ArticlePLoS computational biology2012
Novel approach to meta-analysis of microarray datasets reveals muscle remodeling-related drug targets and biomarkers in Duchenne muscular dystrophy.
Article in PLoS computational biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 2 of them syntheses that pooled it.
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Who cites it
37 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Comparative study of joint analysis of microarray gene expression data in survival prediction and risk assessment of breast cancer patients.Briefings in bioinformatics · 2016Pooled it
- Pooled it
- Advancing Biomarker Discovery and Therapeutic Targets in Duchenne Muscular Dystrophy: A Comprehensive Review.International journal of molecular sciences · 2024Review
- Molecular pathways involved in the control of contractile and metabolic properties of skeletal muscle fibers as potential therapeutic targets for Duchenne muscular dystrophy.Frontiers in physiology · 2024Review
- Regulation of Satellite Cells Functions during Skeletal Muscle Regeneration: A Critical Step in Physiological and Pathological Conditions.International journal of molecular sciences · 2023Review
- Identification of Key Genes and Biological Pathways Associated with Skeletal Muscle Maturation and Hypertrophy inAnimals : an open access journal from MDPI · 2022Article
- DETECTING MULTIPLE REPLICATING SIGNALS USING ADAPTIVE FILTERING PROCEDURES.Annals of statistics · 2022Article
- Plasma lipidomic analysis shows a disease progression signature in mdx mice.Scientific reports · 2021Article
- Investigating an increase in Florida manatee mortalities using a proteomic approach.Scientific reports · 2021Article
- Circadian Genes as Exploratory Biomarkers in DMD: Results From Both theFrontiers in physiology · 2021Article
- Longitudinal serum biomarker screening identifies malate dehydrogenase 2 as candidate prognostic biomarker for Duchenne muscular dystrophy.Journal of cachexia, sarcopenia and muscle · 2020Article
- Tumor Necrosis Factor Receptor SF10A (TNFRSF10A) SNPs Correlate With Corticosteroid Response in Duchenne Muscular Dystrophy.Frontiers in genetics · 2020Article
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- Gene expression profile and molecular pathway datasets resulting from benzo(a)pyrene exposure in the liver and testis of adult tilapia.Data in brief · 2018Article
- Skeletal Muscle Metabolism in Duchenne and Becker Muscular Dystrophy-Implications for Therapies.Nutrients · 2018Review
- Biomarkers of Duchenne muscular dystrophy: current findings.Degenerative neurological and neuromuscular disease · 2018Review
- DANUBE: Data-driven meta-ANalysis using UnBiased Empirical distributions-applied to biological pathway analysis.Proceedings of the IEEE. Institute of Electrical and Electronics Engineers · 2017Article
- Recessive mutations in the kinase ZAK cause a congenital myopathy with fibre type disproportion.Brain : a journal of neurology · 2017Article
- Transcriptomics analysis and hormonal changes of male and female neonatal rats treated chronically with a low dose of acrylamide in their drinking water.Toxicology reports · 2016Article
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5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Elucidation of new biomarkers and potential drug targets from high-throughput profiling data is a challenging task due to a limited number of available biological samples and questionable reproducibility of differential changes in cross-dataset comparisons. In this paper we propose a novel computational approach for drug and biomarkers discovery using comprehensive analysis of multiple expression profiling datasets.The new method relies on aggregation of individual profiling experiments combined with leave-one-dataset-out validation approach. Aggregated datasets were studied using Sub-Network Enrichment Analysis algorithm (SNEA) to find consistent statistically significant key regulators within the global literature-extracted expression regulation network. These regulators were linked to the consistent differentially expressed genes.We have applied our approach to several publicly available human muscle gene expression profiling datasets related to Duchenne muscular dystrophy (DMD). In order to detect both enhanced and repressed processes we considered up- and down-regulated genes separately. Applying the proposed approach to the regulators search we discovered the disturbance in the activity of several muscle-related transcription factors (e.g. MYOG and MYOD1), regulators of inflammation, regeneration, and fibrosis. Almost all SNEA-derived regulators of down-regulated genes (e.g. AMPK, TORC2, PPARGC1A) correspond to a single common pathway important for fast-to-slow twitch fiber type transition. We hypothesize that this process can affect the severity of DMD symptoms, making corresponding regulators and downstream genes valuable candidates for being potential drug targets and exploratory biomarkers.
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