Exploring the Triple Interaction between the Host Genome, the Epigenome, and the Gut Microbiome in Type 1 Diabetes

High-risk genotypes for type 1 diabetes are associated with the imbalance of gut microbiome and serum metabolites

Background

The profile of gut microbiota, serum metabolites, and lipids of type 1 diabetes (T1D) patients with different human leukocyte antigen (HLA) genotypes remains unknown. We aimed to explore gut microbiota, serum metabolites, and lipids signatures in individuals with T1D typed by HLA genotypes.

Methods

We did a cross-sectional study that included 73 T1D adult patients. Patients were categorized into two groups according to the HLA haplotypes they carried: those with any two of three susceptibility haplotypes (DR3, DR4, DR9) and without any of the protective haplotypes (DR8, DR11, DR12, DR15, DR16) were defined as high-risk HLA genotypes group (HR, n=30); those with just one or without susceptibility haplotypes as the non-high-risk HLA genotypes group (NHR, n=43). We characterized the gut microbiome profile with 16S rRNA gene amplicon sequencing and analyzed serum metabolites with liquid chromatography-mass spectrometry.

Results

Study individuals were 32.5 (8.18) years old, and 60.3% were female. Compared to NHR, the gut microbiota of HR patients were characterized by elevated abundances of Prevotella copri and lowered abundances of Parabacteroides distasonis. Differential serum metabolites (hypoxanthine, inosine, and guanine) which increased in HR were involved in purine metabolism. Different lipids, phosphatidylcholines and phosphatidylethanolamines, decreased in HR group. Notably, Parabacteroides distasonis was negatively associated (p ≤ 0.01) with hypoxanthine involved in purine metabolic pathways.

Conclusions

The present findings enabled a better understanding of the changes in gut microbiome and serum metabolome in T1D patients with HLA risk genotypes. Alterations of the gut microbiota and serum metabolites may provide some information for distinguishing T1D patients with different HLA risk genotypes.

Gut Microbiota Functional Traits, Blood pH, and Anti-GAD Antibodies Concur in the Clinical Characterization of T1D at Onset

Alterations of gut microbiota have been identified before clinical manifestation of type 1 diabetes (T1D). To identify the associations amongst gut microbiome profile, metabolism and disease markers, the 16S rRNA-based microbiota profiling and ¹H-NMR metabolomic analysis were performed on stool samples of 52 T1D patients at onset, 17 T1D siblings and 57 healthy subjects (CTRL). Univariate, multivariate analyses and classification models were applied to clinical and -omic integrated datasets. In T1D patients and their siblings, Clostridiales and Dorea were increased and Dialister and Akkermansia were decreased compared to CTRL, while in T1D, Lachnospiraceae were higher and Collinsella was lower, compared to siblings and CTRL. Higher levels of isobutyrate, malonate, Clostridium, Enterobacteriaceae, Clostridiales, Bacteroidales, were associated to T1D compared to CTRL. Patients with higher anti-GAD levels showed low abundances of Roseburia, Faecalibacterium and Alistipes and those with normal blood pH and low serum HbA_1c levels showed high levels of purine and pyrimidine intermediates. We detected specific gut microbiota profiles linked to both T1D at the onset and to diabetes familiarity. The presence of specific microbial and metabolic profiles in gut linked to anti-GAD levels and to blood acidosis can be considered as predictive biomarker associated progression and severity of T1D.

Inflammatory Bowel Disease Treatments and Predictive Biomarkers of Therapeutic Response

Inflammatory bowel disease (IBD) is a chronic immune-mediated inflammation of the gastrointestinal tract with a highly heterogeneous presentation. It has a relapsing and remitting clinical course that necessitates lifelong monitoring and treatment. Although the availability of a variety of effective therapeutic options including immunomodulators and biologics (such as TNF, CAM inhibitors) has led to a paradigm shift in the treatment outcomes and clinical management of IBD patients, some patients still either fail to respond or lose their responsiveness to therapy over time. Therefore, according to the recent Selecting Therapeutic Targets in Inflammatory Bowel Disease (STRIDE-II) recommendations, continuous disease monitoring from symptomatic relief to endoscopic healing along with short- and long-term therapeutic responses are critical for providing IBD patients with a tailored therapy algorithm. Moreover, considering the high unmet need for novel therapeutic approaches for IBD patients, various new modulators of cytokine signaling events (for example, JAK/TYK inhibitors), inhibitors of cytokines (for example IL-12/IL-23, IL-22, IL-36, and IL-6 inhibitors), anti-adhesion and migration strategies (for example, β7 integrin, sphingosine 1-phosphate receptors, and stem cells), as well as microbial-based therapeutics to decolonize the bed buds (for example, fecal microbiota transplantation and bacterial inhibitors) are currently being evaluated in different phases of controlled clinical trials. This review aims to offer a comprehensive overview of available treatment options and emerging therapeutic approaches for IBD patients. Furthermore, predictive biomarkers for monitoring the therapeutic response to different IBD therapies are also discussed.

MIAOME: Human Microbiome Affect The Host Epigenome

Besides the genetic factors having tremendous influences on the regulations of the epigenome, the microenvironmental factors have recently gained extensive attention for their roles in affecting the host epigenome. There are three major types of microenvironmental factors: microbiota-derived metabolites (MDM), microbiota-derived components (MDC) and microbiota-secreted proteins (MSP). These factors can regulate host physiology by modifying host gene expression through the three highly interconnected epigenetic mechanisms (e.g. histone modifications, DNA modifications, and non-coding RNAs). However, no database was available to provide the comprehensive factors of these types. Herein, a database entitled 'Human Microbiome Affect The Host Epigenome (MIAOME)' was constructed. Based on the types of epigenetic modifications confirmed in the literature review, the MIAOME database captures 1068 (63 genus, 281 species, 707 strains, etc.) human microbes, 91 unique microbiota-derived metabolites & components (16 fatty acids, 10 bile acids, 10 phenolic compounds, 10 vitamins, 9 tryptophan metabolites, etc.) derived from 967 microbes; 50 microbes that secreted 40 proteins; 98 microbes that directly influence the host epigenetic modification, and provides 3 classifications of the epigenome, including (1) 4 types of DNA modifications, (2) 20 histone modifications and (3) 490 ncRNAs regulations, involved in 160 human diseases. All in all, MIAOME has compiled the information on the microenvironmental factors influence host epigenome through the scientific literature and biochemical databases, and allows the collective considerations among the different types of factors. It can be freely assessed without login requirement by all users at: http://miaome.idrblab.net/ttd/

Healthy and pro-inflammatory gut ecology plays a crucial role in the digestion and tolerance of a novel Gluten Friendly™ bread in celiac subjects: a randomized, double blind, placebo control in vivo study

Gluten Friendly™ (GF) is a new gluten achieved through a physicochemical process applied to wheat kernels. The goal of this research was to assess the in vivo effects of Gluten Friendly™ bread on celiac gut mucosa and microbiota. In a double-blind placebo-controlled intervention study, 48 celiac disease (CD) patients were randomized into 3 groups to eat 100 g of bread daily, containing different doses (0; 3 g; 6 g) of GF for 12 weeks. The small-bowel morphology (VH/CrD), intraepithelial densities of CD3+, celiac serology, MUC2, CB1, gut permeability, proinflammatory cytokines, gluten in stools, symptoms, and gut microbial composition were assessed. All 48 CD subjects experienced no symptoms. K-means analysis evidenced celiac subjects clustering around unknown parameters independent of GF dosage: K1 35%; K2 30%; K3 35%. VH/CrD significantly decreased in K1 and K2. VH/CrD did not correlate with IEL increase in K2. 33-mer was not detected in 47% and 73% of patients in both K1 and K2, respectively. VH/CrD and IEL did not change significantly and strongly correlated with the absence of 33-mer in K3. Inflammation and VH/CrD decrease are strongly related with the presence of proinflammatory species at the baseline. A boost in probiotic, butyrate-producing genera, is strongly related with GF tolerance at the end of the trial. Our research suggests that a healthy and proinflammatory ecology could play a crucial role in the digestion and tolerance of the new gluten molecule in celiac subjects. However, GF can be completely digested by gut microbiota of CD subjects and shapes it toward gut homeostasis by boosting healthy butyrate-producing populations. The clinical trial registry number is NCT03137862 (https://clinicaltrials.gov).

Gut Microbiota-Modulated Metabolomic Profiling Shapes the Etiology and Pathogenesis of Autoimmune Diseases

Autoimmunity is a complex and multifaceted process that contributes to widespread functional decline that affects multiple organs and tissues. The pandemic of autoimmune diseases, which are a global health concern, augments in both the prevalence and incidence of autoimmune diseases, including type 1 diabetes, multiple sclerosis, and rheumatoid arthritis. The development of autoimmune diseases is phenotypically associated with gut microbiota-modulated features at the molecular and cellular levels. The etiology and pathogenesis of autoimmune diseases comprise the alterations of immune systems with the innate and adaptive immune cell infiltration into specific organs and the augmented production of proinflammatory cytokines stimulated by commensal microbiota. However, the relative importance and mechanistic interrelationships between the gut microbial community and the immune system during progression of autoimmune diseases are still not well understood. In this review, we describe studies on the profiling of gut microbial signatures for the modulation of immunological homeostasis in multiple inflammatory diseases, elucidate their critical roles in the etiology and pathogenesis of autoimmune diseases, and discuss the implications of these findings for these disorders. Targeting intestinal microbiome and its metabolomic associations with the phenotype of autoimmunity will enable the progress of developing new therapeutic strategies to counteract microorganism-related immune dysfunction in these autoimmune diseases.

The link among microbiota, epigenetics, and disease development

The microbiome is a community of various microorganisms that inhabit or live on the skin of humans/animals, sharing the body space with their hosts. It is a sort of complex ecosystem of trillions of commensals, symbiotic, and pathogenic microorganisms, including trillions of bacteria, archaea, protozoa, fungi, and viruses. The microbiota plays a role in the health and disease status of the host. Their number, species dominance, and viability are dynamic. Their long-term disturbance is usually accompanied by serious diseases such as metabolic disorders, cardiovascular diseases, or even cancer. While epigenetics is a term that refers to different stimuli that induce modifications in gene expression patterns without structural changes in the inherited DNA sequence, these changes can be reversible or even persist for several generations. Epigenetics can be described as cell memory that stores experience against internal and external factors. Results from multiple institutions have contributed to the role and close interaction of both microbiota and epigenetics in disease induction. Understanding the mechanisms of both players enables a better understanding of disease induction and development and also opens the horizon to revolutionary therapeutic approaches. The present review illustrates the roles of diet, microbiome, and epigenetics in the induction of several chronic diseases. In addition, it discusses the application of epigenetic data to develop diagnostic biomarkers and therapeutics and evaluate their safety for patients. Understanding the interaction among all these elements enables the development of innovative preventive/therapeutic approaches for disease control.

Relationship between Nutrient Intake and Human Gut Microbiota in Monozygotic Twins

Background and Objectives: The gut microbiota is associated with human health and dietary nutrition. Various studies have been reported in this regard, but it is difficult to clearly analyze human gut microbiota as individual differences are significant. The causes of these individual differences in intestinal microflora are genetic and/or environmental. In this study, we focused on differences between identical twins in Japan to clarify the effects of nutrients consumed on the entire gut microbiome, while excluding genetic differences. Materials and Methods: We selected healthy Japanese monozygotic twins for the study and confirmed their zygosity by matching 15 short tandem repeat loci. Their fecal samples were subjected to 16S rRNA sequencing and bioinformatics analyses to identify and compare the fluctuations in intestinal bacteria. Results: We identified 12 genera sensitive to environmental factors, and found that Lactobacillus was relatively unaffected by environmental factors. Moreover, we identified protein, fat, and some nutrient intake that can affect 12 genera, which have been identified to be more sensitive to environmental factors. Among the 12 genera, Bacteroides had a positive correlation with retinol equivalent intake (rs = 0.38), Lachnospira had a significantly negative correlation with protein, sodium, iron, vitamin D, vitamin B6, and vitamin B12 intake (rs = −0.38, −0.41, −0.39, −0.63, −0.42, −0.49, respectively), Lachnospiraceae ND3007 group had a positive correlation with fat intake (rs = 0.39), and Lachnospiraceae UCG-008 group had a negative correlation with the saturated fatty acid intake (rs = −0.45). Conclusions: Our study is the first to focus on the relationship between human gut microbiota and nutrient intake using samples from Japanese twins to exclude the effects of genetic factors. These findings will broaden our understanding of the more intuitive relationship between nutrient intake and the gut microbiota and can be a useful basis for finding useful biomarkers that contribute to human health.