Identification of Novel Biomarkers in Platelets for Diagnosing Parkinson’s Disease

2021 ◽  
pp. 1-10
Author(s):  
Lei Zhang ◽  
Yiye Shao ◽  
Chunlei Tang ◽  
Zhen Liu ◽  
Dingzhong Tang ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Tumor Necrosis Factor Receptor ◽  
Elongation Factor ◽  
Enrichment Analysis ◽  
The Elderly ◽  
Illumina Hiseq ◽  
Cytoplasmic Vesicle ◽  
Significant Term ◽  
Neutrophil Degranulation

<b><i>Background:</i></b> Parkinson’s disease (PD) is a common neurodegenerative disease affecting the elderly, but there is no blood test for PD diagnosis in the clinic currently. This study aimed to explore promising biomarkers in platelets (PLTs) for PD diagnosis. <b><i>Methods:</i></b> PLTs were isolated from whole blood samples of PD patients and healthy controls (HCs), and RNA was extracted for sequencing. RNA-seq was performed on the Illumina HiSeq platform. <b><i>Results:</i></b> A total of 2,221 genes with differential transcript levels (GDTLs) were identified between PD patients and HCs, 1,041 of which are upregulated genes and 1,180 of which are downregulated genes. <i>WASH5P</i> was the most upregulated gene and <i>AC114491.1</i> was the most downregulated gene. Among the top 12 most relevant genes, metastasis-associated lung adenocarcinoma transcript 1 (<i>MALAT1</i>), eukaryotic elongation factor 1A (<i>EEF1A1</i>), and cathepsin S (<i>CTSS</i>) were reported to be associated with PD. Furthermore, gene ontology analysis showed that the most significant term in biological processes was neutrophil degranulation; the most enriched term in cellular components was cytoplasmic vesicle lumen; and tumor necrosis factor receptor superfamily binding was the most significant term in molecular functions. In the Kyoto Encyclopedia of Genes and Genomes enrichment analysis, inflammation-related pathway accounts for the majority. <b><i>Conclusion:</i></b> Our findings demonstrated <i>WASH5P</i>, <i>MALAT1</i>, <i>EEF1A1,</i> and <i>CTSS</i> may be promising biomarkers in PD, which may contribute to improving the effectiveness and accuracy of diagnosis for PD in the future.

scholarly journals Integrated network analysis identifying potential novel drug candidates and targets for Parkinson's disease

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Pusheng Quan ◽  
Kai Wang ◽  
Shi Yan ◽  
Shirong Wen ◽  
Chengqun Wei ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Drug Target ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Control Group ◽  
Drug Candidates ◽  
Novel Drug

AbstractThis study aimed to identify potential novel drug candidates and targets for Parkinson’s disease. First, 970 genes that have been reported to be related to PD were collected from five databases, and functional enrichment analysis of these genes was conducted to investigate their potential mechanisms. Then, we collected drugs and related targets from DrugBank, narrowed the list by proximity scores and Inverted Gene Set Enrichment analysis of drug targets, and identified potential drug candidates for PD treatment. Finally, we compared the expression distribution of the candidate drug-target genes between the PD group and the control group in the public dataset with the largest sample size (GSE99039) in Gene Expression Omnibus. Ten drugs with an FDR < 0.1 and their corresponding targets were identified. Some target genes of the ten drugs significantly overlapped with PD-related genes or already known therapeutic targets for PD. Nine differentially expressed drug-target genes with p < 0.05 were screened. This work will facilitate further research into the possible efficacy of new drugs for PD and will provide valuable clues for drug design.

Time Trends and Geographical Variation in Parkinson's Disease in Scotland

1992 ◽  
Vol 37 (4) ◽  
pp. 112-115 ◽  
Author(s):  
W.C.S. Smith ◽  
W.J. Mutch
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Time Trends ◽  
Geographical Variation ◽  
The Elderly ◽  
Epidemiological Studies ◽  
Space Distribution ◽  
Mortality Data ◽  
Time And Space ◽  
Factors Affecting

Parkinson's disease is a common and disabling condition which principally affects the elderly. The time and space distribution of Parkinson's disease has been examined to determine if it provides clues as to aetiology and factors affecting its distribution. Previous studies have used mortality data,1 data from epidemiological studies,2 and pre scribing information particularly with regard to the use of levodopa.3 These studies have looked within countries and between countries.

PARKINSON'S DISEASE AND PARKINSONISM IN THE ELDERLY.

Brain ◽  
2000 ◽  
Vol 123 (12) ◽  
pp. 2569-2571
Author(s):  
D. M. W. I. M. Horstink
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
The Elderly

scholarly journals Kin-FOG: Automatic Simulated Freezing of Gait (FOG) Assessment System for Parkinson’s Disease

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2416 ◽  
Author(s):  
Sara Soltaninejad ◽  
Irene Cheng ◽  
Anup Basu
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Freezing Of Gait ◽  
The Elderly ◽  
Assessment System ◽  
Microsoft Kinect ◽  
Data Sets ◽  
Fog Prediction ◽  
Foot Joint ◽  
Rehabilitation Clinic

Parkinson’s disease (PD) is one of the leading neurological disorders in the world with an increasing incidence rate for the elderly. Freezing of Gait (FOG) is one of the most incapacitating symptoms for PD especially in the later stages of the disease. FOG is a short absence or reduction of ability to walk for PD patients which can cause fall, reduction in patients’ quality of life, and even death. Existing FOG assessments by doctors are based on a patient’s diaries and experts’ manual video analysis which give subjective, inaccurate, and unreliable results. In the present research, an automatic FOG assessment system is designed for PD patients to provide objective information to neurologists about the FOG condition and the symptom’s characteristics. The proposed FOG assessment system uses an RGB-D sensor based on Microsoft Kinect V2 for capturing data for 5 healthy subjects who are trained to imitate the FOG phenomenon. The proposed FOG assessment system is called “Kin-FOG”. The analysis of foot joint trajectory of the motion captured by Kinect is used to find the FOG episodes. The evaluation of Kin-FOG is performed by two types of experiments, including: (1) simple walking (SW); and (2) walking with turning (WWT). Since the standing mode has features similar to a FOG episode, our Kin-FOG system proposes a method to distinguish between the FOG and standing episodes. Therefore, two general groups of experiments are conducted with standing state (WST) and without standing state (WOST). The gradient displacement of the angle between the foot and the ground is used as the feature for discriminating between FOG and standing modes. These experiments are conducted with different numbers of FOGs for getting reliable and general results. The Kin-FOG system reports the number of FOGs, their lengths, and the time slots when they occur. Experimental results demonstrate Kin-FOG has around 90% accuracy rate for FOG prediction in both experiments for different tasks (SW, WWT). The proposed Kin-FOG system can be used as a remote application at a patient’s home or a rehabilitation clinic for sending a neurologist the required FOG information. The reliability and generality of the proposed system will be evaluated for bigger data sets of actual PD subjects.

Parkinson's disease and prostate enlargement: Both contribute to overactive bladder in the elderly

2018 ◽  
Vol 25 (11) ◽  
pp. 982-983 ◽  
Author(s):  
Ryuji Sakakibara ◽  
Fang-Ching Lee ◽  
Hiroyoshi Suzuki ◽  
Fuyuki Tateno ◽  
Masahiko Kishi ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Overactive Bladder ◽  
The Elderly ◽  
Prostate Enlargement

scholarly journals Parkinson’s Disease and Symptomatic Osteoarthritis Are Independent Risk Factors of Falls in the Elderly

2019 ◽  
Vol 12 ◽  
pp. 117954411988493 ◽  
Author(s):  
Anneli Teder-Braschinsky ◽  
Aare Märtson ◽  
Marika Rosenthal ◽  
Pille Taba
Keyword(s):  
Risk Factors ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Knee Osteoarthritis ◽  
The Elderly ◽  
Control Group ◽  
Increased Risk ◽  
Symptomatic Knee ◽  
Risk Of Falls ◽  
Risk Factors For Falls

Objectives: Deteriorating functionality and loss of mobility, resulting from Parkinson’s disease, may be worsened by osteoarthritis, which is the most common form of joint disease causing pain and functional impairment. We assessed the association between symptomatic hip or knee osteoarthritis, falls, and the ability to walk among patients with Parkinson’s disease compared to a control group. Methods: A total of 136 patients with Parkinson’s disease in Southern Estonia and 142 controls with an average age of 76.8 and 76.3 years, respectively, were enrolled in a retrospective case-control study. Information on falls and related fractures during the previous year was collected from the patients with Parkinson’s disease and controls. Covariates included gender, age, mobility, duration of Parkinson’s disease, and fractures. Results: Patients with Parkinson’s disease were at an increased risk of falls compared to the control group, and for the higher risk of fractures. Symptomatic knee or hip osteoarthritis was a significant independent predictor of falls in both patients with Parkinson’s disease and controls. The higher risk for fractures during the previous year was demonstrated in symptomatic osteoarthritis. Risk factors for falls included also female gender, use of sleep pills, and the inability to walk 500 m. Conclusions: Symptomatic hip and knee osteoarthritis are risk factors for falls and related fractures among the elderly population with and without Parkinson’s disease. The inability to walk 500 m could be used as a simple predictive factor for the increased risk of falls among elderly populations.

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