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Significant out-of-sample classification from methylation profile scoring for amyotrophic lateral sclerosis

Research output: Contribution to journalArticle

Marta F. Nabais, Tian Lin, Beben Benyamin, Kelly L. Williams, Fleur C. Garton, Anna A.E. Vinkhuyzen, Futao Zhang, Costanza L. Vallerga, Restuadi Restuadi, Anna Freydenzon, Ramona A.J. Zwamborn, Paul J. Hop, Matthew R. Robinson, Jacob Gratten, Peter M. Visscher, Eilis Hannon, Jonathan Mill, Matthew A. Brown, Nigel G. Laing, Karen A. Mather & 17 more Perminder S. Sachdev, Shyuan T. Ngo, Frederik J. Steyn, Leanne Wallace, Anjali K. Henders, Merrilee Needham, Jan H. Veldink, Susan Mathers, Garth Nicholson, Dominic B. Rowe, Robert D. Henderson, Pamela A. McCombe, Roger Pamphlett, Jian Yang, Ian P. Blair, Allan F. McRae, Naomi R. Wray

Original languageEnglish
Article number10
JournalNPJ Genomic medicine
Volume5
Issue number1
DOIs
Publication statusPublished - 1 Dec 2020

King's Authors

Abstract

We conducted DNA methylation association analyses using Illumina 450K data from whole blood for an Australian amyotrophic lateral sclerosis (ALS) case–control cohort (782 cases and 613 controls). Analyses used mixed linear models as implemented in the OSCA software. We found a significantly higher proportion of neutrophils in cases compared to controls which replicated in an independent cohort from the Netherlands (1159 cases and 637 controls). The OSCA MOMENT linear mixed model has been shown in simulations to best account for confounders. When combined in a methylation profile score, the 25 most-associated probes identified by MOMENT significantly classified case–control status in the Netherlands sample (area under the curve, AUC = 0.65, CI95% = [0.62–0.68], p = 8.3 × 10−22). The maximum AUC achieved was 0.69 (CI95% = [0.66–0.71], p = 4.3 × 10−34) when cell-type proportion was included in the predictor.

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