Cerebrospinal Fluid Biomarkers for the Diagnosis and Classification of Alzheimer’s Disease Spectrum

Abstract

Results: CSF Aβ42, total tau (t-tau) and phosphorylated tau (p-tau) significantly differed across the three groups. The area under curve for the differentiation between NC and ADD was highest in t-tau/Aβ42 (0.994) followed by p-tau/Aβ42 (0.963), Aβ42 (0.960), t-tau (0.918), and p-tau (0.684). The concordance rate between CSF Aβ42 and amyloid PET results was 92%. Finally, ATN classification based on CSF biomarker abnormalities led to a majority of NC categorized into A-T-N-(73%), MCI as A+T-N-(30%)/A+T+N+(26%), and ADD as A+T+N+(57%). Conclusion: CSF biomarkers had high sensitivity and specificity in differentiating ADD from NC and were as accurate as amyloid PET. The ATN subtypes based on CSF biomarkers may further serve to predict the prognosis. Background: Cerebrospinal fluid (CSF) biomarkers are increasingly used in clinical practice for the diagnosis of Alzheimer’s disease (AD). We aimed to 1) determine cutoff values of CSF biomarkers for AD, 2) investigate their clinical utility by estimating a concordance with amyloid positron emission tomography (PET), and 3) apply ATN (amyloid/tau/neurodegeneration) classification based on CSF results. Methods: We performed CSF analysis in 51 normal controls (NC), 23 mild cognitive impairment (MCI) and 65 AD dementia (ADD) patients at the Samsung Medical Center in Korea. We attempted to develop cutoff of CSF biomarkers for differentiating ADD from NC using receiver operating characteristic analysis. We also investigated a concordance between CSF and amyloid PET results and applied ATN classification scheme based on CSF biomarker abnormalities to characterize our participants.