Blood-based multivariate methylation risk score for

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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, Alzheimer's Disease Neuroimaging Initiative, 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

Abstract

Alzheimers Dement. 2024 Aug 28. doi: 10.1002/alz.14061. Online ahead of print.

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.

PMID:39193899 | DOI:10.1002/alz.14061