Biological IFNβ s.c. treatment response networks derived from whole genome RNA profiles of MS patients

Objective: This longitudinal systematic gene expression study focuses on MS and the effects of medication by subcutaneous Interferon-β-1b (IFNβ1b). It is the aim to attain human peripheral blood derived gene transcripts that are differenzially regulated throughout therapy and to infer accessory regulatory pathways of the applied drug.

Method: Employing the Affymetrix HGU133A/B array (45.000 transcript species), a full genome study was performed monitoring 25 RRMS patients that received IFNβ1b (s.c.) over a period of 2 years. Peripheral blood mononuclear cells were collected before first treatment and correspondingly before each upcoming injection after 2 days, 4 weeks, 1 and 2 years. Applying a combination of independent criteria, we performed transcriptome data curation and gene filtering to identify sets of differenzially expressed genes (DEGs). Biologically functional analyses were carrried out by Gene Ontology (GO) category evaluation (biological parameter) and knowledge based gene regulatory network inference (Pathway Architect). The graphical tool Cytoscape allowed to incorporate degree of connectivity between direct interactions of attained informative gene sets for respective time points.

Results: As expected, we observed an increased expression of established IFN-β marker genes, e.g. MX1 and OAS-1, -2, -3, several IFITs, STAT-1 and -2, IRF-7 and-9, and differenzial expression of circulating IFN-β responsive candidates like Interleukin 8, TRAIL, and MMP9. Consistently upregulated throughout analyzed time points were 18 genes, namely interferon-induced protein 44 (IFI44; IFI44L) IFIT1,2, and 3, ISG15, SIGLEC1, RSAD2, CD20 and CD20 antigen-like 1, and others, whereas FCER1a was downregulated.

Groups of functionally related genes changed coordinatedly over time in the majority of analyzed individuals. Results of GO and network analyses describe evidence for a general increase in the cellular activity at earlier stages of therapy, resembling the endogenous antiviral response of IFNs. In contrast, more DEGs at years one and two were involved in cellular demise.

Conclusion: The dynamic expression changes of individual RNA profiles reflect the intertwining of disease and therapy course complexities.

t = 1 Month

t = 1 Month

t = 24 Months