C-reactive protein levels and body mass index: elucidating direction of causation through reciprocal Mendelian randomization

孟德尔随机化 体质指数 内科学 观察研究 C反应蛋白 医学 置信区间 因果关系(物理学) 肥胖 内分泌学 遗传学 生物 炎症 基因 物理 基因型 量子力学 遗传变异
作者
Nicholas J. Timpson,Børge G. Nordestgaard,Roger Harbord,Jeppe Zacho,Timothy M. Frayling,Anne Tybjærg‐Hansen,George Davey Smith
出处
期刊:International Journal of Obesity [Springer Nature]
卷期号:35 (2): 300-308 被引量:287
标识
DOI:10.1038/ijo.2010.137
摘要

The assignment of direction and causality within networks of observational associations is problematic outside randomized control trials, and the presence of a causal relationship between body mass index (BMI) and C-reactive protein (CRP) is disputed. Using reciprocal Mendelian randomization, we aim to assess the direction of causality in relationships between BMI and CRP and to demonstrate this as a promising analytical technique. The study was based on a large, cross-sectional European study from Copenhagen, Denmark. Genetic associates of BMI (FTO(rs9939609)) and circulating CRP (CRP(rs3091244)) have been used to reexamine observational associations between them. Observational analyses showed a strong, positive association between circulating CRP and BMI (change in BMI for a doubling in logCRP of 1.03 kg m−2 (95% confidence interval (95% CI): 1.00, 1.07), P<0.0001). Analysis using CRP(rs3091244) to re-estimate the causal effect of circulating CRP on BMI yielded null effects (change in BMI for a doubling in logCRP of −0.24 kg m−2 (95% CI: −0.58, 0.11), P=0.2). In contrast, analysis using FTO(rs9939609) to assess the causal effect of BMI on circulating CRP confirmed observational associations (ratio of geometric means of CRP per s.d. increase in BMI 1.41 (95% CI: 1.10, 1.80), P=0.006). Taken together, these data suggest that the observed association between circulating CRP and measured BMI is likely to be driven by BMI, with CRP being a marker of elevated adiposity. More generally, the method of reciprocal randomization has general applicability in determining the direction of causation within inter-correlated networks of metabolic components.

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