Blood-based multivariate methylation risk score for cognitive impairment and dementia.
Authors
Jarno Koetsier, Rachel Cavill, Rick Reijnders, Joshua Harvey, Jan Homann, Morteza Kouhsar, Kay Deckers, Sebastian Köhler, Lars M T Eijssen, Daniel L A van den Hove, Ilja Demuth, Sandra Düzel, Rebecca G Smith, Adam R Smith, Joe Burrage, Emma M Walker, Gemma Shireby, Eilis Hannon, Emma Dempster, Tim Frayling, Jonathan Mill, Valerija Dobricic, Peter Johannsen, Michael Wittig, Andre Franke, Rik Vandenberghe, Jolien Schaeverbeke, Yvonne Freund-Levi, Lutz Frölich, Philip Scheltens, Charlotte E Teunissen, Giovanni Frisoni, Olivier Blin, Jill C Richardson, Régis Bordet, Sebastiaan Engelborghs, Ellen de Roeck, Pablo Martinez-Lage, Mikel Tainta, Alberto Lleó, Isabel Sala, Julius Popp, Gwendoline Peyratout, Frans Verhey, Magda Tsolaki, Ulf Andreasson, Kaj Blennow, Henrik Zetterberg, Johannes Streffer, Stephanie J B Vos, Simon Lovestone, Pieter-Jelle Visser, Christina M Lill, Lars Bertram, Katie Lunnon, Ehsan Pishva
Year of publication
2024Journal
ALZHEIMERS DEMENTVolume
-Issue
-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.