Diabetes mellitus (DM) is an epidemic and accounts for 80% of premature deaths globally (1, 2). As of 2021, there are approximately 537 million DM patients in the world, with an extended increment to 700 million by 2045 (3). DM is hardly a disease with mere elevation in blood glucose, it brings along a plethora of microvascular complications including diabetic retinopathy (DR), diabetic kidney disease (DKD) and diabetic peripheral neuropathy (DPN) in most cases. These microvascular complications are responsible for the high mortality and morbidity rate in DM patients and account for marked social and economic burdens (4). Although numerous treatments for DM and resulting complications were available, cases are still on the rise. DR is the leading cause of blindness ophthalmic disorder in the population on working age, with a prevalence of 77.8% in 15 years of DM patients (5–7). DKD occurs in approximately 40% of DM, and 30%-90% of DM might suffer from DPN (8). These trends highlight the urgency for a better understanding of diabetic microvascular complications (DC) (9).

The rapid scientific interest in gut microbiota coincided with the global increase in DM (9). The advent of next-generation sequencing technology has greatly enhanced our understanding of gut microbiota and host health (10, 11). The gut microbiota was a complex microbial community, represented by 1500 different species (12, 13). DM and its complications have been linked with dysbiosis of the gut microbiota (14). Differences in gut microbiota composition have been observed in animal models as well as patients with DM and complications such as DKD, DR and DPN. In particular, perturbed Bacteroidetes/Firmicutes eubiosis was proven to be associated with increased intestinal permeability, with bacteria byproducts infiltrated through a leaky gut barrier, triggering inflammatory responses of diabetes. Species Lactobacillus fermentum, Akkermansia muciniphila, Bacteroides fragilis and Roseburia intestinalis were demonstrated to be linked to insulin sensitivity and glucose metabolism. Phyla Bacteroidetes, Actinobacteria and Mucoromycota were depleted, while genera Acidaminococcus, Escherichia and Enterobacter were enriched in patients with DR compared to HC (15). In DPN, the richness of Firmicutes and Actinobacteria was elevated, while Bacteroidetes was depleted. At the genus level, Bacteroides and Faecalibacterium were significantly decreased, whereas Lachnoclostridium and Ruminococcus were enriched (16). In DKD, there was a marked increase in genera Acidaminococcus, Selenomonadales, Bilophila and Shigella, as well as phylum Proteobacteria, and the richness of species Syntrophaceticus schinkii and Citrobacter farmeri was positively correlated with the urinary albumin creatinine ratio (17). Notably, Akkermansia in the gut may contribute to the effect of metformin, the most commonly prescribed drug for DM, on glucose metabolism (18, 19).

Although a plethora of studies had characterized the gut microbiota of DC with promising findings, the relationship between them was still controversial. A meta-analysis on more than 2000 studies on microbiota suggested the alternation of microbiota to differentiate healthy and diseased populations and serve as bio-markers for the diagnosis or treatment of DM (20). Therefore, we performed a meta-analysis of gut microbiota from patients with DC and explored the diversity and bacterial characteristics of the gut microbiota in DC.

The scheme of the review was registered in PROSPERO with registration number CRD42022353144. We followed the Preferred Reporting Items for the Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines (21).

To our knowledge, this meta-analysis was the first to assess alpha diversity and microbiota perturbations in DC compared with DM and HC. This study yielded three major insights into the gut microbial changes in DC. Firstly, patients with DC exhibited a significantly higher richness but lower diversity in gut microbiota when compared to DM. And when compared to HC, DC held a lower richness in gut microbiota. Secondly, the abundance of phylum Proteobacteria was enriched and Firmicutes was depleted in DC when compared to HC. Last, the abundances of genera Bifidobacterium and Faecalibacterium were depleted in DC when compared to DM. And when compared to HC, DC exhibited lower abundances of Faecalibacterium and Lactobacillus but a higher abundance of Klebsiella. All these changes may be associated with the pathology of DC, and serve as promising targets for the management of DC.

One common indicator of dysbiosis is a modified overall microbial alpha diversity, which denotes the relative abundance of microbial species in space and time within a specific community. Alpha diversity indices include OTUs, ACE, Chao1, Simpson and Shannon. ACE and Chao1 focus on species richness. Simpson and Shannon strengthen diversity. Generally, lower alpha diversity was observed in obesity and diabetes, and was considered detrimental to the host (34). Alpha diversity in richness and diversity declined in DR and DKD when compared to HC (28, 29). In contrast, no difference was found in gut microbiota between DM patients with or without cognitive impairment (35). DPN resulted in a more severe disruption of microbiota community richness than DM (16). These findings indicated that the profile of gut microbiota was altered in patients with DC, but further exploration was needed due to the extremely inconsistent findings.

Phylum Proteobacteria was gram-negative bacteria and proved to be significantly different in gut microbiota between DM patients with or without gastrointestinal autonomic neuropathy (36). Proteobacteria was proven to be negatively related to human health and found with a higher abundance in the obese population than the non-obese population (34, 37). The mechanism might be related to the regulation of bile acids, a metabolic controller (38). In line with these results, Proteobacteria was found significantly enriched in DC when compared to HC in this study, concluding that with the risk of DC increased, the abundance of Proteobacteria increased. These findings may further reveal that the alternation of gut microbiota at the phylum level is closely related to DC.

The phyla Firmicutes and Bacteroidetes accounted for more than 90% of the total community of human gut microbiota. Alterations affecting Firmicutes and Bacteroidetes were first described in obese subjects who exhibited increased abundances of Firmicutes at the expense of Bacteroidetes (39). Firmicutes was positively linked with inflammation and the modulation of metabolism, and was supposed to be more efficient at calorie absorption and weight gain (40–42). Bacteroidota was significantly reduced in DR patients, and Firmicutes to Bacteroidetes ratio was proven elevated in gestational diabetes patients (15). However, in opposition to these results, no change or even decreased Firmicutes to Bacteroidetes ratio in obese subjects was reported (43–45). In our study, Firmicutes were significantly depleted in DC compared to HC. The reason might be linked to less bacterial diversity in obese patients than the non-obese subjects (46). Therefore, further research involving this parameter should be high on the list.

In line with the results presented in this study concerning the significant decrease of genera Bifidobacterium, Lactobacillus and Faecalibacterium in DC (p < 0.05), similar results were observed in DR in Zhou’s study (31). Bifidobacteria and Lactobacillus were gram-positive microorganisms, which participated in the restoration of the intestinal mucosal barrier (47, 48). Both of them were inversely associated with inflammation, hyperglycemia, and insulin resistance (49–51). Bifidobacteria was demonstrated to produce bacteriocin that blocks adherence to the mucosa and preserves gut barrier function (52). DM patients presented a significantly lower richness of Bifidobacterium compared to healthy subjects (53, 54). Probiotics, as well as yogurt or milk containing Bifidobacterium and Lactobacillus, decreased fasting blood glucose and glycosylated hemoglobin type A1c (HbA1c) in DM patients (55, 56). Drawing a conclusion that Bifidobacteria and Lactobacillus decreased as the risk of DC increased. The mechanism might be linked to the depletion of potential intestinal pathogens, enhancement of intestinal antioxidant ability and digestive enzyme activity (57). Faecalibacterium was gram-negative, butyrate-producing bacteria, which was demonstrated to be negatively related to HbA1c (26). Faecalibacterium was proven to increase the intestinal synthesis of glucagon-like peptide-1, peptide YY, acetate and butyrate help to maintain glucose homeostasis (58). In this study, Faecalibacterium was depleted in DC, corroborating previous reports that linked Faecalibacterium to positive metabolic outcomes (29, 33, 59–61). These findings revealed that the alternation of gut microbiota at the genus level was closely related to DC, and the increase of Bifidobacterium, Lactobacillus and Faecalibacterium might be responsible for the pathology of DC. Klebsiella is a natural inhabitant of the gastrointestinal tract microbiome of healthy humans and animals, but it often causes extraintestinal infections, including urinary tract infections, pneumoniae and septicemia (62). Recently, Klebsiella was demonstrated to be increased in DKD (63), which was proven to be increased in DC when compared to HC in this study.

Microbiota symbiosis helped regulate metabolism and reduce the risk of DM. Gut microbiota dysbiosis was proven to lead imbalance of intestinal microbial bi-products, and cause insulin resistance, with mechanism unclear. Recently, the mechanism of how microbiota affect DM and its complications has raised academic interests. Firstly, microbiota dysbiosis led to the production of short-chain fatty acids (SCFAs) including butyrate, propionate, and acetate, which then impaired the intestinal barrier integrity, activated the inflammation signaling cascades and thus promoted the multi-organs damage (64). Secondly, microbiota-derived trimethylamine nitrogen oxide (TMAO) increased the accumulation of cholesterol, led to insulin resistance (65), and increased the risk of DM (66, 67). Third, changes in gut microbiota composition were proven to affect gut permeability and inflammation in DM (68, 69). Microbiota-derived lipopolysaccharide (LPS) triggered downstream inflammatory pathways and pro-inflammatory cytokine expression cascades, leading to inflammatory reactions and aggravating insulin resistance (70, 71). Last but not the least, microbiota-derived aromatic amino acids including indoxyl sulfate and p-cresyl sulfate, also known as uremic toxins, might induce mitochondrial dysfunction, podocytes injuries, thicken the glomerular basement membrane, and ultimately lead to renal micro-inflammation, and perivascular fibrosis in DKD (72, 73).

In this meta-analysis, genus Bifidobacterium belonged to the phylum Actinobacteria, genera Faecalibacterium and Lactobacillus belonged to the phylum Firmicutes, genus Klebsiella belonged to the phylum Proteobacteria. Phyla Actinobacteria, Firmicutes and Proteobacteria were both SCFAs-producing and LPS-producing bacteria. Therefore, we hypothesized that SCFAs-induced intestinal barrier integrity impairment and LPS-induced inflammation might be important parts of mechanism of DC. Nevertheless, direct targets of gut microbiota and the potential mechanisms needed to be further elucidated.

In spite of these interesting findings, our study was not without limitations. First, the language of included literature was limited to English, which may increase the possibility of language bias or publication bias. Secondly, since the gut microbiota was closely related to race and living environment, and the included studies originated mostly from Asia (11/13), in which nine studies were conducted in China and two in India. To explore the potential source of heterogeneity caused by it, the subgroup analysis on the nation has been performed in some comparison. The generalization of these results can only represent the characteristics of Asian populations to some extent. Third, in the 13 studies included, there were seven (7/13) studies focused on DKD, five (5/13) focused on DR, and only one (1/13) focused on DPN. To explore the potential source of heterogeneity caused by different microvascular complications of DM, the subgroup analysis on the type of microvascular complications has been performed. Considering the representativeness and potential bias of DPN, a meta-analysis of studies excluding DPN was performed to compare. Although DR and DKD were more representative microvascular complications in some ways, it would be better if a larger number of studies on DPN could be included in this meta-analysis. Fourth, the heterogeneity was high, although subgroup analysis on the type of DC, nation and city was performed, it was far from enough to explain the source of heterogeneity. More studies should be included and more factors related to microbiota such as ethnicity, eating habits, living environment, obesity condition, and even drugs on the changes of gut microbiota. Last, a different method of gene sequencing was also a potential bias on the results.

In conclusion, we demonstrated that the alternation of alpha diversity, the abundances of phyla Proteobacteria and Firmicutes as well as the abundances of genera Bifidobacterium, Faecalibacterium Lactobacillus and Klebsiella may be associated with DC. The changes of microbial features may be noninvasive biomarkers for monitoring the management of DC. However, our findings still need to be verified by further large-scale, multi-center and high-quality studies. Nevertheless, conflicting results have also been reported, and therefore further studies would be necessary to fully understand the relation between gut microbiota and DC.

All data may be obtained within the article, the supplementary files, or from the original articles.

JH, DL, and CM designed the study. JH and TF performed the literature search, screened for eligible studies, and extracted data, which were then analyzed by WL and YD. JH wrote the first draft of the manuscript and all authors contributed to subsequent drafts and approved the final version for submission.

This study was funded by the Traditional Chinese Medicine Bureau of Guangdong Province (Nos. 20231003, 20211003 and 20223001), the National Natural Science Foundation of China (No. 82202560), the Natural Science Foundation of Guangdong Province (No. 2021A1515220050), the Fundamental Research Funds for the Central University (No. 22qntd4813) and the second batch of central subsidy funds for traditional Chinese medicine departments in 2022 (construction of national traditional Chinese medicine specialty) (No. 2022CZ0047).

The authors acknowledged Guangdong Provincial People’s Hospital and Sun Yat-sen University for the academic supports.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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