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The Fahed Lab was well represented at this year’s American Society of Human Genetics (ASHG) Annual Meeting, held right here in Boston. Multiple members of the lab presented their work, reflecting the group’s growing impact across genetics, cardiovascular medicine, and machine learning.
Dr. Akl C. Fahed, the lab’s Principal Investigator, presented on machine learning–driven phenotyping of coronary angiography and how these methods can refine our understanding of coronary artery disease phenotypes.
Several lab members also showcased their work, highlighting the lab’s diversity of expertise and innovative approaches:
Xingyu Chen explored widespread and biologically driven sex disparities in polygenic risk prediction across complex traits.
Zhanqing Hua presented on integrating deep learning–based radiomics and genomics to define the genetic architecture of cardiac morphology and its link to cardiovascular disease.
Injeong Shim discussed integrating rare and common variant polygenic risk scores for comprehensive genetic risk assessment in familial hypercholesterolemia.
Shengxin Liang shared work on optimizing coronary artery disease polygenic risk scores for individual-level risk prediction.
Fouad Bitar presented two projects: a 25-year global bibliometric analysis of polygenic risk score research and economic modeling of polygenic risk prediction of coronary artery disease in childhood.
Yang Sui presented on improving consistency in high-risk classification across polygenic risk models using lasso-based integration.
It was an inspiring week filled with science, collaboration, and connection — and a proud moment for the Fahed Lab to see so many of its members sharing their contributions with the global genetics community.
