Journal Article

DZNE-2024-01342

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png The plasma miRNAome in ADNI: Signatures to aid the detection of at-risk individuals.

Krüger, D. M. (First author)DZNE* ; Pena Centeno, T.DZNE* ; Liu, S. ; Park, T. ; Kaurani, L.DZNE* ; Pradhan, R.DZNE* ; Huang, Y.-N. ; Risacher, S. L. ; Burkhardt, S.DZNE* ; Schütz, A.-L.DZNE* ; Wan, Y. ; Shaw, L. M. ; Brodsky, A. S. ; DeStefano, A. L. ; Lin, H. ; Schroeder, R.DZNE* ; Krunic, A. ; Hempel, N.DZNE* ; Sananbenesi, F.DZNE* ; Blusztajn, J. K. ; Saykin, A. J. ; Delalle, I. ; Nho, K. ; Fischer, A. (Last author)DZNE* ; Initiative, A. D. N. (Collaboration Author)

2024
Wiley Hoboken, NJ

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Please use a persistent id in citations: doi:10.1002/alz.14157

Abstract: 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).We performed small RNA sequencing on plasma samples from 847 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants.We identified microRNA signatures that correlate with AD diagnoses and help predict the conversion from mild cognitive impairment (MCI) to AD.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.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.

Keyword(s): Humans (MeSH) ; Alzheimer Disease: blood (MeSH) ; Alzheimer Disease: genetics (MeSH) ; Alzheimer Disease: diagnosis (MeSH) ; MicroRNAs: blood (MeSH) ; MicroRNAs: genetics (MeSH) ; Cognitive Dysfunction: blood (MeSH) ; Cognitive Dysfunction: genetics (MeSH) ; Cognitive Dysfunction: diagnosis (MeSH) ; Aged (MeSH) ; Female (MeSH) ; Male (MeSH) ; Biomarkers: blood (MeSH) ; Neuropsychological Tests: statistics & numerical data (MeSH) ; Disease Progression (MeSH) ; Aged, 80 and over (MeSH) ; Neuroimaging (MeSH) ; Alzheimer's disease ; blood biomarker ; cognitive decline ; microRNA ; mild cognitive impairment ; plasma ; small non‐coding RNA ; MicroRNAs ; Biomarkers

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Contributing Institute(s):

1. Epigenetics and Systems Medicine in Neurodegenerative Diseases (AG Fischer)
2. Bioinformatics and Genome Dynamics Core (Göttingen) (Bioinformatics Unit (Göttingen))
3. Genome Dynamics in Neurodegenerative Diseases (AG Sananbenesi)

Research Program(s):

1. 352 - Disease Mechanisms (POF4-352) (POF4-352)
2. 899 - ohne Topic (POF4-899) (POF4-899)

Appears in the scientific report 2024

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Database coverage:
; ; ; Clarivate Analytics Master Journal List ; Current Contents - Clinical Medicine ; DEAL Wiley ; Essential Science Indicators ; IF >= 10 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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