A blood‐based multi‐modal assay for diagnosing Alzheimer's disease
Abstract Background Combinations of blood‐based biomarkers have been used to detect Alzheimer’s disease (AD). While these markers provide information about neuropathology, they fail to integrate the cellular dysfunction, such as disease‐associated defects in lysosomal ion homeostasis. To understand cellular dysfunction in AD and its relation to the pathophysiology of the disease, we developed a multi‐modal biomarker diagnostic platform that incorporates lysosomal ionic pH and Ca 2+ and plasma levels of Amyloid beta 1‐42 (Aβ 1‐42 ), Amyloid beta 1‐40 (Aβ 1‐40 ), phosphorylated Tau181 (pTau181), Neurofilament light (NfL) and Glial fibrillary acidic protein (GFAP). Method This multi‐modal blood‐based platform incorporates the concentrations of H + and Ca 2+ ions with single lysosome resolution in monocytes measured using DNA nanodevices from 33 participants (20 Controls and 13 AD patients). It also includes a panel of pathological biomarkers, including Aβ 1‐40 , Aβ 1‐42 , pTau181, NfL, and GFAP, which are measured using the Simoa platform from plasma across seven different cohorts totalling 323 participants (146 Controls, 92 AD patients, 34 amyloid negative and 51 amyloid positive mild cognitive impairment). Result The minimalistic panel of GFAP and pTau181/Aβ 1‐42 ratio performs significantly better (area under the curve [AUC] = 85%) in predicting Amyloid PET status than either NfL, GFAP, Aβ 1‐42 /Aβ 1‐40 ratio or pTau181 alone, with AUCs ranging from 68‐77%. The performance of these individual biomarkers or their combinations were further enhanced when lysosomal ionic information was incorporated, differentiating AD subjects from healthy individuals with an accuracy of 88% (Sensitivity 85%; Specificity 95%). Conclusion The multi‐modal blood platform described here is highly accurate, specific, and sensitive in evaluating AD, representing a promising avenue to explore the connections between cellular biology and the pathological hallmarks of AD, and the diagnosis of this disease.
Authors
- Shareefa Thekkan
- Maura Malpetti (ORCID: https://orcid.org/0000-0001-8923-9656)
- Hernando Martínez Vergara (ORCID: https://orcid.org/0000-0001-6904-2311)
- Leonidas Chouliaras (ORCID: https://orcid.org/0000-0002-3052-3879)
- John T. O’Brien (ORCID: https://orcid.org/0000-0002-0837-5080)
- James B. Rowe (ORCID: https://orcid.org/0000-0001-7216-8679)
- Souvik Modi (ORCID: https://orcid.org/0000-0001-5474-7765)
- Peter Swann (ORCID: https://orcid.org/0000-0003-4115-2425)
Institutions
- MRC Cognition and Brain Sciences Unit (GB)
- University of Cambridge (GB)
- Cambridge University Hospitals NHS Foundation Trust (GB)
- Cambridgeshire and Peterborough NHS Foundation Trust (GB)
- Medical Research Council (GB)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1002/alz.089477
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00