Epigenetic scores for the circulating proteome as tools for disease prediction

Abstract

Chronic morbidities place longstanding burdens on our health as we age. Although protein biomarkers are critical for the early detection of such diseases, current studies are limited by low sample sizes, variability in proteomics methods and fluctuations in inflammatory protein expression. Here, we present a novel framework for protein-by-proxy analysis of incident disease. We show that DNA methylation proxies for nine inflammatory and seven neurology plasma proteins (generated in up to 875 individuals in the Lothian Birth Cohort 1936) predict the incidence of seven leading causes of morbidity in the Generation Scotland cohort (n=9,537), ascertained via electronic health data linkage over a follow-up period of up to 14 years. After correction for multiple testing and adjustment for common disease risk factors, these included proxy associations between CCL11 and depression (Hazard Ratio: HR = 1.45, P = 1.8 x 10-4), VEGFA and ischaemic heart disease (HR = 1.16, P = 0.02) and associations between incident diabetes and FGF-21 (HR = 1.39, P = 9.7 x 10-7), NEP (HR = 1.32, P = 2.8 x 10-6) and N-CDase (HR = 1.16, P = 0.02). Several of the protein-proxy associations with disease pinpoint proteins that are already therapeutic targets for the diseases in question. These results provide new opportunities to identify circulating biomarkers for disease detection and candidate pathways for drug targeting.

Genome-wide study of DNA methylation in Amyotrophic Lateral Sclerosis identifies differentially methylated loci and implicates metabolic, inflammatory and cholesterol pathways

“…To gain further insight into potential intermediate phenotypes associated with ALS, we utilized published poly-methylation scores (PMS) as proxies for various traits and exposures, including BMI, HDL-c, LDL-c, total cholesterol, alcohol consumption, smoking, white blood cell proportions (CD4T, CD8T, monocytes, granulocytes, NK-cells), biological age and a collection of immunological and neurological proteins 11–14,16,41–43 .…”

“…We considered the following poly-methylation scores: smoking 14,42 , alcohol intake 11,14 , BMI 12,14 , HDL-c 14 , LDL-c 14 , total cholesterol 14 , CRP 15 , white blood cell proportions 102 (CD8T-cells, CD4T-cells, NK-cells, Monocytes, Granulocytes, and B-cells), DNA methylation age 13,44,45 , and a collection of 27 immunological and neurological plasma proteins 16,103 .…”

“…The development of standardized assays for quantifying DNA methylation, the best characterized and most stable epigenetic modification, has enabled the systematic analysis of associations between methylomic variation and a wide range of human diseases, including cancer, schizophrenia and various neurodegenerative diseases 6–9 . In addition to a potential mechanistic role in ALS, the quantification of DNA methylation in whole blood DNA can serve as a robust quantifiable biomarker for candidate risk factors including smoking, alcohol intake, BMI, biological age, and various metabolic and inflammatory proteins 10–16 . Moreover, DNA methylation signatures have proven useful as diagnostic and prognostic biomarkers in various settings including common cancers and all- cause mortality 17,18 .…”

Integrated methylome and phenome study of the circulating proteome reveals markers pertinent to brain health

“…The copyright holder for this preprint this version posted September 6, 2021. ; https://doi.org/10.1101/2021.09.03.21263066 doi: medRxiv preprint of neurological outcomes 20,21 and brain health is also thought to be influenced by peripheral factors 12,22 . Brain morphology alterations and disease pathogenesis can occur many years prior to overt neurological, cognitive and behavioural symptom presentation.…”

“…However, proteome-wide assessment of pQTMs has not been tested against a comprehensive spectrum of neurological phenotypes. Bloodbased methylation is unlikely to correlate highly with brain methylation in all cases 19 ; however, proteomic and epigenetic signatures from the blood have been shown to be informative as predictors of neurological outcomes 20,21 and brain health is also thought to be influenced by peripheral factors 12,22 . Brain morphology alterations and disease pathogenesis can occur many years prior to overt neurological, cognitive and behavioural symptom presentation.…”