Title

Detection of Alzheimer's Disease at Mild Cognitive Impairment and Disease Progression Using Autoantibodies as Blood-Based Biomarkers

Document Type

Article

Version Deposited

Published Version

Publication Date

4-12-2016

Publication Title

Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring

DOI

10.1016/j.dadm.2016.03.002

Abstract

INTRODUCTION: There is an urgent need to identify biomarkers that can accurately detect and diagnose Alzheimer's disease (AD). Autoantibodies are abundant and ubiquitous in human sera and have been previously demonstrated as disease-specific biomarkers capable of accurately diagnosing mild-moderate stages of AD and Parkinson's disease. METHODS: Sera from 236 subjects, including 50 mild cognitive impairment (MCI) subjects with confirmed low CSF Aβ42 levels, were screened with human protein microarrays to identify potential biomarkers for MCI. Autoantibody biomarker performance was evaluated using Random Forest and Receiver Operating Characteristic curves. RESULTS: Autoantibody biomarkers can differentiate MCI patients from age-matched and gender-matched controls with an overall accuracy, sensitivity, and specificity of 100.0%. They were also capable of differentiating MCI patients from those with mild-moderate AD and other neurologic and non-neurologic controls with high accuracy. DISCUSSION: Autoantibodies can be used as noninvasive and effective blood-based biomarkers for early diagnosis and staging of AD.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Published Citation

DeMarshall CA, Nagele EP, Sarkar A, Acharya NK, Godsey G, Goldwaser EL, Kosciuk M, Thayasivam U, Han M, Belinka B, Nagele RG, Alzheimer's Disease Neuroimaging Initiative. Detection of Alzheimer's Disease at Mild Cognitive Impairment and Disease Progression Using Autoantibodies as Blood-Based Biomarkers. Alzheimers Dement (Amst). 2016 Apr 12;3:51-62. eCollection 2016. doi: 10.1016/j.dadm.2016.03.002. PMID: 27239548. PMCID: PMC4879649.

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