Integrated micro/messenger RNA regulatory networks in essential thrombocytosis

Abstract

Essential thrombocytosis (ET) is a chronic myeloproliferative disorder with an unregulated surplus of platelets. Complications of ET include stroke, heart attack, and formation of blood clots. Although platelet-enhancing mutations have been identified in ET cohorts, genetic networks causally implicated in thrombotic risk remain unestablished. In this study, we aim to identify novel ET-related miRNA-mRNA regulatory networks through comparisons of transcriptomes between healthy controls and ET patients. Four network discovery algorithms have been employed, including (a) Pearson correlation network, (b) sparse supervised canonical correlation analysis (sSCCA), (c) sparse partial correlation network analysis (SPACE), and, (d) (sparse) Bayesian network analysis–all through a combined data-driven and knowledge-based analysis. The result predicts a close relationship between an 8-miRNA set (miR-9, miR-490-5p, miR-490-3p, miR-182, miR-34a, miR-196b, miR-34b*, miR-181a-2*) and a 9-mRNA set (CAV2, LAPTM4B, TIMP1, PKIG, WASF1, MMP1, ERVH-4, NME4, HSD17B12). The majority of the identified variables have been linked to hematologic functions by a number of studies. Furthermore, it is observed that the selected mRNAs are highly relevant to ET disease, and provide an initial framework for dissecting both platelet-enhancing and functional consequences of dysregulated platelet production.