Mitochondrial disease is a commonly occurring inherited condition, incidence 1/5000, which can affect every organ system and thus exhibits a broad range of clinical phenotypes. The most common are neurological and neuromuscular dysfunction that manifest as neurodegeneration, seizures, ataxia, chronic progressive external opthalmoplegia (CPEO), and hypotonia. Childhood-onset mitochondrial disease most often results from recessive e mutations in the nuclear genome; however, the vast majority of cases remain without a molecular diagnosis and no effective treatments thus underscoring the critical need to identify the genetic aberrations driving these disorders. We propose a personalized functional genomics approach combining genome-wide sequencing, mitochondrial functional profiling in patient cells, and functional genomics to identify validated novel mitochondrial disease genes. We will comprehensively assess the spectrum of genetic variation contributing to childhood-onset mitochondrial encephalopathy through sequencing whole exomes in 200 cases. These cases will be selected from our cohort of over 800 fibroblast cell lines from patients that have been assessed for electron transport chain activity (ETC) and have been pre-screened and shown to be negative for known mitochondrial and nuclear gene mutations. Sequence data will be analyzed by our custom bioinformatics pipeline, AthenaVar, that annotates and prioritizes variants for functional studies. Gene causality will be determined through RNAi knock down, cDNA complementation studies and mitochondrial functional profiling in patient and rescued cells. Additionally, we have innovated a first-in-kind lentiviral vector that delivers a shRNA and cDNA which we will use to simultaneously knock down the endogenous 'healthy' copy of a gene of interest and deliver a mutant copy of the same gene into healthy cells. We will utilize this technology to test the functionality of variants of uncertain significance identified in our sequencing efforts as well as those obtained through collaborators, the BCM diagnostic laboratory, and the public domain. The power of our innovative combination of patient exome sequencing with mitochondrial functional profiling and functional genomics studies will propel this work beyond the bioinformatics stop gap that most disease gene discovery studies experience. This work will generate an unprecedented resource of primary mitochondrial disease patients with complete exome sequence data, systematic profiling of cellular mitochondrial function, and functionally-confirmed pathogenic molecular defects. The elucidation of these pathogenic genes will immediately improve the molecular diagnostic potential for children with suspected mitochondrial disease. Moreover, by identifying the pathogenic genes for primary mitochondrial encephalopathy we will empower the scientific community focused on neurological and neurodegenerative disorders, which have a more complex etiology, by delivering genes and pathways for further study of the pathogenetic mechanisms of these global health problems.

Public Health Relevance

In this proposal we will identify novel disease causing childhood-onset mitochondrial disease through a personalized medicine approach combining approach of genome-wide sequencing, mitochondrial functional profiling in patient cells, and gene rescue studies. This work will significantly advance the diagnosis and treatment of mitochondrial disease, as well as provide new insights into the mechanisms underlying the pathology of mitochondrial respiratory chain disorders and commonly occurring conditions associated with mitochondrial dysfunction such as neurological and neurodegenerative disorders.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS083726-03
Application #
9088513
Study Section
Genetics of Health and Disease Study Section (GHD)
Program Officer
Mamounas, Laura
Project Start
2014-08-15
Project End
2019-05-31
Budget Start
2016-06-01
Budget End
2017-05-31
Support Year
3
Fiscal Year
2016
Total Cost
Indirect Cost
Name
Baylor College of Medicine
Department
Genetics
Type
Schools of Medicine
DUNS #
051113330
City
Houston
State
TX
Country
United States
Zip Code
77030
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