Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2015 Jul;23(7):1493-501.
doi: 10.1002/oby.21111.

Epigenome-wide study identifies novel methylation loci associated with body mass index and waist circumference

Stella Aslibekyan  1 , Ellen W Demerath  2 , Michael Mendelson  3   4   5 , Degui Zhi  6 , Weihua Guan  7 , Liming Liang  3   4   8   9 , Jin Sha  1 , James S Pankow  2 , Chunyu Liu  4   10 , Marguerite R Irvin  1 , Myriam Fornage  11   12 , Bertha Hidalgo  1 , Li-An Lin  12 , Krista Stanton Thibeault  13 , Jan Bressler  12 , Michael Y Tsai  14 , Megan L Grove  12 , Paul N Hopkins  15 , Eric Boerwinkle  11   12 , Ingrid B Borecki  16 , Jose M Ordovas  17   18   19 , Daniel Levy  3   4 , Hemant K Tiwari  6 , Devin M Absher  13 , Donna K Arnett  1
Affiliations

Epigenome-wide study identifies novel methylation loci associated with body mass index and waist circumference

Stella Aslibekyan et al. Obesity (Silver Spring). 2015 Jul.

Abstract

Objective: To conduct an epigenome-wide analysis of DNA methylation and obesity traits.

Methods: DNA methylation was quantified in CD4+ T-cells using the Illumina Infinium HumanMethylation450 array in 991 participants of the Genetics of Lipid Lowering Drugs and Diet Network. Methylation at individual cytosine-phosphate-guanine (CpG) sites as a function of body mass index (BMI) and waist circumference (WC), adjusting for age, gender, study site, T-cell purity, smoking, and family structure, was modeled.

Results: Epigenome-wide significant associations between eight CpG sites and BMI and five CpG sites and WC, successfully replicating the top hits in whole blood samples from the Framingham Heart Study (n = 2,377) and the Atherosclerosis Risk in Communities study (n = 2,097), were found. Top findings were in CPT1A (meta-analysis P = 2.7 × 10(-43) for BMI and 9.9 × 10(-23) for WC), PHGDH (meta-analysis P = 2.0 × 10(-15) for BMI and 4.0 × 10(-9) for WC), CD38 (meta-analysis P = 6.3 × 10(-11) for BMI and 1.6 × 10(-12) for WC), and long intergenic non-coding RNA 00263 (meta-analysis P = 2.2 × 10(-16) for BMI and 8.9 × 10(-14) for WC), regions with biologically plausible relationships to adiposity.

Conclusions: This large-scale epigenome-wide study discovered and replicated robust associations between DNA methylation at CpG loci and obesity indices, laying the groundwork for future diagnostic and/or therapeutic applications.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Manhattan plot of epigenome-wide results of testing for association between epigenome-wide methylation and body mass index. The X-axes display the chromosome on which the CpG site is located, the Y-axes display –log10(P-value). The red horizontal line indicates the threshold for epigenome-wide statistical significance after a Bonferroni correction.
Figure 2
Figure 2
Manhattan plot of epigenome-wide results of testing for association between epigenome-wide methylation and waist circumference. The X-axes display the chromosome on which the CpG site is located, the Y-axes display –log10(P-value). The red horizontal line indicates the threshold for epigenome-wide statistical significance after a Bonferroni correction.
Figure 3
Figure 3
ENCODE annotation of the genomic region containing the transcription start site of CD38.
Figure 4
Figure 4
ENCODE annotation of the genomic region containing the long intergenic non-coding RNA on chromosome 10.
See this image and copyright information in PMC

References

    1. Hemani G, Yang J, Vinkhuyzen A, Powell JE, Willemsen G, Hottenga JJ, et al. Inference of the genetic architecture underlying BMI and height with the use of 20,240 sibling pairs. Am J Hum Genet. 2013;93:865–875. - PMC - PubMed
    1. Vattikuti S, Guo J, Chow CC. Heritability and genetic correlations explained by common SNPs for metabolic syndrome traits. PLoS Genet. 2012;8:e1002637. - PMC - PubMed
    1. Schwenk RW, Vogel H, Schurmann A. Genetic and epigenetic control of metabolic health. Molecular metabolism. 2013;2:337–347. - PMC - PubMed
    1. Dick KJ, Nelson CP, Tsaprouni L, Sandling JK, Aissi D, Wahl S, et al. DNA methylation and body-mass index: a genome-wide analysis. Lancet. 2014;383:1990–1998. - PubMed
    1. Xu X, Su S, Barnes VA, De Miguel C, Pollock J, Ownby D, et al. A genome-wide methylation study on obesity: differential variability and differential methylation. Epigenetics. 2013;8:522–533. - PMC - PubMed

Publication types

Substances