Decoding the Genomics of Abdominal Aortic Aneurysm.

Authors:
Jingjing Li
Jingjing Li
Sun Yat-Sen University
China
Cuiping Pan
Cuiping Pan
Stanford Center for Genomics and Personalized Medicine
Sai Zhang
Sai Zhang
Pingjin Hospital
China
Joshua M Spin
Joshua M Spin
Stanford University School of Medicine
United States
Alicia Deng
Alicia Deng
Stanford University School of Medicine
United States
Ronald L Dalman
Ronald L Dalman
Stanford University Medical Center
United States
Philip S Tsao
Philip S Tsao
Stanford University School of Medicine
United States

Cell 2018 Sep;174(6):1361-1372.e10

Department of Genetics, Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA; Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA 94305, USA. Electronic address:

A key aspect of genomic medicine is to make individualized clinical decisions from personal genomes. We developed a machine-learning framework to integrate personal genomes and electronic health record (EHR) data and used this framework to study abdominal aortic aneurysm (AAA), a prevalent irreversible cardiovascular disease with unclear etiology. Performing whole-genome sequencing on AAA patients and controls, we demonstrated its predictive precision solely from personal genomes. By modeling personal genomes with EHRs, this framework quantitatively assessed the effectiveness of adjusting personal lifestyles given personal genome baselines, demonstrating its utility as a personal health management tool. We showed that this new framework agnostically identified genetic components involved in AAA, which were subsequently validated in human aortic tissues and in murine models. Our study presents a new framework for disease genome analysis, which can be used for both health management and understanding the biological architecture of complex diseases. VIDEO ABSTRACT.

Abstract Video

Towards Precision Medicine for Abdominal Aortic Aneurysm/Cell Sept. 6, 2018 (Vol 174, Issue 6)


Source: Cell Press

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September 2018
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