Predicting Disease — Using Big Data for Precision Medicine

Predicting Disease — Using Big Data for Precision Medicine

Knowledge is power.  Joseph Shieh MD, PhD and his colleagues are developing new tools to leverage big data for precision medicine. In their recent studies, Dr. Shieh, a genomics physician at UCSF, and colleagues Xiaoyan Ge, PhD and Pui-Yan Kwok MD, PhD teamed up to produce practical tools for healthcare application.

“We’re using smart tools to predict disease by analyzing vast amounts of genetic sequence data,” said Dr. Shieh. Building on a foundation from human genome projects and global population sequencing efforts, the team from UCSF set out to examine thousands of human protein-encoding genes for disease-prediction patterns. Science has deciphered a fraction of the genes that affect health, but with exome technologies advancing, Shieh and his colleagues have developed new predictive tools to analyze variation patterns in thousands of genes. Remarkably, they found genes on the X-chromosome, a sex chromosome, are highly influential in early-onset diseases and harbor many novel disease markers useful for disease prediction. Paper

“The power of informatics and genetics to predict human disease is remarkable,” Ge, a post-doctoral fellow with Dr. Shieh, stated. The team would like to expand the work and use of smart tools to revolutionize care in settings such as the UCSF Genomics Clinic, where Dr. Shieh sees his patients. “There are more than twenty thousand genes in the genome and we can now decode that genetic information, but we need to leverage the knowledge for patients,” Shieh remarked. “These efforts forward care for undiagnosed disease patients, and we should also advance children’s health, preterm birth studies, and preventive care in adults using this collective knowledge.”

Paper Abstract | Joseph Shieh | Pui-Yan Kwok | IHG Genomics Tools
UCSF Genetics CareBenioff Children’s Hospital | NIH

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