The Potential of Omics Technologies in Lyme Disease Biomarker Discovery and Early Detection

Abstract

Lyme borreliosis (LB) is the most prevalent arthropod-borne infectious disease in North America and many countries of the temperate Northern Hemisphere. It is associated with local and systemic manifestations and has persistent post-treatment health complications in some individuals. Innate and acquired immunity-related inflammation is likely to play a critical role in both host defense against Borrelia burgdorferi and disease severity. Large-scale analytical approaches to quantify gene expression (transcriptomics), proteins (proteomics) and metabolites (metabolomics) in LB have recently emerged with a potential to advance the development of disease biomarkers in early, disseminated and posttreatment disease stages. These technologies may permit defining the disease stage and facilitate its early detection to improve diagnosis. They will also likely allow elucidating the underlying molecular pathways to aid in identifying molecular targets for therapy. This article reviews the findings within the field of omics relevant to LB and its prospective utility in developing an array of biomarkers that can be employed in LB diagnosis and detection particularly at the early disease stages.

Keywords: Biomarkers; Diagnosis; Inflammation; Innate immunity; Lyme disease; Omics.

Fig. 1

Heat map of pathways modified at the early stages of Lyme disease [70]. Pathways found to be up- or downregulated at Lyme disease diagnosis (stage I) and 3 weeks post-treatment with a standard course of antibiotics (stage II). Levels of change and the corresponding color scheme were extrapolated from the reported z-scores. Based on the level of change (z-scores) of stage I, the 78 modulated pathways were rearranged into four categories: z-score = −5.0 to 0.5 (panel a), 0.5–1.5 (panel b), 1.5–2.5 (panel c) and 2.5–5.0 (panel d). Data were inferred from the supplementary materials of the original study [70]

Fig. 2

Differentially expressed gene transcripts in response to B. burgdorferi [76]. The selected ones are the top 50 downregulated (upper panel) or upregulated (lower panel) gene transcripts. Genes were considered to be differentially expressed when exhibiting ≥2-fold change, compared with unstimulated cells. Mouse macrophages were treated with live B. burgdorferi for 4 h. Data were extrapolated from the supplementary materials of the original study [76]

Fig. 3

Molecular features assigned putative chemical structures for the metabolic biosignature of Lyme disease [14]. The molecular features were assigned according to the number of chemical pathways related to each molecular feature. Data were extrapolated from the supplementary materials of the original study [14]

Fig. 4

Percentage of Lyme disease patients with modified levels of inflammatory markers compared to healthy controls [12]. Data were calculated as the percentage of subjects above or below the average level of the given inflammatory marker by determining the fold change in each Lyme disease patient (n = 44) and healthy controls (n = 23). Data were extrapolated by image analysis of the heat map presenting the levels of immune mediators in the original article [12]