Gut microbiome differences among Mexican Americans with and without type 2 diabetes mellitus

Using gut microbiome metagenomic hypervariable features for diabetes screening and typing through supervised machine learning

Diabetes mellitus is a complex metabolic disorder and one of the fastest-growing global public health concerns. The gut microbiota is implicated in the pathophysiology of various diseases, including diabetes. This study utilized 16S rRNA metagenomic data from a volunteer citizen science initiative to investigate microbial markers associated with diabetes status (positive or negative) and type (type 1 or type 2 diabetes mellitus) using supervised machine learning (ML) models. The diversity of the microbiome varied according to diabetes status and type. Differential microbial signatures between diabetes types and negative group revealed an increased presence of Brucellaceae, Ruminococcaceae, Clostridiaceae, Micrococcaceae, Barnesiellaceae and Fusobacteriaceae in subjects with diabetes type 1, and Veillonellaceae, Streptococcaceae and the order Gammaproteobacteria in subjects with diabetes type 2. The decision tree, elastic net, random forest (RF) and support vector machine with radial kernel ML algorithms were trained to screen and type diabetes based on microbial profiles of 76 subjects with type 1 diabetes, 366 subjects with type 2 diabetes and 250 subjects without diabetes. Using the 1000 most variable features, tree-based models were the highest-performing algorithms. The RF screening models achieved the best performance, with an average area under the receiver operating characteristic curve (AUC) of 0.76, although all models lacked sensitivity. Reducing the dataset to 500 features produced an AUC of 0.77 with sensitivity increasing by 74% from 0.46 to 0.80. Model performance improved for the classification of negative-status and type 2 diabetes. Diabetes type models performed best with 500 features, but the metric performed poorly across all model iterations. ML has the potential to facilitate early diagnosis of diabetes based on microbial profiles of the gut microbiome.

The relationship between dietary index for gut microbiota and diabetes

This study aims to explore the relationship between the Dietary Index for Gut Microbiota (DI-GM) and diabetes. In recent years, there has been increasing attention to the role of the gut microbiome in regulating host metabolism. However, the relationship between DI-GM and the risk of diabetes has not been sufficiently studied. This study utilized relevant data from the National Health and Nutrition Examination Survey (NHANES) 2007-2018. Multiple logistic regression analysis was conducted to explore the relationship between DI-GM and the risk of diabetes. The dose-response relationship between DI-GM and the risk of diabetes was observed using restricted cubic splines (RCS). Threshold effect analysis was performed based on RCS results. Subgroup analyses were used to conduct a sensitivity analysis of the relationship between DI-GM and the risk of diabetes. The results from multiple logistic regression analysis indicated a significant negative correlation between DI-GM and the risk of diabetes (OR, 0.954, 95%CI, 0.918-0.991). RCS results also showed a significant nonlinear negative relationship between DI-GM and the risk of diabetes (P < 0.001, P for nonlinear = 0.010). The threshold effect analysis revealed that when DI-GM was below 6.191, there was a significant negative correlation between DI-GM and the risk of diabetes (OR, 0.921, 95% CI, 0.876-0.969). However, when DI-GM exceeded 6.191, the relationship between DI-GM and the risk of diabetes was no longer significant. Subgroup analysis revealed that the negative correlation between DI-GM and the risk of diabetes remained significant in Whites, participants with a poverty-income ratio > 3.5, body mass index > 24, current drinkers, never or current smokers, and those without chronic kidney disease (P < 0.05). This study demonstrates a nonlinear negative correlation between DI-GM and the risk of diabetes. Maintaining DI-GM above 6.191 may help prevent diabetes.

A systematic review on gut microbiota in type 2 diabetes mellitus

Aims/hypothesis

The gut microbiota play crucial roles in the digestion and degradation of nutrients, synthesis of biological agents, development of the immune system, and maintenance of gastrointestinal integrity. Gut dysbiosis is thought to be associated with type 2 diabetes mellitus (T2DM), one of the world's fastest growing diseases. The aim of this systematic review is to identify differences in the composition and diversity of the gut microbiota in individuals with T2DM.

Methods

A systematic search was conducted to identify studies reporting on the difference in gut microbiota composition between individuals with T2DM and healthy controls. Relevant studies were evaluated, and their characteristics and results were extracted using a standardized data extraction form. The studies were assessed for risk of bias and their findings were reported narratively.

Results

58 observational studies published between 2010 and 2024 were included. Beta diversity was commonly reported to be different between individuals with T2DM and healthy individuals. Genera Lactobacillus, Escherichia-Shigella, Enterococcus, Subdoligranulum and Fusobacteria were found to be positively associated; while Akkermansia, Bifidobacterium, Bacteroides, Roseburia, Faecalibacteirum and Prevotella were found to be negatively associated with T2DM.

Conclusions

This systematic review demonstrates a strong association between T2DM and gut dysbiosis, as evidenced by differential microbial abundances and altered diversity indices. Among these taxa, Escherichia-Shigella is consistently associated with T2DM, whereas Faecalibacterium prausnitzii appears to offer a protective effect against T2DM. However, the heterogeneity and observational nature of these studies preclude the establishment of causative relationships. Future research should incorporate age, diet and medication-matched controls, and include functional analysis of these gut microbes.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42023459937.

Understanding Patterns of the Gut Microbiome May Contribute to the Early Detection and Prevention of Type 2 Diabetes Mellitus: A Systematic Review

The rising burden of type 2 diabetes mellitus (T2DM) is a growing global public health problem, particularly prominent in developing countries. The early detection of T2DM and prediabetes is vital for reversing the outcome of disease, allowing early intervention. In the past decade, various microbiome-metabolome studies have attempted to address the question of whether there are any common microbial patterns that indicate either prediabetic or diabetic gut microbial signatures. Because current studies have a high methodological heterogeneity and risk of bias, we have selected studies that adhered to similar design and methodology. We performed a systematic review to assess if there were any common changes in microbiome belonging to diabetic, prediabetic and healthy individuals. The cross-sectional studies presented here collectively covered a population of 65,754 people, with 1800 in the 2TD group, 2770 in the prediabetic group and 61,184 in the control group. The overall microbial diversity scores were lower in the T2D and prediabetes cohorts in 86% of the analyzed studies. Re-programming of the microbiome is potentially one of the safest and long-lasting ways to eliminate diabetes in its early stages. The differences in the abundance of certain microbial species could serve as an early warning for a dysbiotic gut environment and could be easily modified before the onset of disease by changes in lifestyle, taking probiotics, introducing diet modifications or stimulating the vagal nerve. This review shows how metagenomic studies have and will continue to identify novel therapeutic targets (probiotics, prebiotics or targets for elimination from flora). This work clearly shows that gut microbiome intervention studies, if performed according to standard operating protocols using a predefined analytic framework (e.g., STORMS), could be combined with other similar studies, allowing broader conclusions from collating all global cohort studies efforts and eliminating the effect-size statistical insufficiency of a single study.

Causal association between gut microbiomes and different types of aneurysms: a Mendelian randomization study

Background

Previous studies suggests that gut microbiomes are associated with the formation and progression of aneurysms. However, the causal association between them remains unclear.

Methods

A two-sample Mendelian randomization was conducted to investigate whether gut microbiomes have a causal effect on the risk of intracerebral aneurysm (IA), thoracic aortic aneurysm (TAA) and abdominal aortic aneurysm (AAA), and aortic aneurysm (AA). Single nucleotide polymorphisms (SNPs) smaller than the locus-wide significance level (1 × 10-5) were selected as instrumental variables. We used inverse-variance weighted (IVW) test as the primary method for the evaluation of causal association. MR-Egger, weighted median, weighted mode, and MR Pleiotropy Residual Sum and Outlier (MR-PRESSO) methods were conducted for sensitive analysis. The p-value was adjusted by the false discovery rate (FDR) which adjust the results of multiple comparisons, a p < 0.05 and q < 0.1 was considered a significant causal association. Additionally, a p < 0.05 and q > 0.1 was considered a suggestive causal effect. Additionally, reverse MR was also performed to exclude the possibility of reverse causality.

Results

The phylum Firmicutes (OR = 0.62; 95% CI, 0.48-0.81), class Lentisphaeria (OR = 0.75; 95% CI, 0.62-0.89), and order Victivallales (OR = 0.75; 95% CI, 0.62-0.89) have a causal protective effect on the risk of AAA. Additionally, class Verrucomicrobia, class Deltaproteobacteria, order Verrucomicrobiale, family Verrucomicrobiacea, genus Eubacterium rectale group, genus Akkermansia, and genus Clostridium innocuum group were negatively associated with the risk of different types of aneurysms, whereas class Negativicutes, order Selenomonadales, and genus Roseburia had positive causal association with different types of aneurysms (p < 0.05; q > 0.1). Further sensitivity analysis validated the robustness of our MR results, and no reverse causality was found with these gut microbiomes (p > 0.05).

Conclusion

Our MR analysis confirmed the causal association of specific gut microbiomes with AAA, and these microbiomes were considered as protective factors. Our result may provide novel insights and theoretical basis for the prevention of aneurysms through regulation of gut microbiomes.

Causal relationship between gut microbiota and type 2 diabetes: a two-sample Mendelian randomization study

Background

Studies showed that development of gut microbial dysbiosis has a close association with type 2 diabetes (T2D). It is not yet clear if there is a causal relationship between gut microbiota and T2D.

Methods

The data collected from the published genome-wide association studies (GWASs) on gut microbiota and T2D were analyzed. Two-sample Mendelian randomization (MR) analyses were performed to identify causal relationship between bacterial taxa and T2D. Significant bacterial taxa were further analyzed. To confirm the findings' robustness, we performed sensitivity, heterogeneity, and pleiotropy analyses. A reverse MR analysis was also performed to check for potential reverse causation.

Results

By combining the findings of all the MR steps, we identified six causal bacterial taxa, namely, Lachnoclostridium, Oscillospira, Roseburia, Ruminococcaceae UCG003, Ruminococcaceae UCG010 and Streptococcus. The risk of T2D might be positively associated with a high relative abundance of Lachnoclostridium, Roseburia and Streptococcus but negatively associated with Oscillospira, Ruminococcaceae UCG003 and Ruminococcaceae UCG010. The results of MR analyses revealed that there were causal relationships between the six different genera and T2D. And the reverse MR analysis did not reveal any evidence of a reverse causality.

Conclusion

This study implied that Lachnoclostridium, Roseburia and Streptococcus might have anti-protective effect on T2D, whereas Oscillospira, Ruminococcaceae UCG003 and Ruminococcaceae UCG010 genera might have protective effect on T2D. Our study revealed that there was a causal relationship between specific gut microbiota genera and T2D.

Short-Chain Fatty Acids in the Microbiota-Gut-Brain Axis: Role in Neurodegenerative Disorders and Viral Infections

The gut-brain axis (GBA) is the umbrella term to include all bidirectional communication between the brain and gastrointestinal (GI) tract in the mammalian body. Evidence from over two centuries describes a significant role of GI microbiome in health and disease states of the host organism. Short-chain fatty acids (SCFAs), mainly acetate, butyrate, and propionate that are the physiological forms of acetic acid, butyric acid, and propionic acid respectively, are GI bacteria derived metabolites. SCFAs have been reported to influence cellular function in multiple neurodegenerative diseases (NDDs). In addition, the inflammation modulating properties of SCFAs make them suitable therapeutic candidates in neuroinflammatory conditions. This review provides a historical background of the GBA and current knowledge of the GI microbiome and role of individual SCFAs in central nervous system (CNS) disorders. Recently, a few reports have also identified the effects of GI metabolites in the case of viral infections. Among these viruses, the flaviviridae family is associated with neuroinflammation and deterioration of CNS functions. In this context, we additionally introduce SCFA based mechanisms in different viral pathogenesis to understand the former's potential as agents against flaviviral disease.

Association between gut microbiota and prediabetes in people living with HIV

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Gut microbiota are known to be associated with various metabolic syndromes.

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Diversity of gut microbiota decreases in PLWH with prediabetes.

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Streptococcus and Anaerostignum are more abundant in the prediabetes group.

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Further study of alteration in gut microbiota on glucose metabolism is warranted.

The prevalence of prediabetes is rapidly increasing in general population and in people living with HIV (PLWH). Gut microbiota play an important role in human health, and dysbiosis is associated with metabolic disorders and HIV infection. Here, we aimed to evaluate the association between gut microbiota and prediabetes in PLWH. A cross-sectional study enrolled 40 PLWH who were receiving antiretroviral therapy and had an undetectable plasma viral load. Twenty participants had prediabetes, and 20 were normoglycemic. Fecal samples were collected from all participants. The gut microbiome profiles were analyzed using 16S rRNA sequencing. Alpha-diversity was significantly lower in PLWH with prediabetes than in those with normoglycemia (p<0.05). A significant difference in beta-diversity was observed between PLWH with prediabetes and PLWH with normoglycemia (p<0.05). Relative abundances of two genera in Firmicutes (Streptococcus and Anaerostignum) were significantly higher in the prediabetes group. In contrast, relative abundances of 13 genera (e.g., Akkermansia spp., Christensenellaceae R7 group) were significantly higher in the normoglycemic group. In conclusion, the diversity of gut microbiota composition decreased in PLWH with prediabetes. The abundances of 15 bacterial taxa in the genus level differed between PLWH with prediabetes and those with normoglycemia. Further studies on the effect of these taxa on glucose metabolism are warranted.