Large scale analyses of genotype-phenotype relationships of glycine decarboxylase mutations and neurological disease severity

Abstract

16Monogenetic diseases provide unique opportunity for studying complex, clinical states that 17 underlie neurological severity. Loss of glycine decarboxylase (GLDC) can severely impact 18 neurological development as seen in non-ketotic hyperglycinemia (NKH). NKH is a neuro-19 metabolic disorder lacking quantitative predictors of disease states. It is characterized by 20 elevation of glycine, seizures and failure to thrive, but glycine reduction often fails to confer 21 neurological benefit, suggesting need for alternate tools to distinguish severe from attenuated 22 disease. A major challenge has been that there are 255 unique disease-causing missense 23 mutations in GLDC, of which 206 remain entirely uncharacterized. Here we report a 24Multiparametric Mutation Score (MMS) developed by combining in silico predictions of stability, 25 evolutionary conservation and protein interaction models and suitable to assess 251 of 255 26 mutations. In addition, we created a quantitative scale of clinical disease severity comprising of 27 four major disease domains (seizure, cognitive failure, muscular and motor control and brain-28 malformation) to comprehensively score patient symptoms identified in 131 clinical reports 29 published over the last 15 years. The resulting patient Clinical Outcomes Scores (COS) were 30 used to optimize the MMS for biological and clinical relevance and yield a patient Weighted 31Multiparametric Mutation Score (WMMS) that separates severe from attenuated neurological 32 disease (p < 3.5e-5). Our study provides understanding for developing quantitative tools to predict 33 clinical severity of neurological disease and a clinical scale that advances monitoring disease 34 progression needed to evaluate new treatments for NKH. 35 lack of mutation-based predictors of disease progression and a quantitative scale of disease 61 severity scale impedes both management of NKH as well as development of therapies to treat 62 and cure the disease. 63 64In this study, we developed a multi-parametric mutation scale applicable to all but 4 of 255 65 missense NKH mutations across the GLDC gene and thereby assigned a multi-parametric 66 mutation score (MMS) to 251 patient mutations. The MMS was further optimized against a newly 67 developed patient-based clinical outcomes score that was based on major symptomatic domains 68 extracted from a comprehensive review of clinical cases reported in the literature. Our findings 69 yield a quantitative tool with high predictive value to support disease management and emerging 70 treatments associated with >95% of known clinical NKH mutations. 71 72 Results 73Positional distribution of NKH Missense Mutations. 74The most recently published comprehensive list of NKH missense mutations lists 171 unique 75 mutations across the length of GLDC [8]. To this, we added 85 missense mutations based on 76 additional literature and the Clinvar database. This yielded a list of 256 mutations ascribed to 213 77 unique residues (Table S1, Fig 1A). NKH missense mutations were found in the C-te...