Abstract
Parkinson’s disease (PD) is an age-related, chronic and progressive neurodegenerative disorder characterized by a loss of multifocal neurons, resulting in both non-motor and motor symptoms. While several genetic and environmental contributory risk factors have been identified, more exact methods for diagnosing and assessing prognosis of PD have yet to be established. Here we describe the generation and validation of a dataset comprising whole-blood transcriptomes originally intended for use in detection of blood biomarkers and transcriptomic network changes indicative of PD. Whole-blood samples extracted from both early-stage PD patients and healthy controls were sequenced using no-amplification non-tagging cap analysis of gene expression (nAnT-iCAGE) to analyse differences in global RNA expression patterns across the conditions. Subsequent sampling of a subset of PD patients one-year later provides the opportunity to study changes in transcriptomes arising due to disease progression.
Highlights
Background & SummaryParkinson’s disease (PD) is the second most common neurodegenerative disorder with an average age of onset of 60 years and a prevalence of about 1–2% in industrialized countries[1]
The overall incidence of the disease is increasing, and projections indicate that there will be three times as many individuals affected by PD2 by 2030
Though the exact cause is unknown, a combination of genetic predisposition (including mutations in the leucine-rich repeat kinase 2 (LRRK2) gene[6,7], α-synuclein[8] (SNCA), parkin[9,10] (PARK2), PTEN-induced putative kinase 111 (PINK1) and DJ-112 (PARK7)) and environmental factors are thought to be the primary events in disease induction
Summary
Parkinson’s disease (PD) is the second most common neurodegenerative disorder with an average age of onset of 60 years and a prevalence of about 1–2% in industrialized countries[1]. There is a high demand for diagnostic procedures utilizing clinically-relevant biomarkers of PD: the ability to routinely test for biomarkers through a minimally invasive approach would make for a powerful diagnostic tool This is especially true for biomarkers indicating the earliest stages of PD, as early diagnosis and intervention will likely lead to better prognostic outcomes, as well as limiting misdiagnoses. We collected whole blood samples from PD patients at an early stage of disease progression and healthy controls, with an aim to identify potent transcriptomic biomarkers at high resolution using an unbiased analysis method. The samples collected and described in this paper include 39 PD and 20 control whole blood transcriptome samples[22] These samples focus only on early stage PD, but encompass a range of ages and genders of participants, as well as differences in clinical scores (Table 1), and may account for some of the heterogeneity seen across. The samples described here were collected over two years, allowing for some analysis of disease progression within early PD, in addition to highlighting differences between control and disease conditions
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