# Associations of DNA methylation estimators of protein abundance with concurrent and future physical health risk factors

**Authors:** Scott Waterfield, Paul Yousefi, Matthew Suderman

PMC · DOI: 10.1038/s41598-025-31843-z · Scientific Reports · 2025-12-10

## TL;DR

This study explores how DNA methylation-based protein abundance estimates relate to physical health traits in children and young adults, finding potential associations.

## Contribution

The study introduces episcores as a novel tool for identifying protein-phenotype associations in populations without direct protein measurements.

## Key findings

- 9 cross-sectional and 11 prospective phenotype-episcore associations were identified.
- CHIT1 and SEMA3E episcores showed multiple associations with physical health traits.
- No causal effects were found using Mendelian randomisation between proteins and phenotypes.

## Abstract

DNA methylation (DNAm) is an epigenetic modification which plays a role in gene regulation and has genetic and environmental influences. Recently, DNAm-based models of protein abundance (termed episcores) have been developed and were found to be associated with incident disease in older adults. Here, we ask if these episcores are associated with latent physical health phenotypes in children and young adults in the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Episcores were projected in ALSPAC participants who had DNAm measurements in cord blood, and peripheral blood at ages seven, nine, 17, and 24 (n = 192–2857). We analysed cross-sectional associations between 108 episcores and 17 physical health phenotypes, followed by an examination of prospective associations between episcores and the same phenotypes measured 2 + years after the blood samples used for episcore calculation. Two-sample Mendelian randomisation (2SMR) was then used to evaluate evidence for causal relationships between the underlying proteins and any associated physical health phenotypes. Of the associations tested between 17 physical health phenotypes and 108 episcores at multiple timepoints, 9 cross-sectional (CHIT1 is associated with 8 of these) and 11 prospective (SEMA3E is associated with 7 of these) phenotype-episcore associations were discovered. Of these, no 2SMR analyses suggested a causal effect of a protein on its related phenotype. We find evidence to suggest that episcores may be useful for discovering protein-phenotype associations in populations lacking direct measurements of protein abundance.

The online version contains supplementary material available at 10.1038/s41598-025-31843-z.

## Linked entities

- **Proteins:** CHIT1 (chitinase 1), SEMA3E (semaphorin 3E)

## Full-text entities

- **Genes:** INS (insulin) [NCBI Gene 3630] {aka IDDM, IDDM1, IDDM2, ILPR, IRDN, MODY10}, CCL22 (C-C motif chemokine ligand 22) [NCBI Gene 6367] {aka A-152E5.1, ABCD-1, DC/B-CK, MDC, SCYA22, STCP-1}, DBP (D-box binding PAR bZIP transcription factor) [NCBI Gene 1628] {aka DABP, taxREB302}, CSF3 (colony stimulating factor 3) [NCBI Gene 1440] {aka C17orf33, CSF3OS, GCSF}, ADIPOQ (adiponectin, C1Q and collagen domain containing) [NCBI Gene 9370] {aka ACDC, ACRP30, ADIPQTL1, ADPN, APM-1, APM1}, NMNAT1 (nicotinamide nucleotide adenylyltransferase 1) [NCBI Gene 64802] {aka LCA9, NMNAT, PNAT1, SHILCA}, CD8A (CD8 subunit alpha) [NCBI Gene 925] {aka CD8, CD8alpha, IMD116, Leu2, p32}, CXCL11 (C-X-C motif chemokine ligand 11) [NCBI Gene 6373] {aka H174, I-TAC, IP-9, IP9, SCYB11, SCYB9B}, COG2 (component of oligomeric golgi complex 2) [NCBI Gene 22796] {aka CDG2Q, LDLC}, CD14 (CD14 molecule) [NCBI Gene 929], CHIT1 (chitinase 1) [NCBI Gene 1118] {aka CHI3, CHIT, CHITD}, CSF1 (colony stimulating factor 1) [NCBI Gene 1435] {aka CSF-1, MCSF, PG-M-CSF}, CRP (C-reactive protein) [NCBI Gene 1401] {aka PTX1}, IL6 (interleukin 6) [NCBI Gene 3569] {aka BSF-2, BSF2, CDF, HGF, HSF, IFN-beta-2}, AHRR (aryl hydrocarbon receptor repressor) [NCBI Gene 57491] {aka AHH, AHHR, bHLHe77}, CXCL10 (C-X-C motif chemokine ligand 10) [NCBI Gene 3627] {aka C7, IFI10, INP10, IP-10, SCYB10, crg-2}, CD4 (CD4 molecule) [NCBI Gene 920] {aka CD4mut, IMD79, Leu-3, OKT4D, T4}, SPOCK2 (SPARC (osteonectin), cwcv and kazal like domains proteoglycan 2) [NCBI Gene 9806] {aka testican-2}, SEMA3E (semaphorin 3E) [NCBI Gene 9723] {aka M-SEMAH, M-SemaK, SEMAH, coll-5}
- **Diseases:** Cancer (MESH:D009369), diabetes (MESH:D003920), inflammation (MESH:D007249), ARIES (MESH:D000081042), obesity (MESH:D009765), Bone Mass (MESH:D001847), insulin resistance (MESH:D007333), atherosclerosis (MESH:D050197), heart disease (MESH:D006331)
- **Chemicals:** Lactate (MESH:D019344), Triglyceride (MESH:D014280), met (MESH:D008715), cholesterols (MESH:D002784), d-Acetate (-), NAD + (MESH:D009243), Acetate (MESH:D000085), Glucose (MESH:D005947), Citrate (MESH:D019343)
- **Species:** Homo sapiens (human, species) [taxon 9606]
- **Mutations:** A 450K, Q84R

## Full text

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## Figures

4 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12808646/full.md

## References

6 references — full list in the complete paper: https://tomesphere.com/paper/PMC12808646/full.md

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Source: https://tomesphere.com/paper/PMC12808646