Abstract
Genomic sequencing offers an untargeted, data-driven approach to genetic diagnosis; however, variants of uncertain significance often hinder the diagnostic process. The discovery of rare genomic variants without previously known functional evidence of pathogenicity often results in variants being overlooked as potentially causative, particularly in individuals with undifferentiated phenotypes. Consequently, many neurometabolic conditions, including those in the GABA (gamma-aminobutyric acid) catabolism pathway, are underdiagnosed. Succinic semialdehyde dehydrogenase deficiency (SSADHD, OMIM #271980) is a neurometabolic disorder in the GABA catabolism pathway. The disorder is due to bi-allelic pathogenic variants in ALDH5A1 and is usually characterized by moderate-to-severe developmental delays, hypotonia, intellectual disability, ataxia, seizures, hyperkinetic behavior, aggression, psychiatric disorders, and sleep disturbances. In this study, we utilized an integrated approach to diagnosis of SSADHD by examining molecular, clinical, and metabolomic data from a single large commercial laboratory. Our analysis led to the identification of 16 patients with likely SSADHD along with three novel variants. We also showed that patients with this disorder have a clear metabolomic signature that, along with molecular and clinical findings, may allow for more rapid and efficient diagnosis. We further surveyed all available pathogenic/likely pathogenic variants and used this information to estimate the global prevalence of this disease. Taken together, our comprehensive analysis allows for a global approach to the diagnosis of SSADHD and provides a pathway to improved diagnosis and potential incorporation into newborn screening programs. Furthermore, early diagnosis facilitates referral to genetic counseling, family support, and access to targeted treatments-taken together, these provide the best outcomes for individuals living with either GABA-TD or SSADHD, as well as other rare conditions.