@article{KuzkinaBargarSchmittetal.2021, author = {Kuzkina, Anastasia and Bargar, Connor and Schmitt, Daniela and R{\"o}ßle, Jonas and Wang, Wen and Schubert, Anna-Lena and Tatsuoka, Curtis and Gunzler, Steven A. and Zou, Wen-Quan and Volkmann, Jens and Sommer, Claudia and Doppler, Kathrin and Chen, Shu G.}, title = {Diagnostic value of skin RT-QuIC in Parkinson's disease: a two-laboratory study}, series = {NPJ Parkinson's Disease}, volume = {7}, journal = {NPJ Parkinson's Disease}, number = {1}, doi = {10.1038/s41531-021-00242-2}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-260451}, year = {2021}, abstract = {Skin alpha-synuclein deposition is considered a potential biomarker for Parkinson's disease (PD). Real-time quaking-induced conversion (RT-QuIC) is a novel, ultrasensitive, and efficient seeding assay that enables the detection of minute amounts of alpha-synuclein aggregates. We aimed to determine the diagnostic accuracy, reliability, and reproducibility of alpha-synuclein RT-QuIC assay of skin biopsy for diagnosing PD and to explore its correlation with clinical markers of PD in a two-center inter-laboratory comparison study. Patients with clinically diagnosed PD (n = 34), as well as control subjects (n = 30), underwent skin punch biopsy at multiple sites (neck, lower back, thigh, and lower leg). The skin biopsy samples (198 in total) were divided in half to be analyzed by RT-QuIC assay in two independent laboratories. The a-synuclein RT-QuIC assay of multiple skin biopsies supported the clinical diagnosis of PD with a diagnostic accuracy of 88.9\% and showed a high degree of inter-rater agreement between the two laboratories (92.2\%). Higher alpha-synuclein seeding activity in RT-QuIC was shown in patients with longer disease duration and more advanced disease stage and correlated with the presence of REM sleep behavior disorder, cognitive impairment, and constipation. The alpha-synuclein RT-QuIC assay of minimally invasive skin punch biopsy is a reliable and reproducible biomarker for Parkinson's disease. Moreover, alpha-synuclein RT-QuIC seeding activity in the skin may serve as a potential indicator of progression as it correlates with the disease stage and certain non-motor symptoms.}, language = {en} } @article{JiangOronClarketal.2016, author = {Jiang, Yuxiang and Oron, Tal Ronnen and Clark, Wyatt T. and Bankapur, Asma R. and D'Andrea, Daniel and Lepore, Rosalba and Funk, Christopher S. and Kahanda, Indika and Verspoor, Karin M. and Ben-Hur, Asa and Koo, Da Chen Emily and Penfold-Brown, Duncan and Shasha, Dennis and Youngs, Noah and Bonneau, Richard and Lin, Alexandra and Sahraeian, Sayed M. E. and Martelli, Pier Luigi and Profiti, Giuseppe and Casadio, Rita and Cao, Renzhi and Zhong, Zhaolong and Cheng, Jianlin and Altenhoff, Adrian and Skunca, Nives and Dessimoz, Christophe and Dogan, Tunca and Hakala, Kai and Kaewphan, Suwisa and Mehryary, Farrokh and Salakoski, Tapio and Ginter, Filip and Fang, Hai and Smithers, Ben and Oates, Matt and Gough, Julian and T{\"o}r{\"o}nen, Petri and Koskinen, Patrik and Holm, Liisa and Chen, Ching-Tai and Hsu, Wen-Lian and Bryson, Kevin and Cozzetto, Domenico and Minneci, Federico and Jones, David T. and Chapman, Samuel and BKC, Dukka and Khan, Ishita K. and Kihara, Daisuke and Ofer, Dan and Rappoport, Nadav and Stern, Amos and Cibrian-Uhalte, Elena and Denny, Paul and Foulger, Rebecca E. and Hieta, Reija and Legge, Duncan and Lovering, Ruth C. and Magrane, Michele and Melidoni, Anna N. and Mutowo-Meullenet, Prudence and Pichler, Klemens and Shypitsyna, Aleksandra and Li, Biao and Zakeri, Pooya and ElShal, Sarah and Tranchevent, L{\´e}on-Charles and Das, Sayoni and Dawson, Natalie L. and Lee, David and Lees, Jonathan G. and Sillitoe, Ian and Bhat, Prajwal and Nepusz, Tam{\´a}s and Romero, Alfonso E. and Sasidharan, Rajkumar and Yang, Haixuan and Paccanaro, Alberto and Gillis, Jesse and Sede{\~n}o-Cort{\´e}s, Adriana E. and Pavlidis, Paul and Feng, Shou and Cejuela, Juan M. and Goldberg, Tatyana and Hamp, Tobias and Richter, Lothar and Salamov, Asaf and Gabaldon, Toni and Marcet-Houben, Marina and Supek, Fran and Gong, Qingtian and Ning, Wei and Zhou, Yuanpeng and Tian, Weidong and Falda, Marco and Fontana, Paolo and Lavezzo, Enrico and Toppo, Stefano and Ferrari, Carlo and Giollo, Manuel and Piovesan, Damiano and Tosatto, Silvio C. E. and del Pozo, Angela and Fern{\´a}ndez, Jos{\´e} M. and Maietta, Paolo and Valencia, Alfonso and Tress, Michael L. and Benso, Alfredo and Di Carlo, Stefano and Politano, Gianfranco and Savino, Alessandro and Rehman, Hafeez Ur and Re, Matteo and Mesiti, Marco and Valentini, Giorgio and Bargsten, Joachim W. and van Dijk, Aalt D. J. and Gemovic, Branislava and Glisic, Sanja and Perovic, Vladmir and Veljkovic, Veljko and Almeida-e-Silva, Danillo C. and Vencio, Ricardo Z. N. and Sharan, Malvika and Vogel, J{\"o}rg and Kansakar, Lakesh and Zhang, Shanshan and Vucetic, Slobodan and Wang, Zheng and Sternberg, Michael J. E. and Wass, Mark N. and Huntley, Rachael P. and Martin, Maria J. and O'Donovan, Claire and Robinson, Peter N. and Moreau, Yves and Tramontano, Anna and Babbitt, Patricia C. and Brenner, Steven E. and Linial, Michal and Orengo, Christine A. and Rost, Burkhard and Greene, Casey S. and Mooney, Sean D. and Friedberg, Iddo and Radivojac, Predrag and Veljkovic, Nevena}, title = {An expanded evaluation of protein function prediction methods shows an improvement in accuracy}, series = {Genome Biology}, volume = {17}, journal = {Genome Biology}, number = {184}, doi = {10.1186/s13059-016-1037-6}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-166293}, year = {2016}, abstract = {Background A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent.}, language = {en} } @book{Wang2008, author = {Wang, Wen}, title = {Validation of shRNA clones for gene silencing in 293FT cells}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-25955}, publisher = {Universit{\"a}t W{\"u}rzburg}, year = {2008}, abstract = {...}, subject = {shRNA}, language = {en} }