Dataset Information

Creation of a novel algorithm to identify patients with Becker and Duchenne muscular dystrophy within an administrative database and application of the algorithm to assess cardiovascular morbidity.

ABSTRACT: BACKGROUND:Outcome analyses in large administrative databases are ideal for rare diseases such as Becker and Duchenne muscular dystrophy. Unfortunately, Becker and Duchenne do not yet have specific International Classification of Disease-9/-10 codes. We hypothesised that an algorithm could accurately identify these patients within administrative data and improve assessment of cardiovascular morbidity. METHODS:Hospital discharges (n=13,189) for patients with muscular dystrophy classified by International Classification of Disease-9 code: 359.1 were identified from the Pediatric Health Information System database. An identification algorithm was created and then validated at three institutions. Multi-variable generalised linear mixed-effects models were used to estimate the associations of length of stay, hospitalisation cost, and 14-day readmission with age, encounter severity, and respiratory disease accounting for clustering within the hospital. RESULTS:The identification algorithm improved identification of patients with Becker and Duchenne from 55% (code 359.1 alone) to 77%. On bi-variate analysis, left ventricular dysfunction and arrhythmia were associated with increased cost of hospitalisation, length of stay, and mortality (p<0.001). After adjustment, Becker and Duchenne patients with left ventricular dysfunction and arrhythmia had increased length of stay with rate ratio 1.4 and 1.2 (p<0.001 and p=0.004) and increased cost of hospitalization with rate ratio 1.4 and 1.4 (both p<0.001). CONCLUSIONS:Our algorithm accurately identifies patients with Becker and Duchenne and can be used for future analysis of administrative data. Our analysis demonstrates the significant effects of cardiovascular disease on length of stay and hospitalisation cost in patients with Becker and Duchenne. Better recognition of the contribution of cardiovascular disease during hospitalisation with earlier more intensive evaluation and therapy may help improve outcomes in this patient population.

SUBMITTER: Soslow JH

PROVIDER: S-EPMC6433485 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Creation of a novel algorithm to identify patients with Becker and Duchenne muscular dystrophy within an administrative database and application of the algorithm to assess cardiovascular morbidity.

Soslow Jonathan H JH Hall Matthew M Burnette W Bryan WB Hor Kan K Chisolm Joanne J Spurney Christopher C Godown Justin J Xu Meng M Slaughter James C JC Markham Larry W LW

Cardiology in the young 20190126 3

<h4>Background</h4>Outcome analyses in large administrative databases are ideal for rare diseases such as Becker and Duchenne muscular dystrophy. Unfortunately, Becker and Duchenne do not yet have specific International Classification of Disease-9/-10 codes. We hypothesised that an algorithm could accurately identify these patients within administrative data and improve assessment of cardiovascular morbidity.<h4>Methods</h4>Hospital discharges (n=13,189) for patients with muscular dystrophy clas ...[more]

PMID: 30683166

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Project description:BackgroundDuchenne muscular dystrophy (DMD) and Becker muscular dystrophy (BMD) are characterized by muscle wasting leading to loss of ambulation in the first or third decade, respectively. In DMD, the lack of dystrophin hampers connections between intracellular cytoskeleton and cell membrane leading to repeated cycles of necrosis and regeneration associated with inflammation and loss of muscle ordered structure. BMD has a similar muscle phenotype but milder. Here, we address the question whether proteins at variance in BMD compared with DMD contribute to the milder phenotype in BMD, thus identifying a specific signature to be targeted for DMD treatment.MethodsProteins extracted from skeletal muscle from DMD/BMD patients and young healthy subjects were either reduced and solubilized prior two-dimensional difference in gel electrophoresis/mass spectrometry differential analysis or tryptic digested prior label-free liquid chromatography with tandem mass spectrometry. Statistical analyses of proteins and peptides were performed by DeCyder and Perseus software and protein validation and verification by immunoblotting.ResultsProteomic results indicate minor changes in the extracellular matrix (ECM) protein composition in BMD muscles with retention of mechanotransduction signalling, reduced changes in cytoskeletal and contractile proteins. Conversely, in DMD patients, increased levels of several ECM cytoskeletal and contractile proteins were observed whereas some proteins of fast fibres and of Z-disc decreased. Detyrosinated alpha-tubulin was unchanged in BMD and increased in DMD although neuronal nitric oxide synthase was unchanged in BMD and greatly reduced in DMD. Metabolically, the tissue is characterized by a decrement of anaerobic metabolism both in DMD and BMD compared with controls, with increased levels of the glycogen metabolic pathway in BMD. Oxidative metabolism is severely compromised in DMD with impairment of malate shuttle; conversely, it is active in BMD supporting the tricarboxylic acid cycle and respiratory chain. Adipogenesis characterizes DMD, whereas proteins involved in fatty acids beta-oxidation are increased in BMD. Proteins involved in protein/amino acid metabolism, cell development, calcium handling, endoplasmic reticulum/sarcoplasmic reticulum stress response, and inflammation/immune response were increased in DMD. Both disorders are characterized by the impairment of N-linked protein glycosylation in the endoplasmic reticulum. Authophagy was decreased in DMD whereas it was retained in BMD.ConclusionsThe mechanosensing and metabolic disruption are central nodes of DMD/BMD phenotypes. The ECM proteome composition and the metabolic rewiring in BMD lead to preservation of energy levels supporting autophagy and cell renewal, thus promoting the retention of muscle function. Conversely, DMD patients are characterized by extracellular and cytoskeletal protein dysregulation and by metabolic restriction at the level of ?-ketoglutarate leading to shortage of glutamate-derived molecules that over time triggers lipogenesis and lipotoxicity.

Project description:BACKGROUND:Duchenne Muscular Dystrophy (DMD) is the most common muscle disease in children, and there are no effective therapies for DMD or Becker Muscular Dystrophy (BMD). Currently, targeted gene therapy treatments have emerged. As a result, genetic diagnosis is the basis of treatment. In addition, genetic and prenatal diagnosis significantly reduces their incidence rates. This study combines the application of multiplex ligation-dependent probe amplification technology (MLPA) and "next-generation" sequencing technology (NGS) as the most economical and efficient method of diagnosis. Therefore, in the diagnosis of DMD/BMD, patients' MLPA data are first used to detect DMD gene deletions or duplications, and NGS and Sanger sequencing are then applied to exclude MLPA-negative samples. Meanwhile, polymerase chain reaction (PCR) is used to detect single exon deletions to exclude false-positives in MLPA caused by point mutations. METHODS:In this study, we recruited 1051 proband families of DMD from 2016 to 2018 and had access to information that could identify individual participants during or after data collection. Patients who were diagnosed with DMD were first tested by MLPA. MLPA results with single exon deletions were validated with PCR amplification and Sanger sequencing. The negative results of MLPA were further analysed with NGS and validated by Sanger sequencing. For novel missense mutations, phenotype-genotype correlations were analysed using PolyPhen2 and mutation taster. All methods were performed in accordance with the relevant guidelines and regulations. RESULTS:DMD mutations were identified in 1029 families (97.91%, 1029/1051). Large deletions, duplications, and small mutations accounted for 70.41% (740/1051), 8.28% (87/1051), and 19.12% (201/1051) of all cases, respectively. There were 205 small mutation types, 53 of which were novel. The rate of de novo mutations was 39.45% (187/474) and was higher in large duplications (49.53%, 157/317). Among 68 asymptomatic patients (<?3?years old) with unexplained persistent hyperCKaemia upon conventional physical examination, 63 were diagnosed as DMD/BMD according to genetic diagnosis. CONCLUSION:Our results expand the spectrum of DMD mutations, which could contribute to the treatment of DMD/BMD and provide an effective diagnosis method. Thus, the combination of MLPA, NGS and Sanger sequencing is of great significance for family analysis, gene diagnosis and gene therapy.

Project description:BackgroundThe goal of this study is to identify the hub genes for Duchenne muscular dystrophy (DMD) and Becker muscular dystrophy (BMD) via weighted correlation network analysis (WGCNA).MethodsThe gene expression profile of vastus lateralis biopsy samples obtained in 17 patients with DMD, 11 patients with BMD and 6 healthy individuals was downloaded from the Gene Expression Omnibus (GEO) database (GSE109178). After obtaining different expressed genes (DEGs) via GEO2R, WGCNA was conducted using R package, modules and genes that highly associated with DMD, BMD, and their age or pathology were screened. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) enrichment analysis and protein-protein interaction (PPI) network analysis were also conducted. Hub genes and highly correlated clustered genes were identified using Search Tool for the Retrieval of Interacting Genes (STRING) and Cystoscape software.ResultsOne thousand four hundred seventy DEGs were identified between DMD and control, with 1281 upregulated and 189 downregulated DEGs. Four hundred and twenty DEGs were found between BMD and control, with 157 upregulated and 263 upregulated DEGs. Fourteen modules with different colors were identified for DMD vs control, and 7 modules with different colors were identified for BMD vs control. Ten hub genes were summarized for DMD and BMD respectively, 5 hub genes were summarized for BMD age, 5 and 3 highly correlated clustered genes were summarized for DMD age and BMD pathology, respectively. In addition, 20 GO enrichments were found to be involved in DMD, 3 GO enrichments were found to be involved in BMD, 3 GO enrichments were found to be involved in BMD age.ConclusionIn DMD, several hub genes were identified: C3AR1, TLR7, IRF8, FYB and CD33(immune and inflammation associated genes), TYROBP, PLEK, AIF1(actin reorganization associated genes), LAPTM5 and NT5E(cell death and arterial calcification associated genes, respectively). In BMD, a number of hub genes were identified: LOX, ELN, PLEK, IKZF1, CTSK, THBS2, ADAMTS2, COL5A1(extracellular matrix associated genes), BCL2L1 and CDK2(cell cycle associated genes).

Dataset Information

Creation of a novel algorithm to identify patients with Becker and Duchenne muscular dystrophy within an administrative database and application of the algorithm to assess cardiovascular morbidity.

Publications

Creation of a novel algorithm to identify patients with Becker and Duchenne muscular dystrophy within an administrative database and application of the algorithm to assess cardiovascular morbidity.

Similar Datasets

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