Blood-based epigenome-wide analyses of chronic low-grade inflammation across diverse population cohorts
dc.contributor.author | Hillary, RF | |
dc.contributor.author | Ng, HK | |
dc.contributor.author | McCartney, DL | |
dc.contributor.author | Elliott, HR | |
dc.contributor.author | Walker, RM | |
dc.contributor.author | Campbell, A | |
dc.contributor.author | Huang, F | |
dc.contributor.author | Direk, K | |
dc.contributor.author | Welsh, P | |
dc.contributor.author | Sattar, N | |
dc.contributor.author | Corley, J | |
dc.contributor.author | Hayward, C | |
dc.contributor.author | McIntosh, AM | |
dc.contributor.author | Sudlow, C | |
dc.contributor.author | Evans, KL | |
dc.contributor.author | Cox, SR | |
dc.contributor.author | Chambers, JC | |
dc.contributor.author | Loh, M | |
dc.contributor.author | Relton, CL | |
dc.contributor.author | Marioni, RE | |
dc.contributor.author | Yousefi, PD | |
dc.contributor.author | Suderman, M | |
dc.date.accessioned | 2024-11-13T10:35:40Z | |
dc.date.issued | 2024-04-30 | |
dc.date.updated | 2024-11-12T16:02:30Z | |
dc.description.abstract | Chronic inflammation is a hallmark of age-related disease states. The effectiveness of inflammatory proteins including C-reactive protein (CRP) in assessing long-term inflammation is hindered by their phasic nature. DNA methylation (DNAm) signatures of CRP may act as more reliable markers of chronic inflammation. We show that inter-individual differences in DNAm capture 50% of the variance in circulating CRP (N = 17,936, Generation Scotland). We develop a series of DNAm predictors of CRP using state-of-the-art algorithms. An elastic-net-regression-based predictor outperformed competing methods and explained 18% of phenotypic variance in the Lothian Birth Cohort of 1936 (LBC1936) cohort, doubling that of existing DNAm predictors. DNAm predictors performed comparably in four additional test cohorts (Avon Longitudinal Study of Parents and Children, Health for Life in Singapore, Southall and Brent Revisited, and LBC1921), including for individuals of diverse genetic ancestry and different age groups. The best-performing predictor surpassed assay-measured CRP and a genetic score in its associations with 26 health outcomes. Our findings forge new avenues for assessing chronic low-grade inflammation in diverse populations. | en_GB |
dc.description.sponsorship | Wellcome Trust | en_GB |
dc.format.extent | 100544- | |
dc.format.medium | Print-Electronic | |
dc.identifier.citation | Vol. 4, No. 5, article 100544 | en_GB |
dc.identifier.doi | https://doi.org/10.1016/j.xgen.2024.100544 | |
dc.identifier.grantnumber | 104036/Z/14/Z | en_GB |
dc.identifier.grantnumber | 220857/Z/20/Z | en_GB |
dc.identifier.grantnumber | 217065/Z/19/Z | en_GB |
dc.identifier.grantnumber | 067100 | en_GB |
dc.identifier.grantnumber | 37055891 | en_GB |
dc.identifier.grantnumber | 086676/7/08/Z | en_GB |
dc.identifier.grantnumber | 221890/Z/20/Z | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/138213 | |
dc.identifier | ORCID: 0000-0002-1060-4479 (Walker, Rosie M) | |
dc.identifier | ScopusID: 23029293000 (Walker, Rosie M) | |
dc.language.iso | en | en_GB |
dc.publisher | Cell Press | en_GB |
dc.relation.url | https://www.ncbi.nlm.nih.gov/pubmed/38692281 | en_GB |
dc.relation.url | https://www.sabrestudy.org/home-2/data-sharing/ | en_GB |
dc.relation.url | https://www.ed.ac.uk/lothian-birth-cohorts/data-access-collaboration | en_GB |
dc.relation.url | https://doi.org/ 10.5281/zenodo.10426429 | en_GB |
dc.relation.url | https://doi.org/10.7488/ds/7546 | en_GB |
dc.relation.url | https://doi.org/10.5281/zenodo.10154736 | en_GB |
dc.rights | © 2024 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). | en_GB |
dc.subject | DNA Methylation | en_GB |
dc.subject | C-Reactive Protein | en_GB |
dc.subject | chronic inflammation | en_GB |
dc.subject | feature selection | en_GB |
dc.subject | prediction | en_GB |
dc.subject | ALSPAC | en_GB |
dc.subject | Generation Scotland | en_GB |
dc.subject | SABRE | en_GB |
dc.subject | HELIOS | en_GB |
dc.subject | Lothian Birth Cohorts | en_GB |
dc.title | Blood-based epigenome-wide analyses of chronic low-grade inflammation across diverse population cohorts | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2024-11-13T10:35:40Z | |
dc.identifier.issn | 2666-979X | |
exeter.article-number | 100544 | |
exeter.place-of-publication | United States | |
dc.description | This is the final version. Available from Cell Press via the DOI in this record. | en_GB |
dc.description | Data and code availability: According to the terms of consent for GS participants, access to data must be reviewed by the GS Access Committee. Applications should be made to access@generationscotland.org. ALSPAC data access is through a system of managed open access. Submissions and queries should be directed to alspac-data@bristol.ac.uk. For HELIOS, data access request proposals should be directed to helios_science@ntu.edu.sg for the consideration of the HELIOS Study’s principal investigators. SABRE data used for this submission will be made available on request to mrclha.swiftinfo@ucl.ac.uk. Further details regarding data sharing can be found on the cohort webpages(https://www.sabrestudy.org/home-2/data-sharing/). Lothian Birth Cohort data access requests can be made by following the information at https://www.ed.ac.uk/lothian-birth-cohorts/data-accesscollaboration. Epigenome-wide association statistics from linear models are available via the EWAS Catalog (https://doi.org/ 10.5281/zenodo.10426429). Epigenome-wide association statistics from Bayesian penalised regression are available at the University of Edinburgh Datashare site (https://doi.org/10.7488/ds/7546). CpGs and weights derived from elastic net regression, Bayesian penalised regression and the combined PCA and elastic net regression strategies are made available at the Edinburgh Datashare site (https://doi.org/10.7488/ds/7546). CpGs and weights for the elastic net regression and ‘PCA+elnet’-based approaches from this version of the manuscript are available in Tables S11 and S12. d All original code has been deposited at Zenodo (https://doi.org/10.5281/zenodo.10154736). d Anyadditional information required to reanalyse the data reported in this paper is available from the lead contact upon request. | en_GB |
dc.identifier.eissn | 2666-979X | |
dc.identifier.journal | Cell Genomics | en_GB |
dc.relation.ispartof | Cell Genomics, 4(5) | |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2024-04-03 | |
dc.rights.license | CC BY | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2024-04-30 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2024-11-13T10:30:13Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2024-11-13T10:36:20Z | |
refterms.panel | A | en_GB |
refterms.dateFirstOnline | 2024-04-30 |
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Except where otherwise noted, this item's licence is described as © 2024 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).