Role of Fecal Microbiota in Predicting Graft Rejection and Sepsis Among Recipients of Living Donor Liver Transplant in First Year.

Study Overview
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Brief Summary
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Efficient immunosuppressive therapy and improved surgical techniques have developed liver transplantation as a well-established and life-saving treatment. The 1-year survival rate of approximately 85-90%. Acute cellular rejection (ACR) is one of the main causes of liver dysfunction (LD) after liver trans- plantation, occurring 30% to 70% of transplanted patients and potentially leading to allograft failure. In addition to ACR, presence of sepsis, drug injury, viral infections like CMV or recurrence of viral hepatitis is also other causes of graft dysfunction. Laboratory tests are commonly used as less invasive methods of monitoring allograft rejection, but they are not specific to rejection and are often elevated in other types of graft dysfunction too. Till date the immunosuppressive regimen in liver transplant recipient is considered as an art in absence of an objective measures of the immune state. Therapeutic drug monitoring has little value in the assessment of the immune state and is always used as a supportive guide. The development of specific immune monitoring assays to measure the net immunosuppressive state in a transplant recipient would allow a more individualized therapeutic regimen Patients with altered gut microbiota had more chances of infection and longer course of hospital stay. Probiotics could mediate beneficial effects in graft rejection. Dysbiosis activates T cells through PAMPS and causes the inflammatory injury in the graft liver. The studies shown that lower Eubacteria, Bifidobacterium, Faecal bacterium and Lactobacillus with abundance of Enterococcus and Enterobacteriaceae. They restored to near normal after transplant in majority. This is known that there is a dysbiosis in the natural history of ACLF or decompensated cirrhosis, and often correlated to complications like-endotoxemia, sepsis, worsening liver failure and poor survival. This has led to consider fecal microbiota modulation as an emerging therapy. Liver transplant and consequent recovery, there is over all change in the recipient homeostatic milieu as well as the immune milieu and the same may be happening to the gut flora too.It's well known that liver has animprint of resident gut flora. The preliminary rat model showed alteration of gut flora to predict the development acute cellular rejection before it happens. Similarly the risk of infection is more among transplant recipients with decreased microbial diversity after liver transplant. However the data is scanty and there is an urgent need to understand the mechanism.. The present study was necessitated in view of emerging role of gut microflora and its influence on immune remodeling for the prediction of infection, rejection and may be an early biomarker for the graft dysfunction. This may be of varied cause in liver transplant recipients along with its impact on overall immune status. Uniqueness of the present study will be to understand the mechanism of development of sepsis or graft dysfunction in due course of time using high-throughput tools of single cell analysis in whole blood and gut microbiota alterations among liver transplant recipient as a cause for graft dysfunction in first year of live donor liver transplant.

Detailed Description
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Primary Objective: To characterize the fecal microbiota changes over one year after living donor liver transplantation and its association with graft rejection and sepsis. Secondary objectives : Incidence of graft dysfunction attributable to sepsis, rejection and CMV infection in first year of LDLT. To study the pre-LT immunological profile and its correlation with post-transplant rejection, immunosuppression requirements and restoration of immunosenescence. To correlate the dynamic changes in immune cells and cytokines in predicting graft rejection and sepsis. STUDY DESIGN Type of study - Single centre, prospective, observational study Study population - consecutive 100 patients fulfilling the eligibility criteria and undergoing living donor liver transplant in ILBS between April 2020 to March 2022. Study duration - 24 months from the date of approval of IEC Methodology: Identification of gut microbiota: DNA extraction All subjects will undergo serum and stool collection the same day. About 5-8g of fecal materialwill be collected .The QIAamp Fast DNA Stool Mini Kit for stool samples will be used for DNA extraction. PCR Amplification of the 16s RNA Gene Briefly, PCR amplification of the V3-V4 hypervariable regions will be done by using the 341F and 806R primers containing the sample specific barcode. Purified amplified product (QIAGEN), will be run on the MiSeq platform with custom sequencing primer reads 1 (R1), read 2 (R2) and index. Whole blood: Whole blood will be (5-10ml) will be collected. Plasma will be separated by centrifugation at 2500rpm. Plasma will be stored at -80C in biobank (NLDB) until processed for cytokines array. Remaining blood will be treated with RBC lysis buffer and will be processed for immune cells analysis. Immunophenotyping for frequency/absolute number of immune cells: The cells in the whole blood will be stained with specific flurochrome labelled monoclonal antibodies for the surface markers for T cells subsets (Th1,Th2, Th17, Tregs), B regulatory cells using Flowcytometry and analysis will be done by FCS express software. Cytokine Array: The pro-inflammatory (IL-1β) and anti-inflammatory cytokines (IL-10)will be measured in plasma of the patients under study. The cytokine array kit will be procured commercially and will be done according to the manufacturer's instructions. STATISTICAL ANALYSIS Data will be reported as mean + SD Categorical variables will be compared using the chi-square test or Fisher exact test Normal continuous variables will be compared using the Student t test Non normal continuous variables will be compared using the Mann-Whitney rank-sum test (unpaired data) or the Wilcoxon test (paired data). Comparison between groups on quantitative variables will be analyzed by ANOVA A Cox regression analysis will be performed to identify independent prognostic factors for graft function. STUDY END POINTS Primary End point Development of sepsis, rejection, CMV infection Death Secondary End points Post LT complications requiring surgical interventions Retransplantation Expected outcome of the project: This will help us in designing simple diagnostic tools based on microbial profiling or immune cells signatures for diagnosis of graft dysfunction and sepsis. This will also give us insight about mechanism of immune pathogenesis during the development of severe conditions and this will pave way for newer therapeutic options. Ethical issues in the study and plans to address these issues - None

Official Title
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Role of Fecal Microbiota in Predicting Graft Rejection and Sepsis Among Recipients of Living Donor Liver Transplant in First Year - An Observational Study.

Conditions
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Acute Liver Failure, Acute-On-Chronic Liver Failure, Liver Cirrhosis

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Living donor Liver transplantation for ALF, ACLF, cirrhosis and its complications. Age 12-75 years Valid consent Exclusion Criteria: Deceased Donor Liver Transplants Re-transplants Simultaneous Liver-Kidney Transplants (SLKT)

Ages Eligible for Study
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Minimum Age: 12 Years
Maximum Age: 75 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Development of sepsis | Sepsis diagnosis is based on positive cultures of the patient (Blood, urine, tip of catheter ), foci of infection by cross sectional imaging at any point of time | 1 years | 
| Development of rejection | Rejection dosgnosis is based on graft biopsy and histology - assessed by REJECTION ACTIVITY INDEX (RAI) | 1 years | 
| Development of CMV infection | CMV DNA diagnosis is by RT PCR technique | 1 years | 
| Death |  | 1 years | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Post LT complications requiring surgical interventions |  | 1 years | 
| Number of patients who will undergo Retransplantation |  | 1 years |