Untargeted Metabolomics Reveals Distinct Metabolic Profiles in MMA Patients with MUT Gene Mutations

Methylmalonic acidemia (MMA), the most prevalent congenital organic acidemia, is inherited in an autosomal recessive pattern due to MUT gene mutations that impair methylmalonyl-CoA mutase (MCM) enzyme activity, leading to the toxic accumulation of methylmalonic acid, which causes mitochondrial dysfunction, metabolic disruptions, and multisystem damage. Newborn screening followed by confirmatory biochemical and genetic tests—such as acylcarnitine analysis and urine organic acid profiling—are widely accepted and routinely used in biochemical genetics labs. However, these conventional methods are limited in their ability to detect novel, clinically relevant biomarkers that may offer deeper insights into MMA pathophysiology. This study highlights the importance of untargeted metabolomics in identifying such biomarkers, with potential applications in predicting long-term prognosis and suggesting novel therapeutic strategies. LC-HRMS was used to analyze serum samples from MUT -confirmed MMA patients (n = 27) and healthy controls (n = 27). A total of 267 dysregulated metabolites were identified in MMA patients, including 185 upregulated and 82 downregulated. These metabolites were associated with key affected pathways, including arachidonic acid, nicotinate and nicotinamide, sphingolipid, glutathione, and purine metabolism. Downregulated metabolites included glutamine, isoleucine, deamido-NAD ⁺ , and sphingolipids, while upregulated metabolites included acylcarnitines, succinyladenosine, and leukotriene B4. Notably, biomarkers such as 11,12-epoxyeicosatrienoic acid (AUC = 0.964) and MG (PGF2alpha/0:0/0:0) (AUC = 0.953) are implicated in MMA pathophysiological mechanisms through their association with inflammation, oxidative stress, and altered fatty acid metabolism. These findings may help with improved understanding of disease pathogenesis and ultimately its management. Future research must validate these biomarkers in larger, diverse cohorts and integrate metabolomics with genomics and proteomics to develop comprehensive diagnostic tools and targeted therapies, ultimately improving MMA patient outcomes.