====== Multiomics ======

Multiomics refers to a biological analysis approach in which the data sets are multiple "omes", such as the [[genome]], [[proteome]], [[transcriptome]], [[epigenome]], and [[microbiome]]; in other words, the use of multiple omics technologies to study life in a concerted way.
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No single-omic approach completely elucidates the multitude of alterations taking place in [[Alzheimer's disease]] (AD). 

Marttinen et al., from [[Kuopio]], coupled [[transcriptomics]] and [[phosphoproteomics]] approach to determine the [[temporal]] sequence of changes in [[mRNA]], protein, and [[phosphopeptides]] expression level 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, they evaluated the use of decision trees and [[random]] forests in identifying potential [[biomarker]]s 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
((Marttinen M, Paananen J, Neme A, Mitra V, Takalo M, Natunen T, Paldanius KMA, 
Mäkinen P, Bremang M, Kurki MI, Rauramaa T, Leinonen V, Soininen H, Haapasalo A, 
Pike I, Hiltunen M. A multiomic approach to characterize the temporal sequence in
Alzheimer's disease-related pathology. Neurobiol Dis. 2018 Dec 14. pii:
S0969-9961(18)30479-0. doi: 10.1016/j.nbd.2018.12.009. [Epub ahead of print]
PubMed PMID: 30557660.
)).