Poster No:
688
Submission Type:
Abstract Submission
Authors:
Yipeng Le1
Institutions:
1Tianjin Medical University, Tianjin, Tianjin
First Author:
Yipeng Le
Tianjin Medical University
Tianjin, Tianjin
Introduction:
Introduction: The relationship between brain gray matter volume (GMV) and body mass index (BMI) had been widely reported. However, the causal relationships between GMV and BMI remain uncertain. Besides, the pathways through which genetic risk genes influence GMV or obesity remain to be explored.
Methods:
Methods: We performed a bidirectional two-sample Mendelian randomization (MR) analysis using summary data from the available genome-wide association studies of GMV and BMI to determine whether GMV is causally associated with BMI among European populations. The inverse-variance weighted method was used as the primary approach, with weighted median, MR-Egger, simple and median model as supplementary methods, and a series of sensitivity analyses ensuring stability and reliability of results. Upon establishing causality between regional GMV and BMI, two types of mediation analyses based on structural equation modeling (SEM) was then performed to explore whether GMV could mediate the genetic influence on BMI and whether BMI could mediate the genetic influcence on GMV, respectively. Bootstrap method was applied to test the statistical significance of the resultant mediation effects.
Results:
Results: The forward MR analysis exploring the causal relationship of BMI on GMV showed that higher BMI significantly decreased GMV in the left cingulate gyrus (β = -0.17, 95% CI: -0.25 to -0.094, P = 1.97×10^(-5)) and the left lingual gyrus (β = -0.21, 95% CI: -0.29 to -0.12, P = 1.23×10^(-6)). The reverse MR analysis exploring the causal relationship of GMV on BMI revealed that higher GMV in the right caudate (β = 0.057, 95% CI: 0.028 to 0.085, P = 1.20×10^(-4)), the left cerebellar lobule IX (β = 0.052, 95% CI: 0.025 to 0.078, P = 1.38×10^(-4)), the right cerebellar lobule IX(β = 0.048, 95% CI: 0.024 to 0.073, P = 1.07×10^(-4)), and the right inferior temporal gyrus (β = 0.10, 95% CI: 0.055 to 0.15, P = 2.51×10^(-5)) significantly increased BMI.The mediation analyses indicated that GMV in the left cerebellar lobule IX and right cerebellar lobule IX partially mediated the effect of polygenic risk score (PRS) on BMI, with mediation proportions of 2.85% and 3.12%, respectively.
Conclusions:
Conclusions: Our study revealed the causal relationships between GMV and BMI in both directions and found that GMV in cerebellar regions partially mediated the genetic influences on BMI.
Genetics:
Genetic Modeling and Analysis Methods 1
Modeling and Analysis Methods:
Multivariate Approaches 2
Keywords:
Other - Mendelian randomization; mediation analysis; gray matter volume; body mass index
1|2Indicates the priority used for review
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Please indicate below if your study was a "resting state" or "task-activation” study.
Other
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Healthy subjects
Was this research conducted in the United States?
No
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
NOTE: Any human subjects studies without IRB approval will be automatically rejected.
Not applicable
Were any animal research approved by the relevant IACUC or other animal research panel?
NOTE: Any animal studies without IACUC approval will be automatically rejected.
Not applicable
Please indicate which methods were used in your research:
Structural MRI
For human MRI, what field strength scanner do you use?
3.0T
Which processing packages did you use for your study?
Free Surfer
Provide references using APA citation style.
Arnone, D., et al. (2013). State-dependent changes in hippocampal grey matter in depression. Mol Psychiatry, 18(12), 1265-1272. doi:10.1038/mp.2012.150
Bobb, J. F., et al. (2014). Cross-sectional and longitudinal association of body mass index and brain volume. Hum Brain Mapp, 35(1), 75-88. doi:10.1002/hbm.22159
Bowden, J., et al. (2015). Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol, 44(2), 512-525. doi:10.1093/ije/dyv080
Bowden, J., et al. (2016). Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator. Genet Epidemiol, 40(4), 304-314. doi:10.1002/gepi.21965
Bowden, J., et al. (2017). A framework for the investigation of pleiotropy in two-sample summary data Mendelian randomization. Stat Med, 36(11), 1783-1802. doi:10.1002/sim.7221
Bowden, J., et al. (2018). Improving the visualization, interpretation and analysis of two-sample summary data Mendelian randomization via the Radial plot and Radial regression. Int J Epidemiol, 47(4), 1264-1278. doi:10.1093/ije/dyy101
Brooks, S. J., et al. (2013). Late-life obesity is associated with smaller global and regional gray matter volumes: a voxel-based morphometric study. Int J Obes (Lond), 37(2), 230-236. doi:10.1038/ijo.2012.13
Bumaschny, V. F., et al. (2012). Obesity-programmed mice are rescued by early genetic intervention. J Clin Invest, 122(11), 4203-4212. doi:10.1172/jci62543
Burgess, S., et al. (2011). Avoiding bias from weak instruments in Mendelian randomization studies. Int J Epidemiol, 40(3), 755-764. doi:10.1093/ije/dyr036
Burgess, S., et al. (2013). Mendelian randomization analysis with multiple genetic variants using summarized data. Genet Epidemiol, 37(7), 658-665. doi:10.1002/gepi.21758
Bycroft, C., et al. (2018). The UK Biobank resource with deep phenotyping and genomic data. Nature, 562(7726), 203-209. doi:10.1038/s41586-018-0579-z
Carter, P., et al. (2022). Coffee consumption and cancer risk: a Mendelian randomisation study. Clin Nutr, 41(10), 2113-2123. doi:10.1016/j.clnu.2022.08.019
Chen, L., et al. (2023). Genetic Insights into Obesity and Brain: Combine Mendelian Randomization Study and Gene Expression Analysis. Brain Sci, 13(6). doi:10.3390/brainsci13060892
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