Format

Send to

Choose Destination
J Alzheimers Dis. 2019;67(2):639-651. doi: 10.3233/JAD-180855.

Improved Differential Diagnosis of Alzheimer's Disease by Integrating ELISA and Mass Spectrometry-Based Cerebrospinal Fluid Biomarkers.

Author information

1
Department of Medical Sciences, Clinical Chemistry, Uppsala University, Uppsala, Sweden.
2
Department of Chemistry-BMC, Analytical Chemistry, Uppsala University, Uppsala, Sweden.
3
Division of Affinity Proteomics, SciLifeLab, Department of Protein Science, KTH Royal Institute of Technology, Stockholm, Sweden.
4
Department of Public Health and Caring Sciences/Geriatrics, Uppsala University, Uppsala, Sweden.
5
Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.
6
Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.
7
UK Dementia Research Institute at UCL, London, United Kingdom.
8
Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, United Kingdom.

Abstract

BACKGROUND:

Alzheimer's disease (AD) is diagnosed based on a clinical evaluation as well as analyses of classical biomarkers: Aβ42, total tau (t-tau), and phosphorylated tau (p-tau) in cerebrospinal fluid (CSF). Although the sensitivities and specificities of the classical biomarkers are fairly good for detection of AD, there is still a need to develop novel biochemical markers for early detection of AD.

OBJECTIVE:

We explored if integration of novel proteins with classical biomarkers in CSF can better discriminate AD from non-AD subjects.

METHODS:

We applied ELISA, mass spectrometry, and multivariate modeling to investigate classical biomarkers and the CSF proteome in subjects (n = 206) with 76 AD patients, 74 mild cognitive impairment (MCI) patients, 11 frontotemporal dementia (FTD) patients, and 45 non-dementia controls. The MCI patients were followed for 4-9 years and 21 of these converted to AD, whereas 53 remained stable.

RESULTS:

By combining classical CSF biomarkers with twelve novel markers, the area of the ROC curves (AUROCS) of distinguishing AD and MCI/AD converters from non-AD were 93% and 96%, respectively. The FTDs and non-dementia controls were identified versus all other groups with AUROCS of 96% and 87%, respectively.

CONCLUSIONS:

Integration of new and classical CSF biomarkers in a model-based approach can improve the identification of AD, FTD, and non-dementia control subjects.

KEYWORDS:

Alzheimer’s disease; ELISA; cerebrospinal fluid; mass spectrometry; mild cognitive impairment; proteomics

Supplemental Content

Full text links

Icon for IOS Press Icon for PubMed Central
Loading ...
Support Center