Researchers say they’ve identified a set of biomarkers that could make early diagnosis of Lyme disease easier, a possible first step for more effectively treating the estimated 476,000 people diagnosed with, and treated for, the tick-borne illness every year in the United States.
The scientists sequenced the RNA of 152 patients with post-treatment Lyme disease. The condition’s symptoms vary, but they can include fatigue, brain fog and pain for those who have received antibiotic treatment for Lyme disease. They compared the data with RNA sequenced from 72 patients with acute Lyme disease — earlier symptoms, such as a rash or facial paralysis — and 44 controls without the infection.
The data showed differences in gene expression in those with acute and chronic Lyme disease. Researchers further pared down the list by comparing the gene expression of those with Lyme disease with that observed in patients with other infectious diseases. Then, they used machine learning to shorten the list even further.
Now, they say they’ve identified 35 distinctive biomarkers that distinguish people with either type of Lyme disease from those without the condition. In a news release, researchers say they plan to use the biomarkers to develop a diagnostic test that could identify the condition in other patients.
A genetic test would be an improvement on current FDA-approved tests, which identify antibodies that can take weeks to emerge.
The research was conducted by scientists from the Icahn School of Medicine at Mount Sinai in New York and the Johns Hopkins University School of Medicine. Earlier this year, several of the researchers from Johns Hopkins published a study along with scientists from the University of California at San Francisco announcing that they had developed a panel of 31 biomarkers that allowed them to accurately identify Lyme disease in 95.2 percent of patients.