Integration of transcriptomics and mirnomics for brugada syndrome diagnosis

Abstract

Abstract Background/Introduction Brugada Syndrome (BrS) presents a genetic and phenotypic heterogeneity, so integrating different omics approaches could add information on molecular mechanisms and find new diagnostic markers. Purpose This work aims to provide a transcriptomic and mirnomic profile of patients with Type 1 BrS as a preliminary step for evaluating potential biomolecular markers to assist in the diagnosis of the syndrome. Methods Subjects aged 14–75 years (inclusive) with ECG presenting a spontaneous Type 1 BrS or a suspect BrS pattern were eligible to participate in the study. All the suspect BrS subjects underwent a provocative test (i.v. ajmaline or flecainide administration). A total of 56 patients were collected by clinical centers involved in the BrAID study. According to their diagnosis, these were divided into two main groups: Brugada (28, spontaneous and positive to provocative test) and Controls (28, controls and negative to provocative test). To better characterize the population, a sub-classification was performed: Spontaneous Type 1 BrS (Group A, 14), patients with (Group B, 14) and without (Group C, 14) a Type 1 pattern after the provocative test, and Control group (Group D, 14). Patients with a history of ventricular premature contractions, normal ventricular function, and provocative negative tests were the control group. Whole blood samples (2.5 mL) were collected into PAXgene blood RNA system tubes (DIALAB ITALIA Srl, Milan, Italy) for RNA-Seq analysis. Blood samples were also collected into EDTA (1 mg/mL) for exosome isolation. Total RNA was extracted from whole blood using the PAXgene Blood RNA Kit (Qiagen). Exosomes were extracted using a dedicated and innovative assay (exoRNeasy mini/midi kit, QIAGEN). Samples were quantified and quality tested by Agilent 2100 Bioanalyzer RNA assay. Data were analyzed through web-based platforms for multi-omics integration and network visual analytics (mirNET 2.0, OmicsNet 2.0). Results The comparison of overall Brugada and Controls highlighted the presence of two genes (SLC8A2, RNA18S5) and 3 miRNAs (hsa-miR-584-5p, hsa-miR-148b-3p, hsa-miR-148a-3p) involved in BrS (Figure 1). When Group A and D were compared a statistically significant difference was observed for SLC8A2 and hsa-miR-625-3p, hsa-miR-4488, hsa-miR-328-3p. No significantly different genes were observed comparing the patients with a positive and negative provocative test, while 7 miRNAs were significantly modulated in the two subsets. Different genes and miRNAs were observed comparing spontaneous/positive patients (1 gene, 1 miRNA) and controls/negative (3 genes, 10 miRNAs). The network analysis between genes and miRNAs of the Brugada/Controls comparison showed an interaction of SESN3, ROCK1 and IGFBP5 (Figure 2). Conclusion These results indicate that a new set of molecular markers has the potential to better characterize BrS patients who present phenotypical heterogeneityFig.1Genes and miRNAs in BrS patientsFig.2Network analysis