Abstract:Fabry disease (FD) is a rare X-linked recessive genetic disorder caused by a deficient activity of the lysosomal enzyme alpha-galactosidase A (GLA) and is characterised by intra-lysosomal accumulation of globotriaosylceramide (Gb3). We performed a meta-analysis of peer-reviewed publications including high-throughput omics technologies including naïve patients and those undergoing enzyme replacement therapy (ERT). This study describes FD on a systems level using a systems biology approach, in which molecular da… Show more
“…9 ) were combined and a final hypothesis was generated using validation by deep-mining of the literature. The description and citation of the previous tools and software solutions used in this integrative systems biology pipeline can be found elsewhere 48 , otherwise they are cited within text. Figure 9 Summary of the methodology followed in this study.…”
Multiple sclerosis (MS) is a chronic autoimmune disorder characterized by inflammatory-demyelinating events in the central nervous system. Despite more than 40 years of MS research its aetiology remains unknown. This study aims to identify the most frequently reported and consistently regulated molecules in MS in order to generate molecular interaction networks and thereby leading to the identification of deregulated processes and pathways which could give an insight of the underlying molecular mechanisms of MS. Driven by an integrative systems biology approach, gene-expression profiling datasets were combined and stratified into “Non-treated” and “Treated” groups and additionally compared to other disease patterns. Molecular identifiers from dataset comparisons were matched to our Multiple Sclerosis database (MuScle; www.padb.org/muscle). From 5079 statistically significant molecules, correlation analysis within groups identified a panel of 16 high-confidence genes unique to the naïve MS phenotype, whereas the “Treated” group reflected a common pattern associated with autoimmune disease. Pathway and gene-ontology clustering identified the Interferon gamma signalling pathway as the most relevant amongst all significant molecules, and viral infections as the most likely cause of all down-stream events observed. This hypothesis-free approach revealed the most significant molecular events amongst different MS phenotypes which can be used for further detailed studies.
“…9 ) were combined and a final hypothesis was generated using validation by deep-mining of the literature. The description and citation of the previous tools and software solutions used in this integrative systems biology pipeline can be found elsewhere 48 , otherwise they are cited within text. Figure 9 Summary of the methodology followed in this study.…”
Multiple sclerosis (MS) is a chronic autoimmune disorder characterized by inflammatory-demyelinating events in the central nervous system. Despite more than 40 years of MS research its aetiology remains unknown. This study aims to identify the most frequently reported and consistently regulated molecules in MS in order to generate molecular interaction networks and thereby leading to the identification of deregulated processes and pathways which could give an insight of the underlying molecular mechanisms of MS. Driven by an integrative systems biology approach, gene-expression profiling datasets were combined and stratified into “Non-treated” and “Treated” groups and additionally compared to other disease patterns. Molecular identifiers from dataset comparisons were matched to our Multiple Sclerosis database (MuScle; www.padb.org/muscle). From 5079 statistically significant molecules, correlation analysis within groups identified a panel of 16 high-confidence genes unique to the naïve MS phenotype, whereas the “Treated” group reflected a common pattern associated with autoimmune disease. Pathway and gene-ontology clustering identified the Interferon gamma signalling pathway as the most relevant amongst all significant molecules, and viral infections as the most likely cause of all down-stream events observed. This hypothesis-free approach revealed the most significant molecular events amongst different MS phenotypes which can be used for further detailed studies.
“…In general, the lower the intrinsic enzyme activity of the causative AGAL mutation, the more severe is the overall clinical phenotype, the earlier is the onset of clinical manifestations, and the more extensive is the organ involvement 69. However, the wide phenotypic variability observed among patients with the same GLA mutation, even when they are related males, illustrates the complexity of the genotype-to-phenotype correlations in FD and the need to consider additional genetic and environmental modulating factors for their proper understanding 7,18…”
Section: Clinical Phenotypes and Their Pathology Correlatesmentioning
confidence: 99%
“…Overall, FD can be conceived as a multidomain disease phenotype, where each of the component domains is the laboratory or clinical expression of the causative GLA mutation along a complex pathophysiologic cascade pathway (Figure 1). 18 The phenotypic domains that more closely mirror the genotypic effect are the enzymatic and the storage phenotypes, while the clinical phenotype is most influenced by additional genetic systems and environmental modulators and is critically dependent on age and gender 1–3. Because of the modulating effect of X-chromosome inactivation in the expression of X-linked diseases in females,19 the clinical phenotype and the natural history of FD should be defined in affected males, who have homogeneous tissue expression of the AGAL deficiency.…”
Fabry disease (FD) is a rare X-linked glycosphingolipidosis resulting from deficient α-galactosidase A (AGAL) activity, caused by pathogenic mutations in the GLA gene. In males, the multisystemic involvement and the severity of tissue injury are critically dependent on the level of AGAL residual enzyme activity (REA) and on the metabolic load of the disease, but organ susceptibility to damage varies widely, with heart appearing as the most vulnerable to storage pathology, even with relatively high REA. The expression of FD can be conceived as a multidomain phenotype, where each of the component domains is the laboratory or clinical expression of the causative GLA mutation along a complex pathophysiologic cascade pathway. The AGAL enzyme activity is the most clinically useful marker of the protein phenotype. The metabolic phenotype and the pathologic phenotype are diverse expressions of the storage pathology, respectively, assessed by biochemical and histological/ultrastructural methods. The storage phenotypes are the direct consequences of enzyme deficiency and hence, together with the enzymatic phenotype, constitute the more specific diagnostic markers of FD. In the pathophysiology cascade, the clinical phenotypes are most distantly linked to the underlying genetic causation, being critically influenced by the patients' gender and age, and modulated by the effects of variation in other genetic loci, of polygenic inheritance and of environmental risk factors. A major challenge in the clinical phenotyping of patients with FD is the differential diagnosis between its nonspecific, later-onset complications, particularly the cerebrovascular, cardiac and renal, and similar chronic illnesses that are common in the general population. Comprehensive phenotyping, whenever possible performed in hemizygous males, is therefore crucial for grading the severity of pathogenic GLA variants, to clarify the phenotypic correlations of hypomorphic alleles, to define benign polymorphisms, as well as to establish the pathogenicity of variants of uncertain significance.
“…The bottom‐up systems biology approach examines the mechanisms through which functional properties arise in the interactions of known components . Systems biology has been successfully applied in a wide spectrum of biomedical research and has improved our understanding of neurodegenerative, cancer, inflammatory and genetic diseases …”
Section: Introductionmentioning
confidence: 99%
“…8 Systems biology has been successfully applied in a wide spectrum of biomedical research and has improved our understanding of neurodegenerative, 9 cancer, 10 inflammatory 11 and genetic diseases. 12 A system biology approach based on integrating multiple omics data types along the genome-phenome regulatory cascades can be a well-suited approach for DKD because it provides a comprehensive view of the disease pathophysiology cutting across multiple organ system in a chronic disease process. Although systems biology approaches have just recently been deployed to DKD, studies so far have made an impact by advancing the understanding of the molecular mechanisms underlying DKD pathogenesis.…”
Current therapeutic approaches are ineffective in many patients with established Diabetic Kidney Disease (DKD) disease, an epidemic affecting one in three patients with diabetes. Early identification of patients at high risk for progression and individualizing therapies have the potential to mitigate kidney complications due to diabetes. To achieve this, a better understanding of the complex pathophysiology of DKD is needed. A system biology approach integrating large scale omic data is well suited to unravel the molecular mechanisms driving DKD and may offer new perspectives how to personalize therapy. Recent studies indeed demonstrate that integrating genome scale data sets generated from prospectively designed clinical cohort studies with model systems using innovative bioinformatics analysis revealed critical molecular pathways in DKD and led to the development of candidate prognostic molecular biomarkers. This review seeks to provide an overview of the recent progress in the application of the integrative systems biology approaches specifically in the field of molecular biomarkers for DKD. We will mainly focus the discussion on how to use integrative system biology approach to firstly identify patients at high risk of progression, and secondly to identify patients who may or may not respond to treatment. Challenges and opportunities in applying precision medicine in DKD will also be discussed.
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