Publication Date

2019-08-01

Availability

Open access

Embargo Period

2019-08-01

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PHD)

Department

Human Genetics and Genomics (Medicine)

Date of Defense

2019-06-19

First Committee Member

Stephan L. Zuchner

Second Committee Member

Mustafa Tekin

Third Committee Member

Anthony J. Griswold

Fourth Committee Member

Stefan Wuchty

Abstract

Inherited axonopathies are a group of disorders unified by a common pathological mechanism: length-dependent axonal degeneration. Progressive axonal degeneration can lead to both Charcot-Marie-Tooth type 2 (CMT2) and hereditary spastic paraplegia (HSP) depending on whether the peripheral or central nerves are affected, respectively. Historically, CMT2 and HSP are treated as distinct disorders, but their increasingly apparent clinical and genetic overlap challenges this classification. Either CMT2 or HSP can be caused by mutations within a single gene, yet what determines whether the peripheral or central nerves are affected in each patient remains unclear. Currently, ~30% of CMT2 cases and ~60% of HSP cases have been genetically diagnosed, and only ~25% of clinical exome sequencing results in molecular diagnosis. The percentage of genetically undiagnosed inherited axonopathy cases suggests that novel disease genes remain unidentified. Furthermore, the general rate of exome sequencing diagnosis indicates that rare mutational mechanisms or modes of inheritances may be overlooked in standard whole-exome analysis. The primary aims of my dissertation project were, firstly, to investigate possible rare genetic mechanisms and expand the genetic architecture of inherited axonopathies to address the diagnostic gap and, secondly, to explore cellular pathways that differentiate peripheral versus central nervous system involvement. To catalog the current genetic variant landscape of CMT, I co-developed a web-based platform to catalog, rate, and discuss any variation observed in a CMT case. I analyzed 872 whole exome datasets from patients with CMT and HSP to explore a cumulative mutational burden and di/oligogenic inheritance across known disease genes and to identify risk alleles in both known and novel disease genes. This analysis lead to the identification of a candidate risk allele in EXOC4 for CMT, further expanding the genetic architecture of IA beyond highly penetrant monogenic alleles. To identify rare genetic mechanisms, I screened 96 hereditary motoneuron probands for uniparental isodisomy by scanning whole exome datasets for very long regions of homozygosity. From this pilot screen, I identified one HSP case with complete isodisomy of chromosome 16 harboring a homozygous mutation in FA2H, inherited from one heterozygous parent. To continue looking for rare genetic mechanisms, I screened each possible open reading frame of genome-wide 3’ UTR sequences to classify candidate genes at risk for harboring cryptic amyloidogenic elements. To investigate cellular pathways involved in IA, I analyzed a protein-protein interaction dataset and an RNA-sequencing dataset. The PPI analysis revealed a topological relationship between CMT and HSP as well as cellular pathways putatively involved across the IA spectrum. RNA-sequencing of human motor neuron axonal compartment revealed a significant enrichment of nuclear-encoded mitochondrial genes and IA disease genes.

Keywords

Mendelian genetics; bioinformatics; risk alleles; network analysis; whole-exome sequencing

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