Evidence map›Paper›PMID 38053194›Full record

ArticleGenome biology2023

Integration of datasets for individual prediction of DNA methylation-based biomarkers.

Charlotte Merzbacher, Barry Ryan, Thibaut Goldsborough, Robert F Hillary, Archie Campbell, Lee Murphy, Andrew M McIntosh, David Liewald, Sarah E Harris, Allan F McRae and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genome biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Methylome-wide studies of six metabolic traits.medRxiv : the preprint server for health sciences · 2024
    Article
  6. 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

15 authors.

Charlotte Merzbacher *School of Informatics, University of Edinburgh, Edinburgh, EH8 9AB, UK.ORCID 0009-0000-2853-1864
Barry Ryan *School of Informatics, University of Edinburgh, Edinburgh, EH8 9AB, UK.ORCID 0009-0006-2779-5722
Thibaut Goldsborough *School of Informatics, University of Edinburgh, Edinburgh, EH8 9AB, UK.ORCID 0009-0007-9349-4693
Robert F HillaryCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK.
Archie CampbellCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK.
Lee MurphyEdinburgh Clinical Research Facility, University of Edinburgh, Edinburgh, EH4 2XU, UK.
Andrew M McIntoshCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK.
David LiewaldDepartment of Psychology, Lothian Birth Cohorts, University of Edinburgh, Edinburgh, EH8 9JZ, UK.
Sarah E HarrisDepartment of Psychology, Lothian Birth Cohorts, University of Edinburgh, Edinburgh, EH8 9JZ, UK.
Allan F McRaeInstitute for Molecular Bioscience, University of Queensland, Brisbane, Australia.
Simon R CoxDepartment of Psychology, Lothian Birth Cohorts, University of Edinburgh, Edinburgh, EH8 9JZ, UK.
Timothy I CanningsMaxwell Institute for Mathematical Sciences, School of Mathematics, University of Edinburgh, Edinburgh, EH9 3FD, UK.
Catalina A VallejosMRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK.ORCID 0000-0003-3638-1960
Daniel L McCartney *Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK. Daniel.McCartney@ed.ac.uk.ORCID 0000-0003-3242-0360
Riccardo E Marioni *Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK. Riccardo.Marioni@ed.ac.uk.ORCID 0000-0003-4430-4260

Funding

Biotechnology and Biological Sciences Research Council BB/W008793/1Biotechnology and Biological Sciences Research Council SR176Medical Research CouncilMedical Research Council R42550Wellcome TrustWellcome Trust 104036/Z/14/ZWellcome Trust 216767/Z/19/ZWellcome Trust EP/S02431X/1
6 · The paper itself

Abstract

backgroundEpigenetic scores (EpiScores) can provide biomarkers of lifestyle and disease risk. Projecting new datasets onto a reference panel is challenging due to separation of technical and biological variation with array data. Normalisation can standardise data distributions but may also remove population-level biological variation.

resultsWe compare two birth cohorts (Lothian Birth Cohorts of 1921 and 1936 - n

conclusionsNormalisation methods returning similar EpiScores, whether cohorts are analysed separately or together, will minimise technical variation when projecting new data onto a reference panel. These methods are important for cases where raw data is unavailable and joint normalisation of cohorts is computationally expensive.

Indexed as

DNA MethylationEpigenomicsAgedBiomarkersEpigenesis, GeneticHumansBiomarkersBiomarkerDNA methylationPrediction

Identifiers

PMID38053194
PMCPMC10696831

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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.