Project description:Parkinson's disease (PD) is the second most common neurodegenerative disease after Alzheimer's disease. The purpose of this study was to analyze the profile of the tear proteome of patients with idiopathic PD (iPD), carriers of the E46K-SNCA mutation and healthy subjects (CT) and to identify biomarkers for the early diagnosis of PD. An observational, prospective and case-control pilot study was carried out in 24 patients with iPD, 3 carriers of the E46K-SNCA mutation and 27 CT subjects. The patients' neurological involvement was scored and their tear samples were analyzed using nano-liquid chromatography-mass spectrometry (nLC-MS/MS). These analyses led to the identification of 560 tear proteins in which some of the deregulated proteins were involved in immune response, apoptosis, collagen degradation, protein synthesis, defense and altered lysosomal function. Of these proteins, six related to neurodegenerative processes, showed a good capacity to classify patients and controls. These findings revealed that some proteins were upregulated in the tears of PD patients, mainly those involved in lysosomal function. It is worth highlighting the importance of this study in identifying tear proteins implicated in neurodegeneration and its relationship with PD patients with an aggressive disease phenotype.
Project description:Parkinson's Disease (PD) and Non-Demented Control (NDC) human sera were probed onto human protein microarrays in order to identify differentially expressed autoantibody biomarkers that could be used as diagnostic indicators.
Project description:Parkinson's Disease (PD) and Non-Demented Control (NDC) human sera were probed onto human protein microarrays in order to identify differentially expressed autoantibody biomarkers that could be used as diagnostic indicators. In the study presented here, 29 PD and 40 NDC human serum samples were probed onto human protein microarrays in order to identify differentially expressed autoantibodies. Microarray data was analyzed using several statistical significance algorithms, and autoantibodies that demonstrated significant group prevelance were selected as biomarkers of disease. Prediction classification analysis tested the diagnostic efficacy of the identified biomarkers; and differentiation of PD samples from other neurodegeneratively-diseased and non-neurodegeneratively-diseased controls (Alzheimer's disease, multiple sclerosis, and breast cancer) confirmed their specificity.
Project description:Identification of early Parkinson's disease events by developing methodology that utilizes recent innovations in human pluripotent stem cells and chemical sensors of HSP90-incorporating chaperome networks.
Project description:Parkinson's disease is the second most prevalent neurodegenerative disorder, characterized by the degeneration of dopaminergic neurons. Significant improvements in gait balance, particularly step length and velocity, were revealed by less-invasive wireless cortical stimulation. Transcriptome sequencing was performed to demonstrate the cellular mechanism, specifically targeting the primary motor cortex where the stimulation was applied. Our findings indicated that the differentially expressed genes (DEGs), initially down-regulated following Parkinson's disease induction, were subsequently restored to normal levels after cortical stimulation. We propose these DEGs as a potential target for motor disorder treatment in Parkinson's disease. These genes are implicated in crucial processes such as astrocyte-mediated blood vessel development and microglia-mediated phagocytosis of damaged motor neurons, suggesting their significant roles in improvement of behavior disorder. Moreover, these biomarkers not only facilitate rapid and accurate diagnosis of Parkinson's disease but also assist precision medicine approaches.
Project description:Human serum samples from early-stage Parkinson's disease and non-diseased controls were probed onto human protein microarrays in order to identify differentially expressed autoantibody biomarkers that could be used as diagnostic indicators. Other neurodegenerative and non-neurodegenerative diseases were also used to help measure the specificity of the selected biomarkers.