How EHRs are helping Vanderbilt researchers identify undiagnosed genetic diseases

Research team finds patterns of symptoms that might be caused by an underlying genetic variant.
By Bernie Monegain
03:40 PM
How EHRs are  helping Vanderbilt researchers identify undiagnosed genetic diseases

Researchers at Vanderbilt University Medical Center are looking into diagnoses, such as heart failure, stroke, infertility and kidney failure to see whether they stem from undiagnosed genetic diseases.

The researchers are probing genetic data in EHRs to identify the diseases in large populations in order to tailor treatments to the true cause of the disease.

The findings are reported in the journal Science. Researchers found that 14 percent of patients with genetic variants affecting the kidney had kidney transplants and 10 percent with another variant required liver transplants.

If their genetic cause had been diagnosed, those transplants might have been avoided, the researchers note.

"We started with a simple idea: look for a cluster of symptoms and diseases to find an undiagnosed underlying disease," Josh Denny, MD, a professor of biomedical informatics and medicine and director of the Center for Precision Medicine at Vanderbilt. “We got really excited when we saw how we could systematize it across thousands of genetic diseases to figure out the impact of millions of genetic variants," Denny added.

[Also: NIH fast-tracks genomics in clinical care with $19 million investment]

The new method, developed by Denny, Lisa Bastarache and a team of collaborators, creates a phenotype risk score to find patterns of symptoms that may be caused by an underlying genetic variant. The findings include genetic variants whose effects were not known until now.

The authors figure that many patients currently diagnosed with issues such as heart failure, stroke, infertility or kidney failure might actually be suffering from rare genetic diseases. If that underlying disease could be identified, it might have a specific treatment that would prevent the symptoms from recurring or getting worse.

The researchers employed some new data mining techniques in their work.

"What the phenotype risk score shows us is that if you start with specific combinations of symptoms, the chances of finding a potentially causative genetic variant are pretty high,” they concluded.

“This is a really important step to using clinical genotyping to assess patient risk and inform more precise prevention and treatment of common conditions," Dan Roden, MD, senior vice president for personalized medicine at Vanderbilt and co-author of the study, said in a statement.

"Phenotype risk scoring can easily be applied in any electronic medical record system that is linked to DNA," Bastarache added. "Our work looked at only a small sample of the human genome, about 6,000 variants. The opportunity for additional discoveries using this method is huge."

Twitter: @Bernie_HITN
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