Use of Commercial Claims Data for Evaluating Trends in Lyme Disease Diagnoses, United States, 2010-2018

Lyme Disease

Lyme disease, caused by Borrelia burgdorferi, is the most common vector-borne disease in the United States, and the range of its tick vector continues to expand. Most Lyme disease cases are diagnosed with the onset of the erythema migrans rashes, which can be single or multiple and vary from a homogeneous erythema to bull's-eye patterns. Serologic antibody testing is of low sensitivity at onset but becomes highly sensitive after a few weeks. Early dissemination may lead to neurologic and cardiac complications. Mono- or oligoarticular arthritis may develop in untreated patients. Antibiotic treatment is highly effective, but approximately 10% of treated patients experience persistent symptoms.

Enhanced surveillance for tick-borne rickettsiosis and ehrlichiosis in North Carolina: Protocol and preliminary results

North Carolina (NC) experiences some of the highest incidence rates of spotted fever rickettsiosis (SFR) and ehrlichiosis in the United States (US). Due to the non-specific nature of clinical symptoms, minimal utilization of molecular methods when appropriate, and limitations of sero-diagnostic methods, accurate case identification and subsequent public health reporting is challenging. Herein we detail the protocol and early enrollment results for an enhanced surveillance project aiming to generate more accurate estimates of tick-borne disease incidence in NC. Secondary outcomes of interest include: (i) increasing the obtainment rate of convalescent samples (ii) defining demographic and socioeconomic, behavioral/knowledge, entomologic, and environmental risk factors for disease, and (iii) describing the spectrum and clinical course of disease among cases of SFR and ehrlichiosis up to 90 days after symptom onset. In addition, we will collect remnant serum to establish a biorepository of well characterized samples that we intend to make available to researchers. Of the 150 participants enrolled, highlighted results include 49.5% of participants reported being exposed in their own home compared to 43.2% being exposed due to work or travel showing the importance of tick control and education. We also reported more confirmed cases of SFR and ehrlichiosis (15 and 20 respectively) where the North Carolina State Health Department only reported 14 and 11 confirmed cases in the entire state in 2022. Findings from the project will be reported in subsequent publications.

Extravasation of Borrelia burgdorferi Across the Blood-Brain Barrier is an Extremely Rare Event

Lyme disease, the most widespread tick-borne disease in North America, is caused by the bacterium Borrelia burgdorferi (Bb). Approximately 10-15% of infections result in neuroborreliosis, common symptoms of which include headaches, facial palsy, and long-term cognitive impairment. Previous studies of Bb dissemination focus on assessing Bb transmigration at static time points rather than analyzing the complex dynamic process of extravasation. Furthermore, current in vitro models lack crucial physiological factors such as flow, demonstrating a need for more robust models for studying Bb dissemination to understand its dynamics and mechanisms. Here, a 3D tissue-engineered microvessel model is used and fluorescently-labeled Bb is perfused to model vascular dissemination in non-tissue-specific (iEC) and brain-specific (iBMEC) microvessels while acquiring time-lapse images in real time. In iECs, extravasation involves two steps: adhesion to the endothelium and transmigration into the extracellular matrix, which can be modulated through glycocalyx degradation or inflammation. In contrast, Bb extravasation in iBMECs is an extremely rare event regardless of glycocalyx degradation or inflammation. In addition, circulating Bb do not induce endothelial activation in iECs or iBMECs, but induces barrier dysfunction in iECs. These findings provide a further understanding of Bb vascular dissemination.

The peptidoglycan of Borrelia burgdorferi can persist in discrete tissues and cause systemic responses consistent with chronic illness

Persistent symptoms after an acute infection is an emerging public health concern, but the pathobiology of such conditions is not well understood. One possible scenario involves the persistence of lingering antigen. We have previously reported that patients with postinfectious Lyme arthritis often harbor the peptidoglycan (PG) cell wall of Borrelia burgdorferi, the Lyme disease agent, in the synovial fluid of their inflamed joints after treatment. However, it is not yet known how B. burgdorferi PG persists, in what form, or if it may play a role in other postinfectious complications after Lyme disease. Using a murine model, we developed a real-time in vivo system to track B. burgdorferi PG as a function of cell wall chemistry and validated our findings using both molecular and cellular approaches. Unlike typical bacterial PG, the unique chemical properties of polymeric B. burgdorferi PG drive murine liver accumulation, where the cell wall material persists for weeks. Kupffer cells and hepatocytes phagocytose and retain B. burgdorferi PG and, although liver occupancy coincides with minimal pathology, both organ-specific and secreted protein profiles produced under these conditions bear some similarities to reported proteins enriched in patients with chronic illness after acute infection. Moreover, transcriptomic profiling indicated that B. burgdorferi PG affects energy metabolism in peripheral blood mononuclear cells. Our findings provide mechanistic insights into how a pathogenic molecule can persist after agent clearance, potentially contributing to illness after infection.

A high-resolution screen identifies a preexisting beta-lactam that specifically treats Lyme disease in mice

Lyme disease, caused by Borrelia burgdorferi in the United States, is an escalating human health problem that can cause severe disease if not properly treated. Doxycycline is the primary treatment option for Lyme disease; however, several concerns are associated with high-dose doxycycline treatment. For example, doxycycline is a broad-spectrum antibiotic and kills beneficial bacteria. Doxycycline is also known to produce unwanted off-target effects in eukaryotic cells. Some at-risk populations such as young children cannot be prescribed doxycycline, and in addition to these shortcomings, the treatment appears to fail in 10 to 20% of cases. We reasoned that safe, alternative therapies may currently exist but have not yet been found because of the challenges associated with drug screening approaches. We screened nearly 500 US Food and Drug Administration-approved compounds using an array of physiological, cellular, and molecular techniques. Top-performing candidates were counter screened to identify compounds that did not affect other bacterial phyla. Piperacillin emerged as a compound that eradicated B. burgdorferi at low-nanomolar concentrations by specifically interfering with the unusual, multizonal peptidoglycan synthesis pattern common to the Borrelia clade. Mechanistic in vitro studies identified the cellular target of piperacillin in B. burgdorferi and produced key insights that may explain both the specificity and efficacy of the compound. Further, in vivo studies using an experimental mouse infection model demonstrated that piperacillin treated animals at a 100-fold lower dose than the effective dose of doxycycline without affecting the murine microbiome. Our findings suggest that piperacillin may offer clinicians another therapeutic option for Lyme disease.

Mechanistic insights into the structure-based design of a CspZ-targeting Lyme disease vaccine

Borrelia burgdorferi (Bb) causes Lyme disease (LD), one of the most common vector-borne diseases in the Northern Hemisphere. Here, we solve the crystal structure of a mutated Bb vaccine antigen, CspZ-YA that lacks the ability to bind to host complement factor H (FH). We generate point mutants of CspZ-YA and identify CspZ-YAI183Y and CspZ-YAC187S to trigger more robust bactericidal responses. Compared to CspZ-YA, these CspZ-YA mutants require a lower immunization frequency to protect mice from LD-associated inflammation and bacterial colonization. Antigenicity of wild-type and mutant CspZ-YA proteins are similar, as measured using sera from infected people or immunized female mice. Structural comparison of CspZ-YA with CspZ-YAI183Y and CspZ-YAC187S shows enhanced interactions of two helices adjacent to the FH-binding sites in the mutants, consistent with their elevated thermostability. In line with these findings, protective CspZ-YA monoclonal antibodies show increased binding to CspZ-YA at a physiological temperature (37 °C). In summary, this proof-of-concept study applies structural vaccinology to enhance intramolecular interactions for the long-term stability of a Bb antigen while maintaining its protective epitopes, thus promoting LD vaccine development.

Validation of Algorithms to Detect Acute and Disseminated Lyme Disease in U.S. Administrative Claims Data

Background

Lyme disease (LD) is the most common vector-borne disease in the United States, though traditional LD surveillance underestimates the burden of disease. We validated algorithms for early localized and disseminated LD, with and without LD-specific diagnosis codes, in states with high incidence and their neighboring states with low LD incidence.

Methods

We identified cohorts of potential incident LD cases in administrative insurance claims data, October 2015-October 2023, in 1 national and 1 regional insurer. Three algorithms were studied: a primary algorithm of an LD-specific diagnosis code and indicated antibiotic and 2 secondary algorithms for disseminated LD requiring a non-LD-specific musculoskeletal or neurologic diagnosis code, an antibiotic, and an LD diagnostic test. We included individuals from high LD-incidence states and neighboring low LD-incidence states. We validated the algorithms using medical records for a sample of potential cases, classifying them according to modified surveillance case definitions. We calculated positive predictive values (PPVs) for each algorithm.

Results

Overall, we identified 9483 potential LD cases in claims data and reviewed 841 medical records. The PPVs for the primary algorithm were 90.7% and 81.3% in high-incidence and neighboring states, respectively, when suspect, probable, and confirmed cases were included; they were 76.6% and 28.0% when only confirmed and probable were included. For confirmed and possible cases, the secondary musculoskeletal algorithm PPVs were 12.9% and 4.1%, and the secondary neurologic algorithm PPVs were 6.2% and 1.8% in high-incidence and neighboring states, respectively.

Conclusions

This study found that claims-based algorithms requiring diagnosis codes for LD or for related symptoms, in addition to other criteria, can identify cohorts of true LD cases. These algorithms, adjusted for PPV, can be used to estimate LD incidence in the United States.

Sex- and Age-Specific Lyme Disease Testing Patterns in the United States, 2019 and 2022

OBJECTIVES

Serologic testing is a useful adjunct for the diagnosis of Lyme disease, a major public health problem in certain US regions. We aimed to determine whether Lyme disease serologic testing and results differed by sex and age group.

METHODS

We identified 2 cohorts of individuals across all ages who underwent serologic testing for Lyme disease at a national reference laboratory in 2019 (cohort 1) and 2022 (cohort 2). If an individual had multiple tests in the same year, we included only the first test. We excluded individuals who had been tested in the previous 5 years.

RESULTS

Cohorts 1 and 2 consisted of 578 052 and 550 674 people, respectively. Fewer males than females were tested in cohort 1 (42.7% vs 57.3%) and cohort 2 (42.3% vs 57.7%), although similar numbers were tested for both sexes among nonadults. More males than females had a positive test result in cohort 1 (53.9% more males) and cohort 2 (52.9% more males). The odds ratio of receiving a positive test result among males versus females was 2.09 (95% CI, 2.01-2.17) in cohort 1 and 2.12 (95% CI, 2.05-2.19) in cohort 2. Among people with positive test results, females (except children) were more likely than males to have positive immunoglobulin M and negative immunoglobulin G results, which can serve as a marker of early infection (odds ratio = 1.43 [95% CI, 1.31-1.55] in cohort 1 and 1.38 [95% CI, 1.29-1.47] in cohort 2).

CONCLUSIONS

Further studies are needed to understand whether the observed differences in Lyme disease testing and positivity result from sex- and age-associated disparities in social behavior, health care seeking, clinical practice, or other factors.

The recent trend of twin epidemic in the United States: a 10-year longitudinal cohort study of co-prescriptions of opioids and stimulants

Background

In recent years, the use of central nervous system stimulant medications has increased among the population already using opioids, referred to as a "twin epidemic." There is an increasing concern about its harmful outcomes in large populations. However, very few studies examined the co-prescription pattern of these two drug categories over a long period, and there is currently no clear restriction on stimulant prescriptions among patients under opioid treatment in the United States. The objectives of our study were to identify opioid prescription dosage time-dependent patterns and patient subgroups representing distinct trajectories on a national level in the recent 10 years, and to further investigate longitudinal associations between stimulant and opioid prescriptions and the impact of stimulant prescriptions on opioid dosage patterns.

Methods

We obtained patient records from MarketScan, one of the largest clinical databases of health insurance in the United States. 10 years (2012-2021) of prescription records and related patient profiles, who received at least two independent opioid prescriptions, were utilized for developing a group-based opioid dose trajectory model.

Findings

From an initial cohort including 22 million patients with 96 million opioid prescriptions, we developed a study cohort of 2,895,960 patients with a mean age of 43.9 years (standard deviation [SD] 13.0), of whom 1,244,077 (43%) were male. Significant geographical variations in opioid prescription frequency and dosage among four U.S. regions were observed. The trajectory model identified five distinct opioid dose groups. Stimulant prescription before the initial opioid prescription was positively associated with escalating opioid doses (odds ratio [OR]: 7.58; 95% confidence intervals [CI] 6.14-9.35, opioid dose increasing group compared to the decreasing group). Stimulant co-prescriptions were also associated with increasing opioid doses (OR: 1.73; 95% CI 1.40-2.14) and were identified in patients with a higher prevalence of opioid use disorder.

Interpretation

During the recent 10 years, stimulant prescription is positively associated with escalating opioid prescription activities in U.S. healthcare systems, suggesting co-prescriptions of these two types of drugs are an important contributing factor for a national-level twin epidemic. Healthcare leaders and policymakers should pay more attention to this issue and its potential harms.

Funding

National Institute of General Medical Sciences, National Institute on Drug Abuse, and National Science Foundation.

Tick feeding or vaccination with tick antigens elicits immunity to the Ixodes scapularis exoproteome in guinea pigs and humans

Ixodes scapularis is a primary vector of tick-borne pathogens in North America. Repeated exposure to these ticks can induce a humoral response to tick antigens and acquired tick resistance. However, identifying antigens contributing to this resistance is challenging because of the vast number of I. scapularis proteins secreted during feeding. To address this, we developed I. scapularis rapid extracellular antigen monitoring (IscREAM), a technique to detect antibody responses to more than 3000 tick antigens. We validated IscREAM with immunoglobulin G (IgG) from guinea pigs vaccinated with tick antigens, including a cement antigen cocktail that induced tick resistance. Furthermore, we explored the natural response to tick bites by profiling antigens recognized by IgG isolated from a tick-resistant individual, as well as from others with Lyme disease and tick-bitten guinea pigs and mice, to identify 199 recognized antigens. We observed that several antigens contained histamine-binding domains. This work enhances our understanding of the host immune response to I. scapularis and defines immunogen candidates for future antitick vaccines.

Comparison of 2 Sets of Immunoassays Used in Modified 2-Tiered Testing Algorithms for the Diagnosis of Lyme Disease

BACKGROUND

Since 2019, modified 2-tiered testing (MTTT) algorithms have been available for the diagnosis of Lyme disease. MTTTs replaced the standard algorithms that utilized enzyme immunoassays and immunoblots with sequential enzyme immunoassays that detect different antigens.

METHODS

We compared the performance of serological assays from ZEUS Scientific Inc. and DiaSorin Inc. that are used for the diagnosis of Lyme disease. Serological results were compared with clinical information gathered by chart review.

RESULTS

Percent positive agreement (PPA) and percent negative agreement (PNA) for total immunoglobulin G (IgG)/immunoglogulin M (IgM) (n = 120) were 64% (95% confidence interval 54% to 73%) and 100% (87% to 100%), respectively. PPA and PNA for IgG (n = 93) were 91% (80% to 97%) and 66% (52% to 78%), respectively. PPA and PNA for IgM (n = 93) were 75% (62% to 85%) and 95% (82% to 99%), respectively. Fewer positive total IgG/IgM results confirmed positive for either IgG or IgM for ZEUS compared to DiaSorin. Overall MTTT algorithm interpretation was concordant in 58% (55/95) of samples, and concordance improved when the results were limited to IgM in patients with symptom duration <30 days. Treatment with antibiotics was most strongly associated with IgM positivity.

CONCLUSIONS

This analysis highlights differences in the performance characteristics between commercially available diagnostic assays for Lyme disease. Our data suggest that the DiaSorin assays would result in fewer positive total IgG/IgM tests, decreasing the required number of confirmatory IgG and IgM tests. This would potentially lead to fewer patients treated with antibiotics.

Clinical and Epidemiological Information Required for Lyme Disease Surveillance in a Low-Incidence State, California 2011-2017

Background: Between January 1, 2011, and December 31, 2017, over 12,000 case reports of Lyme disease (LD) were submitted to the California Reportable Disease Information Exchange for further investigation. The number of case reports has tripled compared to previous years, emphasizing the need for efficient estimation and classification methods. We evaluated whether estimation procedures can be implemented in a low-incidence state such as California to correctly classify a case of LD, similar to those procedures used in high-incidence states. Objective: The purpose of this study was to identify whether a minimum number of variables was sufficient to reliably classify cases in California and potentially reduce workload while maintaining the ability to track LD trends in California. Methods: To determine the relative value of diagnostic information, we compared five candidate logistic regression models that were used to classify cases based on information that varied in its degree of difficulty for collection. Results: Our results using California's surveillance data showed that automatically reported data were not sufficient, additional information such as, a patient's clinical presentation and travel history were necessary in a low-incidence state to improve the overall sensitivity of the models. Conclusion: This study may help inform public health surveillance efforts by demonstrating that both clinical and travel information are required to accurately classify a case of LD in a low-incidence state.

Perspective: Incidence of Clinician-Diagnosed Lyme Disease in Manitoba, Canada 2009-2018

Introduction: Lyme disease (LD) surveillance yields useful information to monitor the disease trends and spatial distribution. However, due to several factors, the Manitoba Health surveillance system, as with other systems, could be subject to underreporting. Objectives: To estimate the number and incidence of clinician-diagnosed LD over the study period in Manitoba, describe the epidemiology of clinician-diagnosed LD, and compare the findings with Manitoba Health LD surveillance data during the same period to estimate the extent of underreporting. Methods: A retrospective analysis of administrative health data was performed to calculate the number and incidence of clinician-diagnosed LD from 2009 to 2018 in Manitoba and describe the epidemiological characteristics using the International Classification of Diseases, Tenth and Ninth Revision (ICD-10-CA and ICD-9-CM) codes, and antimicrobial drug prescriptions. Conclusion: Of the 1,629,698 registrants within the Manitoba Health Insurance Registry followed over 10 years, 1658 LD events were identified. Most of the cases occurred from May to July and corresponded to the peak activity of the nymphal stage of the blacklegged tick in the province. LD events presented a bimodal distribution with a peak in children between 5 and 9 years of age for both sexes, and a peak in adults from 65 to 84 and from 50 to 74, respectively, for males and females. We estimated that an average of 165 LD events occurred annually in Manitoba (mean annual incidence of 10.17 per 100,000 population), compared with 30 cases per year reported in the surveillance system; therefore, the LD surveillance yields an important underreporting.

Epidemiology of Lyme Disease as Identified Through Electronic Health Records in a Large Midwestern Health System, 2016-2019

Background

Lyme disease is the most common vector-borne disease in the United States; however, its frequency is not reliably measured through surveillance. Electronic health records (EHR) might capture the frequency and characteristics of Lyme disease cases more accurately. We queried EHR from 1 health system to describe the epidemiology of Lyme disease cases in Wisconsin during 2016-2019.

Methods

Within a cohort of persons evaluated for Lyme disease, we applied a Lyme disease case definition based on first-line antibiotics within 14 days of a Lyme disease diagnosis code or test order or on the same day as a related keyword in clinical notes. We compared characteristics of cases to those of cases reported through surveillance and reviewed medical charts to assess case definition validity.

Results

Among 67 289 possible Lyme disease events in the cohort, 13 494 (20.1%) met our Lyme disease case definition. Cases were more common among males, children 5-9 years, older adults, White non-Hispanic persons, and in the summer months. EHR-based Lyme disease incidence was 4-8 times that reported through surveillance. The EHR definition had moderately high sensitivity (83.4%) and specificity (71.1%) for confirmed and probable Lyme disease.

Conclusions

EHR queries show promise to capture the incidence of Lyme disease more completely and provide more robust clinical information than public health surveillance. Demographic and seasonal characteristics of EHR-identified cases were comparable to those identified through surveillance. Further algorithm refinement might improve accuracy of measuring Lyme disease in EHR systems.

Borrelia burgdorferi tolerates alteration to P66 porin function in a murine infectivity model

Borrelia burgdorferi exists in a complex enzootic life cycle requiring differential gene regulation. P66, a porin and adhesin, is upregulated and essential during mammalian infection, but is not produced or required within the tick vector. We sought to determine whether the porin function of P66 is essential for infection. Vancomycin treatment of B. burgdorferi cultures was used to screen for P66 porin function and found to generate spontaneous mutations in p66 (bb0603). Three novel, spontaneous, missense P66 mutants (G175V, T176M, and G584R) were re-created by site-directed mutagenesis in an infectious strain background and tested for infectivity in mice by ID50 experiments. Two of the three mutants retained infectivity comparable to the isogenic control, suggesting that B. burgdorferi can tolerate alteration to P66 porin function during infection. The third mutant exhibited highly attenuated infectivity and produced low levels of P66 protein. Interestingly, four isolates that were recovered for p66 sequencing from mouse tissues revealed novel secondary point mutations in genomic p66. However, these secondary mutations did not rescue P66 porin function. New structural modeling of P66 is presented and consistent with these experimental results. This is the first work to assess the contribution of P66 porin function to B. burgdorferi pathogenesis.

Individual variation underlies large-scale patterns: Host conditions and behavior affect parasitism

Identifying the factors that affect host-parasite interactions is essential for understanding the ecology and dynamics of vector-borne diseases and may be an important component of predicting human disease risk. Characteristics of hosts themselves (e.g., body condition, host behavior, immune defenses) may affect the likelihood of parasitism. However, despite highly variable rates of parasitism and infection in wild populations, identifying widespread links between individual characteristics and heterogeneity in parasite acquisition has proven challenging because many zoonoses exist over wide geographic extents and exhibit both spatial and temporal heterogeneity in prevalence and individual and population-level effects. Using seven years of data collected by the National Ecological Observatory Network (NEON), we examined relationships among individual host condition, behavior, and parasitism by Ixodid ticks in a keystone host species, the white-footed mouse, Peromyscus leucopus. We found that individual condition, specifically sex, body mass, and reproductive condition, had both direct and indirect effects on parasitism by ticks, but the nature of these effects differed for parasitism by larval versus nymphal ticks. We also found that condition differences influenced rodent behavior, and behavior directly affected the rates of parasitism, with individual mice that moved farther being more likely to carry ticks. This study illustrates how individual-level data can be examined using large-scale datasets to draw inference and uncover broad patterns in host-parasite encounters at unprecedented spatial scales. Our results suggest that intraspecific variation in the movement ecology of hosts may affect host-parasite encounter rates and, ultimately, alter zoonotic disease risk through anthropogenic modifications and natural environmental conditions that alter host space use.

Optimizing Exclusion Criteria for Clinical Trials of Persistent Lyme Disease Using Real-World Data

BACKGROUND/OBJECTIVES

Although eligibility criteria for clinical trials significantly impact study outcomes, these criteria are often established without scientific justification, leading to delayed recruitment, small sample sizes, and limited study generalizability. Persistent Lyme disease (PLD) presents unique challenges due to symptom variability, inconsistent treatment responses, and the lack of reliable biomarkers, underscoring the need for scientifically justified eligibility criteria.

OBJECTIVE

This study examines the effects of commonly used enrollment criteria on sample yield in PLD clinical trials using real-world data (RWD) from the MyLymeData patient registry. The study also compares the effects of these criteria on enrollment for PLD versus acute Lyme disease (ALD) trials and evaluates the scientific rationale for each criterion.

METHODS

Data from 4183 Lyme disease patients enrolled in the MyLymeData registry were analyzed to assess the prevalence and cumulative impact of various criteria on sample yield. A comparative analysis of cohorts with PLD (n = 3589) versus ALD (n = 594) was conducted to identify differences in sample attrition.

RESULTS

In a large PLD cohort study, we found that current commonly used eligibility criteria would exclude approximately 90% of patients, significantly limiting study generalizability. Substantial differences in sample attrition between PLD and ALD cohorts highlight the need for tailored criteria. The strength of scientific justification varied widely among criteria.

CONCLUSIONS

This study demonstrates the importance of using RWD to optimize eligibility criteria in PLD clinical trials. By providing insights into the balance between sample attrition and scientific justification, researchers can enhance trial feasibility, generalizability, and robustness. Our RWD sample demonstrates that researchers could substantially increase the sample yield from 10% to 64% by loosening restrictions on coinfections and misdiagnoses of chronic fatigue syndrome, fibromyalgia syndrome, and psychiatric conditions.

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

Lyme disease is caused by an infection with the spirochete Borrelia burgdorferi, and is the most common vector-borne disease in North America. B. burgdorferi isolates harbor extensive genomic and proteomic variability and further comparison of isolates is key to understanding the infectivity of the spirochetes and biological impacts of identified sequence variants. Here, we applied both transcriptome analysis and mass spectrometry-based proteomics to assemble peptide datasets of B. burgdorferi laboratory isolates B31, MM1, and the infective isolate B31-5A4, to provide a publicly available Borrelia PeptideAtlas. Included are total proteome, secretome, and membrane proteome identifications of the individual isolates. Proteomic data collected from 35 different experiment datasets, totaling 386 mass spectrometry runs, have identified 81,967 distinct peptides, which map to 1,113 proteins. The Borrelia PeptideAtlas covers 86% of the total B31 proteome of 1,291 protein sequences. The Borrelia PeptideAtlas is an extensible comprehensive peptide repository with proteomic information from B. burgdorferi isolates useful for Lyme disease research.

Examining Infant and Child Neurodevelopmental Outcomes After Lyme Disease During Pregnancy

Lyme disease is the most common vector-borne disease in the United States. Recent environmental and socioecological changes have led to an increased incidence of Lyme and other tick-borne diseases, which enhances the urgency of identifying and mitigating adverse outcomes of Lyme disease exposure. Lyme disease during pregnancy, especially when untreated, may lead to adverse pregnancy and neonatal outcomes; however, long-term child outcomes following utero exposure to Lyme disease have not yet been systematically assessed. This concise review describes the current state of knowledge of Lyme disease as a congenital infection and the potential effects of in utero exposure to Lyme disease infection on the neurodevelopment of infants and children. We highlight the importance of distinguishing between acute Lyme disease and a chronic condition termed Post-Treatment Lyme Disease Syndrome, as the impacts of both conditions on the developing fetus and subsequent child development may differ. The importance of placental pathology for patients with acute or chronic symptoms of Lyme disease in pregnancy is explored. Future research aiming to understand and protect neurodevelopment after antenatal Lyme disease must carefully collect potentially confounding variables such as symptomatology and treatment, use clear and standard case definitions, and follow children into school-age and beyond.

Optimizing identification of Lyme disease diagnoses in commercial insurance claims data, United States, 2016-2019

BACKGROUND

Commercial insurance claims data are a stable and consistent source of information on Lyme disease diagnoses in the United States and can contribute to our understanding of overall disease burden and the tracking of epidemiological trends. Algorithms consisting of diagnosis codes and antimicrobial treatment information have been used to identify Lyme disease diagnoses in claims data, but there might be opportunity to improve their accuracy.

METHODS

We developed three modified versions of our existing claims-based Lyme disease algorithm; each reflected refined criteria regarding antimicrobials prescribed and/or maximum days between diagnosis code and qualifying prescription claim. We applied each to a large national commercial claims database to identify Lyme disease diagnoses during 2016-2019. We then compared characteristics of Lyme disease diagnoses identified by each of the modified algorithms to those identified by our original algorithm to assess differences from expected trends in demographics, seasonality, and geography.

RESULTS

Observed differences in characteristics of patients with diagnoses identified by the three modified algorithms and our original algorithm were minimal, and differences in age and sex, in particular, were small enough that they could have been due to chance. However, one modified algorithm resulted in proportionally more diagnoses in men, during peak summer months, and in high-incidence jurisdictions, more closely reflecting epidemiological trends documented through public health surveillance. This algorithm limited treatment to only first-line recommended antimicrobials and shortened the timeframe between a Lyme disease diagnosis code and qualifying prescription claim.

CONCLUSIONS

As compared to our original algorithm, a modified algorithm that limits the antimicrobials prescribed and shortens the timeframe between a diagnosis code and a qualifying prescription claim might more accurately identify Lyme disease diagnoses when utilizing insurance claims data for supplementary, routine identification and monitoring of Lyme disease diagnoses.

Identifying the geographic leading edge of Lyme disease in the United States with internet searches: A spatiotemporal analysis of Google Health Trends data

BACKGROUND

The geographic footprint of Lyme disease is expanding in the United States, which calls for novel methods to identify emerging endemic areas. The ubiquity of internet use coupled with the dominance of Google's search engine makes Google user search data a compelling data source for epidemiological research.

OBJECTIVE

We evaluated the potential of Google Health Trends to track spatiotemporal patterns in Lyme disease and identify the leading edge of disease risk in the United States.

MATERIALS AND METHODS

We analyzed internet search rates for Lyme disease-related queries at the designated market area (DMA) level (n = 206) for the 2011-2019 and 2020-2021 (COVID-19 pandemic) periods. We used maps and other exploratory methods to characterize changes in search behavior. To assess statistical correlation between searches and Lyme disease cases reported to Centers for Disease Control and Prevention (CDC) between 2011 and 2019, we performed a longitudinal ecological analysis with modified Poisson generalized estimating equation regression models.

RESULTS

Mapping DMA-level changes in "Lyme disease" search rates revealed an expanding area of higher rates occurring along the edges of the northeastern focus of Lyme disease. Bivariate maps comparing search rates and CDC-reported incidence rates also showed a stronger than expected signal from Google Health Trends in some high-risk adjacent states such as Michigan, North Carolina, and Ohio, which may be further indication of a geographic leading edge of Lyme disease that is not fully apparent from routine surveillance. Searches for "Lyme disease" were a significant predictor of CDC-reported disease incidence. Each 100-unit increase in the search rate was significantly associated with a 10% increase in incidence rates (RR = 1.10, 95% CI: 1.07, 1.12) after adjusting for environmental covariates of Lyme disease identified in the literature.

CONCLUSION

Google Health Trends data may help track the expansion of Lyme disease and inform the public and health care providers about emerging risks in their areas.

Review of Lyme Borreliosis in Africa-An Emerging Threat in Africa

Lyme borreliosis (LB) is more common in the Northern Hemisphere. It is endemic mainly in North America, where the vectors are Ixodes scapularis and Ixodes pacificus, and in Eurasia, where the vectors are Ixodes ricinus and Ixodes persulcatus. Both tick-borne diseases and LB are influenced by climate change. Africa and South America are crossed by the equator and are situated in both the Northern and Southern Hemispheres. In Africa, the LB is present on the Mediterranean and the Indian Ocean coasts. Borrelia lusitaniae is prevalent in countries bordering the Mediterranean Sea, such as Tunisia, Morocco, Algeria, and Egypt. Ticks were detected in the Ixodes Ricinus, which are carried by migratory birds and the Ixodes inopinatus and captured by the Psammodromus algirus lizards. The Borreliae Lyme Group (LG) and, in particular, Borrelia garinii, have been reported in countries bordering the Indian Ocean, such as Kenya, Tanzania, and Mozambique, transported by migratory birds from North African countries, where the vector was identified as Hyalomma rufipes ticks. This review aims to document the presence of Borreliae LG and LB in Africa.

Mechanistic insights into structure-based design of a Lyme disease subunit vaccine

The quality of protective immunity plays a critical role in modulating vaccine efficacy, with native antigens often not able to trigger sufficiently strong immune responses for pathogen killing. This warrants creation of structure-based vaccine design, leveraging high-resolution antigen structures for mutagenesis to improve protein stability and efficient immunization strategies. Here, we investigated the mechanisms underlying structure-based vaccine design using CspZ-YA, a vaccine antigen from Borrelia burgdorferi, the bacteria causing Lyme disease (LD), the most common vector-borne disease in the Northern Hemisphere. Compared to wild-type CspZ-YA, we found CspZ-YAI183Y and CspZ-YAC187S required lower immunization frequency to protect mice from LD-associated manifestations and bacterial colonization. We observed indistinguishable human and mouse antigenicity between wild-type and mutant CspZ-YA proteins after native infection or active immunization. This supports our newly generated, high-resolution structures of CspZ-YAI183Y and CspZ-YAC187S, showing no altered surface epitopes after mutagenesis. However, CspZ-YAI183Y and CspZ-YAC187S favored the interactions between helices H and I, consistent with their elevated thermostability. Such findings are further strengthened by increasing ability of protective CspZ-YA monoclonal antibodies in binding to CspZ-YA at a physiological temperature (37°C). Overall, this study demonstrated enhanced intramolecular interactions improved long-term stability of antigens while maintaining protective epitopes, providing a mechanism for structure-based vaccine design. These findings can ultimately be extended to other vaccine antigens against newly emerging pathogens for the improvement of protective immunity.

Age- and Sex-Specific Differences in Lyme Disease Health-Related Behaviors, Ontario, Canada, 2015-2022

We investigated differences in risk factors and preventive behaviors by age and sex among persons with reported Lyme disease in Ontario, Canada, during 2015-2022. Incidence rates peaked among children 5-9 and adults 50-79 years of age. Median age was higher for female than male case-patients (54 vs. 51 years). Male case-patients reported more activity in wooded and tall grass areas than did female case-patients; fewer male case-patients reported sharing living space with outdoor-exposed companion animals. As age increased, more case-patients reported activity in blacklegged tick habitats, exposure to ticks, and wearing adequate clothing, but fewer reported sharing living space with outdoor-exposed companion animals. Adoption of preventive behaviors was relatively low and did not differ by sex. Male case-patients, children 5-9 years of age and their parents or caregivers, and adults >59 years of age represent populations that would benefit from tailored public health messaging on Lyme disease prevention.

Central nervous system manifestations in rheumatic diseases

As the role of neurologists in managing patients with rheumatic diseases expands, collaboration between rheumatologists and neurologists becomes increasingly vital. This literature review provides an overview of the central nervous system (CNS) manifestations of major autoimmune rheumatic disorders, which may include parenchymal brain and meningeal disease (stroke, meningoencephalitis, meningitis), myelopathies, psychosis, chorea, seizure disorders, and various forms of cephalea. Novel findings linking specific autoimmune markers to CNS damage reveal a direct, previously underestimated link between systemic inflammation and neural injury. Besides, with the increasing use of biological therapies, it is crucial to recognize when neurological manifestations are related to adverse events of therapy, as this may significantly influence treatment decisions. Neurologists play a key role in this assessment, working closely with rheumatologists. Overall, addressing CNS involvement in rheumatic diseases is important for improving patient outcomes and advancing medical knowledge in this complex field. A thorough understanding of the neurologic aspects of rheumatic diseases is essential for optimal patient care, necessitating a multidisciplinary approach to management.

Rapid Increase in Seroprevalence of Borrelia burgdorferi Antibodies among Dogs, Northwestern North Carolina, USA, 2017-20211

We evaluated spatial-temporal risk for Lyme disease in northwestern North Carolina, USA, by using individual-level canine Borrelia burgdorferi seroprevalence data collected during 2017-2021 at routine veterinary screenings for tickborne diseases. Seroprevalence in dogs increased from 2.2% (47/2,130) in 2017 to 11.2% (339/3,033) in 2021. The percentage of incident seropositivity increased from 2.1% (45/2,130) in 2017 to 7.6% (231/3,033) in 2021. Exploratory geographic analyses found canine seroprevalence shifted from clustered (2017, Moran's I = 0.30) to dispersed (2021, Moran's I = -0.20). Elevation, slope, aspect, and forest land cover density were associated with canine seroprevalence within various household buffer regions in 2017. Slope was associated with seroprevalence at the household level in 2021. Results support the use of individual-level canine seroprevalence data for monitoring human risk for Lyme disease. Establishing sentinel veterinary clinics within Lyme disease-emergent communities might promote prevention and control efforts and provide opportunities for educational and behavioral interventions.

Natural selection and recombination at host-interacting lipoprotein loci drive genome diversification of Lyme disease and related bacteria

Lyme disease, caused by spirochetes in the Borrelia burgdorferi sensu lato clade within the Borrelia genus, is transmitted by Ixodes ticks and is currently the most prevalent and rapidly expanding tick-borne disease in Europe and North America. We report complete genome sequences of 47 isolates that encompass all established species in this clade while highlighting the diversity of the widespread human pathogenic species B. burgdorferi. A similar set of plasmids has been maintained throughout Borrelia divergence, indicating that they are a key adaptive feature of this genus. Phylogenetic reconstruction of all sequenced Borrelia genomes revealed the original divergence of Eurasian and North American lineages and subsequent dispersals that introduced B. garinii, B. bavariensis, B. lusitaniae, B. valaisiana, and B. afzelii from East Asia to Europe and B. burgdorferi and B. finlandensis from North America to Europe. Molecular phylogenies of the universally present core replicons (chromosome and cp26 and lp54 plasmids) are highly consistent, revealing a strong clonal structure. Nonetheless, numerous inconsistencies between the genome and gene phylogenies indicate species dispersal, genetic exchanges, and rapid sequence evolution at plasmid-borne loci, including key host-interacting lipoprotein genes. While localized recombination occurs uniformly on the main chromosome at a rate comparable to mutation, lipoprotein-encoding loci are recombination hotspots on the plasmids, suggesting adaptive maintenance of recombinant alleles at loci directly interacting with the host. We conclude that within- and between-species recombination facilitates adaptive sequence evolution of host-interacting lipoprotein loci and contributes to human virulence despite a genome-wide clonal structure of its natural populations.

IMPORTANCE

Lyme disease (also called Lyme borreliosis in Europe), a condition caused by spirochete bacteria of the genus Borrelia, transmitted by hard-bodied Ixodes ticks, is currently the most prevalent and rapidly expanding tick-borne disease in the United States and Europe. Borrelia interspecies and intraspecies genome comparisons of Lyme disease-related bacteria are essential to reconstruct their evolutionary origins, track epidemiological spread, identify molecular mechanisms of human pathogenicity, and design molecular and ecological approaches to disease prevention, diagnosis, and treatment. These Lyme disease-associated bacteria harbor complex genomes that encode many genes that do not have homologs in other organisms and are distributed across multiple linear and circular plasmids. The functional significance of most of the plasmid-borne genes and the multipartite genome organization itself remains unknown. Here we sequenced, assembled, and analyzed whole genomes of 47 Borrelia isolates from around the world, including multiple isolates of the human pathogenic species. Our analysis elucidates the evolutionary origins, historical migration, and sources of genomic variability of these clinically important pathogens. We have developed web-based software tools (BorreliaBase.org) to facilitate dissemination and continued comparative analysis of Borrelia genomes to identify determinants of human pathogenicity.

Epidemiology of Lyme Disease Diagnoses among Older Adults, United States, 2016-20191

We used Medicare data to identify >88,000 adults >65 years of age diagnosed and treated for Lyme disease during 2016-2019 in the United States. Most diagnoses occurred among residents of high-incidence states, in summer, and among men. Incidence of diagnoses was substantially higher than that reported through public health surveillance.

Spatio-temporal patterns of tick-borne disease diagnoses in Indiana, USA (2009-2018)

AIMS

Although tick-borne disease (TBD) incidence has increased in the United States (U.S.) in the past decade, new evidence suggests that notifiable diseases surveillance records may not accurately reflect the true magnitude of TBD diagnoses. Furthermore, while regional electronic health records (EHR) are readily accessible their potential use as a more stable and consistent source of TBD diagnoses data has remained largely unexplored.

METHODS AND RESULTS

In this study, we used EHR from a database of more than 100 hospitals, healthcare networks, and insurance providers in Indiana, U.S., to better understand incidence, spatio-temporal and demographic distribution of TBD Diagnoses from 2009-2018. Our results revealed that in Indiana, from 2009 to 2018, there were 5173 unique TBD Diagnoses across three diagnoses categories: Lyme disease (72.5%, n = 3751), Rickettsioses (12.0%, n = 623) and Other TBD Diagnoses (15.4%, n = 799). Using EHR, the average yearly Lyme disease diagnoses was more than double the cases obtained using notifiable disease surveillance data for the same period. Patients with a TBD Diagnoses were generally older (ages 45-59) and less racially diverse (96.3% white). Rickettsiosis diagnoses were reported more among male patients (55.2%), while Lyme disease diagnoses were higher among female patients (57.1%). Temporal data illustrated higher frequencies of diagnoses from May to July. Hot spot analysis identified a Lyme disease hot spot in northwest Indiana, while hotspots of Rickettsiosis and Other TBD Diagnoses category were identified in southwest Indiana. Extrapolated to the Indiana population, chi-squared (χ2) tests of independence revealed that the observed distribution of TBD diagnoses in our data was significantly different from the expected distribution in the Indiana population-based race, gender and age groups.

CONCLUSIONS

Our study findings demonstrate that in Indiana, EHR provide a stable data source for elucidating TBD disease burden and for monitoring spatio-temporal trends in TBD diagnoses.

Early Versus Late Periprosthetic Joint Infection After Total Knee Arthroplasty: Do Patient Differences Exist?

BACKGROUND

Periprosthetic joint infection (PJI) is a devastating complication following total knee arthroplasty (TKA). Little evidence exists comparing those with early versus late PJI. The purpose of the study was to determine comorbidity profile differences between patients developing early and late PJI.

METHODS

There were 72,659 patients undergoing primary TKA from 2009 to 2021, who were identified from a commercial claims and encounters database. Subjects diagnosed with PJI were categorized as either 'early' (within 90 days of index procedure) or 'late' (> 2 years after index arthroplasty). Non-infected patients within these periods served as control groups following 4:1 propensity score matching on other extraneous variables. Logistic regression analyses were performed comparing comorbidities between groups.

RESULTS

Patients were significantly younger in the late compared to the early infection group (58.1 versus 62.4 years, P < .001). When compared to those with early PJI, patients who had chronic kidney disease (13.3 versus 4.1%; OR [odds ratio] 5.17, P = .002), malignancy (20.4 versus 10.5%; OR 2.53, P = .009), uncomplicated diabetes (40.8 versus 30.6%; OR 2.00, P = .01), rheumatoid arthritis (9.2 versus 3.3%; OR 2.66, P = .046), and hypertension (88.8 versus 81.6%; OR 2.17, P = .04), were all significant predictors of developing a late PJI.

CONCLUSIONS

When compared to patients diagnosed with early PJI following primary TKA, the presence of chronic kidney disease, malignancy, uncomplicated diabetes, rheumatoid arthritis, and hypertension, were independent risk factors for the development of late PJI. Younger patients who have these comorbidities may be targets for preoperative optimization interventions that minimize the risk of PJI.

Chronic Anticoagulation is Associated With Increased Risk for Postoperative Complications Following Aseptic Revision Total Hip Arthroplasty

BACKGROUND

With an aging global population, the incidence of revision total hip arthroplasty (rTHA) is expected to increase markedly. While patients undergoing primary total hip arthroplasty who require chronic anticoagulation (AC) have been associated with increased postoperative complications, less is known about the impact of chronic AC status on postoperative complications in the rTHA setting. This study sought to compare complication rates following aseptic rTHA between patients who were on chronic AC and those who were not.

METHODS

A large national database was utilized to retrospectively identify 9,421 patients who underwent aseptic rTHA between 2014 and 2019. Patients were divided into 2 cohorts: 1,790 patients (19.0%) were in the chronic AC cohort (ie, having an AC prescription filled within 6 months prior to and following rTHA), and 7,631 patients (81.0%) were not on chronic AC. Postoperative complications at 90-days and 2-years were compared between cohorts utilizing univariate and multivariate analyses, controlling for sex, age, and comorbidities.

RESULTS

At 90-days, chronic AC patients had increased odds of prosthetic joint infections (PJIs) (odds ratio [OR] 3.2, P < .001), surgical site infections (OR 3.6, P < .001), and mechanical prosthetic complications (OR 3.5, P < .001), which included any aseptic loosening, implant dislocation, or broken prosthetic. At 2-years, chronic AC patients had increased odds of PJI (OR 3.3, P < .001) as well as mechanical prosthetic complications (OR 3.2, P < .001). Chronic AC patients were also at increased risk for reoperation within 2 years after initial aseptic rTHA (OR 1.9, P < .001).

CONCLUSIONS

Patients on chronic AC have significantly higher odds of 90-day and 2-year complications after aseptic rTHA. This includes increased odds of PJI, surgical site infection, and mechanical prosthetic complications. Patients receiving chronic AC who undergo rTHA should be counseled on the risk-benefit ratio of their chronic AC status in a multidisciplinary setting to optimize their postoperative outcomes.

Lyme Disease Surveillance and Epidemiology in the United States: A Historical Perspective

In the 40 years since Steere and colleagues first described Lyme disease, the illness has increased in incidence and distribution to become the most common vector-borne disease in the United States. Public health officials have developed, implemented, and revised surveillance systems to describe and monitor the condition. Much has been learned about the epidemiology of the illness, despite practical and logistical constraints that have encumbered the collection and interpretation of surveillance data. Future development of automated data collection from electronic health records as a source of surveillance and clinical information will address practical challenges and help answer ongoing questions about complications and persistent symptoms. Robust surveillance will be essential to monitor the effectiveness and safety of future vaccines and other preventive measures.

Vaccination to Prevent Lyme Disease: A Movement Towards Anti-Tick Approaches

Lyme disease is caused by the spirochete, Borrelia burgdorferi, which is transmitted by Ixodes spp ticks. The rise in Lyme disease cases since its discovery in the 1970s has reinforced the need for a vaccine. A vaccine based on B burgdorferi outer surface protein A (OspA) was approved by the Food and Drug Administration (FDA) several decades ago, but was pulled from the market a few years later, reportedly due to poor sales, despite multiple organizations concluding that it was safe and effective. Newer OspA-based vaccines are being developed and are likely to be available in the coming years. More recently, there has been a push to develop vaccines that target the tick vector instead of the pathogen to inhibit tick feeding and thus prevent transmission of tick-borne pathogens to humans and wildlife reservoirs. This review outlines the history of Lyme disease vaccines and this movement to anti-tick vaccine approaches.

Electronic Health Record Data for Lyme Disease Surveillance, Massachusetts, USA, 2017-2018

Lyme disease surveillance based on provider and laboratory reports underestimates incidence. We developed an algorithm for automating surveillance using electronic health record data. We identified potential Lyme disease markers in electronic health record data (laboratory tests, diagnosis codes, prescriptions) from January 2017-December 2018 in 2 large practice groups in Massachusetts, USA. We calculated their sensitivities and positive predictive values (PPV), alone and in combination, relative to medical record review. Sensitivities ranged from 57% (95% CI 47%-69%) for immunoassays to 87% (95% CI 70%-100%) for diagnosis codes. PPVs ranged from 53% (95% CI 43%-61%) for diagnosis codes to 58% (95% CI 50%-66%) for immunoassays. The combination of a diagnosis code and antibiotics within 14 days or a positive Western blot had a sensitivity of 100% (95% CI 86%-100%) and PPV of 82% (95% CI 75%-89%). This algorithm could make Lyme disease surveillance more efficient and consistent.

Diagnostic Challenges of Lyme Neuroborreliosis in Inpatient Neurology: A Case Series

Lyme disease is a multisystem disorder transmitted through the Ixodes tick and is most commonly diagnosed in northeastern and mid-Atlantic states, Wisconsin, and Minnesota, though its disease borders are expanding in the setting of climate change. Approximately 10%-15% of untreated Lyme disease cases will develop neurologic manifestations of Lyme neuroborreliosis (LNB). Due to varying presentations, LNB presents diagnostic challenges and is associated with a delay to treatment. We discuss three cases of LNB admitted to our referral center in a traditionally low-incidence state to highlight clinical pearls in LNB diagnosis. Three patients from low-incidence areas with prior diagnostic evaluations presented in August with neurologic manifestations of radiculoneuritis, cranial neuropathies, and/or lymphocytic meningitis. MRI findings included cranial nerve, nerve root, and leptomeningeal enhancement leading to broad differential diagnoses. Lumbar puncture demonstrated lymphocytic pleocytosis (range 85-753 cells/uL) and elevated protein (87-318 mg/dL). Each patient tested positive for Lyme on two-tiered serum testing and was diagnosed with LNB. All three cases were associated with a delay to health care presentation (mean 20 days) and a delay to diagnosis and treatment (mean 54 days) due to under-recognition and ongoing evaluation. With the geographic expansion of Lyme disease, increasing awareness of LNB manifestations and acquiring detailed travel histories in low-incidence areas is crucial to prompt delivery of care. Clinicians should be aware of two-tiered serum diagnostic requirements and use adjunctive studies such as lumbar puncture and MRI to eliminate other diagnoses. Treatment with an appropriate course of antibiotics leads to robust improvement in neurological symptoms.

Late-stage borreliosis and substance abuse

Background

Infectious diseases can contribute to substance abuse. Here, a fatal case of borreliosis and substance abuse is reported. This patient had a history of multiple tick bites and increasing multisystem symptoms, yet diagnosis and treatment were delayed. He experimented with multiple substances including phencyclidine (PCP), an N-methyl-d-aspartate (NMDA) receptor antagonist that opposes NMDA agonism caused by Borrelia infection. During PCP withdrawal, he committed one homicide, two assaults, and suicide.

Methods

Brain tissue was obtained from autopsy and stained for microglial activation and quinolinic acid (QA). Immunoflouresence (IFA) and fluorescence in situ hybridization (FISH) were used to identify the presence of pathogens in autopsy tissue.

Results

Autopsy tissue evaluation demonstrated Borrelia in the pancreas by IFA and heart by IFA and FISH. Activated microglia and QA were found in the brain, indicating neuroinflammation. It is postulated that PCP withdrawal may exacerbate symptoms produced by Borrelia-induced biochemical imbalances in the brain. This combination may have greatly increased his acute homicidal and suicidal risk. Patient databases also demonstrated the risk of homicide or suicide in patients diagnosed with borreliosis and confirmed multiple symptoms in these patients, including chronic pain, anxiety, and anhedonia.

Conclusions

Late-stage borreliosis is associated with multiple symptoms that may contribute to an increased risk of substance abuse and addictive disorders. More effective diagnosis and treatment of borreliosis, and attention to substance abuse potential may help reduce associated morbidity and mortality in patients with borreliosis, particularly in endemic areas.

Distribution and pathogen prevalence of field-collected ticks from south-western Korea: a study from 2019 to 2022

Hard ticks are known vectors of various pathogens, including the severe fever with thrombocytopenia syndrome virus, Rickettsia spp., Coxiella burnetii, Borrelia spp., Anaplasma phagocytophilum, and Ehrlichia spp. This study aims to investigate the distribution and prevalence of tick-borne pathogens in southwestern Korea from 2019 to 2022. A total of 13,280 ticks were collected during the study period, with H. longicornis accounting for 86.1% of the collected ticks. H. flava, I. nipponensis and A. testudinarium comprised 9.4%, 3.6%, and 0.8% of the ticks, respectively. Among 983 pools tested, Rickettsia spp. (216 pools, 1.6% MIR) were the most prevalent pathogens across all tick species, with R. japonica and R. monacensis frequently detected in I. nipponensis and Haemaphysalis spp., respectively. Borrelia spp. (28 pools, 0.2% MIR) were predominantly detected in I. nipponensis (27 pools, 13.8% MIR, P < 0.001). Co-infections, mainly involving Rickettsia monacensis and Borrelia afzelii, were detected in I. nipponensis. Notably, this study identified R. monacensis for the first time in A. testudinarium in South Korea. These findings offer valuable insights into the tick population and associated pathogens in the region, underscoring the importance of tick-borne disease surveillance and prevention measures.

Periprosthetic Joint Infection Risk After Primary Total Knee Arthroplasty: Are All Preoperative Corticosteroid Injections the Same?

BACKGROUND

Previous evidence has demonstrated an increased risk of periprosthetic joint infection (PJI) following primary total knee arthroplasty (TKA) in patients receiving corticosteroid injection (CSI) within 3 months of surgery. The study aimed to determine if PJI risk after TKA varied among different corticosteroid agents.

METHODS

A total of 85,073 patients undergoing primary TKA from 2009 to 2019 were identified from a large national database. Of these, 1,092 (1.3%) received an ipsilateral, intra-articular CSI within 90 days of TKA. These patients were compared to those not receiving CSI using multivariate logistic regressions following 1:4 propensity score matching, with PJI development as the primary outcome.

RESULTS

Patients given an injection of any corticosteroid within 90 days of TKA had significantly higher PJI rates compared to controls (1.6 versus 0.41%; P < .001). This finding was driven by patients receiving methylprednisolone acetate (n = 543) or betamethasone (n = 153), with prevalence rates of 1.7 and 2.6%, respectively (P = .003 and P = .01, respectively). No significant increase in the rate of PJI was observed for patients receiving triamcinolone (1.2%; P = .08; n = 342) or dexamethasone (0.0%; P = 1; n = 54) within 90 days preceding TKA. PJI risk for all agents, administered more than 90 days preoperatively normalized to control levels (0.51 versus 0.34%).

CONCLUSIONS

These results suggest that PJI risk varies with CSI type. In this large database study, only patients given methylprednisolone acetate or betamethasone injections within 90 days of surgery had significantly higher PJI rates compared to controls.

Trends in Costs and Professional Reimbursements for Revision Total Hip and Knee Arthroplasty

BACKGROUND

With increasing numbers of revision total hip and total knee arthroplasties (rTHAs and rTKAs), understanding trends in related out-of-pocket (OOP) costs, overall costs, and provider reimbursements is critical to improve patient access to care.

METHODS

A large database was used to identify 92,116 patients who underwent rTHA or rTKA between 2009 and 2018. The OOP costs associated with the surgery and related inpatient care were calculated as the sum of copayment, coinsurance, and deductible payments. Professional reimbursement was calculated as total payments to the principal physician. All monetary data were adjusted to 2018 dollars. Multivariate regressions evaluated the associations between costs and procedure type, insurance type, and region of service.

RESULTS

From 2009 to 2018, overall costs for rTHA significantly increased by 35.0% and overall costs for rTKA significantly increased by 32.3%. The OOP costs for rTHA had no significant changes, while OOP costs for rTKA increased by 20.1%, with patients on Medicare plans having the lowest OOP costs. Professional reimbursements, when measured as a percentage of overall costs, decreased significantly by 4.4% for rTHA and 4.0% for rTKA, with the lowest reimbursements from Medicare plans.

CONCLUSION

From 2009 to 2018, total costs related to rTHA and rTKA significantly increased. The OOP costs significantly increased for rTKA, and professional reimbursements for both rTHA and rTKA decreased relative to total costs. Overall, these trends may combine to create greater financial burden to patients and the healthcare system, as well as further limit patients' access to revision arthroplasty care.

Assessing knowledge gaps and empowering Extension workers in Illinois with information on ticks and tickborne diseases through KAP surveys

Tickborne diseases (TBDs) are increasingly prevalent in Illinois and the Upper Midwest region. People who work in occupations that require time outdoors in agricultural or natural settings, such as some Extension workers, are at risk of tick bites and TBDs. Additionally, Extension workers are often a primary source of information about ticks and TBDs in rural communities. However, there is limited information on the level of awareness about ticks and TBDs in the Extension community. The goals of this study were to sequentially i) determine the baseline awareness of Extension workers in Illinois about ticks and TBDs using a knowledge, attitudes, and practices (KAP) survey tool, ii) provide comprehensive training on ticks and TBDs to this demographic, and iii) measure the uptake of knowledge after the training intervention through a post-training survey. The study period was from June 2022 until May 2023. We received 233 pre-training and 93 paired post-training survey responses. Most survey respondents were Extension volunteers, identified as women, and were over 50 years old. Knowledge about ticks and TBDs varied. We identified several gaps in their current tick awareness, most importantly, in tick prevention measures, tick identification, and TBDs in general. TBD knowledge, attitude, and practice scores all significantly improved after training (p < 0.001), with a mean difference of 10.47, 1.49, and 2.64 points, respectively. Additionally, both Extension professionals (79.2 %) and Extension volunteers (66.7 %) were more likely to feel confident in engaging with their stakeholders on ticks and TBDs after participating in training. Poisson models revealed that higher attitude and practice scores and greater self-reported knowledge were the factors most significantly associated with higher TBD knowledge. We found that greater concern for ticks and TBD (attitudes) and adherence to science-based prevention and management methods (practices) were also associated with higher knowledge scores. To our knowledge, this is the first study in Illinois to capture Extension workers' awareness of ticks and TBDs. The results highlight Extension workers' interest in filling knowledge gaps through learning, and the importance of training Extension workers to disseminate reliable and updated information on ticks and TBDs to their constituents, a critical step in preventing TBDs.

A tick saliva serpin, IxsS17 inhibits host innate immune system proteases and enhances host colonization by Lyme disease agent

Lyme disease (LD) caused by Borrelia burgdorferi is among the most important human vector borne diseases for which there is no effective prevention method. Identification of tick saliva transmission factors of the LD agent is needed before the highly advocated tick antigen-based vaccine could be developed. We previously reported the highly conserved Ixodes scapularis (Ixs) tick saliva serpin (S) 17 (IxsS17) was highly secreted by B. burgdorferi infected nymphs. Here, we show that IxsS17 promote tick feeding and enhances B. burgdorferi colonization of the host. We show that IxsS17 is not part of a redundant system, and its functional domain reactive center loop (RCL) is 100% conserved in all tick species. Yeast expressed recombinant (r) IxsS17 inhibits effector proteases of inflammation, blood clotting, and complement innate immune systems. Interestingly, differential precipitation analysis revealed novel functional insights that IxsS17 interacts with both effector proteases and regulatory protease inhibitors. For instance, rIxsS17 interacted with blood clotting proteases, fXII, fX, fXII, plasmin, and plasma kallikrein alongside blood clotting regulatory serpins (antithrombin III and heparin cofactor II). Similarly, rIxsS17 interacted with both complement system serine proteases, C1s, C2, and factor I and the regulatory serpin, plasma protease C1 inhibitor. Consistently, we validated that rIxsS17 dose dependently blocked deposition of the complement membrane attack complex via the lectin complement pathway and protected complement sensitive B. burgdorferi from complement-mediated killing. Likewise, co-inoculating C3H/HeN mice with rIxsS17 and B. burgdorferi significantly enhanced colonization of mouse heart and skin organs in a reverse dose dependent manner. Taken together, our data suggests an important role for IxsS17 in tick feeding and B. burgdorferi colonization of the host.

Highly heterogenous humoral immune response in Lyme disease patients revealed by broad machine learning-assisted antibody binding profiling with random peptide arrays

Introduction

Lyme disease (LD), a rapidly growing public health problem in the US, represents a formidable challenge due to the lack of detailed understanding about how the human immune system responds to its pathogen, the Borrelia burgdorferi bacterium. Despite significant advances in gaining deeper insight into mechanisms the pathogen uses to evade immune response, substantial gaps remain. As a result, molecular tools for the disease diagnosis are lacking with the currently available tests showing poor performance. High interpersonal variability in immune response combined with the ability of the pathogen to use a number of immune evasive tactics have been implicated as underlying factors for the limited test performance.

Methods

This study was designed to perform a broad profiling of the entire repertoire of circulating antibodies in human sera at the single-individual level using planar arrays of short linear peptides with random sequences. The peptides sample sparsely, but uniformly the entire combinatorial sequence space of the same length peptides for profiling the humoral immune response to a B.burg. infection and compare them with other diseases with etiology similar to LD and healthy controls.

Results

The study revealed substantial variability in antibody binding profiles between individual LD patients even to the same antigen (VlsE protein) and strong similarity between individuals diagnosed with Lyme disease and healthy controls from the areas endemic to LD suggesting a high prevalence of seropositivity in endemic healthy control.

Discussion

This work demonstrates the utility of the approach as a valuable analytical tool for agnostic profiling of humoral immune response to a pathogen.

Patterns and Trends in Continuous Glucose Monitoring Utilization Among Commercially Insured Individuals With Type 1 Diabetes: 2010-2013 to 2016-2019

Prior studies suggest that only ∼30% of patients with type 1 diabetes use continuous glucose monitoring (CGM), but most studies to date focused on children and young adults seen by endocrinologists or in academic centers. This study examined national trends in CGM utilization among commercially insured children and adults with type 1 diabetes. Overall, CGM utilization was 20.12% in 2010-2013 and 49.78% in 2016-2019, reflecting a 2.5-fold increase in utilization within a period of <10 years. Identifying populations with low CGM use is a necessary first step in developing targeted interventions to increase CGM uptake.

Pediatric and Young Adult Household Transmission of the Initial Waves of SARS-CoV-2 in the United States: Administrative Claims Study

BACKGROUND

The correlates responsible for the temporal changes of intrahousehold SARS-CoV-2 transmission in the United States have been understudied mainly due to a lack of available surveillance data. Specifically, early analyses of SARS-CoV-2 household secondary attack rates (SARs) were small in sample size and conducted cross-sectionally at single time points. From these limited data, it has been difficult to assess the role that different risk factors have had on intrahousehold disease transmission in different stages of the ongoing COVID-19 pandemic, particularly in children and youth.

OBJECTIVE

This study aimed to estimate the transmission dynamic and infectivity of SARS-CoV-2 among pediatric and young adult index cases (age 0 to 25 years) in the United States through the initial waves of the pandemic.

METHODS

Using administrative claims, we analyzed 19 million SARS-CoV-2 test records between January 2020 and February 2021. We identified 36,241 households with pediatric index cases and calculated household SARs utilizing complete case information. Using a retrospective cohort design, we estimated the household SARS-CoV-2 transmission between 4 index age groups (0 to 4 years, 5 to 11 years, 12 to 17 years, and 18 to 25 years) while adjusting for sex, family size, quarter of first SARS-CoV-2 positive record, and residential regions of the index cases.

RESULTS

After filtering all household records for greater than one member in a household and missing information, only 36,241 (0.85%) of 4,270,130 households with a pediatric case remained in the analysis. Index cases aged between 0 and 17 years were a minority of the total index cases (n=11,484, 11%). The overall SAR of SARS-CoV-2 was 23.04% (95% CI 21.88-24.19). As a comparison, the SAR for all ages (0 to 65+ years) was 32.4% (95% CI 32.1-32.8), higher than the SAR for the population between 0 and 25 years of age. The highest SAR of 38.3% was observed in April 2020 (95% CI 31.6-45), while the lowest SAR of 15.6% was observed in September 2020 (95% CI 13.9-17.3). It consistently decreased from 32% to 21.1% as the age of index groups increased. In a multiple logistic regression analysis, we found that the youngest pediatric age group (0 to 4 years) had 1.69 times (95% CI 1.42-2.00) the odds of SARS-CoV-2 transmission to any family members when compared with the oldest group (18 to 25 years). Family size was significantly associated with household viral transmission (odds ratio 2.66, 95% CI 2.58-2.74).

CONCLUSIONS

Using retrospective claims data, the pediatric index transmission of SARS-CoV-2 during the initial waves of the COVID-19 pandemic in the United States was associated with location and family characteristics. Pediatric SAR (0 to 25 years) was less than the SAR for all age other groups. Less than 1% (n=36,241) of all household data were retained in the retrospective study for complete case analysis, perhaps biasing our findings. We have provided measures of baseline household pediatric transmission for tracking and comparing the infectivity of later SARS-CoV-2 variants.

Pediatric Lyme disease: systematic assessment of post-treatment symptoms and quality of life

BACKGROUND

Lyme disease is common among children and adolescents. Antibiotic treatment is effective, yet some patients report persistent symptoms following treatment, with or without functional impairment. This study characterized long-term outcome of pediatric patients with Lyme disease and evaluated the case definition of post-treatment Lyme disease (PTLD) syndrome.

METHODS

The sample included 102 children with confirmed Lyme disease diagnosed 6 months-10 years prior to enrollment (M = 2.0 years). Lyme diagnosis and treatment information was extracted from the electronic health record; parent report identified presence, duration, and impact of symptoms after treatment. Participants completed validated questionnaires assessing health-related quality of life, physical mobility, fatigue, pain, and cognitive impact.

RESULTS

Most parents reported their child's symptoms resolved completely, although time to full resolution varied. Twenty-two parents (22%) indicated their child had at least one persistent symptom >6 months post-treatment, 13 without functional impairment (PTLD symptoms) and 9 with functional impairment (PTLD syndrome). Children with PTLD syndrome had lower parent-reported Physical Summary scores and greater likelihood of elevated fatigue.

CONCLUSIONS

In the current study, most children with Lyme disease experienced full resolution of symptoms, including those who initially met PTLD syndrome criteria. Effective communication about recovery rates and common symptoms that may persist post-treatment is needed.

IMPACT

The majority of pediatric patients treated for all stages of Lyme disease reported full resolution of symptoms within 6 months. 22% of pediatric patients reported one or more symptom persisting >6 months, 9% with and 13% without accompanying functional impairment. Effective communication with families about recovery rates and common symptoms that may persist post-treatment of Lyme disease is needed.

Lung Cancer Prediction Using Electronic Claims Records: A Transformer-Based Approach

Electronic claims records (ECRs) are large scale and longitudinal collections of individual's medical service seeking actions. Compared to in-hospital medical records (EMRs), ECRs are more standardized and cross-sites. Recently, there has been studies showing promising results on modeling claims data for a wide range of medical applications. However, few of them address the exclusion criteria on cohort selection to extract new incidence without prior signs and also often lack of emphasis on predicting cancer in early stages. In this work, we aim to design a lung cancer prediction framework using ECRs with rigorous exclusion design using state-of-the-art sequence-based transformer. Furthermore, this work presents one of the first results by applying disease prediction model to the entire population in Taiwan. The result shows over 2.1 predictive power, 5 average positive predictive value (PPV), and 0.668 area under curve (AUC) in all-stage lung cancer and around 2.0 predictive power, 1 average PPV and 0.645 AUC in early-stage in our dataset. Sub-cohort analysis could funnel high precision selective group into prioritized clinical examination. Onset analysis validates the effect of our exclusion criteria. This work presents comprehensive analyses on lung cancer prediction, and the proposed approach can serve as a state-of-the-art disease risk prediction framework on claims data.

Resource selection by New York City deer reveals the effective interface between wildlife, zoonotic hazards and humans

Although the role of host movement in shaping infectious disease dynamics is widely acknowledged, methodological separation between animal movement and disease ecology has prevented researchers from leveraging empirical insights from movement data to advance landscape scale understanding of infectious disease risk. To address this knowledge gap, we examine how movement behaviour and resource utilization by white-tailed deer (Odocoileus virginianus) determines blacklegged tick (Ixodes scapularis) distribution, which depend on deer for dispersal in a highly fragmented New York City borough. Multi-scale hierarchical resource selection analysis and movement modelling provide insight into how deer's movements contribute to the risk landscape for human exposure to the Lyme disease vector-I. scapularis. We find deer select highly vegetated and accessible residential properties which support blacklegged tick survival. We conclude the distribution of tick-borne disease risk results from the individual resource selection by deer across spatial scales in response to habitat fragmentation and anthropogenic disturbances.

Is There a Role for Dark Field Microscopy in the Diagnosis of Lyme Disease?A Narrative Review

The diagnosis of Lyme disease is becoming more common in Turkey. Nonetheless, some physicians are not aware of the diagnostic principles that should be followed when faced with a suspected patient and could use tests that are not recommended, such as darkfield microscopy. Dark field microscopy is a diagnostic technique to visualize the spirochetes that cause Lyme disease; however, it is not recommended for the diagnosis of Lyme disease. One of the main limitations of dark field microscopy is its low sensitivity. Another limitation is its high false-positivity rate, as other microorganisms and cellular debris can be mistaken for spirochetes, leading to a misdiagnosis thatmay result in unnecessary treatment. Therefore, this study aimed to review the literature on the role of dark field microscopy as a diagnostic method for Lyme disease and inform physicians about recommended approaches in line with the recommendations of national or international guidelines. An electronic search of Pubmed, Scopus, and Web of Science was performed using the following medical subject headings (MeSH) search terms: Lyme borreliosis, Lyme disease, Borrelia burgdorferi, diagnosis, and microscopy. With this narrative review, we aimed to inform physicians better and improve patient care for patients with suspected Lyme disease.

Single-cell RNA sequencing of murine ankle joints over time reveals distinct transcriptional changes following Borrelia burgdorferi infection

Lyme disease is caused by the bacterial pathogen Borrelia burgdorferi, which can be readily modeled in laboratory mice. In order to understand the cellular and transcriptional changes that occur during B. burgdorferi infection, we conducted single-cell RNA sequencing (scRNA-seq) of ankle joints of infected C57BL/6 mice over time. We found that macrophages/monocytes, T cells, synoviocytes and fibroblasts all showed significant differences in gene expression of both inflammatory and non-inflammatory genes that peaked early and returned to baseline before the typical resolution of arthritis. Predictions of cellular interactions showed that macrophages appear to communicate extensively between different clusters of macrophages as well as with fibroblasts and synoviocytes. Our data give unique insights into the interactions between B. burgdorferi and the murine immune system over time and allow for a better understanding of mechanisms by which the dysregulation of the immune response may lead to prolonged symptoms in some patients.

Identifying Potential Lyme Disease Cases Using Self-Reported Worldwide Tweets: Deep Learning Modeling Approach Enhanced With Sentimental Words Through Emojis

BACKGROUND

Lyme disease is among the most reported tick-borne diseases worldwide, making it a major ongoing public health concern. An effective Lyme disease case reporting system depends on timely diagnosis and reporting by health care professionals, and accurate laboratory testing and interpretation for clinical diagnosis validation. A lack of these can lead to delayed diagnosis and treatment, which can exacerbate the severity of Lyme disease symptoms. Therefore, there is a need to improve the monitoring of Lyme disease by using other data sources, such as web-based data.

OBJECTIVE

We analyzed global Twitter data to understand its potential and limitations as a tool for Lyme disease surveillance. We propose a transformer-based classification system to identify potential Lyme disease cases using self-reported tweets.

METHODS

Our initial sample included 20,000 tweets collected worldwide from a database of over 1.3 million Lyme disease tweets. After preprocessing and geolocating tweets, tweets in a subset of the initial sample were manually labeled as potential Lyme disease cases or non-Lyme disease cases using carefully selected keywords. Emojis were converted to sentiment words, which were then replaced in the tweets. This labeled tweet set was used for the training, validation, and performance testing of DistilBERT (distilled version of BERT [Bidirectional Encoder Representations from Transformers]), ALBERT (A Lite BERT), and BERTweet (BERT for English Tweets) classifiers.

RESULTS

The empirical results showed that BERTweet was the best classifier among all evaluated models (average F1-score of 89.3%, classification accuracy of 90.0%, and precision of 97.1%). However, for recall, term frequency-inverse document frequency and k-nearest neighbors performed better (93.2% and 82.6%, respectively). On using emojis to enrich the tweet embeddings, BERTweet had an increased recall (8% increase), DistilBERT had an increased F1-score of 93.8% (4% increase) and classification accuracy of 94.1% (4% increase), and ALBERT had an increased F1-score of 93.1% (5% increase) and classification accuracy of 93.9% (5% increase). The general awareness of Lyme disease was high in the United States, the United Kingdom, Australia, and Canada, with self-reported potential cases of Lyme disease from these countries accounting for around 50% (9939/20,000) of the collected English-language tweets, whereas Lyme disease-related tweets were rare in countries from Africa and Asia. The most reported Lyme disease-related symptoms in the data were rash, fatigue, fever, and arthritis, while symptoms, such as lymphadenopathy, palpitations, swollen lymph nodes, neck stiffness, and arrythmia, were uncommon, in accordance with Lyme disease symptom frequency.

CONCLUSIONS

The study highlights the robustness of BERTweet and DistilBERT as classifiers for potential cases of Lyme disease from self-reported data. The results demonstrated that emojis are effective for enrichment, thereby improving the accuracy of tweet embeddings and the performance of classifiers. Specifically, emojis reflecting sadness, empathy, and encouragement can reduce false negatives.