Research

Our lab uses single-cell epigenomics to dissect how genetics and environment jointly shape brain and immune cell states during Alzheimer’s Disease progression. We combine cutting-edge single-cell genomics technologies with computational and AI approaches to understand AD mechanisms and enable precision prevention.

Research Areas

1. Genetics × Environment on AD Progression Using Genetically Diverse Mice

The interplay between genetic background and environmental exposures is a major but poorly understood driver of AD risk and progression. We leverage genetically diverse mouse models — including the Collaborative Cross and Diversity Outbred populations — to systematically dissect how genetic variation interacts with environmental factors (e.g., diet, infection, stress) to shape epigenomic landscapes in brain and immune cells during AD progression.

Key questions:

• How does genetic diversity modulate the epigenomic response to environmental exposures in the context of AD?
• Which genetic variants sensitize or protect specific brain cell types from AD-associated epigenomic changes?
• Can we identify shared and divergent gene regulatory programs across genetically diverse AD mouse models?

2. Genetics × Environment on AD Progression in Human Longitudinal Cohorts

Translating findings from animal models to humans requires studying real-world gene–environment interactions at scale. We analyze longitudinal human cohort data — integrating genetic, epigenomic, and environmental exposure data — to characterize how G×E interactions contribute to AD risk, timing of onset, and rate of progression at the population level.

Key questions:

• What environmental exposures interact with AD genetic risk variants to accelerate or delay disease onset?
• Are there epigenomic biomarkers of G×E interactions that predict cognitive decline?
• How do immune cell epigenomes reflect cumulative genetic and environmental influences in aging individuals?

3. Mechanism of AD Progression Using Mouse Models and iPSC/Fibroblast-Induced Neurons

Understanding the cell-autonomous and non-cell-autonomous mechanisms of AD requires tractable experimental systems. We use AD mouse models alongside iPSC-derived and fibroblast-induced neurons to study how specific genetic risk variants and environmental perturbations rewire gene regulatory networks in disease-relevant cell types.

Key questions:

• How do AD risk variants alter chromatin organization and gene expression in neurons, glia, and immune cells?
• What are the epigenomic signatures of early versus late neurodegeneration in model systems?
• Can induced neuron models faithfully recapitulate the epigenomic features of human AD brain?

4. G×E AI Model for Precision Prevention of AD

Integrating multi-modal genomic, epigenomic, and environmental data requires new computational frameworks. We are developing AI models that learn from G×E interaction data to predict individual AD risk trajectories and identify actionable intervention windows for precision prevention.

Key questions:

• Can we build interpretable AI models that predict AD onset and progression from epigenomic and environmental features?
• Which G×E interactions are most predictive of disease risk across diverse populations?
• How can AI-guided epigenomic signatures guide personalized lifestyle or pharmacological interventions?

Funding

Our research is supported by [funding sources — please update].