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    Topic review

    Complex interactions in T1D

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    Type 1 diabetes (T1D) is an auto-immune disorder characterized by a complex interaction between the host immune system and various environmental factors in genetically susceptible individuals. Genome-wide association studies (GWAS) identified different T1D risk and protection alleles, however, little is known about the environmental factors that can be linked to these alleles. Recent evidence indicated that, among those environmental factors, dysbiosis (imbalance) in the gut microbiota may play a role in the pathogenesis of T1D, affecting the integrity of the gut and leading to systemic inflammation and auto-destruction of the pancreatic β cells.

    1. Introduction

    Type 1 diabetes (T1D) is an auto-immune disorder caused by a complex interaction between the host immune system and different environmental factors in genetically predisposed individuals [1][2][3][4]. Furthermore, it is well known that T1D exhibit gender-related differences in which males are more predisposed to T1D in populations with the highest incidence, whereas a female bias was observed in the lowest risk populations (non-European origin), due to various factors [5][6][7][8].

    According to the recent report from the International Diabetes Federation (IDF), a total of 600,900 children and adolescents up to 14 years old have T1D [9]. The incidence of T1D in children is increasing worldwide, with strong indications of a geographical-specific increase, with the highest rates of T1D (>5 per 100,000) found in North Africa and America [9].

    Recently, a substantial increase in T1D incidence was observed [10], suggesting that multiple contributing factors must be involved in this higher incidence. Those factors include genetic and epigenetics contributors, autoimmunity, viral infections, antibiotics-mediated dysbiosis, gut microbiome composition, and lifestyle factors such as nutrition and modern diet [11][12][13][14][15]. Although certain HLA risk alleles are known to increase the susceptibility to T1D in children at risk, only 5% or fewer of them actually develop T1D [16], highlighting the importance of the non-genetic modifiers, in addition to other environmental factors in T1D pathogenesis [17][18]. While the genetic predisposition is considered to have a direct effect on the disease initiation, recent evidence indicated that different T1D risk alleles are also affecting the gut microbiome composition, however, it remains unclear how these risk alleles are interacting with the host gut microbiome and how these gut microbiomes affect the host epigenome leading to destructive autoimmunity [17][19]. The increasing incidence of T1D in western countries could be explained by the hygiene hypothesis, in which a lack of exposure to infectious agents can affect the maturation of the immune system [20].

    While a great deal of progress has been made in our understanding of T1D pathogenesis, translating this knowledge into a clinical decision is still far from being achieved. This review aims to discuss the triple interaction between the host genome, the epigenome, and the gut microbiome in T1D.

    2. Genetic Predisposition to T1D

    The rapid evolution in genome-wide association studies (GWAS) along with the availability of large genomic consortia have transformed our ability to link between specific gene loci and their association with auto-immune diseases including T1D [21][22][23][24][25][26]. Recent GWAS studies highlighted that the risk for developing T1D is explained by the presence of certain Human leukocyte antigen class-II (HLA class II) risk alleles in addition to 60 plus non-HLA single nucleotide polymorphisms that have been recently identified 26. These key genetic factors include the HLA alleles (mainly HLA DR and DQ genes) at position 6p21, which represent 30–50% of the T1D risk genes, in addition to HLA I and HLA III [27][28]. Around ~50% of the children carrying the HLA-risk genotypes DR3/4-DQ8 or DR4/DR4 develop T1D at a very young age (up to five years old), this risk increases when the child has a family history of T1D [29][30]. Interestingly, studies on familial T1D showed a higher incidence of T1D in offspring of fathers withT1D compared to mothers having T1D, in which the DR4-DQ8 haplotype was the most frequent haplotype in these children [31][32]. In addition to the HLA genes, 60 plus non-HLA risk alleles were shown to be involved in T1D pathogenesis, including several genetic variants in key immune genes such as the insulin gene (INS), the protein tyrosine phosphatase non-receptor type 22 gene (PTPN-22), the cytotoxic T-lymphocyte-associated protein 4 gene (CTLA4), the interleukin 2 receptor alpha (IL-2RA), and interferon-induced with helicase C domain 1 (IFIH1) in addition to PXK/PDHB and PPIL2 [33][34][35][36]. Furthermore, growing evidence from the T1D twins studies showed concordance rates range between ~23–47% in monozygotic twins compared to ~3.8–16.4% in dizygotic twins which depends on the age at diagnosis [37][38][39][40][41]. It is also worth noting that these genetic factors do not provide a 100% positive predictive value, indicating that the progression into T1D is a complex interaction of both genetic determinants and other environmental factors such as the gut microbiome [42].

    3. Gut Microbiome, Immunity, and T1D

    Gut microbiota is the collection of microorganisms living in the gastrointestinal tract including bacteria, viruses, fungi, protozoa, archaea, and accounting for 500–1000 different species, which in healthy individuals, is predominated by two major bacterial phyla Bacteroidetes and Firmicutes [43][44][45]. The benefits of these microbes range from vitamin synthesis, energy homeostasis, maturation of the immune system among others [46][47]. Besides, the byproducts of the gut microbiota can modulate the host physiology and metabolism by facilitating digestion and extraction of energy from indigestible substrates such as extraction of short-chain fatty acids (SCFAs) from indigestible fibers [46]. SCFAs are used as an energy source by the intestinal mucosa, which can in turn maintain the intestinal homeostasis by regulation of the immune response and tumorigenesis in the gut [47].

    Different factors affect the composition of the gut microbiota including the mode of delivery, diet, lifestyle, sex hormones, genetic background, pharmaceutical agents, use of antibiotics, and even the pH of the drinking water [48][49]. The alteration in the gut microbial composition has been involved in the pathogenesis of a wide array of diseases such as cardiovascular disease, gastrointestinal disease, and metabolic disorders including T1D, T2D, and obesity among others [50][51][52][53]. Interestingly, many studies have compared the microbiome composition between individuals with T1D (or those having a genetic risk of T1D) and healthy controls, in which they found differences in the gut microbiome composition, suggesting a role of the dysbiotic gut microbiome in disease pathogenesis [54][55][56][57][58][59].

    4. Microbial Metabolites, Probiotics, and T1D

    Intestinal microbes are well known to produce a range of molecules or metabolites, such as SCFAs including acetate (C2), propionate (C3), and butyrate (C4) that can modulate various host functions [60]. These molecules are byproducts for the bacterial fermentation of the dietary fibers in the colon known to maintain the gut epithelial integrity, enhance the colonic T-reg cells function, and to provide strong anti-inflammatory functions by modulating immune response [60][61]. Butyrate mediates anti-inflammatory functions in the intestinal mucosa through inhibition of the NF-κB transcription factor and activation of the CX3CR1 of macrophages (Mfs) [61][62][63]. Intestinal butyrate is also involved in the regulation of TLR 4 gene expression, by reducing the LPS translocation and blocking of LPS stimulated dendritic cells (DC), in addition to enhancing the activity of Treg cells, as well as inhibiting immune response against the gut microbiota [61][62][63]. Moreover, butyrate is also reported to maintain the intestinal integrity by modulating the intestinal forkhead box protein P3 FOXP3 (transcription factor responsible for activation of regulatory T-cell) [64]. Similar findings were documented in the mice model, for example, feeding NOD.Myd88−/− with a diet rich in starch, fibers, or SCFA resulted in enhanced production of acetate and butyrate in their stool, hepatic, and peripheral blood, and protecting them against T1D [65][66][67]. This indicates the beneficial role of the microbial metabolites in providing immune- regulatory functions [65][66][67]. In addition, feeding of NOD mice with SCFA even at the onset of T1D gave them protection against T1D, by lowering the number of islets auto-reactive T cells and enhancing the proliferation of FoxP3+ Treg cells in the gut mucosa, spleen, and pancreatic lymph nodes, thus enhancing immune tolerance [68].

    On the other hand, the progression into T1D in TLR4-deficient (TLR4−/−) NOD mice showed to be associated with the gradual decrease of SCFA concentration in their portal blood vein [69]. This indicates the beneficial effects of microbial metabolites in maintaining a healthy gut and regulating immune response which shed the light on the potential therapeutic role of probiotics[70] many probiotic bacterial strains showed an immune regulatory function leading to protection against the autoantibody destruction of the pancreatic β cells [70]. Indeed, many microbial-based probiotics have been identified with potential benefit against T1D, for example, VSL3# which consists of eight beneficial Lactobacillus strains shown to prevent or delay T1D in NOD mice, this is mediated by releasing a number of molecules with anti-inflammatory activities, modulating the number of splenic CD8 T cells, enhancing the immune tolerance and the growth of beneficial bacteria in the gut [71][72] (Figure 2). Furthermore, probiotic species such as Lactobacillus spp. (Lactobacillus. fermentum) and Clostridium cluster IV and XIV spp., can promote the integrity of the gut epithelial barrier and protect against leaky gut through enhancing the expression of tight junction proteins including ZO-1, Claudin-1, Occludin, and Cingulin, protecting against T1D associated auto-immune response in the gut [73][74].

    Due to the beneficial effects of probiotics and SCFA in maintaining the immuno-hemostasis, many clinical trials have been conducted in human subjects with T1D such as the TEDDY study, linking the early life consumption of probiotics and islet autoimmunity in genetically susceptible T1D children [75]. This study found a positive correlation between early life (the first 27 days of life), administration of probiotics (mainly Lactobacillus and Bifidobacterium), and the reduced risk of islet autoimmunity, especially in children with the highest risk [75]. Furthermore, a recent probiotic study showed that the administration of Lactobacillus rhamnosus GG can increase the serum tryptophan levels in kids with T1D, which in turn lowers the production of the inflammatory cytokines (IFN-γ, IL-17F) that is associated with the auto-immune response in PBMCs [76]. This suggests that prospective clinical studies are vital for the identification of potential novel microbiome-based therapeutic strategies for T1D.

    5. Role of Genetic Predisposition on the Gut Microbiome Composition in Individuals with T1D

    Although GWAS studies have identified T1D associated genes including both HLA and non-HLA alleles, the predicted genetic contribution does not give us a 100% positive predictive value indicating the possible role of other environmental factors such as gut bacteriome and virome [77][78]. For example, the association between various SNPs in PTPN22, PTPN2, IL10, IL2, IFIH1, INS, HLA-DRA, and CTLA4 genes and their impact on the gut microbiota composition has recently been revealed in individuals with autoimmunity and T1D [79]. Furthermore, rs2476601 and rs1893217 SNPs on PTPN22 and PTPN2 genes, respectively, were associated with a lower abundance of beneficial bacteria such as Faecalibacterium, Bilophila, and Coprococcus, in addition to a higher abundance of Bacteroides in many auto-immune diseases such as Crohn’s disease, and since these SNPs are common also in T1D, it may indicate a possible correlation with gut microbiome [79][80]. These genes are involved in the regulation of innate and adaptive immune responses against different viral and bacterial infections that are associated with the susceptibility to T1D [78]. Interestingly, several cohort studies have found an association between the DR3/4 risk genotype (haplo-genotype A) and the higher abundance of CV-B4 viral antibody levels, Parabacteroides, Bacteroides, Clostridium, Ruminococcus Saccharimonadaceae, Klebisella, Veillonella, Akkermansia, and Erysipelotrichaceae, in T1D children as shown in Figure 1 [78]. This could be explained by the fact that DR3/DR4 risk alleles can increase the susceptibility to infection by making the immune system hyper-reactive [78]. Furthermore, non-HLA T1D associated SNPs can affect the immune system by lowering the activation and the signaling functions of T cells [81]. For example, PTPN22 gene is involved in both T and B cell receptor signaling pathways in which SNPs in this gene can disturb the ability of T and B cells to recognize self from non-self-antigens [81]. In addition, SNPs on PTPN2 are associated with an increased expression of pro-inflammatory cytokines in the intestinal epithelium, stimulating the activated Th1 and Th17 cells and impairing the function of regulatory T cells [78][81]. The stimulated Th1 and Th17 cells can mediate an inflammatory response in the pancreatic tissues, this was shown to be associated with molecular mimicry between the pancreatic cells and microbiome antigens mainly in Bacteroides and Parabacteroides. however, Further studies are required in order to identify the specific correlation between each SNP and its effect on the gut microbiome composition [79][81].

    Interestingly, rs1990760 SNP on the IFIH1 gene showed to be associated with variant levels of Enterovirus RNA in peripheral blood of children at risk for T1D [82][83]. It is well known that The IFIH1 gene codes for the pattern recognition receptor MDA5 which is an innate immune receptor able to detect and interact against viral infection via activation of a cascade of antiviral responses including the stimulation of type I interferons and proinflammatory cytokines that showed to be associated with T1D [84].

    As most of T1D related genes have been identified using advanced linkage studies and GWAS studies, genetic risk scores can be used for early prognosis of T1D combing early life factors such as diet, exposure to infections, and the measuring of early life auto-antibodies that appeared before the initiation of the disease, in which the combination of these factors with the associated gut microbial dysbiosis can expand our knowledge regarding the gut microbiome interaction network, by which this disease is initiated and the possible therapeutic targets that can be applied [85].

    6. Role of Gut Microbiome in Gene Expression and Epigenetic Regulations of T1D

    As discussed, the interactions between genetic predisposition and environmental factors are significantly associated with the initiation and development of T1D. One of the most important interactions is epigenetic regulation which includes histone modifications, DNA methylation, and non-coding RNA binding [86][87]. Those interactions can be triggered by the dysbiosis in the gut microbiome and their metabolites, these metabolites act as cofactors for the key epigenetic enzymes, affecting the methylation and acetylation, in addition to mediating variations in mi-RNA expression in different T1D related genes including NF-KB P65, CTLA4, IL2, and FOXP3 [86][87].

    7. Conclusions

    This review summarizes the association between different genetic, epigenetic, and gut microbiome factors that together, can enhance the pathogenesis and progression of T1D. Although some complex interactions between the gut microbiome, the host genome, and epigenome in T1D have been revealed, still little is known about the effects of the host genome and different T1D variants on the gut microbiome, and whether these dysbiotic microbiomes are genetically determined. Further studies are required to elucidate the molecular mechanisms by which the microbial composition can contribute to protection from T1D, by understanding which bacterial species provide a specific beneficial protective role in T1D, and which type of metabolites can mediate this protective mechanism. Implementing multi-omics approaches will help to move towards identifying novel T1D initiating mechanisms and thus enable us to develop new therapies.

    This entry is adapted from 10.3390/ijms22010125


    1. Siljander, H.; Honkanen, J.; Knip, M. Microbiome and type 1 diabetes. EBioMedicine 2019, 46, 512–521.
    2. Rewers, M.; Ludvigsson, J. Environmental risk factors for type 1 diabetes. Lancet 2016, 387, 2340–2348.
    3. Kemppainen, K.M.; Ardissone, A.N.; Davis-Richardson, A.G.; Fagen, J.R.; Gano, K.A.; León-Novelo, L.G.; Vehik, K.; Casella, G.; Simell, O.; Ziegler, A.G.; et al. Early childhood gut microbiomes show strong geographic differences among subjects at high risk for type 1 diabetes. Diabetes Care 2015, 38, 329–332.
    4. Knip, M.; Simell, O. Environmental triggers of type 1 diabetes. Cold Spring Harb. Perspect. Med. 2012, 2, a007690.
    5. Blohmé, G.;Nyström, L.; Arnqvist, H.; Lithner, F.; Littorin, B.;Olsson, PO.; Scherstén, B.;Wibell L.; Ostman, J. Male predominance of type 1 (insulin-dependent) diabetes mellitus in young adults: Results from a 5-year prospective nationwide study of the 15–34-year age group in Sweden. Diabetologia 1992, 35, 56–62.
    6. Ostman, J.;Lönnberg, G.;Arnqvist, HJ.; Blohmé, G.;Bolinder, J.;EkbomSchnell,A.; Eriksson,JW.; Gudbjörnsdottir, S.;Sundkvist, G.; Nyström, L. Gender differences and temporal variation in the incidence of type 1 diabetes: Results of 8012 cases in the nationwide Diabetes Incidence Study in Sweden 1983–2002. J. Intern. Med. 2008, 263, 386–394.
    7. Fazeli Farsani, S.; Souverein, PC.; van der Vorst, MM.;Knibbe, CA.;Herings, RM.;de Boer, A.;Mantel-Teeuwisse, AK. Increasing trends in the incidence and prevalence rates of type 1 diabetes among children and adolescents in the Netherlands. Pediatric Diabetes 2016, 17, 44–52.
    8. Majeed, N.A.; Shiruhana, S.A.; Maniam, J.; Eigenmann, C.A.; Siyan, A.; Ogle, G.D. Incidence, prevalence and mortality of diabetes in children and adolescents aged under 20 years in the Republic of Maldives. J. Paediatr. Child Health 2020, 56, 746–750.
    9. International Diabetes Federation. IDF Diabetes Atlas, 9th ed.; International Diabetes Federation: Brussels, Belgium, 2019. Available online: https://www.diabetesatlas.org (accessed on 5 December 2019).
    10. Divers, J.; Mayer-Davis, E.J.; Lawrence, J.M.; Isom, S.; Dabelea, D.; Dolan, L.; Imperatore, G.; Marcovina, S.; Pettitt, D.J.; Pihoker, C.; et al. Trends in incidence of type 1 and type 2 diabetes among youths—Selected counties and Indian reservations, United States, 2002–2015. MMWR Morb. Mortal. Wkly. Rep. 2020, 69, 161–165.
    11. Han, H.; Li, Y.; Fang, J.; Liu, G.; Yin, J.; Li, T.; Yin, Y. Gut Microbiota and Type 1 Diabetes. Int. J. Mol. Sci. 2018, 19, 995–1006.
    12. Zheng, P.; Li, Z.; Zhou, Z. Gut microbiome in type 1 diabetes: A comprehensive review. Diabetes Metab. Res. Rev. 2018, 34, e3043.
    13. Sohail, M.U.; Althani, A.; Anwar, H.; Rizzi, R.; Marei, H.E. Role of the Gastrointestinal Tract Microbiome in the Pathophysiology of Diabetes Mellitus. J. Diabetes Res. 2017, 2017, 9631435.
    14. Zhang, P.; Lu, Q. Genetic and epigenetic influences on the loss of tolerance in autoimmunity. Cell. Mol. Immunol. 2018, 15, 575–585.
    15. Cerna, M. Epigenetic Regulation in Etiology of Type 1 Diabetes Mellitus. Int. J. Mol. Sci. 2019, 21, 36.
    16. Krischer, J.P.; Liu, X.; Vehik, K.; Akolkar, B.; Hagopian, W.A.; Rewers, M.J.; She, J.X.; Toppari, J.; Ziegler, A.G.; Lernmark, Å. Predicting islet cell autoimmunity and type 1 diabetes: An 8-year TEDDY study progress report. Diabetes Care 2019, 42, 1051–1060.
    17. Mullaney, J.A.; Stephens, J.E.; Costello, M.E.; Fong, C.; Geeling, B.E.; Gavin, P.G.; Wright, C.M.; Spector, T.D.; Brown, M.A.; Hamilton-Williams, E.E. Type 1 diabetes susceptibility alleles are associated with distinct alterations in the gut microbiota. Microbiome 2018, 6, 35.
    18. Wang, J.; Jia, H. Metagenome-wide association studies: Fine-mining the microbiome. Nat. Rev. Microbiol. 2016, 14, 508–522.
    19. Lee, E.-S.; Song, E.-J.; Nam, Y.-D. Dysbiosis of gut microbiome and its impact on epigenetic regulation. J. Clin. Epigenetics 2017, 3, 1–7.
    20. Bach, J.F.; Chatenoud, L. The hygiene hypothesis: An explanation for the increased frequency of insulin-dependent diabetes. Cold Spring Harb. Perspect. Med. 2012, 2, a007799.
    21. Sharp, S.A.; Weedon, M.N.; Hagopian, W.A.; Oram, R.A. Clinical and research uses of genetic risk scores in type 1 diabetes. Curr. Opin. Genet. Dev. 2018, 50, 96–102.
    22. Sharma, A.; Liu, X.; Hadley, D.; Hagopian, W.; Chen, W.M.; Onengut-Gumuscu, S.; Torn, C.; Steck, A.K.; Frohnert, B.I.; Rewers, M.; et al. Identification of non-HLA genes associated with development of islet autoimmunity and type 1 diabetes in the prospective TEDDY cohort. J. Autoimmun. 2018, 89, 90–100.
    23. Bonifacio, E.; Beyerlein, A.; Hippich, M.; Winkler, C.; Vehik, K.; Weedon, M.N.; Laimighofer, M.; Hattersley, A.T.; Krumsiek, J.; Frohnert, B.I.; et al. Genetic scores to stratify risk of developing multiple islet autoantibodies and type 1 diabetes: A prospective study in children. PLoS Med. 2018, 15, e1002548.
    24. Krischer, J.P.; Lynch, K.F.; Lernmark, A.; Hagopian, W.A.; Rewers, M.J.; She, J.X.; Toppari, J.; Ziegler, A.G.; Akolkar, B.; Group, T.S. Genetic and environmental interactions modify the risk of diabetes-related autoimmunity by 6 years of age: The TEDDY study. Diabetes Care 2017, 40, 1194–1202.
    25. Cousminer, D.L.; Ahlqvist, E.; Mishra, R.; Andersen, M.K.; Chesi, A.; Hawa, M.I.; Davis, A.; Hodge, K.M.; Bradfield, J.P.; Zhou, K.; et al. First genome-wide association study of latent autoimmune diabetes in adults reveals novel insights linking immune and metabolic diabetes. Diabetes Care 2018, 41, 2396–2403.
    26. Pociot, F. Type 1 diabetes genome-wide association studies: Not to be lost in translation. Clin. Transl. Immunol. 2017, 6, e162.
    27. Steck, A.K.; Rewers, M.J. Genetics of type 1 diabetes. Clin. Chem. 2011, 57, 176–185.
    28. Cucca, F.; Lampis, R.; Congia, M.; Angius, E.; Nutland, S.; Bain, S.C.; Barnett, A.H.; Todd, J.A. A correlation between the relative predisposition of MHC class II alleles to type 1 diabetes and the structure of their proteins. Hum. Mol. Genet. 2001, 10, 2025–2037.
    29. Redondo, M.J.; Steck, A.K.; Pugliese, A. Genetics of type 1 diabetes. Pediatr Diabetes 2018, 19, 346–353.
    30. Hagopian, W.A.; Erlich, H.; Lernmark, A.; Rewers, M.; Ziegler, A.G.; Simell, O.; Akolkar, B.; Vogt, R., Jr.; Blair, A.; Ilonen, J.; et al. The environmental determinants of diabetes in the young (TEDDY): Genetic criteria and international diabetes risk screening of 421,000 infants. Pediatric Diabetes 2011, 12, 733–743.
    31. Turtinen, M.; Härkönen, T.; Parkkola, A.; Ilonen, J.; Knip, M. Characteristics of familial type 1 diabetes: Effects of the relationship to the affected family member on phenotype and genotype at diagnosis. Diabetologia 2019, 62, 2025–2039.
    32. Harjutsalo, V.; Reunanen, A.; Tuomilehto, J. Differential transmission of type 1 diabetes from diabetic fathers and mothers to their offspring. Diabetes 2006, 55, 1517–1524.
    33. Todd, J.A.; Walker, N.M.; Cooper, J.D.; Smyth, D.J.; Downes, K.; Plagnol, V.; Bailey, R.; Nejentsev, S.; Field, S.F.; Payne, F.; et al. Robust associations of four new chromosome regions from genome-wide analyses of type 1 diabetes. Nat. Genet. 2007, 39, 857–864.
    34. Bottini, N.; Musumeci, L.; Alonso, A.; Rahmouni, S.; Nika, K.; Rostamkhani, M.; MacMurray, J.; Meloni, G.F.; Lucarelli, P.; Pellecchia, M.; et al. A functional variant of lymphoid tyrosine phosphatase is associated with type I diabetes. Nat. Genet. 2004, 36, 337–338.
    35. Bell, G.I.; Horita, S.; Karam, J.H. A polymorphic locus near the human insulin gene is associated with insulin-dependent diabetes mellitus. Diabetes 1984, 33, 176–183.
    36. Winkler, C.; Lauber, C.; Adler, K.; Grallert, H.; Illig, T.; Ziegler, A.G.; Bonifacio, E. An interferon-induced helicase (IFIH1) gene polymorphism associates with different rates of progression from autoimmunity to type 1 diabetes. Diabetes 2011, 60, 685–690.
    37. Hyttinen, V.; et al. Genetic liability of type 1 diabetes and the onset age among 22,650 young Finnish twin pairs: A nationwide follow-up study. Diabetes 2003, 52, 1052–1055.
    38. Skov, J.; et al. Co-aggregation and heritability of organ-specific autoimmunity: A population-based twin study. Eur. J. Endocrinol. 2020, 182, 473–480.
    39. Nisticò, L.; et al. Emerging effects of early environmental factors over genetic background for type 1 diabetes susceptibility: Evidence from a Nationwide Italian Twin Study. J. Clin. Endocrinol. Metab. 2012, 97, E1483–E1491.
    40. Matsuda, A.; Kuzuya, T. Diabetic twins in Japan. Diabetes Res. Clin. Pract. 1994, 24, S63–S67.
    41. Kaprio, J.; Tuomilehto, J.; Koskenvuo, M.; Romanov, K.; Reunanen, A.; Eriksson, J.; Stengård, J.; Kesäniemi, Y.A. Concordance for type 1 (insulin-dependent) and type 2 (non-insulin-dependent) diabetes mellitus in a population-based cohort of twins in Finland. Diabetologia 1992, 35, 1060–1067.
    42. Russell, J.T.; Roesch, L.F.W.; Ordberg, M.; Ilonen, J.; Atkinson, M.A.; Schatz, D.A.; Triplett, E.W.; Ludvigsson, J. Genetic risk for autoimmunity is associated with distinct changes in the human gut microbiome. Nat. Commun. 2019, 10, 3621.
    43. Stiemsma, L.T.; Michels, K.B. The role of the microbiome in the developmental origins of health and disease. Pediatrics 2018, 141, e20172437.
    44. Rinninella, E.; Raoul, P.; Cintoni, M.; Franceschi, F.; Miggiano, G.A.D.; Gasbarrini, A.; Mele, M.C. What is the Healthy Gut Microbiota Composition? A Changing Ecosystem across Age, Environment, Diet, and Diseases. Microorganisms 2019, 7, 14.
    45. Scepanovic, P.; Hodel, F.; Mondot, S.; Partula, V.; Byrd, A.; Hammer, C.; Alanio, C.; Bergstedt, J.; Patin, E.; Touvier, M.; et al. A comprehensive assessment of demographic, environmental, and host genetic associations with gut microbiome diversity in healthy individuals. Microbiome 2019, 7, 130.
    46. Shreiner, A.B.; Kao, J.Y.; Young, V.B. The gut microbiome in health and in disease. Curr. Opin. Gastroenterol. 2015, 31, 69–75.
    47. Kumar, M.; Singh, P.; Murugesan, S.; Vetizou, M.; McCulloch, J.; Badger, J.H.; Trinchieri, G.; Al Khodor, S. Microbiome as an immunological modifier. Methods Mol. Biol. 2020, 2055, 595–638.
    48. Zhernakova, A.; Kurilshikov, A.; Bonder, M.J.; Tigchelaar, E.F.; Schirmer, M.; Vatanen, T.; Mujagic, Z.; Vila, A.V.; Falony, G.; Vieira-Silva, S.; et al. Population-based metagenomics analysis reveals markers for gut microbiome composition and diversity. Science 2016, 352, 565–569.
    49. Kumar, M.; Mathur, T.; Joshi, V.; Upadhyay, D.J.; Inoue, S.I.; Masuda, N. Effect of DS-2969b, a novel GyrB inhibitor, on rat and monkey intestinal microbiota. Anaerobe 2018, 51, 120–123.
    50. de la Cuesta-Zuluaga, J.; Mueller, N.T.; Alvarez-Quintero, R.; Velasquez-Mejia, E.P.; Sierra, J.A.; Corrales-Agudelo, V.; Carmona, J.A.; Abad, J.M.; Escobar, J.S. Higher fecal short-chain fatty acid levels are associated with gut microbiome dysbiosis, obesity, hypertension and cardiometabolic disease risk factors. Nutrients 2018, 11, 51.
    51. Salguero, M.V.; Al-Obaide, M.A.I.; Singh, R.; Siepmann, T.; Vasylyeva, T.L. Dysbiosis of Gram-negative gut microbiota and the associated serum lipopolysaccharide exacerbates inflammation in type 2 diabetic patients with chronic kidney disease. Exp. Ther. Med. 2019, 18, 3461–3469.
    52. Maya-Lucas, O.; Murugesan, S.; Nirmalkar, K.; Alcaraz, L.D.; Hoyo-Vadillo, C.; Pizano-Zarate, M.L.; Garcia-Mena, J. The gut microbiome of Mexican children affected by obesity. Anaerobe 2019, 55, 11–23.
    53. Saffouri, G.B.; Shields-Cutler, R.R.; Chen, J.; Yang, Y.; Lekatz, H.R.; Hale, V.L.; Cho, J.M.; Battaglioli, E.J.; Bhattarai, Y.; Thompson, K.J.; et al. Small intestinal microbial dysbiosis underlies symptoms associated with functional gastrointestinal disorders. Nat. Commun. 2019, 10, 2012.
    54. Murri, M.; Leiva, I.; Gomez-Zumaquero, J.M.; Tinahones, F.J.; Cardona, F.; Soriguer, F.; Queipo-Ortuno, M.I. Gut microbiota in children with type 1 diabetes differs from that in healthy children: A case-control study. BMC Med. 2013, 11, 46.
    55. Leiva-Gea, I.; Sanchez-Alcoholado, L.; Martin-Tejedor, B.; Castellano-Castillo, D.; Moreno-Indias, I.; Urda-Cardona, A.; Tinahones, F.J.; Fernandez-Garcia, J.C.; Queipo-Ortuno, M.I. Gut microbiota differs in composition and functionality between children with type 1 diabetes and MODY2 and healthy control subjects: A case-control study. Diabetes Care 2018, 41, 2385–2395.
    56. de Goffau, M.C.; Luopajarvi, K.; Knip, M.; Ilonen, J.; Ruohtula, T.; Harkonen, T.; Orivuori, L.; Hakala, S.; Welling, G.W.; Harmsen, H.J.; et al. Fecal microbiota composition differs between children with beta-cell autoimmunity and those without. Diabetes 2013, 62, 1238–1244.
    57. Higuchi, B.S.; Rodrigues, N.; Gonzaga, M.I.; Paiolo, J.C.C.; Stefanutto, N.; Omori, W.P.; Pinheiro, D.G.; Brisotti, J.L.; Matheucci, E., Jr.; Mariano, V.S.; et al. Intestinal dysbiosis in autoimmune diabetes is correlated with poor glycemic control and increased Interleukin-6: A pilot study. Front. Immunol. 2018, 9, 1689.
    58. Vatanen, T.; Franzosa, E.A.; Schwager, R.; Tripathi, S.; Arthur, T.D.; Vehik, K.; Lernmark, Å.; Hagopian, W.A.; Rewers, M.J.; She, J.X.; Toppari, J.; et al. The human gut microbiome in early-onset type 1 diabetes from the TEDDY study. Nature 2018, 562, 589–594.
    59. Zhao, G.; Vatanen, T.; Droit, L.; Park, A.; Kostic, A.D.; Poon, T.W.; Vlamakis, H.; Siljander, H.; Härkönen, T.; Hämäläinen, A.M.; et al. Intestinal virome changes precede autoimmunity in type I diabetes-susceptible children. Proc. Natl. Acad. Sci. USA 2017, 114, e6166–e6175.
    60. Mariño, E.; Richards, J.L.; McLeod, K.H.; Stanley, D.; Yap, Y.A.; Knight, J.; McKenzie, C.; Kranich, J.; Oliveira, A.C.; Rossello, F.J.; et al. Gut microbial metabolites limit the frequency of autoimmune T cells and protect against type 1 diabetes. Nat. Immunol. 2017, 18, 552–562.
    61. Meng, X.; Zhou, H.Y.; Shen, H.H.; Lufumpa, E.; Li, X.M.; Guo, B.; Li, B.Z. Microbe-metabolite-host axis, two-way action in the pathogenesis and treatment of human autoimmunity. Autoimmun. Rev. 2019, 18, 455–475.
    62. Kasubuchi, M.; Hasegawa, S.; Hiramatsu, T.; Ichimura, A.; Kimura, I. Dietary gut microbial metabolites, short-chain fatty acids, and host metabolic regulation. Nutrients 2015, 7, 2839–2849.
    63. Aljutaily, T.; Consuegra-Fernandez, M.; Aranda, F.; Lozano, F.; Huarte, E. Gut microbiota metabolites for sweetening type I diabetes. Cell. Mol. Immunol. 2018, 15, 92–95.
    64. Al Nabhani, Z.; Dulauroy, S.; Marques, R.; Cousu, C.; Al Bounny, S.; Dejardin, F.; Sparwasser, T.; Berard, M.; Cerf-Bensussan, N.; Eberl, G. A weaning reaction to microbiota is required for resistance to immunopathologies in the adult. Immunity 2019, 50, 1276–1288.
    65. Kim, C.H. Microbiota or short-chain fatty acids: Which regulates diabetes? Cell. Mol. Immunol. 2018, 15, 88–91.
    66. Wen, L.; Wong, F.S. Dietary short-chain fatty acids protect against type 1 diabetes. Nat. Immunol. 2017, 18, 484–486.
    67. Luu, M.; Visekruna, A. Short-chain fatty acids: Bacterial messengers modulating the immunometabolism of T cells. Eur. J. Immunol. 2019, 49, 842–848.
    68. Sorini, C.; Cosorich, I.; Falcone, M. New therapeutic perspectives in Type 1 Diabetes: Dietary interventions prevent beta cell-autoimmunity by modifying the gut metabolic environment. Cell. Mol. Immunol. 2017, 14, 951–953.
    69. Simon, M.C.; Reinbeck, A.L.; Wessel, C.; Heindirk, J.; Jelenik, T.; Kaul, K.; Arreguin-Cano, J.; Strom, A.; Blaut, M.; Backhed, F.; et al. Distinct alterations of gut morphology and microbiota characterize accelerated diabetes onset in nonobese diabetic mice. J. Biol. Chem. 2020, 295, 969–980.
    70. Mishra, S.P.; Wang, S.; Nagpal, R.; Miller, B.; Singh, R.; Taraphder, S.; Yadav, H. Probiotics and prebiotics for the amelioration of type 1 diabetes: Present and future perspectives. Microorganisms 2019, 7, 67.
    71. Valladares, R.; Sankar, D.; Li, N.; Williams, E.; Lai, K.K.; Abdelgeliel, A.S.; Gonzalez, C.F.; Wasserfall, C.H.; Larkin, J.; Schatz, D.; et al. Lactobacillus johnsonii N6.2 mitigates the development of type 1 diabetes in BB-DP rats. PLoS ONE 2010, 5, e10507.
    72. Jia, L.; Cao, M.; Chen, H.; Zhang, M.; Dong, X.; Ren, Z.; Sun, J.; Pan, L.L. Butyrate ameliorates antibiotic-driven type 1 diabetes in the female offspring of nonobese diabetic mice. J. Agric. Food Chem. 2020, 68, 3112–3120.
    73. Sanders, M.E.; Merenstein, D.J.; Reid, G.; Gibson, G.R.; Rastall, R.A. Probiotics and prebiotics in intestinal health and disease: From biology to the clinic. Nat. Rev. Gastroenterol. Hepatol. 2019, 16, 605–616.
    74. Chen, Y.; Zhang, L.; Hong, G.; Huang, C.; Qian, W.; Bai, T.; Song, J.; Song, Y.; Hou, X. Probiotic mixtures with aerobic constituent promoted the recovery of multi-barriers in DSS-induced chronic colitis. Life Sci. 2020, 240, 117089.
    75. Uusitalo, U.; Liu, X.; Yang, J.; Aronsson, C.A.; Hummel, S.; Butterworth, M.; Lernmark, A.; Rewers, M.; Hagopian, W.; She, J.X.; et al. Association of early exposure of probiotics and islet autoimmunity in the TEDDY study. JAMA Pediatrics 2016, 170, 20–28.
    76. Mondanelli, G.; Orecchini, E.; Volpi, C.; Panfili, E.; Belladonna, M.L.; Pallotta, M.T.; Moretti, S.; Galarini, R.; Esposito, S.; Orabona, C. Effect of probiotic administration on serum tryptophan metabolites in pediatric type 1 diabetes patients. Int. J. Tryptophan Res. 2020, 13, 1178646920956646.
    77. Torn, C.; Hadley, D.; Lee, H.S.; Hagopian, W.; Lernmark, A.; Simell, O.; Rewers, M.; Ziegler, A.; Schatz, D.; Akolkar, B.; et al. Role of type 1 diabetes-associated snps on risk of autoantibody positivity in the TEDDY study. Diabetes 2015, 64, 1818–1829.
    78. Blanter, M.; Sork, H.; Tuomela, S.; Flodstrom-Tullberg, M. Genetic and environmental interaction in type 1 diabetes: A relationship between genetic risk alleles and molecular traits of enterovirus infection? Curr. Diabetes Rep. 2019, 19, 82.
    79. Sharp, R.C.; Abdulrahim, M.; Naser, E.S.; Naser, S.A. Genetic variations of PTPN2 and PTPN22: Role in the pathogenesis of type 1 diabetes and Crohn’s disease. Front. Cell. Infect. Microbiol. 2015, 5, 95.
    80. Yilmaz, B.; Spalinger, M.R.; Biedermann, L.; Franc, Y.; Fournier, N.; Rossel, J.B.; Juillerat, P.; Rogler, G.; Macpherson, A.J.; Scharl, M. The presence of genetic risk variants within PTPN2 and PTPN22 is associated with intestinal microbiota alterations in Swiss IBD cohort patients. PLoS ONE 2018, 13, e0199664.
    81. Jerram, S.T.; Leslie, R.D. The genetic architecture of Type 1 diabetes. Genes 2017, 8,
    82. Cinek, O.; Tapia, G.; Witso, E.; Kramna, L.; Holkova, K.; Rasmussen, T.; Stene, L.C.; Ronningen, K.S. Enterovirus RNA in peripheral blood may be associated with the variants of rs1990760, a common type 1 diabetes associated polymorphism in IFIH1. PLoS ONE 2012, 7, e48409.
    83. Jermendy, A.; Szatmari, I.; Korner, A.; Szabo, A.J.; Toth-Heyn, P.; Hermann, R. Association between interferon-induced helicase (IFIH1) rs1990760 polymorphism and seasonal variation in the onset of type 1 diabetes mellitus. Pediatric Diabetes 2018, 19, 300–304.
    84. Domsgen, E.; Lind, K.; Kong, L.; Huhn, M.H.; Rasool, O.; van Kuppeveld, F.; Korsgren, O.; Lahesmaa, R.; Flodstrom-Tullberg, M. An IFIH1 gene polymorphism associated with risk for autoimmunity regulates canonical antiviral defence pathways in Coxsackievirus infected human pancreatic islets. Sci. Rep. 2016, 6, 39378.
    85. Redondo, M.J.; Geyer, S.; Steck, A.K.; Sharp, S.; Wentworth, J.M.; Weedon, M.N.; Antinozzi, P.; Sosenko, J.; Atkinson, M.; Pugliese, A.; et al. A type 1 diabetes genetic risk score predicts progression of islet autoimmunity and development of type 1 diabetes in individuals at risk. Diabetes Care 2018, 41, 1887–1894.
    86. Chen, B.; Sun, L.; Zhang, X. Integration of microbiome and epigenome to decipher the pathogenesis of autoimmune diseases. J. Autoimmun. 2017, 83, 31–42.
    87. Miro-Blanch, J.; Yanes, O. Epigenetic regulation at the interplay between gut microbiota and host metabolism. Front. Genet. 2019, 10, 638.