PT - JOURNAL ARTICLE AU - Wu, Zixuan AU - Lewis, Ethan AU - Zhao, Qingyuan AU - Wang, Jingshu TI - Causal mediation analysis for time-varying heritable risk factors with Mendelian Randomization AID - 10.1101/2024.02.10.579129 DP - 2024 Jan 01 TA - bioRxiv PG - 2024.02.10.579129 4099 - http://biorxiv.org/content/early/2024/02/12/2024.02.10.579129.short 4100 - http://biorxiv.org/content/early/2024/02/12/2024.02.10.579129.full AB - Understanding the causal pathogenic mechanisms of diseases is crucial in clinical research. When randomized controlled experiments are not available, Mendelian Randomization (MR) offers an alternative, leveraging genetic mutations as a natural “experiment” to mitigate environmental confoundings. However, most MR analyses treat the risk factors as static variables, potentially oversimplifying dynamic risk factor effects. The framework of life-course MR has been introduced to address this issue. However, current methods face challenges especially when the age-specific GWAS datasets have limited cohort sizes and there are substantial correlations between time points for a single trait. This study proposes a novel approach, estimating a unified system of structural equations for a sequence of temporally ordered heritable traits, requiring only GWAS summary statistics. The method facilitates statistical inference on direct, indirect, and path-wise causal effects and demonstrates superior efficiency and reliability, particularly with noisy GWAS data. By incorporating a spike-and-slab prior for genetic effects, the approach can address extreme polygenicity and weak instrument bias. Through this methodology, we uncovered a protective effect of BMI on breast cancer during a confined period of childhood development. We also analyzed how BMI, systolic blood pressure (SBP), and low-density cholesterol levels influence stroke risk across childhood and adulthood, and identified the intriguing relationships between these risk factors.Competing Interest StatementThe authors have declared no competing interest.