Evidence map›Paper›PMID 37410739›Full record

ReviewPLoS medicine2023

Blood-based epigenome-wide analyses of 19 common disease states: A longitudinal, population-based linked cohort study of 18,413 Scottish individuals.

Robert F Hillary, Daniel L McCartney, Hannah M Smith, Elena Bernabeu, Danni A Gadd, Aleksandra D Chybowska, Yipeng Cheng, Lee Murphy, Nicola Wrobel, Archie Campbell and 5 more

Open access · goldAbstract readReview
In one paragraph

Review in PLoS medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed, 2 pooled it
10.2field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

55 citing papers in PubMed, 2 syntheses or guidelines pooled it, 66 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Blood DNA Methylation Predicts Long-Term Risk of Dementia in Prospective Cohorts.medRxiv : the preprint server for health sciences · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 4 institutions in 1 country.

Robert F HillaryCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom.ORCID 0000-0002-2595-552X
Daniel L McCartneyCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom.
Hannah M SmithCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom.ORCID 0000-0002-2972-821X
Elena BernabeuCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom.ORCID 0000-0002-5848-5720
Danni A GaddCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom.ORCID 0000-0001-6398-5407
Aleksandra D ChybowskaCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom.ORCID 0000-0002-1916-318X
Yipeng ChengCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom.
Lee MurphyEdinburgh Clinical Research Facility, University of Edinburgh, Edinburgh, United Kingdom.ORCID 0000-0001-6467-7449
Nicola WrobelEdinburgh Clinical Research Facility, University of Edinburgh, Edinburgh, United Kingdom.ORCID 0000-0001-9995-8662
Archie CampbellCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom.ORCID 0000-0003-0198-5078
Rosie M WalkerCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom.ORCID 0000-0002-1060-4479
Caroline HaywardCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom.ORCID 0000-0002-9405-9550
Kathryn L EvansCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom.ORCID 0000-0002-7884-5877
Andrew M McIntoshCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom.ORCID 0000-0002-0198-4588
Riccardo E MarioniCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom.ORCID 0000-0003-4430-4260
Edinburgh Cancer Research · GBUniversity of Edinburgh · GBRoyal Edinburgh Hospital · GBUniversity of Exeter · GB

Funding

British Heart Foundation FS/IPBSRF/22/27042Medical Research Council MC_PC_17209Medical Research Council MC_UU_00007/10Medical Research Council MR/S035818/1Medical Research Council MR/W014386/1Wellcome Trust 104036/Z/14/ZWellcome Trust 108890/Z/15/ZWellcome Trust 216767/Z/19/ZWellcome Trust 218493/Z/19/ZWellcome Trust 220857/Z/20/Z
6 · The paper itself

Abstract

backgroundDNA methylation is a dynamic epigenetic mechanism that occurs at cytosine-phosphate-guanine dinucleotide (CpG) sites. Epigenome-wide association studies (EWAS) investigate the strength of association between methylation at individual CpG sites and health outcomes. Although blood methylation may act as a peripheral marker of common disease states, previous EWAS have typically focused only on individual conditions and have had limited power to discover disease-associated loci. This study examined the association of blood DNA methylation with the prevalence of 14 disease states and the incidence of 19 disease states in a single population of over 18,000 Scottish individuals. METHODS AND

findingsDNA methylation was assayed at 752,722 CpG sites in whole-blood samples from 18,413 volunteers in the family-structured, population-based cohort study Generation Scotland (age range 18 to 99 years). EWAS tested for cross-sectional associations between baseline CpG methylation and 14 prevalent disease states, and for longitudinal associations between baseline CpG methylation and 19 incident disease states. Prevalent cases were self-reported on health questionnaires at the baseline. Incident cases were identified using linkage to Scottish primary (Read 2) and secondary (ICD-10) care records, and the censoring date was set to October 2020. The mean time-to-diagnosis ranged from 5.0 years (for chronic pain) to 11.7 years (for Coronavirus Disease 2019 (COVID-19) hospitalisation). The 19 disease states considered in this study were selected if they were present on the World Health Organisation's 10 leading causes of death and disease burden or included in baseline self-report questionnaires. EWAS models were adjusted for age at methylation typing, sex, estimated white blood cell composition, population structure, and 5 common lifestyle risk factors. A structured literature review was also conducted to identify existing EWAS for all 19 disease states tested. The MEDLINE, Embase, Web of Science, and preprint servers were searched to retrieve relevant articles indexed as of March 27, 2023. Fifty-four of approximately 2,000 indexed articles met our inclusion criteria: assayed blood-based DNA methylation, had >20 individuals in each comparison group, and examined one of the 19 conditions considered. First, we assessed whether the associations identified in our study were reported in previous studies. We identified 69 associations between CpGs and the prevalence of 4 conditions, of which 58 were newly described. The conditions were breast cancer, chronic kidney disease, ischemic heart disease, and type 2 diabetes mellitus. We also uncovered 64 CpGs that associated with the incidence of 2 disease states (COPD and type 2 diabetes), of which 56 were not reported in the surveyed literature. Second, we assessed replication across existing studies, which was defined as the reporting of at least 1 common site in >2 studies that examined the same condition. Only 6/19 disease states had evidence of such replication. The limitations of this study include the nonconsideration of medication data and a potential lack of generalizability to individuals that are not of Scottish and European ancestry.

conclusionsWe discovered over 100 associations between blood methylation sites and common disease states, independently of major confounding risk factors, and a need for greater standardisation among EWAS on human disease.

Indexed as

COVID-19Diabetes Mellitus, Type 2AdolescentAdultAgedAged, 80 and overCohort StudiesCpG IslandsCross-Sectional StudiesDNA MethylationEpigenesis, GeneticEpigenomeFemaleGenome-Wide Association StudyHumansMale

Identifiers

PMID37410739
PMCPMC10325072
OpenAlexW4383337813

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.