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

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 MecocciSimon Lovestone, Iwona Kłoszewska, Bruno Vellas, Australian Imaging Biomarkers and Lifestyle study, 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*

*Corresponding author for this work

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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.

Original languageEnglish
Article number90
Pages (from-to)1-30
Number of pages30
JournalGenome biology
Volume22
Issue number1
DOIs
Publication statusPublished - 26 Mar 2021

Bibliographical note

Copyright the Author(s) 2021. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

  • DNA methylation
  • Inflammatory markers
  • Methylation profile score
  • Mixed-linear models
  • Neurodegenerative disorders
  • Out-of-sample classification

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