Dataset Information

Distinctive patterns of microRNA expression in primary muscular disorders.

ABSTRACT: The primary muscle disorders are a diverse group of diseases caused by various defective structural proteins, abnormal signaling molecules, enzymes and proteins involved in posttranslational modifications, and other mechanisms. Although there is increasing clarification of the primary aberrant cellular processes responsible for these conditions, the decisive factors involved in the secondary pathogenic cascades are still mainly obscure. Given the emerging roles of microRNAs (miRNAs) in modulation of cellular phenotypes, we searched for miRNAs regulated during the degenerative process of muscle to gain insight into the specific regulation of genes that are disrupted in pathological muscle conditions. We describe 185 miRNAs that are up- or down-regulated in 10 major muscular disorders in humans [Duchenne muscular dystrophy (DMD), Becker muscular dystrophy, facioscapulohumeral muscular dystrophy, limb-girdle muscular dystrophies types 2A and 2B, Miyoshi myopathy, nemaline myopathy, polymyositis, dermatomyositis, and inclusion body myositis]. Although five miRNAs were found to be consistently regulated in almost all samples analyzed, pointing to possible involvement of a common regulatory mechanism, others were dysregulated only in one disease and not at all in the other disorders. Functional correlation between the predicted targets of these miRNAs and mRNA expression demonstrated tight posttranscriptional regulation at the mRNA level in DMD and Miyoshi myopathy. Together with direct mRNA-miRNA predicted interactions demonstrated in DMD, some of which are involved in known secondary response functions and others that are involved in muscle regeneration, these findings suggest an important role of miRNAs in specific physiological pathways underlying the disease pathology.

SUBMITTER: Eisenberg I

PROVIDER: S-EPMC2040449 | biostudies-literature | 2007 Oct

REPOSITORIES: biostudies-literature

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Distinctive patterns of microRNA expression in primary muscular disorders.

Eisenberg Iris I Eran Alal A Nishino Ichizo I Moggio Maurizio M Lamperti Costanza C Amato Anthony A AA Lidov Hart G HG Kang Peter B PB North Kathryn N KN Mitrani-Rosenbaum Stella S Flanigan Kevin M KM Neely Lori A LA Whitney Duncan D Beggs Alan H AH Kohane Isaac S IS Kunkel Louis M LM

Proceedings of the National Academy of Sciences of the United States of America 20071017 43

The primary muscle disorders are a diverse group of diseases caused by various defective structural proteins, abnormal signaling molecules, enzymes and proteins involved in posttranslational modifications, and other mechanisms. Although there is increasing clarification of the primary aberrant cellular processes responsible for these conditions, the decisive factors involved in the secondary pathogenic cascades are still mainly obscure. Given the emerging roles of microRNAs (miRNAs) in modulatio ...[more]

PMID: 17942673

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Project description:BackgroundParkinson's Disease (PD) varies widely among individuals, and Artificial Intelligence (AI) has recently helped to identify three disease progression subtypes. While their clinical features are already known, their gene expression profiles remain unexplored.ObjectivesThe objectives of this study were (1) to describe the transcriptomics characteristics of three PD progression subtypes identified by AI, and (2) to evaluate if gene expression data can be used to predict disease subtype at baseline.DesignThis is a retrospective longitudinal cohort study utilizing the Parkinson's Progression Markers Initiative (PPMI) database.MethodsWhole blood RNA-Sequencing data underwent differential gene expression analysis, followed by multiple pathway analyses. A Machine Learning (ML) classifier, namely XGBoost, was trained using data from multiple modalities, including gene expression values.ResultsOur study identified differentially expressed genes (DEGs) that were uniquely associated with Parkinson's disease (PD) progression subtypes. Importantly, these DEGs had not been previously linked to PD. Gene-pathway analysis revealed both distinct and shared characteristics between the subtypes. Notably, two subtypes displayed opposite expression patterns for pathways involved in immune response alterations. In contrast, the third subtype exhibited a more unique profile characterized by increased expression of genes related to detoxification processes. All three subtypes showed a significant modulation of pathways related to the regulation of gene expression, metabolism, and cell signaling. ML revealed that the progression subtype with the worst prognosis can be predicted at baseline with 0.877 AUROC, yet the contribution of gene expression was marginal for the prediction of the subtypes.ConclusionThis study provides novel information regarding the transcriptomics profiles of PD progression subtypes, which may foster precision medicine with relevant indications for a finer-grained diagnosis and prognosis.

Dataset Information

Distinctive patterns of microRNA expression in primary muscular disorders.

Publications

Distinctive patterns of microRNA expression in primary muscular disorders.

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