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Article . 2022 . Peer-reviewed
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A retrotransposon storm marks clinical phenoconversion to late-onset Alzheimer’s disease

Authors: Macciardi, Fabio; Giulia Bacalini, Maria; Miramontes, Ricardo; Boattini, Alessio; Taccioli, Cristian; Modenini, Giorgia; Malhas, Rond; +9 Authors

A retrotransposon storm marks clinical phenoconversion to late-onset Alzheimer’s disease

Abstract

AbstractRecent reports have suggested that the reactivation of otherwise transcriptionally silent transposable elements (TEs) might induce brain degeneration, either by dysregulating the expression of genes and pathways implicated in cognitive decline and dementia or through the induction of immune-mediated neuroinflammation resulting in the elimination of neural and glial cells. In the work we present here, we test the hypothesis that differentially expressed TEs in blood could be used as biomarkers of cognitive decline and development of AD. To this aim, we used a sample of aging subjects (age > 70) that developed late-onset Alzheimer’s disease (LOAD) over a relatively short period of time (12–48 months), for which blood was available before and after their phenoconversion, and a group of cognitive stable subjects as controls. We applied our developed and validated customized pipeline that allows the identification, characterization, and quantification of the differentially expressed (DE) TEs before and after the onset of manifest LOAD, through analyses of RNA-Seq data. We compared the level of DE TEs within more than 600,000 TE-mapping RNA transcripts from 25 individuals, whose specimens we obtained before and after their phenotypic conversion (phenoconversion) to LOAD, and discovered that 1790 TE transcripts showed significant expression differences between these two timepoints (logFC ± 1.5, logCMP > 5.3, nominal p value < 0.01). These DE transcripts mapped both over- and under-expressed TE elements. Occurring before the clinical phenoconversion, this TE storm features significant increases in DE transcripts of LINEs, LTRs, and SVAs, while those for SINEs are significantly depleted. These dysregulations end with signs of manifest LOAD. This set of highly DE transcripts generates a TE transcriptional profile that accurately discriminates the before and after phenoconversion states of these subjects. Our findings suggest that a storm of DE TEs occurs before phenoconversion from normal cognition to manifest LOAD in risk individuals compared to controls, and may provide useful blood-based biomarkers for heralding such a clinical transition, also suggesting that TEs can indeed participate in the complex process of neurodegeneration.

Keywords

Aging, Retroelements, 610, Neurodegenerative, Alzheimer's Disease, Blood biomarkers, Alzheimer Disease, Machine learning, Acquired Cognitive Impairment, Genetics, 2.1 Biological and endogenous factors, Humans, Aetiology, Neurosciences, Alzheimer disease; Blood biomarkers; Gene expression; Machine learning; Retrotransposons; Transposable elements; Biomarkers; Humans; RNA; Alzheimer Disease; Retroelements NIH R01AG030753 and DOD W81XWH-09–1-0107 to H.J.F, by grant NIMH R21-MH115327-01 to F.M. and G.G., and by grant U19AG068054-01, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Alzheimer disease; Blood biomarkers; Gene expression; Machine learning; Retrotransposons; Transposable elements, Brain Disorders, Retrotransposons, Neurological, RNA, Dementia, Original Article, Gene expression, Alzheimer disease, Transposable elements, Biomarkers

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
29
Top 10%
Average
Top 10%
Green
hybrid