Global Transcriptome Analysis Identifies a Diagnostic Signature for Early Disseminated Lyme Disease and Its Resolution

Symptoms after Lyme disease: What's past is prologue

Protracted fatigue and other symptoms can occur after Lyme disease and other infections, with numerous possible drivers. Studies on posttreatment Lyme disease have been inconclusive, with no confirmed biomarker emerging. Prolonged antibiotic therapy provides no benefit. Thus, a holistic approach toward understanding and treating this complex disease is necessary.

Insights From Omics in Lyme Disease

Lyme disease is a zoonotic infection due to Ixodes tick-transmitted Borrelia burgdorferi sensu lato spirochetes and the most common vector-borne disease in the Northern Hemisphere. Despite nearly 50 years of investigation, the pathogenesis of this infection and its 2 main adverse outcomes-postinfectious Lyme arthritis and posttreatment Lyme disease syndrome-are incompletely understood. Advancement in sequencing and mass spectrometry have led to the rapid expansion of high-throughput omics technologies, including transcriptomics, metabolomics, and proteomics, which are now being applied to human diseases. This review summarizes findings of omics studies conducted on blood and tissue samples of people with acute Lyme disease and its postinfectious outcomes.

Protocol for a longitudinal cohort study of Lyme disease with physical, mental and immunological assessment

INTRODUCTION

There are limited data on the longitudinal impact of Lyme disease. Predictors of recovery have not been fully established using validated data collection instruments. There are sparse data on the immunological response to infection over time.

METHODS AND ANALYSIS

This study is a longitudinal cohort study that will recruit 120 participants with Lyme disease in Ontario and Nova Scotia, Canada, with follow-up for up to 24 months. Data will be collected using the Short-Form 36 physical and mental component summaries, Depression and Anxiety Severity Scale Questionnaire, Fatigue Severity Scale and a battery of neuropsychological tests. Mononuclear cells, gene expression and cytokine profiling from blood samples will be used to assess immunological response. Analyses will include the use of non-linear mixed-effects modelling and proportional hazards models.

ETHICS AND DISSEMINATION

Ethics approval has been obtained from ethics boards at McMaster University (Hamilton Integrated Research Ethics Board) (7564), Queens University (EMD 315-20) and Nova Scotia Health Research Ethics Board (1027173), and the study is enrolling participants. Written informed consent is obtained from all participants. The results will be disseminated by publication in a peer-reviewed journal and presented at a relevant conference. A brief report will be provided to decision-makers and patient groups.

Lyme borreliosis diagnosis: state of the art of improvements and innovations

With almost 700 000 estimated cases each year in the United States and Europe, Lyme borreliosis (LB), also called Lyme disease, is the most common tick-borne illness in the world. Transmitted by ticks of the genus Ixodes and caused by bacteria Borrelia burgdorferi sensu lato, LB occurs with various symptoms, such as erythema migrans, which is characteristic, whereas others involve blurred clinical features such as fatigue, headaches, arthralgia, and myalgia. The diagnosis of Lyme borreliosis, based on a standard two-tiered serology, is the subject of many debates and controversies, since it relies on an indirect approach which suffers from a low sensitivity depending on the stage of the disease. Above all, early detection of the disease raises some issues. Inappropriate diagnosis of Lyme borreliosis leads to therapeutic wandering, inducing potential chronic infection with a strong antibody response that fails to clear the infection. Early and proper detection of Lyme disease is essential to propose an adequate treatment to patients and avoid the persistence of the pathogen. This review presents the available tests, with an emphasis on the improvements of the current diagnosis, the innovative methods and ideas which, ultimately, will allow more precise detection of LB.

Longitudinal transcriptional analysis of peripheral blood leukocytes in COVID-19 convalescent donors

BACKGROUND

SARS-CoV2 can induce a strong host immune response. Many studies have evaluated antibody response following SARS-CoV2 infections. This study investigated the immune response and T cell receptor diversity in people who had recovered from SARS-CoV2 infection (COVID-19).

METHODS

Using the nCounter platform, we compared transcriptomic profiles of 162 COVID-19 convalescent donors (CCD) and 40 healthy donors (HD). 69 of the 162 CCDs had two or more time points sampled.

RESULTS

After eliminating the effects of demographic factors, we found extensive differential gene expression up to 241 days into the convalescent period. The differentially expressed genes were involved in several pathways, including virus-host interaction, interleukin and JAK-STAT signaling, T-cell co-stimulation, and immune exhaustion. A subset of 21 CCD samples was found to be highly "perturbed," characterized by overexpression of PLAU, IL1B, NFKB1, PLEK, LCP2, IRF3, MTOR, IL18BP, RACK1, TGFB1, and others. In addition, one of the clusters, P1 (n = 8) CCD samples, showed enhanced TCR diversity in 7 VJ pairs (TRAV9.1_TCRVA_014.1, TRBV6.8_TCRVB_016.1, TRAV7_TCRVA_008.1, TRGV9_ENST00000444775.1, TRAV18_TCRVA_026.1, TRGV4_ENST00000390345.1, TRAV11_TCRVA_017.1). Multiplexed cytokine analysis revealed anomalies in SCF, SCGF-b, and MCP-1 expression in this subset.

CONCLUSIONS

Persistent alterations in inflammatory pathways and T-cell activation/exhaustion markers for months after active infection may help shed light on the pathophysiology of a prolonged post-viral syndrome observed following recovery from COVID-19 infection. Future studies may inform the ability to identify druggable targets involving these pathways to mitigate the long-term effects of COVID-19 infection.

TRIAL REGISTRATION

https://clinicaltrials.gov/ct2/show/NCT04360278 Registered April 24, 2020.

Longitudinal serum proteomics analyses identify unique and overlapping host response pathways in Lyme disease and West Nile virus infection

Advancement in proteomics methods for interrogating biological samples has helped identify disease biomarkers for early diagnostics and unravel underlying molecular mechanisms of disease. Herein, we examined the serum proteomes of 23 study participants presenting with one of two common arthropod-borne infections: Lyme disease (LD), an extracellular bacterial infection or West Nile virus infection (WNV), an intracellular viral infection. The LC/MS based serum proteomes of samples collected at the time of diagnosis and during convalescence were assessed using a depletion-based high-throughput shotgun proteomics (dHSP) pipeline as well as a non-depleting blotting-based low-throughput platform (MStern). The LC/MS integrated analyses identified host proteome responses in the acute and recovery phases shared by LD and WNV infections, as well as differentially abundant proteins that were unique to each infection. Notably, we also detected proteins that distinguished localized from disseminated LD and asymptomatic from symptomatic WNV infection. The proteins detected in both diseases with the dHSP pipeline identified unique and overlapping proteins detected with the non-depleting MStern platform, supporting the utility of both detection methods. Machine learning confirmed the use of the serum proteome to distinguish the infection from healthy control sera but could not develop discriminatory models between LD and WNV at current sample numbers. Our study is the first to compare the serum proteomes in two arthropod-borne infections and highlights the similarities in host responses even though the pathogens and the vectors themselves are different.

Gene set predictor for post-treatment Lyme disease

Lyme disease (LD) is tick-borne disease whose post-treatment sequelae are not well understood. For this study, we enrolled 152 individuals with symptoms of post-treatment LD (PTLD) to profile their peripheral blood mononuclear cells (PBMCs) with RNA sequencing (RNA-seq). Combined with RNA-seq data from 72 individuals with acute LD and 44 uninfected controls, we investigated differences in differential gene expression. We observe that most individuals with PTLD have an inflammatory signature that is distinguished from the acute LD group. By distilling gene sets from this study with gene sets from other sources, we identify a subset of genes that are highly expressed in the cohorts but are not already established as biomarkers for inflammatory response or other viral or bacterial infections. We further reduce this gene set by feature importance to establish an mRNA biomarker set capable of distinguishing healthy individuals from those with acute LD or PTLD as a candidate for translation into an LD diagnostic.

Comprehensive analyses of transcriptomes induced by Lyme spirochete infection to CNS model system

BACKGROUND

Lyme disease is a zoonotic disease caused by infection with Borrelia burgdorferi (Bb), the involvement of the nervous system in Lyme disease is usually referred to as Lyme neuroborreliosis (LNB). LNB has diverse clinical manifestations, most commonly including meningitis, Bell's palsy, and encephalitis. However, the molecular pathogenesis of neuroborreliosis is still poorly understood. Comprehensive transcriptomic analysis following Bb infection could provide new insights into the pathogenesis of LNB and may identify novel biomarkers or therapeutic targets for LNB diagnosis and treatment.

METHODS

In the present study, we pooled transcriptomic dataset of Macaca mulatta (rhesus) from our laboratory and the human astrocyte dataset GSE85143 from the Gene Expression Omnibus database to screen common differentially expressed genes (DEGs) in the Bb infection group and the control group. Functional and enrichment analyses were applied for the DEGs. Protein-Protein Interaction network, and hub genes were identified using the Search Tool for the Retrieval of Interaction Genes database and the CytoHubba plugin. Finally, mRNA expression of hub genes was validated in vitro and ex vivo from Bb infected models and normal controls by quantitative reverse transcription PCR (qRT-PCR).

RESULTS

A total of 80 upregulated DEGs and 32 downregulated DEGs were identified. Among them, 11 hub genes were selected. The pathway enrichment analyses on 11 hub genes revealed that the PI3K-Akt signaling pathway was significantly enriched. The mRNA levels of ANGPT1, TLR6, SREBF1, LDLR, TNC, and ITGA2 in U251 cells and/or rhesus brain explants by exposure to Bb were validated by qRT-PCR.

CONCLUSION

Our study suggested that TLR6, ANGPT1, LDLR, SREBF1, TNC, and ITGA may be candidate mammal biomarkers for LNB, and the TLR6/PI3K-Akt signaling pathway may play an important role in LNB pathogenesis.

Identifying platelet-derived factors as amplifiers of B. burgdorferi-induced cytokine production

Previous studies have shown that monocytes can be 'trained' or tolerized by certain stimuli to respond stronger or weaker to a secondary stimulation. Rewiring of glucose metabolism was found to be important in inducing this phenotype. As we previously found that Borrelia burgdorferi (B. burgdorferi), the causative agent of Lyme borreliosis (LB), alters glucose metabolism in monocytes, we hypothesized that this may also induce long-term changes in innate immune responses. We found that exposure to B. burgdorferi decreased cytokine production in response to the TLR4-ligand lipopolysaccharide (LPS). In addition, B. burgdorferi exposure decreased baseline levels of glycolysis, as assessed by lactate production. Using GWAS analysis, we identified a gene, microfibril-associated protein 3-like (MFAP3L) as a factor influencing lactate production after B. burgdorferi exposure. Validation experiments proved that MFAP3L affects lactate- and cytokine production following B. burgdorferi stimulation. This is mediated by functions of MFAP3L, which includes activating ERK2 and through activation of platelet degranulation. Moreover, we showed that platelets and platelet-derived factors play important roles in B. burgdorferi-induced cytokine production. Certain platelet-derived factors, such chemokine C-X-C motif ligand 7 (CXCL7) and (C-C motif) ligand 5 (CCL5), were elevated in the circulation of LB patients in comparison to healthy individuals.

A diagnostic classifier for gene expression-based identification of early Lyme disease

Background

Lyme disease is a tick-borne illness that causes an estimated 476,000 infections annually in the United States. New diagnostic tests are urgently needed, as existing antibody-based assays lack sufficient sensitivity and specificity.

Methods

Here we perform transcriptome profiling by RNA sequencing (RNA-Seq), targeted RNA-Seq, and/or machine learning-based classification of 263 peripheral blood mononuclear cell samples from 218 subjects, including 94 early Lyme disease patients, 48 uninfected control subjects, and 57 patients with other infections (influenza, bacteremia, or tuberculosis). Differentially expressed genes among the 25,278 in the reference database are selected based on ≥1.5-fold change, ≤0.05 p value, and ≤0.001 false-discovery rate cutoffs. After gene selection using a k-nearest neighbor algorithm, the comparative performance of ten different classifier models is evaluated using machine learning.

Results

We identify a 31-gene Lyme disease classifier (LDC) panel that can discriminate between early Lyme patients and controls, with 23 genes (74.2%) that have previously been described in association with clinical investigations of Lyme disease patients or in vitro cell culture and rodent studies of Borrelia burgdorferi infection. Evaluation of the LDC using an independent test set of samples from 63 subjects yields an overall sensitivity of 90.0%, specificity of 100%, and accuracy of 95.2%. The LDC test is positive in 85.7% of seronegative patients and found to persist for ≥3 weeks in 9 of 12 (75%) patients.

Conclusions

These results highlight the potential clinical utility of a gene expression classifier for diagnosis of early Lyme disease, including in patients negative by conventional serologic testing.

Borreliella burgdorferi Antimicrobial-Tolerant Persistence in Lyme Disease and Posttreatment Lyme Disease Syndromes

The annual incidence of Lyme disease, caused by tick-transmitted Borreliella burgdorferi, is estimated to be at least 476,000 cases in the United States and many more worldwide. Ten to 20% of antimicrobial-treated Lyme disease patients display posttreatment Lyme disease syndrome (PTLDS), a clinical complication whose etiology and pathogenesis remain uncertain. Autoimmunity, cross-reactivity, molecular mimicry, coinfections, and borrelial tolerance to antimicrobials/persistence have been hypothesized and studied as potential causes of PTLDS. Studies of borrelial tolerance/persistence in vitro in response to antimicrobials and experimental studies in mice and nonhuman primates, taken together with clinical reports, have revealed that B. burgdorferi becomes tolerant to antimicrobials and may sometimes persist in animals and humans after the currently recommended antimicrobial treatment. Moreover, B. burgdorferi is pleomorphic and can generate viable-but-nonculturable bacteria, states also involved in antimicrobial tolerance. The multiple regulatory pathways and structural genes involved in mediating this tolerance to antimicrobials and environmental stressors by persistence might include the stringent (rel and dksA) and host adaptation (rpoS) responses, sugar metabolism (glpD), and polypeptide transporters (opp). Application of this recently reported knowledge to clinical studies can be expected to clarify the potential role of bacterial antibacterial tolerance/persistence in Lyme disease and PTLDS.

Metabolic Response in Patients With Post-treatment Lyme Disease Symptoms/Syndrome

BACKGROUND

Post-treatment Lyme disease symptoms/syndrome (PTLDS) occurs in approximately 10% of patients with Lyme disease following antibiotic treatment. Biomarkers or specific clinical symptoms to identify patients with PTLDS do not currently exist and the PTLDS classification is based on the report of persistent, subjective symptoms for ≥6 months following antibiotic treatment for Lyme disease.

METHODS

Untargeted liquid chromatography-mass spectrometry metabolomics was used to determine longitudinal metabolic responses and biosignatures in PTLDS and clinically cured non-PTLDS Lyme patients. Evaluation of biosignatures included (1) defining altered classes of metabolites, (2) elastic net regularization to define metabolites that most strongly defined PTLDS and non-PTLDS patients at different time points, (3) changes in the longitudinal abundance of metabolites, and (4) linear discriminant analysis to evaluate robustness in a second patient cohort.

RESULTS

This study determined that observable metabolic differences exist between PTLDS and non-PTLDS patients at multiple time points. The metabolites with differential abundance included those from glycerophospholipid, bile acid, and acylcarnitine metabolism. Distinct longitudinal patterns of metabolite abundance indicated a greater metabolic variability in PTLDS versus non-PTLDS patients. Small numbers of metabolites (6 to 40) could be used to define PTLDS versus non-PTLDS patients at defined time points, and the findings were validated in a second cohort of PTLDS and non-PTLDS patients.

CONCLUSIONS

These data provide evidence that an objective metabolite-based measurement can distinguish patients with PTLDS and help understand the underlying biochemistry of PTLDS.

Optimizing use of multi-antibody assays for Lyme disease diagnosis: A bioinformatic approach

Multiple different recombinant and peptide antigens are now available for serodiagnosis of Lyme disease (LD), but optimizing test utilization remains challenging. Since 1995 the Centers for Disease Control and Prevention (CDC) has recommended a 2-tiered serologic approach consisting of a first-tier whole-cell enzyme immunoassay (EIA) for polyvalent antibodies to Borrelia burgdorferi followed by confirmation of positive or equivocal results by IgG and IgM immunoblots [standard 2-tiered (STT) approach]. Newer modified 2-tiered (MTT) approaches employ a second-tier EIA to detect antibodies to B. burgdorferi rather than immunoblotting. We applied modern bioinformatic techniques to a large public database of recombinant and peptide antigen-based immunoassays to improve testing strategy. A retrospective CDC collection of 280 LD samples and 559 controls had been tested using the STT approach as well as kinetic-EIAs for VlsE1-IgG, C6-IgG, VlsE1-IgM, and pepC10-IgM antibodies. When used individually, the cutoff for each kinetic-EIA was set to generate 99% specificity. Utilizing logistic-likelihood regression analysis and receiver operating characteristic (ROC) techniques we determined that VlsE1-IgG, C6-IgG, and pepC10-IgM antibodies each contributed significant diagnostic information; a single-tier diagnostic score (DS) was generated for each sample using a weighted linear combination of antibody levels to these 3 antigens. DS performance was then compared to the STT and to MTT models employing different combinations of kinetic-EIAs. After setting the DS cutoff to match STT specificity (99%), the DS was 22.5% more sensitive than the STT for early-acute-phase disease (95% CI: 11.8% to 32.2%), 16.0% more sensitive for early-convalescent-phase disease (95% CI: 7.2% to 24.7%), and equivalent for detection of disseminated infection. The DS was also significantly more sensitive for early-acute-phase LD than MTT models whose specificity met or exceeded 99%. Prospective validation of this single-tier diagnostic score for Lyme disease will require larger studies using a broader range of potential cross-reacting conditions.

Lyme arthritis: linking infection, inflammation and autoimmunity

Infectious agents can trigger autoimmune responses in a number of chronic inflammatory diseases. Lyme arthritis, which is caused by the tick-transmitted spirochaete Borrelia burgdorferi, is effectively treated in most patients with antibiotic therapy; however, in a subset of patients, arthritis can persist and worsen after the spirochaete has been killed (known as post-infectious Lyme arthritis). This Review details the current understanding of the pathogenetic events in Lyme arthritis, from initial infection in the skin, through infection of the joints, to post-infectious chronic inflammatory arthritis. The central feature of post-infectious Lyme arthritis is an excessive, dysregulated pro-inflammatory immune response during the infection phase that persists into the post-infectious period. This response is characterized by high amounts of IFNγ and inadequate amounts of the anti-inflammatory cytokine IL-10. The consequences of this dysregulated pro-inflammatory response in the synovium include impaired tissue repair, vascular damage, autoimmune and cytotoxic processes, and fibroblast proliferation and fibrosis. These synovial characteristics are similar to those in other chronic inflammatory arthritides, including rheumatoid arthritis. Thus, post-infectious Lyme arthritis provides a model for other chronic autoimmune or autoinflammatory arthritides in which complex immune responses can be triggered and shaped by an infectious agent in concert with host genetic factors.

Predicting Lyme Disease From Patients' Peripheral Blood Mononuclear Cells Profiled With RNA-Sequencing

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.

Systemic immune responses in patients with early localized or early disseminated Borrelia afzelii lyme borreliosis

Introduction

The role of host immune responses in the pathogenesis of borrelial dissemination in early Lyme borreliosis (LB) in the form of multiple erythema migrans (MEM) or LB‐associated symptoms is incompletely understood.

Methods

In this study, fifteen cytokine or chemokine levels, representative of innate, Th1, and Th17 immune responses, were assessed using a bead‐based Luminex multiplex assay in acute sera from 76 adult patients with skin culture‐positive Borrelia afzelii solitary erythema migrans (SEM) and 58 patients with MEM at a single‐center university hospital. Differences between the groups were tested by modeling each cytokine or chemokine concentration by means of left‐censored regression using the classic Tobit model.

Results

Mean serum cytokine or chemokine levels were low. When taking into account the proportion of patients with cytokine or chemokine concentrations below the lowest detectable limit, only levels of CXCL10 (p = .03) and CCL19 (p = .02), representatives of the Th1 immune response, differed between patients with SEM and those with MEM; however, the differences did not reach statistical significance when adjusted for multiple comparisons. In addition, we did not find differences in systemic inflammatory responses when comparing patients with and those without LB‐associated constitutional symptoms.

Conclusion

No significant differences in systemic immune responses represented by selected cytokines or chemokines in serum samples of patients with EM infected with B. afzelii suggest that systemic mediators are not pivotal in the pathogenesis of dissemination of early infection in the form of MEM or LB‐associated symptoms. Localized immune responses in the skin or other pathogenetic mechanisms may be more important in this regard.

Lyme Disease in Humans

Lyme disease (Lyme borreliosis) is a tick-borne, zoonosis of adults and children caused by genospecies of the Borrelia burgdorferi sensu lato complex. The ailment, widespread throughout the Northern Hemisphere, continues to increase globally due to multiple environmental factors, coupled with increased incursion of humans into habitats that harbor the spirochete. B. burgdorferi sensu lato is transmitted by ticks from the Ixodes ricinus complex. In North America, B. burgdorferi causes nearly all infections; in Europe, B. afzelii and B. garinii are most associated with human disease. The spirochete's unusual fragmented genome encodes a plethora of differentially expressed outer surface lipoproteins that play a seminal role in the bacterium's ability to sustain itself within its enzootic cycle and cause disease when transmitted to its incidental human host. Tissue damage and symptomatology (i.e., clinical manifestations) result from the inflammatory response elicited by the bacterium and its constituents. The deposition of spirochetes into human dermal tissue generates a local inflammatory response that manifests as erythema migrans (EM), the hallmark skin lesion. If treated appropriately and early, the prognosis is excellent. However, in untreated patients, the disease may present with a wide range of clinical manifestations, most commonly involving the central nervous system, joints, or heart. A small percentage (~10%) of patients may go on to develop a poorly defined fibromyalgia-like illness, post-treatment Lyme disease (PTLD) unresponsive to prolonged antimicrobial therapy. Below we integrate current knowledge regarding the ecologic, epidemiologic, microbiologic, and immunologic facets of Lyme disease into a conceptual framework that sheds light on the disorder that healthcare providers encounter.