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Gadd, D.A.* ; Hillary, R.F.* ; McCartney, D.L.* ; Zaghlool, S.B.* ; Stevenson, A.J.* ; Cheng, Y.* ; Fawns-Ritchie, C.* ; Nangle, C.* ; Campbell, A.* ; Flaig, R.* ; Harris, S.E.* ; Walker, R.M.* ; Shi, L.* ; Tucker-Drob, E.M.* ; Gieger, C. ; Peters, A. ; Waldenberger, M. ; Graumann, J.* ; McRae, A.F.* ; Deary, I.J.* ; Porteous, D.J.* ; Hayward, C.* ; Visscher, P.M.* ; Cox, S.R.* ; Evans, K.L.* ; McIntosh, A.M.* ; Suhre, K.* ; Marioni, R.E.*

Epigenetic scores for the circulating proteome as tools for disease prediction.

eLife 11:e71802 (2022)
Verlagsversion Forschungsdaten DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
Protein biomarkers have been identified across many age-related morbidities. However, characterising epigenetic influences could further inform disease predictions. Here, we leverage epigenome-wide data to study links between the DNAm signatures of the circulating proteome and incident diseases. Using data from four cohorts, we trained and tested epigenetic scores (EpiScores) for 953 plasma proteins, identifying 109 scores that explained between 1% and 58% of the variance in protein levels after adjusting for known protein quantitative trait loci (pQTL) genetic effects. By projecting these EpiScores into an independent sample, (Generation Scotland; n=9,537) and relating them to incident morbidities over a follow-up of 14 years, we uncovered 137 EpiScore - disease associations. These associations were largely independent of immune cell proportions, common lifestyle and health factors and biological aging. Notably, we found that our diabetes-associated EpiScores highlighted previous top biomarker associations from proteome-wide assessments of diabetes. These EpiScores for protein levels can therefore be a valuable resource for disease prediction and risk stratification.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Epidemiology ; Genetics ; Genomics ; Global Health ; Human
ISSN (print) / ISBN 2050-084X
e-ISSN 2050-084X
Zeitschrift eLife
Quellenangaben Band: 11, Heft: , Seiten: , Artikelnummer: e71802 Supplement: ,
Verlag eLife Sciences Publications
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Epidemiology II (EPI2)
Förderungen Bavarian State Ministry of Health and Care
Age UK
Medical Research Council and Biotechnology and Biological Sciences Research Council
Australian Research Council
Australian Research Council Fellowship
Scottish Funding Council
Chief Scientist Office of the Scottish Government Health Directorates
Medical Research Council
Biotechnology and Biological Sciences Research Council
Munich Center of Health Sciences
German Federal Ministry of Education and Research
Qatar National Research Fund
Qatar Foundation
MRC Human Genetics Unit
Health Data Research UK
Alzheimer's Research UK
NIH HHS
Dementias Platform UK