NIH R35 Grant Awarded

Wed, 11 Mar 2026 00:00:00 +0000

Our proposal “Causal Inference in Genetics: Integrative Methods for Mendelian Randomization and Single-Cell CRISPR Screening” has been awarded an NIH R35 grant from the National Institute of General Medical Sciences.

The grant supports our research on statistical methods for causal inference in genetics and genomics, including integrative approaches for Mendelian randomization and single-cell CRISPR screening.

FLOW-MR Published in Nature Communications

Mon, 28 Jul 2025 00:00:00 +0000

Our paper, Causal mediation analysis for time-varying heritable risk factors with Mendelian Randomization, has been published in Nature Communications:

👉 Nature Communications doi: 10.1038/s41467-025-61648-7
👉 Original preprint: bioRxiv 2024.02.10.579129

The paper introduces FLOW-MR, a computational framework for estimating causal structural equations for temporally ordered traits using only GWAS summary statistics. FLOW-MR enables decomposition of total genetic effects into:

direct effects
indirect mediation effects
pathway-specific causal contributions

Key methodological innovations include:

handling correlated longitudinal risk factors with limited GWAS sample sizes,
improved stability and efficiency under strong polygenicity and weak instruments through a spike-and-slab prior, and
robust inference even in noisy settings.

Using FLOW-MR, we identify a childhood-specific protective effect of BMI on breast cancer, and analyze the evolving causal impacts of BMI, systolic blood pressure, and cholesterol on stroke risk over the life course.

Statistical Genetics | Jingshu Wang

NIH R35 Grant Awarded

FLOW-MR Published in Nature Communications