Evidence map›Paper›PMID 31775873›Full record

ArticleClinical epigenetics2019

Validation and characterisation of a DNA methylation alcohol biomarker across the life course.

Paul Darius Yousefi, Rebecca Richmond, Ryan Langdon, Andrew Ness, Chunyu Liu, Daniel Levy, Caroline Relton, Matthew Suderman, Luisa Zuccolo

Abstract read
In one paragraph

Article in Clinical epigenetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Epigenome-wide analyses identify DNA methylation signatures of dementia risk.Alzheimer's & dementia (Amsterdam, Netherlands) · 2020
    Article
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

9 authors.

Paul Darius YousefiMRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK. paul.yousefi@bristol.ac.uk.ORCID 0000-0003-3284-3240
Rebecca RichmondMRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK.
Ryan LangdonMRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK.
Andrew NessNational Institute of Health Bristol Biomedical Research Centre, University of Bristol, Bristol, UK.
Chunyu LiuDepartment of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
Daniel LevyThe Framingham Heart Study, Framingham, MA, USA.
Caroline ReltonMRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK.
Matthew SudermanMRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK.
Luisa ZuccoloMRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK.

Funding

Biotechnology and Biological Sciences Research Council BB/I025263/1Biotechnology and Biological Sciences Research Council BB/I025751/1Cancer Research UK 19169Department of Health RP-PG-0707-10034Medical Research Council G0902144Medical Research Council G9815508Medical Research Council MC_PC_15018Medical Research Council MC_PC_19009Medical Research Council MC_UU_00011/1Medical Research Council MC_UU_00011/5Medical Research Council MC_UU_12013/1Medical Research Council MC_UU_12013/2Wellcome Trust 102215/2/13/2
6 · The paper itself

Abstract

backgroundRecently, an alcohol predictor was developed using DNA methylation at 144 CpG sites (DNAm-Alc) as a biomarker for improved clinical or epidemiologic assessment of alcohol-related ill health. We validate the performance and characterise the drivers of this DNAm-Alc for the first time in independent populations.

resultsIn N = 1049 parents from the Avon Longitudinal Study of Parents and Children (ALSPAC) Accessible Resource for Integrated Epigenomic Studies (ARIES) at midlife, we found DNAm-Alc explained 7.6% of the variation in alcohol intake, roughly half of what had been reported previously, and interestingly explained a larger 9.8% of Alcohol Use Disorders Identification Test (AUDIT) score, a scale of alcohol use disorder. Explanatory capacity in participants from the offspring generation of ARIES measured during adolescence was much lower. However, DNAm-Alc explained 14.3% of the variation in replication using the Head and Neck 5000 (HN5000) clinical cohort that had higher average alcohol consumption. To investigate whether this relationship was being driven by genetic and/or earlier environment confounding, we examined how earlier versus concurrent DNAm-Alc measures predicted AUDIT scores. In both ARIES parental and offspring generations, we observed associations between AUDIT and concurrent, but not earlier DNAm-Alc, suggesting independence from genetic and stable environmental contributions.

conclusionsThe stronger relationship between DNAm-Alcs and AUDIT in parents at midlife compared to adolescents despite similar levels of consumption suggests that DNAm-Alc likely reflects long-term patterns of alcohol abuse. Such biomarkers may have potential applications for biomonitoring and risk prediction, especially in cases where reporting bias is a concern.

Indexed as

DNA MethylationGenetic MarkersAdolescentAdultAlcohol DrinkingAlcoholismChildEpigenesis, GeneticFemaleHumansLongitudinal StudiesMaleMiddle AgedYoung AdultGenetic MarkersAlcohol use disorderALSPACAUDITCHARGEPrediction

Identifiers

PMID31775873
PMCPMC6880546

What OpenQuestion 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 OpenQuestion graph.