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

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.

Metadata

Item Type:	Article
Authors/Creators:	Nabais, 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 https://orcid.org/0000-0002-8925-2567 Shaw, CE Morrison, KE Al-Chalabi, A Veldink, JH Hannon, E Mill, J Wray, NR McRae, AF
Copyright, Publisher and Additional Information:	© 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.
Keywords:	Neurodegenerative disorders; DNA methylation; Mixed-linear models; Methylation profile score; Out-of-sample classification; Inflammatory markers
Dates:	Published: 26 March 2021 Published (online): 26 March 2021 Accepted: 20 January 2021
Institution:	The University of Sheffield
Academic Units:	The University of Sheffield > Sheffield Teaching Hospitals
Funding Information:	Funder Grant number EUROPEAN COMMISSION - FP6/FP7 EUROMOTOR - 259867 EUROPEAN COMMISSION - HORIZON 2020 633413
Depositing User:	Symplectic Sheffield
Date Deposited:	15 Apr 2021 13:11
Last Modified:	16 Apr 2021 13:09
Status:	Published
Publisher:	Springer Science and Business Media LLC
Refereed:	Yes
Identification Number:	10.1186/s13059-021-02275-5
Related URLs:	PubMed URL Dataset
Open Archives Initiative ID (OAI ID):	oai:eprints.whiterose.ac.uk:173063

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

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

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