| 1 | Machine Learning to Detect Alzheimer’s Disease from Circulating Non-coding RNAs显示文摘Blood-borne small non-coding(snc RNAs)are among the prominent candidates for blood-based diagnostic tests.Often,high-throughput approaches are applied to discover biomarker signatures.These have to be validated in larger cohorts and evaluated by adequate statistical learning approaches.Previously,we published high-throughput sequencing based microRNA(miRNA)signatures in Alzheimer’s disease(AD)patients in the United States(US)and Germany.Here,we determined abundance levels of 21 known circulating miRNAs in 465 individuals encompassing AD patients and controls by RT-qPCR.We computed models to assess the relation between miRNA expression and phenotypes,gender,age,or disease severity(Mini-Mental State Examination;MMSE).Of the 21 miRNAs,expression levels of 20 miRNAs were consistently de-regulated in the US and German cohorts.18 miRNAs were significantly correlated with neurodegeneration(Benjamini-Hochberg adjusted P<0.05)with highest significance for miR-532-5 p(BenjaminiHochberg adjusted P=4.8×10^-30).Machine learning models reached an area under the curve(AUC)value of 87.6%in differentiating AD patients from controls.Further,ten miRNAs were significantly correlated with MMSE,in particular miR-26a/26b-5p(adjusted P=0.0002).Interestingly,the miRNAs with lower abundance in AD were enriched in monocytes and T-helper cells,while those up-regulated in AD were enriched in serum,exosomes,cytotoxic t-cells,and B-cells.Our study represents the next important step in translational research for a miRNA-based AD test. | Nicole Ludwig Tobias Fehlmann Fabian Kern Manfred Gogol Walter Maetzler Stephanie Deutscher Simone Gurlit Claudia Schulte Anna-Katharina von Thaler Christian Deuschle Florian Metzger Daniela Berg Ulrike Suenkel Verena Keller Christina Backes Hans-Peter Lenhof Eckart Meese Andreas Keller | 2019 | Genomics, Proteomics & Bioinformatics2019，17，4： | 2 |
| 4 | No association between Parkinson disease and autoantibodies against NMDA-type glutamate receptors显示文摘Background:IgG-class autoantibodies to N-Methyl-D-Aspartate(NMDA)-type glutamate receptors define a novel entity of autoimmune encephalitis.Studies examining the prevalence of NMDA IgA/IgM antibodies in patients with Parkinson disease with/without dementia produced conflicting results.We measured NMDA antibodies in a large,well phenotyped sample of Parkinson patients without and with cognitive impairment(n=296)and controls(n=295)free of neuropsychiatric disease.Detailed phenotyping and large numbers allowed statistically meaningful correlation of antibody status with diagnostic subgroups as well as quantitative indicators of disease severity and cognitive impairment.Methods:NMDA antibodies were analysed in the serum of patients and controls using well established validated assays.We used anti-NMDA antibody positivity as the main independent variable and correlated it with disease status and phenotypic characteristics.Results:The frequency of NMDA IgA/IgM antibodies was lower in Parkinson patients(13%)than in controls(22%)and higher than in previous studies in both groups.NMDA IgA/IgM antibodies were neither significantly associated with diagnostic subclasses of Parkinson disease according to cognitive impairment,nor with quantitative indicators of disease severity and cognitive impairment.A positive NMDA antibody status was positively correlated with age in controls but not in Parkinson patients.Conclusion:It is unlikely albeit not impossible that NMDA antibodies play a significant role in the pathogenesis or progression of Parkinson disease e.g.to Parkinson disease with dementia,while NMDA IgG antibodies define a separate disease of its own. | Franziska Hopfner Stefanie HMüller Dagmar Steppat Joanna Miller Nele Schmidt Klaus-Peter Wandinger Frank Leypoldt Daniela Berg Andre Franke Wolfgang Lieb Lukas Tittmann Monika Balzer-Geldsetzer Simon Baudrexel Richard Dodel Ruediger Hilker-Roggendorf Elke Kalbe Jan Kassubek Thomas Klockgether Inga Liepelt-Scarfone Brit Mollenhauer Petra Neuser Kathrin Reetz Oliver Riedel Claudia Schulte Jörg BSchulz Annika Spottke Alexander Storch Claudia Trenkwalder Hans-Ulrich Wittchen Karsten Witt Ullrich Wüllner Günther Deuschl Gregor Kuhlenbäumer | 2019 | Translational Neurodegeneration2019，8，1： | 0 |
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