Inference about causation from examination of familial confounding (ICE FALCON): a model for assessing causation analogous to Mendelian randomization

Abstract

Background We developed a method to make Inference about Causation from Examination of FAmiliaL CONfounding (ICE FALCON) using observational data for related individuals and considering changes in a pair of regression coefficients. ICE FALCON has some similarities to Mendelian randomization (MR) but uses in effect all the familial determinants of the exposure, not just those captured by measured genetic variants, and does not require genetic data nor make strong assumptions. ICE FALCON can assess tracking of a measure over time, an issue often difficult to assess using MR due to lack of a valid instrumental variable. Methods We describe ICE FALCON and present two empirical applications with simulations. Results We found evidence consistent with body mass index (BMI) having a causal effect on DNA methylation at the ABCG1 locus, the same conclusion as from MR analyses but providing about 2.5 times more information per subject. We found evidence that tracking of BMI is consistent with longitudinal causation, as well as familial confounding. The simulations supported the validity of ICE FALCON. Conclusions There are conceptual similarities between ICE FALCON and MR, but empirically they are giving similar conclusions with possibly more information per subject from ICE FALCON. ICE FALCON can be applied to circumstances in which MR cannot be applied, such as when there is no a priori genetic knowledge and/or data available to create a valid instrumental variable, or when the assumptions underlying MR analysis are suspect. ICE FALCON could provide insights into causality for a wide range of public health questions.

Associations of fertility parameters with fatty acids and DNA methylation in Mexican women undergoing in vitro fertilization

“…We also tested for any association between the BMI and DNAm. Since at least two studies have indicated that the BMI causes DNAm rather than vice versa, we employed a linear regression model with BMI as independent variable, adjusted for age 31,32 . No signi cant association was detected (Supplementary Table 4).…”

DNA methylome analysis identifies BMI‐related epigenetic changes associated with non‐small cell lung cancer susceptibility

“…The interrelationship between BMI and DNA methylation is complex and possibly bidirectional. Li et al carried out the ICE FALCON (Inference about Causation from Examination of Familial Confounding) 34 analysis in 479 Australian women from twin families and found that BMI had a causal effect on DNA methylation level at ABCG1 cg06500161 35 . Wahl et al calculated a weighted genetic risk score (GRS) based on 29 known BMI SNPs and observed the significant direct effects of BMI‐weighted GRS on methylations of ABCG1 cg06500161 ( p = 6.4E‐05) and SREBF1 cg11024682 ( p = 4.1E‐03) 13 .…”

Education, income, and obesity: A nationwide Chinese twin study

“…We explored the causal inference between SES and obesity using Inference about Causation through Examination of FAmiliaL CONfounding (ICE FALCON), a statistical modeling approach used to obtain observational data for related individuals, particularly twin pairs (24‐27). ICE FALCON makes causal inference using the familial similarity of an exposure, which has similarities with bidirectional Mendelian randomization (28). By causal, it is meant that, were it possible to vary a predictor measure experimentally, the expected value of the outcome measure would change (25).…”