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Tytuł pozycji:

Meta-analysis of genome-wide DNA methylation identifies shared associations across neurodegenerative disorders

Tytuł:
Meta-analysis of genome-wide DNA methylation identifies shared associations across neurodegenerative disorders
Autorzy:
Marta F. Nabais
Simon M. Laws
Tian Lin
Costanza L. Vallerga
Nicola J. Armstrong
Ian P. Blair
John B. Kwok
Karen A. Mather
George D. Mellick
Perminder S. Sachdev
Leanne Wallace
Anjali K. Henders
Ramona A. J. Zwamborn
Paul J. Hop
Katie Lunnon
Ehsan Pishva
Janou A. Y. Roubroeks
Hilkka Soininen
Magda Tsolaki
Patrizia Mecocci
Simon Lovestone
Iwona Kłoszewska
Bruno Vellas
the Australian Imaging Biomarkers and Lifestyle study
the Alzheimer’s Disease Neuroimaging Initiative
Sarah Furlong
Fleur C. Garton
Robert D. Henderson
Susan Mathers
Pamela A. McCombe
Merrilee Needham
Shyuan T. Ngo
Garth Nicholson
Roger Pamphlett
Dominic B. Rowe
Frederik J. Steyn
Kelly L. Williams
Tim J. Anderson
Steven R. Bentley
John Dalrymple-Alford
Javed Fowder
Jacob Gratten
Glenda Halliday
Ian B. Hickie
Martin Kennedy
Simon J. G. Lewis
Grant W. Montgomery
John Pearson
Toni L. Pitcher
Peter Silburn
Futao Zhang
Peter M. Visscher
Jian Yang
Anna J. Stevenson
Robert F. Hillary
Riccardo E. Marioni
Sarah E. Harris
Ian J. Deary
Ashley R. Jones
Aleksey Shatunov
Alfredo Iacoangeli
Wouter van Rheenen
Leonard H. van den Berg
Pamela J. Shaw
Cristopher E. Shaw
Karen E. Morrison
Ammar Al-Chalabi
Jan H. Veldink
Eilis Hannon
Jonathan Mill
Naomi R. Wray
Allan F. McRae
Temat:
Neurodegenerative disorders
DNA methylation
Mixed-linear models
Methylation profile score
Out-of-sample classification
Inflammatory markers
Biology (General)
QH301-705.5
Genetics
QH426-470
Źródło:
Genome Biology, Vol 22, Iss 1, Pp 1-30 (2021)
Wydawca:
BMC, 2021.
Rok publikacji:
2021
Kolekcja:
LCC:Biology (General)
LCC:Genetics
Typ dokumentu:
article
Opis pliku:
electronic resource
Język:
English
ISSN:
1474-760X
Relacje:
https://doaj.org/toc/1474-760X
DOI:
10.1186/s13059-021-02275-5
Dostęp URL:
https://doaj.org/article/201eefeb04d04cf0871060b72f55eedd  Link otwiera się w nowym oknie
Numer akcesji:
edsdoj.201eefeb04d04cf0871060b72f55eedd
Czasopismo naukowe
Abstract Background People with neurodegenerative disorders show diverse clinical syndromes, genetic heterogeneity, and distinct brain pathological changes, but studies report overlap between these features. DNA methylation (DNAm) provides a way to explore this overlap and heterogeneity as it is determined by the combined effects of genetic variation and the environment. In this study, we aim to identify shared blood DNAm differences between controls and people with Alzheimer’s disease, amyotrophic lateral sclerosis, and Parkinson’s disease. Results We use a mixed-linear model method (MOMENT) that accounts for the effect of (un)known confounders, to test for the association of each DNAm site with each disorder. While only three probes are found to be genome-wide significant in each MOMENT association analysis of amyotrophic lateral sclerosis and Parkinson’s disease (and none with Alzheimer’s disease), a fixed-effects meta-analysis of the three disorders results in 12 genome-wide significant differentially methylated positions. Predicted immune cell-type proportions are disrupted across all neurodegenerative disorders. Protein inflammatory markers are correlated with profile sum-scores derived from disease-associated immune cell-type proportions in a healthy aging cohort. In contrast, they are not correlated with MOMENT DNAm-derived profile sum-scores, calculated using effect sizes of the 12 differentially methylated positions as weights. Conclusions We identify shared differentially methylated positions in whole blood between neurodegenerative disorders that point to shared pathogenic mechanisms. These shared differentially methylated positions may reflect causes or consequences of disease, but they are unlikely to reflect cell-type proportion differences.

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