Genetic profiling of Lyme disease could bring new therapeutic targets 

Tick bite

Researchers have identified 35 genes associated with long-term Lyme disease that could potentially be used as biomarkers to diagnose patients with the condition. 

The findings, from the Icahn School of Medicine at Mount Sinai in New York and published in the journal Cell Reports Medicine, may also lead to new therapeutic targets. The study is the first to use transcriptomics as a blood test to measure RNA levels in patients with long-term Lyme disease.  

Lyme disease is a tick-borne illness that is not well understood. Approximately 30,000 diagnosed cases are reported to the CDC each year, but the estimated real number is closer to 476,000 cases, carrying an annual healthcare cost of about $1 billion in the United States.  

While most patients are diagnosed and treated with antibiotics at the earliest stages of Lyme disease, about 20% develop long-term complications, which could include arthritis, neurologic symptoms, and/or heart problems. 

“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 Avi Ma’ayan, Professor, Pharmacological Sciences, and Director of the Mount Sinai Center for Bioinformatics at Icahn Mount Sinai, and senior author of the paper. 

Distinctive inflammatory signature 

As part of the study, RNA sequencing was conducted using blood samples from 152 patients with symptoms of post-treatment Lyme disease to measure their immune response.  

Combined with RNA sequencing data from 72 patients with acute Lyme disease and 44 uninfected controls, the investigators found that most of the post-treatment Lyme disease patients had a distinctive inflammatory signature compared with the acute Lyme disease group. 

The researchers also identified a subset of genes that were highly expressed but have not been previously established for this Lyme-associated inflammatory response. 

Value of omics technologies 

Using machine learning, the researchers further reduced the group of genes to establish an mRNA biomarker set capable of distinguishing healthy patients from those with acute or post-treatment Lyme disease. 

“We should not underestimate the value of using omics technologies, including transcriptomics, to measure RNA levels to detect the presence of many complex diseases, like Lyme disease. 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.    

 

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