Metabolites in patients’ urine may be markers of disease, ERT response
11 markers may help in diagnosing Sanfilippo and response to potential therapy
Researchers identified 11 new candidate metabolite biomarkers in the urine of people with Sanfilippo syndrome, a study reported.
Metabolomics, or examining global changes in metabolites in metabolic disorders such as Sanfilippo syndrome, may shed light on underlying disease mechanisms and provide a source of noninvasive biomarkers to support diagnosis, monitor treatment response, or predict outcomes, the research team concluded.
The biomarker study, “Untargeted LC-HRMS metabolomics reveals candidate biomarkers for mucopolysaccharidoses,” was published in the journal Clinica Chimica Acta.
11 of 12 metabolites ID’d higher in Sanfilippo patients than unaffected controls
Mucopolysaccharidoses (MPSs) are a group of inherited metabolic disorders characterized by the deficiency or absence of enzymes that break down complex sugar molecules called glycosaminoglycans.
Sanfilippo syndrome is a type of MPS, called MPS III, caused by a lack of one of four enzymes that degrade the glycosaminoglycan known as heparan sulfate. As a result, heparan sulfate builds to toxic levels inside cells, causing damage, especially in brain tissue.
While there is no cure for Sanfilippo syndrome, various treatments are being developed, including enzyme replacement therapy (ERT), which involves administering the missing enzyme from an external source.
Blood tests to measure the levels of these enzymes are the gold standard for diagnosing Sanfilippo syndrome, supported by urine tests to measure heparan sulfate and similar sugar molecules. Genetic testing can provide a conclusive diagnosis.
Metabolomics is the study of low molecular weight metabolites in biological systems, and it is emerging as a tool to help understand genetic metabolic diseases.
Researchers in Brazil and the U.S. applied a metabolomics approach to urine samples collected from 37 MPS patients, including five with Sanfilippo, and 38 unaffected individuals, as controls, to identify biomarker candidates for MPS.
Urine samples were analyzed using a technique called liquid chromatography-high resolution mass spectrometry (LC-HRMS), which separated and identified individual metabolites.
Based on an overview of the similarities and differences across samples, their technique correctly classified all control and most (95%) MPS samples. Consistently, adjusted statistical analysis demonstrated an accuracy of 93% in correctly classifying 37 control and 33 MPS samples.
Acylaminosugar levels lower in people given enzyme replacement therapy
The team identified 12 metabolites in all MPS patients that were elevated compared with the control group, indicating that some disease-causing mechanisms correlated across all MPSs, the researchers noted.
Among them, 11 were significantly higher in Sanfilippo patients than in controls. They were N, N-dimethylarginine, glutamylhydroxyproline, creatine, dihydrophaseic acid, N2-Succinyl-L-glutamic acid 5-semialdehyde, N-gamma-Glutamyl-S-allylcysteine, glutamic acid, phenylalanylhydroxyproline, isoleucylhydroxyproline, galNAc4S, and galNAc6S.
Metabolites N, N-dimethylarginine and N-gamma-Glutamyl-S-allylcysteine showed the largest, most significant difference between Sanfilippo and controls.
Researchers noted that N, N-dimethylarginine has been reported as a potential biomarker for adverse cardiovascular events and, as such, may be useful as a “complementary biomarker in MPS syndromes as an early indicator of cardiovascular risk.”
Another significantly elevated metabolite in Sanfilippo was glutamic acid, whereby higher glutamic acid levels in the brain and spinal cord are thought to cause cell damage, they added.
Many candidate biomarkers correlated with impaired protein metabolism, inflammation, increases in glycosaminoglycan-related metabolites, and oxidative stress, marked by the excess production of tissue-damaging reactive oxygen species.
Patients treated with ERT also had lower levels of acylaminosugars, such as galNAc4S and galNAc6S, than did untreated patients across all MPS types.
“Our findings demonstrated that untargeted metabolomics is a powerful tool to unveil metabolic changes in MPSs, expanding our understanding of the mechanisms involved in these diseases,” the team concluded. “Those candidate biomarkers can potentially be used in screening methods to support diagnosis and ERT efficacy.”
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