Genetics and epigenetics

Inference about causation between body mass index and DNA methylation in blood from a twin family study



Several studies have reported DNA methylation in blood to be associated with body mass index (BMI), but few have investigated causal aspects of the association. We used a twin family design to assess this association at two life points and applied a novel analytical approach to appraise the evidence for causality.


The methylation profile of DNA from peripheral blood was measured for 479 Australian women from 130 twin families. Linear regression was used to estimate the associations of DNA methylation at ~410,000 cytosine-guanine dinucleotides (CpGs), and of the average DNA methylation at ~20,000 genes, with current BMI, BMI at age 18–21 years, and the change between the two (BMI change). A novel regression-based methodology for twins, Inference about Causation through Examination of Familial Confounding (ICE FALCON), was used to assess causation.


At a 5% false discovery rate, nine, six and 12 CpGs at 24 loci were associated with current BMI, BMI at age 18–21 years and BMI change, respectively. The average DNA methylation of the BHLHE40 and SOCS3 loci was associated with current BMI, and of the PHGDH locus with BMI change. From the ICE FALCON analyses with BMI as the predictor and DNA methylation as the outcome, a woman’s DNA methylation level was associated with her co-twin’s BMI, and the association disappeared after conditioning on her own BMI, consistent with BMI causing DNA methylation. To the contrary, using DNA methylation as the predictor and BMI as the outcome, a woman’s BMI was not associated with her co-twin’s DNA methylation level, consistent with DNA methylation not causing BMI.


For middle-aged women, peripheral blood DNA methylation at several genomic locations is associated with current BMI, BMI at age 18–21 years and BMI change. Our study suggests that BMI has a causal effect on peripheral blood DNA methylation.

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We thank all women participating in this study. The data analysis was facilitated by Spartan, the High Performance Computer and Cloud hybrid system of the University of Melbourne. This research was facilitated through access to Twins Research Australia, a national resource supported by a Centre of Research Excellence Grant (ID: 1079102), from the National Health and Medical Research Council (NHMRC). . The AMDTSS was supported by NHMRC (grant numbers 1050561 and 1079102), Cancer Australia and National Breast Cancer Foundation (grant number 509307). SL is supported by the Australian Government Research Training Program Scholarship from the University of Melbourne. TLN is supported by a NHMRC Post-Graduate Scholarship and the Richard Lovell Travelling Scholarship from the University of Melbourne. MCS is a NHMRC Senior Research Fellow. JLH is a NHMRC Senior Principal Research Fellow.

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Correspondence to John L Hopper.

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