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July 30, 2018

Tool of the trade: researcher applies artificial intelligence to uncover causes, risks for disease

By Sharon Rosen

Manolis Kellis, Ph.D.

Some diseases, such as certain breast and colon cancers, are linked to genetic mutations passed down in families. But for many other diseases there are no direct genetic links that explain why the disease develops. That’s why Manolis Kellis, Ph.D. and his team are using artificial intelligence to uncover the hidden cause of disease.

Dr. Kellis will discuss his team’s landmark research in combining computational models and experimental techniques to help analyze genomic, epigenomic and health care data at this year’s Individualizing Medicine Conference: Advancing Care through Genomics. His plenary presentation will highlight how his approach can identify epigenomic factors, which are elements in the human genome and associated proteins involved in regulating gene activity, and how these elements respond to environmental factors to control genes. He’ll also highlight how these environmental influences can be revealed by analyzing patients’ electronic medical record.

Dr. Kellis, a computational biologist at Massachusetts Institute of Technology (MIT) and the Broad Institute, and his team have developed computer models to sift through large amounts of genomic, biological and health care data to identify mechanisms driving disease. They’ve already made great strides, identifying underlying factors leading to obesity, heart disease, cancer, psychological disorders and Alzheimer’s disease. Dr. Kellis’ computational model that enables the systematic discovery of functional elements of the genome and the functions of noncoding genetic variants is now a tool of the trade, used widely to define disease processes and predict disease risk.

Defining the “dark matter” of the genome to uncover disease risk

Tamas Ordog, M.D.

Dr. Kellis and his team have helped define what is often called the “dark matter” of the genome — large regions between genes, which contain 93 percent of disease-associated genetic variants. Investigators have been puzzled for a long time about what underlying mechanisms mediate the effects of genetic variations on disease risk.  Thanks to the work of Dr. Kellis and his colleagues, we now have a better understanding of how these variants modify the regulation of gene expression by biological and environmental signals and affect the development and course of human disease.

“Dr. Kellis’ landmark research has helped define what was previously unknown — the function of the vast amount of DNA material that exists outside of known genes. His work has helped reveal mechanisms that cause disease and predict where in the body disease may develop. This information will be invaluable to researchers working to develop tests to identify which patients are at risk for specific diseases, allowing earlier diagnose and treatment,” says Tamas Ordog, M.D., director, Mayo Clinic Center for Individualized Medicine Epigenomics Program.

Personalizing the search – adding clinical data to identify individualized treatments

Dr. Kellis and his team are now refining their model by adding clinical information from electronic health records to advance personalized care for patients.

“We’re excited to be collaborating with Dr. Kellis and his team as they refine their model to identify individualized treatments for patients. To date, Dr. Kellis’ approach has successfully integrated multiple layers of epigenomic data and genetic information to better understand disease. By adding patients’ clinical information, he and his team are accelerating the search for more personalized approaches to treating many diseases,” says Dr. Ordog.

Dr. Kellis directs the MIT Computational Biology Group. He has helped lead several large-scale genomics projects, including the National Institutes of Health Roadmap Epigenomics project, the comparative analysis of 29 mammals, the Encyclopedia of DNA Elements (ENCODE) project, and the Genotype Tissue-Expression (GTEx) project. Dr. Kellis has also received several awards for his work, including the US Presidential Early Career Award in Science and Engineering (PECASE), the NSF CAREER award, and the Alfred P. Sloan Fellowship.

Join us at the conference

Mayo Clinic Center for Individualized Medicine is hosting the Individualizing Medicine Conference on Sept. 12-13, 2018.  The conference brings together experts from Mayo Clinic and around the world to discuss how the latest discoveries in precision medicine can be applied to improve patient care.

 

Tags: #CIMCon18, #computational genetics, #Dr. Manolis Kellis, #Dr. Tamas Ordog, #Individualizing Medicine 2018, #Massachusetts Institute of Technology, #mathematical models, #Mayo Clinic Center for Individualized Medicine Epigenomics Program, #MIT Computational Biology Group, #obesity, Alzheimer’s disease, Cancer, center for individualized medicine, Epigenomics, Heart Disease, mayo clinic, medical research, Precision Medicine

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