Characterization of methylation profile in biofluid cell-free DNA and identification of differentially methylated genes for phenotypic representations in Parkinson's disease

Abstract

Background

The potential biomarkers for Parkinson’s Disease (PD) in blood circulating cell-free DNA (cfDNA) have been infrequently explored. This study aims to identify specific methylation markers in blood cfDNA that could aid in the diagnosis of PD.

Methods

A total of twenty patients with PD and nine healthy participants were recruited for this study. Cerebrospinal fluid (CSF) and/or blood samples were collected from the patients. Whole-genome bisulfite sequencing (WGBS) was conducted to analyze cfDNA methylation patterns in both CSF and blood samples. Data analysis and figure plotting were performed using R software.

Results

We identified 1322 differentially methylated genes (DMGs) in CSF and 118 DMGs in blood cfDNA between patients with PD and healthy participants, with 16 DMGs being common across both sample types. Significant correlations were observed within the CSF regarding methylation signatures related to sex,age,occupational nature,dietary habits(meat-only, vegetarian or mixed),tea consumption,family history of disease, hypertension,diabetes,postural instability and gait disorder,hyposmia,as well as glossolalia. Conversely, significant correlations found in blood included associations between methylation signatures and factors such as duration of residence at high altitudes, cigarette use, diabetes prevalence, dysphagia occurrence, family history of PD, scores on the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS), and results from the Hamilton Anxiety Scale (HAMA). Furthermore, potential diagnostic markers comprising common DMGs present in both CSF and blood cfDNA alongside phenotypic factors were identified. The CSF markers consisted of five methylated genes—APMAP,C19orf25,TMA16,NIT2,and NDST2—and three phenotypic factors including duration of residence at high altitude locations, hyperhidrosis, and family history of PD. In contrast, the blood cfDNA markers encompassed eight differentially methylated genes—QPCT,TMA16,APMAP,NIT2,DCP2,ATP,TNFAIP1,and ZNF700—and two phenotypic factors which included tea consumption and hyposmia.

Conclusions

For the first time, specific methylation signatures related to PD have been identified in blood samples. Furthermore, correlations were observed between methylation signatures in CSF and cfDNA from blood with various patient phenotype factors. Diagnostic markers for PD based on CSF and blood cfDNA methylation patterns, along with phenotypic characteristics, have been established.