Evidence map›Paper›PMID 39709440›Full record

ArticleClinical epigenetics2024

DNA methylation models of protein abundance across the lifecourse.

Scott Waterfield, Paul Yousefi, Matt Suderman

Abstract read
In one paragraph

Article in Clinical epigenetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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

  1. Pooled it
  2. Article
  3. 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

3 authors.

Scott WaterfieldMRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK. scott.waterfield@bristol.ac.uk.
Paul YousefiMRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
Matt SudermanMRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.

Funding

Cancer Research UK C18281/A29019Cancer Research UK C18281/A30905Medical Research Council MC_UU_00032/3
6 · The paper itself

Abstract

backgroundMultiple studies have shown that DNA methylation (DNAm) models of protein abundance can be informative about exposure, phenotype and disease risk. Here we investigate and provide descriptive details of the capacity of DNAm to capture non-genetic variation in protein abundance across the lifecourse.

methodsWe evaluated the performance of 14 previously published DNAm models of protein abundance (episcores) in peripheral blood from a large adult population using the Avon Longitudinal Study of Parents and Children (ALSPAC) at ages 7-24 and their mothers antenatally and in middle age (N range = 145-1464). New age-specific episcores were trained in ALSPAC and evaluated at different ages. In all instances, episcore-protein associations were evaluated with and without adjustment for genetics. The association between longitudinal protein stability and longitudinal episcore projection was also evaluated, as was sex-specificity of episcores derived solely in female participants.

findingsOf the 14 Gadd episcores, 10 generated estimates associated with abundance in middle age, 9 at age 24, and none at age 9. Eight of these episcores explained variation beyond genotype in adulthood (6 at age 24; 7 at midlife). At age 9, the abundances of 22 proteins could be modelled by DNAm, 7 beyond genotype of which one trained model generated informative estimates at ages 24 and in middle age. At age 24, 31 proteins could be modelled by DNAm, 19 beyond genotype, of which 5 trained models generated informative estimates at age 9 and 8 in middle age. In middle age, 23 proteins could be modelled, 13 beyond genotype, of which 3 were informative at age 9 and 7 at age 24.

interpretationWe observed that episcores performed better at older ages than in children with several episcores capturing non-genetic variation at all ages.

Indexed as

DNA MethylationAdolescentAdultChildEpigenesis, GeneticFemaleGenotypeHumansLongitudinal StudiesMaleMiddle AgedProteinsYoung AdultProteinsALSPACDNA methylationEpigeneticsLifecourse epidemiologyPenalised regressionProteomics

Identifiers

PMID39709440
PMCPMC11663311

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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.