Discovering statistically significant pathways in expression profiling studies

TLDR

Accurate and rapid identification of perturbed pathways from genome‑wide expression profiles facilitates generation of biological hypotheses. The authors propose a statistical framework and tests to assess coordinated association of gene sets with phenotypes, clarifying hypothesis‑testing issues. The framework applies statistical tests for two association aspects to diabetes, inflammatory myopathies, and Alzheimer’s datasets compiled from public gene sets. The method corrects bias from correlation structure, achieves higher power than existing approaches, identifies known cytotoxic T‑lymphocyte autoimmunity in inclusion body myositis, predicts novel dendritic‑cell and IFN‑α/β responses in dermatomyositis, and these predictions are confirmed by immunohistochemistry.

Abstract

Accurate and rapid identification of perturbed pathways through the analysis of genome-wide expression profiles facilitates the generation of biological hypotheses. We propose a statistical framework for determining whether a specified group of genes for a pathway has a coordinated association with a phenotype of interest. Several issues on proper hypothesis-testing procedures are clarified. In particular, it is shown that the differences in the correlation structure of each set of genes can lead to a biased comparison among gene sets unless a normalization procedure is applied. We propose statistical tests for two important but different aspects of association for each group of genes. This approach has more statistical power than currently available methods and can result in the discovery of statistically significant pathways that are not detected by other methods. This method is applied to data sets involving diabetes, inflammatory myopathies, and Alzheimer's disease, using gene sets we compiled from various public databases. In the case of inflammatory myopathies, we have correctly identified the known cytotoxic T lymphocyte-mediated autoimmunity in inclusion body myositis. Furthermore, we predicted the presence of dendritic cells in inclusion body myositis and of an IFN-α/β response in dermatomyositis, neither of which was previously described. These predictions have been subsequently corroborated by immunohistochemistry.