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

• DOI: 10.1038/s41525-020-0118-3
• Publication Date: 2020-02-27T11:04:32Z
• Authors: Marta F. Nabais; Tian Lin; Beben Benyamin; Kelly L. Williams; Fleur C. Garton; Anna A. E. Vinkhu...; Futao Zhang; Costanza L. Vallerga; Restuadi Restuadi; Anna Freydenzon; Ramona A. J. Zwam...; Paul J. Hop; Matthew R. Robinson; Jacob Gratten; Peter M. Visscher; Eilis Hannon; Jonathan Mill; Matthew A. Brown; Nigel G. Laing; Karen A. Mather; 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
• Keywords: Sample (material)

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. found a significantly higher proportion of neutrophils compared to controls which replicated independent Netherlands (1159 637 The MOMENT model has been shown simulations best account confounders. When combined profile score, 25 most-associated probes identified by classified status sample (area under curve, AUC = 0.65, CI95% [0.62-0.68], p 8.3 × 10-22). maximum achieved was 0.69 (CI95% [0.66-0.71], 4.3 10-34) when cell-type included predictor.