ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2015
Development of a metabolic biosignature for detection of early Lyme disease.
Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 1 of them a synthesis that pooled it.
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Who cites it
48 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Metabolites of prostaglandin synthases as potential biomarkers of Lyme disease severity and symptom resolution.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2019Pooled it
- Machine learning-driven identification of virulence determinants in Borrelia burgdorferi associated with human dissemination.PLoS computational biology · 2026Article
- Application of Mass Spectrometry-Based Metabolomics and Machine Learning in the Diagnostics of Lyme Neuroborreliosis.ACS omega · 2026Article
- From forest floor to doctor's office: the immunological journey ofFrontiers in immunology · 2026Review
- Metabolomics-Based Machine Learning Diagnostics of Post-Acute Sequelae of SARS-CoV-2 Infection.Metabolites · 2025Article
- External Validation of Raman Spectroscopy for Lyme Disease Diagnostics.Journal of biophotonics · 2025Article
- UHPLC-MS/MS-based untargeted metabolite profiling of Lyme neuroborreliosis.Scientific reports · 2025Article
- Insights From Omics in Lyme Disease.The Journal of infectious diseases · 2024Review
- Cholesterol Contributes to Risk, Severity, and Machine Learning-Driven Diagnosis of Lyme Disease.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023Article
- Touching Base with Some Mediterranean Diseases of Interest from Paradigmatic Cases at the "Magna Graecia" University Unit of Infectious Diseases: A Didascalic Review.Diagnostics (Basel, Switzerland) · 2023Review
- Lyme borreliosis diagnosis: state of the art of improvements and innovations.BMC microbiology · 2023Review
- Large-Scale Sequencing ofGenes · 2022Review
- The glycerol-3-phosphate dehydrogenases GpsA and GlpD constitute the oxidoreductive metabolic linchpin for Lyme disease spirochete host infectivity and persistence in the tick.PLoS pathogens · 2022Article
- Biomarker selection and a prospective metabolite-based machine learning diagnostic for lyme disease.Scientific reports · 2022Article
- A diagnostic classifier for gene expression-based identification of early Lyme disease.Communications medicine · 2022Article
- Testing Raman spectroscopy as a diagnostic approach for Lyme disease patients.Frontiers in cellular and infection microbiology · 2022Article
- Metabolic Response in Patients With Post-treatment Lyme Disease Symptoms/Syndrome.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2021Article
- Discovery and Surveillance of Tick-Borne Pathogens.Journal of medical entomology · 2021Article
- Quantitative multiplexed strategies for human Lyme disease serological testing.Experimental biology and medicine (Maywood, N.J.) · 2021Review
- Laboratory Diagnosis of Lyme Borreliosis.Clinical microbiology reviews · 2021Review
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
backgroundEarly Lyme disease patients often present to the clinic prior to developing a detectable antibody response to Borrelia burgdorferi, the etiologic agent. Thus, existing 2-tier serology-based assays yield low sensitivities (29%-40%) for early infection. The lack of an accurate laboratory test for early Lyme disease contributes to misconceptions about diagnosis and treatment, and underscores the need for new diagnostic approaches.
methodsRetrospective serum samples from patients with early Lyme disease, other diseases, and healthy controls were analyzed for small molecule metabolites by liquid chromatography-mass spectrometry (LC-MS). A metabolomics data workflow was applied to select a biosignature for classifying early Lyme disease and non-Lyme disease patients. A statistical model of the biosignature was trained using the patients' LC-MS data, and subsequently applied as an experimental diagnostic tool with LC-MS data from additional patient sera. The accuracy of this method was compared with standard 2-tier serology.
resultsMetabolic biosignature development selected 95 molecular features that distinguished early Lyme disease patients from healthy controls. Statistical modeling reduced the biosignature to 44 molecular features, and correctly classified early Lyme disease patients and healthy controls with a sensitivity of 88% (84%-95%), and a specificity of 95% (90%-100%). Importantly, the metabolic biosignature correctly classified 77%-95% of the of serology negative Lyme disease patients.
conclusionsThe data provide proof-of-concept that metabolic profiling for early Lyme disease can achieve significantly greater (P < .0001) diagnostic sensitivity than current 2-tier serology, while retaining high specificity.
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