Systematic review assessing the effectiveness of dietary intervention on gut microbiota in adults with type 2 diabetes

Eligibility criteria

Included studies were RCTs or specific arms of non-RCTs that reported on the effectiveness of dietary and physical activity/exercise interventions on modulating the gut microbiota and improving glucose control (i.e. HbA_1c, fasting blood glucose, 2 h frequently sampled [2 h^fs] OGTT and/or HOMA-IR or insulin). Participants of interest were adults with type 2 diabetes. Studies reporting on lifestyle interventions in adults with type 1 diabetes were excluded.

It was a requirement that the gut microbiota was measured from stool samples using any form of sequencing technique targeting the 16S ribosomal RNA gene. No standardised criteria defining type 2 diabetes mellitus were specified because the methods for clinical diagnosis vary between studies. However, individuals with type 2 diabetes mellitus had to be clinically diagnosed with their diabetes controlled by diet, oral medication and/or insulin.

Eligible lifestyle interventions included those that targeted diet, physical activity/exercise, use of prebiotics, probiotics or synbiotics, or a combination of these. Studies that included pharmacotherapy, herbal remedies and surgery were excluded. Studies where individuals were already receiving medication as part of their standard care and with no increase in dose during the study were eligible for inclusion.

The primary outcomes of interest were modulation of the gut microbiota, including changes in the relative abundance of bacteria and diversity changes (α and β), and glucose control. The composition of the gut microbiota could also be reported as a secondary outcome. Other secondary outcomes were changes in weight and inflammatory markers (i.e. IL-6, TNF-α, IL-1 receptor antagonist [IL-1RA], C-reactive protein [CRP] and faecal lipocalin-2).

Search strategy

MEDLINE, EMBASE, Scopus, Web of Science and the Cochrane Library were searched using a combination of MeSH headings and keywords to identify potentially relevant literature (see electronic supplementary material [ESM] Methods). Searches were completed up to 9 February 2017 and were limited to studies published in the English language. Manual searching (i.e. reference lists and citation searching) of studies fulfilling the eligibility criteria was also conducted.

Selection of studies

Two authors (D. Houghton and T. Hardy) independently screened the titles and abstracts of all the studies generated by the search. Full-text articles retained from the first stage were reassessed independently by the same two authors and assessed by a third independent author (C. Stewart) using a study-selection form. Any disagreements were resolved via discussion with the review team.

Data extraction

Details of the study population, interventions, comparators and outcomes were captured using a data-extraction form. Data were extracted from all included studies independently by two members of the review team (D. Houghton and T. Hardy). Where applicable, the corresponding authors from the retained studies were contacted via email to request additional information. The Cochrane Collaboration risk of bias tool [28] was used to assess the methodological quality of the included studies and the overall risk of bias (i.e. low, unclear or high). All studies were independently assessed for methodological quality by two authors (D. Houghton and L. Avery).

Data synthesis

Insufficient data were reported to enable overall effect-size estimates to be calculated using meta-analyses for all outcomes of interest; therefore, the study authors were contacted to request additional outcome data where applicable. This enabled meta-analyses to be conducted for the composition of the gut microbiota (Bifidobacterium, Roseburia and Lactobacillus) and for fasting blood glucose, HbA_1c, insulin and HOMA-IR levels. Results for other outcomes of interest are presented narratively. Data are expressed as standardised mean difference (SMD) (95% CI) between treatment and control/comparator groups.

Characteristics of participants with type 2 diabetes

The total sample size across the included studies was 395, including at least 225 men and 135 women; one study failed to report the sex of participants (n = 35) [35]. Participants were aged 33–77 years (58 ± 4 years [mean ± SD]) with a BMI range of 25–45 kg/m². Six studies recruited only individuals diagnosed with type 2 diabetes mellitus [29, 30, 32, 33, 34, 35]. One study compared participants with type 2 diabetes mellitus and control participants at baseline, prior to the introduction of any intervention, however, these 13 participants were not included in the analyses reported here [32]. Two studies [31, 36] reported on a sample including individuals with and without type 2 diabetes mellitus (Table 1). Only one study reported the ethnicity of participants and none of the included studies reported the time since diagnosis of type 2 diabetes mellitus. Five studies reported treatment regimens: insulin injection (n = 11), insulin secretagogue (n = 34), metformin (n = 52), sulfonylurea (n = 12), α-glucosidase inhibitor (n = 41), sitagliptin (n = 7), thiazolidinedione (n = 1), peroxisome proliferator-activated receptor γ (PPAR-γ) antagonist (n = 15) or statins (n = 5) [30, 31, 34]. One study recruited individuals who managed their type 2 diabetes mellitus through diet only [29], and two studies used eligibility criteria that restricted the use of insulin but allowed hypoglycaemic drugs and dietary interventions, but provided no specific details [32, 33]. Two studies [35, 36] did not report any treatment regimens (Table 1).

Intervention characteristics

The duration of interventions ranged from 21 days to 6 months. All included studies involved some form of dietary intervention, including dietary manipulation and/or supplements. One RCT supplemented participants with a synbiotic [35], one single-group study instructed participants to follow a strict vegetarian diet [36], one RCT [32] instructed participants to follow a strict Ma-Pi diet [37] and a further RCT asked participants to follow a diet recommended for type 2 diabetes mellitus incorporating an increased intake of sardines [29]. The last two of these studies included information on nutrient intake, although Balfegó et al [29] did not provide any information on what constituted the type 2 diabetic diet. Two RCTs provided participants with probiotics [31, 33], but only one recorded nutrient intake and provided guidelines on dietary intake based on type 2 diabetes mellitus guidelines [33]. One RCT provided a prebiotic, detailed in Vulevic et al [38], with no dietary advice, but recorded nutrient intake [34]; and one RCT provided participants with a digestive supplement and recorded nutrient intake at baseline [30].

All eight studies reported on glucose control, including HbA_1c, fasting blood glucose, 2 h^fs OGTT, HOMA-IR or insulin, or a combination of these, and the gut microbiota (using various techniques; ESM Table 1).

Methodological quality assessment

Four studies provided enough information to confirm the use of adequate sequence generation [29, 30, 33, 34], two studies provided sufficient detail on the methods used to conceal allocation sequences [30, 33] and three studies provided explicit detail on blinding of the research team [30, 31, 33]. Seven studies provided detail on outcome assessors [29, 30, 31, 32, 33, 34, 36] and five studies provided sufficient detail to establish the likely absence of selective outcome reporting [29, 32, 33, 34, 35]. Overall, seven of the studies were considered to be low risk of bias [29, 30, 31, 32, 33, 34, 36] and the risk of bias of one [35] was unclear (Table 2).

Effects of lifestyle modulation on gut microbiota

Additional data on the gut microbiota were requested from all authors of the included studies. Two studies comparing supplementation with a prebiotic vs control for 12 weeks [34] and the Ma-Pi diet vs a control diet for 21 days [32] provided sufficient data for meta-analyses to be conducted. Changes in the relative abundance of bacteria in the genera Bifidobacterium (SMD 1.29% [95% CI −4.45, 7.03], I² = 33%), Roseburia (SMD −0.85% [95% CI −2.91, 1.21], I² = 79%) and Lactobacillus (SMD 0.04% [95% CI −0.01, 0.09], I² = 0%) (ESM Fig. 1) were reported, however, these changes were not significantly different when comparing dietary interventions with controls.

Candela et al [32] compared a fibre-rich macrobiotic diet with a control diet. The authors reported a significant change in weighted UniFrac following receipt of the intervention. Levels of Faecalibacterium were significantly negatively correlated with fasting blood glucose; Akkermansia and Bacteroides both showed a positive significant relationship with LDL-cholesterol; and Ruminococcus was significantly positively correlated with fasting blood glucose. Significant increases in the relative abundance of Peptostreptococcaceae and Leuconostocaceae were also reported, and both of these genera were positively correlated with dietary components (fermented products).

Balfegó et al [29] compared a type 2 diabetes diet, one enriched with 100 g of sardines and one without. The authors reported a decrease in Firmicutes and an increase in Escherichia coli in both groups between baseline and study completion. In the sardine enriched group there was also a decrease in the Firmicutes:Bacteroidetes ratio and an increase in Bacteroides-Prevotella when compared with baseline. Kim et al [36] reported a significant increase in the relative abundance of Bacteroidetes and a correlation between weighted and unweighted UniFrac and a strict vegetarian diet. However, these analyses involved the whole sample of participants, including those without a confirmed diagnosis of type 2 diabetes. Two RCTs [31, 33] supplemented participants with probiotics and reported significant changes in bacterial composition: Andreasen et al [31] reported a significant increase in the presence of Lactobacillus acidophilus from near non-detectable levels to 6.4 colony-forming units; and similarly, Firouzi et al [33] reported significant increases of 4.5- and twofold in Bifidobacterium and Lactobacillus spp., respectively.

Pedersen et al [34] conducted an RCT in which participants were supplemented with a prebiotic compared with placebo. No between-group differences were shown; however, an increase in α diversity was reported within the prebiotic group. Furthermore, correlations between bowel permeability, metabolic profile, inflammatory markers and bacteria were reported (ESM Table 2). Sheth et al [35] supplemented participants with a synbiotic (two species of Lactobacillus and Bifidobacterium each, one species of Streptococcus and yeast, and 300 mg oligosaccharide), although the dietary intake provided alongside the supplements was unclear. Increases in both Lactobacillus and Bifidobacterium were reported following the intervention. Sasaki et al [30] reported significant changes in the Firmicutes:Bacteroidetes ratio between baseline and 12 weeks following supplementation with 300 and 900 mg/day of transglucosidase.

Effects of dietary intervention modulation on glucose control

Four studies comparing dietary interventions including prebiotics, probiotics and Ma-Pi diet vs controlled diets for a duration of between 21 to 84 days reported or provided sufficient data to enable meta-analyses of fasting blood glucose, HbA_1c, fasting insulin and HOMA-IR (ESM Fig. 2) [30, 32, 33, 34]. Reductions were shown in all glucose control variables. HbA_1c was significantly reduced (standardised mean difference [SMD] −2.31 mmol/mol [95% CI −2.76, −1.85] [0.21%; 95% CI −0.26, −0.16]; I² = 0%, p < 0.01), however, fasting blood glucose (SMD −0.25 mmol/l [95% CI −0.85, 0.35], I² = 87%, p > 0.05), fasting insulin (SMD −1.82 pmol/l [95% CI −7.23, 3.60], I² = 54%, p > 0.05) and HOMA-IR (SMD −0.15 [95% CI −0.63, 0.32], I² = 69%, p > 0.05) were not significantly reduced when comparing dietary interventions with comparator groups.

All eight studies reported on glucose control; however, only four provided sufficient data to calculate overall effect sizes [30, 32, 33, 34] (ESM Fig. 2). Kim et al [36] and Sasaki et al [30] reported positive changes in fasting blood glucose, 2 h^fs OGTT, fasting insulin and HbA_1c, although these were not statistically significant. Andreasen et al [31] reported baseline fasting blood glucose, HbA_1c, 2 h^fs OGTT and HOMA-IR, but did not report data for these variables at the 4 week follow-up point. A significant between-group improvement in insulin sensitivity was reported, but post-hoc t tests revealed no significant within-group changes. Unfortunately, analyses were not reported for participants with type 2 diabetes mellitus only, making it difficult to extrapolate the effects of the intervention.

Two RCTs showed significant improvements in glucose control [29, 32]. Candela et al [32] reported reductions in fasting blood glucose (−2.3 vs −1.9 mmol/l), postprandial blood glucose (−4.0 vs −4.3 mmol/l), HbA_1c (−5.5 vs −2.2 mmol/mol [−0.5% vs −0.2%] and HOMA-IR (−1.9 vs −1.5). Balfegó et al [29] reported significant reductions in fasting insulin (−35% vs −23%) and HOMA-IR (−49% vs −22%) for treatment and comparator groups, respectively. Three RCTs supplemented participants with a prebiotic, probiotic or synbiotic. Firouzi et al [33] reported significant reductions in insulin at 6 and 12 weeks (−16 and −20 pmol/l, respectively) and HbA_1c at 12 weeks (−1.1 mmol/mol [−0.1%]) between the probiotic and control group. Sheth et al [35] reported reductions in fasting blood glucose, postprandial blood glucose and HbA_1c; however, it is unclear from the reported findings whether differences between groups were assessed, as data were not provided. Pedersen et al [34] reported no statistical improvements in glucose control following supplementation with prebiotics.

Effects of dietary intervention modulation on inflammation

Four studies reported no significant differences in the inflammatory markers TNF-α, IL-6, IL-1RA or CRP between groups [29, 31, 33, 34]. Kim et al [36] reported significant reductions in faecal lipocalin 2; however, these analyses included participants without type 2 diabetes mellitus, making it difficult to extrapolate results for the subgroup of participants with type 2 diabetes. One RCT reported significant reductions in TNF-α, IL-6 and CRP following 21 days consuming the Ma-Pi 2 diet [32].

Effects of dietary intervention on short-chain fatty acids

Kim et al [36] reported a significant increase in butyrate and a reduction in total short-chain fatty acids (SCFAs), acetate, propionate and butyrate concentrations. However, these analyses were conducted on all individuals recruited, including those without a confirmed diagnosis of type 2 diabetes. Sheth et al [35] also reported increased concentrations in butyrate and propionate, although it is unclear what statistical analyses were conducted.

Effects of dietary intervention on anthropometrics

Seven studies reported BMI at baseline [29, 30, 31, 32, 33, 34, 36] and six of these studies reported BMI postintervention [29, 30, 32, 33, 34, 36]. Five studies reported no significant changes in anthropometrics, including weight, BMI and hip and waist circumferences [29, 30, 32, 33, 34]. Kim et al [36] provided BMI data upon request showing a postintervention reduction; however, it is unclear from the published article or the additional information provided whether this was statistically significant.

Changes in nutrition

Four studies recorded nutritional intake at baseline and the postintervention follow-up, including energy intake and the consumption of fat, protein, carbohydrates and fibre. Although Candela et al [32] reported dietary intake, no statistical analyses were reported. Firouzi et al [33] reported a statistically significant 9% reduction in fat intake and Balfegó et al [29] reported an 11% reduction in energy intake. Pedersen et al [34] reported a statistically significant 1.1% increase in protein intake in the control group compared with the prebiotic group.

Conclusion/future directions

Lifestyle intervention holds potential for improving the gut microbiota and glucose control. To truly use the potential of the gut microbiota and its implications for disease pathophysiology and health, future studies should consider using an appropriate intervention duration and sample size, and conducting long-term follow-up to assess whether changes in the gut microbiota and glucose control are maintained. Lifestyle behaviour change through a combination of diet and/or physical activity/exercise has been shown to have a significant beneficial impact upon glucose control [55]. However, the role that the gut microbiota plays in this process remains unclear. Another unanswered question is why some individuals respond to interventions more profoundly than others. To date, studies have focused predominantly on preclinical models, limiting their transferability into humans for use as therapeutic interventions. This review highlights the need for further well-conducted human intervention studies. As the pathology of type 2 diabetes mellitus advances and our understanding of the gut microbiota increases, there is significant potential to determine the importance of specific bacteria and their function in a given bacterial community. This will, in turn, lay the foundation for translating preclinical data into clinical practice by integrating multiple techniques and the characteristics of individuals into a systems biology approach to provide personalised lifestyle interventions.

Contribution statement

DH, TH, CS, LE, CPD, LA and MIT conceived the review protocol. LA and MIT supervised the review. DH, TH, CS, LE and LA developed the search strategy. DH and LE performed the electronic searches. DH, TH and CS screened titles and abstracts, and evaluated the eligibility of full-text articles. DH and LA assessed the included studies for methodological quality and the overall risk of bias. All authors provided input to the development of the methods and interpretation of the results. DH and LA drafted the manuscript and all authors commented upon the manuscript for important intellectual content. All authors approved and gave their permission for the final version to be published. DH and LA are responsible for the integrity of the work as a whole.