title: Gene expression and micro RNA profiling in acute pancreatitis
Creators: name: Altaf, K
Publisher: name: University of Liverpool Repository
Year: 2019

description: Introduction Prognostication in Acute pancreatitis (AP) remains a challenging issue. This study aimed to measure gene expression of the peripheral blood in patients with acute pancreatitis and identify an expression signature that would accurately stratify patients into either mild or severe disease groups. MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression and play important roles in a variety of cellular functions. These have emerged as major potential biomarkers in a variety of sepsis related disorders and cancers. Alongside, gene expression profiling, the prognostic potential of micro RNA at the time of admission in context of acute pancreatitis was also explored. Methods This observational study was conducted at Royal Liverpool University Hospital, NHS Foundation Trust, in collaboration with University Hospital Aintree, NHS Foundation Trust. For gene expression profiling, Affymetrix HGU133 Plus 2.0 microarrays were utilised. Total RNA extracted from whole blood samples of patients collected at the time of admission was included. A pilot study was conducted in the first instance to enable sample size calculations. Analysis was performed using Partek Genomics Suite software. Expression level data were quantile normalised and ANOVA was used with batch hybridization effects. For microRNA analysis, a similar pilot study was undertaken to estimate sample size. Total RNA was extracted from plasma samples of patients obtained at the time of admission. RNA were hybridised to GeneChipTM miRNA 2.0 arrays. Analysis was performed using appropriate packages in R/Bioconductor and using Partek Genomics Suite software. Expression level data were invariant set normalized. Differential expression of miRNAs in severe compared to mild pancreatitis was detected using ANOVA with batch hybridization effects removed. Severity was defined in line with Atlanta criteria for both the parts of the study. Results 58 patients were included (23 severe, 35 mild). After adjusting for batch effects, setting power at 80%, fold change at 1.5 and significance at 0.05, 98 genes were identified that were differentially expressed between mild and severe disease. More specifically, 49 genes were up-regulated in severe form and 49 were down-regulated when compared to the mild disease. Canonical pathway analysis revealed signalling in T cells and lymphocytes to be the most significant pathway involved in the process. These were specifically down-regulated in severe form of the disease. While a lot of processes associated with the cellular immune response were down-regulated in severe pancreatitis, the innate response didn’t change and the humoral response might be stimulated. Nuclear Factor of Activated T cells (NFAT) was noted to be the most significantly implicated gene in the dataset, being a key molecule implicated in at least 12 different pathways. Nineteen patients were included (severe 9, mild 10) for the miRNA profiling. Keeping the FDR p &lt;0.05, 45 micro RNA were found to be differentially expressed between mild and severe pancreatitis. Out of these, only 23 were annotated in IPA – 22 were novel discoveries. Interestingly, 19 small nucleolar RNA (snoRNAs) were identified to be differentially expressed between the two groups. Conclusions Understanding more about the pathophysiology and genomic regulation in acute pancreatitis will provide us with potential prognostic biomarkers and targets for therapy. This study has selected a series of gene expression features which could act as biomarkers to accurately stratify patients into mild and severe groups. Appropriate therapy can then be chosen earlier to improve outcomes in the disease. MiRNA and snoRNA can predict severity of acute pancreatitis at the time of admission. These can also be developed to predict specific complications of the disease, including organ failure and pancreatic necrosis, as early as, at the time of admission. Once developed, this could fill in the gap that currently exists in prognostication arena in acute pancreatitis.