Genomic abnormalities of the murine model of Fabry disease after disease-related perturbation, a systems biology approach

Abstract

Fabry disease is a disorder of ␣-D-galactosyl-containing glycolipids resulting from a deficiency of ␣-galactosidase A. Patients have a poorly understood vascular dysregulation. We hypothesized that disease-related perturbation by using enzyme replacement therapy in the murine model of Fabry disease would provide insight into abnormal biological processes in Fabry disease. Gene expression analyses of the heart, aorta, and liver of male ␣-galactosidase A knockout mice 28 weeks of age were compared with that of WT mice. Microarray analyses were performed before and after six weekly injections of ␣-galactosidase A. Alteration of Rpgrip1 ranked highest statistically in all three organs when knockout mice were compared with WT, and its splice variants responded in a unique way to ␣-galactosidase A. Enzyme replacement therapy tended to not only normalize gene expression, e.g., reduce the overexpression of securin, but also specifically modified gene expression in each tissue examined. Following multiple comparison analysis, gene expression correlation graphs were constructed, and a priori hypotheses were examined by using structural equation modeling. This systems biology approach demonstrated multiple and complex parallel cellular abnormalities in Fabry disease. These abnormalities form the basis for informed, in a Bayesian sense, sequential, hypothesis-driven research that can be subsequently tested experimentally.glycolipids ͉ growth factor ͉ lysosomal ͉ reactive oxygen species

Structural and functional plasticity of subcellular tethering, targeting and processing of RPGRIP1 by RPGR isoforms

“…Moreover, ablation of Rpgrip1 expression in the mouse recapitulates well the human disease by strongly suppressing the formation of the outer segments of photoreceptors and causing the rapid degeneration of these neurons and ultimately, blindness (Won et al, 2009). Rpgrip1 encodes various protein isoforms with differential expression across tissues (Ferreira, 2005; Roepman et al, 2000a) and the expression of some RPGRIP1 isoforms are pharmacologically modulated in mouse models of Fabry's disease (Moore et al, 2007). Among the RPGRIP1 isoforms identified, a large ∼175 kDa isoform, RPGRIP1α 1 , is specifically expressed in the retina and it is present in the connecting cilium and outer segments of photoreceptors, where it partially co-localizes with RPGR (Brunner et al, 2010; Castagnet et al, 2003; Ferreira, 2005; Mavlyutov et al, 2002; Roepman et al, 2000a).…”

Expression of genes and their responses to enzyme replacement therapy in a Fabry disease mouse model

“…As elevated levels of Gb3 and the clinical manifestation of Fabry disease are not necessarily correlated, there is a need to better understand the etiology of this disease and to identify biomarkers for diagnosis, monitoring disease progression and testing the effect of therapies in clinical trials. Moore et al reported a well-designed and systemic microarray study in which a Fabry disease mouse model was used (14). They reported that several important genes are involved in the pathogenesis of Fabry disease, including Rpgrp1, securin and Sod3, and demonstrated multiple and complex cellular abnormalities in this disease (14).…”

“…Moore et al reported a well-designed and systemic microarray study in which a Fabry disease mouse model was used (14). They reported that several important genes are involved in the pathogenesis of Fabry disease, including Rpgrp1, securin and Sod3, and demonstrated multiple and complex cellular abnormalities in this disease (14).…”

Ethanol modulation of gene networks: Implications for alcoholism

“…We have suggested here that the most informative network strategies, those most likely to predict functional gene/phenotype associations, are likely to be constructed from multiple types of data from both human and animal models. Coupling large scale phenotypic, genetic and genomic investigations across temporal and phenotypic space will allow productive use of approaches such as structural equation modeling (Moore et al 2007) in better defining network centrality and generating testable hypotheses. These informative lines of interpretation will critically depend on the continued development of large-scale bioinformatics resources that can help define temporal and spatial patterns of gene expression or other gene-gene interactions.…”