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Neurobiol Dis. 2019 Apr;124:454-468. doi: 10.1016/j.nbd.2018.12.009. Epub 2018 Dec 15.

A multiomic approach to characterize the temporal sequence in Alzheimer's disease-related pathology.

Author information

1
Institute of Biomedicine, University of Eastern Finland, Kuopio 70210, Finland.
2
Proteome Sciences plc, Cobham, London WC1H 9BB, United Kingdom.
3
Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Psychiatry, Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Neurosurgery of Neuro Center, Kuopio University Hospital, Kuopio 70029, Finland.
4
Department of Pathology, Kuopio University Hospital and University of Eastern Finland, Kuopio 70029, Finland.
5
Neurosurgery of Neuro Center, Kuopio University Hospital, Kuopio 70029, Finland.
6
Neurology of Neuro Center, Kuopio University Hospital, Kuopio 70029, Finland; Institute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio 70210, Finland.
7
A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio 70211, Finland.
8
Institute of Biomedicine, University of Eastern Finland, Kuopio 70210, Finland. Electronic address: mikko.hiltunen@uef.fi.

Abstract

No single-omic approach completely elucidates the multitude of alterations taking place in Alzheimer's disease (AD). Here, we coupled transcriptomic and phosphoproteomic approaches to determine the temporal sequence of changes in mRNA, protein, and phosphopeptide expression levels from human temporal cortical samples, with varying degree of AD-related pathology. This approach highlighted fluctuation in synaptic and mitochondrial function as the earliest pathological events in brain samples with AD-related pathology. Subsequently, increased expression of inflammation and extracellular matrix-associated gene products was observed. Interaction network assembly for the associated gene products, emphasized the complex interplay between these processes and the role of addressing post-translational modifications in the identification of key regulators. Additionally, we evaluate the use of decision trees and random forests in identifying potential biomarkers differentiating individuals with different degree of AD-related pathology. This multiomic and temporal sequence-based approach provides a better understanding of the sequence of events leading to AD.

KEYWORDS:

Alzheimer's disease; Human brain; Phosphoproteomics; Systems biology; Transcriptomics

PMID:
30557660
DOI:
10.1016/j.nbd.2018.12.009
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