Biomarker-Based Analysis of Pain in Patients with Tick-Borne Infections before and after Antibiotic Treatment

Abstract

Tick-borne illnesses (TBIs), especially those caused by Borrelia, are increasingly prevalent worldwide. These diseases progress through stages of initial localization, early spread, and late dissemination. The final stage often leads to post-treatment Lyme disease syndrome (PTLDS) or chronic Lyme disease (CLD), characterized by persistent and non-specific multisystem symptoms affecting multiple systems, lasting over six months after antibiotic therapy. PTLDS significantly reduces functional ability, with 82-96% of patients experiencing pain, including arthritis, arthralgia, and myalgia. Inflammatory markers like CRP and TNF-alpha indicate ongoing inflammation, but the link between chronic pain and other biomarkers is underexplored. This study examined the relationship between pain and biomarkers in TBI patients from an Irish hospital and their response to antibiotic treatment. Pain ratings significantly decreased after antibiotic treatment, with median pain scores dropping from 7 to 5 (U = 27215.50, p < 0.001). This suggests a persistent infection responsive to antibiotics. Age and gender did not influence pain ratings before and after treatment. The study found correlations between pain ratings and biomarkers such as transferrin, CD4%, platelets, and neutrophils. However, variations in these biomarkers did not significantly predict pain changes when considering biomarkers outside the study. These findings imply that included biomarkers do not directly predict pain changes, possibly indicating allostatic load in symptom variability among long-term TBI patients. The study emphasizes the need for appropriate antibiotic treatment for TBIs, highlighting human rights issues related to withholding pain relief.

Keywords: Lyme disease; chronic Lyme disease; pain; post-treatment Lyme disease syndrome; tick-borne disease.

Figure 1

Age and gender do not influence pain ratings at time points T0 and T2. The charts in panels (A,B) show the overall distribution of age and gender in the study. Panels (C,D) show the distribution of pain ratings across different ages and genders, respectively, at time points T0 and T2.

Figure 2

The pain ratings have significantly decreased from time point T0 to T2. Panel (A) displays the pain ratings recorded at these time points. Panel (B) illustrates a boxplot showing a decrease in the median pain ratings from T0 to T2. The statistical analysis from the Mann–Whitney U test is also included in this panel. Panel (C) presents the empirical distribution function (ECDF) of pain ratings at T0 and T2, including the results from the Kolmogorov–Smirnov (K-S) test.

Figure 3

The median transferrin levels are consistently lower at time point T2 across all pain ratings, with notable decreases observed, particularly from pain ratings 6 to 9. The panel compares the median values at time points T0 and T2 for (A) transferrin, (B) CD4%, (C) platelets, (D) neutrophils, and (E) transferrin saturation %. Green stars on the x-axis indicate the pain ratings where differences in median values were statistically significant (p-value ≤ 0.05). For a detailed statistical analysis, refer to Table S1.

Figure 4

Temporal analysis reveals correlations between pain ratings and biomarkers (transferrin, CD4%, platelets, neutrophils, transferrin saturation %), suggesting external influences on pain perception. The panel displays cluster maps at time points: (A) before treatment (T0) and (B) after treatment (T2). Each map features a top dendrogram that clusters the pain ratings with biomarkers and a left dendrogram that groups patients based on their similarities. Blue and red colors within each cluster map denote lower and higher values, respectively. For detailed Euclidean distances of individual pain ratings, refer to Figure S4.