Dataset Information

A Proteomics-Based Analysis Reveals Predictive Biological Patterns in Fabry Disease.

ABSTRACT: Background: Fabry disease (FD) is an X-linked progressive lysosomal disease (LD) due to glycosphingolipid metabolism impairment. Currently, plasmatic globotriaosylsphingosine (LysoGb3) is used for disease diagnosis and monitoring. However, this biomarker is inconstantly increased in mild forms and in some female patients. Materials and Methods: We applied a targeted proteomic approach to explore disease-related biological patterns that might explain the disease pathophysiology. Forty proteins, involved mainly in inflammatory and angiogenesis processes, were assessed in 69 plasma samples retrieved from the French Fabry cohort (FFABRY) and from 83 healthy subjects. For predictive performance assessment, we also included other LD samples (Gaucher, Pompe and Niemann Pick C). Results: The study yielded four discriminant proteins that include three angiogenesis proteins (fibroblast growth factor 2 (FGF2), vascular endothelial growth factor A (VEGFA), vascular endothelial growth factor C (VEGFC)) and one cytokine interleukin 7 (IL-7). A clear elevation of FGF2 and IL-7 concentrations was observed in FD compared to other LD samples. No correlation was observed between these proteins and globotriaosylsphingosine (LysoGb3). A significant correlation exists between IL-7 and residual enzyme activity in a non-classical phenotype. This highlights the orthogonal biological information yielded by these proteins that might help in stratifying Fabry patients. Conclusion: This work highlights the potential of using proteomics approaches in exploring FD and enhancing FD diagnosis and therapeutic monitoring performances.

SUBMITTER: Tebani A

PROVIDER: S-EPMC7290805 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Proteomics-Based Analysis Reveals Predictive Biological Patterns in Fabry Disease.

Tebani Abdellah A Mauhin Wladimir W Abily-Donval Lenaig L Lesueur Céline C Berger Marc G MG Nadjar Yann Y Berger Juliette J Benveniste Oliver O Lamari Foudil F Laforêt Pascal P Noel Esther E Marret Stéphane S Lidove Olivier O Bekri Soumeya S

Journal of clinical medicine 20200502 5

Background: Fabry disease (FD) is an X-linked progressive lysosomal disease (LD) due to glycosphingolipid metabolism impairment. Currently, plasmatic globotriaosylsphingosine (LysoGb3) is used for disease diagnosis and monitoring. However, this biomarker is inconstantly increased in mild forms and in some female patients. Materials and Methods: We applied a targeted proteomic approach to explore disease-related biological patterns that might explain the disease pathophysiolo ...[more]

PMID: 32370284

Similar Datasets

Project description:BackgroundA huge amount of associations among different biological entities (e.g., disease, drug, and gene) are scattered in millions of biomedical articles. Systematic analysis of such heterogeneous data can infer novel associations among different biological entities in the context of personalized medicine and translational research. Recently, network-based computational approaches have gained popularity in investigating such heterogeneous data, proposing novel therapeutic targets and deciphering disease mechanisms. However, little effort has been devoted to investigating associations among drugs, diseases, and genes in an integrative manner.ResultsWe propose a novel network-based computational framework to identify statistically over-expressed subnetwork patterns, called network motifs, in an integrated disease-drug-gene network extracted from Semantic MEDLINE. The framework consists of two steps. The first step is to construct an association network by extracting pair-wise associations between diseases, drugs and genes in Semantic MEDLINE using a domain pattern driven strategy. A Resource Description Framework (RDF)-linked data approach is used to re-organize the data to increase the flexibility of data integration, the interoperability within domain ontologies, and the efficiency of data storage. Unique associations among drugs, diseases, and genes are extracted for downstream network-based analysis. The second step is to apply a network-based approach to mine the local network structure of this heterogeneous network. Significant network motifs are then identified as the backbone of the network. A simplified network based on those significant motifs is then constructed to facilitate discovery. We implemented our computational framework and identified five network motifs, each of which corresponds to specific biological meanings. Three case studies demonstrate that novel associations are derived from the network topology analysis of reconstructed networks of significant network motifs, further validated by expert knowledge and functional enrichment analyses.ConclusionsWe have developed a novel network-based computational approach to investigate the heterogeneous drug-gene-disease network extracted from Semantic MEDLINE. We demonstrate the power of this approach by prioritizing candidate disease genes, inferring potential disease relationships, and proposing novel drug targets, within the context of the entire knowledge. The results indicate that such approach will facilitate the formulization of novel research hypotheses, which is critical for translational medicine research and personalized medicine.

Project description:BackgroundBiological heart age estimation can provide insights into cardiac aging. However, existing studies do not consider differential aging across cardiac regions.PurposeTo estimate biological age of the left ventricle (LV), right ventricle (RV), myocardium, left atrium, and right atrium using magnetic resonance imaging radiomics phenotypes and to investigate determinants of aging by cardiac region.Study typeCross-sectional.PopulationA total of 18,117 healthy UK Biobank participants including 8338 men (mean age = 64.2 ± 7.5) and 9779 women (mean age = 63.0 ± 7.4).Field strength/sequenceA 1.5 T/balanced steady-state free precession.AssessmentAn automated algorithm was used to segment the five cardiac regions, from which radiomic features were extracted. Bayesian ridge regression was used to estimate biological age of each cardiac region with radiomics features as predictors and chronological age as the output. The "age gap" was the difference between biological and chronological age. Linear regression was used to calculate associations of age gap from each cardiac region with socioeconomic, lifestyle, body composition, blood pressure and arterial stiffness, blood biomarkers, mental well-being, multiorgan health, and sex hormone exposures (n = 49).Statistical testMultiple testing correction with false discovery method (threshold = 5%).ResultsThe largest model error was with RV and the smallest with LV age (mean absolute error in men: 5.26 vs. 4.96 years). There were 172 statistically significant age gap associations. Greater visceral adiposity was the strongest correlate of larger age gaps, for example, myocardial age gap in women (Beta = 0.85, P = 1.69 × 10-26 ). Poor mental health associated with large age gaps, for example, "disinterested" episodes and myocardial age gap in men (Beta = 0.25, P = 0.001), as did a history of dental problems (eg LV in men Beta = 0.19, P = 0.02). Higher bone mineral density was the strongest associate of smaller age gaps, for example, myocardial age gap in men (Beta = -1.52, P = 7.44 × 10-6 ).Data conclusionThis work demonstrates image-based heart age estimation as a novel method for understanding cardiac aging.Evidence level1.Technical efficacyStage 1.

Project description:Fabry disease (FD) is a progressive, X-linked inherited disorder of glycosphingolipid metabolism due to deficient or absent lysosomal α-galactosidase A activity. FD is pan-ethnic and the reported annual incidence of 1 in 100,000 may underestimate the true prevalence of the disease. Classically affected hemizygous males, with no residual α-galactosidase A activity may display all the characteristic neurological (pain), cutaneous (angiokeratoma), renal (proteinuria, kidney failure), cardiovascular (cardiomyopathy, arrhythmia), cochleo-vestibular and cerebrovascular (transient ischemic attacks, strokes) signs of the disease while heterozygous females have symptoms ranging from very mild to severe. Deficient activity of lysosomal α-galactosidase A results in progressive accumulation of globotriaosylceramide within lysosomes, believed to trigger a cascade of cellular events. Demonstration of marked α-galactosidase A deficiency is the definitive method for the diagnosis of hemizygous males. Enzyme analysis may occasionnally help to detect heterozygotes but is often inconclusive due to random X-chromosomal inactivation so that molecular testing (genotyping) of females is mandatory. In childhood, other possible causes of pain such as rheumatoid arthritis and 'growing pains' must be ruled out. In adulthood, multiple sclerosis is sometimes considered. Prenatal diagnosis, available by determination of enzyme activity or DNA testing in chorionic villi or cultured amniotic cells is, for ethical reasons, only considered in male fetuses. Pre-implantation diagnosis is possible. The existence of atypical variants and the availability of a specific therapy singularly complicate genetic counseling. A disease-specific therapeutic option - enzyme replacement therapy using recombinant human α-galactosidase A - has been recently introduced and its long term outcome is currently still being investigated. Conventional management consists of pain relief with analgesic drugs, nephroprotection (angiotensin converting enzyme inhibitors and angiotensin receptors blockers) and antiarrhythmic agents, whereas dialysis or renal transplantation are available for patients experiencing end-stage renal failure. With age, progressive damage to vital organ systems develops and at some point, organs may start to fail in functioning. End-stage renal disease and life-threatening cardiovascular or cerebrovascular complications limit life-expectancy of untreated males and females with reductions of 20 and 10 years, respectively, as compared to the general population. While there is increasing evidence that long-term enzyme therapy can halt disease progression, the importance of adjunctive therapies should be emphasized and the possibility of developing an oral therapy drives research forward into active site specific chaperones.

Project description:Neurodegenerative diseases are often defined pathologically by the presence of protein aggregates. These aggregates, including amyloid plaques in Alzheimer's disease (AD), result from the abnormal accumulation and processing of proteins, and may ultimately lead to neuronal dysfunction and cell death. To date, conventional biochemical studies have revealed abundant core components in protein aggregates. However, rapidly improving proteomics technologies offer opportunities to revisit pathologic aggregate composition, and to identify less abundant but potentially important functional molecules that participate in neurodegeneration. The purpose of this study was to establish a proteomic strategy for the profiling of neurodegenerative disease tissues for disease-specific changes in protein abundance. Using high resolution liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS), we analyzed detergent-insoluble frontal cortex samples from AD and unaffected control cases. In addition, we analyzed samples from frontotemporal lobar degeneration (FTLD) cases to identify AD-specific changes not present in other neurodegenerative diseases. We used a labeling-free quantification technique to compare the abundance of identified peptides in the samples based on extracted ion current (XIC) of their corresponding ions. Of the 512 identified proteins, quantitation demonstrated significant changes in 81 AD-specific proteins. Following additional manual filtering, 11 proteins were accepted with high confidence as increased in AD compared to control and FTLD brains, including beta-amyloid, tau and apolipoprotein E, all well-established AD-linked proteins. In addition, we identified and validated the presence of serine protease 15, ankyrin B, and 14-3-3 eta in the detergent-insoluble fraction. Our results provide further evidence for the capacity of proteomics applications to identify conserved sets of disease-specific proteins in AD, to enhance our understanding of disease pathogenesis, and to deliver new candidates for the development of effective therapies for this, and other, devastating neurodegenerative disorders.

Dataset Information

A Proteomics-Based Analysis Reveals Predictive Biological Patterns in Fabry Disease.

Publications

A Proteomics-Based Analysis Reveals Predictive Biological Patterns in Fabry Disease.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets