Lyme disease, also known as Lyme borreliosis, is a tick-borne disease caused by the Borrelia burgdorferi bacterium. It is the most common vector-borne disease in the Northern Hemisphere. If left untreated, infection can spread to joints, the heart, and the nervous system. Lyme disease is difficult to diagnose due to variability in signs and symptoms that are often flu-like in nature. Definitive diagnosis requires laboratory testing as early clinical signs are usually non-specific. Although detection of Lyme antibodies remains the mainstay of diagnosis, advanced diagnostic techniques are being developed to improve early diagnosis. This article discusses the challenges in Lyme disease diagnostics and recent advancements being made.
Challenges in Diagnosis
Early localized infection is difficult to diagnose clinically as symptoms mimic many other common illnesses like the flu. A challenge is that not all infected individuals develop objective signs of illness. According to CDC, around 80% of patients with early localized Lyme disease develop erythema migrans rash. However, rash is often absent in about 20% of patients which hampers diagnosis.
Testing for antibodies also poses challenges in early infection. It often takes 2-4 weeks after infection for antibodies to develop and be detected by current two-tiered testing which involves ELISA and Western Blot methods. During this period, standard serology may produce false negatives. Even later stage disease diagnosis can be tricky. Some patients may continue to relapse despite treatment due to presence of persistent forms of the bacteria.
Symptoms of disseminated disease affecting multiple organs can resemble various medical conditions like arthritis, cardiovascular involvement or neurological disorders. This overlap with other diseases creates ambiguity in diagnosis based solely on clinical examination. Thus, current diagnostic approaches have limitations in detecting early and late stages of Lyme disease.
Advancements in Diagnostics
Research efforts are underway to develop improved diagnostic methods with higher sensitivity and specificity. One promising solution is utilizing nucleic acid amplification testing. PCR based methods can detect the genetic material of the Lyme disease spirochete directly from body fluids and tissues. This increases detection sensitivity in early localized infection when antibody levels are still low.
Advanced proteomics is also being investigated to identify unique infection biomarkers. Scientists analyzed blood samples from Lyme patients using mass spectrometry to identify disease-specific bacterial protein fragments called peptides. Further studies validated a 10-peptide biomarker panel that differentiated active Lyme infection from uninfected individuals with 90% accuracy. Such proteomic biomarkers could potentially supplement two-tiered testing.
New Diagnostic Tests
Several European diagnostic companies are developing novel diagnostic kits for Lyme disease with higher sensitivity. One test (LymPro) uses recombinant Borrelia antigens and advanced ELISA technique to detect infection-specific antibodies sooner after tick bite. Early studies showed LymPro detected Lyme antibodies on average 12 days faster than current standard two-tier testing.
Another assay under development combines detection of Borrelia specific antibodies along with a biomarker indicative of inflammation directly caused by the spirochetal infection. Called C6 Lyme ELISA, it detects a portion of the bacterial membrane that triggers inflammatory response in humans. Large scale multi-center clinical trials are evaluating the diagnostic accuracy of these novel assays compared to existing methods.
Advancing Diagnosis through AI
Artificial intelligence powered machine learning algorithms are finding new applications in diagnostic medicine. Researchers fed an AI system over 5000 blood test results from Lyme patients and healthy controls. The AI analyzed complex patterns in results to develop a diagnostic model. When tested on an independent validation set, the AI achieved 96% accuracy in identifying Lyme disease, far exceeding current two-tiered testing.
Continued efforts are now focusing on training the AI system with even larger clinically confirmed datasets. The goal is to develop an “artificial clinician” that can assimilate a patient’s symptoms, physical findings and multi-platform laboratory results to provide a definitive diagnosis in a manner comparable to infectious disease experts. While regulatory approvals will take time, AI shows promise in assisting physicians with Lyme disease diagnosis.
Conclusion
Lyme disease presents ongoing challenges in diagnosis due to variability in presentation and limitations of current testing approaches. Advancements like improved molecular, proteomic and AI based diagnostic techniques are being developed and validated in clinical studies. If regulatory approved, these new sensitive assays and artificial intelligence powered diagnostics have the potential to transform Lyme disease diagnosis. Earlier and more definitive detection will help streamline treatment decisions and improve clinical outcomes. Continued research is warranted to develop innovative solutions that can combat this growing public health problem.
*Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it
