TY - JOUR
T1 - Meta-analysis of genome-wide DNA methylation identifies shared associations across neurodegenerative disorders
AU - the Australian Imaging Biomarkers and Lifestyle study
AU - The Alzheimer’s Disease Neuroimaging Initiative
AU - Nabais, Marta F.
AU - Laws, Simon M.
AU - Lin, Tian
AU - Vallerga, Costanza L.
AU - Armstrong, Nicola J.
AU - Blair, Ian P.
AU - Kwok, John B.
AU - Mather, Karen A.
AU - Mellick, George D.
AU - Sachdev, Perminder S.
AU - Wallace, Leanne
AU - Henders, Anjali K.
AU - Zwamborn, Ramona A.J.
AU - Hop, Paul J.
AU - Lunnon, Katie
AU - Pishva, Ehsan
AU - Roubroeks, Janou A.Y.
AU - Soininen, Hilkka
AU - Tsolaki, Magda
AU - Mecocci, Patrizia
AU - Lovestone, Simon
AU - Kłoszewska, Iwona
AU - Vellas, Bruno
AU - Furlong, Sarah
AU - Garton, Fleur C.
AU - Henderson, Robert D.
AU - Mathers, Susan
AU - McCombe, Pamela A.
AU - Needham, Merrilee
AU - Ngo, Shyuan T.
AU - Nicholson, Garth
AU - Pamphlett, Roger
AU - Rowe, Dominic B.
AU - Steyn, Frederik J.
AU - Williams, Kelly L.
AU - Anderson, Tim J.
AU - Bentley, Steven R.
AU - Dalrymple-Alford, John
AU - Fowder, Javed
AU - Gratten, Jacob
AU - Halliday, Glenda
AU - Hickie, Ian B.
AU - Kennedy, Martin
AU - Lewis, Simon J.G.
AU - Montgomery, Grant W.
AU - Pearson, John
AU - Shatunov, Aleksey
AU - Iacoangeli, Alfredo
AU - Al-Chalabi, Ammar
AU - Mill, Jonathan
N1 - Publisher Copyright:
© 2021, The Author(s).
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/12
Y1 - 2021/12
N2 - 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.
AB - 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.
KW - DNA methylation
KW - Inflammatory markers
KW - Methylation profile score
KW - Mixed-linear models
KW - Neurodegenerative disorders
KW - Out-of-sample classification
UR - http://www.scopus.com/inward/record.url?scp=85103554258&partnerID=8YFLogxK
U2 - 10.1186/s13059-021-02275-5
DO - 10.1186/s13059-021-02275-5
M3 - Article
C2 - 33771206
AN - SCOPUS:85103554258
SN - 1474-7596
VL - 22
JO - Genome Biology
JF - Genome Biology
IS - 1
M1 - 90
ER -