Affiliations: [a] Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen, and Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany | [b] Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA | [c] Department of Psychiatry and Psychotherapy, Charité Berlin, Berlin, Germany | [d] Department of Psychiatry and Psychotherapy, Georg-August Universität Göttingen, Göttingen, Germany
Correspondence:
[*]
Correspondence to: Prof. Dr. med. Piotr Lewczuk, Lab for Clinical Neurochemistry and Neurochemical Dementia Diagnostics, Department of Psychiatry and Psychotherapy, Schwabachanlage 6, 91054 Erlangen, Germany. Tel.: +49 9131 85 34324; Fax: +49 9131 85 34238; [email protected]
Note: [1] These authors contributed equally to this work and should be considered the first author.
Abstract:
Background: In previous studies, a dichotomous stratification of subjects into “cerebrospinal fluid (CSF) normal” and “CSF pathologic” was used to investigate the role of biomarkers in the prediction of progression to dementia in pre-dementia/mild cognitive impairment subjects. With the previously published Erlangen Score Algorithm, we suggested a division of CSF patterns into five groups, covering all possible CSF result combinations based on the presence of pathologic tau and/or amyloid-β CSF values.
Objective: This study aimed to validate the Erlangen Score diagnostic algorithm based on the results of biomarkers analyses obtained in different patients cohorts, with different pre-analytical protocols, and with different laboratory analytical platforms.
Methods: We evaluated the algorithm in two cohorts of pre-dementia subjects: the US-Alzheimer’s Disease Neuroimaging Initiative and the German Dementia Competence Network.
Results: In both cohorts, the Erlangen scores were strongly associated with progression to Alzheimer’s disease. Neither the scores of the progressors nor the scores of the non-progressors differed significantly between the two projects, in spite of significant differences in the cohorts, laboratory methods, and the samples treatment.
Conclusions: Our findings confirm the utility of the Erlangen Score algorithm as a useful tool in the early neurochemical diagnosis of Alzheimer’s disease.
