Evidence map›Paper›PMID 37834090›Full record

ArticleInternational journal of molecular sciences2023

Genome-Wide DNA Methylation Profiles in Whole-Blood and Buccal Samples-Cross-Sectional, Longitudinal, and across Platforms.

Austin J Van Asselt, Jeffrey J Beck, Casey T Finnicum, Brandon N Johnson, Noah Kallsen, Jouke Jan Hottenga, Eco J C de Geus, Bios Consortium, Dorret I Boomsma, Erik A Ehli and 1 more

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.2field-weighted citation impact, top 20% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. 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

11 authors at 2 institutions in 2 countries.

Austin J Van AsseltAvera McKennan Hospital, University Health Center, Sioux Falls, SD 57105, USA.ORCID 0000-0002-3931-044X
Jeffrey J BeckAvera McKennan Hospital, University Health Center, Sioux Falls, SD 57105, USA.ORCID 0000-0002-1152-9968
Casey T FinnicumAvera McKennan Hospital, University Health Center, Sioux Falls, SD 57105, USA.
Brandon N JohnsonAvera McKennan Hospital, University Health Center, Sioux Falls, SD 57105, USA.
Noah KallsenAvera McKennan Hospital, University Health Center, Sioux Falls, SD 57105, USA.
Jouke Jan HottengaDepartment of Biological Psychology, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands.
Eco J C de GeusDepartment of Biological Psychology, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands.ORCID 0000-0001-6022-2666
Bios Consortium
Dorret I BoomsmaDepartment of Biological Psychology, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands.ORCID 0000-0002-7099-7972
Erik A EhliAvera McKennan Hospital, University Health Center, Sioux Falls, SD 57105, USA.ORCID 0000-0002-7865-3015
Jenny van DongenDepartment of Biological Psychology, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands.ORCID 0000-0003-2063-8741
Avera McKennan Hospital & University Health Center · USVrije Universiteit Amsterdam · NL

Funding

Integration of Genomics & Transcriptomics in Normal Twins & Major DepressionRC2MH089951 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SULLIVAN, PATRICK F · 2009 to 2010
$6.5M
Genomics of Developmental Trajectories in TwinsRC2MH089995 · NIMH · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI HUDZIAK, JAMES J. · 2009 to 2010
$3.8M
Collaborative Study of Genetics of Dizygotic TwinningR01HD042157 · NICHD · QUEENSLAND INSTITUTE OF MEDICAL RESEARCH · PI MONTGOMERY, GRANT W · 2002 to 2006
$2.0M
Major Depression: Stage 1 Genomewide Association in Population-Based SamplesR01MH081802 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SULLIVAN, PATRICK F · 2007 to 2007
$138k
EPA EP-C-15-001NICHD NIH HHS R01 HD042157NIH HHS 1RC2 MH089995NIH HHS Grand Opportunity grants 1RC2 MH089951NIH HHS NIH R01 HD042157-01A1, MH081802NIMH NIH HHS R01 MH081802NIMH NIH HHS RC2 MH089951NIMH NIH HHS RC2 MH089995
6 · The paper itself

Abstract

The field of DNA methylation research is rapidly evolving, focusing on disease and phenotype changes over time using methylation measurements from diverse tissue sources and multiple array platforms. Consequently, identifying the extent of longitudinal, inter-tissue, and inter-platform variation in DNA methylation is crucial for future advancement. DNA methylation was measured in 375 individuals, with 197 of those having 2 blood sample measurements ~10 years apart. Whole-blood samples were measured on Illumina Infinium 450K and EPIC methylation arrays, and buccal samples from a subset of 58 participants were measured on EPIC array. The data were analyzed with the aims to examine the correlation between methylation levels in longitudinal blood samples in 197 individuals, examine the correlation between methylation levels in the blood and buccal samples in 58 individuals, and examine the correlation between blood methylation profiles assessed on the EPIC and 450K arrays in 83 individuals. We identified 136,833, 7674, and 96,891 CpGs significantly and strongly correlated (>0.50) longitudinally, across blood and buccal samples as well as array platforms, respectively. A total of 3674 of these CpGs were shared across all three sets. Analysis of these shared CpGs identified previously found associations with aging, ancestry, and 7016 mQTLs as well.

Indexed as

AgingDNA MethylationCpG IslandsCross-Sectional StudiesEpigenesis, GeneticHumansDNA methylationepigeneticsIllumina microarrayslongitudinal designplatform comparisontissue comparison

Identifiers

PMID37834090
PMCPMC10572275
OpenAlexW4387138990

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.