Authors
Marta F. Nabais
Simon M. Laws, Edith Cowan UniversityFollow
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
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
the Alzheimer's Disease Neuroimaging Initiative
the Australian Imaging Biomarkers and Lifestyle study
Document Type
Journal Article
Publication Title
Genome Biology
Volume
22
Issue
1
PubMed ID
33771206
Publisher
Springer Nature
School
School of Medical and Health Sciences / Centre for Precision Health
RAS ID
35484
Funders
Funding information : https://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02275-5 National Health and Medical Research Council Australian Research Council Edith Cowan University
Grant Number
NHMRC Number : 1078037, 1078901, 1103418, 1107258, 1127440, 1113400, 1405325, 1132524, 1084560,ARC Number : DP160102400, FT180100186, CE10001021
Grant Link
http://purl.org/au-research/grants/nhmrc/1078037 http://purl.org/au-research/grants/nhmrc/1078901 http://purl.org/au-research/grants/nhmrc/1103418 http://purl.org/au-research/grants/nhmrc/1107258 http://purl.org/au-research/grants/nhmrc/1127440 http://purl.org/au-research/grants/nhmrc/1113400 http://purl.org/au-research/grants/nhmrc/1132524 http://purl.org/au-research/grants/nhmrc/1084560 http://purl.org/au-research/grants/arc/DP160102400 http://purl.org/au-research/grants/arc/FT180100186
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.
DOI
10.1186/s13059-021-02275-5
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Comments
Nabais, M. F., Laws, S. M., Lin, T., Vallerga, C. L., Armstrong, N. J., Blair, I. P., ... McRae, A. F. (2021). Meta-analysis of genome-wide DNA methylation identifies shared associations across neurodegenerative disorders. Genome Biology, 22, article 90. https://doi.org/10.1186/s13059-021-02275-5