Abstract
Parkinson’s disease (PD), the second most common progressive neurodegenerative disorder, was long believed to be a non-genetic sporadic syndrome. Today, only a small percentage of PD cases with genetic inheritance patterns are known, often complicated by reduced penetrance and variable expressivity. The few well-characterized Mendelian genes, together with a number of risk factors, contribute to the major sporadic forms of the disease, thus delineating an intricate genetic profile at the basis of this debilitating and incurable condition. Along with single nucleotide changes, gene-dosage abnormalities and copy number variations (CNVs) have emerged as significant disease-causing mutations in PD. However, due to their size variability and to the quantitative nature of the assay, CNV genotyping is particularly challenging. For this reason, innovative high-throughput platforms and bioinformatics algorithms are increasingly replacing classical CNV detection methods. Here, we report the design strategy, development, validation and implementation of NeuroArray, a customized exon-centric high-resolution array-based comparative genomic hybridization (aCGH) tailored to detect single/multi-exon deletions and duplications in a large panel of PD-related genes. This targeted design allows for a focused evaluation of structural imbalances in clinically relevant PD genes, combining exon-level resolution with genome-wide coverage. The NeuroArray platform may offer new insights in elucidating inherited potential or de novo structural alterations in PD patients and investigating new candidate genes.Electronic supplementary materialThe online version of this article (doi:10.1007/s10048-016-0494-0) contains supplementary material, which is available to authorized users.
Highlights
Parkinson’s disease (PD) is a progressive debilitating movement disorder that affects approximately 1 % of the population older than 65 years of age worldwide [1]
Our findings show the advantages of the NeuroArray platform in terms of results, time and costs, as well as for the discovery of new potential genetic biomarkers underlying the pathogenic mechanisms of PD and commonly shared genetic signatures with other neurological diseases
To perform a comprehensive analysis of copy number variations (CNVs) in PD-related genes, we developed a focused customized oligonucleotide array-based comparative genomic hybridization (aCGH) design targeting 505 genes and 6826 exonic regions linked to PD
Summary
Parkinson’s disease (PD) is a progressive debilitating movement disorder that affects approximately 1 % of the population older than 65 years of age worldwide [1]. Genomewide linkage scans and exome sequencing of wellcharacterized PD families have been successful in discovering disease-causing mutations in dominant (SNCA, LRRK2, VPS35 and the recent TMEM230), recessive (PARK2, PINK1, DJ1, DNAJC6) [2,3,4] and X-linked (RAB39B) PD genes [5, 6]. Despite the existence of these rare Mendelian monogenic forms, it is clear that PD is a genetically heterogeneous and most likely complex disorder This complexity is underlined by the notion that we are currently aware of dozens of loci, genes and risk factors that seem to contribute to PD [2, 10]. These genes are involved in numerous cellular pathways, such as the ubiquitinproteasome system, synaptic transmission, autophagy, lysosomal autophagy, endosomal trafficking, mitochondrial metabolism, apoptosis and inflammatory mechanisms, all of which are generally implicated in neuronal cell death [11]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
