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Tatonetti Heritability Image

Each subgraph in this image is a family reconstructed from EHR data: Each node represents an individual and the colors represent different health conditions. (Figure: Nicholas Tatonetti, PhD, Columbia University Vagelos College of Physicians and Surgeons).

Acne is highly heritable, passed down through families via genes, but anxiety appears more strongly linked to environmental causes, according to a new study that analyzed data from millions of electronic health records to estimate the heritability of hundreds of different traits and conditions. 

As reported by the Columbia Newsroom, the findings, published in Cell by researchers at Columbia University Irving Medical Center and NewYork-Presbyterian could streamline efforts to understand and mitigate disease risk—especially for diseases with no known disease-associated genes.

“Knowledge of a condition’s heritability—how much the condition’s variability can be attributed to genes—is essential for understanding the biological causes of the disease and for precision medicine,” says study co-leader Nicholas Tatonetti, PhD , the Herbert Irving Assistant Professor of Biomedical Informatics at Columbia University Vagelos College of Physicians and Surgeons and an assistant professor of systems biology. “It is clinically useful for estimating disease risk, customizing treatment, and tailoring patient care.”

May 7, 2018

From Code to Cure

Columbia Magazine

Published Spring 2018 cover story , Columbia Magazine

As reported by David J. Craig, senior editor at Columbia Magazine , we are living in the age of big data, and with every link we click, every message we send, and every movement we make, we generate torrents of information. In the past two years, the world has produced more than 90 percent of all the digital data that has ever been created. New technologies churn out an estimated 2.5 quintillion bytes per day. 

Today, researchers at Columbia University Irving Medical Center (CUIMC) are using the power of data to identify previously unrecognized drug side effects; they are predicting outbreaks of infectious diseases by monitoring Google search queries and social-media activity; and they are developing novel cancer treatments by using predictive analytics to model the internal dynamics of diseased cells. These ambitious projects, many of which involve large interdisciplinary teams of computer scientists, engineers, statisticians, and physicians, represent the future of academic research.

Craig covers Dr. Nicholas Tatonetti's work involving prescription drug safety and his innovative use of digital health and clinical records and Dr. Andrea Califano's unconventional computational approaches in advancing cancer research.

To read the full article , visit the online issue of Columbia Magazine

Nicholas P. Tatonetti, PhD, has recently been named director of clinical informatics at the Institute for Genomic Medicine (IGM) at Columbia University Medical Center. In this new role, he is charged with planning, organizing, directing and evaluating all clinical informatics efforts across the Institute. In particular, he will focus on the integration of electronic health record data for use in genetics and genomics studies.

Dr. Tatonetti, who is Herbert Irving Assistant Professor of Biomedical informatics with an interdisciplinary appointment in the Department of Systems Biology, specializes in advancing the application of data science in biology and health science. Researchers in his lab integrate their medical observations with systems and chemical biology models to not only explain drug effects, but also further understanding of basic biology and human disease. They focus also on integration of high throughput data capture technologies, such as next-generation genome and transcriptome sequencing, metabolomics, and proteomics, with the electronic medical record to study the complex interplay between genetics, environment, and disease.

At the Institute for Genomic Medicine, researchers are focused on innovative approaches to genomic medicine. Their multi-tiered approach to genomic medicine utilizes large scale genomic sequencing and analysis, paired with functional biology to advance the diagnosis, characterization, and treatment of genetic diseases. IGM is playing a critical role in Columbia’s overall Precision Medicine Initiative, a major University-wide effort to provide medical diagnosis, prevention and treatment based on an individual’s variation in genes, environment, and lifestyle. 

Dr. Tatonetti, who joined Columbia in 2012, is also affiliated with the Center for Computational Biology and Bioinformatics, the Department of Medicine, the Department of Biomedical Informatics, and the Center for Cancer Systems Therapeutics.