The proposed research is for the fourth competitive renewal of a long-term project to define the molecular basis of the muscular dystrophies. Previous awards have been used to define novel causes of muscular dystrophy, conduct genotype/phenotype correlations, probe molecular mechanisms of the different types, and to develop sensitive and specific molecular tests. During the previous award period, the applicant turned to genome-wide expression profiling of patient muscle biopsy RNA to interrogate both molecular pathophysiology of Duchenne muscular dystrophy, as well as continuing work on new genetic causes of muscular dystrophy. The new preliminary data on a 128 muscle biopsy whole-genome (U133A/B) profiling study demonstrates proof of principle that novel biochemical pathways can be defined using large scale data modeling and statistical analyses. Specifically, the investigators define a temporal pathway of Lamin A/C-Rb-MyoD in muscle regeneration that is specifically perturbed in Emery-Dreifuss muscular dystrophy. The proposed aims are to extend this data analysis into the poorly defined and heterogeneous Limb-girdle muscular dystrophy group of disorders. This new application is very heavily oriented towards large-scale data generation, data modeling and statistical analyses.
The specific aims are: 1. to develop mRNA fingerprints diagnostic of the most common known causes of limb-girdle muscular dystrophy (LGMD); 2. to define biochemical pathways for Limb-girdle muscular dystrophy from the profiling data, as has been done for Emery-Dreifuss dystrophy; 3. extend data modeling into the definition of novel diagnostic categories of LGMD. The proposed research will be conducted by a collaborative team of molecular geneticists (Drs. Hoffman, Bakay, Zhao), and data modeling and statistical computer scientists and electrical engineers (Drs. Wang, Xuan, Miller). Importantly, all data will be released to the public via a highly evolved web database portal developed by the PI's lab (PEPR), including web-based dynamic data analysis tools.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS029525-15
Application #
7224192
Study Section
Special Emphasis Panel (ZRG1-MABS (01))
Program Officer
Porter, John D
Project Start
1991-01-01
Project End
2010-02-28
Budget Start
2007-03-01
Budget End
2008-02-29
Support Year
15
Fiscal Year
2007
Total Cost
$559,206
Indirect Cost
Name
Children's Research Institute
Department
Type
DUNS #
143983562
City
Washington
State
DC
Country
United States
Zip Code
20010
Punetha, Jaya; Kesari, Akanchha; Hoffman, Eric P et al. (2017) Novel Col12A1 variant expands the clinical picture of congenital myopathies with extracellular matrix defects. Muscle Nerve 55:277-281
Many, Gina M; Yokosaki, Yasuyuki; Uaesoontrachoon, Kitipong et al. (2016) OPN-a induces muscle inflammation by increasing recruitment and activation of pro-inflammatory macrophages. Exp Physiol 101:1285-1300
Perovanovic, Jelena; Dell'Orso, Stefania; Gnochi, Viola F et al. (2016) Laminopathies disrupt epigenomic developmental programs and cell fate. Sci Transl Med 8:335ra58
Chen, Xi; Jung, Jin-Gyoung; Shajahan-Haq, Ayesha N et al. (2016) ChIP-BIT: Bayesian inference of target genes using a novel joint probabilistic model of ChIP-seq profiles. Nucleic Acids Res 44:e65
Punetha, Jaya; Mansoor, Simin; Bertorini, Tulio E et al. (2016) Somatic mosaicism due to a reversion variant causing hemi-atrophy: a novel variant of dystrophinopathy. Eur J Hum Genet 24:1511-4
Willkomm, Lena; Heredia, Raul; Hoffmann, Katrin et al. (2016) Homozygous mutation in Atlastin GTPase 1 causes recessive hereditary spastic paraplegia. J Hum Genet 61:571-3
O'Grady, Gina L; Lek, Monkol; Lamande, Shireen R et al. (2016) Diagnosis and etiology of congenital muscular dystrophy: We are halfway there. Ann Neurol 80:101-11
Punetha, Jaya; Kesari, Akanchha; Uapinyoying, Prech et al. (2016) Targeted Re-Sequencing Emulsion PCR Panel for Myopathies: Results in 94 Cases. J Neuromuscul Dis 3:209-225
Wang, Niya; Hoffman, Eric P; Chen, Lulu et al. (2016) Mathematical modelling of transcriptional heterogeneity identifies novel markers and subpopulations in complex tissues. Sci Rep 6:18909
Wang, Niya; Gong, Ting; Clarke, Robert et al. (2015) UNDO: a Bioconductor R package for unsupervised deconvolution of mixed gene expressions in tumor samples. Bioinformatics 31:137-9

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