New Research from Johns Hopkins Will Promote Hospitals' Ability to Utilize Precision Medicine

Using computer learning to analyze genetic variations leads to important results impacting hospitals that utilize precision medicine

New research from Johns Hopkins University has resulted in promising information that is crucial for identifying rare genetic variations between individuals. There are many variations in the genetics of every individual person, and some of these variations can be quite rare. With genetic science still in its early days, the significance and implications of these many variations are only just beginning to be understood, but they hold the potential to offer individualized diagnoses and treatments. Finding these rare variations can, however, be quite difficult.

Research led by Alexis Battle, PhD, at Johns Hopkins University applies computer science to the genetic concepts that are the foundation of precision medicine. Battle is an Associate Professor of Biomedical Engineering and Computer Science and is a leading member of the National Institutes of Health's (NIH) Genotype-Tissue Expression (GTEx) Consortium.

Battle Laboratory: Unique Computational System at Work

Battle's laboratory has developed a unique computational system, called "Watershed." This program analyzes genetic data and gene expression to predict how variants from a specific individual's genome will function. The predictions were validated then applied to large gene collection, helping to yield further results on what rare genetic variations may be impacting human traits.

Alexis Battle, PhD (above), is a 2016 Searle Scholar and an Associate Professor of Biomedical Engineering and Computer Science at Johns Hopkins University. Battle's research is concentrated on the development of computational biology tools and machine-learning strategies to examine genetic differences on gene regulation and disease. (Photo source: Johns Hopkins University)

"The implications of this could be quite large. Everyone has around 50,000 variants that are rare in the population and we have absolutely no idea what most of them are doing," Battle said in a recent article published at ScienceDaily. "If you collect gene expression data, which shows which proteins are being produced in a patient's cells at what levels, we're going to be able to identify what's going on at a much higher rate.

"We really don't know how many people are out there walking around with a genetic aberration that is causing them health issues," Battle explained. "They go completely undiagnosed, meaning we cannot find the genetic cause of their problems."

Area of Focus: Non-Coding Parts of the Genome

Battle's work has focused on rare genetic variations that affect the "non-coding" parts of the genome that do not specifically encode a protein. These parts are often not tested in the field of personalized genomics, even though genetic variations of these areas can lead to effects in humans.

"Any improvement we can make in this area has implications for public health," Battle said. "Even pointing to what the genetic cause is gives parents and patients a huge sense of relief and understanding and can point to potential therapeutics."

Ultimately, Battle's work shows that the standard practices for collecting genetic information should be expanded. There are many genetic causes for disorders that go undetected but could be recognized if the scope of existing methods of genetic collection was widened to include variants identified by Battle's lab, for example.

As precision medicine becomes the leading edge of progress, hospitals will play an increasingly important role in collecting and applying the genetic information of their patients. While genetic testing is often viewed as a somewhat homogenous term, hospital administrators should be aware that the scope of genetic testing can vary significantly, based on how much of the genome it analyzes. 

Battle's research provides improved guidance on how the scope of genetic testing programs should be expanded to achieve the greatest good for the largest number of patients.

-Caleb Williams

Related Information: 

Alexis Battle, PhD

Battle Lab

New genetic analysis method could advance personal genomics

The GTEx Consortium atlas of genetic regulatory effects across human tissues

Snapshot: Genotype Tissue Expression Consortium