Genome Biology (Mar 2021)

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 Mecocci,
  • Simon Lovestone,
  • Iwona Kłoszewska,
  • Bruno Vellas,
  • the Australian Imaging Biomarkers and Lifestyle study,
  • the 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

DOI
https://doi.org/10.1186/s13059-021-02275-5
Journal volume & issue
Vol. 22, no. 1
pp. 1 – 30

Abstract

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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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