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The development of an IgG avidity Western blot with potential to differentiate patients with active Lyme borreliosis from those with past infection. | LitMetric

AI Article Synopsis

Article Abstract

Objectives: Current serological methods cannot distinguish active from past infection with Borrelia burgdorferi sensu lato. The aim of this study was to develop an IgG avidity Western blot and assess its potential to differentiate patients with early and late Lyme borreliosis (LB) i.e. active disease, from those infected in the past.

Methods: An IgG avidity Western blot was developed. Penalized linear discriminant analysis (PLDA) was employed to compare the Western blot/avidity Western blot profiles of an evaluation panel consisting of 75 sera from patients with early (n = 26) and late (n = 24) LB and past infection (n = 25). The PLDA models produced were used to predict infection stage for 20 well characterised sera from the Centers for Disease Control and Prevention (CDC) Lyme disease serum repository and 112 routine seropositive sera (disease stage unknown), to validate and assess the usefulness of the avidity Western blot/avidity Western blot and PLDA approach.

Results: PLDA correctly classified 40/51 (78%) of patients when early LB and past infection groups in the evaluation panel were compared. Likewise, when late LB and past infection groups were compared, 34/49 (69%) were correct. The resultant PLDA models correctly predicted infection stage for 18/20 (90%) of the CDC sera, validating the use of the avidity Western blot/avidity Western blot and PLDA approach. When tested with the routine sera, 21/29 (72%) tested with the early LB vs. past infection model were correct but only 32/83 (39%) with the late LB vs. past infection model. Past infection was predicted for 40/112 (35%) of the routine sera, 80% of which correlated with the clinical picture.

Conclusion: The Western blot/avidity Western blot with PLDA approach shows exciting potential for being able to predict disease stage in some patients with LB, which could improve patient management.

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Source
http://dx.doi.org/10.1016/j.mimet.2018.02.002DOI Listing

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