Abstract
INTRODUCTION: Nonketotic hyperglycinemia (NKH) is a rare, autosomal recessive-inherited disorder of amino acid metabolism known as glycine encephalopathy. Clinical manifestations arise because of the enzyme deficiency involved in glycine degradation. Currently, no effective treatment exists to alter the prognosis of NKH; available therapies focus primarily on reducing glycine accumulation in the body. MicroRNAs (miRNAs) are small noncoding RNAs that function as transcriptional and post-transcriptional regulators of gene expression. Here, we report the comparative profiling of small RNA sequencing (RNA-seq) data generated from clinical samples diagnosed with a specific condition. METHODS: We identified miRNAs using miRNA-seq with samples obtained from three NKH patients, five individuals with heterozygous variants in NKH genes, and seven control cases. Utilising pathways from the PubChem database, we identified NKH-related pathways and used bioinformatics tools for miRNA, pathway, and disease prediction. This was followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to enrich the predicted target genes of differentially expressed miRNAs based on miRNA-target interactions. RESULTS: In our study, 10 known miRNAs were identified to be associated with NKH using at least two different tools. Our study is the first to demonstrate altered miRNA profiles in cases where the expression of AMT and GLDC genes is reduced. CONCLUSION: NKH is an ultrarare and difficult-to-diagnose disease. This study determines the miRNA-based biomarkers for early detection of NKH and provides a robust framework for advancing future experimental research and diagnostic strategies.