Introduction:

Personalized genomic medicine has radically changed the ability to diagnose rare diseases. The discovery of potentially causal gene variants has steadily improved, yet a key barrier to progress is the ability to prove pathogenicity with functional assessment of candidate variants. At our center, we have integrated clinical evaluation, next generation sequencing, and biological validation for over 500 families with rare disorders. Our success rate in finding a genetic diagnosis in all recruited families is about 40%.  In selected cases, further studies are done using cellular and animal (zebrafish and mouse) models.

Methods:

Here we will present an analysis of our cohort of patients grouped according to specific phenotypic terms including epilepsy, leukodystrophy, developmental delay, intellectual disability, hypotonia, weakness, ataxia, suspected mitochondrial disease, neurodegeneration, and GI dysmotility.

Results:

Using tools such as GeneMatcher and Decipher, we have discovered new neurogenetic syndromes linked to KCNA2, PACS2, ATP6V1A, DDX6 and others. Genetic diagnostic rates correlated to phenotype (participants may fall into more than one category): 83% leukodystrophy (n=12), 79% neurodegenerative (n=14), 55% ataxia (n=20), 54% epilepsy (n=96), 49% DD/ID (n=206), 29% mitochondrial disease (n=58), 0% GI dysmotility primary diagnosis (n=10), 0% POTS and dysautonomia (n=11).

Conclusions:

Patient phenotypes such as epilepsy, DD/ID, ataxia, neurodegeneration or more specific diagnoses are associated with a higher likelihood of success when using whole exome sequencing. Terms such as suspected mitochondrial disease, GI dysmotility are associated with a much lower success rate.