A method to predict whether a mutation will cause severe or more mild forms of NKH
Tech ID: 20-050
Inventors: Dr. Kasturi Haldar, Joseph Farris
Date added: August 30, 2020
A computational model that quantitatively predicts NKH disease severity based on GLDC gene mutations.
Non-ketotic hyperglycinemia (NKH) is a rare genetic disease with an approximate incidence of 1 in 76,000 births. 85% of NKH cases are caused by mutations in the glycine decarboxylase gene (GLDC), a protein that breaks down glycine. There are hundreds of possible mutations of the GLDC gene that cause varied disease severity, the majority of which remain entirely uncharacterized. Lack of mutation-based predictors of disease progression and a quantitative scale of disease severity impedes both management and development of therapies for NKH. Severe cases of NKH are characterized by intractable seizures, failure to thrive, lack of developmental milestones, and often premature death. If well-managed, patients in whom the disease is attenuated are often able to control seizures, go to school, and live into adulthood. Current methods of determining disease severity involve monitoring symptoms and tracking glycine levels in the blood and cerebrospinal fluid (CSF). However, blood glycine levels do not accurately predict disease outcome, and while CSF glycine level is a strong indicator of severity, continuous CSF monitoring is not feasible for long-term disease management. Since there is currently no effective treatment for NKH and current methods of determining disease severity are inadequate, new methods for predicting clinical severity of NKH cases and evaluating therapies are necessary to elevate the quality of care for NKH patients.
Researchers at the University of Notre Dame have recently developed a computational model that quantitatively indicates NKH disease severity based on factors affecting glycine decarboxylase function for the mutations of the GLDC gene. The model produces a Multiparametric Mutation Score (MMS) with easily interpreted results to assess disease severity for determination of treatment options. Additionally, researchers at the University of Notre Dame have developed a quantitative scale of clinical NKH disease severity comprising four major disease domains to comprehensively score patient symptoms: seizure, cognitive failure, muscular and motor control, and brain-malformation.
• High predictive value to support disease management and emerging treatments associated with >95% of known clinical NKH mutations.
Clinical and Market Applications
• Management of NKH by clinicians and patients
• Development of therapies for NKH
Large scale analyses of genotype-phenotype relationships of glycine decarboxylase mutations and
neurological disease severity.
Technology Readiness Status
TRL 3 - Experimental Proof of Concept