Frontiers in Neuroscience (Aug 2022)
Serum metabolomic characterization of PLA2G6-associated dystonia–parkinsonism: A case-control biomarker study
Abstract
IntroductionPhospholipase A2 Group VI (PLA2G6), encoding calcium-independent phospholipase A2, has been isolated as the gene responsible for an autosomal recessive form of early-onset Parkinson’s disease (namely, PARK14). Compared to idiopathic Parkinson’s disease (iPD), PARK14 has several atypical clinical features. PARK14 has an earlier age at onset and is more likely to develop levodopa-induced dyskinesia. In iPD, serum metabolomics has observed alterations in several metabolic pathways that are related to disease status and clinical manifestations. This study aims to describe the serum metabolomics features of patients with PARK14.DesignThis case-control biomarker study tested nine patients diagnosed with PARK14. Eight age and sex-matched healthy subjects were recruited as controls. To evaluate the influence of single heterozygous mutation, we enrolled eight healthy one-degree family members of patients with PARK14, two patients diagnosed with early-onset Parkinson’s disease (EOPD) who had only a single heterozygous PLA2G6 mutation, and one patient with EOPD without any known pathogenic mutation.MethodsThe diagnosis of PARK14 was made according to the diagnostic criteria for Parkinson’s disease (PD) and confirmed by genetic testing. To study the serum metabolic features, we analyzed participants’ serum using UHPLC-QTOF/MS analysis, a well-established technology.ResultsWe quantified 50 compounds of metabolites from the serum of all the study subjects. Metabolites alterations in serum had good predictive accuracy for PARK14 diagnosis (AUC 0.903) and advanced stage in PARK14 (AUC 0.944). Of the 24 metabolites that changed significantly in patients’ serum, eight related to lipid metabolism. Oleic acid and xanthine were associated with MMSE scores. Xanthine, L-histidine, and phenol correlated with UPDRS-III scores. Oleic acid and 1-oleoyl-L-alpha-lysophosphatidic acid could also predict the subclass of the more advanced stage in the PLA2G6 Group in ROC models.ConclusionThe significantly altered metabolites can be used to differentiate PLA2G6 pathogenic mutations and predict disease severity. Patients with PLA2G6 mutations had elevated lipid compounds in C18:1 and C16:0 groups. The alteration of lipid metabolism might be the key intermediate process in PLA2G6-related disease that needs further investigation.
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