Schade, Sebastian

[["dc.bibliographiccitation.artnumber","mds.28738"],["dc.bibliographiccitation.firstpage","2874"],["dc.bibliographiccitation.issue","12"],["dc.bibliographiccitation.journal","Movement Disorders"],["dc.bibliographiccitation.lastpage","2887"],["dc.bibliographiccitation.volume","36"],["dc.contributor.affiliation","Schulz, Isabel; 1\r\nParacelsus‐Elena‐Klinik\r\nKassel Germany"],["dc.contributor.affiliation","Kruse, Niels; 2\r\nDepartment of Neuropathology\r\nUniversity Medical Centre Goettingen\r\nGoettingen Germany"],["dc.contributor.affiliation","Gera, Roland G.; 3\r\nDepartment of Medical Statistics\r\nUniversity Medical Centre Goettingen\r\nGoettingen Germany"],["dc.contributor.affiliation","Kremer, Thomas; 4\r\nRoche Pharmaceutical Research and Early Development\r\nNRD Neuroscience and Rare Disease, Roche Innovation Center Basel, F. Hoffmann‐La Roche Ltd\r\nBasel Switzerland"],["dc.contributor.affiliation","Cedarbaum, Jesse; 5\r\nCoeruleus Clinical Sciences LLC\r\nWoodbidge Connecticut USA"],["dc.contributor.affiliation","Barbour, Robin; 7\r\nProthena Biosciences Inc.\r\nSan Francisco California USA"],["dc.contributor.affiliation","Zago, Wagner; 7\r\nProthena Biosciences Inc.\r\nSan Francisco California USA"],["dc.contributor.affiliation","Schade, Sebastian; 8\r\nDepartment of Neurology\r\nUniversity Medical Centre Goettingen\r\nGoettingen Germany"],["dc.contributor.affiliation","Otte, Birgit; 8\r\nDepartment of Neurology\r\nUniversity Medical Centre Goettingen\r\nGoettingen Germany"],["dc.contributor.affiliation","Bartl, Michael; 8\r\nDepartment of Neurology\r\nUniversity Medical Centre Goettingen\r\nGoettingen Germany"],["dc.contributor.affiliation","Hutten, Samantha J.; 9\r\nThe Michael J. Fox Foundation for Parkinson's Research\r\nNew York New York USA"],["dc.contributor.affiliation","Trenkwalder, Claudia; 1\r\nParacelsus‐Elena‐Klinik\r\nKassel Germany"],["dc.contributor.author","Schulz, Isabel"],["dc.contributor.author","Kruse, Niels"],["dc.contributor.author","Gera, Roland G."],["dc.contributor.author","Kremer, Thomas"],["dc.contributor.author","Cedarbaum, Jesse"],["dc.contributor.author","Barbour, Robin"],["dc.contributor.author","Zago, Wagner"],["dc.contributor.author","Schade, Sebastian"],["dc.contributor.author","Otte, Birgit"],["dc.contributor.author","Bartl, Michael"],["dc.contributor.author","Mollenhauer, Brit"],["dc.contributor.author","Hutten, Samantha J."],["dc.contributor.author","Trenkwalder, Claudia"],["dc.date.accessioned","2021-09-01T06:42:14Z"],["dc.date.available","2021-09-01T06:42:14Z"],["dc.date.issued","2021"],["dc.date.updated","2022-03-21T11:31:27Z"],["dc.description.abstract","ABSTRACT Background Objective diagnostic biomarkers are needed to support a clinical diagnosis. Objectives To analyze markers in various neurodegenerative disorders to identify diagnostic biomarker candidates for mainly α‐synuclein (aSyn)‐related disorders (ASRD) in serum and/or cerebrospinal fluid (CSF). Methods Upon initial testing of commercially available kits or published protocols for the quantification of the candidate markers, assays for the following were selected: total and phosphorylated aSyn (pS129aSyn), neurofilament light chain (NfL), phosphorylated neurofilament heavy chain (pNfH), tau protein (tau), ubiquitin C‐terminal hydrolase L1 (UCHL‐1), glial fibrillary acidic protein (GFAP), calcium‐binding protein B (S100B), soluble triggering receptor expressed on myeloid cells 2 (sTREM‐2), and chitinase‐3‐like protein 1 (YKL‐40). The cohort comprised participants with Parkinson's disease (PD, n = 151), multiple system atrophy (MSA, n = 17), dementia with Lewy bodies (DLB, n = 45), tau protein‐related neurodegenerative disorders (n = 80, comprising patients with progressive supranuclear palsy (PSP, n = 38), corticobasal syndrome (CBS, n = 16), Alzheimer's disease (AD, n = 11), and frontotemporal degeneration/amyotrophic lateral sclerosis (FTD/ALS, n = 15), as well as healthy controls (HC, n = 20). Receiver operating curves (ROC) with area under the curves (AUC) are given for each marker. Results CSF total aSyn was decreased. NfL, pNfH, UCHL‐1, GFAP, S100B, and sTREM‐2 were increased in patients with neurodegenerative disease versus HC (P < 0.05). As expected, some of the markers were highest in AD (i.e., UCHL‐1, GFAP, S100B, sTREM‐2, YKL‐40). Within ASRD, CSF NfL levels were higher in MSA than PD and DLB (P < 0.05). Comparing PD to HC, interesting serum markers were S100B (AUC: 0.86), sTREM2 (AUC: 0.87), and NfL (AUC: 0.78). CSF S100B and serum GFAP were highest in DLB. Conclusions Levels of most marker candidates tested in serum and CSF significantly differed between disease groups and HC. In the stratification of PD versus other tau‐ or aSyn‐related conditions, CSF NfL levels best discriminated PD and MSA. CSF S100B and serum GFAP best discriminated PD and DLB. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson Movement Disorder Society."],["dc.identifier.doi","10.1002/mds.28738"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/89011"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-455"],["dc.relation.eissn","1531-8257"],["dc.relation.issn","0885-3185"],["dc.rights","This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited."],["dc.title","Systematic Assessment of 10 Biomarker Candidates Focusing on α‐Synuclein‐Related Disorders"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1"],["dc.bibliographiccitation.journal","Journal of Parkinson's Disease"],["dc.bibliographiccitation.lastpage","16"],["dc.contributor.author","Bartl, Michael"],["dc.contributor.author","Dakna, Mohammed"],["dc.contributor.author","Schade, Sebastian"],["dc.contributor.author","Wicke, Tamara"],["dc.contributor.author","Lang, Elisabeth"],["dc.contributor.author","Ebentheuer, Jens"],["dc.contributor.author","Weber, Sandrina"],["dc.contributor.author","Trenkwalder, Claudia"],["dc.contributor.author","Mollenhauer, Brit"],["dc.date.accessioned","2021-12-01T09:23:00Z"],["dc.date.available","2021-12-01T09:23:00Z"],["dc.date.issued","2021"],["dc.description.abstract","Background: The MDS-Unified Parkinson’s disease (PD) Rating Scale (MDS-UPDRS) is the most used scale in clinical trials. Little is known about the predictive potential of its single items. Objective: To systematically dissect MDS-UPDRS to predict PD progression. Methods: 574 de novo PD patients and 305 healthy controls were investigated at baseline (BL) in the single-center DeNoPa (6-year follow-up) and multi-center PPMI (8-year follow-up) cohorts. We calculated cumulative link mixed models of single MDS-UPDRS items for odds ratios (OR) for class change within the scale. Models were adjusted for age, sex, time, and levodopa equivalent daily dose. Annual change and progression of the square roots of the MDS-UDPRS subscores and Total Score were estimated by linear mixed modeling. Results: Baseline demographics revealed more common tremor dominant subtype in DeNoPa and postural instability and gait disorders-subtype and multiethnicity in PPMI. Subscore progression estimates were higher in PPMI but showed similar slopes and progression in both cohorts. Increased ORs for faster progression were found from BL subscores I and II (activities of daily living; ADL) most marked for subscore III (rigidity of neck/lower extremities, agility of the legs, gait, hands, and global spontaneity of movements). Tremor items showed low ORs/negative values. Conclusion: Higher scores at baseline for ADL, freezing, and rigidity were predictors of faster deterioration in both cohorts. Precision and predictability of the MDS-UPDRS were higher in the single-center setting, indicating the need for rigorous training and/or video documentation to improve its use in multi-center cohorts, for example, clinical trials."],["dc.description.abstract","Background: The MDS-Unified Parkinson’s disease (PD) Rating Scale (MDS-UPDRS) is the most used scale in clinical trials. Little is known about the predictive potential of its single items. Objective: To systematically dissect MDS-UPDRS to predict PD progression. Methods: 574 de novo PD patients and 305 healthy controls were investigated at baseline (BL) in the single-center DeNoPa (6-year follow-up) and multi-center PPMI (8-year follow-up) cohorts. We calculated cumulative link mixed models of single MDS-UPDRS items for odds ratios (OR) for class change within the scale. Models were adjusted for age, sex, time, and levodopa equivalent daily dose. Annual change and progression of the square roots of the MDS-UDPRS subscores and Total Score were estimated by linear mixed modeling. Results: Baseline demographics revealed more common tremor dominant subtype in DeNoPa and postural instability and gait disorders-subtype and multiethnicity in PPMI. Subscore progression estimates were higher in PPMI but showed similar slopes and progression in both cohorts. Increased ORs for faster progression were found from BL subscores I and II (activities of daily living; ADL) most marked for subscore III (rigidity of neck/lower extremities, agility of the legs, gait, hands, and global spontaneity of movements). Tremor items showed low ORs/negative values. Conclusion: Higher scores at baseline for ADL, freezing, and rigidity were predictors of faster deterioration in both cohorts. Precision and predictability of the MDS-UPDRS were higher in the single-center setting, indicating the need for rigorous training and/or video documentation to improve its use in multi-center cohorts, for example, clinical trials."],["dc.identifier.doi","10.3233/JPD-212860"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/94538"],["dc.notes.intern","DOI-Import GROB-478"],["dc.relation.eissn","1877-718X"],["dc.relation.issn","1877-7171"],["dc.title","Longitudinal Change and Progression Indicators Using the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale in Two Independent Cohorts with Early Parkinson’s Disease"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","mds.29257"],["dc.bibliographiccitation.journal","Movement Disorders"],["dc.contributor.author","Bartl, Michael"],["dc.contributor.author","Dakna, Mohammed"],["dc.contributor.author","Schade, Sebastian"],["dc.contributor.author","Otte, Birgit"],["dc.contributor.author","Wicke, Tamara"],["dc.contributor.author","Lang, Elisabeth"],["dc.contributor.author","Starke, Maritta"],["dc.contributor.author","Ebentheuer, Jens"],["dc.contributor.author","Weber, Sandrina"],["dc.contributor.author","Toischer, Karl"],["dc.contributor.author","Mollenhauer, Brit"],["dc.date.accessioned","2022-11-01T10:16:50Z"],["dc.date.available","2022-11-01T10:16:50Z"],["dc.date.issued","2022"],["dc.identifier.doi","10.1002/mds.29257"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/116667"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-605"],["dc.relation.eissn","1531-8257"],["dc.relation.issn","0885-3185"],["dc.rights.uri","http://creativecommons.org/licenses/by/4.0/"],["dc.title","Blood Markers of Inflammation, Neurodegeneration, and Cardiovascular Risk in Early Parkinson's Disease"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]