Dataset Information

Validation of the Erlangen Score Algorithm for Differential Dementia Diagnosis in Autopsy-Confirmed Subjects.

ABSTRACT: BACKGROUND:Despite decades of research on the optimization of the diagnosis of Alzheimer's disease (AD), its biomarker-based diagnosis is being hampered by the lack of comparability of raw biomarker data. In order to overcome this limitation, the Erlangen Score (ES), among other approaches, was set up as a diagnostic-relevant interpretation algorithm. OBJECTIVE:To validate the ES algorithm in a cohort of neuropathologically confirmed cases with AD (n?=?106) and non-AD dementia (n?=?57). METHODS:Cerebrospinal fluid (CSF) biomarker concentrations of A?1-42, T-tau, and P-tau181 were measured with commercially available single analyte ELISA kits. Based on these biomarkers, ES was calculated as previously reported. RESULTS:This algorithm proved to categorize AD in different degrees of likelihood, ranging from neurochemically "normal", "improbably having AD", "possibly having AD", to "probably having AD", with a diagnostic accuracy of 74% using the neuropathology as a reference. CONCLUSION:The ability of the ES to overcome the high variability of raw CSF biomarker data may provide a useful diagnostic tool for comparing neurochemical diagnoses between different labs or methods used.

SUBMITTER: Somers C

PROVIDER: S-EPMC6484252 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Validation of the Erlangen Score Algorithm for Differential Dementia Diagnosis in Autopsy-Confirmed Subjects.

Somers Charisse C Lewczuk Piotr P Sieben Anne A Van Broeckhoven Christine C De Deyn Peter Paul PP Kornhuber Johannes J Martin Jean-Jacques JJ Bjerke Maria M Engelborghs Sebastiaan S

Journal of Alzheimer's disease : JAD 20190101 3

<h4>Background</h4>Despite decades of research on the optimization of the diagnosis of Alzheimer's disease (AD), its biomarker-based diagnosis is being hampered by the lack of comparability of raw biomarker data. In order to overcome this limitation, the Erlangen Score (ES), among other approaches, was set up as a diagnostic-relevant interpretation algorithm.<h4>Objective</h4>To validate the ES algorithm in a cohort of neuropathologically confirmed cases with AD (n = 106) and non-AD dementia (n ...[more]

PMID: 30883344

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Project description:Growing evidence suggests overlap between Alzheimer's disease (AD) and Parkinson's disease (PD) pathophysiology in a subset of patients. Indeed, 50-80% of autopsy cases with a primary clinicopathological diagnosis of Lewy body disease (LBD)-most commonly manifesting during life as PD-have concomitant amyloid-beta and tau pathology, the defining pathologies of AD. Here we evaluated common genetic variants in genome-wide association with AD as predictors of concomitant AD pathology in the brains of people with a primary clinicopathological diagnosis of PD or Dementia with Lewy Bodies (DLB), diseases both characterized by neuronal Lewy bodies. In the first stage of our study, 127 consecutive autopsy-confirmed cases of PD or DLB from a single center were assessed for AD neuropathological change (ADNC), and these same cases were genotyped at 20 single nucleotide polymorphisms (SNPs) found by genome-wide association study to associate with risk for AD. In these 127 training set individuals, we developed a logistic regression model predicting the presence of ADNC, using backward stepwise regression for model selection and tenfold cross-validation to estimate performance. The best-fit model generated a risk score for ADNC (ADNC-RS) based on age at disease onset and genotype at three SNPs (APOE, BIN1, and SORL1 loci), with an area under the receiver operating curve (AUC) of 0.751 in our training set. In the replication stage of our study, we assessed model performance in a separate test set of the next 81 individuals genotyped in our center. In the test set, the AUC was 0.781, and individuals with ADNC-RS in the top quintile had four-fold increased likelihood of having AD pathology at autopsy compared with those in each of the lowest two quintiles. Finally, in the validation stage of our study, we applied our ADNC-RS model to 70 LBD individuals from 20 Alzheimer's Disease Research Centers (ADRC) whose autopsy and genetic data were available in the National Alzheimer's Coordinating Center (NACC) database. In this validation set, the AUC was 0.754. Thus, in patients with autopsy-confirmed PD or DLB, a simple model incorporating three AD-risk SNPs and age at disease onset substantially enriches for concomitant AD pathology at autopsy, with implications for identifying LBD patients in which targeting amyloid-beta or tau is a therapeutic strategy.

Project description:BACKGROUND:The previously described and validated Erlangen Score (ES) algorithm enables interpretation of the cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD), ordering them on an ordinal scale: from neurochemically normal (ES?=?0) through improbable AD (ES?=?1), possible AD (ES?=?2 or 3), to probable AD (ES?=?4). Here we assess the accuracy of the ES in predicting hazards of progression from the mild cognitive impairment (MCI) stage of AD to the dementia stage of the disease (Alzheimer's disease dementia (ADD)) in a novel, single-center cohort. METHODS:Baseline CSF biomarkers (amyloid beta (A?) 1-42, A?42/40, Tau, and pTau181), interpreted according to the ES, were used to estimate time to progression from the MCI stage of AD to ADD, conditional on age, gender, APOE ?4 genotype, and Mini Mental State Examination score in 144 MCI subjects, using the Extended Cox Model; the subjects were followed-up until they developed dementia or until they had been cognitively stable for at least 2?years. In addition, ES distributions were studied in 168 ADD cases and 66 neurologic controls. Further, we stratified MCI patients into those who progressed to ADD faster (within 3 years, n?=?47) and those who progressed slower (n?=?74). RESULTS:The distributions of the ES categories across the four diagnostic groups (Controls, MCI-Stable, MCI-AD, and ADD) were highly significantly different (Kruskal-Wallis ?2(df?=?3)?=?151.4, p?<?0.001), with significant contrasts between each pair (p?<?0.005), except between the ADD and the MCI-AD groups (p?=?1.0). MCI patients with ES?=?2 or 3 had 6-8 times higher hazards to progress to ADD compared to patients with ES?=?0 or 1 in the first 3 follow-up years, and then their hazards decreased to those of the group with ES?=?0 or 1. Patients with ES?=?4 had hazards 8-12 times higher compared to the ES?=?0 or 1 group. Faster progressors with ES?=?2 or 3 had, in comparison to slower progressors, significantly lower A?1-42, A?1-40, and A?42/40, but comparable Tau and pTau181. A highly significant difference of the ES distributions between these two groups was observed (p?<?0.001). CONCLUSIONS:Our current results reconfirm and extend the conclusions of the previously published report that the Erlangen Score is a useful tool facilitating interpretation of a complex pattern of the CSF AD biomarkers.

Dataset Information

Validation of the Erlangen Score Algorithm for Differential Dementia Diagnosis in Autopsy-Confirmed Subjects.

Publications

Validation of the Erlangen Score Algorithm for Differential Dementia Diagnosis in Autopsy-Confirmed Subjects.

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