Meta-analysis of genome-wide DNA methylation identifies shared associations across neurodegenerative disorders (2021)
Type of ContentJournal Article
PublisherSpringer Science and Business Media LLC
- Science: Journal Articles 
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.
CitationNabais MF, Laws SM, Lin T, Vallerga CL, Armstrong NJ, Blair IP, Kwok JB, Mather KA, Mellick GD, Sachdev PS, Wallace L, Henders AK, Zwamborn RAJ, Hop PJ, Lunnon K, Pishva E, Roubroeks JAY, Soininen H, Tsolaki M, Mecocci P, Lovestone S, Kłoszewska I, Vellas B, Furlong S, Garton FC, Henderson RD, Mathers S, McCombe PA, Needham M, Ngo ST, Nicholson G, Pamphlett R, Rowe DB, Steyn FJ, Williams KL, Anderson TJ, Bentley SR, Dalrymple-Alford J, Fowder J, Gratten J, Halliday G, Hickie IB, Kennedy M, Lewis SJG, Montgomery GW, Pearson J, Pitcher TL, Silburn P, Zhang F, Visscher PM, Yang J, Stevenson AJ, Hillary RF, Marioni RE, Harris SE, Deary IJ, Jones AR, Shatunov A, Iacoangeli A, van Rheenen W, van den Berg LH, Shaw PJ, Shaw CE, Morrison KE, Al-Chalabi A, Veldink JH, Hannon E, Mill J, Wray NR, McRae AF (2021). Meta-analysis of genome-wide DNA methylation identifies shared associations across neurodegenerative disorders. Genome Biology. 22(1). 90-.
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Keywordsneurodegenerative disorders; DNA methylation; Mixed-linear models; Methylation profile score; Out-of-sample classification; inflammatory markers
ANZSRC Fields of Research32 - Biomedical and clinical sciences::3209 - Neurosciences::320905 - Neurology and neuromuscular diseases
31 - Biological sciences::3105 - Genetics::310504 - Epigenetics (incl. genome methylation and epigenomics)
Rights© The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
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