Challenges in the Diagnosis and Treatment of Lyme Disease

A Comprehensive Review of Lyme Disease: A Focus on Cardiovascular Manifestations

Lyme disease is a tick-borne illness known for its ability to cause multi-systemic manifestations. It can affect several different systems, including neurological, musculoskeletal, and dermatological systems. However, one of the most concerning biological systems affected is the cardiac system. Lyme carditis typically presents with varying degrees of atrioventricular (AV) block. Additionally, current literature also endorses atypical manifestations, including but not limited to atrial fibrillation and bundle branch blocks. These atypical manifestations are important as they can be the first presenting symptoms in patients with Lyme disease. Therefore, educating clinicians on various signs, symptoms, and manifestations of Lyme carditis remains paramount in reducing morbidity and mortality. We conducted a literature review using PubMed, MEDLINE, and CINAHL, collecting a total of 13 articles to gather information on atypical manifestations of Lyme carditis. This literature review serves to summarize the current research and studies describing these cardiac manifestations and the cardiac pathophysiology associated with Lyme disease. These findings aim to contribute to the expanding understanding of Lyme carditis, subsequently preventing long-term effects through prompt diagnosis and treatment.

Prevalence of Powassan Virus Seropositivity Among People with History of Lyme Disease and Non-Lyme Community Controls in the Northeastern United States

Introduction: Lyme disease (LD) affects ∼476,000 people each year in the United States. Symptoms are variable and include rash and flu-like symptoms. Reasons for the wide variation in disease outcomes are unknown. Powassan virus (POWV) is a tick-borne flavivirus that causes disease ranging from asymptomatic infection to encephalitis, neurologic damage, and death. POWV and LD geographic case distributions overlap, with Ixodes species ticks as the common vectors. Clinical ramifications of coinfection or sequential infection are unknown. Objectives: This study's primary objective was to determine the prevalence of POWV-reactive antibodies in sera samples collected from previously studied cohorts of individuals with self-reported LD history residing in the Northeastern United States. As a secondary objective, we studied clinical differences between people with self-reported LD history and low versus high POWV antibody levels. Methods: We used an enzyme-linked immunosorbent assay (ELISA) to quantify IgG directed at the POWV envelope (E) protein domain III in 538 samples from individuals with self-reported LD history and 16 community controls. The samples were also tested with an ELISA assay to quantify IgG directed at the POWV NS1 protein. Results: The percentage of individuals with LD history and possible evidence of POWV exposure varied depending on the assay utilized. We found no significant difference in clinical symptoms between those with low or high POWV IgG levels in the in-house assay. Congruence of the EDIII and NS1 assays was low with only 12% of those positive in the in-house EDIII ELISA testing positive in the POWV NS1 ELISA. Conclusions: The results highlight the difficulty in flavivirus diagnostic testing, particularly in the retrospective detection of flavivirus exposure. The findings suggest that a prospective study with symptomatic patients using approved clinical testing is necessary to address the incidence and clinical implications of LD and POWV co-infection or sequential infection.

Screening Marine Microbial Metabolites as Promising Inhibitors of Borrelia garinii: A Structural Docking Approach towards Developing Novel Lyme Disease Treatment

Lyme disease caused by the Borrelia species is a growing health concern in many parts of the world. Current treatments for the disease may have side effects, and there is also a need for new therapies that can selectively target the bacteria. Pathogens responsible for Lyme disease include B. burgdorferi, B. afzelii, and B. garinii. In this study, we employed structural docking-based screening to identify potential lead-like inhibitors against the bacterium. We first identified the core essential genome fraction of the bacterium, using 37 strains. Later, we screened a library of lead-like marine microbial metabolites (n = 4730) against the arginine deiminase (ADI) protein of Borrelia garinii. This protein plays a crucial role in the survival of the bacteria, and inhibiting it can kill the bacterium. The prioritized lead compounds demonstrating favorable binding energies and interactions with the active site of ADI were then evaluated for their drug-like and pharmacokinetic parameters to assess their suitability for development as drugs. Results from molecular dynamics simulation (100 ns) and other scoring parameters suggest that the compound CMNPD18759 (common name: aureobasidin; IUPAC name: 2-[(4R,6R)-4,6-dihydroxydecanoyl]oxypropan-2-yl (3S,5R)-3,5-dihydroxydecanoate) holds promise as a potential drug candidate for the treatment of Lyme disease, caused by B. garinii. However, further experimental studies are needed to validate the efficacy and safety of this compound in vivo.

Leveraging machine learning approaches for predicting potential Lyme disease cases and incidence rates in the United States using Twitter

BACKGROUND

Lyme disease is one of the most commonly reported infectious diseases in the United States (US), accounting for more than [Formula: see text] of all vector-borne diseases in North America.

OBJECTIVE

In this paper, self-reported tweets on Twitter were analyzed in order to predict potential Lyme disease cases and accurately assess incidence rates in the US.

METHODS

The study was done in three stages: (1) Approximately 1.3 million tweets were collected and pre-processed to extract the most relevant Lyme disease tweets with geolocations. A subset of tweets were semi-automatically labelled as relevant or irrelevant to Lyme disease using a set of precise keywords, and the remaining portion were manually labelled, yielding a curated labelled dataset of 77, 500 tweets. (2) This labelled data set was used to train, validate, and test various combinations of NLP word embedding methods and prominent ML classification models, such as TF-IDF and logistic regression, Word2vec and XGboost, and BERTweet, among others, to identify potential Lyme disease tweets. (3) Lastly, the presence of spatio-temporal patterns in the US over a 10-year period were studied.

RESULTS

Preliminary results showed that BERTweet outperformed all tested NLP classifiers for identifying Lyme disease tweets, achieving the highest classification accuracy and F1-score of [Formula: see text]. There was also a consistent pattern indicating that the West and Northeast regions of the US had a higher tweet rate over time.

CONCLUSIONS

We focused on the less-studied problem of using Twitter data as a surveillance tool for Lyme disease in the US. Several crucial findings have emerged from the study. First, there is a fairly strong correlation between classified tweet counts and Lyme disease counts, with both following similar trends. Second, in 2015 and early 2016, the social media network like Twitter was essential in raising popular awareness of Lyme disease. Third, counties with a high incidence rate were not necessarily related with a high tweet rate, and vice versa. Fourth, BERTweet can be used as a reliable NLP classifier for detecting relevant Lyme disease tweets.

Infectious Neuropathies

OBJECTIVE

This article discusses the clinical manifestations and management of infectious peripheral neuropathies.

LATEST DEVELOPMENTS

Several infectious etiologies of peripheral neuropathy are well-recognized and their treatments are firmly established. The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is associated with several central and peripheral nervous system manifestations, including peripheral neuropathies. Additionally, some COVID-19 vaccines have been associated with Guillain-Barré syndrome. These disorders are an active area of surveillance and research. Recent evidence-based guidelines have provided updated recommendations for the diagnosis and treatment of Lyme disease.

ESSENTIAL POINTS

Infectious agents of many types (primarily bacteria and viruses) can affect the peripheral nerves, resulting in various clinical syndromes such as mononeuropathy or mononeuropathy multiplex, distal symmetric polyneuropathy, radiculopathy, inflammatory demyelinating polyradiculoneuropathy, and motor neuronopathy. Knowledge of these infections and the spectrum of peripheral nervous system disorders associated with them is essential because many have curative treatments. Furthermore, understanding the neuropathic presentations of these disorders may assist in diagnosing the underlying infection.

Lyme Disease and Post-treatment Lyme Disease Syndrome: Current and Developing Treatment Options

Lyme disease and its treatment implications have become an ever-increasing area of concern within the United States related to the markedly increased prevalence of infection within the last two decades. The presentation, pathophysiology, and epidemiology of Lyme disease have been well studied, and thus treatments for this disease are widely available. While the treatment of its early and late stages is relatively simple with 10-14 day and four-week courses of doxycycline, respectively, the main problem rests in the understanding of the etiology and pathology of post-treatment Lyme disease syndrome (PTLDS). With the time of symptoms onsetting approximately six months after treatment and potentially lasting indefinitely, this syndrome's effect on patients' quality of life could be devastating. Searching on PubMed, Google Scholar, MEDLINE, and ScienceDirect using keywords including Lyme disease, PTLDS, doxycycline, erythema migrans, azlocillin, and treatment, the authors have tried to make clear the different aspects. The authors have reviewed and discussed clinical studies of Lyme disease and its treatments/potential therapeutics as well as PTLDS and its sparse treatments/potential therapeutics.

SYNCOPE: A RARE PRESENTATION OF LYME DISEASE

BACKGROUND

Lyme disease is one of the most common vector-borne illnesses in the United States. It is caused by Borrelia burgdorferi infection transmitted via the Ixodes tick. Rarely, it can progress to early disseminated Lyme disease with cardiac or neurologic manifestations, or both.

CASE REPORT

A 41-year-old previously healthy man presented to the emergency department (ED) by ambulance after an episode of syncope. Electrocardiogram revealed right bundle branch block with borderline first-degree atrioventricular nodal block. During his admission he was noted to have night sweats and elevated procalcitonin. Infectious workup revealed positive Borrelia enzyme-linked immunosorbent assay. Further testing revealed positive Borrelia immunoglobulin M with negative immunoglobulin G, indicating a recent infection. Why should an emergency physician be aware of this? Lyme disease should be on the differential for patients presenting with vague, flu-like symptoms in the summer months in endemic areas. Treatment of early Lyme disease with doxycycline can prevent progression to secondary Lyme, which can present as a true cardiac or neurologic emergency.

Borrelia PeptideAtlas: A proteome resource of common Borrelia burgdorferi isolates for Lyme research

Lyme disease, caused by an infection with the spirochete Borrelia burgdorferi, is the most common vector-borne disease in North America. B. burgdorferi strains harbor extensive genomic and proteomic variability and further comparison is key to understanding the spirochetes infectivity and biological impacts of identified sequence variants. To achieve this goal, both transcript and mass spectrometry (MS)-based proteomics was applied to assemble peptide datasets of laboratory strains B31, MM1, B31-ML23, infective isolates B31-5A4, B31-A3, and 297, and other public datasets, to provide a publicly available Borrelia PeptideAtlas http://www.peptideatlas.org/builds/borrelia/. Included is information on total proteome, secretome, and membrane proteome of these B. burgdorferi strains. Proteomic data collected from 35 different experiment datasets, with a total of 855 mass spectrometry runs, identified 76,936 distinct peptides at a 0.1% peptide false-discovery-rate, which map to 1,221 canonical proteins (924 core canonical and 297 noncore canonical) and covers 86% of the total base B31 proteome. The diverse proteomic information from multiple isolates with credible data presented by the Borrelia PeptideAtlas can be useful to pinpoint potential protein targets which are common to infective isolates and may be key in the infection process.

Assessment of Physician Knowledge, Attitudes, and Practice for Lyme Disease in a Low-Incidence State

Lyme disease (LD), caused by the bacterium Borrelia burgdorferi, is transmitted to humans in California through the bite of infected blacklegged ticks (Ixodes pacificus). Overall, the incidence of LD in California is low: approximately 0.2 confirmed cases per 100,000 population. However, California's unique ecological diversity results in wide variation in local risk, including regions with local foci at elevated risk of human disease. The diagnosis of LD can be challenging in California because the prior probability of infection for individual patients is generally low. Combined with nonspecific symptoms and complicated laboratory testing, California physicians need a high level of awareness of LD in California to recognize and diagnose LD efficiently. This research addresses an under-studied area of physicians' knowledge and practice of the testing and treatment of LD in a low-incidence state. We assessed knowledge and practices related to LD diagnosis using an electronic survey distributed to physicians practicing in California through mixed sampling methods. Overall, responding physicians in California had a general awareness of Lyme disease and were knowledgeable regarding diagnosis and treatment. However, we found that physicians in California could benefit from further education to improve test-ordering practices, test interpretation, and awareness of California's disease ecology with elevated levels of focal endemicity, to improve recognition, diagnosis, and treatment of LD in California patients.

Immunoinformatics-Based Proteome Mining to Develop a Next-Generation Vaccine Design against Borrelia burgdorferi: The Cause of Lyme Borreliosis

The tick-borne bacterium, Borrelia burgdorferi has been implicated in Lyme disease-a deadly infection, formerly confined to North America, but currently widespread across Europe and Asia. Despite the severity of this disease, there is still no human Lyme disease vaccine available. A reliable immunoinformatic approach is urgently needed for designing a therapeutic vaccine against this Gram-negative pathogen. Through this research, we explored the immunodominant proteins of B. burgdorferi and developed a novel and reliable vaccine design with great immunological predictability as well as low contamination and autoimmunity risks. Our initial analysis involved proteome-wide analysis to filter out proteins on the basis of their redundancy, homology to humans, virulence, immunogenicity, and size. Following the selection of proteins, immunoinformatic tools were employed to identify MHC class I & II epitopes and B-cell epitopes, which were subsequently subjected to a rigorous screening procedure. In the final formulation, ten common MHC-I and II epitopes were used together with a suitable adjuvant. We predicted that the final chimeric multi-epitope vaccine could invoke B-cell responses and IFN-gamma-mediated immunity as well as being stable and non-allergenic. The dynamics simulations predicted the stable folding of the designed molecule, after which the molecular docking predicted the stability of the interaction between the potential antigenic epitopes and human immune receptors. Our studies have shown that the designed next-generation vaccine stimulates desirable immune responses, thus potentially providing a viable way to prevent Lyme disease. Nevertheless, further experimental studies in a wet lab are needed in order to validate the results.

Global seroprevalence and sociodemographic characteristics of Borrelia burgdorferi sensu lato in human populations: a systematic review and meta-analysis

Introduction

Borrelia burgdorferi sensu lato (Bb) infection, the most frequent tick-transmitted disease, is distributed worldwide. This study aimed to describe the global seroprevalence and sociodemographic characteristics of Bb in human populations.

Methods

We searched PubMed, Embase, Web of Science and other sources for relevant studies of all study designs through 30 December 2021 with the following keywords: ‘Borrelia burgdorferi sensu lato’ AND ‘infection rate’; and observational studies were included if the results of human Bb antibody seroprevalence surveys were reported, the laboratory serological detection method reported and be published in a peer-reviewed journal. We screened titles/abstracts and full texts of papers and appraised the risk of bias using the Cochrane Collaboration-endorsed Newcastle-Ottawa Quality Assessment Scale. Data were synthesised narratively, stratified by different types of outcomes. We also conducted random effects meta-analysis where we had a minimum of two studies with 95% CIs reported. The study protocol has been registered with PROSPERO (CRD42021261362).

Results

Of 4196 studies, 137 were eligible for full-text screening, and 89 (158 287 individuals) were included in meta-analyses. The reported estimated global Bb seroprevalence was 14.5% (95% CI 12.8% to 16.3%), and the top three regions of Bb seroprevalence were Central Europe (20.7%, 95% CI 13.8% to 28.6%), Eastern Asia (15.9%, 95% CI 6.6% to 28.3%) and Western Europe (13.5%, 95% CI 9.5% to 18.0%). Meta-regression analysis showed that after eliminating confounding risk factors, the methods lacked western blotting (WB) confirmation and increased the risk of false-positive Bb antibody detection compared with the methods using WB confirmation (OR 1.9, 95% CI 1.6 to 2.2). Other factors associated with Bb seropositivity include age ≥50 years (12.6%, 95% CI 8.0% to 18.1%), men (7.8%, 95% CI 4.6% to 11.9%), residence of rural area (8.4%, 95% CI 5.0% to 12.6%) and suffering tick bites (18.8%, 95% CI 10.1% to 29.4%).

Conclusion

The reported estimated global Bb seropositivity is relatively high, with the top three regions as Central Europe, Western Europe and Eastern Asia. Using the WB to confirm Bb serological results could significantly improve the accuracy. More studies are needed to improve the accuracy of global Lyme borreliosis burden estimates.

PROSPERO registration number

CRD42021261362.

An antigen-targeting assay for Lyme disease: Combining aptamers and SERS to detect the OspA protein

Lyme disease is the fastest growing vector-borne disease in the United States. However, current testing modalities are ill suited to detection of Lyme disease, leading to the diagnosis of many cases after treatment is effective. We present an improved, direct method Lyme disease diagnosis, where the Lyme specific biomarker Outer Surface Protein A (OspA) in clinical serum samples is identified using a diagnostic platform combining surface enhanced Raman scattering (SERS) and aptamers. Employing orthogonal projections to latent structures discriminant analysis, the system accurately identified 91% of serum samples from Lyme patients, and 96% of serum samples from symptomatic controls. In addition, the OspA limit-of-detection, determined to be 1 × 10^-4 ng/mL, is greater than four orders of magnitude lower than that found in serum samples from early Lyme disease patients. The application of this platform to detect this difficult-to-diagnose disease suggests its potential for detecting other diseases that present similar difficulties.

Pediatric unilateral knee swelling: a case report of a complicated differential diagnosis and often overlooked cause

Lyme disease is the most common vector-borne illness in the United States. However, Lyme arthritis is a diagnosis that is often missed, even in children, who are the population with the highest incidence of Lyme disease. Lyme arthritis, which presents in the later stage of Borrelia burgdorferi infection, needs to be recognized and managed promptly, especially in endemic areas or when exposure to ticks is known. We present a case of a 3-year-old female presenting to the emergency department with a history of limping for 2 weeks. The mother of the child recognized a tick bite. However, the child was not taken to seek care expeditiously, because she had not developed any rashes. Test results demonstrated that the patient was IgG positive and IgM negative for Lyme disease, with Western blot confirming the diagnosis of Lyme arthritis. Most patients presenting with Lyme arthritis do not recall having a tick bite, making it difficult to differentiate it from other pediatric conditions. When this diagnosis is missed, it can result in long-term morbidity, which is generally refractory to intravenous antibiotic therapy, oftentimes requiring synovectomy. Hence, this underscores the importance of the consideration of Lyme arthritis as a differential diagnosis in patients presenting with joint effusion.

Forty Years of Evidence on the Efficacy and Safety of Oral and Injectable Antibiotics for Treating Lyme Disease of Adults and Children: A Network Meta-Analysis

Lyme disease (LD) is a heavy public health burden. The most common manifestations of LD include erythema migrans (EM), Lyme neuroborreliosis (LNB), and Lyme arthritis (LA). The efficacy and safety of antibiotics for treating LD is still controversial. Thus, we performed a network meta-analysis (NMA) to obtain more data and tried to solve this problem. We searched studies in the databases of Embase and PubMed from the date of their establishments until 22 April 2021. Odds ratios (ORs) were used to assess dichotomous outcomes. A total of 31 randomized controlled trials (RCTs) involving 2,748 patients and 11 antibiotics were included. Oral amoxicillin (1.5 g/day), oral azithromycin (0.5 g/day), injectable ceftriaxone, and injectable cefotaxime were effective for treating LD (range of ORs, 1.02 to 1,610.43). Cefuroxime and penicillin were safe for treating LD (range of ORs, 0.027 to 0.98). Amoxicillin was effective for treating EM (range of ORs, 1.18 to 25.66). Based on the results, we thought oral amoxicillin (1.5 g/day), oral azithromycin (0.5 g/day), injectable ceftriaxone, and injectable cefotaxime were effective for treating LD. Cefuroxime and penicillin were safe for treating LD. Amoxicillin was effective for treating EM. We did not observe evidence proving the advantage of doxycycline in efficacy and safety for treating LD, LA, LNB, and EM of children or adults. We did not have sufficient data to prove the significant difference of efficacy for treating LA and LNB in adults and LD in children, the significant difference of safety of oral drugs for treating LD, and the significant difference of safety of drugs for treating EM. IMPORTANCE Some previous studies investigated the efficacy and safety of antibiotics for treating Lyme disease (LD). However, due to technical limitations, several questions regarding the routes of drug administration and the dosages of drug are still unclear, which might be causing problems for clinicians. Hence, we performed network meta-analysis (NMA) to quantitatively analyze the clinical data published during the last 40 years. Here, we demonstrate the evidence regarding the efficacy and safety of antibiotics commonly used for treating LD in adults and children. We found that amoxicillin, azithromycin, ceftriaxone, and cefotaxime were effective for treating LD, but we did not observe significant efficacy and safety of doxycycline for treating LD.

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.