Large-scale copy number variant analysis in genes linked to Parkinson´s disease

Abstract

Genetic studies of Parkinson's disease (PD) have focused on single nucleotide variants (SNVs), with limited attention to copy number variants (CNVs). This study investigates CNVs in PD using candidate PD-related genes and genome-wide approaches. We identified CNVs from the ProtectMove project genotyping data of 2364 PD patients and 2909 controls using PennCNV. We validated 119 of 137 detected CNVs in PD-related genes (87%) using MLPA/qPCR, including 104 in PRKN, six in PARK7, four in SNCA, and others in LRRK2, RAB32, and VPS35. CNVs were present in 2.4% of patients and 1.5% of controls. Notably, 0.9% of patients carried potentially disease-causing CNVs compared to 0.1% in controls. CNVs were enriched in patients (OR = 1.67, p = 0.03) due to PRKN CNVs, particularly in early-onset cases. These results highlight the importance of CNVs in PD, particularly in PRKN, and suggest that rare CNVs in LRRK2 and RAB32 may contribute to disease risk and diagnostic potential.

Fig. 1. Overview of study design and CNV burden analyses in Parkinson’s disease.

A Overview of the study: schematic representation of the analysis workflow. B. Visualisation of CNVs in the PRKN gene. C-D Forest plot showing the CNV burden of validated CNVs in PD-related genes and PRKN (C) and the genome-wide CNV burden (D) in PD patients compared to controls. The sample size for each comparison was included in the figures showing the number of corresponding carriers and the total number of samples. Logistic regression was used to estimate odds ratios (ORs) and p-values for each CNV category and were adjusted for age at assessment, sex, and the first five components of PCA. (*) significant p-values were adjusted using FDR methods.