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

Institutions

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
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A blood‐based multi‐modal assay for diagnosing Alzheimer's disease

Shareefa Thekkan, Maura Malpetti, Hernando Martínez Vergara, Leonidas Chouliaras et al.
Alzheimer s & Dementia
Computational Drug Discovery Methods
article

A blood‐based multi‐modal assay for diagnosing Alzheimer's disease

Shareefa Thekkan, Maura Malpetti, Hernando Martínez Vergara, Leonidas Chouliaras, John T. O’Brien, James B. Rowe, Souvik Modi, Peter Swann
article en

Abstract

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.

Alzheimer s & DementiaVol. 20(S2)
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)
Good health and well-being
Openalex Percentile: Top 70%
Computational Drug Discovery Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.