Georgia Institute of Technology researchers developed a novel approach to summarize disease risk, creating a score for an individual based on gene expression – transcriptional risk score (TRS). They’ve applied this score in a recent ground-breaking study, which accurately predicts complications in Crohn’s disease, and potentially paves the way for personalized medicine strategies in the future.
“We were testing an intuition,” says Urko Marigorta, lead author of the study, “Transcriptional Risk Scores link GWAS to eQTL and Predict Complications in Crohn’s Disease,” published in the journal Nature Genetics.
“We wanted to see if checking the actual expression of pathogenic genes involved in disease is better than just looking at an individual’s DNA when assessing the risk for disease,” adds Marigorta, a postdoctoral researcher in lab of Greg Gibson, professor in the School of Biological Sciences and a researcher in the Petit Institute for Bioengineering and Bioscience at Georgia Tech.
This was part of a multicenter research initiative, the Crohn’s & Colitis Foundation’s “RISK Stratification” study (the largest new-onset study of pediatric Crohn’s disease patients), and a follow-up to research published earlier this year in the journal, The Lancet.
That study, says Gibson, evaluated “whether anti-TNF treatment really is beneficial in reducing inflammation and preventing progression to complicated Crohn’s disease. It is, but apparently only for a subset of patients. Our contribution there was to show that this subset can, to some extent, be identified at diagnosis on the basis of their overall gene expression profile in the ileum.”
The Nature Genetics paper takes advantage of the data sets analyzed in the previously published research. The RISK Stratification Study involved 28 clinics and 1,800 pediatric patients – a good sample size, according to Marigorta, who adds, “most important, [we had] two forms of biological data: DNA and gene expression from the small intestine. Importantly, the gene expression from RISK was obtained at diagnosis, when kids went to the hospital and before developing complicated versions of Crohn’s disease.”
So basically, Marigorta and Gibson wanted to test their novel approach, TRS, against genetic risk scores (GRS), or scores based on an individual’s DNA, which is currently the dominant approach in the field. But predicting disease risk from just DNA is difficult.
“In the last few years we’ve learned about many genes that are associated with disease – genes that have mutations, that are more frequent in people with disease than in healthy people,” Marigorta says. “But many people with mutated genes do fine, whereas others without them end up getting sick with some disease. Most of the field is trying to discover more of these mutations, which is totally fine because that will tell us more about biology, and will make for good drug targets. But we’re not sure it will add that much in terms of prediction.”
Marigorta’s statistical and bioinformatics analyses of the genomic data demonstrated that their intuition was on target: gauging the expression of risk genes (TRS) does a better job of predicting complications of Crohn’s than just adding up the number of risk genes (GRS).
“So, instead of trying to predict how good a football team is going to be by adding up how many players make $10 million a year, we actually evaluate how well they are performing,” says Gibson, using a familiar sports analogy.
This paper published in Nature Genetics was a collaboration of 23 author/researchers from 18 institutions – two in Canada and 16 in the U.S., including Emory University’s School of Medicine. Emory physician/professor Subra Kugathasan, director of the Children’s Healthcare of Atlanta Combined Center for Pediatric Inflammatory Bowel Disease, shares senior authorship with Gibson (who was the corresponding author). Key leadership also came from co-authors Lee Denson (Cincinnati Children’s Hospital) and Jeff Hyams (Connecticut Children’s Medical Center)
Going forward, Marigorta sees two primary directions that the TRS research may take.
“We’d like to see if it works for other traits and we have evidence that it does, at least for autoimmune diseases such as juvenile arthritis,” he says. “And more importantly, we’d like to see if it works when using gene expression from blood draws. Imagine, down the road, if you could fine-tune the predictions of risk due to your DNA with information gained from looking at gene expression from a simple blood draw at your once-a-year checkup.”
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