Lyme disease is caused by a bacterium called Borrelia burgdorferi, which is transmitted by tick bites. The incidence of Lyme disease has been increasing steadily, in part because diagnosis is improving, but also because the range of ticks that spread the disease is expanding. There is still a lot we don't know about Lyme disease, including how to treat it. But diagnosis may get easier soon, now that researchers have identified 35 genes that are more active in people with a long-term form of the disease; the genes could be useful in Lyme disease diagnostics. These genes may also aid in the development of therapeutics for Lyme. The findings have been outlined in Cell Reports Medicine.
While about 30,000 people are diagnosed with Lyme disease in the United States every year, the true number could be as high as 476,000, according to the Centers for Disease Control and Prevention. People who are diagnosed can be treated with antibiotics, but about 20 percent of patients will go on to develop long-term complications that can affect the neurological system, cause arthritis, or heart problems.
There is a major need for better tests for Lyme disease, and this work is the first to look for transcriptional changes associated with long-term cases.
"We wanted to understand whether there is a specific immune response that can be detected in the blood of patients with long-term Lyme disease to develop better diagnostics for this debilitating disease," said senior study author Avi Ma'ayan, Ph.D., a Professor and Director of the Mount Sinai Center for Bioinformatics at Icahn Mount Sinai.
In this study, the researchers sequenced the RNA in blood samples from 152 patients with post-treatment Lyme disease symptoms, 72 patient with acute Lyme disease, and 44 uninfected individuals. That RNA can provide a snapshot of how active the patient's genes were (in the blood) at the time the blood was drawn. The researchers were particularly interested in genes related to the immune response.
This revealed that there was a unique inflammatory pattern in the post-treatment Lyme disease patients compared to those with acute Lyme disease. Within that group of inflammatory genes, there were some that were expressed in a way that is different from other patterns caused by infections with other pathogens. Machine learning was used to create a set of mRNA biomarkers that can differentiate between healthy people, those with post-treatment Lyme disease, or acute Lyme disease. This highly expressed subset of genes has been found before, and could be used to diagnose Lyme disease, as well as which stage it is.
"A diagnostic for Lyme disease may not be a panacea but could represent meaningful progress toward a more reliable diagnosis and, as a result, potentially better management of this disease," said Dr. Ma'ayan.
The investigators want to repeat the study with other samples, develop a diagnostic tool, and test it with patient samples. They are also interested in using machine learning to find ways to diagnose other challenging disorders.
A vaccine for Lyme disease is also being tested, as outlined in the video.
