Metabolic Response in Patients With Post-treatment Lyme Disease Symptoms/Syndrome

Author:

Fitzgerald Bryna L1ORCID,Graham Barbara2,Delorey Mark J1,Pegalajar-Jurado Adoracion1,Islam M Nurul2,Wormser Gary P3,Aucott John N4,Rebman Alison W4,Soloski Mark J4,Belisle John T2,Molins Claudia R1

Affiliation:

1. Centers for Disease Control and Prevention, Fort Collins, Colorado, USA

2. Department of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, Colorado, USA

3. Division of Infectious Diseases, New York Medical College, Valhalla, New York, USA

4. The Lyme Disease Research Center, Division of Rheumatology, Department of Medicine, Johns Hopkins University School of Medicine, Lutherville, Maryland, USA

Abstract

Abstract Background Post-treatment Lyme disease symptoms/syndrome (PTLDS) occurs in approximately 10% of patients with Lyme disease following antibiotic treatment. Biomarkers or specific clinical symptoms to identify patients with PTLDS do not currently exist and the PTLDS classification is based on the report of persistent, subjective symptoms for ≥6 months following antibiotic treatment for Lyme disease. Methods Untargeted liquid chromatography–mass spectrometry metabolomics was used to determine longitudinal metabolic responses and biosignatures in PTLDS and clinically cured non-PTLDS Lyme patients. Evaluation of biosignatures included (1) defining altered classes of metabolites, (2) elastic net regularization to define metabolites that most strongly defined PTLDS and non-PTLDS patients at different time points, (3) changes in the longitudinal abundance of metabolites, and (4) linear discriminant analysis to evaluate robustness in a second patient cohort. Results This study determined that observable metabolic differences exist between PTLDS and non-PTLDS patients at multiple time points. The metabolites with differential abundance included those from glycerophospholipid, bile acid, and acylcarnitine metabolism. Distinct longitudinal patterns of metabolite abundance indicated a greater metabolic variability in PTLDS versus non-PTLDS patients. Small numbers of metabolites (6 to 40) could be used to define PTLDS versus non-PTLDS patients at defined time points, and the findings were validated in a second cohort of PTLDS and non-PTLDS patients. Conclusions These data provide evidence that an objective metabolite-based measurement can distinguish patients with PTLDS and help understand the underlying biochemistry of PTLDS.

Funder

Centers for Disease Control and Prevention

National Institute of Allergy and Infectious Diseases

National Institute of Arthritis and Musculoskeletal and Skin Diseases

Publisher

Oxford University Press (OUP)

Subject

Infectious Diseases,Microbiology (medical)

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