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Methylome-wide studies of six metabolic traits.

Authors :
Smith HM
Ng HK
Moodie JE
Gadd DA
McCartney DL
Bernabeu E
Campbell A
Redmond P
Taylor A
Page D
Corley J
Harris SE
Tay D
Deary IJ
Evans KL
Robinson MR
Chambers JC
Loh M
Cox SR
Marioni RE
Hillary RF
Source :
MedRxiv : the preprint server for health sciences [medRxiv] 2024 May 29. Date of Electronic Publication: 2024 May 29.
Publication Year :
2024

Abstract

Exploring the molecular correlates of metabolic health measures may identify the shared and unique biological processes and pathways that they track. Here, we performed epigenome-wide association studies (EWASs) of six metabolic traits: body mass index (BMI), body fat percentage, waist-hip ratio (WHR), and blood-based measures of glucose, high-density lipoprotein (HDL) cholesterol, and total cholesterol. We considered blood-based DNA methylation (DNAm) from >750,000 CpG sites in over 17,000 volunteers from the Generation Scotland (GS) cohort. Linear regression analyses identified between 304 and 11,815 significant CpGs per trait at P<3.6×10 <superscript>-8</superscript> , with 37 significant CpG sites across all six traits. Further, we performed a Bayesian EWAS that jointly models all CpGs simultaneously and conditionally on each other, as opposed to the marginal linear regression analyses. This identified between 3 and 27 CpGs with a posterior inclusion probability ≥ 0.95 across the six traits. Next, we used elastic net penalised regression to train epigenetic scores (EpiScores) of each trait in GS, which were then tested in the Lothian Birth Cohort 1936 (LBC1936; European ancestry) and Health for Life in Singapore (HELIOS; Indian-, Malay- and Chinese-ancestries). A maximum of 27.1% of the variance in BMI was explained by the BMI EpiScore in the subset of Malay-ancestry Singaporeans. Four metabolic EpiScores were associated with general cognitive function in LBC1936 in models adjusted for vascular risk factors (Standardised β <subscript>range</subscript> : 0.08 - 0.12, P <subscript>FDR</subscript> < 0.05). EpiScores of metabolic health are applicable across ancestries and can reflect differences in brain health.<br />Competing Interests: R.E.M has received a speaker fee from Illumina, is an advisor to the Epigenetic Clock Development Foundation and Optima Partners Ltd. D.A.G and D.L.M. are employed by Optima Partners Ltd in a part-time capacity. R.F.H has acted as a scientific consultant to Optima Partner Ltd and has received consultant fees from Illumina. The remaining authors declare no competing interests.

Details

Language :
English
Database :
MEDLINE
Journal :
MedRxiv : the preprint server for health sciences
Publication Type :
Academic Journal
Accession number :
38853823
Full Text :
https://doi.org/10.1101/2024.05.29.24308103