WO2022171685A1 - Tnf-alpha blocking agent for preventing, suppressing and/or delaying the onset of type 1 diabetes - Google Patents

Abstract

Type 1 diabetes (T1D) is an autoimmune disease caused by the destruction of pancreatic cells producing insulin. The present studies demonstrate that gut mucosa alterations and dysbiosis in T1D are primarily linked to inflammation rather than hyperglycemia. Anti- inflammatory treatment with TNF-blocking agent preserves gut homeostasis and protective commensal flora reducing T1D incidence. More particularly, the results reveal SFB as a potential biomarker of T1D progression in at-risk individuals and suggest that an anti- inflammatory treatment with TNF blocking agents might be of interest to reduce intestinal alteration associated with T1D onset.

Description

TNF-ALPHA BLOCKING AGENT FOR PREVENTING, SUPPRESSING AND/OR DELAYING THE ONSET OF TYPE 1 DIABETES

FIELD OF THE INVENTION:

The present invention is in the field of medicine.

BACKGROUND OF THE INVENTION:

Type I diabetes (T1D) is an autoimmune disease characterized by the destruction of pancreatic b-cells that produce insulin [1] The pathological activation of the immune system results in pancreatic inflammation, anti-islet antibody production, and islet infiltration by cytotoxic cells [2,3] Both innate and adaptive immune systems are inappropriately activated and involved in disease progression, in the pancreas and associated pancreatic lymph nodes (PLN) [2,3] The resulting loss of insulin production leads to chronic hyperglycemia and forces patients to rely on an insulin replacement therapy for life [1]

Another organ severely affected in T1D is the gastrointestinal tract. Several studies have described structural alterations of the gut mucosa, such as a reduction in crypt length and tight junction proteins expression in both T1D patients and animal models [4-9] Functional studies using mannitol -lactose clearance in patients with T1D and FITC-dextran in animal models of T1D demonstrated that gut integrity is weakened, allowing an increased crossing of bacterial components from the gut lumen to systemic circulation [10-13] Several factors are suspected to be involved in gut permeability rise in the context of diabetes, including alimentation, microbiota alteration, and enteric infection [8,14-17]

In parallel, the gut immune system, which resides in close contact with microbiota, displays pro-inflammatory features upon T1D development [18-20] The incidence of chronic intestinal inflammation is higher in T1D patients compared to the general population [21,22] Infiltration of pro-inflammatory cells is increased in the gut mucosa of T1D patients compared to healthy controls while Forkhead box P3⁺ (FOXP3⁺) regulatory T cells frequencies are reduced [18,19,23] We previously reported that Mucosal-Associated Invariant T (MAIT) cells exert a key role in maintaining gut integrity that is lost during T1D progression in Non-obese diabetic (NOD) mice [24] Indeed, MAIT-deficient NOD mice develop an exacerbated disease associated with increased gut alterations and bacteria DNA translocation into PLN [24] During disease progression in NOD females, MAIT cells lose IL-17A and IL-22 production, two critical cytokines required to maintain gut integrity [25-27] SUMMARY OF THE INVENTION:

The present invention is defined by the claims. In particular, the present invention relates to the use of TNFa blocking agent for preventing, suppressing and/or delaying the onset of type 1 diabetes.

PET ATT /ED DESCRIPTION OF THE INVENTION:

Type 1 diabetes (T1D) is an autoimmune disease caused by the destruction of pancreatic b-cells producing insulin. Both T1D patients and animal models exhibit gut microbiota and mucosa alterations, although the exact cause for these remains poorly understood. The inventors investigated the production of key cytokines controlling gut integrity, the abundance of Segmented Filamentous Bacteria (SFB) involved in the production of these cytokines, and the respective role of auto-immune inflammation and hyperglycemia. The inventors used several mouse models of autoimmune T1D as well as mice rendered hyperglycemic without inflammation to study gut mucosa and microbiota dysbiosis. They analyzed cytokine expression by immune cells, epithelial cell function, SFB abundance and microbiota composition by 16S sequencing. They also assessed the role of anti-TNFa on gut mucosa inflammation and T1D onset. The inventors show in models of autoimmune T1D a conserved loss of IL-17A, IL-22, and IL-23A in gut mucosa. Intestinal epithelial cell function was altered and gut integrity was impaired. These defects were associated with dysbiosis including progressive loss of SFB. Transfer of diabetogenic T-cells recapitulated these gut alterations, whereas induction of hyperglycemia with no inflammation failed to do so. Moreover, anti inflammatory treatment restored gut mucosa and immune cell function and dampened diabetes incidence. The results demonstrate that gut mucosa alterations and dysbiosis in T1D are primarily linked to inflammation rather than hyperglycemia. Anti-inflammatory treatment with TNF-blocking agent preserves gut homeostasis and protective commensal flora reducing T1D incidence. More particularly, the results reveal SFB as a potential biomarker of T1D progression in at-risk individuals and suggest that an anti-inflammatory treatment with TNF blocking agents might be of interest to reduce intestinal alteration associated with T1D onset.

The present invention relates to methods for treating, preventing, suppressing and/or delaying the onset, or reducing the risk of developing type 1 diabetes, or the symptoms associated with, or related to, type 1 diabetes, in a subject in need thereof comprising administering to the subject a therapeutically effective amount of a TNFa blocking agent.

As used herein, the term “Type 1 diabetes” has its general meaning in the art and refers to the condition in which a subject has, in the presence of autoimmunity towards the pancreatic beta cell as detected through pancreatic biopsy or imaging), a fasting (i.e., no caloric intake for 8 hours) blood glucose or serum glucose concentration greater than 125 mg/dL (6.94 mmol/L). Type 1 diabetes is also defined as the condition in which a subject has, in the presence of autoimmunity towards the pancreatic beta-cell, HbAlc equal to, or greater than 6.5%, a two hour plasma glucose equal to, or greater than 200 mg/dL (11.1 mmol/L) during an oral glucose tolerance test (OGTT) or a random glucose equal to, or greater than 200 mg/dL (11.1 mmol/L) in conjunction with classic symptoms of hyperglycaemia or hyperglycaemic crisis. The measurement of blood glucose values is a standard procedure in routine medical analysis. The assessment of HbAlc should be performed using a method certified by the National Glycohemoglobin Standardization Program (NGSP) and standardized or traceable to the Diabetes Control and Complications Trial (DCCT) reference assay. If an OGTT is carried out, the blood sugar level of a diabetic will be in excess of 200 mg of glucose per dL (11.1 mmol/I) of plasma 2 hours after 75 g of glucose have been taken on an empty stomach, in the presence of autoimmunity towards the pancreatic beta cell. In a glucose tolerance test 75 g of glucose are administered orally to the patient being tested after a minimum of 8 hours, typically, 10-12 hours, of fasting and the blood sugar level is recorded immediately before taking the glucose and 1 and 2 hours after taking it. Typically a genetic predisposition is present (e.g. HLA, INS VNTR and PTPN22), but this is not always the case.

As used herein, the term “overt diabetes” or “diabetes onset” is intended to mean a disease state in which the pancreatic islet cells are destroyed and which is manifested clinically by overt hyperglycemia (i.e., fasting blood glucose levels ³ 250 mg/dL). Typically, the time of progression from presymptomatic to clinical type 1 diabetes varies from weeks to decades.

In some embodiments, the subject is a child. In some embodiments, the subject is a premature human infant. In some embodiments the child is 3 to 5 years old. In some embodiments, the subject is an adult. In some embodiments, the adult is more than 18 years old. In some embodiments, the subject is a pre-diabetic subject. As used herein the term “prediabetic subject” is a subject at risk for the development of diabetes (e.g., genetically predisposed) at any stage in the disease process prior to overt diabetes or diabetes onset. In particular, the pre-diabetic subject exhibits one or more biomarkers that indicate that the subject is at risk of having type 1 diabetes and/or abnormal first phase insulin test (insulin response to an i.v. glucose bolus). The autoantibodies currently used as biomarkers of type 1 diabetes in the clinic are mainly those targeting insulin, glutamic acid decarboxylase (GAD), a tyrosine phosphatase-like protein (islet antigen-2 [IA-2]) and zinc transporter-8 (ZnT8). The development of autoantibodies against multiple beta cell antigens is recognized as a critical step in the disease pathogenesis and is associated with a significantly higher type 1 diabetes risk than the presence of just a single autoantibody. Moreover, multiple beta cell autoantibody positive individuals are at high risk of type 1 diabetes regardless of family history, and children who develop two or more beta cell autoantibody types almost inevitably progress to clinically symptomatic diabetes. Typically, biomarkers are typically discussed in Mathieu, C., Lahesmaa, R., Bonifacio, E. et al. Immunological biomarkers for the development and progression of type 1 diabetes. Diabetologia 61, 2252 2258 (2018).

In some embodiments, the subject exhibits a dysbiosis. As used herein, the term “dysbiosis” has its general meaning in the art and refers to an altered state of the microbiota occurring during diseases compared to the compositional and functional homeostasis in healthy individuals. Dysbiosis is currently viewed as a sign of an altered microbe-host crosstalk and is a primary target of strategies aiming at restoring or maintaining intestinal functional homeostasis.

In some embodiments, the dysbiosis includes progressive loss of Segmented Filamentous Bacteria B (SFB).

In some embodiments, the dysbiosis is progressive loss of Segmented Filamentous Bacteria B (SFB).

Thus, in some embodiments, the method of the present invention comprises the steps of measuring the abundance of SFB in a fecal sample obtained from the subject. In some embodiments, the method herein described comprises the steps consisting of i) measuring the abundance of SFB in a fecal sample obtained from the subject ii) comparing the determined abundance with a predetermined reference value wherein differential between said determined abundance and said predetermined reference value indicates whether or not the subject is administered with a therapeutically effective amount of a TNFa blocking agent.

In some embodiment, a therapeutically effective amount of a TNFa blocking agent is administered to the subject when the determined abundance is lower than said predetermined reference value.

As used herein, the term “abundance” refers to the quantity or the concentration of said bacteria in a location/sample. In some embodiments, the abundance is absolute abundance. As used herein, the term “absolute abundance” refers to the concentration of said bacteria in a location/sample expressed for instance in number of UFC per mL or genome equivalent per mL. In some embodiments, the abundance is relative abundance. As used herein, the term “relative abundance” refers to the percent composition of a bacterium genus relative to the total number of bacteria genus in a given location/sample.

As used herein, the term “Segmented Filamentous Bacteria B” or “SFB” has its general meaning in the art and refers to a group of bacteria that are unique immune modulatory bacteria colonizing the small intestine of a variety of animals in a host-specific manner. SFB exhibit filamentous growth and attach to the host’s intestinal epithelium. The SFB was classified as Candidatus savagella.

In some embodiments, the abundance of SFB bacteria is measuring by any routine method well known in the art and typically by using molecular methods. In some embodiments, the abundance of SFB is measuring using 16S rRNA deep-sequencing. In some embodiments, the abundance of SFB is measuring using the abundance table generated by the next-generation sequencing of 16S rRNA genes of all bacteria within a given biological sample using qPCR technique. Nucleic acids may be extracted from a sample by routine techniques such as those described in Diagnostic Molecular Microbiology: Principles and Applications (Persing et al. (eds), 1993, American Society for Microbiology, Washington D.C.). U.S. Pat. Nos. 4,683,202, 4,683,195, 4,800,159, and 4,965,188 disclose conventional PCR techniques. PCR typically employs two oligonucleotide primers that bind to a selected target nucleic acid sequence. Primers useful in the present invention include oligonucleotides capable of acting as a point of initiation of nucleic acid synthesis within the target nucleic acid sequence. qPCR involves use of a thermostable polymerase. Typically, the polymerase is a Taq polymerase (i.e. Thermus aquaticus polymerase). The primers are combined with PCR reagents under reaction conditions that induce primer extension. The newly synthesized strands form a double-stranded molecule that can be used in the succeeding steps of the reaction. The steps of strand separation, annealing, and elongation can be repeated as often as needed to produce the desired quantity of amplification products corresponding to the target nucleic acid sequence molecule. The limiting factors in the reaction are the amounts of primers, thermostable enzyme, and nucleoside triphosphates present in the reaction. The cycling steps (i.e., denaturation, annealing, and extension) are preferably repeated at least once. For use in detection, the number of cycling steps will depend, e.g., on the nature of the sample. If the sample is a complex mixture of nucleic acids, more cycling steps will be required to amplify the target sequence sufficient for detection. Generally, the cycling steps are repeated at least about 20 times, but may be repeated as many as 40, 60, or even 100 times. The 16S deep-sequencing technique is well-described in the state of the art for instance, Shendure and Ji. "Next-generation DNA sequencing", Nature Biotechnology, 26(10): 1135-1145 (2008)). The 16S deep-sequencing technique also known as “next-generation DNA sequencing” ("NGS"), "high-throughput sequencing", "massively parallel sequencing” and "deep sequencing" refers to a method of sequencing a plurality of nucleic acids in parallel. See e.g., Bentley et al, Nature 2008, 456:53-59. The leading commercially available platforms produced by Roche/454 (Margulies et al, 2005a), Illumina/Solexa (Bentley et al, 2008), Life/APG (SOLiD) (McKernan et al, 2009) and Pacific Biosciences (Eid et al, 2009) may be used for deep sequencing. For example, in the 454 method, the DNA to be sequenced is either fractionated and supplied with adaptors or segments of DNA can be PCR-amplified using primers containing the adaptors. The adaptors are nucleotide 25- mers required for binding to the DNA Capture Beads and for annealing the emulsion PCR Amplification Primers and the Sequencing Primer. The DNA fragments are made single stranded and are attached to DNA capture beads in a manner that allows only one DNA fragment to be attached to one bead. Next, the DNA containing beads are emulsified in a water- in-oil mixture resulting in microreactors containing just one bead. Within the microreactor, the fragment is PCR-amplified, resulting in a copy number of several million per bead. After PCR, the emulsion is broken and the beads are loaded onto a pico titer plate. Each well of the pico- titer plate can contain only one bead. Sequencing enzymes are added to the wells and nucleotides are flowed across the wells in a fixed order. The incorporation of a nucleotide results in the release of a pyrophosphate, which catalyzes a reaction leading to a chemiluminescent signal. This signal is recorded by a CCD camera and a software is used to translate the signals into a DNA sequence. In the lllumina method (Bentley (2008)), single stranded, adaptor-supplied fragments are attached to an optically transparent surface and subjected to "bridge amplification". This procedure results in several million clusters, each containing copies of a unique DNA fragment. DNA polymerase, primers and four labeled reversible terminator nucleotides are added and the surface is imaged by laser fluorescence to determine the location and nature of the labels. Protecting groups are then removed and the process is repeated for several cycles. The SOLiD process (Shendure (2005)) is similar to 454 sequencing, DNA fragments are amplified on the surface of beads. Sequencing involves cycles of ligation and detection of labeled probes. Several other techniques for high-throughput sequencing are currently being developed. Examples of such are The Helicos system (Harris (2008)), Complete Genomics (Drmanac (2010)) and Pacific Biosciences (Lundquist (2008)). As this is an extremely rapidly developing technical field, the applicability to the present invention of high throughput sequencing methods will be obvious to a person skilled in the art.

In some embodiments, the method of the present invention comprises the steps of i) determining the abundance of SFB in a fecal sample obtained from the subject, ii) comparing the abundance determined at step i) with a predetermined reference value and iii) administering to the subject a therapeutically effective amount of a TNFa blocking agent when the abundance is lower than the predetermined reference value.

In other words, the invention refers to a methods for treating, preventing, suppressing and/or delaying the onset, or reducing the risk of developing type 1 diabetes, or the symptoms associated with, or related to, type 1 diabetes, in a subject in need thereof comprising the steps of i) measuring the abundance of SFB in a fecal sample obtained from the subject, ii) comparing the abundance determined at step i) with a predetermined reference value and iii) administering to the subject a therapeutically effective amount of a TNFa blocking agent when the abundance determined at step i) is lower than the predetermined reference value.

Typically, the predetermined reference value is a threshold value or a cut-off value. Typically, a "threshold value" or "cut-off value" can be determined experimentally, empirically, or theoretically. A threshold value can also be arbitrarily selected based upon the existing experimental and/or clinical conditions, as would be recognized by a person of ordinary skilled in the art. For example, retrospective measurement in properly banked historical subject samples may be used in establishing the predetermined reference value. The threshold value has to be determined in order to obtain the optimal sensitivity and specificity according to the function of the test and the benefit/risk balance (clinical consequences of false positive and false negative). Typically, the optimal sensitivity and specificity (and so the threshold value) can be determined using a Receiver Operating Characteristic (ROC) curve based on experimental data. For example, after determining the abundance of SFB in a group of reference, one can use algorithmic analysis for the statistic treatment of the abundances determined in samples to be tested, and thus obtain a classification standard having significance for sample classification. The full name of ROC curve is receiver operator characteristic curve, which is also known as receiver operation characteristic curve. It is mainly used for clinical biochemical diagnostic tests. ROC curve is a comprehensive indicator that reflects the continuous variables of true positive rate (sensitivity) and false positive rate (1 -specificity). It reveals the relationship between sensitivity and specificity with the image composition method. A series of different cut-off values (thresholds or critical values, boundary values between normal and abnormal results of diagnostic test) are set as continuous variables to calculate a series of sensitivity and specificity values. Then sensitivity is used as the vertical coordinate and specificity is used as the horizontal coordinate to draw a curve. The higher the area under the curve (AUC), the higher the accuracy of diagnosis. On the ROC curve, the point closest to the far upper left of the coordinate diagram is a critical point having both high sensitivity and high specificity values. The AUC value of the ROC curve is between 1.0 and 0.5. When AUC>0.5, the diagnostic result gets better and better as AUC approaches 1. When AUC is between 0.5 and 0.7, the accuracy is low. When AUC is between 0.7 and 0.9, the accuracy is moderate. When AUC is higher than 0.9, the accuracy is high. This algorithmic method is preferably done with a computer. Existing software or systems in the art may be used for the drawing of the ROC curve, such as: MedCalc 9.2.0.1 medical statistical software, SPSS 9.0, ROCPOWER.SAS, DESIGNROC.FOR, MULTIREADER POWER S AS, CREATE-ROC.SAS, GB STAT VIO.O (Dynamic Microsystems, Inc. Silver Spring, Md., USA), etc.

As used herein, the term "TNFa" or “TNF-alpha” denotes the tumor necrosis factor - alpha. The human TNF-alpha is a human cytokine encoded by the TNF-alpha gene. TNF-alpha, a naturally occurring cytokine, plays a central role in the inflammatory response and in immune injury. It is formed by the cleavage of a precursor transmembrane protein, forming soluble molecules, which aggregate to form trimolecular complexes. These complexes then bind to receptors found on a variety of cells. Binding produces an array of pro-inflammatory effects, including release of other pro-inflammatory cytokines, including IL-6, IL-8, and IL-1; release of matrix metalloproteinases; and up regulation of the expression of endothelial adhesion molecules, further amplifying the inflammatory and immune cascade by attracting leukocytes into extravascular tissues. As used herein, the term “TNFa blocking agent" or "TBA", it is herein meant a biological agent which is capable of neutralizing the effects of TNFa. Said agent is a preferentially a protein such as a soluble TNFa receptor, e.g. Pegsunercept, or an antibody. In some embodiments, the TBA is a monoclonal antibody having specificity for TNFa or for TNFa receptor. In some embodiments, the TBA is selected in the group consisting of Etanercept (Enbrel®), Infliximab (Remicade®), Adalimumab (Humira®), Certolizumab pegol (Cimzia®), and golimumab (Simponi®). Recombinant TNF-receptor based proteins have also been developed (e.g. etanercept, a recombinant fusion protein consisting of two extracellular parts of soluble TNFa receptor 2 (p75) joined by the Fc fragment of a human IgGl molecule). A pegylated soluble TNF type 1 receptor can also be used as a TNF blocking agent. Additionally, thalidomide has been demonstrated to be a potent inhibitor of TNF production. TNFa blocking agents thus further include phosphodiesterase 4 (IV) inhibitor thalidomide analogues and other phosphodiesterase IV inhibitors. As used herein, the term “etanercept” or “ETA” denotes the tumor necrosis factor - alpha (TNFa) antagonist used for the treatment of rheumatoid arthritis. The term “etanercept” (ETA, ETN, Enbrel) is a recombinant TNF-receptor IgG-Fc-fusion protein composed of the p75 TNF receptor genetically fused to the Fc domain of IgGl. Etanercept neutralizes the proinflammatory cytokine tumor necrosis factor-a (TNFa) and lymphotoxin-a (Batycka-Baran et ah, 2012).

As demonstrated in EXAMPLE, the TNFa blocking agent would be suitable for restoring intestinal homeostasis in pre-diabetic subjects and more particular would be suitable for reducing gut inflammation. Even more particularly, the TNFa blocking agent would also be suitable for reducing the promotion of the anti-islet T cell and thus would be suitable for reducing to pancreatic infiltration. Reducing inflammation the TNFa blocking agent would also be suitable for correcting T ID-associated SFB dysbiosis and mucosal dysfunctions.

As used herein, the term "therapeutically effective amount" as used herein refers to an amount or dose of the TNFa blocking agent that is sufficient to prevent the onset of diabetes. The "therapeutically effective amount" is determined using procedures routinely employed by those of skill in the art such that an "improved therapeutic outcome" results. It will be understood, however, that the total daily usage of the compounds and compositions of the present invention will be decided by the attending physician within the scope of sound medical judgment. The specific therapeutically effective dose level for any particular subject will depend upon a variety of factors including the disorder being treated and the severity of the disorder; activity of the specific compound employed; the specific composition employed, the age, body weight, general health, sex and diet of the subject; the time of administration, route of administration, and rate of excretion of the specific compound employed; the duration of the treatment; drugs used in combination or coincidential with the specific polypeptide employed; and like factors well known in the medical arts. For example, it is well within the skill of the art to start doses of the compound at levels lower than those required to achieve the desired therapeutic effect and to gradually increase the dosage until the desired effect is achieved. However, the daily dosage of the products may be varied over a wide range from 0.01 to 1,000 mg per adult per day. Typically, the compositions contain 0.01, 0.05, 0.1, 0.5, 1.0, 2.5, 5.0, 10.0, 15.0, 25.0, 50.0, 100, 250 and 500 mg of the active ingredient for the symptomatic adjustment of the dosage to the subject to be treated. A medicament typically contains from about 0.01 mg to about 500 mg of the active ingredient, preferably from 1 mg to about 100 mg of the active ingredient. An effective amount of the drug is ordinarily supplied at a dosage level from 0.0002 mg/kg to about 20 mg/kg of body weight per day, especially from about 0.001 mg/kg to 7 mg/kg of body weight per day.

In some embodiments, the TNFa blocking agent is locally administered to the patient (i.e. in the subject’s gut). Typically the present invention thus comprises preparations of TNFa blocking agent which are suitable for topical delivery. Such topical preparations may be prepared in the form of aqueous-based solutions, gels, or patches for topical administration, and suspensions for administration, as pills, tablets, capsules or suppositories for immediate or sustained release to the gastrointestinal tract.

The invention will be further illustrated by the following figures and examples. However, these examples and figures should not be interpreted in any way as limiting the scope of the present invention.

FIGURES:

Figure 1. T1D development in NOD mice is associated with decreased SFB level. LP cells from small intestine (ileum) of prediabetic (8-10 weeks) and diabetic females NOD mice were analyzed. (A, B) Ileal tissues and fecal content were collected and extracted DNA was analyzed by qPCR for the presence of intestinal SFB (n=15 mice per group). (C) SFB level was assessed by qPCR in feces from non-diabetic NOD mice from 4 to 13 weeks of age (n=4-12 mice per group). (D) SFB level was quantified by qPCR and followed from 7 weeks to 13 weeks of age in feces from female C57BL/6J mice, female NOD mice that became, or not, diabetic at 13 weeks of age (n=4-15 mice per group). Significant differences between C57BL/6J and diabetic NOD mice are represented by a $ symbol. (E) Spearman’s correlation between SFB level and Fut2 relative expression in ileal tissues (n=16 diabetic mice). (F) Intestinal gut permeability measured by in vivo FITC-dextran assay in NOD mice at 6, 10, 12 weeks of age and at diabetes onset (n=3-10 mice per group). Data are representative from at least two independent experiments and horizontal lines indicate the median, each data point represents an individual mouse. */$P<0.05, **P<0.01, ***P<0.001 and ****p<0.0001 (two-tailed Mann-Whitney test).

Figure 2. Anti-TNFa treatment prevents gut mucosa alteration and diabetes onset.

Recipient CD45.1⁺ Ir^' ac NOD mice were transferred with 0.5 x 10⁶ CD45.2⁺ CD4⁺ CD62L⁺ BDC2.5 T cells and treated with anti-TNFa (lOmg/kg) or human control IgGl antibodies on day 0, 3, and 6. (A) RT-qPCR analysis of mRNA encoding for 1117a, 1122, 1122a and Foxp3 from LP cells (n=9-ll mice per group). Results were normalized to the expression of Gapdh. (B) Flow cytometric analysis of intestinal ECs (CD45 EpCam⁺) was performed with UEA-1- FITC to detect fucosylated-ECs. Representative dot-plots and percentages of fucosylated-ECs are shown (n=3-9 mice per group) according to cell size (FSC-A). (C) RT-qPCR analysis of mRNA encoding for Cldn4 , Tjpl, Ocln , and Muc2 in sorted ECs from ileum (n=10 mice per group). Results were normalized to the expression of Gapdh. (D) Intestinal gut permeability was evaluated with in vivo FITC-dextran assay (n=6-10 mice per group). (E) Relative SFB abundance and level determined by 16S-sequencing and qPCR of fecal contents and ileum tissue on day 13 post-transfer (n=6-10 mice per group). qPCR results were normalized to the respective abundance of total bacteria. (F) Analysis of pancreatic islet infiltration and incidence of diabetes of recipient Trac^/~ NOD mice on day 15 after transfer with BDC2.5 T cells and treatment with either anti-TNFa or human control IgGl antibodies (n=26-27 mice per group). All data are representative of at least three independent experiments and horizontal lines indicate the median, each data point represents an individual mouse. *P<0.05, **P<0.01 and ***P<0.001 (unpaired t-test (in panel A, for Foxp3 mRNA) and two-tailed Mann-Whitney test).

EXAMPLE:

Methods Mice. Male and female C57BL/6J, male and female NOD, female RORyt-GFP NOD, female BDC2.5 CD45.2^+/+ Trac NOD, and female recipient CD45.1^+/+ Trac NOD mice were previously described [24,59] All mice were bred under specific pathogen-free conditions. This study was approved by the Ethics Committee on Animal Experimentation (APAFIS#3474- 2015102016444419v3 and APAFIS# 17515-201811091441828v4).

Isolation of DNA, RNA, and RT. For DNA extraction, fresh stool or small pieces of ileum tissue were weighted, recovered, immediately frozen in liquid nitrogen upon collection, and stored at -80°C until DNA isolation. DNA extraction was performed using NucleoSpin Tissue (Macherey -Nagel) following the manufacturer’s instructions. Sections of liver near the portal vein were recovered from mice at different ages and DNA was extracted as previously described [24] For RNA isolation, cells were lysed in RLT buffer with 1% b-mercaptoethanol, and mRNA was purified from lysed cells using RNeasy Mini Kit (Qiagen). cDNA was synthesized using the Superscript III reverse transcriptase (Invitrogen). qPCR Quantitative-PCR analysis was performed with SYBR Green (Roche) and analyzed using a LightCycler 480 (Roche). The relative expression was calculated using the 2 ^DDa method and normalized to the expression of the housekeeping gene Gapdh or the expression of total bacteria, as appropriate. The stability of Gapdh expression was confirmed by comparison with hypoxanthine phosphoribosyltransferase ( Hprt ) mRNA expression.

Fecal microbiota analysis. 16S rRNA gene amplification and library constructions were performed according to Illumina recommendations. Sequencing was performed on an Illumina MiSeq. Taxonomy and data analyses were conducted using QIIME.

Statistical analysis. Statistical analyses were performed with Prism software (Graph Pad V8.3). All datasets were tested for normal distribution using the Shapiro-Wilk normality test. Datasets were compared using either parametric two-tailed unpaired t-test, nonparametric two-tailed Mann-Whitney or Kruskal -Wallis tests with multiple comparisons Dunn’s post-test, as appropriate. Significant differences in taxonomic abundances were assessed with nonparametric Kruskal-Wallis test with the false-discovery rate correction implemented in Qiime. Diabetes incidence was plotted according to the Kaplan-Meier method and statistical differences were analyzed using the Mantel-Cox (log-rank test). Differences were considered significant at P < 0.05 (*/$P<0.05, **P<0.01, ***P<0.001, ****P<0.0001). Results

T1D development in NOD mice is associated with decreased production of IL-17A, IL-22, and IL-23A by intestinal immune cells.

We first began our investigation of gut alterations by analyzing the production of cytokines in the lamina propria (LP) of ileum from female NOD mice at pre-diabetic stage (8-10 weeks) and at diabetes onset. A significant decrease in transcripts for //-77a, 11-22 and 11-23a was observed in diabetic compared to younger pre-diabetic NOD mice (data not shown). To confirm this decrease at the protein level, flow cytometry analyses of LP cells were performed. Intracellular labeling of IL-17A and IL-22 cytokines of hematopoietic cells (CD45⁺), TCR-b- cells and TCR-b lymphoid cells also revealed a significant decrease in the frequency of IL- 17A and IL-22-producing cells in diabetic mice (data not shown). Similar reductions were observed in absolute cell numbers (data not shown).

Since the Retinoic-acid-receptor-related Orphan nuclear Receptor gamma (RORyt) is a key transcription factor controlling IL-17A [28] and IL-22 production [27], we used a RORyt-GFP reporter NOD mouse line that we had generated to evaluate RORyt cellular expression [24] At the diabetic stage, an overall decrease of RORyt-GFP expression was observed in CD45⁺, TCRb⁺, and TCRb cells (data not shown). Moreover, we observed the same decrease in CD4 T, invariant Natural Killer T (iNKT), MAIT, gdT, and innate lymphoid cells (ILCs) (data not shown). These data show that T1D development is associated with a general defect in IL-17A and IL-22 production by gut mucosa immune cells.

T1D development is associated with alteration of gut mucosa functions and decreased segmented filamentous bacteria abundance.

The fucosyltransferase 2 (FUT2) enzyme expressed by gut epithelial cells (EC) is representative of a protective mechanism promoting the maintenance of the commensal gut microbiota, protecting the host against opportunistic pathogens [29] Since IL-22 can induce Fut2 expression by ileum ECs, we analyzed Fut2 expression in the ileum of female NOD mice at different disease stages [29,30] mRNA expression of Fut2 in ileum of diabetic mice was significantly lower than in younger prediabetic mice (data not shown). In addition, analysis of a(l,2)-fucose levels on EC surface by the binding of fluorescent Ulex europaeus agglutinin-1 (UEA-1) lectin showed a significant decrease in the frequency and intensity of EC fucosylation in diabetic mice (data not shown). Since SFB are intimately attached to ECs in ileum and induce IL-17A and IL-22 production by gut immune cells [31-36], we investigated whether ECs alterations were associated with a loss of SFB. The relative abundance of SFB in ileum was significantly reduced in diabetic mice compared to prediabetic mice (Figure 1A). The decrease of SFB relative quantities in diabetic mice was also observed in feces (Figure IB). Analysis revealed that SFB levels progressively decreased from 4-week up to 13-week old female NOD mice free from diabetes (Figure 1C). Progressive loss of SFB was similar between age-matched female C57BL/6J and female NOD mice that remained diabetes-free until up to 13 weeks of age. However, SFB loss was significantly increased as soon as 9 weeks of age in female NOD mice that became subsequently diabetic at 13 weeks of age (Figure ID). Of note, SFB relative quantity stabilized at diabetes onset. The diminished amount of SFB in ileum positively correlated with the decreased expression of Fut2 mRNA in diabetic mice (data not shown).

After oral gavage, blood FITC-dextran concentration was significantly higher in diabetic NOD mice than in 10-week old NOD mice (data not shown). We also observed a reduction of claudin-4 ( Cldn4 ), tight junction protein 1 ( Tjpl ), occludin ( Ocln ) and mucin-2 (Muc2) mRNA in sorted ECadhesion molecule (EpCam)⁺ ECs of ileum from diabetic compared to younger mice (data not shown).

We next analyzed whether loss of gut integrity in diabetic mice was associated with bacterial translocation. Increased detection of 16S DNA was observed in liver of diabetic NOD mice compared to prediabetic NOD and C57BL/6J mice (data not shown). There was also an increase of CFU of anaerobic and aerobic bacteria in liver from 17-week old and diabetic mice compared to younger NOD and control C57BL/6J mice (data not shown). Bacteria analysis highlighted that bacteria of anaerobic and aerobic culture from the liver are mostly Lactobacillus murinus (data not shown). Together these data show that progression toward diabetes in NOD mice is associated with several gut mucosa alterations and a dramatic decrease of SFB.

Gut mucosa alterations in streptozotocin-induced diabetes in NOD and C57BL/6J mice We next investigated whether the observed gut mucosa alterations and SFB loss were restricted to T1D development in NOD mice or could be observed in other T1D mouse models. A commonly used mouse model of T1D is based on treatment with multiple low doses of streptozotocin (STZ) [37] (data not shown). NOD males became diabetic shortly after STZ treatment and harbored the same mucosa alterations as spontaneous diabetic NOD females: notably reduced //-77a, 11-22 and Il-23a mRNA expression in LP cells of ileum (data not shown), a significant decrease of UEA-1⁺ ECs frequencies (figure 3C) as well as a reduction of Fut2 mRNA transcription (data not shown) and diminished levels of SFB in feces associated with treatment duration (data not shown). To exclude the possibility of NOD mouse-specific defects we also analyzed C57BL/6J mice treated with STZ (data not shown). As in diabetic NOD mice, diabetes in STZ-treated C57BL/6J mice was associated with reduced transcripts for II- 17 a, 11-22 , and Il-23a in LP cells of ileum (data not shown), decreased frequencies of UEA- 1⁺ ileum ECs, as well as a slight decrease of mean fluorescence intensity (MFI) of UEA-1 (p=0.0519) (data not shown). We observed decreased levels of SFB in ileum and feces as in NOD mice (data not shown). Therefore, these gut microbiota and mucosa alterations seem to represent common features associated with T1D onset.

Hyperglycemia does not replicate intestinal alterations observed in T1D

Next, we investigated whether these alterations observed in diabetic mice could occur upon induction of hyperglycemia in absence of autoimmune/inflammatory reaction. To this end, C57BL/6J mice were grafted with a pump allowing continuous diffusion of S961, an insulin receptor antagonist [38] (data not shown). In contrast to what was observed in prediabetic NOD and STZ-treated mice, hyperglycemia in S961 -treated mice induced a significant increase of SFB abundance in feces and ileum (data not shown). Moreover, there was no difference in UEA-1 expression on intestinal ECs and no modification of //-77a and 11-22 mRNA expression in cells from ileum LP (data not shown). However, hyperglycemia induced a significant increase of Il-23a mRNA expression in LP cells from ileum (data not shown). These data show that hyperglycemia alone does not induce SFB, IL-17A, IL-22 and IL-23A loss that we observed in NOD and STZ-treated mice.

Diabetes induced by diabetogenic T-cells alters intestinal homeostasis and SFB level.

We transferred i. v. diabetogenic T cells (BDC2.5) in Trac NOD recipient mice. This model allows synchronization of T1D induction and monitoring of diabetogenic CD4⁺ T cells migration within different tissues. Onset of diabetes in recipient mice (data not shown) was associated with the same gut alterations as observed in NOD mice such as a significant decrease of SFB in ileum and feces (data not shown), an enhanced gut permeability evaluated by FITC- dextran in blood after oral gavage (data not shown), and a decrease in mRNA transcripts coding for 7/-/7a, 11-22 and 11-23a in cells from ileum (data not shown). Increased gut permeability in diabetic recipient mice was associated with a significant decrease of Tjpl and Muc2 mRNA levels and a slight reduction of Cldn4 (p=0.07) and Ocln (p=0.10) mRNA levels in intestinal epithelium cells (data not shown).

We next assessed whether diabetogenic BDC2.5 T cells could home into the ileum of recipient mice. Flow cytometry analysis showed presence of BDC2.5 T cells from day 2 to day 13 in the ileum, PLN and mesenteric lymph nodes (MLN) (data not shown). BDC2.5 T cell frequency in ileum was higher at day 13 compared to MLN and PLN (data not shown). Furthermore, an elevated frequency of BDC2.5 T cells in ileum produced IFN-g and TNF-a compared to MLN and PLN (data not shown). We also transferred BDC2.5 T cells in wild-type NOD recipient mice, in which they do not induce diabetes [39], allowing analysis of BDC2.5 T cell behavior without potential contribution of homeostatic proliferation that could occur in Trac ^A NOD recipient mice. Flow cytometry analysis confirmed the presence of BDC2.5 T cells at day 8 in ileum, MLN, PLN and pancreatic islets (data not shown). Increased frequency of BDC2.5 T cells in these organs resulted from their higher proliferation rate compared to host CD45.2 CD4⁺ T cells (data not shown). Moreover, BDC2.5 T cells produced high levels of IFN-g and TNFa in ileum, MLN and PLN compared to host CD45.2 CD4⁺ T cells, and the highest TNFa level in BDC2.5 T cells was observed in ileum even when compared to all organs, including pancreatic islets (data not shown). These data suggest that gut mucosa alterations in recipient mice are caused by diabetogenic T cell production of inflammatory cytokines in ileum.

Gut microbiota alteration in NOD mice matches the observations in BDC2.5 model.

As our data revealed the impact of gut inflammation on SFB levels, we next performed a more extensive analysis of gut microbiota alterations in mouse models of T1D versus our non- autoimmune hyperglycemic mouse model. 16S ribosomal DNA sequencing confirmed SFB reduction with T1D progression in NOD mice at different ages as well as in BDC2.5 T cell recipient mice (data not shown). 16S DNA sequencing also confirmed the increase of SFB in hyperglycemic S961 -treated mice (figure 6A). Principal Component Analysis (PCA) of 16S ribosomal DNA sequencing showed an unsupervised overview of gut microbiota modification in these mice (data not shown). In NOD mice there was a shift of the gut microbiome from 6/10-week old mice to diabetic mice with the PC2 (9.85%). In BDC2.5 T cell transfer experiments, two clusters separated control from BDC2.5 T cell-induced diabetic mice mostly by PC2 (20.23%) (data not shown). Lastly, in S961 experiments we observed two clusters that separated control from hyperglycemic mice mostly by PCI (34.05%) (data not shown).

We next explored more precisely gut microbiota modifications during T1D progression in NOD mice. 16S sequencing of fecal content from NOD mice from 6 weeks of age to diabetes onset showed a total of 24 phyla and genera modifications (data not shown). As previously shown, relative abundance of Bacteroidetes and Firmicutes were respectively decreased and increased in diabetic NOD mice as compared to pre-diabetic mice [40] We further observed other modifications during T1D progression in NOD mice and several were common with modifications occurring in BDC2.5 T cell recipient mice that became diabetic. A significant increase of Coprococcus , Dorea, Oscillospira , Thiobacter was associated with disease progression (data not shown). However, other gut microbiota modifications were similar during the development of diabetes in NOD mice and induction of hyperglycemia in S961- treated mice. In both mouse models, there was a significant decrease of Bacteroidetes phylum and an increase of Bacteroides genus. Conversely, Parabacteroides was reduced in hyperglycemic mice compared to diabetic NOD mice (data not shown). We did not observe any similarities in microbiome alteration between BDC2.5 T cells transferred mice and hyperglycemic S961 -treated mice (data not shown). Some modifications only occurred in S961 -treated mice such as an increase of Enterococcus, Erwinia, and Klebsiella and a decrease of Allobaculum genera (data not shown). While Coprococcus increased in diabetic NOD mice and BDC2.5 T cell transferred mice, this genus was rather reduced (p=0.0642) in hyperglycemic S961 -treated mice compared to their controls (data not shown). Similarly, the increase of Dorea and Oscillospira genera in both diabetic NOD mice and BDC2.5 T cell transferred mice was not observed in hyperglycemic S961 -treated mice. Overall, these data highlight several gut microbiota modifications occurring in two mouse models of autoimmune diabetes but not upon induction of hyperglycemia.

Anti-TNFa treatment prevents gut mucosa alterations, restores SFB levels, and prevents T1D onset.

Since transferred BDC2.5 diabetogenic T cells migrated and expanded to the ileum where they produced a large amount of TNFa, we assessed the impact of Remicade^®, an anti-TNFa antibody (Infliximab), on gut inflammation and diabetes development. Anti-TNFa antibody treatment had a major impact on gut mucosa as it increased II- 17 a and 11-22 mRNA level as well as Foxp3 transcript abundance in LP cells of ileum from treated mice compared to isotype- injected control mice (Figure 2A). Ileal EC function was improved by anti-TNFa treatment as UEA-1 expression on intestinal ECs increased (Figure 2B). In addition, transcript levels coding for Cldn4 , Ocln were significantly elevated, with a slight increase of Muc2 mRNA level (p=0.07), and gut permeability was significantly decreased (Figure 2C,D) This was associated with an increase of SFB frequencies and relative quantity in fecal content, although it remained similar in ileum (Figure 2E). Changes were also observed in other bacterial genera with an increase mAF12, Parracoccus, Acinobacter, and a decrease in Clostridium , Coprobacillus , and Streptococcus (data not shown). Of note, macrophages, which are able to produce TNFa in the LP, were not affected by anti-TNFa treatment (data not shown). We next analyzed dendritic cells (DCs) since we had previously shown that loss of gut integrity in NOD mice could lead to bacterial components translocation and increased CDl lc⁺CDl lb⁺CD103⁺ DCs frequencies and activation [24] Indeed, anti-TNFa antibodies induced a significant reduction of this DCs subset in ileum of BCD2.5 T cell-transferred mice, however, such reduction was not observed in PLN (data not shown). Moreover, anti-TNFa treatment also decreased ileum CDl lc⁺CDl lb⁺CD103⁺ DCs activation as shown by their lower surface levels of MHC-II compared to non-treated control mice (data not shown). Interestingly anti-TNFa reduced the frequency and absolute numbers of BDC2.5 T cells in ileum but not in PLN (data not shown). This was associated with a significant increase of FOXP3⁺ BDC2.5 T cell frequency in ileum and not in PLN (data not shown). Further analysis of autoreactive T cells showed a significant reduction of their IFN-g production in both ileum and PLN from mice treated with anti-TNFa compared to control mice whereas TNFa production by BDC2.5 T cells remained unchanged (data not shown). Finally, the decreased IFN-g production by BDC2.5 T cells in anti-TNFa treated mice was associated with a lower incidence of T1D and less severe insulitis (Figure 2F). Altogether these data support again a key role for gut inflammation in promoting anti-islet T cell effector function leading to pancreatic infiltration and T1D onset. Reducing inflammation (by anti-TNFa treatment) helps correcting TID-associated SFB dysbiosis and mucosal dysfunctions (data not shown).

Discussion:

Our study brings new knowledge on the nature and the origin of gut mucosa and microbiota alterations associated with T1D development. Using several mouse models of T1D, we showed that with disease development i) gut immune cells produced lower levels of IL-17A, IL-22 and IL-23 A, ii) intestinal ECs displayed decreased expression markers of gut integrity (Claudin 4, Occludin, Tight junction protein 1, and Mucin 2), and decreased fucosylation levels and iii) gut microbiota changes were associated with reduced abundance of SFB in ileum. Moreover, our results revealed that these modifications were not observed upon metabolic induction of hyperglycemia. Several reports had described gut alterations in T1D, obesity, and T2D as well as after induction of hyperglycemia by insulin receptor blockade [12,13,41] While NOD mice develop gut alterations in several weeks, the other diabetic models (STZ multi -low-dose injections, S961 -treatment, and BDC2.5 T cell transfer) induced diabetes within a week. Therefore, chronicity of gut inflammation is not required for gut alterations observed in T1D. Modifications of gut microbiota composition were very similar between spontaneously diabetic NOD, and BDC2.5 T cells transferred Trac^ recipient mice in contrast to gut microbiota modification observed in metabolically induced hyperglycemic mice. Taken together, this suggests that targeting only hyperglycemia in T1D would not resolve mucosal dysfunctions whereas treating inflammation could restore intestinal homeostasis.

T1D is characterized by the development of autoimmune responses associated with inappropriate activation of immune cells that infiltrate the pancreas [1-3] We and others have described gut inflammation associated with T1D suggesting that gut inflammation could lead to decreased mucosal IL-17A, IL-22 and IL-23A production, EC defect and loss of ileum SFB [24,42] It was striking that BDC2.5 T cell frequency was higher in the gut mucosa than in MLN and PLN, and they produced the highest level of TNFa in the gut. TNFa production by low-proliferating BDC2.5 T cells in ileum is probably due to the pro-inflammatory environment rather than potential microbiota cross-reactivity. These results prompted us to assess the efficiency of anti-TNFa treatment, which is a common treatment in Crohn’s disease [43] This treatment had a major effect on the gut mucosa as it increased IL-22 and IL-17A production, fucosylation of ECs and SFB abundance. Moreover, lower DC activation and increased T regulatory cell frequency were observed in the ileum but not in PLN supporting a primary effect on the gut mucosa. Furthermore, it has been reported that gut IL-10⁺ T regulatory cells could migrate to PLN [44] Systemic anti-TNFa treatment does not exclude that anti-inflammatory mAb could directly act on pathogenic cells in PLN and pancreas. TNFa can exert an ambivalent role in the development of T1D in mouse models [45-48] and a previous report has shown that anti-TNFa treatment at the perinatal period in NOD mice prevents T1D onset [47] Of note, gut mucosa was not analyzed in this pioneer study. Interestingly, anti-TNFa treatment in a patient with Crohn’s disease and T1D not only improved intestinal pathology but also T1D [49] Our present data further highlights the relevance of controlling gut inflammatory status to dampen pathogenic anti -islet T cells in PLN, severe insulitis and T1D.

We showed for the first time that SFB levels in ileum and feces were decreased during the establishment of spontaneous diabetes in NOD mice, in T1D induced by STZ treatment in NOD and C57BL/6J mice as well as upon transfer of autoreactive BDC2.5 T cells. In contrast, metabolic induction of hyperglycemia enhanced SFB levels in ileum and feces and is reminiscent with SFB requiring high glucose levels to grow on ECs [50] Thus, low SFB level in T1D might be a consequence of local inflammation, despite increased glycemia. This finding is interesting in light to previous studies asking whether SFB could exert a protective role against T1D. Comparison of two NOD colonies from different breeding companies showed that the colony harboring SFB had a lower incidence of T1D than the other colony [42] In another study, germ-free NOD mice were colonized with SFB however incidence of T1D was only slightly decreased in recipient males, not females [51] Our study established a strong parallel between SFB abundance in ileum and intestinal IL-17A and IL-22 production. Both cytokines can be induced by SFB [32-36] and maintain gut homeostasis thereby preventing bacterial component translocation and inflammation. Several mechanisms could be at play. IL-22 can upregulate Fut2 expression and ECs fucosylation favoring the maintenance of commensal flora [29,30] IL-22 can also maintain gut integrity by promoting expression of tight junctions proteins and production of mucus preventing pathogenic bacteria invasiveness [52] IL-22 could also alleviate pancreatic b cell stress, preventing the generation of islet neoantigens playing a critical role in the autoimmune attack of b cells [52-54]

The role of SFB in the dampening of gut mucosa inflammation and diabetes development can also be associated with increased diabetes incidence after antibiotic treatment [55] Indeed, SFB is extremely sensitive to antibiotics [56] Another protective role of SFB could be related to their ability to prevent bacterial and viral infections. SFB can induce the production of IL-22 that controls C. rodentium infection [57], an intestinal pathogenic bacteria that is known to accelerate T1D development in NOD mice [8] Similarly, SFB prevents rotavirus infection in mice that might be involved in T1D development [56,58] Thus, our study provides new insights in the deleterious role of gut inflammation against protective commensal microbiota in the physiopathology of T1D.

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Throughout this application, various references describe the state of the art to which this invention pertains. The disclosures of these references are hereby incorporated by reference into the present disclosure.

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Claims

CLAIMS:

1. A method for treating, preventing, suppressing and/or delaying the onset, or reducing the risk of developing type 1 diabetes, or the symptoms associated with, or related to, type 1 diabetes, in a subject in need thereof comprising administering to the subject a therapeutically effective amount of a TNFa blocking agent.

2. The method of the claim 1 wherein the subject is a child.

3. The method of claim 1 wherein the subject is a pre-diabetic subject.

4. The method of claim 1 wherein the subject exhibits a dysbiosis.

5. The method of claim 4 wherein the dysbiosis includes progressive loss of Segmented Filamentous Bacteria B (SFB).

6. The method of claim 1 that comprises the steps of measuring the abundance of SFB in a fecal sample obtained from the subject.

7. The method of claim 1 that comprises the steps of i) determining the abundance of SFB in a fecal sample obtained from the subject, ii) comparing the abundance determined at step i) with a predetermined reference value and iii) administering to the subject a therapeutically effective amount of a TNFa blocking agent when the abundance is lower than the predetermined reference value.

8. The method of claim 1 wherein wherein the TNFa blocking agent is a soluble TNFa receptor or an antibody having specificity for TNFa or for TNFa receptor 1.

9. The method of claim 8 wherein the TNFa blocking agent is selected from the group consisting of Etanercept (Enbrel®), Infliximab (Remicade®), Adalimumab (Humira®), Certolizumab pegol (Cimzia®), and golimumab (Simponi®).

10. The method of claim 1 wherein the TNFa blocking agent is locally administered to the gastrointestinal tract of the subject.