Precision Medicine Vision

Precision medicine is medical diagnosis, prevention and treatment based on an individual’s variation in genes, environment, and lifestyle. Knowledge of an individual’s personal genome allows us to make informed decisions about the best medical care available, for that person. From fundamental discoveries to the clinic, Columbia... Read more

CUMC Project Adds Patient DNA Data to Electronic Health Records

Friday, December 4, 2015

As part of a nationwide NIH research program, a group of CUMC researchers will begin incorporating genomic information into electronic health records of thousands of CUMC patients. The project will help researchers learn the best way to individualize medical care for patients based on their unique genomic profile.

The project is part of the Electronic Medical Records and Genomics (eMERGE) program administered by the National Human Genome Research Institute. The primary goal of the eMERGE Network, established in 2007, is to combine genetic data with electronic medical record systems to gain new insights into the genetic basis of disease and improve diagnosis, disease risk assessment, preventive strategies, and treatment options for a broad range of conditions.

The initiative is led by Chunhua Weng, PhD, George Hripcsak, MD, and Ali Gharavi, MD, and will be conducted by a 12-member team with expertise in biomedical informatics, systems biology, clinical genetics, data science, pharmacology, public health, and bioethics.

“We expect that the solutions we develop and knowledge gained will be broadly applicable around the country,” says Dr. Hripcsak. “In the end, these solutions could translate into better-informed decisions regarding choices of treatment or screening procedures to improve clinical outcomes for patients.”

To integrate electronic health records with genetic data, the researchers will tap into their database of DNA sequences from an ethnically diverse group of more than 3,000 CUMC patients, including residents of Washington Heights, and combine these data with the databases of 80,000 patients from other eMERGE institutions.

They will then look for new disease-causing variations in about 100 genes that have already been linked to a wide range of diseases, including cancer, cardiovascular disease, stroke, and kidney disease. Previously identified variations in most of these genes have a high likelihood of causing potentially fatal conditions that can be treated to prevent death and disability if recognized.

By combining information about a patient’s symptoms from the electronic medical record with information about the genetic variations, the researchers will determine if the mutations are linked to symptoms of these conditions or possibly entirely different diseases. The research could potentially reveal new associations between these genes and diseases in humans.

“These results, which will then be incorporated back into each patient’s electronic health record, will provide clinicians with detailed genetic information that could improve diagnosis and disease risk assessment for patients, paving the way for prompt and personalized interventions to prevent or treat a range of diseases,” says Dr. Weng.

The researchers will look for both rare and common genetic variations, but the focus of the newest phase of eMERGE is on the rare variants. “It has been challenging to determine which rare variants are associated with disease, because this analysis requires very large populations from multiple ethnicities,” Dr. Gharavi says. “By aggregating results among the different eMERGE sites, and by using sophisticated computational algorithms, we can reveal hard-to-detect associations between mutations and disease.”

Columbia’s recently established Institute for Genomic Medicine, led by eMERGE co-investigator David Goldstein, PhD, is a key partner in recruitment and analysis.

Columbia’s eMERGE team also will examine how results should be shared with patients and care providers. Investigators led by Wendy Chung, MD, PhD, will develop individualized educational materials for patients and online surveys to assess their preferences for, and responses to, returned results. They also will add a clinical decision-support system to the electronic medical record that will automatically screen patients for potentially life-threatening mutations and send alerts and relevant educational materials to their physicians.

The researchers expect to start returning their results to patients in two years.

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