Accuracy of clinical diagnosis of Parkinson disease: A systematic review and meta-analysis

Jellinger, K. A.; Logroscino, Giancarlo; Rizzo, Giovanni; Copetti, Massimiliano; Arcuti, Simona; Martino, Davide; Fontana, Andrea

doi:10.1212/wnl.0000000000002876

Cited by 42 publications

(29 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Despite the large societal impact of PD, the cause of PD remains elusive and only symptomatic treatments exists. In addition, the clinical diagnosis of PD poses a clear diagnostic challenge and is rejected in 20% of the cases [14]. There is furthermore a need for biomarkers that would allow identification of PD already in the prodromal period [15].…”

mentioning

confidence: 99%

Increasing Comparability and Utility of Gut Microbiome Studies in Parkinson’s Disease: A Systematic Review

Boertien

Pereira

Aho

et al. 2019

JPD

136

160

View full text Add to dashboard Cite

Gut microbiota have been studied in relation to the pathophysiology of Parkinson's disease (PD) due to the early gastrointestinal symptomatology and presence of alpha-synuclein pathology in the enteric nervous system, hypothesized to ascend via the vagal nerve to the central nervous system. Accordingly, sixteen human case-control studies have published gut microbiome composition changes in PD and reported over 100 differentially abundant taxa covering all taxonomic levels from phylum to genus or species, depending on methodology. While certain findings were replicated across several studies, various contradictory findings were reported. Here, differences in methodologies and the presence of possible confounders in the study populations are assessed for their potential to confound the results of gut microbiome studies in PD. Gut microbiome studies in PD exhibited considerable variability with respect to the study population, sample transport conditions, laboratory protocols and sequencing, bioinformatics pipelines, and biostatistical methods. To move from the current heterogeneous dataset towards clinically relevant biomarkers and the identification of putative therapeutic targets, recommendations are derived from the limitations of the available studies to increase the future comparability of microbiome studies in PD. In addition, integration of currently available data on the gut microbiome in PD is proposed to identify robust gut microbiome profiles in PD. Furthermore, expansion of the current dataset with atypical parkinsonism cohorts, prodromal and treatmentnaïve de novo PD subjects, measurements of fecal microbial concentrations and multi-omics assessments are required to provide clinically relevant biomarkers and reveal therapeutic targets within the gut microbiome of PD.

show abstract

mentioning

confidence: 99%

Increasing Comparability and Utility of Gut Microbiome Studies in Parkinson’s Disease: A Systematic Review

Boertien

Pereira

Aho

et al. 2019

JPD

136

160

View full text Add to dashboard Cite

show abstract

“…As a next step in further characterizing the cellular reporter system, we evaluated its ability to detect human-originated αSyn with the future perspective of developing it further into a diagnostic tool [83][84][85][86] . Here, we used CSF samples from a readily available cohort of individuals (42).…”

Section: Discussionmentioning

confidence: 99%

A nanobody-based fluorescent reporter reveals human α-synuclein in the cell cytosol

Gerdes

Waal

Offner

et al. 2019

Preprint

View full text Add to dashboard Cite

Aggregation and spreading of α-Synuclein (αSyn) are hallmarks of several neurodegenerative diseases, thus monitoring human αSyn (hαSyn) in animal models or cell cultures is vital for the field. However, the detection of native hαSyn in such systems is challenging. We found that the nanobody NbSyn87, previously-described to bind hαSyn, also shows cross-reactivity for the proteasomal subunit Rpn10. As such, when the NbSyn87 is expressed in the absence of hαSyn, it is continuously degraded by the proteasome, while it is stabilized when it binds to hαSyn. Here, we exploited this feature to design a new Fluorescent Reporter for hαSyn (FluoReSyn) by coupling NbSyn87 to fluorescent proteins, which results in fluorescence signal fluctuations depending on the presence and amounts of intracellular hαSyn. We characterized this biosensor in cells and tissues, and finally, revealed the presence of transmittable αSyn in human cerebrospinal fluid demonstrating the potential of FluoReSyn for clinical research and diagnostics.

show abstract

“…Till today, in most clinics, these images are interpreted by clinicians; with added possibility of human error. In a study it was reported that the pooled accuracy of clinical diagnosis of Parkinson"s disease is only 80.6% [2]. This motivated us to come up with a new and simple approach to detect Parkinson"s disease at an early stage automatically using Image Processing and Artificial Neural Network.…”

mentioning

confidence: 99%

Early detection of Parkinson’s disease using image processing and artificial neural network

Rumman

Tasneem

Sadia

et al. 2018

2018 Joint 7th International Conference on Informatics, Electronics &Amp; Vision (ICIEV) and 2018 2nd International Conference

View full text Add to dashboard Cite

Early detection of Parkinson"s Disease (PD) is very crucial for effective management and treatment of the disease. Dopaminergic images such as Single Photon Emission Tomography (SPECT) using 123 I-Ioflupane can substantially detect Parkinson"s Disease at an early stage. However, till today, these images are mostly interpreted by humans which can manifest interobserver variability and inconsistency. To improve the imaging diagnosis of PD, we propose a model in this paper, for early detection of Parkinson"s disease using Image Processing and Artificial Neural Network (ANN). The model used 200 SPECT images, 100 of healthy normal and 100 of PD, obtained from Parkinson"s Progression Marker"s Initiative (PPMI) database and processed them to find the area of Caudate and Putamen which is the Region of Interest (ROI)for this study. The area values were then fed to the ANN which is hypothesized to mimic the pattern recognition of a human observer. The simple but fast ANN built, could classify subjects with and without PD with an accuracy of 94%, sensitivity of 100% and specificity of 88%.Hence it can be inferred that the proposed system has the potential to be an effective way to aid the clinicians in the accurate diagnosis of Parkinson"s disease.iii Acknowledgment First of all thanks to the Almighty for giving us the capability to conduct this research and finish our work successfully.Moreover, we would all like to thank our thesis supervisor DR. Md. Ashraful Alam for guiding us all along and working as the main driving force whenever we lacked anything in our work. He kept his door open to us to assist with any problems, big or small, and enlightened us with his immense knowledge on our concerned topic. Furthermore, sincere thanks to BRAC University for creating an entire thesis lab which is well facilitated with sufficient computers, fast internet and all equipment needed for our work. This lab provided all of our team members the opportunity to work together whenever we had to work as a team or work separately.We would also like to thank the Parkinson"s Progress Marker"s Initiative (PPMI) for letting us use their data to conduct our study successfully.Last but not the least, our sincere gratitude to every faculty members who assisted us in making ourselves capable enough throughout our university life and also to all the staffs of our university who are a part of creating a wonderful environment here that contributed to a good and healthy university life.iv

show abstract

Accuracy of clinical diagnosis of Parkinson disease: A systematic review and meta-analysis

Cited by 42 publications

References 9 publications

Increasing Comparability and Utility of Gut Microbiome Studies in Parkinson’s Disease: A Systematic Review

Increasing Comparability and Utility of Gut Microbiome Studies in Parkinson’s Disease: A Systematic Review

A nanobody-based fluorescent reporter reveals human α-synuclein in the cell cytosol

Early detection of Parkinson’s disease using image processing and artificial neural network

Contact Info

Product

Resources

About