ArticleNature communications2025
The diagnostic potential of proteomics and machine learning in Lyme neuroborreliosis.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Serum Borrelia IgG as a rule-out test in suspected lyme neuroborreliosis: a large retrospective cohort study.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026Article
- Biomarkers of Lyme neuroborreliosis: a systematic review.Infection · 2026Review
- Edema as a Key Presentation of Acrodermatitis Chronica Atrophicans: A Retrospective Cohort Study from a Tertiary Setting in Denmark 2017-2025.Diagnostics (Basel, Switzerland) · 2026Article
- From forest floor to doctor's office: the immunological journey ofFrontiers in immunology · 2026Review
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Lyme neuroborreliosis (LNB), a nervous system infection caused by tick-borne spirochetes of the Borrelia burgdorferi sensu lato complex, is among the most frequent bacterial infections of the nervous system in Europe. Early diagnosis and continuous monitoring remain challenging due to limited sensitivity and specificity of current methods and requires invasive lumbar punctures, underscoring the need for improved, less invasive diagnostic tools. Here, we apply mass spectrometry-based proteomics to analyse 308 cerebrospinal fluid (CSF) samples and 207 plasma samples from patients with LNB, viral meningitis, controls and other manifestations of Lyme borreliosis. Diagnostic panels of regulated proteins are identified and evaluated through machine learning-assisted proteome analyses. In CSF, the classifier distinguishes LNB from viral meningitis and controls with AUCs of 0.92 and 0.90, respectively. In plasma, LNB is distinguished from controls with an AUC of 0.80. Our findings suggest a potential diagnostic role for machine learning-assisted proteomics in adults with LNB.
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Registered trials
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