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

the Australian Imaging Biomarkers and Lifestyle study(The University of Queensland), Marta F. Nabais(Edith Cowan University), the Alzheimer’s Disease Neuroimaging Initiative(The University of Queensland), Simon M. Laws(Edith Cowan University), Tian Lin(The University of Queensland), Costanza L. Vallerga(The University of Queensland), Nicola J. Armstrong(The University of Sydney), Ian P. Blair(University of South Australia), John B. Kwok(Griffith University), Karen A. Mather(UNSW Sydney), George D. Mellick(Griffith University), Perminder S. Sachdev(The University of Queensland), Leanne Wallace(The University of Queensland), Anjali K. Henders(The University of Queensland), Ramona A.J. Zwamborn(Utrecht University), Paul J. Hop(Utrecht University), Katie Lunnon(University of Exeter), Ehsan Pishva(University of Eastern Finland), Janou A. Y. Roubroeks(Aristotle University of Thessaloniki), Hilkka Soininen(University of Eastern Finland), Magda Tsolaki(Aristotle University of Thessaloniki), Patrizia Mecocci(University of Perugia), Simon Lovestone(Inserm), Iwona Kłoszewska(Medical University of Lodz), Bruno Vellas(Inserm), Sarah Furlong(The University of Queensland), Fleur C. Garton(The University of Queensland), Robert D. Henderson(The University of Queensland), Susan Mathers(Fiona Stanley Hospital), Pamela McCombe(The University of Queensland), Merrilee Needham(Murdoch University), Shyuan T. Ngo(The University of Sydney), Garth A. Nicholson(Concord Repatriation General Hospital), Roger Pamphlett(The University of Sydney), Dominic B. Rowe(Macquarie University), Frederik J. Steyn(The University of Queensland), Kelly L. Williams(Griffith University), Tim Anderson(New Zealand Brain Research Institute), Steven R. Bentley(Griffith University), John C. Dalrymple‐Alford(Translational Research Institute), Javed Fowder(Griffith University), Jacob Gratten(The University of Sydney), Glenda M. Halliday(The University of Sydney), Ian B. Hickie(The University of Sydney), Martin A. Kennedy(The University of Queensland), Simon J.G. Lewis(The University of Sydney), Grant W. Montgomery(The University of Queensland), John F. Pearson(The University of Queensland), Toni L. Pitcher(The University of Queensland), Peter A. Silburn(The University of Queensland), Futao Zhang(The University of Queensland), Peter M. Visscher(The University of Queensland), Jian Yang(The University of Queensland), Anna J. Stevenson(University of Edinburgh), Robert F. Hillary(University of Edinburgh), Riccardo E. Marioni(University of Edinburgh), Sarah E. Harris(King's College London), Ian J. Deary(King's College London), Ashley R. Jones(King's College London), Aleksey Shatunov(King's College London), Alfredo Iacoangeli(King's College London), Wouter van Rheenen(Utrecht University), Leonard H. van den Berg(King's College London), Pamela J. Shaw(Queen's University Belfast), Cristopher E. Shaw(King's College London), Karen Morrison(Queen's University Belfast), Ammar Al‐Chalabi(King's College London), Jan H. Veldink(King's College London), Eilís Hannon(The University of Queensland), Jonathan Mill(The University of Queensland), Naomi R. Wray(The University of Queensland), Allan F. McRae(The University of Queensland)
Genome biology
March 26, 2021
Cited by 106Open Access
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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.


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