10.6084/m9.figshare.7886671.v1 Friederike Ehrhart Friederike Ehrhart Susan L. Coort Susan L. Coort Lars Eijssen Lars Eijssen Elisa Cirillo Elisa Cirillo Eric E. Smeets Eric E. Smeets Nasim Bahram Sangani Nasim Bahram Sangani Chris T. Evelo Chris T. Evelo Leopold M.G. Curfs Leopold M.G. Curfs Integrated analysis of human transcriptome data for Rett syndrome finds a network of involved genes Taylor & Francis Group 2019 Rett syndrome rare diseases neurological disorder bioinformatics pathway analysis 2019-03-25 10:02:10 Dataset https://tandf.figshare.com/articles/dataset/Integrated_analysis_of_human_transcriptome_data_for_Rett_syndrome_finds_a_network_of_involved_genes/7886671 <p><b>Objectives:</b> Rett syndrome (RTT) is a rare disorder causing severe intellectual and physical disability. The cause is a mutation in the gene coding for the methyl-CpG binding protein 2 (MECP2), a multifunctional regulator protein. Purpose of the study was integration and investigation of multiple gene expression profiles in human cells with impaired <i>MECP2</i> gene to obtain a robust, data-driven insight in molecular disease mechanisms.</p> <p><b>Methods:</b> Information about changed gene expression was extracted from five previously published studies, integrated and the resulting differentially expressed genes were analysed using overrepresentation analysis of biological pathways and gene ontology, and network analysis.</p> <p><b>Results:</b> We identified a set of genes, which are significantly changed not in all but several transcriptomics datasets and were not mentioned in the context of RTT before. We found that these genes are involved in several processes and molecular pathways known to be affected in RTT. Integrating transcription factors we identified a possible link how MECP2 regulates cytoskeleton organisation via MEF2C and CAPG.</p> <p><b>Conclusions:</b> Integrative analysis of omics data and prior knowledge databases is a powerful approach to identify links between mutation and phenotype especially in rare disease research where little data is available.</p>