al. [24] and Lactobacillus spp. in the study by Mazloom et al. [21], could be the factor explaining the negative outcome observed. Marteau [41] claimed that the beneficial outcome of probiotic administration could be most likely achieved with the combined use of multiple probiotic strains. Different strains or species seemed to exhibit different mechanisms of action, and how these differences influence the study outcome (i.e. glycaemic control) are yet to be determined in clinical trials. Lactobacilli (i.e. L. bulgaricus, L. plantarum, L.acidophilus), for instance, have been shown to be useful in lowering total cholesterol [42], increasing high-density lipoprotein level [43] and exhibiting anti-carcinogenic effects [44]. The bifidobacteria (i.e. B. longum, B. breve, B. adolescentis), on the other hand, are beneficial in reducing the secretion of pro-inflammatory cytokine’s (i.e. IL-12, TNF-α) [45], minimising the risk of colon cancer and reducing Helicobacter pylori infection symptoms [46]. Nevertheless, due to great variability of probiotic strains used in the reported RCT and the relatively small number of the existing RCT, subgroup analyses for assessment of the efficacy of each probiotic strain on hypoglycaemic, anti-inflammatory and anti-oxidant effects were not able to be performed in the current meta-analysis.
Another important consideration for interpreting the inconsistencies of the study findings is the homogeneity of the study populations. The study by Andreasen et al. [24], for instance, have included three different groups of subject participants [i.e. T2DM patients (n = 18), subjects with impaired glucose tolerance (n = 5) and healthy subjects (n = 22)]. The heterogeneity of the subjects in this study [24] could be the possible reason for the absent effect on inflammatory parameters. The heterogeneity of subjects or the absence of standardisation in subject population could lead to variation in results, overestimation and bias [47]. In addition, neither of these studies has profiled the changes of gut microbiota and evaluated the quality of life of T2DM patients upon administration of probiotics. No 16
published studies have investigated the role of probiotics on gut hormone regulation as well. Well-designed clinical trials that address the aforementioned limitations and considerations are needed to determine the efficacy of probiotics in T2DM setting.
The marked increase of clinical studies on the application of probiotics in T2DM patients over the last two years is an acknowledgement of the potential usefulness of probiotics in managing glycaemic control [16]. Nevertheless, the quality of reporting for the majority of the RCT was low, lacking adequate information to facilitate understanding of the trial's design, conduct, analysis and interpretation, and to assess the validity of its findings. As revealed in the risk of bias graph [Figure 2(A)] and summary [Figure 2(B)], most of the RCT have unclear risk of bias. Of the six clinical studies included in this systematic review, three [8, 21, 24] did not report on the power calculation when determining their sample sizes; most RCT randomised a small number of participants (i.e. 34 - 60) [8, 20-24]. As such, it remains unknown if the effect of a given size could be detected in these studies [48]. Four [8, 21-23] RCT did not mention the concealment of their treatment allocation and the steps taken to conceal the sequence of intervention that were assigned. In RCT, it is vital to make sure that treatment allocation is conducted to eliminate all potential selection bias [49]. Most studies reported only the genus and species [21, 23], but not the strains of probiotics that were given to the intervention arm. Additionally, there was one study that did not reveal the dose of probiotics at all [21]. In all the clinical studies identified, none has indicated if an ITT analysis was performed [8, 20-24]. Also, all did not explicitly state the primary and secondary outcomes of the clinical trials. In addition, it is apparent that none of the studies reported on adverse events of the probiotic products used in their trials; therefore, the safety profile of these probiotics remain unknown.
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The present work has several limitations. Firstly, significant substantial unexplained interstudy heterogeneity was noted in most analyses except for FBG and MDA. Due to the small number of RCT included in this meta-analysis for certain outcome measures, most subgroup analyses were underpowered in assessing confounding factors (e.g. the efficacy of certain probiotic strains or blends) that would have influenced glycaemic control in T2DM patients. The lack of assessment of probiotic specific adverse events was another limitation.
5.0 Conclusion The current meta-analysis suggested moderate beneficial hypoglycaemic effects of certain probiotics, with significantly lower FBG. Findings on HBA1c, anti-inflammatory and antioxidative effects of probiotics in the clinical setting, however, remain inconsistent, and thus, merits further investigations in future clinical studies. Based on the current literature, well designed, prospective clinical studies investigating the effects of probiotic administration on glycaemic control in T2DM patients remain scarce. Existing clinical trials are limited by their variation in the study design, quality and depth of the methodologies employed, and thus hindering meaningful conclusions to be made.
Declaration of Interest No competing interest declared by the authors.
Authors Contribution Each author contributed equally in this study.
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Acknowledgements The authors thank the Ministry of Education Malaysia for financial support under the Fundamental Research Grant Scheme [600-RMI/FGRS 5/3 (22/2014)].
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http://www.marketsandmarkets.com/Market-Reports/probiotic-market-advancedtechnologies-and-global-market-69.html [12] Shida K, Sato T, Iizuka R, Hoshi R, Watanabe O, Igarashi T, et al. Daily intake of fermented milk with Lactobacillus casei strain Shirota reduces the incidence and duration of upper respiratory tract infections in healthy middle-aged office workers. Eur J Nutr. 2015:19. [13] Kim E-H, Hong H, Hong K-S, Choi K-S, Han Y-M, Kangwan N, et al. High Concentrated Probiotics Improve Inflammatory Bowel Diseases Better than Commercial Concentration of Probiotics. J Food Drug Anal. 2012;20:292-5.
20
[14] Wong S, Jamous A, O'Driscoll J, Sekhar R, Weldon M, Yau CY, et al. A Lactobacillus casei Shirota probiotic drink reduces antibiotic-associated diarrhoea in patients with spinal cord injuries: a randomised controlled trial. Br J Nutr. 2014;111:672-8. [15] Goldin BR, Gorbach SL. Clinical indications for probiotics: an overview. Clin Infect Dis. 2008;46. [16] Gomes AC, Bueno AA, Souza RGMd, Mota JF. Gut microbiota, probiotics and diabetes. Nutr J. 2014;13:1-13. [17] Carvalho BM, Saad MJA. Influence of gut microbiota on subclinical inflammation and insulin resistance. Mediators Inflamm. 2013:1-13. [18] Ruan Y, Sun J, He J, Chen F, Chen R, Chen H. Effect of Probiotics on Glycemic Control: A Systematic Review and Meta-Analysis of Randomized, Controlled Trials. PloS One. 2015;10. [19] Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0 [updated March 2011]. In: Higgins J, Green S, editors.: The Cochrane Collaboration; 2011. [20] Ejtahed H, Mohtadi-Nia J, Homayouni-Rad A, Niafar M, Asgari-Jafarabadi M, Mofid V. Probiotic yogurt improves antioxidant status in type 2 diabetic patients. Nutrition 2012;28:539-43. [21] Mazloom Z, Yousefinejad A, Dabbaghmanesh MH. Effect of probiotics on lipid profile, glycemic control, insulin action, oxidative stress and inflammatory markers in patients with Type 2 Diabetes: A clinical trial. Iran J Med Sci. 2013;38:38-43. [22] Asemi Z, Zare Z, Shakeri H, Sabihi S-s, Esmaillzadeh A. Effect of multispecies probiotic supplements on metabolic profiles, hs-CRP and oxidative stress in patients with type 2 diabetes. Ann Nutr Metab. 2013;63:1-9. [23] Ostadrahimi A, Taghizadeh A, Mobasseri M, Farrin N, Payahoo L, Ghheshlaghi ZB, et al. Effect of probiotic fermented Milk (Kefir) on glycemic control and lipid profile in type 2
21
diabetic patients: a randomized double-blind placebo-controlled clinical trial. Iran J Public Health. 2015;44:228-37. [24] Andreasen AS, Larsen N, Pedersen-Skovsgaard T, Berg RM, Moller K, Svendsen KD, et al. Effects of Lactobacillus acidophilus NCFM on insulin sensitivity and the systemic inflammatory response in human subjects. Br J Nutr. 2010;104:1831-8. [25] Nazaimoon WMW, Isa SHM, Mohamad WBW, Khir AS, kamaruddin NA, Kamarul IM, et al. prevalence of diabetes in Malaysia and usefulness of HbA1c as a diagnostic criterion. Diabet Med. 2013:1-4. [26] Stratton IM, Adler AI, Andrew H, Neil W, Matthews DR, Manley SE, et al. Association of glycaemia with macrovascular and microvascular complications of type 2 diabetes (UKPDS 35): a prospective observational study. Br Med J. 2000;321:405-12. [27] Soranzo N. Genetic determinants of variability in glycated hemoglobin (HbA1c) in humas: review of recent progress and prospects for use in diabetes care. Curr Diab Rep. 2011;11:562-9. [28] Noordzij M, Tripepi G, Dekker FW, Zocalli C, Tanck MW, Jager KJ. Sample size calculations: basic principles and common pitfalls. Nephrol Dial Transplant. 2010;24:138893. [29] Inzucchi SE, Bergenstal RM, Buse JB, Diamant M, Ferrannini E, Nauck M, et al. Management of hyperglycemia in Type 2 Diabetes: A patient-centered approach. Diabetes Care. 2012;35:1364-79. [30] Alsayadi M, Jawfi YA, Belarbi M, Soualem-Mami Z, Merzouk H, Sari DC, et al. Evaluation of anti hypeglycemia and anti hyperlipidemic activities of water kefir as probiotic on streptozotocin-induced diabetic wistar rats. J Diabetes Mellitus. 2014;4:85-95.
22
[31] Stenman LK, Waget A, Garret C, Klopp P, Burcelin R, Lahtinen S. Potential probiotic Bifidobacterium animalis ssp. lactis 420 prevents weight gain and glucose intolerance in diet-induced obese mice. Benef Microbes. 2014;5:437-45. [32] Yun SI, Park HO, Kang JH. Effect of Lactobacillus gasseri BNR17 on blood glucose levels and body weight in a mouse model of type 2 diabetes. J Appl Microbiol. 2009;107:1681-6. [33] Andersson U, Branning C, Ahrne S, Molin G, Alenfall J, Onning G, et al. Probiotics lower plasma glucose in the high-fat fed C57BL/6J mouse. Benef Microbes. 2010;1:189-96. [34] Dai C, Zhen C-Q, Meng FJ, Zhou Z, Sang L-x, Jiang M. VSL#3 probiotic exerts the anti inflammatory activity via P13k/Akt and NF-kB pathway in rat model of Dss-induced colitis. Mol Cell Biochem. 2013;374:1-11. [35] Valladares R, Sankar D, Li N, Williams E, Lai K-K, Abdelgeliel AS, et al. Lactobacillus johnsonii N6.2 mitigates the developement of type 1 diabetes in BB-DP rats. Plos One. 2010;5:1-9. [36] Henriksen EJ, Diamond-Stanic MK, Marchionne EM. Oxidative stress and the etiology of insulin resistance and type 2 diabetes. Free Radical Biol Med. 2011;51:993-9. [37] Faghihi T, Radfar M, Barmal M, Amini P, Qorabani M, Abdollahi M, et al. A randomized, placebo controlled trial of selenium supplementation in patients with type2 diabtes: Effect on glucose homeostasis, oxidative stress and lipid profile. Am J Ther. 2014;21:491-5. [38] Al-Rawi NH. oxidative stress, antioxidant status and lipid profile in the saliva of type 2 diabetics. Diab Vasc Dis Res. 2011;8:22-8. [39] Zhang Y, Du R, Wang L, Zhang H. The antioxidative effects of probiotic Lactobacillus casei Zhang on the hyperlipidemic rats. Eur Food Res Technol. 2010;231:151-8.
23
[40] Harisa GI, Taha EI, Khalil AF, Salem MM. Oral administration of Lactobacillus Acidophilus restores nitric oxide level in diabetic rats. Aust j basic appl sci. 2009;3:2963-9. [41] Marteau P. Evidence of probiotic strain specificity makes extrapolation of results impossible from a strain to another, even from the same species. Ann Gastroentol Hepatol. 2011:1-3. [42] Nguyen TDT, Kang JH, Lee MS. Characterization of Lactobacillus plantarum PH04, a potential probiotic bacterium with cholesterol-lowering effects. Int J Food Microbiol. 2007;113:358-61. [43] Ranasinghe J, Silva S, Herath N. Changes of serum lipids and protein during probiotics feeding and its exposure. International Journal of Scientific and Research Publications. 2013;3. [44] Wollowski I, Rechkemmer G, Pool-Zobel BL. Protective role of probiotics and prebiotics in colon cancer. The American Journal of Clinical Nutrition. 2001;73:451s-5s. [45] Abd El-Gawad IA, El-Sayed EM, Hafez SA, El-Zeini HM, Saleh FA. The hypocholesterolaemic effect of milk yoghurt and soy-yoghurt containing bifidobacteria in rats fed on a cholesterol-enriched diet. Int Dairy J. 2005;15:37-44. [46] Myllyluoma E, Veijola L, Ahlroos T, Tynkkynen S, Kankuri E, Vapaatalo H, et al. Probiotic supplementation improves tolerance to Helicobacter pylori eradication therapy – a placebo-controlled, double-blind randomized pilot study. Aliment Pharmacol Ther. 2005;21:1263-72. [47] Noto H, Goto A, Tsujimoto T, Noda M. Cancer Risk in Diabetic Patients Treated with Metformin: A Systematic Review and Meta-analysis Plos One. 2012;7:1-9.
24
[48] Button KS, Ioannidis JP, Mokrysz C, Nosek BA, Flint J, Robinson ESJ, et al. Power failure: why small sample size undermines the reliability of neuroscience. Nat Rev Neurosci. 2013;14:365-76. [49] Schulz KF, Grimes DA. Allocation concealment in randomised trials: defending against deciphering. Lancet. 2002;359:614-8.
25
Figure Legends Figure 1. Study Selection Process Figure 2. Risk of Bias (A) Graph, and (B) Summary Figure 3. Forest Plot of the Effect of Probiotics on (A) HbA1c, and (B) FBG Supplementary Figure 1. Forest Plot of the Effect of Probiotics on (A) HOMA-IR, and (B) Fasting Plasma Insulin Supplementary Figure 2. Forest Plot of the Effect of Probiotics on (A) CRP, and (B) IL-6 Supplementary Figure 3. Forest Plot of the Effect of Probiotics on MDA
26
Table 1. Clinical Studies on the Efficacy of Probiotics in Type 2 Diabetes Mellitus Patients (n = 6)
Author,
Probiotic Strains (Dose)
Study Population
Intervention
(n)
Period
Country
Mohamadshahi Lactobacillus delbrueckii subsp. et al. (9), Iran
bulgaricus1
T2DM patients (n =
8 weeks
54)
Study Findings Hypoglyca
Anti-
Anti-
emic
inflammatory
oxidative
HbA1c2, FBG
TNF-α2, IL-6,
-
CRP
Streptococcus thermophilus1 Bifidobacterium animalis subsp. lactis Bb12 (3.7 × 106 CFU/g) L. acidophilus (3.7 × 106 CFU/g) Ejtahed et al.
L. acidophilus La5 (7.23 × 106 CFU/g) T2DM patients (n =
(64), Iran
B. lactis Bb12 (6.04 × 106 CFU/g) L. bulgaricus1 Streptococcus thermophilus1
64)
6 weeks
HbA1c2, FBG2
-
SOD2, GPx2 , TAS MDA
Mazloom et al.
L. acidophilus1
T2DM patients (n =
(65), Iran
L. bulgaricus1
40)
6 weeks
FBG
IL-6
MDA
CRP
L. bifidum1 L. casei1 Asemi et al.
L. acidophilus (2 × 109 CFU/g)
T2DM patients (n =
(69), Iran
L. rhamnosus (1.5 × 109 CFU /g)
54)
8 weeks
CRP2
HbA1c,
GSH2,
FBG2
TAC
L. bulgaricus (2 × 108 CFU /g) L. casei (7 × 109 CFU /g) S. thermophilus (1.5 × 109 CFU /g) B. longum (7 × 109 CFU /g) B. breve (2 × 1010 CFU /g) Ostadrahimi et
L. casei (2 × 106 CFU /mL)
T2DM patients (n =
al. (67), Iran
L. acidophilus (3×106 CFU /mL)
60)
8 weeks
HbA1c2,
-
-
FBG2
B. lactis (0.5 × 106 CFU /mL) Andreasen et
L. acidophilus NCFM (1 × 1010 CFU
T2DM patients (n =
al. (68),
/g)
18)
4 weeks
No changes No changes in in HbA1c
TNF-α
-
Denmark3
Impaired glucose
FBG
tolerance (n = 5)
IL-6, IL-1rA CRP
Healthy subjects (n =22) 1
No dose or strength was reported in this study.
2
Significant difference was noted between the intervention and placebo groups (post-intervention).
3
Excluded from the meta-analysis.
CRP = C-reactive protein; FBG = Fasting blood glucose; GPx = Glutathione peroxidase; GSH = Gluthathione; HbA1c = Glycated haemoglobin; IL-6 = Interleukin-6; IL-1rA = IL-1 receptor antagonist; MDA = Malondialdehyde; SOD = Superoxide dismutase; TAC = Total anti-oxidant capacity; TAS = Total anti-oxidant status; TNF-α = Tumor Necrosis Factor-α
Table 2. Results of Subgroup Analyses of RCT in Meta-analysis Subgroups
Hypoglycaemic Effects HbA1c (%) n
MD
P
(95%CI)
Anti-inflammatory Effects
FBG (mmol/L) I2
Pheterogeneity
n
(%)
MD
P
(95%CI)
Fasting Plasma Insulin (µIU/mL) I2
Pheterogeneity
n
(%)
MD
P
(95%CI)
CRP (mg/L)
I2
Pheterogeneit
(%)
y
52
0.15
n
MD
P
(95%CI)
I2
Pheterogeneity
(%)
Probiotic dose < 10
3
billion CFU ≥ 10
-0.45 (-
0.17
55
0.11
4
1.10, 0.19) 1
0.88 (0.69,
<
1.07)
0.00001
billion CFU
-0.81 (-
0.03
47
0.13
2
1.55, -0.07) -
-
1
1.55 (-
0.07
2
0.13, 3.23)
-0.99 (-
<
1.19, -0.79)
0.00001
-
-
1
-0.07 (-
0.24
28
0.24
-0.97 (-
<
-
-
1.25, -
0.00001
0.52
-
-
-0.93 (-
<
0
0.34
1.20, -
0.00001
0.50
87
0.006
0.31
-
-
0.52
-
-
-0.93 (-
<
0
0.34
1.20, -
0.00001
0.82, 0.67)
-2.19 (-
<
2.90, -
0.00001
-
-
1
1.48)
0.69)
Duration of intervention ≤ 6 weeks
1
0.00 (-0.50,
1.00
-
-
2
0.50) >6 weeks
3
-0.19 (-
-0.18 (-
0.71
0
0.97
2
1.09, 0.74) 0.79
92
< 0.00001
3
1.57, 1.19)
1.55 (-
0.07
52
0.15
1
0.13, 3.23)
-1.02 (-
<
1.22, -0.81)
0.00001
28
0.25
1
0.27 (0.56, 1.10)
-2.19 (-
<
2.90, -
0.00001
-
-
2
1.48)
0.66)
Probiotic dosage forms Capsule
1
0.88 (0.69,
<
1.07)
0.00001
Yogurt or
3
-0.45 (-
0.17
kefir
-
-
2
55
0.11
3
1.10, 0.19)
-0.98 (-
<
1.19, -0.78)
0.00001
-1.22 (-
0.09
0
0.55
2
63
0.07
1
-0.01 (-
1.00
97
< 0.00001
2
0.65
-
-
1
4.34, 4.32)
2.62, 0.19)
0.47 (-
-0.41 (1.62, 0.79)
1.58, 2.52)
-0.49 (1.44, 0.46)
Probiotic genus Single
0
-
-
-
-
1
-0.22 (-
0.86
-
-
1
2.74, 2.30) Multiple
4
-
-
-
-
4
-1.01 (1.67, -0.35)
2.23 (1.01,
0.0003
-
-
1
3.45) 0.14
46
0.14
2
-1.04 (3.62, 1.54)
0.27 (0.56, 4.10)
0.43
83
0.02
2
0.66)
Figures Figure 1. Study Selection Process
27
Figure 2(A). Risk of Bias Graph
Figure 2(B). Risk of Bias Summary
28
Figure 3(A). Forest Plot of the Effect of Probiotics on HbA1c
29
Figure 3(B). Forest Plot of the Effect of Probiotics on FBG
30
Highlights • • •
Significant reduction in FBG was noted in the probiotic group. Inconsistent effects of probiotics on HbA1c, inflammation and oxidative stress. Clinical studies must consider probiotic strains and study population.
31
S0168-8227(16)30164-4 http://dx.doi.org/10.1016/j.diabres.2016.06.014 DIAB 6672
To appear in:
Diabetes Research and Clinical Practice
Received Date: Revised Date: Accepted Date:
18 January 2016 23 May 2016 6 June 2016
Please cite this article as: S. Samah, K. Ramasamy, S.M. Lim, C.F. Neoh, Probiotics for the Management of Type 2 Diabetes Mellitus: A Systematic Review and Meta-analysis, Diabetes Research and Clinical Practice (2016), doi: http://dx.doi.org/10.1016/j.diabres.2016.06.014
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Title: Probiotics for the Management of Type 2 Diabetes Mellitus: A Systematic Review and Meta-analysis
Authors: Syamimi Samah1, Kalavathy Ramasamy1,2, Siong Meng Lim1,2, Chin Fen Neoh1,2*
Affiliations: 1
Faculty of Pharmacy, Universiti Teknologi MARA (UiTM), 42300 Bandar Puncak Alam,
Selangor Darul Ehsan, Malaysia. 2
Collaborative Drug Discovery Research (CDDR) Group, Pharmaceutical and Life Sciences
Community of Research, Universiti Teknologi MARA (UiTM), 40450 Shah Alam, Selangor Darul Ehsan, Malaysia.
*Corresponding
author:
Chin
Fen
Neoh,
Phone:
+603-32584708,
E-mail:
[email protected]
Keyword: probiotics; glycaemic; type 2 diabetes mellitus; review Abstract word count: 250 Manuscript word count: 4451
1
ABSTRACT Aims: To systematically review evidence of probiotic interventions against type 2 diabetes mellitus (T2DM) and analyse the effects of probiotics on glycaemic control among T2DM patients.
Methods: Electronic search using five electronic databases was performed until October 2015. Relevant studies were identified, extracted and assessed for risk of bias. The primary outcomes of this review were glycated haemoglobin (HbA1c) and fasting blood glucose (FBG). Fasting plasma insulin, Homeostasis Model Assessment-Insulin Resistance, Creactive protein, Interleukin-6 and Malondialdehyde, were identified as the secondary outcomes. Mean differences (MD) between probiotics and control groups for all outcomes were pooled using either Fixed- or Random-Effect Model. Statistical heterogeneity was assessed using I² and Chi² tests.
Results: Six randomised controlled trials (RCTs) were included in the systematic review, whereas only five were included in meta-analysis. Most RCTs were presented with low or unclear risk of bias. When compared to placebo, FBG was significantly lower with probiotic consumption (MD = -0.98 mmol/L; 95% CI: -1.17, 0.78, p < 0.00001), with moderate but insignificant heterogeneity noted. Insignificant changes between the groups were also noted for HbA1c and other secondary outcomes.
Conclusions: A moderate hypoglycaemic effect of probiotics, with a significantly lower FBG was noted. Findings on HbA1c, anti-inflammatory and anti-oxidative effects of probiotics in the clinical setting, however, remain inconsistent. The findings imply the need for well-
2
designed clinical studies to further assess the potential beneficial effects of probiotics in management of T2DM.
3
1.0 Introduction Type 2 diabetes mellitus (T2DM), a metabolic disease characterised by hyperglycaemia, is associated with either insensitivity of insulin or lack of insulin secretion [1]. It is the leading cause of cardiovascular disorders, blindness, end-stage renal failure, amputations and hospitalisation [2]. The incidence of T2DM is increasing. In 2011, 366 million adults worldwide were estimated to suffer from diabetes mellitus. The number is projected to increase to 592 million by year 2035 [3]. In addition, the management of T2DM is costly. In 2010, the global estimation of diabetes expenditures was USD376 billion; the expenditure is predicted to increase to USD490 billion in the next 20 years [4]. Given its substantial health and socio-economic burden, identifying an optimal therapy for T2DM is important.
The underlying mechanisms of the abnormal rise of blood glucose level are complex and multi-factorial [5]. T2DM associated risk factors that have already been identified include age, genetic predisposition, sedentary lifestyle, diet patterns and stress [6]. Recently, emerging data suggested that gut microbiota may have an important role in progression and development of T2DM. It was reported that when the microbiome balance is shifted in favour of the unhealthy ones, the level of metabolic endotoxin will increase and potentially trigger a chronic, low-grade inflammation [7]. The release of inflammatory cytokines can cause oxidative stress [8], and ultimately, lead to destruction of β-cells in the pancreas. It was found that probiotic consumption could increase the amount of beneficial bacteria (i.e. Bifidobacteria) in the gut, which could in turn reduce intestinal permeability towards lipopolysaccharide (LPS) produced by unhealthy gut microorganisms, and altogether attenuate systemic inflammation responses [9]. As such, modulating gut microbiota through dietary interventions (e.g. probiotic intake) may be useful in the prevention and control of inflammatory metabolic disorders including T2DM.
4
Probiotics are live microorganisms that when administered in sufficient amounts can confer health benefit to their host [10]. Lactobacilli and bifidobacteria are the two most common types of probiotics [5]. The global probiotic market was estimated at USD33.19 billion in 2015 and it is projected to reach USD46.55 billion by 2020; dominated by Asia-Pacific market [11]. The applications of probiotics as alternative biotherapeutics have been successfully demonstrated in treatment of respiratory infection [12], inflammatory bowel disease [13], antibiotic associated diarrhoea [14] and ulcerative colitis [15]. In spite of the booming in vitro and in vivo probiotic studies against metabolic diseases such as T2DM, their application at clinical settings remains scarce [16, 17]. In fact, the findings from the very few clinical trials that have been conducted were inconsistent. The most recent systematic review and meta-analysis on probiotic use in glycaemic control comprised of 17 trials, involving a broad range of study populations [i.e. healthy participants, T2DM patients, patients with hypercholesterolaemia,
non-alcoholic steatohepatitis or metabolic syndrome, obese
populations and patients with gestational diabetes mellitus (GDM)]. The findings, however, were limited by substantial inter-study clinical heterogeneity [18]. In addition, the effects of probiotics against vital parameters like glycated haemoglobin (HbA1c), anti-inflammatory and anti-oxidative markers were not assessed [18]. This systematic review and meta-analysis focused mainly on clinical studies that have investigated the efficacy of probiotics in T2DM patients, highlighting areas that were not usually addressed by previous review (Supplementary Table 1): the effect of probiotic on HbA1c and fasting blood glucose (FBG), anti-inflammation and anti-oxidation.
2.0 Material and methods 2.1 Literature Search Strategy
5
A search of electronic databases, including EMBASE, PubMed/Medline, SpringerLink, the Cochrane Library and trial registry website (ClinicalTrials.gov) was performed. The final search was carried out in October 2015, using combinations of search terms which included ‘diabetes mellitus’, ‘probiotics’, ‘lactobacilli’, ‘bifidobacter’, ‘streptococcus’, ‘microbiota’, ‘microflora’, ‘microbiome’, ‘gut hormone’, ‘insulin sensitivity’, ‘anti-oxidant’ and ‘antiinflammatory’. In addition, citations in each paper were also used to further identify relevant papers that were not found in electronic databases.
2.2 Study Selection The inclusion criteria for this systematic review and meta-analysis were as follow: (a) randomised controlled trials (RCT), (b) adult T2DM patients (i.e. age of 18 and above), and (c) the use of probiotics (of any form, including capsule, yogurt and kefir) as an intervention. On the other hand, studies presented only as abstracts with no subsequent full report of findings, on-going clinical studies, quasi-randomised study design, in vitro or in vivo studies, review papers, non-English literatures, studies involving patients with GDM, Type 1 diabetes mellitus (T1DM), any other metabolic diseases such as obesity or hypercholesterolaemia, studies with no probiotic genus/strains reported and studies using synbiotics (i.e. probiotics combined with prebiotics) were all excluded. Whilst the primary outcomes for meta-analysis were HbA1c and FBG, the secondary outcomes included fasting plasma insulin, homeostasis model assessment of insulin resistance (HOMA-IR), inflammatory markers [i.e. C-reactive protein (CRP), interleukin-6 (IL-6)] and anti-oxidative or oxidative stress markers [i.e. malondialdehyde (MDA)]. The eligibility of all potential studies identified for inclusion was independently assessed by two review authors (SS and CFN). Discrepancies on study inclusion were resolved through discussion and consensus.
6
2.3 Data Extraction and Collection Data (e.g. probiotic strains, dose, duration of intervention, dosage forms, sample size, baseline and post-intervention values for the aforementioned outcome measures) obtained from the included studies were independently extracted by two authors (SS and CFN), using a standardised, electronic abstraction form.
2.4 Assessments of Risk Bias and Publication Bias Risk bias for the included studies were independently assessed (SS and CFN) using criteria as outlined in the Cochrane Handbook for Systematic Reviews of Interventions [19]. The assessment included selection bias (method for random sequence generation and allocation concealment), performance bias (blinding of participants and personnel), detection bias (blinding of outcome assessment), attrition bias (incomplete outcome data), reporting bias (selective reporting) and other sources of bias. In addition, sample size calculation and funding declaration associated with each clinical trial were also assessed. Any disagreement was resolved by discussion. Potential publication bias was assessed using visual inspection of Funnel Plots (if RCTs included in meta-analysis < 10) and Egger’s Test (if RCTs included in meta-analysis > 10).
2.5 Data Analysis Statistical analyses were performed by employing the Review Manager Software version 5.3 (The Nordic Cochrane Centre, Copenhagen, Denmark). Mean differences (MD) between intervention (probiotics) and control group for each aforementioned outcome were first pooled using the Fixed-Effect Model. The statistical heterogeneity in each meta-analysis was assessed using I² and Chi² statistics. Heterogeneity was regarded as substantial if I² > 50% or I² > 25% with a low p value of < 0.10 in the Chi² test. In this case, the Random-Effect Model
7
was performed. In order to explore the source of heterogeneity, subgroup analyses were conducted by comparing the mean difference for each outcome measure as follow: (a) probiotic dose [< 10 9 colony forming unit (CFU) versus ≥ 10 9 CFU], (b) duration of probiotic intervention (≤ 6 weeks versus > 6 weeks), (c) probiotic dosage forms (capsule versus yogurt or kefir), and (d) probiotic genus (single versus multiple genus). Also, sensitivity analyses were performed to examine the robustness of meta-analysis findings. This was achieved by excluding studies with small sample size (i.e. < 20 patients) for each intervention and control group.
3.0 Results 3.1 Description of Included Studies Out of the 260 records that have been identified through the search (after removal of duplicates), 254 records were excluded based on the pre-specified criteria (Figure 1). Table 1 outlines the details of all eligible studies and their findings. Whilst a total of six eligible studies that have investigated the use of probiotics in T2DM patients were included in the qualitative synthesis (systematic review) [8, 20-24], only five were included in quantitative synthesis (meta-analysis) [8, 20-23]; all studies were published within the past five years. The study by Andreasen et al. [24] was excluded from the meta-analysis because findings for outcomes of interest exclusive for T2DM patients were not reported. There were two trials that used probiotics in yogurt form [8, 20], one in the form of kefir [23] and the remaining in capsule form [21, 22, 24]. Except for one Denmark-based study [24], all studies [8, 20-23] were conducted in Middle East countries (i.e. Iran). The majority of the trials (n = 4) used blends of various probiotic genera, including lactobacilli and bifidobacteria [8, 20, 22, 23]. No changes in study participants’ diabetic medication regimens (e.g. metformin, glibenclamide, glitazones) was reported in two of the studies trials [8, 23]. Two trials [20, 22]
8
were categorised as industry sponsored whereas four studies explicitly stated no competing interests [8, 21, 23, 24].
3.2 Risk Bias and Publication Bias Figures 2(A) and 2(B) summarise the authors’ judgements on each risk of bias item for all six RCTs included in this systematic review. In general, most RCT were presented with either low or unclear risk of bias. Publication bias was not assessed using Egger’s regression given that RCTs included in this meta-analysis were less than 10 studies; the Funnel Plots for all outcome measures were approximately symmetric.
3.3 Hypoglycaemic Effects 3.3.1 HbA1c and FBG Figures 3(A) and 3(B) illustrate the Forest Plots of the pooled estimates of probiotics on HbA1c and FBG, respectively. All six studies [8, 20-24] investigated the hypoglycaemic effects of probiotics; four studies documented significant decrease (p < 0.05) in HbA1c and/ or FBG levels. In the current meta-analysis, no significant difference was noted in HbA1c (MD = -0.11%, 95% CI: -1.00, 0.78, p = 0.81) between the probiotic and control groups [Figure 3(A)]. Significant substantial inter-study heterogeneity was noted (I2 = 91%, p < 0.00001). Subgroup analyses (Table 2) revealed that the extreme inconsistency among four trials in HbA1c (I2 = 91%) was reduced to I2 = 55% when differences in probiotic dose and dosage form are accounted for. A significant increase (p < 0.05) in HbA1c was noted in trials using probiotic dose of ≥ 109 CFU and capsule dosage form. The findings, however, remain inconclusive as the number of trials included in these subgroups was small. No significant difference in HbA1c lowering effect of probiotics was observed in trials with administration
9
of probiotics > 6 weeks (p = 0.79). Subgroup analysis for probiotic genus was not performed as all trials included for HbA1c analysis used multiple probiotic genus products.
In contrast, a significantly lower FBG at 0.98 mmol/L (95% CI: -1.17, -0.78, p < 0.00001), but with non-significant moderate inter-study heterogeneity was noted (I2 = 32%, p = 0.21). Further to removal of study with small sample size (i.e. n < 20 for each group) and the use of Random-Effect Model, no change in the significance of the pooled estimates of FBG (MD = 0.98 mmol/L; 95% CI: -1.18, -0.78, p < 0.00001 and MD = -0.95 mmol/L; 95% CI: -1.52, 0.39, p = 0.001) was noted, respectively. Subgroup analysis revealed that a significantly lower FBG was noted in those trials with administration of probiotics > 6 weeks; greater consistency was observed within the subgroups as well (Table 2). The use of probiotic capsules has resulted in a significantly lower FBG with low heterogeneity (I2 = 0%, p = 0.55). Significantly lower FBG was noted in both subgroups receiving probiotic dose < 109 CFU and ≥ 109 CFU. No significant difference in FBG lowering effect of probiotics was observed in trials using single or multiple probiotic genus.
3.3.2 HOMA-IR and Fasting Plasma Insulin Three studies investigated the effects of probiotics against insulin resistance [21, 22, 24] but only one [22] with positive findings. Forest Plot of the pooled estimates of probiotics on HOMA-IR [Supplementary Figure 1(A)] revealed a non-significant difference between the groups (MD = -0.79, 95% CI: -2.71, 1.14, p = 0.42) but with significant substantial interstudy heterogeneity observed (I2 = 85%, p = 0.009). Subgroup analyses was not performed given the number of studies included was small (n = 2).
10
There were only three studies that documented the effects of probiotics on fasting insulin concentration [20-22]. There was, however, no significant difference in fasting plasma insulin (MD = 0.13 µIU/mL, 95% CI: -3.02, 3.28, p = 0.93) between the probiotic and control groups. The findings were presented with significant substantial inter-study heterogeneity (I2 = 95%, p < 0.00001) [Supplementary Figure 1(B)]. Subsequent removal of the study with small sample size [21] had led to no change in the significance of the pooled estimates of fasting plasma insulin (MD = -1.04 µIU/mL, 95% CI: -3.62, 1.54, p = 0.43). Subgroup analyses (Table 2) of trials using probiotic dose ≥ 109 CFU and > 6 weeks revealed significant reductions of fasting plasma insulin. Also, significant increase of fasting plasma insulin was noted in the trial using single probiotic genus; the findings, however, remain inconclusive as the number of trials included in these subgroups was small. The extreme inconsistency among three trials in fasting plasma insulin (I2 = 95%) was reduced to I2 = 52% when differences in probiotic dose and duration of trial were accounted for. There was no significant association between the pooled estimates of probiotics on fasting plasma insulin and probiotic dosage form.
3.4 Anti-inflammatory Effects A total of four studies reported on anti-inflammatory effects of probiotics, and all were with mixed responses [8, 21, 22, 24]. Both Forest Plots indicated that there were no significant differences in CRP [Supplementary Figure 2(A)] (MD = -0.47 mg/L, 95% CI: -1.25, 0.32, p = 0.25) and IL-6 [Supplementary Figure 2(B)] (MD = -0.57 pg/mL, 95% CI: -3.26, 2.12, p = 0.68) levels, respectively. Significant inter-study heterogeneity was observed in the overall analyses for CRP (I2 = 76%, p = 0.02) and IL-6 (I2 = 87%, p = 0.005) levels. The removal of a study with small sample size [21], however, led to significant reduction of CRP level (MD = -0.93 mg/L; 95% CI: -1.20, -0.66, p < 0.00001) and low heterogeneity (I2 = 0%, p = 0.34).
11
Subgroup analyses of trials (Table 2) revealed significant reductions of CRP in groups using probiotic dose ≥ 10 9 CFU and multiple probiotic genus for > 6 weeks; the findings, however, remain inconclusive as the number of trials included in these subgroups was small. The inconsistency among three trials in CRP (I2 = 75%) was reduced when differences in probiotic dose (I2 = 28%), probiotic genus (I2 = 0%) and duration of trial (I2 = 0%) were accounted for. There was no significant evidence for an association between reduction of CRP level and the probiotic dosage form. Subgroup analyses for IL-6 was not performed given the small number of studies included (n = 2).
3.5 Anti-oxidative Effects There were only three studies that documented the anti-oxidative properties of probiotics [2022]. As there was only one single study that investigated the changes of SOD, GPx, CAT, total antioxidant status [20] and GSH [22] after probiotic consumption, no pooled analysis was performed for the abovementioned parameters. Forest Plot of the pooled estimate of probiotics on MDA (Supplementary Figure 3) revealed non-significant difference between the groups (p = 0.54), with low inter-study heterogeneity noted (I2 = 0%, p = 0.90).
4.0 Discussion The current meta-analysis is the first to examine the pooled estimate of probiotics on HbA1c. The use of HbA1c is a gold standard in clinical management of T2DM [25] and it permits comparability among the published studies. A 1% reduction in HbA1c has been associated with 21% risk reduction of diabetes related-end points and 37% risk reduction for microvascular complications [26]. Hence, a 1% reduction in HbA1c is considered to be clinically relevant. The findings from the current meta-analysis revealed no significant difference in HbA1c between the probiotic and the control groups; substantial heterogeneity,
12
however, was noted across the clinical studies. Even though results of the subgroup analyses indicated that there were significant associations between the effects of probiotics on HbA1c and the probiotic dose or capsule dosage form, but not for the duration of probiotic intervention, these findings were limited by the small number of studies included in the subgroup analyses. One of the common limitations in all the studies included in this review is the fact that none investigated the long term effects of probiotics; all these studies were conducted in a period ranging from 4 to 8 weeks. Accordingly, the findings on HbA1c from these studies were doubtful given that the changes in HbA1c could only be detected every three months as per the life cycle of red blood cells [27]. In addition, only one study [23] in this review determined sample sizes based on the reduction in HbA1c between intervention and placebo groups; the other two studies which reported a power calculation were aimed to detect the differences in pro-inflammatory markers [i.e. hypersensitive (hs)-CRP] [22] or anti-oxidative enzymes (i.e. CAT) [20]. Of note, having sample size based on the primary outcome provides a better focus path for trial as well as adding quality to the results obtained [28, 29].
Consistent with Ruan et al. [18], a significantly lower FBG upon probiotic intake when compared to the control group was documented. A strength of the current findings is the fact that insignificant moderate inter-study heterogeneity was noted, as opposed to the findings by Ruan et al. [18]. Of note, the pooled estimate of probiotics on FBG in the current metaanalysis was primarily driven by the findings of Asemi et al. [22], in which the intake of probiotics exerted a preventive effect on the rise of FBG rather than resulting in a lower FBG level, as compared to placebo group. In addition, our subgroup analysis revealed that the lowering effect of FBG was significant in those trials with intervention period > 6 weeks. These clinical findings were consistent with the in vivo studies using diabetic mice and rat
13
models, which reported significant reductions of glycaemic parameters (i.e. FBG and 2 hours post prandial glucose), and improvement in glucose tolerance [30-32]. The intervention period in in vivo studies were usually longer (i.e. 8 to 20 weeks) [30-33], in comparison to the clinical studies (i.e. 4 to 8 weeks). The specific mechanisms underlying the hypoglycaemic effects of probiotics, however, remain unclear. Some researchers described these hypoglycaemic effects as the positive consequences of probiotic-mediated decrease in systemic inflammation or oxidative stress [5, 18].
Earlier meta-analysis by Ruan et al. [18] did not examine the pooled anti-inflammatory effects of probiotics. In the current meta-analysis, no significant differences in CRP and IL-6 levels, however, were noted in the probiotic group, from which significant heterogeneity observed. Our findings suggested that high probiotic dose, longer duration of probiotic intervention and the use of multiple probiotic genuses associated significantly with better anti-inflammatory effects of probiotics. Of note, the removal of study with small sample size [21] had led to significant reduction of CRP level and low heterogeneity among those in the probiotic group. The inconsistency of results had also been observed in vivo. Although a significant decrease of TNF-α and IL-6 levels were noted among colitis-induced rats fed with probiotics [34], yet another study revealed a statically indifferent insignificant decrease of IFN-γ [35]. It is important to note that these in vivo studies used different inflammatory markers, probiotic genus/strain and feeding duration, making it difficult to directly compare and assess the anti-inflammatory effects of probiotics.
Similar to systemic inflammation, the levels of free radical and oxidative stress in T2DM patients were also reported to be higher than the healthy subjects [36-38]. It has been postulated that probiotic consumption would increase the level of anti-oxidative enzymes (i.e.
14
SOD, GPx, CAT) which are able to rapidly scavenge reactive oxygen species, and therefore, reduce the rate of oxidative stress in T2DM patients [20, 21]. In agreement with the clinical studies [20, 22], the majority of the in vivo studies observed significantly increase antioxidative enzyme activities (i.e. SOD and GSH-Px) in hyperlipidaemic and diabetic rats [39, 40] after consumption of L. casei and L. acidophilus (7.56 x 10 7 to 2 x 1010 CFU/mL) for one to four weeks. The current meta-analysis, however, revealed a non-significant difference in MDA, with low inter-study heterogeneity noted.
Contrary to the findings by Ruan et al. [18], the current study revealed no significant difference in HOMA-IR in groups that have received probiotics. It is interesting to note that Ruan et al. [18] indicated an opposing pooled effect of probiotics on fasting plasma insulin in which a significant reduction was observed, particularly in the hyperglycaemic subgroup. The current study, however, suggested otherwise. The pooled effect of probiotics on fasting plasma insulin in the current meta-analysis was sensitive to the omission of RCT with small sample size. The inconsistencies in the pooled findings of fasting plasma insulin and insulin resistance between the current work and Ruan et al. [18] have hindered meaningful conclusions to be made and these data should be interpreted with caution given the substantial inter-study heterogeneity observed in both meta-analyses.
Also, there remain gaps in the knowledge albeit the increase of number of trials that investigate the efficacy of probiotics in T2DM in clinical settings. Inconsistencies in the findings were noted across the clinical studies included in this meta-analysis [8, 20-22, 24]. The possible reasons underlying this observation remain to be elucidated. It is believed that the beneficial effects of probiotics (i.e. hypoglycaemic, anti-inflammatory or anti-oxidative properties) could be highly strain specific. The use of a single strain, such as L. acidophilus
15
NCFM in the study by Andreasen et al. [24] and Lactobacillus spp. in the study by Mazloom et al. [21], could be the factor explaining the negative outcome observed. Marteau [41] claimed that the beneficial outcome of probiotic administration could be most likely achieved with the combined use of multiple probiotic strains. Different strains or species seemed to exhibit different mechanisms of action, and how these differences influence the study outcome (i.e. glycaemic control) are yet to be determined in clinical trials. Lactobacilli (i.e. L. bulgaricus, L. plantarum, L.acidophilus), for instance, have been shown to be useful in lowering total cholesterol [42], increasing high-density lipoprotein level [43] and exhibiting anti-carcinogenic effects [44]. The bifidobacteria (i.e. B. longum, B. breve, B. adolescentis), on the other hand, are beneficial in reducing the secretion of pro-inflammatory cytokine’s (i.e. IL-12, TNF-α) [45], minimising the risk of colon cancer and reducing Helicobacter pylori infection symptoms [46]. Nevertheless, due to great variability of probiotic strains used in the reported RCT and the relatively small number of the existing RCT, subgroup analyses for assessment of the efficacy of each probiotic strain on hypoglycaemic, anti-inflammatory and anti-oxidant effects were not able to be performed in the current meta-analysis.
Another important consideration for interpreting the inconsistencies of the study findings is the homogeneity of the study populations. The study by Andreasen et al. [24], for instance, have included three different groups of subject participants [i.e. T2DM patients (n = 18), subjects with impaired glucose tolerance (n = 5) and healthy subjects (n = 22)]. The heterogeneity of the subjects in this study [24] could be the possible reason for the absent effect on inflammatory parameters. The heterogeneity of subjects or the absence of standardisation in subject population could lead to variation in results, overestimation and bias [47]. In addition, neither of these studies has profiled the changes of gut microbiota and evaluated the quality of life of T2DM patients upon administration of probiotics. No 16
published studies have investigated the role of probiotics on gut hormone regulation as well. Well-designed clinical trials that address the aforementioned limitations and considerations are needed to determine the efficacy of probiotics in T2DM setting.
The marked increase of clinical studies on the application of probiotics in T2DM patients over the last two years is an acknowledgement of the potential usefulness of probiotics in managing glycaemic control [16]. Nevertheless, the quality of reporting for the majority of the RCT was low, lacking adequate information to facilitate understanding of the trial's design, conduct, analysis and interpretation, and to assess the validity of its findings. As revealed in the risk of bias graph [Figure 2(A)] and summary [Figure 2(B)], most of the RCT have unclear risk of bias. Of the six clinical studies included in this systematic review, three [8, 21, 24] did not report on the power calculation when determining their sample sizes; most RCT randomised a small number of participants (i.e. 34 - 60) [8, 20-24]. As such, it remains unknown if the effect of a given size could be detected in these studies [48]. Four [8, 21-23] RCT did not mention the concealment of their treatment allocation and the steps taken to conceal the sequence of intervention that were assigned. In RCT, it is vital to make sure that treatment allocation is conducted to eliminate all potential selection bias [49]. Most studies reported only the genus and species [21, 23], but not the strains of probiotics that were given to the intervention arm. Additionally, there was one study that did not reveal the dose of probiotics at all [21]. In all the clinical studies identified, none has indicated if an ITT analysis was performed [8, 20-24]. Also, all did not explicitly state the primary and secondary outcomes of the clinical trials. In addition, it is apparent that none of the studies reported on adverse events of the probiotic products used in their trials; therefore, the safety profile of these probiotics remain unknown.
17
The present work has several limitations. Firstly, significant substantial unexplained interstudy heterogeneity was noted in most analyses except for FBG and MDA. Due to the small number of RCT included in this meta-analysis for certain outcome measures, most subgroup analyses were underpowered in assessing confounding factors (e.g. the efficacy of certain probiotic strains or blends) that would have influenced glycaemic control in T2DM patients. The lack of assessment of probiotic specific adverse events was another limitation.
5.0 Conclusion The current meta-analysis suggested moderate beneficial hypoglycaemic effects of certain probiotics, with significantly lower FBG. Findings on HBA1c, anti-inflammatory and antioxidative effects of probiotics in the clinical setting, however, remain inconsistent, and thus, merits further investigations in future clinical studies. Based on the current literature, well designed, prospective clinical studies investigating the effects of probiotic administration on glycaemic control in T2DM patients remain scarce. Existing clinical trials are limited by their variation in the study design, quality and depth of the methodologies employed, and thus hindering meaningful conclusions to be made.
Declaration of Interest No competing interest declared by the authors.
Authors Contribution Each author contributed equally in this study.
18
Acknowledgements The authors thank the Ministry of Education Malaysia for financial support under the Fundamental Research Grant Scheme [600-RMI/FGRS 5/3 (22/2014)].
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Figure Legends Figure 1. Study Selection Process Figure 2. Risk of Bias (A) Graph, and (B) Summary Figure 3. Forest Plot of the Effect of Probiotics on (A) HbA1c, and (B) FBG Supplementary Figure 1. Forest Plot of the Effect of Probiotics on (A) HOMA-IR, and (B) Fasting Plasma Insulin Supplementary Figure 2. Forest Plot of the Effect of Probiotics on (A) CRP, and (B) IL-6 Supplementary Figure 3. Forest Plot of the Effect of Probiotics on MDA
26
Table 1. Clinical Studies on the Efficacy of Probiotics in Type 2 Diabetes Mellitus Patients (n = 6)
Author,
Probiotic Strains (Dose)
Study Population
Intervention
(n)
Period
Country
Mohamadshahi Lactobacillus delbrueckii subsp. et al. (9), Iran
bulgaricus1
T2DM patients (n =
8 weeks
54)
Study Findings Hypoglyca
Anti-
Anti-
emic
inflammatory
oxidative
HbA1c2, FBG
TNF-α2, IL-6,
-
CRP
Streptococcus thermophilus1 Bifidobacterium animalis subsp. lactis Bb12 (3.7 × 106 CFU/g) L. acidophilus (3.7 × 106 CFU/g) Ejtahed et al.
L. acidophilus La5 (7.23 × 106 CFU/g) T2DM patients (n =
(64), Iran
B. lactis Bb12 (6.04 × 106 CFU/g) L. bulgaricus1 Streptococcus thermophilus1
64)
6 weeks
HbA1c2, FBG2
-
SOD2, GPx2 , TAS MDA
Mazloom et al.
L. acidophilus1
T2DM patients (n =
(65), Iran
L. bulgaricus1
40)
6 weeks
FBG
IL-6
MDA
CRP
L. bifidum1 L. casei1 Asemi et al.
L. acidophilus (2 × 109 CFU/g)
T2DM patients (n =
(69), Iran
L. rhamnosus (1.5 × 109 CFU /g)
54)
8 weeks
CRP2
HbA1c,
GSH2,
FBG2
TAC
L. bulgaricus (2 × 108 CFU /g) L. casei (7 × 109 CFU /g) S. thermophilus (1.5 × 109 CFU /g) B. longum (7 × 109 CFU /g) B. breve (2 × 1010 CFU /g) Ostadrahimi et
L. casei (2 × 106 CFU /mL)
T2DM patients (n =
al. (67), Iran
L. acidophilus (3×106 CFU /mL)
60)
8 weeks
HbA1c2,
-
-
FBG2
B. lactis (0.5 × 106 CFU /mL) Andreasen et
L. acidophilus NCFM (1 × 1010 CFU
T2DM patients (n =
al. (68),
/g)
18)
4 weeks
No changes No changes in in HbA1c
TNF-α
-
Denmark3
Impaired glucose
FBG
tolerance (n = 5)
IL-6, IL-1rA CRP
Healthy subjects (n =22) 1
No dose or strength was reported in this study.
2
Significant difference was noted between the intervention and placebo groups (post-intervention).
3
Excluded from the meta-analysis.
CRP = C-reactive protein; FBG = Fasting blood glucose; GPx = Glutathione peroxidase; GSH = Gluthathione; HbA1c = Glycated haemoglobin; IL-6 = Interleukin-6; IL-1rA = IL-1 receptor antagonist; MDA = Malondialdehyde; SOD = Superoxide dismutase; TAC = Total anti-oxidant capacity; TAS = Total anti-oxidant status; TNF-α = Tumor Necrosis Factor-α
Table 2. Results of Subgroup Analyses of RCT in Meta-analysis Subgroups
Hypoglycaemic Effects HbA1c (%) n
MD
P
(95%CI)
Anti-inflammatory Effects
FBG (mmol/L) I2
Pheterogeneity
n
(%)
MD
P
(95%CI)
Fasting Plasma Insulin (µIU/mL) I2
Pheterogeneity
n
(%)
MD
P
(95%CI)
CRP (mg/L)
I2
Pheterogeneit
(%)
y
52
0.15
n
MD
P
(95%CI)
I2
Pheterogeneity
(%)
Probiotic dose < 10
3
billion CFU ≥ 10
-0.45 (-
0.17
55
0.11
4
1.10, 0.19) 1
0.88 (0.69,
<
1.07)
0.00001
billion CFU
-0.81 (-
0.03
47
0.13
2
1.55, -0.07) -
-
1
1.55 (-
0.07
2
0.13, 3.23)
-0.99 (-
<
1.19, -0.79)
0.00001
-
-
1
-0.07 (-
0.24
28
0.24
-0.97 (-
<
-
-
1.25, -
0.00001
0.52
-
-
-0.93 (-
<
0
0.34
1.20, -
0.00001
0.50
87
0.006
0.31
-
-
0.52
-
-
-0.93 (-
<
0
0.34
1.20, -
0.00001
0.82, 0.67)
-2.19 (-
<
2.90, -
0.00001
-
-
1
1.48)
0.69)
Duration of intervention ≤ 6 weeks
1
0.00 (-0.50,
1.00
-
-
2
0.50) >6 weeks
3
-0.19 (-
-0.18 (-
0.71
0
0.97
2
1.09, 0.74) 0.79
92
< 0.00001
3
1.57, 1.19)
1.55 (-
0.07
52
0.15
1
0.13, 3.23)
-1.02 (-
<
1.22, -0.81)
0.00001
28
0.25
1
0.27 (0.56, 1.10)
-2.19 (-
<
2.90, -
0.00001
-
-
2
1.48)
0.66)
Probiotic dosage forms Capsule
1
0.88 (0.69,
<
1.07)
0.00001
Yogurt or
3
-0.45 (-
0.17
kefir
-
-
2
55
0.11
3
1.10, 0.19)
-0.98 (-
<
1.19, -0.78)
0.00001
-1.22 (-
0.09
0
0.55
2
63
0.07
1
-0.01 (-
1.00
97
< 0.00001
2
0.65
-
-
1
4.34, 4.32)
2.62, 0.19)
0.47 (-
-0.41 (1.62, 0.79)
1.58, 2.52)
-0.49 (1.44, 0.46)
Probiotic genus Single
0
-
-
-
-
1
-0.22 (-
0.86
-
-
1
2.74, 2.30) Multiple
4
-
-
-
-
4
-1.01 (1.67, -0.35)
2.23 (1.01,
0.0003
-
-
1
3.45) 0.14
46
0.14
2
-1.04 (3.62, 1.54)
0.27 (0.56, 4.10)
0.43
83
0.02
2
0.66)
Figures Figure 1. Study Selection Process
27
Figure 2(A). Risk of Bias Graph
Figure 2(B). Risk of Bias Summary
28
Figure 3(A). Forest Plot of the Effect of Probiotics on HbA1c
29
Figure 3(B). Forest Plot of the Effect of Probiotics on FBG
30
Highlights • • •
Significant reduction in FBG was noted in the probiotic group. Inconsistent effects of probiotics on HbA1c, inflammation and oxidative stress. Clinical studies must consider probiotic strains and study population.
31