Evaluating MiRomics and Integrative Proteomics for Identification of Plasma miRNAs as Potential Pharmacodynamic Biomarkers of IFNß-1a Biologics
We used miRNA-sequencing to identify candidate plasma pharmacodynamic (PD) biomarkers of interferon beta-1a (IFNß-1a) biologics and to explore miRNA-mRNA targeted protein relationships and networks to support identified miRNA candidates. Plasma samples from 36 healthy subjects from a placebo-controlled randomized single dose clinical study with IFNß-1a and pegIFNß-1a were used. Mature miRNAs were measured using an in-house miRNA-seq workflow at baseline, at 9 timepoints over 6 days in IFNß-1a group (n=11[30µg]), and at 11 timepoints over 13 days in pegIFNß-1a group (n=11[125µg]) and placebo-specific groups (n=6 each). A miRNA was only considered expressed if it had a read count =10 in more than 50% of the samples across all treatment groups. Linear mixed-effects models (lmer) regressing miRNA changes with treatment, time and their interaction were used to identify differentially expressed miRNAs, which were further prioritized based on magnitude of response and biological relevance using in silico predicted miRNA-protein targets and regulatory network analyses. Ten and 13 miRNAs were impacted by IFNß-1a and pegIFNß-1a, respectively (lmer FDR-corrected p- value <0.1), compared to placebo, of which miR.223.3p and miR.21.5p were prioritized as candidate PD biomarkers for both products. Systems level analysis of integrated proteomics data highlighted miRNA protein targets for both miR.223.3p and miR.21.5p that were linked to previously reported top proteomic response proteins and predicted regulatory networks including IFN beta. Using miRNA-sequencing and linking candidates to predicted target proteins and regulatory networks, results suggest miR.223.3p and miR.21.5p as potential novel PD biomarkers of IFNß-1a biologics for further investigation. Overall design: To identify potential PD miRNA biomarkers of IFNß-1a biologics, we collected plasma samples from healthy participants randomized into three treatment groups (IFNß-1a, pegIFNß-1a, and placebo). These samples were obtained at time zero (baseline), at  9 timepoints over 6 days following administration of IFNß-1a, and at 11 timepoints over 13 days following administration of pegIFNß-1a and placebo. We then performed miRNA sequencing (next generation sequencing) on these samples. Uisng the normalized sequencing data, we conducted miRNA differential expression analysis to identify differentially expressed miRNAs by treatment from baseline.