The link between DNA methylation, obesity, and adiposity-related diseases in the general population remains uncertain.
Methods and Findings
We conducted an association study of body mass index (BMI) and differential methylation for over 400,000 CpGs assayed by microarray in whole-blood-derived DNA from 3,743 participants in the Framingham Heart Study and the Lothian Birth Cohorts, with independent replication in three external cohorts of 4,055 participants. We examined variations in whole blood gene expression and conducted Mendelian randomization analyses to investigate the functional and clinical relevance of the findings. We identified novel and previously reported BMI-related differential methylation at 83 CpGs that replicated across cohorts; BMI-related differential methylation was associated with concurrent changes in the expression of genes in lipid metabolism pathways. Genetic instrumental variable analysis of alterations in methylation at one of the 83 replicated CpGs, cg11024682 (intronic to sterol regulatory element binding transcription factor 1 [SREBF1]), demonstrated links to BMI, adiposity-related traits, and coronary artery disease. Independent genetic instruments for expression of SREBF1 supported the findings linking methylation to adiposity and cardiometabolic disease. Methylation at a substantial proportion (16 of 83) of the identified loci was found to be secondary to differences in BMI. However, the cross-sectional nature of the data limits definitive causal determination.
We present robust associations of BMI with differential DNA methylation at numerous loci in blood cells. BMI-related DNA methylation and gene expression provide mechanistic insights into the relationship between DNA methylation, obesity, and adiposity-related diseases.
Digital Object Identifier (DOI)
The Framingham Heart Study is funded by National Institutes of Health contract N01-HC-25195 and HHSN268201500001I. The Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) epigenetics study is funded by the NIH National Heart, Lung, and Blood Institute grant R01 HL 104135-01. The Atherosclerosis Risk in Communities (ARIC) study is carried out as a collaborative study supported by the National Heart, Lung, and Blood Institute (NHLBI) contracts (HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN2682011000010C, HHSN2682011000011C, HHSN2682011000012C).
Due to the large number of funding sources, only the first few are listed in this section. For the complete list of funding sources, please download this article.
Data on adiposity traits have been contributed by GIANT investigators and have been downloaded from https://www.broadinstitute.org/collaboration/giant/index.php/. Data on glycemic traits have been contributed by MAGIC investigators and have been downloaded from https://www.magicinvestigators.org. Data on diabetes traits have been contributed by the DIAGRAM consortium and have been downloaded from http://diagram-consortium.org/. Data on coronary artery disease/myocardial infarction have been contributed by CARDIoGRAMplusC4D investigators and have been downloaded from http://www.cardiogramplusc4d.org/.
Participant-level phenotype and genotype data from the Framingham Heart Study are accessible from the U.S. National Center for Biotechnology Information (NCBI) database of Genotypes and Phenotypes (dbGaP) at https://dbgap.ncbi.nlm.nih.gov/ to approved scientific investigators pursuing research questions that are consistent with the informed consent agreements provided by individual research participants. The FHS methylation data are available at dbGaP under the accession number phs000724.v2.p9 and gene expression data at accession number phs000363.v3.p6. Lothian Birth Cohorts' methylation data have been submitted to the European Genome-phenome Archive under accession number EGAS00001000910; phenotypic data are available at dbGaP under the accession number phs000821.v1.p1.
Mendelson, Michael M.; Marioni, Riccardo E.; Joehanes, Roby; Liu, Chunyu; Hedman, Åsa K.; Aslibekyan, Stella; Demerath, Ellen W.; Guan, Weihua; Zhi, Degui; Yao, Chen; Huan, Tianxiao; Willinger, Christine; Chen, Brian; Courchesne, Paul; Multhaup, Michael; Irvin, Marguerite R.; Cohain, Ariella; Schadt, Eric E.; Grove, Megan L.; Bressler, Jan; North, Kari; Sundström, Johan; Gustafsson, Stefan; Shah, Sonia; McRae, Allan F.; Harris, Sarah E.; Gibson, Jude; Redmond, Paul; Corley, Janie; Murphy, Lee; and Arnett, Donna K., "Association of Body Mass Index with DNA Methylation and Gene Expression in Blood Cells and Relations to Cardiometabolic Disease: A Mendelian Randomization Approach" (2017). Epidemiology Faculty Publications. 18.
S1 Fig. Quantile-quantile plot of expected versus observed −log10 p-values from the epigenome-wide association study of BMI in the FHS-LBC meta-analysis.
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S2 Fig. Quantile-quantile plot of expected versus observed −log10 p-values from the epigenome-wide association study of BMI in FHS alone.
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S3 Fig. Manhattan plot of the epigenome-wide association study of BMI in the FHS-LBC meta-analysis in age- and sex-adjusted models.
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S4 Fig. Comparison of −log10 p-values of results of the FHS-LBC BMI epigenome-wide association study.
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S5 Fig. Three-dimensional scatterplot of −log10 p-values for 135 epigenome-wide significant CpGs from the FHS-LBC discovery cohorts in three external replication cohorts.
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S6 Fig. Variation in BMI explained (adjusted R2) by differential methylation of 77 nonredundant replicated CpGs in the FHS-LBC epigenome-wide association study and tested in the independent PIVUS cohort.
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S7 Fig. Boxplot of BMI in the PIVUS cohort across deciles of the additive weighted composite measure of differential DNA methylation at 77 nonredundant replicated CpGs.
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S8 Fig. Relationship between location of CpG relative to the transcription start site and proportion of variation in changes in corresponding gene expression, stratified by whether the CpG resides in a known DHS or enhancer region.
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S9 Fig. Relationship between location of CpG relative to the transcription start site and proportion of variation in changes in corresponding gene expression, stratified based on location relative to nearest CpG island.
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S10 Fig. Enrichment of nonredundant replicated differentially methylated CpGs from the BMI epigenome-wide association study in DNase I hypersensitive sites among various cell and tissue types using ENCODE and 2012 Roadmap Epigenomics Project data.
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S11 Fig. Enrichment of nonredundant replicated differentially methylated CpGs from the BMI epigenome-wide association study in DNAse I hypersensitive sites among various cell and tissue types using consolidated Roadmap Epigenomics Project and BLUEPRINT Epigenome data.
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S12 Fig. Enrichment of nonredundant replicated differentially methylated CpGs from the BMI epigenome-wide association study in regions overlapping histone modifications in the consolidated Roadmap Epigenomics Project data: H3K4me1 and H3K4me3 histone modifications.
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S13 Fig. Enrichment of nonredundant replicated differentially methylated CpGs from the BMI epigenome-wide association study in regions overlapping histone modifications in the consolidated Roadmap Epigenomics Project data: H3K9me3 and H3K27me3 histone modifications.
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S14 Fig. Enrichment of nonredundant replicated differentially methylated CpGs from the BMI epigenome-wide association study in regions overlapping histone modifications in the consolidated Roadmap Epigenomics Project data: H3K36me3 histone modifications.
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S15 Fig. Depiction of an example result for SREBF1 from the bidirectional Mendelian randomization analyses for each of the replicated CpGs and BMI.
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S16 Fig. DNA methylation and mRNA expression of CPT1A and SREBF1 in whole blood in triglyceride and fatty acid catabolism (beta-oxidation) pathways was observed in association with higher BMI.
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S1 Methods. Supplemental methods.
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S1 STROBE Checklist.
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S1 Table. Complete list of methylome-wide significant (p-value < 1.2 × 10−7) CpGs associated with BMI in the FHS-LBC meta-analysis.
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S2 Table. Secondary models including additional adjustment for smoking and exclusion of BMI < 18 and > 35 kg/m2.
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S3 Table. External replication of methylome-wide significant CpGs.
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S4 Table. Distribution and variability of replicated BMI-related differentially methylated CpGs.
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S5 Table. Secondary models testing age and sex interactions.
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S6 Table. Sex-stratified models for cg26651978 (LGALS3BP) in the replication cohorts.
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S7 Table. Association of BMI with the replicated CpGs conditional on the top methylation QTL in the FHS.
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S8 Table. Three-way association results of CpGs, expression levels of nearby annotated genes, and BMI.
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S9 Table. Enrichment of BMI-related CpGs associated with gene expression in DNase I hypersensitive sites and enhancers.
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S10 Table. Results from the forward Mendelian randomization (DNA methylation affecting BMI) for the 83 replicated CpGs.
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S11 Table. Results from the mediator-to-outcome analyses of the two-step trans-tissue Mendelian randomization.
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S12 Table. Results from the reverse Mendelian randomization for the 83 replicated CpGs using the BMI genetic risk score instrumental variable.
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S13 Table. Sensitivity analyses for the reverse Mendelian randomization for the 16 implicated CpGs using the FTO locus SNP instrumental variable.
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S14 Table. Overlap between replicated BMI-related CpGs and metabolites as reported from the KORA cohort .
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S1 Text. Project proposal.