Buu Truong

Buu Truong

PhD Student in Genetic Epidemiology & Statistical Genetics at Harvard University | Computational Biologist at the Broad Institute of MIT and Harvard

About Me

I am a PhD student at Harvard T.H. Chan School of Public Health and a Computational Biologist at the Broad Institute of MIT and Harvard. I develop statistical and computational methods for genomics – connecting genetic variation to disease risk across diverse populations.

I work with Prof. Alkes Price, Prof. Liming Liang, and Dr. Pradeep Natarajan.

Previously, I trained as a Medical Doctor in Vietnam and worked as a visiting researcher in statistical genetics at the South Australian Health and Medical Research Institute.

Research

I build methods that bridge genomics and clinical medicine. My work spans three areas:

Polygenic Risk Scores – I developed PRSmix, an integrative approach that combines trait-specific and cross-trait polygenic scores to improve disease prediction. I study how PRS interacts with clinical risk factors and how to make these tools work better across ancestries.

Single-Cell Genomics & Disease – I leverage large-scale single-cell ATAC-seq and RNA-seq data (1M+ cells) to map disease-relevant cell types and understand gene regulation at cellular resolution. This work connects GWAS signals to specific cell populations in the brain, cardiovascular system, and beyond.

Causal Inference in Genomics – Using Mendelian Randomization, Bayesian networks, and multi-omics integration (proteomics, metabolomics, transcriptomics), I investigate causal pathways underlying cardiovascular disease, preeclampsia, obesity, and cancer.

Selected Publications

* Equal contribution; + Co-corresponding

  1. Truong, B. et al. Integrative polygenic risk score improves the prediction accuracy of complex traits and diseases. Cell Genomics (2024). DOI

  2. Honigberg, M.C., Truong, B.* et al. Polygenic prediction of preeclampsia and gestational hypertension. Nature Medicine (2023). DOI

  3. Truong, B. et al. Modification of coronary artery disease clinical risk factors by coronary artery disease polygenic risk score. Med (2024). DOI

  4. Kim, S.+, Truong, B.+ et al. Leveraging single-cell ATAC-seq and RNA-seq to identify disease-critical fetal and adult brain cell types. Nature Communications (2024). DOI

  5. Truong, B. et al. Efficient polygenic risk scores for biobank scale data by exploiting phenotypes from inferred relatives. Nature Communications (2020). DOI

  6. Misra, A., Truong, B. et al. Instability of high polygenic risk classification and mitigation by integrative scoring. Nature Communications (2025). DOI

  7. Ardissino, M., Truong, B.* et al. Proteome- and transcriptome-wide genetic analysis identifies biological pathways and candidate drug targets for preeclampsia. Circ: Genomic and Precision Medicine (2024). DOI

  8. Schuermans, A., Truong, B. et al. Genetic associations of circulating cardiovascular proteins with gestational hypertension and preeclampsia. JAMA Cardiology (2024). DOI

Full list on Google Scholar

Highlights