Abstract
Although widely prevalent, Lyme disease is still under-diagnosed and misunderstood. Here we followed 73 acute Lyme disease patients and uninfected controls over a period of a year. At each visit, RNA-sequencing was applied to profile patients' peripheral blood mononuclear cells in addition to extensive clinical phenotyping. Based on the projection of the RNA-seq data into lower dimensions, we observe that the cases are separated from controls, and almost all cases never return to cluster with the controls over time. Enrichment analysis of the differentially expressed genes between clusters identifies up-regulation of immune response genes. This observation is also supported by deconvolution analysis to identify the changes in cell type composition due to Lyme disease infection. Importantly, we developed several machine learning classifiers that attempt to perform various Lyme disease classifications. We show that Lyme patients can be distinguished from the controls as well as from COVID-19 patients, but classification was not successful in distinguishing those patients with early Lyme disease cases that would advance to develop post-treatment persistent symptoms.
Highlights
Lyme disease (LD) is a tick-borne illness that has become a growing concern in the United States (US) and Canada
We applied Uniform Manifold Approximation and Projection (UMAP) [19] to estimate similarities and differences between the samples, each representing a patient at a specific visit
LD cases are divided into two distinct clusters, clusters 0 and 1, with a smaller group of cases clustering with the controls in cluster 2 (Figure 1C)
Summary
Lyme disease (LD) is a tick-borne illness that has become a growing concern in the United States (US) and Canada. The disease is caused by the spirochete bacteria Borrelia burgdorferi sensu stricto and is transmitted to humans through one of the vector’s blood meals [1]. Comprising 62.6% of all vector-borne diseases, and 81.19% of all tick-borne disease, Borrelia burgdorferi sensu stricto was the most common vector-borne pathogen in the United States from 2004 to 2016 [2]. Due to the tick’s seasonal lifecycle, transmission of the pathogen and subsequent human infection occurs at higher rates in spring, summer, and the early part of autumn when the various life-stages of the vector quest for a meal [6]. Initial onset of symptoms can manifest ∼7–14 days after transmission, both earlier and later initial onset has been documented [6]
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