Biology subjects

Farris, J.

Publications and source records attributed to Farris, J..

3 recordsLinked to original sources

bioRxiv2025

Variants in glycine decarboxylase activate mechanisms of mitochondrial energy metabolism in the brain.

Brain energy metabolism is produced from glucose by mitochondrial oxidative phosphorylation. Variants in the mitochondrial enzyme glycine decarboxylase (GLDC) cause a rare neurological disease, non-ketotic hyperglycinemia (NKH), with expected hallmarks of brain glycine elevation and responsiveness to folate deficiency that are equivalent to the severity of Gldc mutations. We remarkably find that brains of young- attenuated mutant mice with a 1.5-fold increase in glycine are reduced > 5-fold in GLDC, show a decline in both the mitochondrial lipoyl-transfer protein GCSH and lipoylation of the pyruvate dehydrogenase (PDH) complex, as well as concomitant rise in signatures of astrocyte mitochondrial {beta}-oxidation of fatty acids and activation of neuronal PDH. Our findings suggest a novel GLDC mechanism of remodeling mitochondrial energy systems throughout the brain, established early in and sustained throughout post-natal NKH disease.

neuroscience↗

bioRxiv2020

Genomic analyses of glycine decarboxylase neurogenic mutations yield a large scale prediction model for prenatal disease.

Glycine decarboxylase (GLDC) is a mitochondrial protein, hundreds of mutations in which cause a neurometabolic disorder Non-ketotic Hyperglycinemia (NKH), associated with elevation of plasma glycine. But why a mutation induces severe or attenuated neurological disease is poorly understood. We combined a human multiparametric mutation scale that separates severe from attenuated clinical, neurological disease, with new in silico tools to assess 238 of 255 NKH mutations in murine GLDC. We unified novel murine and human genome level-analyses across a linear scale of neurological severity, with in vivo evidence from mice engineered with a top-ranking attenuated mutation and another mutation >10 times more pathogenic and integrated the data in a model of pre- and post-natal disease outcomes, relevant for over a hundred major and minor neurogenic mutations. Our findings suggest that highly severe neurogenic mutations predict fatal, prenatal disease that can be remedied by metabolic supplementation of dams, in absence of amelioration of persistent and age-dependent elevation of plasma glycine.

bioinformatics↗

bioRxiv2019

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

Monogenetic diseases provide unique opportunity for studying complex, clinical states that underlie neurological severity. Loss of glycine decarboxylase (GLDC) can severely impact neurological development as seen in non-ketotic hyperglycinemia (NKH). NKH is a neuro-metabolic disorder lacking quantitative predictors of disease states. It is characterized by elevation of glycine, seizures and failure to thrive, but glycine reduction often fails to confer neurological benefit, suggesting need for alternate tools to distinguish severe from attenuated disease. A major challenge has been that there are 255 unique disease-causing missense mutations in GLDC, of which 206 remain entirely uncharacterized. Here we report a Multiparametric Mutation Score (MMS) developed by combining in silico predictions of stability, evolutionary conservation and protein interaction models and suitable to assess 251 of 255 mutations. In addition, we created a quantitative scale of clinical disease severity comprising of four major disease domains (seizure, cognitive failure, muscular and motor control and brain-malformation) to comprehensively score patient symptoms identified in 131 clinical reports published over the last 15 years. The resulting patient Clinical Outcomes Scores (COS) were used to optimize the MMS for biological and clinical relevance and yield a patient Weighted Multiparametric Mutation Score (WMMS) that separates severe from attenuated neurological disease (p < 3.5e-5). Our study provides understanding for developing quantitative tools to predict clinical severity of neurological disease and a clinical scale that advances monitoring disease progression needed to evaluate new treatments for NKH.

bioinformatics↗