Entwicklung einer metabolischen Biosignatur zur Detektion der frühen Lyme-Borreliose
Ein neuer Test soll frühzeitiger Klarheit über eine Borrelieninfektion geben können.
Zur Entwicklung eines neuen Testsysstems wurden metabolische Veränderungen im Körper bei der Infektion im Frühstadium betrachtet. Eine Sensitivtät von 84-95% und eine Spezifität von 90-100% ist beschrieben. Die metabolische Biosignatur soll damit bei 77-95% aller seronegativer Patienten in der Frühphase dazu dienen können, die Erkrankung mit Borrelien frühzeitiger erkennen zu können.
Um welche Borrelienerreger es sich dabei handelt wird im Abstract nicht weiter beschrieben - es ist somit derzeit also überhaupt nicht absehbar, ob dieser Test, falls er zur Anwendung kommt, auf die europäischen Unterschiede der Erregersubtypen 1:1 anwendbar ist.
http://cid.oxfordjournals.org/content/ea...5.abstract
Development of a metabolic biosignature for detection of early Lyme disease
Claudia R. Molins, Laura V. Ashton, Gary P. Wormser, Ann M.Hess4, Mark J. Delorey, Sebabrata Mahapatra, Martin E. Schriefer, and John T. Belisle
Abstract
Background. Early Lyme disease patients often present to the clinic prior to developing a detectable antibody response to Borrelia burgdorferi, the etiologic agent. Thus, existing two-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.
Methods. Retrospective 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 two-tier serology.
Results. Metabolic 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.
Conclusion. The data provide proof-of-concept that metabolic profiling for early Lyme disease can achieve significantly greater (p<0.0001) diagnostic sensitivity than current two-tier serology, while retaining high specificity
Ein neuer Test soll frühzeitiger Klarheit über eine Borrelieninfektion geben können.
Zur Entwicklung eines neuen Testsysstems wurden metabolische Veränderungen im Körper bei der Infektion im Frühstadium betrachtet. Eine Sensitivtät von 84-95% und eine Spezifität von 90-100% ist beschrieben. Die metabolische Biosignatur soll damit bei 77-95% aller seronegativer Patienten in der Frühphase dazu dienen können, die Erkrankung mit Borrelien frühzeitiger erkennen zu können.
Um welche Borrelienerreger es sich dabei handelt wird im Abstract nicht weiter beschrieben - es ist somit derzeit also überhaupt nicht absehbar, ob dieser Test, falls er zur Anwendung kommt, auf die europäischen Unterschiede der Erregersubtypen 1:1 anwendbar ist.
http://cid.oxfordjournals.org/content/ea...5.abstract
Development of a metabolic biosignature for detection of early Lyme disease
Claudia R. Molins, Laura V. Ashton, Gary P. Wormser, Ann M.Hess4, Mark J. Delorey, Sebabrata Mahapatra, Martin E. Schriefer, and John T. Belisle
Abstract
Background. Early Lyme disease patients often present to the clinic prior to developing a detectable antibody response to Borrelia burgdorferi, the etiologic agent. Thus, existing two-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.
Methods. Retrospective 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 two-tier serology.
Results. Metabolic 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.
Conclusion. The data provide proof-of-concept that metabolic profiling for early Lyme disease can achieve significantly greater (p<0.0001) diagnostic sensitivity than current two-tier serology, while retaining high specificity
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