Abstract
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 DNA methylation (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 = 9537) 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.
Highlights
Chronic morbidities place longstanding burdens on our health as we age
Independent test set data were not available for four Olink 176 proteins. They were included based on their performance (r > 0.1 and P < 0.05) in a 177 holdout sample of 150 individuals who were left out of the training set
We show that EpiScore - diabetes associations highlight previously measured protein - diabetes relationships
Summary
Chronic morbidities place longstanding burdens on our health as we age. Stratifying an individual’s risk prior to symptom presentation is critical (NHS England, 2016). DNA methylation (DNAm) encodes information on the epigenetic landscape of an individual and blood-based DNAm signatures have been found to predict all cause mortality and disease onset, providing strong evidence to suggest that methylation is an important measure of disease risk DNAm can regulate gene transcription (Lea et al, 2018), and epigenetic differences can be reflected in the variability of the proteome (Hillary et al, 2019; Hillary, Trejo-Banos, et al, 2020; Zaghlool et al, 2020). Low-grade inflammation, which is thought to exacerbate many age-related morbidities, is well-captured through DNAm studies of plasma protein levels (Zaghlool et al, 2020). As proteins are the primary effectors of disease, connecting the epigenome, proteome and time to disease onset may help to resolve predictive biological signatures
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