Gut microbiota and liver disease are very closely linked. Microbiota influences the various liver diseases by Dysbiosis ratio .There is loss of tolerance targeting liver antigens which is thought to initiate disease in genetically susceptible individuals. This is triggered by environmental agents such as pathogens.Autoimmune Liveer disease(AILD )patients have Specific bacterial profile and Alterations in bacterial metabolites and immune pathways trigger Autoimmune hepatitis( AIH)& lead to its progression .Apoptosis of intestinal epithelial cells in response to microbial stimuli presentation of self-antigens leading to differentiation of autoreactive Th17 cells and other T helper cells leading to T-cell response of AILD.(1). Disease-associated dysbiosis in untreated patients with AIH was characterised by reduced biodiversity, decreased abundance of anaerobes and increase of the genera Veillonella, Klebsiella, Streptococcus and Lactobacillus(2-3).It remains unclear whether this microbial signature is specific compared to other autoimmune liver diseases or other immune-mediated diseases, and whether it is reproducible across geographic borders .However there is Scarce paediatric data comparing gut microbiota in AILD vs other liver diseases and no data on role of gut microbiota on response to treatment in AILD .

The aim of this study will be to To compare the gut microbiota (dysbiosis ratio, alpha and beta diversity, Shannon index) in children with autoimmune liver disease and Wilson disease, and study its influence on response to treatment in children with autoimmune liver disease.

Aim and Objective - To compare the gut microbiota (dysbiosis ratio, alpha and beta diversity, Shannon index) in children with autoimmune liver disease versus those with Wilson disease, and study its influence on response to treatment in children with autoimmune liver disease.

(b) Methodology:

• Study population:Disease cohort: Children with evidence of chronic liver disease with autoimmune Liver disease and Wilson disease (hepatic involvement) under 18 years of age
• Control cohort: Agematched healthy children under-18-year age with Study design:Prospective observational study
• Study period:From the time of Ethical approval to June 2025

Stool for 16S r-RNA sequencing: Fresh stool samples will be collected from study subjects and controls. Stool samples will be delivered to the laboratory in sterile plastic containers at 4°C, and stored at -80°C till further analysis .The amplified DNA will be sequenced in the next generation sequencing platform. Sequence data would be processed using standardized analysis pipeline. Briefly, sequences would be joined, depleted of barcodes, sequences <150bp and those with ambiguous base calls would be removed. Sequences would be denoised, operational taxonomic units (OTUs) generated and chimeras removedThe intestinal microbiome will be studied by whole genome shotgun metagenomic sequencing (WGSM).By detection of bacterial genes for metabolic digestive enzymes of taxa present, metabolic capacities and potential production of metabolites by the gut microbiome will be predicted.Sequences would be denoised, operational taxonomic units (OTUs) generated and chimeras removed .The intestinal microbiome will be studied by whole genome shotgun metagenomic sequencing (WGSM) .By detection of bacterial genes for metabolic digestive enzymes of taxa present, metabolic capacities and potential production of metabolites by the gut microbiome will be predicted.

• Monitoring and assessment:Children with evidence of chronic liver disease with autoimmune Liver disease and Wilson disease (hepatic involvement) will be included Control cohort: Age, gender and socio-economic status matched healthy children under-18-year age with TNF-alpha , IL-6,Plasma endotoxin , CRP, Procalcitonin, Duodenal aspirate for culture to identify bacterial overgrowth . Stool samples will be collected at baseline in Patients with AILD , Wilson and Healthy controls .AILD patients will be started On treatment with Prednisolone 1 mg/kg/day along with Azathioprine 1 mg/kg/day and Stool samples of them will be collected at the end yo see the response to immunosuppression Difficult to treat AILD (which will be defined Failure to normalize AST/ALT within 1.5 times or failure to normalize IgG within 6 months. )

STATISTICAL ANALYSIS:

• The categorical and continuous variables will be expressed as frequencies and mean or median ±SD, respectively. Chi-square test and student's t-test (Fisher's exact test) will be applied for assessment of causality. Correlation between 2 continuous variables will be assessed as per Spearman's correlation. Statistical significance will be mentioned as p-value <0.05, and Odd's ratio and 95% confidence intervals (95% CI). For metagenomic data, in the absence of gene catalogue for the study population, we will study the metagenomic data in first 10 AILD, 5 Wilson and 5 controls ,].

Inclusion Criteria:

1. Disease cohort: Children with evidence of chronic liver disease with autoimmune Liver disease and Wilson disease (hepatic involvement).
2. Control cohort: Age and socio-economic status matched healthy children under-18-year age with
3. Wilson disease: Diagnosis as per AASLD guidelines i.e. presence of either 3 of the following: Kayser Fleischer ring in cornea, 24-hour urine copper >40 microgm /day, serum ceruloplasmin <20 mg/dL; Leipzig score >4 or presence of one homozygous or 2 or more compound heterozygous disease causing mutations in ATP7B gene.
4. Autoimmune liver disease: Diagnosis on the basis of presence of abnormalities in transaminases with hypergammaglobinemia, positive autoantibodies (anti-nuclear, anti-smooth muscle, anti-liver-kidney-microsomal, anti-soluble liver antigen), suggestive liver biopsy (interface hepatitis, plasma cell infiltrates, emperipolesis, pseudorosettes) in absence of other known causes of liver disease (viral hepatitis, Wilson disease, Budd-Chiari syndrome, etc) and simplified score ≥ 6

Exclusion Criteria:

1. Antibiotic usage for last 1 week or immunosuppression usage for last 4 weeks
2. Liver tumours
3. Active or recent episode of gastroenteritis within 1 week of presentation
4. Diabetes mellitus
5. Primary and secondary immunodeficiency states (HIV)
6. Abdominal surgery
7. Usage of proton pump inhibitors in last 1 week.
8. Uncertain diagnosis or incomplete work-up

• Study population:Disease cohort: Children with evidence of chronic liver disease with autoimmune Liver disease and Wilson disease (hepatic involvement) under 18 years of age
• Control cohort: Agematched healthy children under-18-year age with