I am a psychiatric epidemiologist with a broad range of research skills encompassing study design, causal inference, statistical genetics, population-based surveys, and real-world evidence studies.
My interdisciplinary approach and extensive experience with diverse datasets, including longitudinal cohort data, electronic health records, and population-based surveys, have been instrumental in contributing to ongoing national and international collaborative consortia, such as PsycheMERGE and the International Hundred K+ Cohort Consortium.
Recently, I have focused on applying causal inference methods and machine learning techniques to investigate and mitigate selection bias in large-scale biobank studies. In addition, I serve as the lead analyst in multiple NIH-funded projects involving the Mass General Brigham Biobank and the NIH All of Us Research Program. These projects capitalize on the wealth of data available in these biobanks to investigate the genetic and environmental factors contributing to psychiatric disorders on a large scale.
By integrating high-dimensional electronic health records, genomic data, and advanced statistical techniques, I aim to uncover the intricate interplay between genetics, clinical characteristics, and environmental influences in shaping the risk and progression of mental health conditions, and to discover actionable insights for prevention, diagnosis, and personalized treatment of psychiatric disorders.
My interdisciplinary approach and extensive experience with diverse datasets, including longitudinal cohort data, electronic health records, and population-based surveys, have been instrumental in contributing to ongoing national and international collaborative consortia, such as PsycheMERGE and the International Hundred K+ Cohort Consortium.
Recently, I have focused on applying causal inference methods and machine learning techniques to investigate and mitigate selection bias in large-scale biobank studies. In addition, I serve as the lead analyst in multiple NIH-funded projects involving the Mass General Brigham Biobank and the NIH All of Us Research Program. These projects capitalize on the wealth of data available in these biobanks to investigate the genetic and environmental factors contributing to psychiatric disorders on a large scale.
By integrating high-dimensional electronic health records, genomic data, and advanced statistical techniques, I aim to uncover the intricate interplay between genetics, clinical characteristics, and environmental influences in shaping the risk and progression of mental health conditions, and to discover actionable insights for prevention, diagnosis, and personalized treatment of psychiatric disorders.
Recent Publications
Justin D. Tubbs, T. Mallard, Maria Dalby, Yunxuan Jiang, Y. Lee, Karmel W Choi, Tian Ge, Niels Plath, L. Hammer-Helmich, J. Granka, A. Grotzinger, David Hinds, Jordan W Smoller, Joshua W. Buckholtz
medRxiv, 2025
Uncovering Genetic Risk Beyond Diagnoses in Suicidal Thoughts and Behaviors: Insights from All of Us
Phil H Lee, Brandon T. Sanzo, Y. Lee, Daniel H. Jung, Jodi M. Gilman, Matthew K. Nock, J. Smoller, Richard T. Liu, Ronald C Kessler
medRxiv, 2025
Y. Lee, Yingzhe Zhang, Ana Lucia Espinosa Dice, Josephine H. Li, J. Tubbs, Yen-Chen Anne Feng, Tian Ge, A. Maihofer, C. Nievergelt, J. Smoller, K. Koenen, Andrea L. Roberts, Natalie Slopen
medRxiv, 2025
Genetic architecture and socio-environmental risk factors for major depressive disorder in Nepal.
Karmel W Choi, J. Tubbs, Y. Lee, Yixuan He, K. Tsuo, Mary T Yohannes, Lethukuthula L Nkambule, Emily M. Madsen, Dirgha J. Ghimire, Sabrina Hermosilla, Tian Ge, Alicia R. Martin, W. Axinn, Jordan W Smoller
Psychological Medicine, 2024
Examining the Genetic Links between Clusters of Immune-mediated Diseases and Psychiatric Disorders
S. Breunig, Y. Lee, Elizabeth Karlson, Arjun Krishnan, J. M. Lawrence, L. S. Schaffer, A. Grotzinger
medRxiv, 2024
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