WO2025168815A1 - Methods for the diagnosis, prognosis and the treatment of transplant rejection - Google Patents

Abstract

Allogeneic kidney transplantation is a common transplant procedure and an optimal form of therapy for individuals who reach end-stage renal disease, significantly improving their quality of life, as compared to dialysis and supportive care. Nonetheless, its success relies on lifelong immunosuppression (IS), which causes serious complications. Moreover, despite immunosuppression (IS), around 8% of renal transplants will be rejected due to T cell-mediated and/or antibody-mediated reactions towards donor-specific allo-antigens. Importantly, scarce kidney recipients achieve an immunosuppressive drug-free tolerance, suggesting the existence of active tolerance mechanisms. Biomarkers to predict rejection risks and identify patients in which tolerance mechanisms could allow IS weaning, as well as a non-invasive biomarker to diagnose a rejection event, are highly needed to improve patient's care. The inventors identify circulating CD73⁺ DP8α Tregs or the expansion of CD73⁺ DP8α Tregs after transplantation as a non-invasive biomarker to predict rejection risks from 3 months post-transplantation. These data advocate for the potential value of these cells to improve kidney grafted patients' care through IS minimization and/or tolerance-inducing therapies. Strikingly, these results were observed in two independent cohorts, at 1-year post-transplantation. The present invention relates to a method of determining in a subject whether a subject has or is at a risk of developing transplant rejection comprising the steps of: i) determining the frequency of CD73-expressing DP8α Tregs among any T cell subset in particular among total CD3⁺ T cells or among total CD4⁺ T cells or among total CD8⁺ T cells in a sample obtained from the subject after transplantation, ii) comparing the frequencies determined at step i) with a predetermined reference value wherein detecting differential between the frequency of CD73- expressing DP8α Tregs among any T cell subset in particular among total CD3⁺ T cells or among total CD4⁺ T cells or among total CD8⁺ T cells determined at step i) and the predetermined reference value is indicative of whether a subject has or is at a risk of developing a transplant rejection.

Description

_{METHODS FOR THE DIAGNOSIS, PROGNOSIS AND THE TREATMENT OF TRANSPLANT REJECTION} FIELD OF THE INVENTION: _{The invention relates to methods for the prediction and the treatment of transplant rejection.} BACKGROUND OF THE INVENTION: Allogeneic kidney transplantation is a common transplant procedure and an optimal form of therapy for individuals who reach end-stage renal disease, significantly improving their quality of life, as compared to dialysis and supportive care. The success of this therapy, especially in terms of short-term graft outcome, has considerably improved in the last decades due to the implementation of immunosuppressive strategies. Nonetheless, despite immunosuppression (IS), around 8% of renal transplants will be rejected due to T cell-mediated and/or antibody- mediated reactions towards donor-specific allo-antigens. Although T cell-mediated rejection occurs rapidly, often within 12 months, antibody-mediated rejections may develop any time after transplantation and remain the major cause for graft failure, leading to acute or chronic graft rejection events. So far, a clinically validated biomarker to predict immune-mediated _{rejection events after transplantation and a non-invasive biomarker to diagnose rejection are is} still missing, despite intensive investigations. IS leads to grave adverse events, including infections and cancers. Importantly, the observation that a fraction, albeit very small, of kidney transplant recipients display stable graft function after discontinuing IS (TOL patients) reveals the existence of a state of so-called operational tolerance (OT). The identification of mechanisms underlying OT and predictive markers represents a major challenge. Indeed, their identification would help select patients likely to benefit from IS adaptation/minimization and promote the development of innovative strategies _{to treat rejection or induce tolerance (Brouard, Am J Transplant 12, 3296–3307, 2012; Wekerle, Clin Exp Immunol 189, 133–134, 2017)} Recent studies and preclinical models revealed that the immunological outcome of allogeneic organ transplantation is influenced by the recipient’s gut microbiota composition (Winichakoon P Transplant Rev 202236:100668; Garcia-Martinez Y Biology 2023;12: 163; Ardalan, Biomed _{Pharmacother 90, 229–236, 2017) and by extracellular purine nucleotides, including adenosine} triphosphate (ATP) and adenosine, as modulators of ischemia‐reperfusion injury and post- _{transplantation outcome (Degauque N et al 2018, Front Immunol 9, article 1465; Dwyer K M, 2020, Nature Reviews Nephrology, 16, 520; Yeudall S Am J Transplant, 2020, 20, 633-640).} Moreover, numerous evidences support, at least in preclinical models, the contribution of Tregs _{(both Tr1 and Foxp3+) to long-term graft persistence (Fortunato 2021, Front Immunol, 12, article 641596; Hoogduijn, 2021, Transpl Int 34, 233–244; WU H, 2020, J Am Soc Nephrol} 31, 1445-1461; Que, 2022, Sci Adv 8: eabo4413; Braza 2015, J Am Soc Nephrol, 26, 1795- _{1805, Gupta P K Cellular and Molecular Immunology, 2019, 16, 324-333). The inventors therefore hypothesized that microbiota-induced DP8^ Tregs, whose suppressive activity} depends on their high expression of the CD39 and CD73 purinergic enzymes (Godefroy E, _{2018, Gastroenterol, 155, 1205-1217), could play a role in the induction of kidney graft} tolerance and thereby represent a novel much-needed prognostic biomarker. _{Microbiota-induced Tregs were identified in mice as IL-10-secreting FoxP3+ Tregs induced in the colonic mucosa by a panel of Clostridium bacteria (Atarashi K, 2011, Science). They were shown to be critical for local homeostasis, but also systemically (Hanna, 2023 Immunity, 56,1- 18; Al Nabhani Z 2019, Immunity 50, 113). The inventors then identified IL-10-secreting Tregs specific for the Clostridium Faecalibacterium prausnitzii (F. prausnitzii) in the human colon and blood Sarrabayrouse G, 2012, Plos Biol 12, e1001833; Godefroy E, 2018, Gastroenterol,} 155, 1205-1217). Despite their similar colonic origin and Clostridium specificity, F. prausnitzii-reactive human Tregs differ from mouse colon Tregs in their lack of constitutive FoxP3 expression, hence resembling Tr1 cells (Type 1 regulatory T cells). Importantly, F. prausnitzii-reactive Tregs, were shown to exhibit a highly reliable phenotype characterized by the co-expression of CD4, low levels of CD8^, CCR6 and CXCR6, allowing accurate studies _{of this subset in human blood and colon (Godefroy E, 2018, Gastroenterol, 155, 1205-1217). Moreover, the inventors established the dominant role of the purinergic enzymes CD39 and CD73 in their regulatory function in vitro (Godefroy E, 2018, Gastroenterol, 155, 1205-1217; Jotereau F, 2022, Front Immunol, 13, 1026994). Previously, the inventors also demonstrated that low levels of circulating DP8^ Tregs represented a reliable biomarker for IBD diagnosis (Godefroy E, 2018, Gastroenterol, 155, 1205-1217), which, together with the ability of these cells to prevent colitis in a mouse model (Touch S, 2022, JCI insight, 7, e154722), strongly} support their contribution to gut homeostasis. _{Here, the inventors addressed the potential role of DP8^ Tregs in kidney graft tolerance, taking} advantage of the large DIVAT biocollection (DIVAT: Données Informatiques Validées en Transplantation; French Research Ministry: RC12_0452, large agreement N° 13334, N° CNIL for the cohort: 891735; http//www.divat.fr/), comprising PBMCs prospectively collected before _{and at 3- and 12-month post-transplantation from all the patients undergoing a kidney transplantation in Nantes hospital since 2008 (n>500) and of another large cohort of PBMCs from kidney-grafted patients (ORLY-EST cohort) at 12-month post-transplantation.} SUMMARY OF THE INVENTION: _{The invention relates to methods for the prediction and the treatment of transplant rejection. In} particular, the present invention is defined by the claims. DETAILED DESCRIPTION OF THE INVENTION: Allogeneic kidney transplantation is a critical therapy for end-stage renal diseases. Nonetheless, its success relies on lifelong immunosuppression (IS), which may cause serious complications. Moreover, in about 8% patients, immune rejection remains an unpredictable cause of kidney graft failure. Importantly, scarce kidney recipients achieve an immunosuppressive drug-free tolerance, suggesting the existence of active tolerance mechanisms. Biomarkers to predict rejection risks and identify patients in which tolerance mechanisms could allow IS weaning are _{highly needed to improve patient's care. Here, using a large biocollection of PBMCs derived} from over 500 kidney transplant recipients, grafted between 2008 and 2021, we observed that graft tolerance (lack of any rejection event) was highly associated with an increased frequency _{among blood total T cells of DP8^ Tregs expressing CD73, occurring post-transplantation. This increase was not seen in the vast majority of patients who ended up undergoing a rejection event} later on. Importantly, careful biostatistical analyses established the potent prognostic value of such frequency, measured at three-month post-transplantation and before any rejection event if _{any, through unadjusted and multivariable cause-specific time-dependent Cox models and} leave-one-out bootstrap sampling. The AUCs obtained in the leave-one-out bootstrap samples were 0.89 (95% CI from 0.80 to 0.97). Choosing a threshold value of 0.053%, the frequency of _{circulating CD73+ DP8^ Tregs among total T cells allowed to discriminate patients who will undergo a rejection event within the 3-years post-sampling with a PPV of 80% and a NPV of 96%. Altogether these data identify the frequency of circulating CD73+ DP8^ Tregs, at three months post-transplantation as a non-invasive biomarker to predict rejection risks beyond, as well as strongly support a role of these cells in kidney graft tolerance. These data advocate for} the potential value of these cells to improve kidney grafted patients’ care through IS minimization and/or tolerance-inducing therapies. _{Main definitions of the invention: As used herein, the term “graft” or “transplant” have their general meaning in the art and refer} to a medical procedure in which an organ is removed from one body and placed in the body of a recipient, to replace a damaged or missing organ. Organs and/or tissues that are transplanted within the same person's body are called autografts. Transplants that are recently performed between two subjects of the same species are called allografts. Allografts can either be from a living or cadaveric source. _{As used herein, the term "transplant donor" or “graft donor” refers to a subject to whom an} organ, tissue or cell to be transplanted is harvested from. As used herein, the term "transplant recipient" refers to a subject who will receive a transplanted organ, tissue or cell. In the present application, the terms “recipient”, “transplant recipient”, “transplanted _{recipient”, “transplanted patient”, “graft recipient”, “grafted recipient” or “subject} recipient” are used interchangeably. In some embodiments a recipient according to the invention is a candidate recipient. As used, the term “kidney” has it general meaning in the art and refers toreddish-brown bean- shaped blood-filtering organs that are a multilobar multipapillary form of mammalian kidney, usually without signs of external lobulation. They are located on the left and right in the retroperitoneal space, and in adult humans are about 12 centimetres (4+1⁄2 inches) in length. They receive blood from the paired renal arteries; blood exits into the paired renal veins. Each _{kidney is attached to a ureter, a tube that carries excreted urine to the bladder. The kidney} participates in the control of the volume of various body fluids, fluid osmolality, acid–base balance, various electrolyte concentrations, and removal of toxins. Filtration occurs in the glomerulus: one-fifth of the blood volume that enters the kidneys is filtered. Examples of substances reabsorbed are solute-free water, sodium, bicarbonate, glucose, and amino acids. Examples of substances secreted are hydrogen, ammonium, potassium and uric acid. The nephron is the structural and functional unit of the kidney. Each adult human kidney contains around 1 million nephrons, while a mouse kidney contains only about 12,500 nephrons. The kidneys also carry out functions independent of the nephrons. For example, they convert a precursor of vitamin D to its active form, calcitriol; and synthesize the hormones erythropoietin and renin. _{As used herein, the terms “sample” or “biological sample” refer to any sample obtained from a subject, such as a skin tissue, a serum sample, a plasma sample, a urine sample, a blood} sample, a lymph sample, or a tissue biopsy. _{The term “blood sample” refers to a sample, which includes whole blood obtained from a subject. Before being used or analyzed, the blood sample may be submitted to at least one} treatment step, such as elutriation, adding an anticoagulant, for example adding EDTA, centrifugation, such as Ficoll gradient, dilution, heat or cold treatment, adding at least one _{reagent other than an anticoagulant and their combinations. Alternatively, the blood sample is} used directly, i.e., untreated. A blood sample may for example be total blood or a blood fraction. As used herein the term “Risk" in the context of the present invention, relates to the probability that an event will occur over a specific time period, as in the conversion to critical form of transplant rejection, and can mean a subject's "absolute" risk or "relative" risk. Absolute risk can be measured with reference to either actual observation post-measurement for the relevant time cohort, or with reference to index values developed from statistically valid historical cohorts that have been followed for the relevant time period. Relative risk refers to the ratio of absolute risks of a subject compared either to the absolute risks of low-risk cohorts or an average population risk, which can vary by how clinical risk factors are assessed. Odds ratios, the proportion of positive events to negative events for a given test result, are also commonly used _{(odds are according to the formula p/(l-p) where p is the probability of event and (1- p) is the} probability of no event) to no conversion. Alternative continuous measures, which may be assessed in the context of the present invention, include time to critical form of transplant _{rejection conversion risk reduction ratios.} "Risk evaluation," or "evaluation of risk" in the context of the present invention encompasses making a prediction of the probability, odds, or likelihood that an event or disease state may occur, the rate of occurrence of the event or conversion from one disease state to another, i.e., _{from a normal condition or asymptomatic form of transplant rejection or symptomatic form of transplant rejection to a critical form of transplant rejection condition or to one at risk of} developing a critical form of transplant rejection. Risk evaluation can also comprise prediction of future clinical parameters, traditional laboratory risk factor values, or other indices of critical form of transplant rejection, such as cellular population determination in peripheral tissues, in serum or other fluid, either in absolute or relative terms in reference to a previously measured population. The methods of the present invention may be used to make continuous or categorical measurements of the risk of conversion to critical form of transplant rejection, thus diagnosing and defining the risk spectrum of a category of subjects defined as being at risk for a critical form of transplant rejection. In the categorical scenario, the invention can be used to discriminate between normal and other subject cohorts at higher risk for critical form of transplant rejection. As used herein, the term "treatment" or "treat" refer to both prophylactic or preventive treatment as well as curative, improving the patient’s condition or disease modifying treatment, including treatment of patient at risk of contracting the disease or suspected to have contracted the disease as well as patients who are ill or have been diagnosed as suffering from a disease or medical condition, and includes suppression of clinical relapse. The treatment may be administered to a subject having a medical disorder or who ultimately may acquire the disorder, in order to prevent, cure, delay the onset of, reduce the severity of, or ameliorate one or more symptoms of a disorder or recurring disorder, or in order to prolong the survival of a subject beyond that expected in the absence of such treatment. By "therapeutic regimen" is meant the pattern of treatment of an illness, e.g., the pattern of dosing used during therapy. A therapeutic regimen may include an induction regimen and a maintenance regimen. The phrase "induction regimen" or "induction period" refers to a therapeutic regimen (or the portion of a therapeutic regimen) that is used for the initial treatment of a disease. The general goal of an induction regimen is to provide a high level of drug to a patient during the initial period of a treatment regimen. An induction regimen may employ (in part or in whole) a "loading regimen", which may include administering a greater dose of the drug than a physician would employ during a _{maintenance regimen, administering a drug more frequently than a physician would administer} the drug during a maintenance regimen, or both. The phrase "maintenance regimen" or "maintenance period" refers to a therapeutic regimen (or the portion of a therapeutic regimen) that is used for the maintenance of a patient during treatment of an illness, e.g., to keep the patient in remission for long periods of time (months or years). A maintenance regimen may employ continuous therapy (e.g., administering a drug at regular intervals, e.g., daily, weekly, monthly, yearly, etc.) or intermittent therapy (e.g., interrupted treatment, intermittent treatment, treatment at relapse, or treatment upon achievement of a particular predetermined criteria [e.g., disease manifestation, etc.]). _{As used herein, the term “preventing” intends characterizing a prophylactic method or process that is aimed at delaying or preventing the onset of a disorder or condition to which such term} applies. _{As used herein, the term "therapeutically effective amount" refers to an amount effective, at} dosages and for periods of time necessary, to achieve a desired therapeutic result. A therapeutically effective amount of drug may vary according to factors such as the disease state, age, sex, and weight of the individual, and the ability of drug to elicit a desired response in the individual. A therapeutically effective amount is also one in which any toxic or detrimental effects of the antibody or antibody portion are outweighed by the therapeutically beneficial effects. The efficient dosages and dosage regimens for drug depend on the disease or condition to be treated and may be determined by the persons skilled in the art. A physician having ordinary skill in the art may readily determine and prescribe the effective amount of the pharmaceutical composition required. For example, the physician could start doses of drug employed in the pharmaceutical composition at levels lower than that required in order to achieve the desired therapeutic effect and gradually increase the dosage until the desired effect is achieved. In general, a suitable dose of a composition of the present invention will be that amount of the compound which is the lowest dose effective to produce a therapeutic effect according to a particular dosage regimen. Such an effective dose will generally depend upon the factors described above. For example, a therapeutically effective amount for therapeutic use may be measured by its ability to stabilize the progression of disease. One of ordinary skill in the art would be able to determine such amounts based on such factors as the subject's size, the severity of the subject's symptoms, and the particular composition or route of administration selected. An exemplary, non-limiting range for a therapeutically effective amount of drug is about 0.1-100 mg/kg, such as about 0.1-50 mg/kg, for example about 0.1-20 mg/kg, such as about 0.1-10 mg/kg, for instance about 0.5, about such as 0.3, about 1, about 3 mg/kg, about 5 mg/kg or about 8 mg/kg. Administration may e.g., be intravenous, intramuscular, intraperitoneal, or subcutaneous, and for instance administered proximal to the site of the target. Dosage regimens in the above methods of treatment and uses are adjusted to provide the _{optimum desired response (e.g., a therapeutic response). For example, a single bolus may be} administered, several divided doses may be administered over time or the dose may be proportionally reduced or increased as indicated by the exigencies of the therapeutic situation. _{In some embodiments, the efficacy of the treatment is monitored during the therapy, e.g., at} predefined points in time. As non-limiting examples, treatment according to the present invention may be provided as a daily dosage of the agent of the present invention in an amount of about 0.1-100 mg/kg, such as 0.2, 0.5, 0.9, 1.0, 1.1, 1.5, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 40, 45, 50, 60, 70, 80, 90 or 100 mg/kg, per day, on at least one of days 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, _{19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, or 40, or} alternatively, at least one of weeks 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 or 20 after initiation of treatment, or any combination thereof, using single or divided doses every 24, 12, 8, 6, 4, or 2 hours, or any combination thereof. _{As used herein, the terms "Pharmaceutically" or "pharmaceutically acceptable" refer to} molecular entities and compositions that do not produce an adverse, allergic or other untoward reaction when administered to a mammal, especially a human, as appropriate. A pharmaceutically acceptable carrier or excipient refers to a non-toxic solid, semi-solid or liquid filler, diluent, encapsulating material or formulation auxiliary of any type. The pharmaceutical compositions of the present invention for oral, sublingual, subcutaneous, intramuscular, intravenous, transdermal, local or rectal administration, the active principle, alone or in combination with another active principle, can be administered in a unit administration form, as a mixture with conventional pharmaceutical supports, to animals and human beings. Suitable unit administration forms comprise oral-route forms such as tablets, gel capsules, powders, granules and oral suspensions or solutions, sublingual and buccal administration forms, aerosols, implants, subcutaneous, transdermal, topical, intraperitoneal, intramuscular, intravenous, subdermal, transdermal, intrathecal and intranasal administration forms and rectal administration forms. Typically, the pharmaceutical compositions contain vehicles which are pharmaceutically acceptable for a formulation capable of being injected. These may be in particular isotonic, sterile, saline solutions (monosodium or disodium phosphate, sodium, potassium, calcium or magnesium chloride and the like or mixtures of such salts), or dry, especially freeze-dried compositions which upon addition, depending on the case, of sterilized water or physiological saline, permit the constitution of injectable solutions. The pharmaceutical forms suitable for injectable use include sterile aqueous solutions or dispersions; formulations including sesame oil, peanut oil or aqueous propylene glycol; and sterile powders for the extemporaneous preparation of sterile injectable solutions or dispersions. In all cases, the form must be sterile and must be fluid to the extent that easy syringability exists. It must be stable under the conditions of manufacture and storage and must be preserved against the contaminating action of microorganisms, such as bacteria and fungi. Solutions comprising compounds of the invention as free base or pharmacologically acceptable salts can be prepared in water suitably mixed with a surfactant, such as hydroxypropylcellulose. Dispersions can also be prepared in glycerol, liquid polyethylene glycols, and mixtures thereof and in oils. Under ordinary conditions of storage and use, these preparations contain a preservative to prevent the growth of microorganisms. The polypeptide (or nucleic acid encoding thereof) can be formulated into a composition in a neutral or salt form. Pharmaceutically acceptable salts include the acid addition salts (formed with the free amino groups of the protein) and which are formed with inorganic acids such as, for example, hydrochloric or phosphoric acids, or such organic acids as acetic, oxalic, tartaric, mandelic, and the like. Salts formed with the free carboxyl groups can also be derived from inorganic bases such as, for example, sodium, potassium, ammonium, calcium, or ferric hydroxides, and such organic bases as isopropylamine, trimethylamine, histidine, procaine and the like. The carrier can also be a solvent or dispersion medium containing, for example, water, ethanol, polyol (for example, glycerol, propylene glycol, and liquid polyethylene glycol, and the like), suitable mixtures _{thereof, and vegetables oils. The proper fluidity can be maintained, for example, by the use of} a coating, such as lecithin, by the maintenance of the required particle size in the case of dispersion and by the use of surfactants. The prevention of the action of microorganisms can be brought about by various antibacterial and antifungal agents, for example, parabens, chlorobutanol, phenol, sorbic acid, thimerosal, and the like. In many cases, it will be preferable to include isotonic agents, for example, sugars or sodium chloride. Prolonged absorption of the injectable compositions can be brought about by the use in the compositions of agents delaying absorption, for example, aluminium monostearate and gelatin. Sterile injectable solutions are prepared by incorporating the active polypeptides in the required amount in the appropriate solvent with several of the other ingredients enumerated above, as required, followed by filtered sterilization. Generally, dispersions are prepared by incorporating the various sterilized active ingredients into a sterile vehicle which contains the basic dispersion medium and the required other ingredients from those enumerated above. In the case of sterile powders for the preparation of sterile injectable solutions, the preferred methods of preparation are vacuum- drying and freeze-drying techniques which yield a powder of the active ingredient plus any additional desired ingredient from a previously sterile-filtered solution thereof. Upon formulation, solutions will be administered in a manner compatible with the dosage formulation and in such amount as is therapeutically effective. The formulations are easily administered in a variety of dosage forms, such as the type of injectable solutions described above, but drug _{release capsules and the like can also be employed. For parenteral administration in an aqueous} solution, for example, the solution should be suitably buffered if necessary and the liquid diluent first rendered isotonic with sufficient saline or glucose. These particular aqueous solutions are especially suitable for intravenous, intramuscular, subcutaneous and intraperitoneal administration. In this connection, sterile aqueous media which can be employed will be known _{to those of skill in the art in light of the present disclosure. For example, one dosage could be} dissolved in 1 ml of isotonic NaCl solution and either added to 1000 ml of hypodermoclysis fluid or injected at the proposed site of infusion. Some variation in dosage will necessarily occur depending on the condition of the subject being treated. The person responsible for administration will, in any event, determine the appropriate dose for the individual subject. As used herein, the term “combination” is intended to refer to all forms of administration that provide a first drug together with a further (second, third…) drug. The drugs may be administered simultaneously, separately or sequentially and in any order. According to the invention, the drug is administered to the subject using any suitable method that enables the drug to reach the chondrocytes of the bone growth plate. In some embodiments, the drug administered to the subject systemically (i.e., via systemic administration). Thus, in some embodiments, the drug is administered to the subject such that it enters the circulatory system and is distributed throughout the body. In some embodiments, the drug is administered to the subject by local administration, for example by local administration to the growing bone. As used herein, the terms “combined treatment”, “combined therapy” or “therapy combination” refer to a treatment that uses more than one medication. The combined therapy may be dual therapy or bi-therapy. As used herein, the term “administration simultaneously” refers to administration of 2 active ingredients by the same route and at the same time or at substantially the same time. The term “administration separately” refers to an administration of 2 active ingredients at the same time or at substantially the same time by different routes. The term “administration sequentially” refers to an administration of 2 active ingredients at different times, the administration route being identical or different. As used herein, the term "Immunosuppressive agent" or “immunosuppressive drug” refers to a compound, composition or treatment that indirectly or directly inhibits or decreases a _{detrimental immune response and/or that decreases the side effects of other therapies.} Immunotherapy is thus a therapy that directly or indirectly stimulates or enhances the immune system's responses and/or lessens the side effects that may have been caused by other agents. Immunotherapy is also referred to in the art as immunologic therapy, biological therapy biological response modifier therapy and biotherapy. Examples of common _{immunosuppressive agents known in the art include, but are not limited to, cytokines, non-} cytokine adjuvants, glucocorticoids, cytostatics, monoclonal antibodies, tyrosine kinase _{inhibitor or drugs acting on immunophilins. Alternatively, the immunotherapeutic treatment} may consist of administering the subject with a number of immune cells (T cells, NK cells, _{dendritic cells, B cells…). Immunosuppressive agents can be non-specific, i.e., boost the regulatory arm of the immune system generally so that the human body can be protected against inflammation, or they can be specific, i.e., targeted to the cells that destroy the patient cells themselves. immunotherapy regimens may combine the use of non-specific and specific immunotherapeutic agents. Non-specific immunosuppressive agents are substances that stimulate or indirectly improve the regulatory arm of the immune system. Non-specific immunosuppressive agents have been used alone as a main therapy, as well as in addition to a} main therapy, in which case the non-specific immunotherapeutic agent functions as an adjuvant _{to enhance the effectiveness of other therapies. Non-specific immunosuppressive agents can} also function in this latter context to reduce the side effects of other therapies, for example, bone marrow suppression induced by certain chemotherapeutic agents. Non-specific _{immunosuppressive agents can act on key immune system cells and cause secondary responses, such as decreased production of cytokines and immunoglobulins. Alternatively, the agents can themselves comprise cytokines. Non-specific immunosuppressive agents are generally} classified as cytokines or non-cytokine adjuvants. Diagnostic and prognostic methods according to the invention: _{The present invention relates to a method of determining whether a subject has or is at a risk of developing a transplant rejection comprising the steps of: i) determining the frequency of CD73-expressing DP8α Tregs among any T cell subset in a sample obtained from the subject after transplantation ii) comparing the frequency determined at step i) with a predetermined} reference value wherein detecting differential between the frequency of CD73-expressing DP8α _{Tregs among any T cell subset determined at step i) and the predetermined reference value is indicative of whether a subject has or is at a risk of developing a transplant rejection. The present invention also relates to a method of determining whether a subject has or is at a} risk of developing a transplant rejection comprising the steps of: i) determining the frequency _{of CD73-expressing DP8α Tregs among total CD3+ T cells, or among total CD4+ T cells or among total CD8+ T cells in a sample obtained from the subject after transplantation ii) comparing these frequencies determined at step i) with a predetermined reference value wherein detecting differential between the frequency of CD73-expressing DP8α Tregs among total CD3+ T cells or among total CD4+ T cells or among total CD8+ T cells determined at step i)} and the predetermined reference value is indicative of whether a subject has or is at a risk of developing a transplant rejection. In one embodiment, the method according to the present invention comprises the step of _{comparing the frequency of CD73-expressing DP8α Tregs among any T cell subset after transplantation, to a control reference value wherein a low frequency of CD73-expressing DP8α Tregs among any T cell subset compared to said predetermined reference value is indicative of} whether a subject has or is at a risk of developing transplant rejection. In one embodiment, the method according to the present invention comprises the step of _{comparing frequencies of CD73-expressing DP8α Tregs among total CD3+ T cells or among total CD4+ T cells or among total CD8+ T cells after transplantation to a control reference value wherein a low frequency of CD73-expressing DP8α Tregs among total CD3+ T cells or among total CD4+ T cells or among total CD8+ T cells compared to said predetermined reference value is indicative of whether a subject has or is at a risk of developing transplant rejection.} In one embodiment, the method according to the present invention comprises the step of _{comparing the frequency of CD73-expressing DP8α Tregs among any T cell subset after transplantation, to a control reference value wherein a high frequency of CD73-expressing DP8α Tregs among any T cell subset compared to said predetermined reference value is indicative of whether a subject has or will develop a transplant tolerance or a significant} decrease in the risk of rejection. In one embodiment, the method according to the present invention comprises the step of _{comparing said frequencies of CD73-expressing DP8α Tregs among total CD3+ T cells or among total CD4+ T cells or among total CD8+ T cells after transplantation to a control reference value wherein a high frequency of CD73-expressing DP8α Tregs among total CD3+ T cells or among total CD4+ T cells or among total CD8+ T cells compared to said predetermined reference value is indicative of whether a subject has or will develop a transplant} tolerance or a significant decrease in the risk of rejection. Subject of the invention: _{As used herein, the terms “subject” or “patient” denote a mammal, such as a rodent, a feline,} a canine, and a primate. Particularly, the subject according to the invention is a Human. More _{particularly, the subject according to the invention has or is susceptible to a transplant rejection.} In some embodiments, the subject is a receiver person that is to say a person who is awaiting the receipt of, or is receiving medical care or was/is/will be the object of a medical procedure, _{or is monitored for the development of a disease. In some embodiments, the subject is a donor} person, that is to say a person who is giving or agreeing to give an organ or part of it to help someone else. In some embodiments, the subject is an adult (for example a subject above the age of 18). In some embodiments, the subject is a child (for example a subject below the age of 18). In some embodiments, the subject is an elderly human (for example a subject above the age of 60). In some embodiments, the subject is a male. In some embodiments, the subject is a female. _{In particular, the subject of the present invention includes a subject who cannot live without} immunosuppressive drug. _{In particular, the subject of the present invention was transplanted and did not receive an immunosuppressive drug or stopped immunosuppressive drug treatment. In particular, the subject of the present invention has been transplanted whatever his pre-transplant treatment or} post-transplant treatment. Biological sample: In some aspect, biological samples to be used in the methods according to the invention may _{be blood samples (e.g., whole blood sample or PBMC sample). A blood sample may be} obtained by methods known in the art including venipuncture or a finger stick. Serum and plasma samples may be obtained by centrifugation methods known in the art. The sample may be diluted with a suitable buffer before conducting the assay. As used herein, the term “PBMC” or “peripheral blood mononuclear cells” or “unfractionated PBMC”, as used herein, refers _{to whole PBMC, i.e., to a population of white blood cells having a round nucleus, which has} not been enriched for a given sub-population. Cord blood mononuclear cells are further included in this definition. Typically, the PBMC sample according to the invention has not been subjected to a selection step to contain only adherent PBMC (which consist essentially of >90% monocytes) or non-adherent PBMC (which contain T cells, B cells, natural killer (NK) cells, _{NKT cells and DC or DC precursors). A PBMC sample according to the invention therefore} contains lymphocytes (B cells, T cells, NK cells, NKT cells), monocytes, and precursors thereof. Typically, these cells can be extracted from whole blood using Ficoll, a hydrophilic _{polysaccharide that separates layers of blood according to cell densities, with the PBMC} forming a cell ring under a layer of plasma. Additionally, PBMC can be extracted from whole blood using a hypotonic lysis buffer which will preferentially lyse red blood cells. Such procedures are known to the expert in the art. Cell of the invention: _{As used herein, the term "CD73” (cluster of differentiation 73) also knows as 5’-nucleotidase (5’-NT) or ecto-5’-nucleotidase or CD73 refers to an enzyme that, in humans, is encoded by the NT5E gene. CD73 commonly serves to convert AMP into adenosine. Human CD73 has the} Uniprot sequence: P21589. _{As used herein, the term “White Blood Cells” (WBC) refers to leukocyte populations, are the cells of the immune system. All white blood cells are produced and derived from multipotent cells in the bone marrow known as hematopoietic stem cells. Leukocytes are found throughout the body, including the blood and lymphatic system. Typically, WBC or some cells among WBC can be extracted from whole blood by using i) immunomagnetic separation procedures, ii) Percoll or Ficoll density gradient centrifugation, iii) cell sorting using flow cytometer (FACS). Additionally, WBC can be extracted from whole blood using a hypotonic lysis buffer, which will preferentially lyse red blood cells. Such procedures are known to the expert in the} art. As used herein, the term “T cell” has its general meaning in the art and refers to a type of lymphocytes that play an important role in cell-mediated immunity and are distinguished from other lymphocytes, such as B cells, by the presence of a T-cell receptor (TCR) on the cell _{surface. In particular, T cells are characterised by the expression of CD3. In particular, T cells are characterised by the expression of CD4. In particular, T cells are characterised by the} expression of CD8. As used herein, the term “regulatory T cells” or “Tregs”, formerly known as suppressor T _{cells, refers to a subpopulation of T cells, which modulates the immune system, maintains tolerance to self-antigens or self-associated antigens (such as intestinal microbiota antigens), and prevents autoimmune diseases. These cells generally suppress or downregulate induction} and proliferation of effector T cells. As used herein, the term "CD3" refers to the protein complex associated with the T cell receptor _{and is composed of four distinct chains. In mammals, the complex contains a CD3^ chain, a CD3^ chain, and two CD3^ chains. These chains associate with the TCR and the ^-chain (zeta-} chain) to generate an activation signal in T lymphocytes. The TCR, ^-chain, and CD3 molecules together constitute the TCR complex. In particular, T cells are characterized by the expression _{of CD4 or CD8 and thus be classified as CD4+ T cells and CD8+ cells. CD3 is expressed on the} cell surface. _{As used herein, the term “CD4” has its general meaning in the art and refers to the T cell surface} glycoprotein CD4. CD4 is a co-receptor of the T cell receptor (TCR) and assists the latter in communicating with antigen-presenting cells. The TCR complex and CD4 each bind to distinct _{regions of antigen-presenting MHC II molecules. CD4 is expressed on the cell surface. As used herein, the term “CD8^” has its general meaning in the art and refers to the T cell surface glycoprotein CD8 alpha chain. In particular, CD8^ is a transmembrane glycoprotein} that when heterodimerized with the CD8beta chain serves as a co-receptor for the T cell receptor (TCR). As a single chain it was reported to be a ligand for CEACAM5. Like the TCR, CD8ab _{binds to a major histocompatibility complex (MHC) molecule, but specifically to class I MHC} proteins. _{As used herein, the term “CCR6” or “CCR6 protein” refers to “Chemokine receptor 6”, “CD196” or “cluster of differentiation 196” and means a CC chemokine receptor protein encoded by the CCR6 gene. CCR6 is expressed on the cell surface. As used herein, the term “CXCR6” or “CXCR6 protein”, refers to “C-X-C chemokine receptor type 6”, “CD186” or “cluster of differentiation 186”, it herein means a chemokine receptor that is encoded by the CXCR6 gene. CXCR6 is expressed on the cell surface.} As used herein, the terms “expressing (or +)” and “not expressing (or -)” are well known in the art and refer to the detection of the expression of the phenotypic marker of interest, in that the detection of the phenotypic marker corresponding to “+” is high, low or intermediate, also _{referred as phenotypic marker corresponding to ” is a null or with no detection of} the phenotypic marker. _{As used herein, the terms “DP8α Treg”, “DP8a Treg”, “DP8α cells”, “DP8α T regulatory} lymphocytes” “T regulatory lymphocytes with a _{CD3+/CD4+/CD8αLOW/CCR6+/CXCR6+ phenotype” and “T regulatory lymphocytes characterized by a CD3+/CD4+/CD8αLOW/CCR6+/CXCR6+ phenotype” are used interchangeably and refer to lymphocytes, which express and display at their surfaces ex vivo at least the cluster of differentiation molecules CD3, CD4, CCR6 and CXCR6 and the cluster of differentiation molecule CD8α at a level lower than that expressed by the classical CD8^^} T cell subset, and in the absence of expression of the CD8beta chain. _{As used herein, the terms “CD73 expressing DP8α Treg”, “CD73 expressing DP8a Treg”, “CD73 expressing DP8α cells”, “CD73 expressing DP8α T regulatory lymphocytes” “T} regulatory lymphocytes with a CD73+/CD3+/CD4+/CD8αLOW/CCR6+/CXCR6+ _{phenotype” and “T regulatory lymphocytes characterized by a CD73/CD3+/CD4+/CD8αLOW/CCR6+/CXCR6+ phenotype” are used interchangeably and} refer to lymphocytes, which express and display at their surfaces ex vivo at least the cluster of _{differentiation molecules CD73, CD3, CD4, CCR6 and CXCR6 and at a low level the cluster of differentiation molecule CD8α in the absence of the CD8beta molecule.} The cells of the present invention and used according to the method of the invention are cells expressing CD73, CD3, CD4, CD8α, CCR6 and CXCR6. _{As used, the term “CD8α LOW” refers to a level of CD8α expression on the cells of the invention measured by flow cytometry FACS or others methods which is inferior to the level expressed by the classical CD8^^ T cell subset, and in the absence of expression of the CD8beta} chain. As used herein, the term “population” refers to a population of cells, wherein the majority (e.g., at least about 50%, preferably at least about 60%, more preferably at least about 70%, and even more preferably at least about 80%) of the total number of cells have the specified _{characteristics of the cells of interest and express the markers of interest (e.g., a population of human DP8^ Treg cells comprises at least about 50%, preferably at least about 60%, more preferably at least about 70%, and even more preferably at least about 80% of cells, which have} the highly suppressive functions and express the particular markers of interest, such as CD3, CD4, CD8α, CCR6 or CXCR6). _{As used herein, the term “isolated” or “purified” with regard to a population of DP8α Treg refers to a cell population which either has no naturally-occurring counterpart or has been separated or purified from other components, including other cell types, which naturally} accompany it, e.g., in normal or diseased tissues such as colon tissue, lymphoid organs or body _{fluids such as blood. Typically, an isolated cell population is at least two-fold, four-fold, eight- fold, ten-fold, twenty-fold or more enriched for DP8^ Tregs when compared to the natural source from which the population was obtained. In an isolated population of DP8^ T regulatory lymphocytes, the number of DP8^ T regulatory lymphocytes represents at least 50%, 75%, 80%, 90%, 95% or, most particularly, at least 96%, 97%, 98% or 99% or 100% of the total cell} number of the population. _{Isolating DP8^ T regulatory lymphocytes (or a population of DP8^ T regulatory lymphocytes) can be performed by using selective expression of surface markers unique to these cells. In particular, DP8^ T regulatory lymphocytes may be sorted in a first time through positive selection of the cell surface protein CD4, the cell surface protein CD3 or the cell surface protein} CD8α. _{Methods for carrying out selection based on the presence or the absence of cell surface proteins are well-known to one skilled in the art. For instance, these cells may be isolated, i.e., purified, by immunologic selection using antibodies, which selectively bind to a selected cell surface} protein. _{Measure of the cells of the invention: As used herein, the term “frequency” refers to the frequency of CD73-expressing DP8α Tregs} among any T cells subset and in particular total CD3⁺ T cells, total CD4⁺ T cells or total CD8⁺ _{T cells. Typically, the frequency of CD73-expressing DP8α Tregs among any T cells subset and in particular total CD3+ T cells or total CD4+ T cells or total CD8+ T cells is highly variable,} mostly ranging from 0.005% to 0.1%. _{In some embodiment, the frequency of CD73-expressing DP8α Tregs is determined after} transplantation. As used herein, the term "expression frequency" may be determined by any technology known _{by a person skilled in the art. In some embodiments, the expression of the phenotypic marker} is assessed at the mRNA level. Methods for assessing the transcription level of a molecule are well known in the prior art. Examples of such methods include, but are not limited to, RT-PCR, RT-qPCR, Northern Blot, hybridization techniques such as, for example, in situ hybridization, use of microarrays, and combination thereof including but not limited to, hybridization of amplicons obtained by RT-PCR, sequencing such as, for example, next-generation DNA sequencing (NGS) or RNA-seq (also known as “Whole Transcriptome Shotgun Sequencing”) and the like. In some embodiments, the expression of the phenotypic marker is assessed at the protein level. Methods for determining a protein level in a sample are well-known in the art. Examples of such methods include, but are not limited to, immunohistochemistry, Multiplex methods (Luminex), western blot, enzyme-linked immunosorbent assay (ELISA), sandwich ELISA, fluorescent-linked immunosorbent assay (FLISA), enzyme immunoassay (EIA), radioimmunoassay (RIA), flow cytometry (FACS) and the like. _{In some embodiment, the sample of the present invention (i.e., blood sample) is analyzed by flow cytometry to determine the frequency of CD73-expressing DP8α Tregs after transplantation among any T cell subset, in particular among total CD3+ T cells or among total} CD4⁺ T cells or among total CD8⁺ T cells. _{In particular, the flow cytometry is done by staining PBMCs in which the number of T lymphocytes per volume of blood was quantified thanks to the use of so-called "TruCount" beads. After, knowing this number and the frequency of Tregs among the T cells, the number of DP8^ Tregs per volume of blood can be calculated. As used herein, the term "flow cytometry methods" refers to a technique for counting cells of} interest, by suspending them in a stream of fluid and passing them through an electronic _{detection apparatus. Flow cytometry methods allow simultaneous multiparametric analysis of} the physical and/or chemical parameters of up to thousands of particles per second, such as _{fluorescent parameters. Modern flow cytometry instruments usually have multiple lasers and fluorescence detectors. A common variation of flow cytometry techniques is to physically sort} particles based on their properties, so as to purify or detect populations of interest, using "fluorescence-activated cell sorting". _{As used herein, "fluorescence-activated cell sorting" (FACS) refers to a flow cytometric} method for sorting a heterogeneous mixture of cells from a biological sample into two or more containers, one cell at a time, based upon the specific light scattering and fluorescent characteristics of each cell and provides fast, objective and quantitative recording of fluorescent signals from individual cells as well as physical separation of cells of particular interest. _{Accordingly, FACS can be used with the methods described herein to isolate and detect the} subpopulation of DP8α Tregs. _{In some embodiments, the preferred agents are antibodies that specifically bind the cell-surface} markers, and can include polyclonal and monoclonal antibodies, and antigen-binding derivatives or fragments thereof. Well-known antigen binding fragments include, for example, single domain antibodies (dAbs; which consist essentially of single VL or VH antibody domains), Fv fragment, including single chain Fv fragment (scFv), Fab fragment, and F(ab')2 fragment. Methods for the construction of such antibody molecules are well known in the art. Accordingly, as used herein, the term "antibody" refers to an intact immunoglobulin or to a monoclonal or polyclonal antigen-binding fragment with the Fc (crystallizable fragment) region or FcRn binding fragment of the Fc region. Antigen-binding fragments may be produced by recombinant DNA techniques or by enzymatic or chemical cleavage of intact antibodies. "Antigen-binding fragments" include, inter alia, Fab, Fab', F(ab')2, Fv, dAb, and complementarity determining region (CDR) fragments, single -chain antibodies (scFv), single domain antibodies, chimeric antibodies, diabodies and polypeptides that contain at least a portion of an immunoglobulin that is sufficient to confer specific antigen binding to the polypeptide. The terms Fab, Fc, pFc', F(ab') 2 and Fv are employed with standard immunological meanings (Roitt, I. (1991) Essential Immunology, 7th Ed., (Blackwell Scientific Publications, Oxford)]. Such antibodies or antigen-binding fragments are available commercially from vendors such as R&D Systems, BD Biosciences, e-Biosciences, Proimmune and Miltenyi, or can be raised against these cell-surface markers by methods known to those skilled in the art. _{In some embodiments, an agent that specifically binds to a cell-surface marker, such as an antibody or antigen-binding fragment, is labelled with a tag to facilitate the isolation and detection of the cell populations of the invention.} As used herein, the terms "label" or "tag" refer to a composition capable of producing a detectable signal indicative of the presence of a target, such as, the presence of a specific cell- surface marker in a biological sample. Suitable labels include fluorescent molecules, radioisotopes, nucleotide chromophores, enzymes, substrates, chemiluminescent moieties, _{magnetic particles, bioluminescent moieties, and the like. As such, a label is any composition detectable by spectroscopic, photochemical, biochemical, immunochemical, electrical, optical or chemical means needed for the methods to isolate and detect the cell populations of the invention. Non-limiting examples of fluorescent labels or tags for labeling the agents such as} antibodies for use in the methods of invention include Hydroxycoumarin, Succinimidyl ester, Aminocoumarin, Succinimidyl ester, Methoxycoumarin, Succinimidyl ester, Cascade Blue, Hydrazide, Pacific Blue, Maleimide, Pacific Orange, Lucifer yellow, NBD, NBD-X, R-Phycoerythrin (PE), a PE-Cy5 conjugate (Cychrome, R670, Tri-Color, Quantum Red), a PE-Cy7 conjugate, Red 613, PE-Texas Red, PerCP, Peridinin chlorphyll protein, TruRed (PerCP-Cy5.5 conjugate), FluorX, Fluoresceinisothyocyanate (FITC), BODIPY-FL, TRITC, X-Rhodamine (XRITC), Lissamine Rhodamine B, Texas Red, Allophycocyanin (APC), an APC-Cy7 conjugate, Alexa Fluor 350, Alexa Fluor 405, Alexa Fluor 430, Alexa Fluor 488, Alexa Fluor 500, Alexa Fluor 514, Alexa Fluor 532, Alexa Fluor 546, Alexa Fluor 555, Alexa Fluor 568, Alexa Fluor 594, Alexa Fluor 610, Alexa Fluor 633, Alexa Fluor 647, Alexa Fluor 660, Alexa Fluor 680, Alexa Fluor 700, Alexa Fluor 750, Alexa Fluor 790, Cy2, Cy3, Cy3B, Cy3.5, Cy5, Cy5.5 or Cy7. _{In some embodiment, the DP8^ Tregs are specific for bacteria of the Faecalibacterium genus F. prausnitzii or F. duncaniae for example (also called F. prausnitzii-induced DP8^ Tregs), i.e., they express T cell receptors specific for antigens bacteria of the Faecalibacterium genus,} so that they react specifically to antigen-presenting cells loaded with bacteria of the _{Faecalibacterium genus. As used herein, the term Faecalibacterium genus” refers to a commensal bacteria of the human gut microbiota classified in the Firmicutes phylum, Clostridia class, Clostridiales order and} Clostridiaceae family. _{In one embodiment, the population of CD73 expressing cells may be detected by using labelled agent specifically binding CD73 (e.g., a labelled antibody specifically binding CD73). In one embodiment, the DP8^ Tregs are obtained 10 days post-transplantation, 1-month post- transplantation, 3 months post-transplantation, 1 year post-transplantation or 3 years post-} transplantation. Control reference values are easily determinable by the one skilled in the art, by using the same techniques as for determining the level of cell surface biomarker or cell death in blood samples previously collected from the patient under testing. A “reference value” can be 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. 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. Preferably, the person skilled in the art may compare frequency of _{CD73-expressing DP8α Tregs after transplantation among any T cell subset, in particular among total CD3+ T cells or among total CD4+ T cells or among total CD8+ T cells with a} defined threshold value. In one embodiment of the present invention, the threshold value is _{derived from the frequency of CD73-expressing DP8α Tregs after transplantation among any T cell subset, in particular among total CD3+ T cells or among total CD4+ T cells or among total CD8+ T cells (or ratio, or score) determined in a blood sample derived from one or more subjects} who are responders (to the method according to the invention). In one embodiment of the present invention, the threshold value may also be derived frequency of CD73-expressing DP8α _{Tregs after transplantation among any T cell subset in particular among total CD3+ T cells or among total CD4+ T cells or among total CD8+ T cells (or ratio, or score) determined in a blood} sample derived from one or more subjects who are non-responders. Furthermore, retrospective _{measurement of the frequency of CD73-expressing DP8α Tregs after transplantation among any T cell subset in particular among total CD3+ T cells or among total CD4+ T cells or among} total CD8⁺ T cells (or ratio, or scores) in properly banked historical subject samples may be used in establishing these threshold values. _{In some embodiment and for example, the inventors demonstrate that a threshold value of 0.053% of circulating CD73+ DP8^ Tregs among total CD3+ T cells or the equivalent percentage of these cells among any T cell subset in particular among total CD4+ T cells or} among total CD8⁺ T cells, at three months post-transplantation allowed to discriminate patients who will undergo a rejection event within the 3-year post-transplantation sampling with a _{negative predictive value (NPV) of 96% and a positive predictive value (PPV) of 80%. Thus, when the percentage of CD73+ DP8^ Tregs among total CD3+ T cells is higher than 0,053, the patient has no risk of transplant rejection and when the percentage of CD73+ DP8^^ Tregs among total CD3+ T cells is lower than 0,053, the patient is at a high risk of transplant} rejection. Reference values are easily determinable by the one skilled in the art, by using the same _{techniques as for determining the frequency of CD73-expressing DP8α Tregs after transplantation among any T cell subset in particular among total CD3+ T cells or among total} CD4⁺ T cells or among total CD8⁺ T cells in fluids samples previously collected from the patient _{under testing after transplantation.} In some embodiments, the predetermined reference value is determined by carrying out a method comprising the steps of a) providing a collection of blood samples from subject suffering from transplant rejection; _{b) providing, for each blood sample provided at step a), information relating to the actual} clinical outcome for the corresponding subject c) providing a serial of arbitrary quantification values; d_{) quantifying the frequency of CD73-expressing DP8α Tregs among any T cell subset in each blood sample contained in the collection provided at step a);} e) classifying said blood samples in two groups for one specific arbitrary quantification value provided at step c), respectively: (i) a first group comprising blood samples that exhibit a quantification value for level that is lower than the said arbitrary quantification value contained in the said serial of quantification values; (ii) a second group comprising blood samples that exhibit a quantification value for said level that is higher than the said arbitrary quantification value contained in the said serial of quantification values; whereby two groups of blood samples are obtained for the said specific quantification value, wherein the blood samples of each group are separately enumerated; f_{) calculating the statistical significance between (i) the quantification values obtained} at step e) and (ii) the actual clinical outcome of the subjects from which blood samples contained in the first and second groups defined at step f) derive; g) reiterating steps f) and g) until every arbitrary quantification value provided at step d) is tested; h_{) setting the said predetermined reference values as consisting of the arbitrary quantification value for which the highest statistical significance (most significant P-value} obtained with a log-rank test, significance when P<0.05) has been calculated at step g). In some embodiments, the predetermined reference value is determined by carrying out a method comprising the steps of a) providing a collection of blood samples from subject suffering from transplant rejection; b_{) providing, for each blood sample provided at step a), information relating to the actual} clinical outcome for the corresponding subject c) providing a serial of arbitrary quantification values; d_{) quantifying the frequency of CD73-expressing DP8α Tregs among total CD3+ T cells or among total CD4+ T cells or among total CD8+ T cells in each blood sample contained in the} collection provided at step a); e) classifying said blood samples in two groups for one specific arbitrary quantification value provided at step c), respectively: (i) a first group comprising blood samples that exhibit a quantification value for level that is lower than the said arbitrary quantification value contained in the said serial of quantification values; (ii) a second group comprising blood samples that exhibit a quantification value for said level that is higher than the said arbitrary quantification value contained in the said serial of quantification values; whereby two groups of blood samples are obtained for the said specific quantification value, wherein the blood samples of each group are separately enumerated; f_{) calculating the statistical significance between (i) the quantification values obtained} at step e) and (ii) the actual clinical outcome of the subjects from which blood samples contained in the first and second groups defined at step f) derive; g) reiterating steps f) and g) until every arbitrary quantification value provided at step d) is tested; h_{) setting the said predetermined reference values as consisting of the arbitrary quantification value for which the highest statistical significance (most significant P-value} obtained with a log-rank test, significance when P<0.05) has been calculated at step g). _{Transplanted organ:} In some embodiment, the transplant organ of the invention includes but not limited to kidney, heart, liver, lung, pancreas, intestine, stomach, thymus, uterus, testis, hand skin and tissues which include bones, tendons (both referred to as musculoskeletal grafts), corneae, skin, heart valves, nerves and veins. In a particular embodiment, the graft or transplanted organ of the present invention is the kidney. In a particular embodiment, the kidney suffers from chronic kidney disease. As used herein, the term “chronic kidney disease” or “CKD” has its general meaning in the art and refers to a progressive loss in renal function over a period of months or years. CKD is used to classify numerous conditions that affect the kidney, destruction of the renal parenchyma and the loss of functional nephrons or glomeruli. It should be further noted that CKD can result _{from different causes, but the final consequence remains renal fibrosis. CKD is defined as} kidney damage or glomerular filtration rate (GFR) <60 mL/min/1.73 m² for 3 months or more, irrespective of cause. Kidney damage in many kidney diseases can be ascertained by the presence of albuminuria, defined as albumin-to-creatinine ratio >30 mg/g in two of three spot urine specimens. GFR can be estimated from calibrated serum creatinine and estimating equations, such as the Modification of Diet in Renal Disease (MDRD) Study equation or the Cockcroft-Gault formula. Examples of etiology of CKD include, but are not limited to, cardiovascular diseases, hypertension, diabetes, glomerulonephritis, polycystic kidney diseases, and kidney graft rejection. In some , the patient in need thereof suffers from a disease selected from the group consisting of nephropathy (e.g. membranous nephropathy (MN), diabetic nephropathy and hypertensive nephropathy), glomerulonephritis (e.g. membranous glomerulonephritis and membranoproliferative glomerulonephritis (MPGN) such as rapidly progressive glomerulonephritis (RPGN)), interstitial nephritis, lupus nephritis, idiopathic nephrotic syndrome (INS) (e.g. minimal change nephrotic syndrome (MCNS) and focal segmental glomerulosclerosis (FSGS)), obstructive uropathy, polycystic kidney disease (e.g. Autosomal Dominant Polycystic Kidney Disease (ADPKD) and Autosomal Recessive Polycystic Kidney Disease (ARPKD)), cardiovascular diseases, hypertension, diabetes (e.g. diabetic nephropathy), and kidney graft rejection (e.g. acute and chronic kidney rejection). In some embodiment, the CKD is focal segmental glomerulosclerosis (FSGS). In some embodiment, the CKD is a progressive CKD after a partial nephrectomy. In some embodiment, the CKD is a diabetic kidney disease (DKD). Kidney disease severity is classified into five stages according to the level of GFR: - _{Stage 1 CKD: patients have a normal eGFR of 90 or greater and mild damage to their kidneys. The kidneys are still working well, with no symptoms. Patient can have other} signs of kidney damage, such as protein in their urine. - _{Stage 2 CKD: patients have an eGFR which has gone down to between 60 and 89, and they have mild damage to their kidneys. Most of the time, their kidneys are still working well, with no symptoms. Patient can have other signs of kidney damage, such as protein in their urine or physical damage. - Stage 3 CKD: patients have an eGFR between 30 and 59 and mild to moderate damage} to their kidneys. Their kidneys do not work as well as they should to filter waste and extra fluid out of their bloods. This waste can build up in their bodies and begin to cause other health problems, such as high blood pressure and bone disease. They may begin to have symptoms, such as feeling weak and tired or swelling in your hands or feet. With treatment and healthy life changes, many people in Stage 3 do not move to Stage 4 _{or Stage 5. Stage 3 CKD is split into two substages based on your eGFR: o Stage 3a: means the patient have an eFGR between 45 and 59 o Stage 3b: means the patients have an eGFR between 30 and 44 - Stage 4 CKD: the patients have an eGFR between 15 and 29 and moderate to severe damage to their kidneys. Their kidneys do not work as well as they should to filter waste} out of your blood. This waste can build up in your body and cause other health problems, s_{uch as high blood pressure, bone disease and heart disease. They will likely have symptoms such as swelling of their hands and feet and pain in their lower back. This is} the last stage before kidney failure. - _{Stage 5 CKD: patients have an eGFR less than 15 and severe damage to their kidneys. Their kidneys are getting very close to failure or have already failed (stopped working). Because their kidneys have stopped working to filter waste out of your blood, waste products build up in your body, which can make them very sick and cause other health problems. When the kidneys fail, treatment options to survive include dialysis or a} kidney transplant. In a particular embodiment, the graft or transplant organ of the present invention is the lung. In a particular embodiment, the organ of the present invention is in a first-stage organ disease _{or in an end-stage organ disease.} As used herein, the term "first-stage organ disease” refers to the first stage of the disease. The organ can always meet the needs of the organism. _{As used herein, the term "end-stage organ disease” refers to the stage where the organ can no longer support the body's needs. Death usually occurs within a few weeks. As used herein, the term "autograft” refer to the transplant of tissue to the same person.} Sometimes this is done with surplus tissue, tissue that can regenerate, or tissues more desperately needed elsewhere (examples include skin grafts, vein extraction for CABG, etc.). Sometimes an autograft is done to remove the tissue and then treat it or the person before returning it (examples include stem cell autograft and storing blood in advance of surgery). _{As used herein, the term "allograft” refers to a transplant of an organ or tissue between two} genetically non-identical members of the same species. Most human tissue and organ transplants are allografts. Due to the genetic difference between the organ and the recipient, the recipient's immune system will identify the organ as foreign and attempt to destroy it, causing transplant rejection. _{As used herein, the term "xenograft” refers to a transplant of organs or tissue from one species} to another. _{As used herein, the terms "transplantation tolerance” or “transplant tolerance” refer to a} state in which the host immune system can be reprogrammed and then guided to accept a _{transplant without the need of long-term immunosuppression, while maintains the response to} other antigens, and is widely regarded as a solution to those factors currently limiting long-term allograft survival in the clinic _{In some embodiment, the transplant organ of the present invention can be rejected.} Method of Treatment: _{The present invention relates to a method of treatment or a method of prevention of transplant rejection in a patient presenting a low frequency of CD73-expressing DP8α Tregs after transplantation among any T cell subset after transplantation comprising administering a therapeutically effective amount of an immunosuppressive agent or an infusion of DP8α Tregs} exhibiting appropriate features (e.g. infusion of CD73⁺ DP8α Tregs) or DP8α target antigens _{(F. prausnitzii-derived) in the form of peptides, proteins, or even} bacteria/probiotics/recombinant bacteria. _{The present invention also relates to a method of treatment or a method of prevention of transplant rejection in a patient presenting a low frequency of CD73-expressing DP8α Tregs after transplantation among total CD3+ T cells or among total CD4+ T cells or among total CD8+} T cells after transplantation comprising administering a therapeutically effective amount of an _{immunosuppressive agent or an infusion of DP8α Tregs exhibiting appropriate features (e.g. infusion of CD73+ DP8α Tregs) or DP8α target antigens (F. prausnitzii-derived) in the form of} peptides, proteins, or even bacteria/probiotics/recombinant bacteria. In a particular embodiment, the present invention relates to a method of treatment or a method of prevention of transplant rejection in a patient presenting a low frequency of CD73-expressing _{DP8α Tregs after transplantation among any T cell subset in particular among total CD3+ T cells or among total CD4+ T cells or among total CD8+ T cells, after a transplantation} comprising administering a therapeutically effective amount of an immunosuppressive agent or an infusion of DP8α Tregs exhibiting appropriate features (e.g. infusion of CD73⁺ DP8α Tregs) or DP8α target antigens (F. prausnitzii-derived) in the form of peptides, proteins, or even bacteria/probiotics/recombinant bacteria. _{The present invention also relates to a method for treating or preventing transplant rejection in} a subject in need thereof comprising a step of: i_{) Determining the frequency of CD73-expressing DP8α Tregs among any T cell subs in a blood sample obtained from the subject after} transplantation, i_{i) Comparing the frequency determined at step i) with a predetermined} reference value and i_{ii) Administering said subject with a therapeutically effective amount of an} immunosuppressive agent or an infusion of DP8α Tregs exhibiting a_{ppropriate features (e.g., infusion of CD73+ DP8α Tregs) or DP8α target antigens (F. prausnitzii-derived) in the form of peptides, proteins, or} even bacteria/probiotics when the frequency of CD73-expressing DP8α T_{regs among any T cell subset, is lower at step i) than the predetermined} reference value. _{The present invention also relates to a method for treating or preventing transplant rejection in} a subject in need thereof comprising a step of: i_{) Determining the frequency of CD73-expressing DP8α Tregs among total CD3+ T cells or among total CD4+ T cells or among total CD8+ T cells in a blood sample obtained from the subject after transplantation, ii) Comparing the frequencies determined at step i) with a predetermined} reference value and i_{ii) Administering said subject with a therapeutically effective amount of an} immunosuppressive agent or an infusion of DP8α Tregs exhibiting a_{ppropriate features (e.g., infusion of CD73+ DP8α Tregs) or DP8α target antigens (F. prausnitzii-derived) in the form of peptides, proteins, or} even bacteria/probiotics when the frequency of CD73-expressing DP8α T_{regs among total CD3+ T cells or among total CD4+ T cells or among} total CD8⁺ T cells is lower at step i) than the predetermined reference value. The present invention also relates to a method for treating or preventing transplant rejection in a subject in need thereof comprising a step of: i_{) Determining the frequency of CD73-expressing DP8α Tregs among any T cell} subset in a blood sample obtained from the subject before transplantation i_{i) Comparing the frequency determined before transplantation with the frequency} determined after transplantation i_{ii) Administering said subject with a therapeutically effective amount of an} immunosuppressive agent or an infusion of DP8α Tregs exhibiting appropriate f_{eatures (e.g., infusion of CD73+ DP8α Tregs) or DP8α target antigens (F.} prausnitzii-derived) in the form of peptides, proteins, or even bacteria/probiotics w_{herein the frequency of CD73-expressing DP8α Tregs among any T cell} subset, is similar after and before transplantation. The present invention also relates to a method for treating or preventing transplant rejection in a subject in need thereof comprising a step of: i_{) Determining the frequency of CD73-expressing DP8α Tregs among total CD3+ T cells or among total CD4+ T cells or among total CD8+ T cells in a blood} sample obtained from the subject before transplantation i_{i) Comparing the frequencies determined before transplantation with the frequency} determined after transplantation i_{ii) Administering said subject with a therapeutically effective amount of an} immunosuppressive agent or an infusion of DP8α Tregs exhibiting appropriate f_{eatures (e.g., infusion of CD73+ DP8α Tregs) or DP8α target antigens (F.} prausnitzii-derived) in the form of peptides, proteins, or even bacteria/probiotics w_{herein the frequency of CD73-expressing DP8α Tregs among total CD3+ T} cells or among total CD4⁺ T cells or among total CD8⁺ T cells is similar after and before transplantation. _{In some embodiments the infusion of in vitro-expanded CD73+ DP8^ Tregs exhibiting} appropriate features and possibly the infusion of their target antigens (F. prausnitzii-derived) in the form of peptides, proteins, or even bacteria/probiotics or prebiotics is used to restore a _{functional population of DP8^ Tregs. In some embodiments the infusion of DP8α target} antigens (F. prausnitzii-derived) in the form of peptides, proteins or even bacteria probiotics or _{prebiotics is used to restore a functional population of DP8^ Tregs, by stimulating the} expansion of pre-existing cells or by inducing their differentiation from naïve CD4 by antigenic stimulation (bacteria or its antigens) In some embodiments, the treatment consists of administering to the subject an immunosuppressive agent. _{In some embodiments, the treatment consists of administering to the subject interleukins. Interleukins contemplated by the present invention include IL-2, and IL-10. Examples of} commercially available recombinant interleukins include Proleukin® (IL-2; Chiron Corporation). _{In some embodiments, the treatment consists of administering to the subject Colony-stimulating} factors (CSFs). Colony-stimulating factors (CSFs) contemplated by the present invention include granulocyte colony stimulating factor (G-CSF or filgrastim), granulocyte-macrophage colony stimulating factor (GM-CSF or sargramostim) and erythropoietin (epoetin alfa, darbepoietin). Treatment with one or more growth factors can help to stimulate the generation of new blood cells in subjects undergoing traditional chemotherapy. Accordingly, treatment with CSFs can be helpful in decreasing the side effects associated with chemotherapy and can allow for higher doses of chemotherapeutic agents to be used. Various-recombinant colony stimulating factors are available commercially, for example, Neupogen® (G-CSF; Amgen), Neulasta (pelfilgrastim; Amgen), Leukine (GM-CSF; Berlex), Procrit (erythropoietin; Ortho Biotech), Epogen (erythropoietin; Amgen), Arnesp (erytropoietin). In addition to having specific or non-specific targets, immunotherapeutic agents can be active, i.e. stimulate the body's own immune response, or they can be passive, i.e. comprise immune system components that were generated external to the body. _{Passive or adoptive specific immunotherapy can involve the use of one or more monoclonal} antibodies that are specific for a particular antigen found on the surface of a cell or that are specific for a particular cell growth factor. Monoclonal antibodies may be used in the treatment of graft rejection. Example of monoclonal antibodies and related compounds suitable for use in methods of embodiments of the present invention include, but are not limited to, Alemtuzumab, _{Infliximab, Vedolizumab, Natalizumab, Brentuximab vedotin or Rituximab.} Passive or adoptive specific immunotherapy also involves the infusion of patient's derived T cells usually selected and expanded ex-vivo and genetically modified or not (CAR T cells ). _{In some embodiments, the treatment consists of administering to the subject glucocorticoids. As used herein, the term “glucocorticoids” are corticosteroids that bind to the glucocorticoid receptor. Examples of glucocorticoids and related compounds suitable for use in methods of embodiments of the present invention include, but are not limited to prednisone, methylprednisolone, dexamethasone, and hydrocortisone. In some embodiments, the treatment consists of administering to the subject drugs acting on immunophilins. Example of drugs acting on immunophilins and related compounds suitable for use in methods of embodiments of the present invention include but are not limited to} cyclosporine, tacrolimus, sirolimus or everolimus. _{In some embodiments, the treatment consists of administering to the subject cyclosporine. The term “cyclosporine” as used herein, refers to a calcineurin inhibitor, used as an} immunosuppressant medication. _{In some embodiments, the treatment consists of administering to the subject tacrolimus. The term “tacrolimus” as used herein, refers to a macrolide lactone produced by the bacterium Streptomyces tsukubaensis and that acts by inhibiting calcineurin. In some embodiments, the treatment consists of administering to the subject sirolimus. The term “sirolimus” as used herein, refers to a macrolide lactone, produced by the actinomycete bacterium Streptomyces hygroscopicus. Sirolimus is a mTOR inhibitor. In some embodiments, the treatment consists of administering to the subject everolimus. The term “everolimus” as used herein, refers to an analog of sirolimus and also is an mTOR} inhibitor. _{In some embodiments, the treatment consists of administering to the subject cytostatics.} As used herein, the term “cytostatics” refers to compounds that inhibit the cell division. Example of cytostatics and related compounds suitable for use in methods of embodiments of the present invention include but are not limited to alkylating agents, antimetabolites, _{methotrexate (folic acid, purine analogs, pyrimidine analogues…), azathioprine and} mercaptopurine, cytotoxic antibiotics (e.g; anthracyclines, mitomycin C, bleomycin, mithramycin, dactinomycin…). _{In some embodiments, the treatment consists of administering to the subject tyrosine kinase} inhibitor (TKI). As used herein, the term “tyrosine kinase inhibitor” refers to a pharmaceutical drug that inhibits tyrosine kinases. Tyrosine kinases are enzymes responsible for the activation of many _{proteins by signal transduction cascades. Example of tyrosine kinase inhibitor and related compounds suitable for use in methods of embodiments of the present invention include but are not limited to ruxolitinib or itacitinib.} As used herein the terms "administering" or "administration" refer to the act of injecting or otherwise physically delivering a substance as it exists outside the body (e.g. immunosuppressive agent or an infusion of DP8α Tregs exhibiting appropriate features or DP8α _{target antigens (F. prausnitzii-derived) in the form of peptides, proteins, or even bacteria/probiotics) into the subject, such as by mucosal, intradermal, intravenous,} subcutaneous, intramuscular delivery and/or any other method of physical delivery described herein or known in the art. When a disease, or a symptom thereof, is being treated, administration of the substance typically occurs after the onset of the disease or symptoms thereof. When a disease or symptoms thereof, are being prevented, administration of the substance typically occurs before the onset of the disease or symptoms thereof. The present invention also relates to a therapeutically effective amount of a combination an _{infusion of CD73+ DP8α Tregs exhibiting appropriate features and an immunosuppressive agent for use in the treatment of transplant rejection.} The present invention also relates to a therapeutically effective amount of a combination an infusion of DP8α target antigens (F. prausnitzii-derived) in the form of peptides, proteins or _{even bacteria probiotics or prebiotics and an immunosuppressive agent for use in the treatment of transplant rejection. In a particular embodiment, the invention relates to i) an infusion of DP8α Tregs exhibiting appropriate features and ii) an immunosuppressive agent for simultaneous, separate or} sequential use in the treatment of transplant rejection. _{In a particular embodiment, the invention relates to i) an infusion of DP8α target antigens (F.} prausnitzii-derived) in the form of peptides, proteins or even bacteria probiotics or prebiotics _{and ii) an immunosuppressive agent for simultaneous, separate or sequential use in the} treatment of transplant rejection. _{The infusion of DP8α Tregs exhibiting appropriate features as described above may be} combined with pharmaceutically acceptable excipients, and optionally sustained-release matrices, such as biodegradable polymers, to form pharmaceutical compositions. Infused cells could be genetically modified anti-donor antigens CAR DP8α TREGS. In a particular embodiment, the invention relates to i) an infusion of CD73⁺ DP8α Tregs _{exhibiting appropriate features and ii) an immunosuppressive agent for simultaneous, separate or sequential use in the treatment of transplant rejection. In a particular embodiment, the invention relates to i) an infusion of CD73+ DP8α target} antigens (F. prausnitzii-derived) in the form of peptides, proteins or even bacteria probiotics or _{prebiotics and ii) an immunosuppressive agent for simultaneous, separate or sequential use in the treatment of transplant rejection. The infusion of CD73+ DP8α Tregs exhibiting appropriate features as described above may be} combined with pharmaceutically acceptable excipients, and optionally sustained-release matrices, such as biodegradable polymers, to form pharmaceutical compositions. Infused cells could be genetically modified anti-donor antigens CAR CD73⁺ DP8α Tregs. Kit: A further object of the invention relates to kit comprising means for performing the methods of the present invention. Typically, the kit comprises means for detection of the presence or absence of the phenotypic markers of interest. _{In some embodiments, the present invention relates to a kit for diagnosing, prognosing and/or} predicting the risk of developing transplant rejection wherein said kit comprises means for _{determining the number and/or concentration and/or proportion and/or frequency of CD73- expressing DP8α Tregs among any T cell subset in particular among total CD3+ T cells or among total CD4+ T cells or among total CD8+ T cells after transplantation.} In some embodiments, said means are antibodies as described above. In some embodiments, _{the kit comprises an antibody specific for CD73. Typically, the kit described above will also comprise one or more other containers, containing} for example, wash reagents, and/or other reagents capable of quantitatively detecting the presence of bound antibodies. The kit also contains agents suitable for performing intracellular flow cytometry such as agents for permeabilization and fixation of cells. Typically, compartmentalised kit includes any kit in which reagents are contained in separate containers, and may include small glass containers, plastic containers or strips of plastic or paper. Such containers may allow the efficient transfer of reagents from one compartment to another compartment whilst avoiding cross-contamination of the samples and reagents, and the addition of agents or solutions of each container from one compartment to another in a quantitative fashion. Such kits may also include a container which will accept the sample, a container which contains the antibody(s) used in the assay, containers which contain wash reagents (such as phosphate buffered saline, Tris-buffers, and like), and containers which contain the detection reagent. In some embodiment, the present invention relates to a kit for assessing after transplantation _{whether the frequency of circulating CD73+ DP8α Tregs might allow to identify patients who might tolerate immunosuppression (IS) reduction.} 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. Frequency, among blood T cells, of DP8^ Tregs and fractions of these cells expressing CD39 or CD73 in kidney-transplanted patients rejection-free at 3-month post- transplantation. PBMCs from kidney-grafted patients (DIVAT cohort) still rejection-free at 3 months post-transplantation were assessed for DP8^ Treg frequency among total CD3+ T cells (A) and for expression by these cells of CD39 (B) or CD73 (C). Three groups of patients were} tested: STA/MIS patients (under full or minimized immunosuppression, respectively) who _{never had an identified rejection episode and patients who experienced, later on, acute or} chronic rejection events. Healthy donors (HD) are also represented as a reference. One-way ANOVA tests were used. All statistically significative p values (<.05) are shown. _{Figure 2. Frequency, among blood T cells, of DP8^ Tregs and fractions of these cells} expressing CD39 and CD73 in rejection free-patients at 1-year post-transplantation. _{PBMCs from kidney-grafted patients (DIVAT cohort) still rejection-free at one-year post-} transplantation. were assessed for DP8a Treg frequency among total CD3⁺ T cells (A) and for _{expression by these cells of CD39 (B) or CD73 (C). Three groups of patients were tested: STA/MIS patients who never had an identified rejection episode and patients who experienced acute or chronic rejection events later on. Healthy donors (HD) are also represented as a} reference. One-way ANOVA tests were used. All statistically significative p values (<.05) are shown. _{Figure 3. Frequency of circulating CD39-expressing and CD73-expressing DP8^ Tregs in rejection-free patients who will or will not undergo a rejection event. PBMCs from kidney- grafted patients (DIVAT cohort) were assessed for CD39+ DP8^ Treg frequency (A), and for CD73+ DP8^ Treg frequency (B), among total CD3+ T cells at either 3- or 12-month post- transplantation. Three groups of patients were tested: STA/MIS patients (STA) as well as acute} rejection (AR) and chronic rejection (CR) patients. Healthy donors (HD) are also represented as a reference. One-way ANOVA tests were used. All statistically significative p values (<.05) are shown. _{Figure 4. The higher frequency of CD73-expressing DP8^ Tregs observed at 3 months} post-transplantation in rejection-free patients who will not have a rejection event, as _{compared to those who will have, is not observed before transplantation and thus results from an expansion/generation of these cells after transplantation. A) PBMCs from kidney- grafted patients (DIVAT cohort) were assessed for CD73+ DP8^ Treg frequency among total CD3+ T cells before transplantation (“pre”) or at 3 months post-transplantation (“post”). B) PBMCs from kidney grafted patients (DIVAT cohort) were assessed for CD73+ DP8^ Treg} frequency among total CD3⁺ T cells individually both before transplantation (“pre”) and at 3 months post-transplantation (“post”). One-way ANOVA tests were used. All statistically _{significative p values (< .05) are shown. Three groups of patients were tested: STA/MIS patients (STA) as well as acute rejection (AR) and chronic rejection (CR) patients (A), or both rejection} types together (B). Healthy donors (HD) are also represented as a reference. One-way ANOVA _{tests were used. All statistically significative p values (< .05) are shown. Figure 5. A High Frequency of circulating CD73+ DP8^ Tregs among T cell subsets characterizes rejection-free patients who will not reject their graft later on. A) PBMCs} from 507 rejection-free kidney-grafted patients (DIVAT cohort) were assessed for CD73⁺ _{DP8^ Treg frequency among total CD3+ T cells at 3 months post-transplantation. Healthy} donors (HD, n=53) are also represented as a reference. One-way ANOVA tests were used. All _{statistically significative p values (< .05) are shown. B-C) Frequencies of CD73+ DP8^ Treg among T cell subsets in kidney grafted patients according to rejection status: among CD4+ T cells (B), among CD8+ T cells (C). D) Receiver operating characteristic (ROC) curves to evaluate the capacity of the biomarker CD73+ DP8^ Tregs frequency among blood T cells and} the two other scores to discriminate between patients who will present at least one rejection episode in the 3 years post-sample and the others. Figure 6. CD73⁺ DP8α Tregs are increased at 1-year post-transplantation in patients who _{will not reject. PBMCs from kidney-grafted patients (ORLY-EST cohort) at 1-year post- transplantation were assessed for CD73+ DP8α Treg frequency among total CD3+ T cells at day} 0 just before transplantation (pre-Tx) and at 1-year post-transplantation (post-Tx). Of note, no patients had yet an identified rejection episode at the 1-year time point. Pre-transplantation, we assessed 99 patients who will not reject and 34 patients who will reject after 1 year. Post- _{transplantation, we assessed 193 patients who will not reject and 36 patients who will reject} after 1 year. Healthy volunteers (HV) are also represented as a reference (n=53). One-way ANOVA tests were used. All statistically significative p values (<.05) are shown. _{Figure 7. Detection of CD73-expressing DP8α Tregs at 3-months post transplantation in} kidney graft biopsies from patients who remained rejection free onwards. A-B. These cells were identified by immunofluorescence multiplexing at the protein level:. CD8^⁺/CD4⁺/CD73⁺ _{cells are shown by the white arrow.} EXAMPLE: Material & Methods Patient population and sample collection PBMCs from the DIVAT cohort (Données Informatiques Validées en Transplantation; French Research Ministry) of kidney-grafted patients were obtained from the CRB (Biological resource _{center for biobanking), CHU Nantes, F-44093, France (BRIF:BB-0033-00040). Clinical data} used were recipient characteristics: age, gender, transplantation rank, the initial renal disease (possibly recurrent or not), the history of neoplasia. Donor features were age, gender and the donor type (living or deceased). Baseline transplantation parameters were the number of HLA- A-B-DR and DQ incompatibilities, anti-class I and II immunization, donor-specific antibodies (DSA) and induction therapy. Parameters collected at 3-month post-transplantation were the creatinine and the maintenance immunosuppressive treatment. The follow-up and the collection of data stopped upon return to dialysis or death. Follow-ups allowed for rejection episodes and de novo DSA detection. Renal allograft biopsies were performed as a DIVAT protocol biopsy at 3 and 12 months and /or during the diagnostic workup for allograft dysfunction or proteinuria. All patients provided informed consent to follow the DIVAT protocol. The study received approval from the Ethics committee of Nantes Hospital. Biostatistics Statistical analyses were performed by an independent biostatistical center, LabCom RISCA. To study the confounder-adjusted association between the biomarker, composed of CD73+ DP8a Treg frequency among circulating T cells, clinical data including recipient characteristics at 3-month post-transplantation and donor characteristics before transplantation were extracted from the French DIVAT cohort. All analyses were performed in complete case. Patients excluded for some analyses because of missing data were compared to the studied patients using Chi-square or Fisher exact tests for categorical variables and using Student t-tests for _{continuous variables. All analyses were performed with R 3.2.1 (R Development Core Team.} R: A Language and Environment for Statistical Computing [Internet]. Computing RF for S, editor. Vienna, Austria; 2010. Available from: http://www.R-project.org/). _{The characteristics of the 507 kidney transplant recipients included in the biostatistical analysis} are shown in Table I. The median time of follow-up for the 507 included recipients was 5.7 years (range from 0.1 to 16.6 years). During the follow-up 41 rejection episodes, 53 return to dialysis and 54 deaths with functioning graft were observed in the whole sample. The _{cumulative incidence rates of first rejection episode at 3- and 8-years post-sample were 7.7%} (95% CI from 5.3% to 10.1%) and 9.0% (95% CI from 6.3% to 11.6%), respectively. _{Cumulative incidence rates of the return to dialysis at 3- and 8-years post-sample were 4.4%} (95% CI from 2.6% to 6.3%) and 16.9% (95% CI from 11.4% to 22.0%), respectively. _{Rejection episodes were recorded during follow-up. Patient's follow-up and the collection of data stopped upon return to dialysis or death. End of follow-up without previous rejection} episode were right-censored. The outcome was the rejection free survival defined by the time between the 3-month sample and the first rejection episode (acute or chronic). The cumulative incidence curves of the outcomes were obtained by the Kaplan-Meier estimator (Kaplan EL, _{Meier P. 1958, Journal of the American Statistical Association 53:457–81). Multivariable} cause-specific Cox models were used to estimate the relationship between the biomarker and the outcomes by taking into account potential confounding factors (Cox D. 1972, Journal of _{the Royal Statistical Society B(24), 187–220). The hazard proportionality assumption was} tested from the Schoenfeld residuals (Schoenfeld D, 1982, Biometrika, 69:239–41). If this _{assumption did not hold, two different periods were considered. For baseline continuous} covariates, the log-linearity assumption has been checked in univariate analysis if the Bayesian Information Criterion was not reduced using natural spline transformation compared to the inclusion of the covariate in its natural scale. In case of violation, variables were transformed _{or categorized. For this reason, we studied the log transformation of the CD73+ DP8^ Treg} biomarker. We choose 3 years post-sample as the prognostic time from the cumulative incidence curve of the rejection outcome. From the linear predictors of the previous multivariable Cox models, we obtained prognostic scores including clinical variables and biomarkers. We estimated the corresponding time-dependent receiver operating characteristic (ROC) curves and the _{corresponding area under the curve (AUC) (Blanche P et al.2013, Biom J, 55, 687–704) to} evaluate the discriminative capacities of the biomarker enriched with clinical variables. Finally, we estimated the time-dependent ROC curves of the cause-specific multivariable Cox model including only clinical variables to evaluate the increase of the prognostic capacities due to biomarkers compared with clinical variables only. We calculated the area under the curve and used generalized estimating equations to re-estimate the sensitivity and specificity at the selected cutoff point after adjustment for the lack of independence resulting from the inclusion of multiple clinical data from the majority of patients. Forty-four patients had to be removed from the adjusted analysis because of missing data on the covariates retained for this analysis. To address potential model overfitting and evaluate the risk score model’s internal validity, we _{applied the leave-one-out bootstrap technique (Efron B, 1983, Journal of the American Statistical Association 78:316–31; Jiang W, Simon R. A. 2007, Stat Med, 26, 5320–34). This procedure generates a total of B bootstrap samples. We chose B=1000 based on previous} literature. The multivariable Cox models are fitted on each bootstrap samples to obtain the predictive scores. Based on these scores the AUCs can be calculated using the patients not included in the bootstrap sample. In this way, the method avoids testing the predictive score on the patients used for the construction of the score. Flow Cytometry Upon thawing, PBMCs were stained for 45min at 4°C in PBS/0.1%BSA with the following antibodies: anti-CD3 (clone UCHT1, Becton-Dickinson), anti-CD4 (clone 13B8.2, Beckman- Coulter), anti-CD8a (clone RPA-T8, Becton-Dickinson), anti-CCR6 (clone G034E3, Biolegend), anti-CXCR6 (clone K041E5, Biolegend), anti-CD39 (clone A1, Biolegend), anti- CD73 (clone AD2, Biolegend). Samples were run using an LSR II flow cytometer and analyzed using FlowJo and Diva softwares. Kidney biopsies Precisely, 4 µm-thick histological sections from paraffin-embedded kidney biopsies have been bought from our local anatomo-pathology department in the university hospital of Nantes _{(Service d'Anatomie et Cytologie Pathologiques, CHU de Nantes). Half of the biopsies came} from patients who rejected their graft and the other half came from stable rejection-free patients. All slides are from biopsies performed at approximatively 3 months post-transplantation. Samples were fixed in Carnoy when sampling was carried out before 2019 or in alcohol formalin acetic acid (AFA). Immunofluorescence _{Lymphocytes co-expressing CD4, CD8α and CD73 were stained to detect CD73+ DP8α Tregs.} After blocking with Animal Free Blocker (SP-5030-250 Vector Labs) for 30 min, sections were incubated at room temperature for 60 min with primary antibodies against human CD4 (Clone _{N4UG0, Invitrogen, 10 µg/ml) hCD8α (Clone, C8/144B, Dako, 30 µg/ml) and hCD73 (clone} EPR6114, Abcam, 4 µg/ml). After Sections were then incubated with secondary antibodies for _{45 min at room temperature : goat anti-Mouse IgG2b AF568 (A-21144, Life Tech), goat anti-} Mouse IgG1 AF488 (A21121, Life Tech) and goat anti-Rabbit IgG Alexa Fluor 647 (A-21246, _{Life Tech) for respectively, CD4, CD8α and CD73 staining. Sections were slightly} counterstained 3 min with the Invitrogen NucBlue Live ReadyProbes (Hoechst 33342), and mounted with Prolong Gold Antifade Reagent (Life Techologies). Microscopy and image analysis Image acquisition was performed using the Zeiss Cell Discoverer 7 microscopy workstation, _{where samples were acquired as whole sections. Analysis of the multiplexing images has been} achieved using QuPath open-source software (Bankhead et al. 2017), and in particular cell _{segmentation have been carried out using the Stardist module (Pécot et al. 2022) . The} expression of mutiplexing markers by these cells was analyzed using steps involving artificial intelligence. A non-parametric analysis has been performed using the Cytomap software to detect different clusters within the cell population. Statistical Analysis Statistical analyses were performed using GraphPad Prism version 9.5 using mainly Mann- Whitney (for single comparisons) or one-way ANOVA tests (for multiple comparisons), as indicated in the figure legend. p<0.05 was considered statistically significant. Results _{The frequency of circulating DP8^ Tregs and their regulatory potential differ between} patients who will and will not undergo rejection events later on _{We first asked whether frequencies of DP8^ Tregs and their regulatory potential (fractions of} these cells expressing the purinergic enzymes CD39 or CD73 used as a proxy), measured after transplantation, differed between patients as a function of the immunological outcome, i.e., _{occurrence of a rejection event or not. To this end, we screened PBMCs collected at 3-months} or at one-year post-transplantation, from patients who remained rejection-free at these time- points. Some patients did not reject ever since and were under either conventional or minimized IS regimen (STA and MIS respectively). Other patients experienced acute or chronic rejection _{events (AR and CR, respectively) despite conventional IS. At both 3- (Figures 1A-1C) and 12- month (Figures 2A-2C) post-transplantation, the frequency of DP8^ Tregs among total T cells} and their expression of CD39 and CD73, were higher in STA and MIS patients, as compared to patients who experienced acute or chronic rejection events later on. _{Importantly, other circulating T cell subsets measured alongside: CD8+, CD4+ and DP8^ T cells} lacking CCR6 and CXCR6 co-expression, showed no significant alteration associated with _{immune graft outcome (Data not shown). Therefore, DP8^ Tregs are specifically increased in} MIS/STA patients, as compared to rejection patients or healthy individuals, as well as fractions of these cells expressing the purinergic enzymes involved in their regulatory activity (Godefroy _{E, Gastroenterol, 2018; 155:1205-1217). The frequency of CD73-expressing DP8^ Tregs highly differs between patients who will and} will not undergo rejection events later on. Data shown above were then analyzed by a model of multivariate logistic regression to assess the association of the three variables under study with the rejection outcome. Results revealed that CD39 and CD73 variables were highly correlated together as well as with the immune _{outcome. On the other hand, the frequency of DP8^ Tregs, despite a lower correlation with} CD39 and CD73 expression, provided highly complementary information to these variables _{regarding rejection prediction (Data not shown). Accordingly, the frequencies of DP8^ Tregs} expressing CD39 or CD73 were measured and appeared strongly associated with the _{immunological outcome (Figures 3A-3B). This association was stronger for CD73- than for} CD39-expressing Tregs. We then therefore investigated whether elevated levels of circulating _{CD73-expressing DP8^ Tregs could provide a prognostic information in kidney grafted} patients. _{Elevated frequencies of circulating CD73+ DP8^ Tregs in STA/MIS patients result from their} expansion upon transplantation. _{We first asked whether the elevated frequencies of CD73+ DP8^ Tregs observed at 3- and 12-} month post-transplantation in rejection-free patients either already existed before transplantation or was induced upon transplantation. To do so, the frequency of circulating _{CD73+ DP8^ Tregs among total T cells was also assessed before transplantation in STA/MIS, AR and CR patients. Before transplantation, the frequencies of CD73+ DP8^ Tregs were similar in the 3 patients' groups as well as in HD (Figure 4A). The elevated frequency CD73+ DP8^} Tregs in STA patients was only observed after transplantation, suggesting that graft tolerance was associated with an amplification of these cells post-transplantation. We furthermore aimed at evaluating this amplification in paired PBMC samples collected before and at 3-month post-transplantation. As expected, the frequency of CD73-expressing _{DP8^ Tregs increased during this period in all but three STA patients (Figure 4B), whereas} this frequency either decreased or remained unaffected during the same period in most patients diagnosed later on with rejection. As a consequence, the frequency of CD73-expressing DP8^ _{Tregs among total CD3+ T cells (Figure 5A), among total CD4+ T cells (Figure 5B) or among total CD8+ T cells (Figure 5C) was clearly higher at 3-months post-transplantation, as compared to before transplantation suggesting that expansion after transplantation could serve} as a non-invasive biomarker to predict the risk of kidney graft rejection. _{CD73+ DP8^ Treg frequency: a biomarker to predict kidney graft outcome at 3-month post-} transplantation _{To formally address this question, we measured CD73+ DP8^ Tregs among circulating T cells} in all available DIVAT PBMC samples from rejection-free kidney-grafted patients, collected at a median time of 90 days (range 61 to 140 days) after the transplantation (n=507) (Figure 5A). A biostatistical analysis was then launched to assess the association between the frequency of _{DP8^ Tregs expressing CD73 among circulating T cells and the first rejection episode, through} unadjusted and multivariable cause-specific time-dependent Cox models. The characteristics of the 507 kidney transplant recipients included are shown in Table I. The median follow-up time of the 507 included recipients was 5.7 years, (ranging from 0.1 to 16.6 years). During follow- up, 41 rejection episodes, 53 return to dialysis and 54 deaths with functioning graft were _{observed. The cumulative incidence rates of first rejection episode at 3- and 8-years post-sample} were 7.7% (95% CI from 5.3% to 10.1%) and 9.0% (95% CI from 6.3% to 11.6%), respectively. _{Cumulative incidence rates of the return to dialysis at 3- and 8-years post-sample were 4.4%} (95% CI from 2.6% to 6.3%) and 16.9% (95% CI from 11.4% to 22.0%) respectively. Tables II and III present the results of the unadjusted and multivariable Cox models studying the association between the biomarker and the rejection episode. The unadjusted HR associated with the log transformation of the biomarker was 0.26 (95% CI: 0.21; 0.32). The confounder- adjusted Hazard Ratio (HR), representing the increase in the instantaneous hazard, for the patient with the higher biomarker was 0.21 (95% CI: 0.15; 0.29). Then, the ability of the biomarker to discriminate between patients who will make the rejection event and those who will not in the 3-years post-sampling was assessed through time-dependent receiver operating characteristic (ROC curves) and the corresponding area under the curve _{(AUC). Figure 5D presents the time-dependent ROC curves on the whole sample associated} with the biomarker score alone (Table II), the score including the biomarker enriched with clinical variables (Table III) and also a score including only the clinical variables. The biomarker alone presented an AUC under the ROC curve equal to 0.89, the complete score an AUC equal to 0.91 and the score with the clinical variable only and AUC of 0.72. As we could _{not apply the model to an internal validation cohort because of the limited number of rejections in the available cohort we evaluated the risk score model's internal validity using the leave-} One-out bootstrap technique generating a total of 1000 bootstrap samples. The average AUCs obtained in the leave-one-out bootstrap samples were 0.89 (95% CI from 0.80 to 0.97) for the biomarker alone, 0.80 (95% CI from 0.62 to 0.94) for the complete score (including the biomarker and the clinical variables) and 0.54 (95% CI from 0.39 to 0.67) for the score including only the clinical variables. The difference between the AUC associated to the complete score and the AUC associated to the clinical score was estimated at 0.25 (95% CI from 0.12 to 0.41). Therefore, in our cohort of transplant recipients, patients with a higher frequency of CD73⁺ _{DP8^ Tregs at 3 months post-transplantation had a significant decrease in the risk of rejection} episode (HR = 0.21, 95% CI from 0.15 to 0.29). In terms of discriminatory capacities, both the biomarker alone and the complete score were associated to good performances to discriminate patients with rejection episode in the 3 years post-sampling. In particular, the biomarker alone presented an AUC under the ROC curve equal to 0.89 (95% CI from 0.80 to 0.97). The complete score was not associated to better performances than the biomarker alone especially on the leave-one-out bootstrap accounting for potential overfitting. The clinical score performs worse. At the optimal threshold of 0.053 % the biomarker had a negative predictive value (NPV) of 96% and a positive predictive value (PPV) of 80%. _{We also investigated an association between CD73+ DP8^ Treg frequency and non-immune} patient's outcomes: death with a functional graft or return to dialysis without immune rejection. _{Distribution of CD73+ DP8^ Tregs in these patients was similar to that observed in patients who did not suffer a rejection event and thus differed from that observed in patients who did reject} the graft (Data not shown). These data establish a clear association and predictive value of a lack of post-transplantation _{expansion of CD73+ DP8^ Treg in the blood of kidney-transplanted patients with immune-} mediated transplant rejection both acute and chronic rejection, but not with other non-immune _{mediated outcomes. Altogether these data reveal that CD73+ DP8^ Treg expansion after} transplantation is involved in rejection prevention together with IS and hence suggest a role of these cells in graft tolerance.

_{Table I. Descriptive table of studied patients versus those excluded because of missing data} on the covariates retained for adjusted analysis (p-values are obtained using Chi-square test or Fisher exact test ( ) for categorical variables and using Student t-test for continuous variables).

Table II. Results of the unadjusted cause-specific time-dependent Cox models studying the risk of a first rejection episode after 3-month post-transplantation (n=507, with 41 events observed during the follow-up). Table III. Results of the multivariable cause-specific Cox model studying the risk of a first rejection episode after 3-month post-transplantation (n=463 with 39 events observed during the follow-up, 44 recipients were removed because of missing data). The heightened CD73⁺ DP8a Treg frequency post-transplantation in patients who will not reject was validated in an additional cohort (ORLY-Est) To validate the increased CD73⁺ DP8α Treg frequency observed post-transplantation in patients from the DIVAT cohort who did not reject their graft, but not in those who did, we identically screened, both pre- and 1-year post-transplantation, the PBMC from an independent cohort of kidney-transplanted patients, named ORLY-Est. Strikingly, at 1-year post-transplantation, the _{mean frequency of CD73+ DP8α Treg was significantly higher in patients who did not reject} (n=193), as compared to patients who did (n=36): 0.065% and 0.035% of total CD3⁺ T cells, respectively (p<0.0012) (Figure 6). Moreover, such a difference was not observed before transplantation and therefore resulted, as in the DIVAT cohort, from an expansion/generation of these cells after transplantation in patients who will not reject, as supported by their significantly heightened mean frequency after transplantation (0.044% to 0.065 % of total CD3⁺ T cells, p=0.0009) (Figure 6). Therefore, results from the DIVAT cohort were confirmed with _{the ORLY-Est validation cohort, further demonstrating that CD73+ DP8α Treg frequency} represent a reliable biomarker for kidney graft rejection. _{CD73+ DP8^ Tregs colonize kidney transplants} Results in animal models reported the accumulation of Treg cells in tolerant allografts (Lee I, 2005, J Exp Med, 201, 1037-1044; Graca L, 2002, J Exp Med,195, 1641-6). Therefore, we _{assessed the presence of CD73+ DP8^ Tregs on histological sections of kidney graft biopsies from both STA and rejection patients, using immunofluorescence, and multiplexing at the protein level (Figures 7A and 7B), to detect lymphocytes co-expressing the CD4 molecule, the CD8^ molecule at a low level and/or not the CD73 molecule. Among the lymphoid infiltrate, systematically abundant in biopsies from patients undergoing a rejection event, we detected the presence of double-positive CD4+/CD8^^^lymphocytes but most of these lacked CD73 expression (Data not shown). In contrast, biopsy sections from STA patients revealed a significant presence of DP8^ cells expressing CD73 despite, as expected, the small size of the} lymphoid infiltrate present in these samples. These data demonstrate the presence of a _{significant proportion among T cells of CD73+ DP8^ Tregs in stably grafted kidney at 3-months} post-transplantation. Discussion: This is the first study addressing a role of gut microbiota-induced Tregs in allograft tolerance. Immune tolerance to transplanted kidney remains a hot research issue, in part warranted by the _{existence of rare cases of operational tolerance among grafted patients and by the need to} identify efficient prognostic and diagnostic biomarkers of rejection to improve patients’ care. _{Strikingly, we showed that a clear and sustainable expansion of circulating DP8^ Tregs expressing CD73 takes place after transplantation, as detected at 3 months post-transplantation,} but also at 12-months post-transplantation in rejection-free patients who did not undergo a _{rejection event onwards. Remarkably such an expansion was not observed in the majority of patients who developed a rejection event (acute or chronic) later on, or when present remained} limited. Importantly, through a rigorous biostatistical analysis of the association between the _{frequency of CD73+ DP8^ Treg among total blood T cells and rejection occurring in patients} treated by an allogeneic kidney graft in Nantes hospital between 2008 and 2021 (n=507), we demonstrated that a cut-off frequency of 0.053% of these cells at 3 months post-transplantation allowed to discriminate between patients who will and those who will not undergo rejection, with a PPV of 80% and a NPV of 96%. _{Therefore, provided that these results will be validated with an independent cohort, the expansion and frequency of circulating DP8^ Tregs post transplantation represent efficient biomarkers to predict the rejection risk in kidney grafted patients. Moreover, low frequencies of DP8^ Treg (below 0.53 % of T cells) at 3 months post-transplantation being associated with a 80% risk of rejection, the frequency of these cells also represent a non-invasive biomarker to} help rejection diagnosis, which relies so far essentially on biopsy analysis by _{anatomopathologists. Importantly, measurement of CD73-expressing DP8^ Tregs in blood is both non-invasive and very low-cost, which would permit its routine handling by most transplantation centers to improve patients care. Importantly, the high correlation observed here between the expansion of CD73+ DP8^ Tregs in blood and a lack of rejection strongly suggested that DP8^ Tregs, based on their high regulatory potential, might be not only a biomarker but also active players in the prevention of} rejection. The presence of these cells in graft biopsies from stably grafted patients and their lack _{thereof in biopsies from kidney grafts undergoing rejection strongly supports this hypothesis. Moreover, also supporting a role of CD73+ DP8^ Tregs in allogeneic graft tolerance, we} recently showed that one month after allogeneic stem cell transplantation, a lack of CD73- _{expressing DP8^ Tregs in patient's blood was strongly associated with the development of acute graft versus host disease. Moreover, a human CD73+ DP8^ Treg clone efficiently} protected immuno-deficient mice against xeno-GvHD through limiting deleterious inflammation and preserving gut integrity. _{Because of the major risks of long-term immunosuppressive therapy (IS), operational tolerance induction or detection (as it develops spontaneously in a few patients) allowing to reduce IS} remains the ultimate goal in organ transplantation. However, the quest for biomarkers allowing _{to identify patients who might tolerate IS reduction, has remained so far unsuccessful (Dugast et al 2016, Am J Transplant, 16, 3255-3261). Interestingly, we observed that the expansion of CD73+ DP8^ Tregs, which characterize stably grafted patients, from 3 months post- transplantation, is highly variable, yielding fractions of these cells ranging from 0.05 to 4% of T cells. If a role of these cells in rejection prevention is confirmed, high frequencies of these cells could provide a better protection against rejection events, as compared to low frequencies. In this context, a high frequency of blood CD73+ DP8^ Tregs post-transplantation might constitute the elusive biomarker allowing to select patients who might benefit from IS weaning. Therefore, at 3 months post-transplantation the frequency of peripheral CD73+ DP8^ Tregs among T cells allows to predict the rejection risks for kidney transplanted patients. However acute early rejection events often take place before 3 months. It will be important to determine whether the beneficial post-transplant expansion of CD73+ DP8^ Tregs in patients who will} not reject their graft starts and may be detected before 3 months which would also provide a _{biomarker to predict earliest rejection events. Regulatory T cells, especially the CD4+ subset, characterized by the expression of FoxP3,} constitute an essential part of the tolerance machinery. Studies in mice demonstrated the potency of these Tregs to prevent allo-graft rejection and induce transplantation tolerance _{(Waldmann H Semin Immunol 2004,16,119-126; Hu M et al Am J Transplant, 2013,13,2819- 2830). However, such a role for these Tregs could not be clearly established in humans so far (Fortunato 2021, Front Immunol, 12, article 641596; Hoogduijn, 2021, Transpl Int 34, 233– 244). Although they do not exclude a contribution of FoxP3 Tregs in rejection prevention, our data clearly point to a major role of DP8^ Tregs in this process, raising important questions} regarding this apparent discrepancy with mice. A potential reason of this difference may be _{related to purine nucleotides being important modulators of post-transplantation outcome and ischemia reperfusion injury (Yeudall 2020 Am J Transplant, 20,633) and to the unique role of CD73 in catalysing the production of the suppressive adenosine. Surprisingly, although contradictory reports exist, convincing studies revealed that CD73 is almost absent on human Foxp3 Tregs (Schneider et al 2021 Nat Commun; 12:5911), at variance in with DP8^ Tregs.} Our data further support the critical role of CD73 in graft tolerance as the strongest correlation _{of graft outcome was not with the frequency of total DP8^ Tregs but with the frequency of} those Tregs expressing CD73. _{Moreover, the transcriptomic signature of DP8^ Tregs, identified recently (Jotereau F, 2022, Front Immunol, 13, 1026994), points to several other potent regulatory functions of DP8^ Tregs that might explain their contribution to limiting allo-immunization following} transplantation. Among these, are found 1/ their high trafficking potential, demonstrated by their high _{expression ex vivo of chemokine receptors such as CXCR3 and CXCR4 allowing migration to} non-lymphoid tissues and especially of CCR5, which promotes migration to inflammatory sites, 2/ their high potential to interact with immune cells through expression of a large array of _{chemokines, e.g., CCL1, CCL3, CCL4, CCL5, which may recruit T cells, as well as XCL1, the} ligand of XCR1 expressed on dendritic cells, 3/ a high lytic potential, based on high expression _{levels of granzymes, perforin and eomesodermin translating into efficient in vitro killing abilities towards antigen-presenting cells of the myeloid lineage (Jotereau F, 2022, Front Immunol, 13, 1026994). Importantly, XCL1-dependent recruitment and killing of host dendritic} cells presenting donor antigens could promote tolerance through preventing donor-reactive T cells priming. Therefore, DP8a Tregs appears well-equipped to inhibit donor specific T cell responses. Their ability to inhibit B cell responses remains to be questioned. On the other hand, while complement activation plays a major role in the rejection mechanisms occurring early _{after transplantation (Moreau A et al 2013, Cold Spring Harb Perspect Med, 3, a015461), we also reported that DP8a Tregs express the CFH gene, which encodes a complement inhibitor not expressed by Foxp3+ Tregs (Jotereau F, 2022, Front Immunol, 13, 1026994). Moreover, based on their high IL-10 and IFN^ production as well as their lack of stable Foxp3 expression, DP8^ cells partly resemble Tr1-like Tregs. Interestingly, a role for Tr1 cells in mediating long-} term chimerism in SCID patients following immune reconstitution by HLA-mismatched stem cell transplantation was proposed (Roncarolo M G et al, 2014, Curr Top Microbiol Immunol, 380, 39-68) and permanent allograft acceptance could be achieved by generating Tr1-type _{Tregs, in mice (Que W et al 2022, Sci Adv, 8, eabo4413).} Importantly, although this study was not prospective, all samples used were prospectively collected. Nonetheless, prospective validation studies will be required, in order to formally _{establish whether the frequency of circulating CD73+ DP8^ Tregs among total T cells and/or} their absolute number indeed represents the much-needed prognostic biomarker, as suggested by the present study. Prospective studies should also ask whether the frequency of CD73⁺ DP8^ Tregs also represent a diagnostic biomarker for kidney graft rejection. In 5 kidney grafted patients diagnosed with acute rejection between 11 and 46-days post-transplantation, we _{observed that frequencies of CD73+ DP8^ Tregs among peripheral T cells at 3-month post transplantation were particularly low (0.009 %-0.03%), i.e., clearly below 0.053 %, the critical threshold identified from our biostatistical analysis. However, it remains unknown whether} these low frequencies are related to the rejection risk or to a post-transplantation time too-short to permit a detectable expansion of these cells in periphery. _{Importantly, measuring in blood the frequency among T cells of CD73+ DP8^ Tregs is clearly} non-invasive and very low-cost, which would permit its routine handling of this biomarker by most transplantation centers. Well-known risk factors such as human leukocyte antigen mismatch or the presence of pre- transplant donor-specific antibodies did not predict rejection with the same accuracy and did _{not fully correlate with CD73+ DP8^ Treg characteristics. Altogether these data suggest that} kidney graft rejection, independently of its subtype, is highly associated with a suboptimal _{intensity of the regulatory response mediated by microbiota-induced DP8^ Tregs expressing CD73, thus paving the way not only for better prediction of kidney graft outcome, but also for the development of DP8^ Treg-based therapies.} REFERENCES: 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.

Claims

CLAIMS: 1. A method of determining whether a subject has or is at a risk of developing a transplant r_{ejection comprising the steps of: i) determining the frequency of CD73-expressing DP8α Tregs among any T cell subset in a sample obtained from the subject after transplantation, ii) comparing the frequency determined at step i) with a predetermined reference value wherein detecting differential between the frequency of CD73- expressing DP8α Tregs among any T cell subset determined at step i) and the} predetermined reference value is indicative of whether a subject has or is at a risk of d_{eveloping a transplant rejection. 2. The method of claim 1 wherein a low frequency of CD73-expressing DP8α Tregs among any T cell subset compared to said predetermined reference value is indicative} of whether a subject has or is at a risk of developing a transplant rejection. _{3. The method of claim 1 wherein a high frequency of CD73-expressing DP8α Tregs among any T cell subset compared to said predetermined reference value is indicative} of whether a subject has or will develop a transplant tolerance or a significant decrease in the risk of rejection. 4_{. The method of claims 1 to 3 wherein the T cell subsets are chosen among total CD3+ T cells or among total CD4+ T cells or among total CD8+ T cells. 5. The method of claims 1 to 4 wherein the sample is a blood sample. 6. The method of claim 1 wherein the sample is analyzed by flow cytometry to determine DP8α Treg frequency. 7. The method of claim 1 wherein the predetermined reference value, at three months post- transplantation, allows to discriminate patients who will undergo a rejection event} within the 3-years post-sampling. _{8. The method of claims 1 to 7 wherein the DP8^ Tregs are obtained 10 days post-} transplantation, 1-month post-transplantation, 3-month post-transplantation, 1-year p_{ost-transplantation or 3-year post-transplantation.}

_{9. The method of claims 1 to 8 wherein the transplant is a kidney, heart, liver, lung,} pancreas, intestine, stomach, thymus, uterus, testis, hand skin and tissues which include bones, tendons (both referred to as musculoskeletal grafts), corneae, skin, heart valves, n_{erves or veins. 10. A method of treatment of transplant rejection in a patient diagnosed with a low frequency of CD73-expressing DP8α Tregs among any T cell subset after transplantation} comprising administering a therapeutically effective amount of an immunosuppressive a_{gent or an infusion of CD73+ DP8α Tregs exhibiting appropriate features or DP8α target antigens (F. prausnitzii-derived) in the form of peptides, proteins, or even} bacteria/probiotics. _{11. A method for treating or preventing transplant rejection in a subject in need thereof} comprising a step of: i_{) Determining the frequency of CD73-expressing DP8α Tregs among any T cell subset, in a blood sample obtained from the subject after transplantation , ii) Comparing the frequency determined at step i) with a predetermined reference value} and iii) Administering said subject with a therapeutically effective amount of an i_{mmunosuppressive agent or an infusion of CD73+ DP8α Tregs exhibiting appropriate features or DP8α target antigens (F. prausnitzii-induced DP8^ Tregs) in the form of peptides, proteins, or even bacteria/probiotics when the frequency of CD73-expressing DP8α Tregs among any T cell subsets is lower than the predetermined reference value. 12. The method of treatment of claims 10 or 11 wherein the frequency of CD73+ DP8α Tregs is determined amongst chosen T cell subsets such as total CD3+ T cells or total CD4+ T} cells or total CD8⁺ T cells. 1_{3. A kit for diagnosing, prognosing and/or predicting the risk of developing transplant rejection wherein said kit comprises means for determining the number and/or concentration and/or proportion and/or frequency of CD73-expressing DP8α Tregs among any T cell subset after transplantation.}