An epigenome-wide study of selenium status and DNA methylation in the Strong Heart Study.

American Indian populations DNA methylation Epigenetics Selenium Strong Heart Study

Journal

Environment international
ISSN: 1873-6750
Titre abrégé: Environ Int
Pays: Netherlands
ID NLM: 7807270

Informations de publication

Date de publication:
14 Aug 2024
Historique:
received: 26 01 2024
revised: 19 06 2024
accepted: 13 08 2024
medline: 19 8 2024
pubmed: 19 8 2024
entrez: 18 8 2024
Statut: aheadofprint

Résumé

Selenium (Se) is an essential nutrient linked to adverse health endpoints at low and high levels. The mechanisms behind these relationships remain unclear and there is a need to further understand the epigenetic impacts of Se and their relationship to disease. We investigated the association between urinary Se levels and DNA methylation (DNAm) in the Strong Heart Study (SHS), a prospective study of cardiovascular disease (CVD) among American Indians adults. Selenium concentrations were measured in urine (collected in 1989-1991) using inductively coupled plasma mass spectrometry among 1,357 participants free of CVD and diabetes. DNAm in whole blood was measured cross-sectionally using the Illumina MethylationEPIC BeadChip (850 K) Array. We used epigenome-wide robust linear regressions and elastic net to identify differentially methylated cytosine-guanine dinucleotide (CpG) sites associated with urinary Se levels. The mean (standard deviation) urinary Se concentration was 51.8 (25.1) μg/g creatinine. Across 788,368 CpG sites, five differentially methylated positions (DMP) (hypermethylated: cg00163554, cg18212762, cg11270656, and hypomethylated: cg25194720, cg00886293) were significantly associated with Se in linear regressions after accounting for multiple comparisons (false discovery rate p-value: 0.10). The top hypermethylated DMP (cg00163554) was annotated to the Disco Interacting Protein 2 Homolog C (DIP2C) gene, which relates to transcription factor binding. Elastic net models selected 425 hypo- and hyper-methylated DMPs associated with urinary Se, including three sites (cg00163554 [DIP2C], cg18212762 [MAP4K2], cg11270656 [GPIHBP1]) identified in linear regressions. Urinary Se was associated with minimal changes in DNAm in adults from American Indian communities across the Southwest and the Great Plains in the United States, suggesting that other mechanisms may be driving health impacts. Future analyses should explore other mechanistic biomarkers in human populations, determine these relationships prospectively, and investigate the potential role of differentially methylated sites with disease endpoints.

Sections du résumé

BACKGROUND BACKGROUND
Selenium (Se) is an essential nutrient linked to adverse health endpoints at low and high levels. The mechanisms behind these relationships remain unclear and there is a need to further understand the epigenetic impacts of Se and their relationship to disease. We investigated the association between urinary Se levels and DNA methylation (DNAm) in the Strong Heart Study (SHS), a prospective study of cardiovascular disease (CVD) among American Indians adults.
METHODS METHODS
Selenium concentrations were measured in urine (collected in 1989-1991) using inductively coupled plasma mass spectrometry among 1,357 participants free of CVD and diabetes. DNAm in whole blood was measured cross-sectionally using the Illumina MethylationEPIC BeadChip (850 K) Array. We used epigenome-wide robust linear regressions and elastic net to identify differentially methylated cytosine-guanine dinucleotide (CpG) sites associated with urinary Se levels.
RESULTS RESULTS
The mean (standard deviation) urinary Se concentration was 51.8 (25.1) μg/g creatinine. Across 788,368 CpG sites, five differentially methylated positions (DMP) (hypermethylated: cg00163554, cg18212762, cg11270656, and hypomethylated: cg25194720, cg00886293) were significantly associated with Se in linear regressions after accounting for multiple comparisons (false discovery rate p-value: 0.10). The top hypermethylated DMP (cg00163554) was annotated to the Disco Interacting Protein 2 Homolog C (DIP2C) gene, which relates to transcription factor binding. Elastic net models selected 425 hypo- and hyper-methylated DMPs associated with urinary Se, including three sites (cg00163554 [DIP2C], cg18212762 [MAP4K2], cg11270656 [GPIHBP1]) identified in linear regressions.
CONCLUSIONS CONCLUSIONS
Urinary Se was associated with minimal changes in DNAm in adults from American Indian communities across the Southwest and the Great Plains in the United States, suggesting that other mechanisms may be driving health impacts. Future analyses should explore other mechanistic biomarkers in human populations, determine these relationships prospectively, and investigate the potential role of differentially methylated sites with disease endpoints.

Identifiants

pubmed: 39154409
pii: S0160-4120(24)00541-5
doi: 10.1016/j.envint.2024.108955
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

108955

Informations de copyright

Copyright © 2024. Published by Elsevier Ltd.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Wil Lieberman-Cribbin (W)

Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA. Electronic address: wfl2112@cumc.columbia.edu.

Arce Domingo-Relloso (A)

Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA; Department of Biostatistics, Columbia University Mailman School of Public Health, New York, NY, USA.

Ronald A Glabonjat (RA)

Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA.

Kathrin Schilling (K)

Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA.

Shelley A Cole (SA)

Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA.

Marcia O'Leary (M)

Missouri Breaks Industries Research, Cheyenne River Sioux Tribe, Eagle Butte, SD 57625, USA.

Lyle G Best (LG)

Missouri Breaks Industries Research, Cheyenne River Sioux Tribe, Eagle Butte, SD 57625, USA.

Ying Zhang (Y)

Department of Biostatistics and Epidemiology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.

Amanda M Fretts (AM)

Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA.

Jason G Umans (JG)

MedStar Health Research Institute, Hyattsville, MD, USA; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, USA.

Walter Goessler (W)

Institute of Chemistry, University of Graz, Graz, Austria.

Ana Navas-Acien (A)

Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA.

Maria Tellez-Plaza (M)

Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Instituto de Salud Carlos III, 28029, Madrid, Spain.

Allison Kupsco (A)

Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA.

Classifications MeSH