Blood-based multivariate methylation risk score for cognitive impairment and dementia

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 FraylingJonathan 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, Alzheimer's Disease Neuroimaging Initiative, Stephanie Vos, Pieter Visser, Ehsan Pishva*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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.

Original languageEnglish
Pages (from-to)6682-6698
Number of pages17
JournalAlzheimer's & Dementia
Volume20
Issue number10
DOIs
Publication statusPublished - Oct 2024

Keywords

  • Alzheimer's disease
  • DNA methylation
  • Parkinson's disease
  • aging
  • dementia
  • epigenetics
  • machine learning
  • mild cognitive impairments
  • risk prediction

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