Identification of gene clusters with phenotype-dependent expression with application to normal and premature ageing

Abstract

Background: Hutchinson Gilford progeria syndrome (HGPS) is a rare genetic disease with symptoms of aging manifested at a very early age. Molecular basis of HGPS is not entirely clear, although there are some known and other presumed overlaps with normal aging process. Comparative investigation of biological processes associated with HGPS and normal aging may reveal common and distinctive pathways underlying these two conditions. Results: To investigate transcriptome changes through aging we have performed RNA-seq profiling in fibroblast cell cultures at three different cellular ages as measured by number of passages through culture growth, both from HGPS patients and matched normal samples. We then developed a novel iterative multiple regression approach that leverages co-expressed gene clusters to identify gene clusters whose expression changes significantly with age and/or disease state. We establish the robustness of our approach. Finally, we perform a comparative investigation of biological processes underlying normal aging and HGPS. Conclusion: Based on an iterative multiple regression approach applied to novel RNA-seq data in HGPS and aging our results recapitulate the previously known processes underlying aging while at the same time suggests numerous unique processes underlying aging and HGPS.