Genotypic-Phenotypic Analysis, Metabolic Profiling and Clinical Correlations in Parkinson's Disease Patients from Tamil Nadu Population, India

Abstract

Parkinson's disease (PD) is an ageing disorder caused by dopaminergic neuron depletion with age. Growing research in the field of metabolomics is expected to play a major role in PD diagnosis, prognosis and therapeutic development. In this study, we looked at how SNCA and GBA1 gene mutations, as well as metabolomic abnormalities of kynurenine and cholesterol metabolites, were linked to alpha-synuclein (α-syn) and clinical characteristics in three different PD age groups. In all three age groups, a metabolomics analysis revealed an increased amount of 27-hydroxycholesterol (27-OHC) and a lower level of kynurenic acid (KYNA). The effect of 27-OHC on SNCA and GBA1 modifications was shown to be significant (P < 0.05) only in the A53T variant of the SNCA gene in late-onset and early-onset PD groups, whereas GBA1 variants were not. Based on the findings, we observed that the increase in 27-OHC would have elevated α-syn expression, which triggered the changes in the SNCA gene but not in the GBA1 gene. Missense variations in the SNCA and GBA1 genes were investigated using the sequencing technique. SNCA mutation A53T has been linked to increased PD symptoms, but there is no phenotypic link between GBA1 and PD. As a result of the data, we hypothesise that cholesterol and kynurenine metabolites play an important role in PD, with the metabolite 27-OHC potentially serving as a PD biomarker. These findings will aid in the investigation of pathogenic causes as well as the development of therapeutic and preventative measures for PD.

Keywords: Alpha-synuclein; Cholesterol; Genetic alterations; Kynurenine; Parkinson’s disease; Phenotypic signs.