Epigenetic scores for the circulating proteome as tools for disease prediction
- University of Edinburgh, United Kingdom
- Virginia Tech, United States
- University of Oxford, United Kingdom
- The University of Texas at Austin, United States
- Helmholtz Zentrum München, Germany
- Max Planck Institute for Heart and Lung Research, Germany
- University of Queensland, Australia
- The University of Edinburgh, United Kingdom
- Weill Cornell Medical College in Qatar, Qatar
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 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.
Data availability
Datasets generated in this study are made available in Supplementary file 1; this file includes the protein EpiScore weights for the 109 EpiScores we provide for future studies to use. All datasets used to create figures are included in Supplementary file 1 and specific locations for these are noted in figure legends.All code used in the analyses is available with open access at the following Gitlab repository: https://github.com/DanniGadd/EpiScores-for-protein-levels.The source datasets analysed during the current study are not publicly available due to them containing information that could compromise participant consent and confidentiality. Data can be obtained from the data owners. Instructions for Lothian Birth Cohort data access can be found here: https://www.lothianbirthcohort.ed.ac.uk/content/collaboration. Dr Simon Cox must be contacted to obtain a Lothian Birth Cohort 'Data Request Form' by email: simon.cox@ed.ac.uk. Instructions for accessing Generation Scotland data can be found here: https://www.ed.ac.uk/generation-scotland/for-researchers/access; the 'GS Access Request Form' can be downloaded from this site. Completed request forms must be sent to access@generationscotland.org to be approved by the Generation Scotland access committee. Data from the KORA study can be requested from KORA-gen: http://epi.helmholtz-muenchen.de/kora-gen. Requests are submitted online and are subject to approval by the KORA board.
Article and author information
Author details
Riccardo E Marioni
Funding
Wellcome Trust (108890/Z/15/Z)
- Danni A Gadd
- Robert F Hillary
Dementias Platform UK (MR/L023784/2)
- Liu Shi
Medical Research Council (MC_UU_00007/10)
- Caroline Hayward
Wellcome Trust (104036/Z/14/Z)
- Ian J Deary
- David J Porteous
- Andrew M McIntosh
Wellcome Trust (220857/Z/20/Z)
- Andrew M McIntosh
Wellcome Trust (216767/Z/19/Z)
- Chloe Fawns-Ritchie
- Cliff Nangle
- Archie Campbell
- Robin Flaig
- Ian J Deary
- David J Porteous
- Caroline Hayward
- Andrew M McIntosh
- Riccardo E Marioni
Chief Scientist Office of the Scottish Government Health Directorates (CZD/16/6)
- David J Porteous
Scottish Funding Council (HR03006)
- David J Porteous
Australian Research Council Fellowship (FT200100837)
- Allan F McRae
Australian Research Council (DP160102400,FL180100072)
- Peter M Visscher
Australian National Health and Medical Research Council (1113400,1010374)
- Peter M Visscher
Wellcome Trust (203771/Z/16/Z)
- Anna J Stevenson
Medical Research Council and Biotechnology and Biological Sciences Research Council (MR/K026992/1)
- Ian J Deary
UK's Biotechnology and Biological Sciences Research Council
- Ian J Deary
Royal Society-Wolfson Research Merit Award
- Ian J Deary
Chief Scientist Office of the Scottish Government's Health Directorates
- Ian J Deary
Age UK ((Disconnected Mind project))
- Sarah E Harris
- Ian J Deary
- Simon R Cox
Medical Research Council (G0701120,G1001245,MR/M013111/1,MR/R024065/1)
- Ian J Deary
- Simon R Cox
Biotechnology and Biological Sciences Research Council (BB/F019394/1)
- Ian J Deary
Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (221890/Z/20/Z)
- Simon R Cox
National Institutes of Health (RF1AG073593,P2CHD042849,P30AG066614)
- Elliot M Tucker-Drob
National Institutes of Health (R01AG054628)
- Elliot M Tucker-Drob
- Ian J Deary
- Simon R Cox
Alzheimer's Research UK (ARUK-PG2017B−10)
- Daniel L McCartney
- Riccardo E Marioni
Health Data Research UK (substantive site award)
- Archie Campbell
MRC Human Genetics Unit (MRC core support)
- Caroline Hayward
Qatar Foundation (Biomedical Research Program at Weill Cornell Medicine)
- Shaza B Zaghlool
- Karsten Suhre
Qatar National Research Fund (NPRP11C-0115-180010)
- Shaza B Zaghlool
- Karsten Suhre
German Federal Ministry of Education and Research (Helmholtz Zentrum München)
- Christian Gieger
- Annette Peters
- Melanie Waldenberger
- Johannes Graumann
Munich Center of Health Sciences (LMUinnovativ)
- Christian Gieger
- Annette Peters
- Melanie Waldenberger
- Johannes Graumann
Bavarian State Ministry of Health and Care (DigiMed Bayern)
- Christian Gieger
- Annette Peters
- Melanie Waldenberger
- Johannes Graumann
NIHR Biomedical Research Centre at Oxford Health NHS Foundation Trust
- Liu Shi
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: All KORA participants have given written informed consent and the study was approved by the Ethics Committee of the Bavarian Medical Association.All components of GS received ethical approval from the NHS Tayside Committee on Medical Research Ethics (REC Reference Number: 05/S1401/89). GS has also been granted Research Tissue Bank status by the East of Scotland Research Ethics Service (REC Reference Number: 20/ES/0021), providing generic ethical approval for a wide range of uses within medical research.Ethical approval for the LBC1921 and LBC1936 studies was obtained from the Multi-Centre Research Ethics Committee for Scotland (MREC/01/0/56) and the Lothian Research Ethics committee (LREC/1998/4/183; LREC/2003/2/29). In both studies, all participants provided written informed consent. These studies were performed in accordance with the Helsinki declaration.
Copyright
© 2022, Gadd et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Epigenetic scores for the circulating proteome as tools for disease prediction
eLife 11:e71802.
https://doi.org/10.7554/eLife.71802
Further reading
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- Epidemiology and Global Health
Background:
Biological aging exhibits heterogeneity across multi-organ systems. However, it remains unclear how is lifestyle associated with overall and organ-specific aging and which factors contribute most in Southwest China.
Methods:
This study involved 8396 participants who completed two surveys from the China Multi-Ethnic Cohort (CMEC) study. The healthy lifestyle index (HLI) was developed using five lifestyle factors: smoking, alcohol, diet, exercise, and sleep. The comprehensive and organ-specific biological ages (BAs) were calculated using the Klemera–Doubal method based on longitudinal clinical laboratory measurements, and validation were conducted to select BA reflecting related diseases. Fixed effects model was used to examine the associations between HLI or its components and the acceleration of validated BAs. We further evaluated the relative contribution of lifestyle components to comprehension and organ systems BAs using quantile G-computation.
Results:
About two-thirds of participants changed HLI scores between surveys. After validation, three organ-specific BAs (the cardiopulmonary, metabolic, and liver BAs) were identified as reflective of specific diseases and included in further analyses with the comprehensive BA. The health alterations in HLI showed a protective association with the acceleration of all BAs, with a mean shift of –0.19 (95% CI −0.34, –0.03) in the comprehensive BA acceleration. Diet and smoking were the major contributors to overall negative associations of five lifestyle factors, with the comprehensive BA and metabolic BA accounting for 24% and 55% respectively.
Conclusions:
Healthy lifestyle changes were inversely related to comprehensive and organ-specific biological aging in Southwest China, with diet and smoking contributing most to comprehensive and metabolic BA separately. Our findings highlight the potential of lifestyle interventions to decelerate aging and identify intervention targets to limit organ-specific aging in less-developed regions.
Funding:
This work was primarily supported by the National Natural Science Foundation of China (Grant No. 82273740) and Sichuan Science and Technology Program (Natural Science Foundation of Sichuan Province, Grant No. 2024NSFSC0552). The CMEC study was funded by the National Key Research and Development Program of China (Grant No. 2017YFC0907305, 2017YFC0907300). The sponsors had no role in the design, analysis, interpretation, or writing of this article.
