Dataset Information

Potential Tear Biomarkers for the Diagnosis of Parkinson's Disease-A Pilot Study.

ABSTRACT: Parkinson's disease (PD) is the second most common neurodegenerative disease after Alzheimer's disease. In this study, the tear proteome profile of patients with idiopathic PD (iPD, n = 24), carriers of the E46K-SNCA mutation (n = 3) and healthy control (CT, n = 27) subjects was analyzed to identify candidate biomarkers for the diagnosis of PD. An observational, prospective and case-control pilot study was carried out, analyzing the participants tear samples by nano-liquid chromatography-mass spectrometry (nLC-MS/MS) and assessing their neurological impairment. The proteomic data obtained are available at ProteomeXchange with identifier 10.6019/PXD028811. These analyses led to the identification of 560 tear proteins, some of which were deregulated in PD patients and that have been implicated in immune responses, inflammation, apoptosis, collagen degradation, protein synthesis, defense, lipid transport and altered lysosomal function. Of these proteins, six were related to neurodegenerative processes and showed a good capacity to classify patients and controls. These findings revealed that certain proteins were upregulated in the tears of PD patients, mainly proteins involved in lysosomal function. Thus, in this study, tear proteins were identified that are implicated in neurodegeneration and that may be related to an aggressive disease phenotype in PD patients.

SUBMITTER: Acera A

PROVIDER: S-EPMC8788479 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Potential Tear Biomarkers for the Diagnosis of Parkinson's Disease-A Pilot Study.

Acera Arantxa A Gómez-Esteban Juan Carlos JC Murueta-Goyena Ane A Galdos Marta M Azkargorta Mikel M Elortza Felix F Ruzafa Noelia N Ibarrondo Oliver O Pereiro Xandra X Vecino Elena E

Proteomes 20220113 1

Parkinson's disease (PD) is the second most common neurodegenerative disease after Alzheimer's disease. In this study, the tear proteome profile of patients with idiopathic PD (iPD, n = 24), carriers of the E46K-SNCA mutation (n = 3) and healthy control (CT, n = 27) subjects was analyzed to identify candidate biomarkers for the diagnosis of PD. An observational, prospective and case-control pilot study was carried out, analyzing the participants tear samples by nano-liquid c ...[more]

PMID: 35076620

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Project description:Parkinson's disease (PD) is a progressive neurodegenerative disease whose etiology is attributed to development of Lewy bodies and degeneration of dopaminergic neurons in the substantia nigra (SN). Currently, there are no definitive diagnostic indicators for PD. In this study, we aimed to identify potential diagnostic biomarkers for PD and analyzed the impact of immune cell infiltrations on disease pathogenesis. The PD expression profile data for human SN tissue, GSE7621, GSE20141, GSE20159, GSE20163 and GSE20164 were downloaded from the Gene Expression Omnibus (GEO) database for use in the training model. After normalization and merging, we identified differentially expressed genes (DEGs) using the Robust rank aggregation (RRA) analysis. Simultaneously, DEGs after batch correction were identified. Gene interactions were determined through venn Diagram analysis. Functional analyses and protein-protein interaction (PPI) networks were used to the identify hub genes, which were visualized through Cytoscape. A Lasso Cox regression model was employed to identify the potential diagnostic genes. The GSE20292 dataset was used for validation. The proportion of infiltrating immune cells in the samples were determined via the CIBERSORT method. Sixty-two DEGs were screened in this study. They were found to be enriched in nerve conduction, dopamine (DA) metabolism, and DA biosynthesis Gene Ontology (GO) terms. The PPI network and Lasso Cox regression analysis revealed seven potential diagnostic genes, namely SLC18A2, TAC1, PCDH8, KIAA0319, PDE6H, AXIN1, and AGTR1, were subsequently validated in peripheral blood samples obtained from healthy control (HC) and PD patients, as well as in the GSE20292 dataset. The results revealed the exceptional sensitivity and specificity of these genes in PD diagnosis and monitoring. Moreover, PD patients exhibited a higher number of plasma cells, compared to HC individuals. The SLC18A2, TAC1, PCDH8, KIAA0319, PDE6H, AXIN1, and AGTR1 are potential diagnostic biomarkers for PD. Our findings also reveal the essential roles of immune cell infiltration in both disease onset and trajectory.

Project description:BackgroundThe identification of circulating biomarkers that closely correlate with Parkinson's Disease (PD) has failed several times in the past. Nevertheless, in this pilot study, a translational approach was conducted, allowing the evaluation of the plasma levels of two mitochondrial-related proteins, whose combination leads to a robust model with potential diagnostic value to discriminate the PD patients from matched controls.MethodsThe proposed translational approach was initiated by the analysis of secretomes from cells cultured under control or well-defined oxidative stress conditions, followed by the identification of proteins related to PD pathologic mechanisms that were altered between the two states. This pipeline was further translated into the analysis of undepleted plasma samples from 28 control and 31 PD patients.ResultsFrom the secretome analysis, several mitochondria-related proteins were found to be differentially released between control and stress conditions and to be able to distinguish the two secretomes. Similarly, two mitochondrial-related proteins were found to be significantly changed in a PD cohort compared to matched controls. Moreover, a linear discriminant model with potential diagnostic value to discriminate PD patients was obtained using the combination of these two proteins. Both proteins are associated with apoptotic mitochondrial changes, which may correspond to potential indicators of cell death. Moreover, one of these proteins, the VPS35 protein, was reported in plasma for the first time, and its quantification was only possible due to its previous identification in the secretome analysis.ConclusionsIn this work, an adaptation of a translational pipeline for biomarker selection was presented and transposed to neurological diseases, in the present case Parkinson's Disease. The novelty and success of this pilot study may arise from the combination of: i) a translational research pipeline, where plasma samples are interrogated using knowledge previously obtained from the evaluation of cells' secretome under oxidative stress; ii) the combined used of statistical analysis and an informed selection of candidates based on their link with relevant disease mechanisms, and iii) the use of SWATH-MS, an untargeted MS method that allows a complete record of the analyzed samples and a targeted data extraction of the quantitative values of proteins previously identified.

Project description:BackgroundAlzheimer's disease (AD) is the most common cause of dementia, and due to increasing life expectancy the number of patients is expected to grow. The diagnosis of AD involves the use of biomarkers determined by an amyloid PET scan or cerebrospinal fluid analyses that are either invasive or expensive, and not available in each hospital, thus limiting their usage as a front-line screener. The TearAD study aims to use tear fluid as a potential source for AD biomarkers. In previous reports, we demonstrated that AD biomarkers amyloid-beta and tau, are measurable in tear fluid and are associated with disease severity and neurodegeration. This study aims to validate previous results in a larger cohort and evaluate the diagnostic accuracy of tear biomarkers to discriminate between individuals with and without neurodegeneration as determined by hippocampal atrophy.MethodsThe TearAD study is an observational longitudinal multi-center study that will enroll 50 cognitively healthy controls, 50 patients with subjective cognitive decline, 50 patients with mild cognitive impairment and 50 patients with AD dementia from the memory clinic. Participants will be examined at baseline, after one year, and after two years follow-up. Study assessments include neuropsychological tests and ophthalmic examination. All participants will receive a MRI scan, and a subset of the study population will undergo cerebral spinal fluid collection and an amyloid PET scan. Tear fluid will be collected with Schirmer strips and levels of Aβ38, Aβ40, Aβ42, t-tau and p-tau in tear fluid will be determined using multiplex immunoassays. Blood samples will be collected from all participants. Images of the retina will be obtained with a standard, hyperspectral and ultra-wide field fundus camera. Additionally, macular pigment optical density will be measured with the macular pigment reflectometer, and cross-sectional images of the retina will be obtained through optical coherence tomography imaging.DiscussionThe TearAD study will provide insight into the potential diagnostic use of tear biomarkers as a minimally invasive and low cost tool for the screening and diagnosis of AD.Trial registrationRetrospectively registered at clinicaltrials.gov (NCT05655793).

Dataset Information

Potential Tear Biomarkers for the Diagnosis of Parkinson's Disease-A Pilot Study.

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Potential Tear Biomarkers for the Diagnosis of Parkinson's Disease-A Pilot Study.

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