CSF biomarkers cutoffs: the importance of coincident neuropathological diseases

Abstract

The effects of applying clinical versus neuropathological diagnosis and the inclusion of cases with coincident neuropathological diagnoses have not been assessed specifically when studying cerebrospinal fluid (CSF) biomarker classification cutoffs for patients with neurodegenerative diseases that cause dementia. Thus, 142 neuropathologically diagnosed neurodegenerative dementia patients [71 Alzheimer's disease (AD), 29 frontotemporal lobar degeneration (FTLD), 3 amyotrophic lateral sclerosis, 7 dementia with Lewy bodies, 32 of which cases also had coincident diagnoses] were studied. 96 % had enzyme-linked immunosorbant assay (ELISA) CSF data and 77 % had Luminex CSF data, with 43 and 46 controls for comparison, respectively. Aβ(42), total, and phosphorylated tau(181) were measured. Clinical and neuropathological diagnoses showed an 81.4 % overall agreement. Both assays showed high sensitivity and specificity to classify AD subjects against FTLD subjects and controls, and moderate sensitivity and specificity for classifying FTLD subjects against controls. However, among the cases with neuropathological diagnoses of AD plus another pathology (26.8 % of the sample), 69.4 % (ELISA) and 96.4 % (Luminex) were classified as AD according to their biomarker profiles. Use of clinical diagnosis instead of neuropathological diagnosis led to a 14-17 % underestimation of the biomarker accuracy. These results show that while CSF Aβ and tau assays are useful for diagnosis of AD and neurodegenerative diseases even at MCI stages, CSF diagnostic analyte panels that establish a positive diagnosis of Lewy body disease and FTLD are also needed, and must be established based on neuropathological rather than clinical diagnoses.

Fig. 1

Levels of Aβ₄₂, t- and p-tau as measured by Luminex assay

Fig. 2

ROC curve and density probabilities of the classification groups based on the probabilities obtained in the regression models. The values inside the parenthesis in the AUC curves indicate the specificity and sensitivity of the selected cutoff. The ROC curves and density plots represent values and distributions for AD versus FTLD and controls (a, b), FTLD versus controls (c, d) and AD versus FTLD versus AD (e, f) using ELISA. For the Luminex assay the ROC curves and density plots represent values and distributions for AD versus FTLD and controls (g, h), FTLD versus controls (i, j) and AD versus FTLD versus AD (k, 1)

Fig. 3

Classification of the cases based on ELISA (a) and Luminex assays (b) using the logistic regression models based on neuropathological diagnoses. The upper box represents all the cases available for the corresponding platform and the boxes below show how cases were classified. Prob. Log. Regr. probability obtained in the logistic regression model