Blood‐based multivariate methylation risk score for cognitive impairment and dementia
J.C. Koetsier, Rachel Cavill, Rick A. Reijnders, Joshua Harvey, Jan Homann, Morteza Kouhsar, Kay Deckers, Sebastian Köhler, Lars Eijssen, Daniël L.A. van den Hove, Ilja Demuth, Sandra Düzel, for the Alzheimer's Disease Neuroimaging Initiative, Rebecca G. Smith, Adam R. Smith, Joe Burrage, Emma Walker, Gemma Shireby, Eilís Hannon, Emma Dempster, Timothy M. Frayling, Jonathan Mill, Valerija Dobričić, Peter Johannsen, Michael Wittig, Andre Franke, Rik Vandenberghe, Jolien Schaeverbeke, Yvonne Freund‐Levi, Lutz Frölich, Philip Scheltens, Charlotte E. Teunissen, Giovanni B. Frisoni, Olivier Blin, Jill Richardson, Régis Bordet, Sebastiaan Engelborghs, Ellen De Roeck, Pablo Martínez‐Lage, Mikel Tainta, Alberto Lleó, Isabel Sala, Julius Popp, Gwendoline Peyratout, Frans Verhey, Magda Tsolaki, Ulf Andréasson, Kaj Blennow, Henrik Zetterberg, Johannes Streffer, Stephanie J. B. Vos, Simon Lovestone, Pieter Jelle Visser, Christina M. Lill, Lars Bertram, Katie Lunnon, Ehsan Pishva
Abstract
Abstract INTRODUCTION The established link between DNA methylation and pathophysiology of dementia, along with its potential role as a molecular mediator of lifestyle and environmental influences, positions blood‐derived DNA methylation as a promising tool for early dementia risk detection. METHODS In conjunction with an extensive array of machine learning techniques, we employed whole blood genome‐wide DNA methylation data as a surrogate for 14 modifiable and non‐modifiable factors in the assessment of dementia risk in independent dementia cohorts. RESULTS We established a multivariate methylation risk score (MMRS) for identifying mild cognitive impairment cross‐sectionally, independent of age and sex ( P = 2.0 × 10 −3 ). This score significantly predicted the prospective development of cognitive impairments in independent studies of Alzheimer's disease (hazard ratio for Rey's Auditory Verbal Learning Test (RAVLT)‐Learning = 2.47) and Parkinson's disease (hazard ratio for MCI/dementia = 2.59). DISCUSSION Our work shows the potential of employing blood‐derived DNA methylation data in the assessment of dementia risk. Highlights We used whole blood DNA methylation as a surrogate for 14 dementia risk factors. Created a multivariate methylation risk score for predicting cognitive impairment. Emphasized the role of machine learning and omics data in predicting dementia. The score predicts cognitive impairment development at the population level.