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The diagnosis of primary sclerosing cholangitis (PSC) is difficult due to the lack of sensitive and specific biomarkers, as is the early diagnosis of cholangiocarcinoma (CC), a complication of PSC. The aim of this study was to identify specific serum miRNAs as diagnostic biomarkers for PSC and CC. The levels of 667 miRNAs were evaluated in 90 human serum samples (30 PSC, 30 CC and 30 control subjects) to identify disease-associated candidate miRNAs (discovery phase). The deregulated miRNAs were validated in an independent cohort of 140 samples [40 PSC, 40 CC, 20 primary biliary cirrhosis (PBC) and 40 controls]. Receiver operating characteristic (ROC) curves were established and only miRNAs with an area under the curve (AUC) > 0·70 were considered useful as biomarkers. In the discovery phase we identified the following: 21 miRNAs expressed differentially in PSC, 33 in CC and 26 in both in comparison to control subjects as well as 24 miRNAs expressed differentially between PSC and CC. After the validation phase, miR-200c was found to be expressed differentially in PSC versus controls, whereas miR-483-5p and miR-194 showed deregulated expression in CC compared with controls. We also demonstrate a difference in the expression of miR-222 and miR-483-5p in CC versus PSC. Combination of these specific miRNAs further improved the specificity and accuracy of diagnosis. This study provides a basis for the use of miRNAs as biomarkers for the diagnosis of PSC and CC., (© 2016 British Society for Immunology.)

The high-throughput analysis of microRNAs (miRNAs) circulating within the blood of healthy and diseased individuals is an active area of biomarker research. Whereas quantitative real-time reverse transcription polymerase chain reaction (qPCR)-based methods are widely used, it is yet unresolved how the data should be normalized. Here, we show that a combination of different algorithms results in the identification of candidate reference miRNAs that can be exploited as normalizers, in both discovery and validation phases. Using the methodology considered here, we identify normalizers that are able to reduce nonbiological variation in the data and we present several case studies, to illustrate the relevance in the context of physiological or pathological scenarios. In conclusion, the discovery of stable reference miRNAs from high-throughput studies allows appropriate normalization of focused qPCR assays., (© The Author 2015. Published by Oxford University Press.)

The altered expression of micro-RNA (miRNA) has been associated with Crohn's disease (CD) and ulcerative colitis (UC). The aim of this study was to establish specific miRNA expression patterns in the serum and mucosa of inflammatory bowel disease (IBD) patients (UC and CD with colonic involvement) at different stages of the disease. Serum and biopsies from nine active CD (aCD), nine inactive CD (iCD), nine active UC (aUC) and nine inactive UC (iUC) and serum from 33 healthy subjects were collected. Up to 700 miRNAs were evaluated by the TaqMan human miRNA array. The ΔCt values were obtained using the mean expression values of all expressed miRNAs in a given sample as a normalization factor for miRNA real-time quantitative polymerase chain reaction data. The levels of serum miRNAs in CD and UC patients were different to healthy subjects. Thirteen serum miRNAs were expressed commonly in CD and UC patients. Two miRNAs were higher and four miRNAs were lower in the serum of aCD than iCD. No serum miRNA was regulated exclusively in aUC compared with iUC patients. Four miRNAs were higher and three miRNAs were lower in the mucosa of aCD than iCD. Two miRNAs were higher and three miRNAs were lower in the mucosa of aUC than iUC. No serum miRNAs coincided with tissue miRNAs in aCD and aUC patients. Our results suggest the existence of specific miRNA expression patterns associated with IBD and their different stages and support the utility of miRNA as possible biomarkers. This pilot study needs to be validated in a large prospective cohort., (© 2013 British Society for Immunology.)

Motivation: The Illumina Infinium 450 k DNA Methylation Beadchip is a prime candidate technology for Epigenome-Wide Association Studies (EWAS). However, a difficulty associated with these beadarrays is that probes come in two different designs, characterized by widely different DNA methylation distributions and dynamic range, which may bias downstream analyses. A key statistical issue is therefore how best to adjust for the two different probe designs., Results: Here we propose a novel model-based intra-array normalization strategy for 450 k data, called BMIQ (Beta MIxture Quantile dilation), to adjust the beta-values of type2 design probes into a statistical distribution characteristic of type1 probes. The strategy involves application of a three-state beta-mixture model to assign probes to methylation states, subsequent transformation of probabilities into quantiles and finally a methylation-dependent dilation transformation to preserve the monotonicity and continuity of the data. We validate our method on cell-line data, fresh frozen and paraffin-embedded tumour tissue samples and demonstrate that BMIQ compares favourably with two competing methods. Specifically, we show that BMIQ improves the robustness of the normalization procedure, reduces the technical variation and bias of type2 probe values and successfully eliminates the type1 enrichment bias caused by the lower dynamic range of type2 probes. BMIQ will be useful as a preprocessing step for any study using the Illumina Infinium 450 k platform., Availability: BMIQ is freely available from http://code.google.com/p/bmiq/., Contact: a.teschendorff@ucl.ac.uk, Supplementary Information: Supplementary data are available at Bioinformatics online.