한빛사논문
Dennis M Krüger 1 2 †, Tonatiuh Pena-Centeno 1 2 †, Shiwei Liu 3 †, Tamina Park 3 †, Lalit Kaurani 1, Ranjit Pradhan 1, Yen-Ning Huang 3, Shannon L Risacher 3, Susanne Burkhardt 1, Anna-Lena Schütz 4, Yang Wan 5, Leslie M Shaw 5, Alexander S Brodsky 6, Anita L DeStefano 7, Honghuang Lin 8, Robert Schroeder 1, Andre Krunic 9, Nina Hempel 1, Farahnaz Sananbenesi 4, Jan Krzysztof Blusztajn 9, Andrew J Saykin 10 *, Ivana Delalle 9 *, Kwangsik Nho 10 *, Andre Fischer 1 11 12 13 *; Alzheimer's Disease Neuroimaging Initiative
1Department for Epigenetics and Systems Medicine in Neurodegenerative Diseases, German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany.
2Bioinformatics Unit, German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany.
3Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, USA.
4Research Group for Genome Dynamics in Brain Diseases, German Center for Neurodegenerative Diseases, Göttingen, Germany.
5Perelman School of Medicine, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
6Department of Pathology and Laboratory Medicine, Rhode Island Hospital, Warren Alpert Medical School at Brown University, Providence, Rhode Island, USA.
7Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA.
8Department of Medicine, UMass Chan Medical School, Worcester, Massachusetts, USA.
9Department of Pathology & Laboratory Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts, USA.
10Department of Radiology and Imaging Sciences and the Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA.
11Department for Psychiatry and Psychotherapy, University Medical Center of Göttingen, Georg-August University, Göttingen, Germany.
12Cluster of Excellence "Multiscale Bioimaging: from Molecular Machines to Networks of Excitable Cells" (MBExC), University of Göttingen, Göttingen, Germany.
13German Center for Cardiovascular Diseases (DZKH) Göttingen, Göttingen, Germany.
†Dennis M. Krüger, Tonatiuh Pena-Centeno, Shiwei Liu, and Tamina Park contributed equally to this study.
*Andrew J. Saykin, Ivana Delalle, Kwangsik Nho,and Andre Fischer directed the study
Abstract
Introduction: MicroRNAs are short non-coding RNAs that control proteostasis at the systems level and are emerging as potential prognostic and diagnostic biomarkers for Alzheimer's disease (AD).
Methods: We performed small RNA sequencing on plasma samples from 847 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants.
Results: We identified microRNA signatures that correlate with AD diagnoses and help predict the conversion from mild cognitive impairment (MCI) to AD.
Discussion: Our data demonstrate that plasma microRNA signatures can be used to not only diagnose MCI, but also, critically, predict the conversion from MCI to AD. Moreover, combined with neuropsychological testing, plasma microRNAome evaluation helps predict MCI to AD conversion. These findings are of considerable public interest because they provide a path toward reducing indiscriminate utilization of costly and invasive testing by defining the at-risk segment of the aging population.
Highlights: We provide the first analysis of the plasma microRNAome for the ADNI study. The levels of several microRNAs can be used as biomarkers for the prediction of conversion from MCI to AD. Adding the evaluation of plasma microRNA levels to neuropsychological testing in a clinical setting increases the accuracy of MCI to AD conversion prediction.
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