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University of Washington CSF biomarker study for Parkinson disease

ABSTRACT:

There is a clear need to develop biomarkers for Parkinson disease (PD) diagnosis and monitoring disease progression. In this study we evaluated cerebrospinal fluid (CSF) proteins, which are known to be critically involved in PD or identified in our preliminary profiling studies, aptamers, and RNAs as potential PD biomarkers. Access to subjects for this study was via the Pacific Northwest Udall Center (PANUC) and the Alzheimer's Disease Research Center (ADRC) at the University of Washington and Oregon Health and Sciences University (OHSU). Using CSF samples from 30 well-characterized patients with PD and 30 age-, sex-matched healthy controls, we prepared RNA seq libraries and performed deep sequencing of all RNA species, including small and long RNA, mRNAs, noncoding RNAs and differentially spliced transcripts. We then tried several methods for RNAseq data analysis to optimize our analysis pipeline. We identified a total of 3381 transcripts corresponding to 182 long intergenic RNAs (LincRNAs), 11 microRNAs (miRNAs), 2861 protein-coding transcripts, 200 pseudogenes and 127 antisense RNAs; some of them were differentially expressed between PD and control groups. Selected differentially expressed RNAs have been validated in the same set of CSF samples using real-time PCR (RT-PCR). Further validations in independent, larger cohorts of samples are still ongoing. Our results obtained so far suggested that CSF proteins and RNAs could be used as good indexes for PD diagnosis and disease severity/progression. This study is a part of the NIDDS-funded Parkinson's Disease Biomarkers Program (PDBP).

PROVIDER: phs000901 | dbGaP |

SECONDARY ACCESSION(S): PRJNA281517PRJNA281516

REPOSITORIES: dbGaP

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			Action	DRS
	GapExchange_phs000901.v1.p1.xml	Xml
	dbGaPEx2.1.5.xsd	Other
	Study_Report.phs000901.ParkinsonCerebrospinalFluidBiomarker.v1.p1.MULTI.pdf	Pdf
	manifest_phs000901.ParkinsonCerebrospinalFluidBiomarker.v1.p1.c1.GRU.pdf	Pdf
	datadict_v2.xsl	Other

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Project description:Parkinson’s disease (PD) is a prevalent and incurable neurodegenerative disease for which robust biomarkers for early detection and tailored treatment are needed. Protein abundance measurements have so far not proven discriminative as PD biomarkers. Since alterations in protein structure reflect various functionally relevant molecular events, such as allostery, chemical modification, protein misfolding or molecular interaction, we have tested whether global analysis of protein structural changes is informative about PD pathophysiology and status and could form the basis of the new concept of structural biomarkers of disease. We applied limited proteolysis-mass spectrometry (LiP-MS) for the detection of global protein structural changes in cerebrospinal fluid (CSF) of PD patients and age-matched healthy individuals. Using linear modeling to correct for covariates, we identified 76 proteins as structurally altered in the CSF of patients with PD. We identified structural alterations in several proteins implicated in PD, many of which were also structurally altered in PD brain tissue suggesting that this approach provides insight into pathological mechanisms, although validation in independent cohorts is needed. Protein structural information from CSF outperformed protein abundance information in discriminating between healthy and PD subjects. Further, candidate structural biomarkers from our screen provided complementary information to CSF measures of the hallmark PD protein α-synuclein and thus improved the sensitivity and specificity of discriminating the healthy and PD states. Finally, we present the first analysis of inter-individual variability of a structural proteome in healthy humans, identifying biophysical and structural features of variable and invariable protein regions. Structurally variable protein regions show a greater propensity for protein-protein interaction and higher disorder than non-variable peptides. This dataset will be a valuable resource for structural biology and for future structure-based biomarker research. Our data suggest that global analyses of the human structural proteome will lead to the discovery of novel, structural biomarkers of disease and enables hypothesis-generation about the molecular events underlying disease processes.

Project description:Parkinson disease (PD) is a neurodegenerative disease characterized by the accumulation of alpha-synuclein (SNCA) and other proteins in aggregates termed âLewy Bodiesâ within neurons. PD has both genetic and environmental risk factors, and while processes leading to aberrant protein aggregation are unknown, past work points to abnormal levels of SNCA and other proteins. Although several genome-wide studies have been performed for PD, these have focused on DNA sequence variants by genome-wide association studies (GWAS) and on RNA levels (microarray transcriptomics), while genome-wide proteomics analysis has been lacking. After appropriate filters, proteomics identified 3,558 unique proteins and 283 of these (7.9%) were significantly different between PD and controls (q-value<0.05). RNA-sequencing identified 17,580 protein-coding genes and 1,095 of these (6.2%) were significantly different (FDR p-value<0.05), but only 166 of the FDR significant protein-coding genes (0.94%) were present among the 3,558 proteins characterized. Of these 166, eight genes (4.8%) were significant in both studies, with the same direction of effect. Functional enrichment analysis of the proteomics results strongly supports mitochondrial-related pathways, while comparable analysis of the RNA-sequencing results implicates protein folding pathways and metallothioneins. Ten of the implicated genes or proteins co-localized to GWAS loci. Evidence implicating SNCA was stronger in proteomics than in RNA-sequencing analyses. Notably, differentially expressed protein-coding genes were more likely to not be characterized in the proteomics analysis, which lessens the ability to compare across platforms. Combining multiple genome-wide platforms offers novel insights into the pathological processes responsible for this disease by identifying pathways implicated across methodologies. The study consists of mRNA-Seq (29 PD, 44 neurologically normal controls) and three-stage Mass Spectrometry Tandem Mass Tag Proteomics (12 PD, 12 neurologically normal controls) performed in post-mortem BA9 brain tissue. The proteomics samples are a subset of the RNA-Seq samples.

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University of Washington CSF biomarker study for Parkinson disease

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