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Cheng, Y.* ; Gadd, D.A.* ; Gieger, C. ; Monterrubio-Gómez, K.* ; Zhang, Y.* ; Berta, I.* ; Stam, M.J.* ; Szlachetka, N.* ; Lobzaev, E.* ; Wrobel, N.* ; Murphy, L.* ; Campbell, A.* ; Nangle, C.* ; Walker, R.M.* ; Fawns-Ritchie, C.* ; Peters, A. ; Rathmann, W.* ; Porteous, D.J.* ; Evans, K.L.* ; McIntosh, A.M.* ; Cannings, T.I.* ; Waldenberger, M. ; Ganna, A.* ; McCartney, D.L.* ; Vallejos, C.A.* ; Marioni, R.E.*

Development and validation of DNA methylation scores in two European cohorts augment 10-year risk prediction of type 2 diabetes.

Nature Aging 3, 450-458 (2023)
Publ. Version/Full Text DOI PMC
Open Access Gold (Paid Option)
Type 2 diabetes mellitus (T2D) presents a major health and economic burden that could be alleviated with improved early prediction and intervention. While standard risk factors have shown good predictive performance, we show that the use of blood-based DNA methylation information leads to a significant improvement in the prediction of 10-year T2D incidence risk. Previous studies have been largely constrained by linear assumptions, the use of cytosine-guanine pairs one-at-a-time and binary outcomes. We present a flexible approach (via an R package, MethylPipeR) based on a range of linear and tree-ensemble models that incorporate time-to-event data for prediction. Using the Generation Scotland cohort (training set ncases = 374, ncontrols = 9,461; test set ncases = 252, ncontrols = 4,526) our best-performing model (area under the receiver operating characteristic curve (AUC) = 0.872, area under the precision-recall curve (PRAUC) = 0.302) showed notable improvement in 10-year onset prediction beyond standard risk factors (AUC = 0.839, precision-recall AUC = 0.227). Replication was observed in the German-based KORA study (n = 1,451, ncases = 142, P = 1.6 × 10-5).
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Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords Epigenome-wide Association; Regularization Paths; Population; Diagnosis; Disease; Models
ISSN (print) / ISBN 2662-8465
e-ISSN 2662-8465
Journal Nature Aging
Quellenangaben Volume: 3, Issue: 4, Pages: 450-458 Article Number: , Supplement: ,
Publisher Springer
Publishing Place Campus, 4 Crinan St, London, N1 9xw, England
Non-patent literature Publications
Reviewing status Peer reviewed
Grants Chief Scientist Office of the Scottish Government Health Directorates
Scottish Funding Council
Medical Research Council UK
Brain & Behavior Research Foundation
Royal College of Physicians of Edinburgh
University of Edinburgh
University of Helsinki joint PhD program in Human Genomics
Alzheimer's Research UK
Wellcome Trust
United Kingdom Research and Innovation
UKRI Centre for Doctoral Training in Biomedical AI at the University of Edinburgh
NHS Research Scotland
Chief Scientist Office of the Scottish Government
Helmholtz Zentrum Munchen-German Research Center for Environmental Health - German Federal Ministry of Education and Research
State of Bavaria
Munich Center of Health Sciences
German Centre for Cardiovascular Research - Bavarian State Ministry of Health and Care
Alzheimer's Society