Lewczuk Piotr, Kornhuber Johannes, Toledo Jon B, Trojanowski John Q, Knapik-Czajka Malgorzata, Peters Oliver, Wiltfang Jens, Shaw Leslie M
Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen, and Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany.
Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
J Alzheimers Dis. 2015;48(2):433-41. doi: 10.3233/JAD-150342.
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.
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.
We evaluated the algorithm in two cohorts of pre-dementia subjects: the US-Alzheimer's Disease Neuroimaging Initiative and the German Dementia Competence Network.
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.
Our findings confirm the utility of the Erlangen Score algorithm as a useful tool in the early neurochemical diagnosis of Alzheimer's disease.
在以往的研究中，将受试者二分法分层为“脑脊液（CSF）正常”和“CSF病理状态”，以研究生物标志物在预测痴呆前期/轻度认知障碍受试者进展为痴呆中的作用。基于之前发表的埃尔朗根评分算法，我们建议将CSF模式分为五组，涵盖基于病理性tau和/或淀粉样β蛋白CSF值存在的所有可能的CSF结果组合。
本研究旨在基于在不同患者队列、不同分析前方案以及不同实验室分析平台上获得的生物标志物分析结果，验证埃尔朗根评分诊断算法。
我们在两个痴呆前期受试者队列中评估了该算法：美国阿尔茨海默病神经影像倡议队列和德国痴呆症能力网络队列。
在两个队列中，埃尔朗根评分均与进展为阿尔茨海默病密切相关。尽管两个项目在队列、实验室方法和样本处理方面存在显著差异，但进展者和非进展者的评分在两个项目之间均无显著差异。
我们的研究结果证实了埃尔朗根评分算法作为阿尔茨海默病早期神经化学诊断有用工具的实用性。
