Dataset Information

Diagnostic Utility of Gene Expression Profiles.

ABSTRACT: Two crucial problems arise from a microarray experiment in which the primary objective is to locate differentially expressed genes for the diagnosis of diseases such as cancer and Alzheimer's. The first problem is the detection of a subset of genes which provides an optimum discriminatory power between diseased and normal subjects, and the second problem is the statistical estimation of discriminatory power from the optimum subset of genes between two groups of subjects. We develop a new method to select an optimum subset of discriminatory genes by searching over possible linear combinations of gene expression profiles and locating the one which provides the maximum discriminatory power between two sources of RNA as measured by the area under the receiver operating characteristic (ROC) curve. We further provide an estimate to the optimum discriminatory power between the diseased and the healthy subjects over the selected subsets of genes. The proposed stepwise approach takes in account of the gene-to-gene correlations in the estimation of discriminating power as well as the associated variability and allows the number of genes to be selected based on the increment of the discriminating power. Finally, the proposed methodology is applied to a benchmark microarray experiment and compared to the results obtained through existing approaches in the literature.

SUBMITTER: Xiong C

PROVIDER: S-EPMC4026209 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature

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Diagnostic Utility of Gene Expression Profiles.

Xiong Chengjie C Yan Yan Y Gao Feng F

Journal of biometrics & biostatistics 20130101 1

Two crucial problems arise from a microarray experiment in which the primary objective is to locate differentially expressed genes for the diagnosis of diseases such as cancer and Alzheimer's. The first problem is the detection of a subset of genes which provides an optimum discriminatory power between diseased and normal subjects, and the second problem is the statistical estimation of discriminatory power from the optimum subset of genes between two groups of subjects. We develop a new method ...[more]

PMID: 24851193

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Project description:Effective management and control of parasitic infections on farms depends on their early detection. Traditional serological diagnostic methods for Fasciola hepatica infection in livestock are specific and sensitive, but currently the earliest detection of the parasite only occurs at approximately three weeks post-infection. At this timepoint, parasites have already entered the liver and caused the tissue damage and immunopathology that results in reduced body weight and loss in productivity. Here, we investigated whether the differential abundance of micro(mi)miRNAs in sera of F. hepatica-infected sheep has potential as a tool for the early diagnosis of infection. Using miRNA sequencing analysis, we discovered specific profiles of sheep miRNAs at both the pre-hepatic and hepatic infection phases in comparison to non-infected sheep. In addition, six F. hepatica-derived miRNAs were specifically identified in sera from infected sheep. Thus, a panel of differentially expressed miRNAs comprising four sheep (miR-3231-3p; miR133-5p; 3957-5p; 1197-3p) and two parasite miRNAs (miR-124-3p; miR-Novel-11-5p) were selected as potential biomarkers. The expression of these candidates in sera samples from longitudinal sheep infection studies collected between 7 days and 23 weeks was quantified using RT-qPCR and compared to samples from age-matched non-infected sheep. We identified oar-miR-133-5p and oar-miR-3957-5p as promising biomarkers of fasciolosis, detecting infection as early as 7 days. The differential expression of the other selected miRNAs was not sufficient to diagnose infection; however, our analysis found that the most abundant forms of fhe-miR-124-3p in sera were sequence variants (IsomiRs) of the canonical miRNA, highlighting the critical importance of primer design for accurate diagnostic RT-qPCR. Accordingly, this investigative study suggests that certain miRNAs are biomarkers of F. hepatica infection and validates miRNA-based diagnostics for the detection of fasciolosis in sheep.

Dataset Information

Diagnostic Utility of Gene Expression Profiles.

Publications

Diagnostic Utility of Gene Expression Profiles.

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