A cell-based multivariate blood test (iCAP) for early detection of Alzheimer’s disease capturing non-amyloid-β biology
Abstract
The indicator cell assay platform (iCAP) is a blood-based diagnostic approach that uses standardized cells as biosensors to transduce complex circulating signals into cell-based gene-expression profiles for multivariate disease classification. We developed an iCAP for early detection of Alzheimer’s disease (AD-iCAP) by incubating plasma from patients with early-stage AD (mild cognitive impairment or mild dementia) and non-affected controls with standardized neurons and training classifiers on transcriptomic responses. Modeling features were restricted to a predefined 84-gene panel derived independently by analyzing 5xFAD mouse plasma in the AD-iCAP. In this exploratory study, a model was trained and tested using 191 retrospectively collected human plasma samples across three cohorts. The classifier achieved AUC = 0.64 (95% CI 0.51–0.78) in an external validation set during model development (n = 82) and AUC = 0.77 (95% CI 0.57–0.96) in a blind test set (n = 23). The multivariate model incorporated 5 genes including AKT3 , GPR50 , PALLD , RGMA , and PCDH10 , implicated in AD, neuronal signaling and/or cytoskeletal dynamics. The cell-based approach is orthogonal to direct detection of circulating amyloid and tau, and these exploratory findings support further evaluation of AD-iCAP in prospective studies for combinatorial diagnostics and patient stratification for clinical trials.
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BibTeX
@article{qi2026cellbased,
title = {{A cell-based multivariate blood test (iCAP) for early detection of Alzheimer’s disease capturing non-amyloid-β biology}},
author = {Yijun Qi and Leslie Rae Miller and Mark D. D’Ascenzo and Jason D. Berndt and G. Adam Whitney and Fergal Duffy and Samuel A. Danziger and Elaine Peskind and Ge Li and Colin L. Masters and Christopher Fowler and Australian Imaging Biomarkers and Lifestyle Study of Ageing (AIBL) Research Group and Lidija Milicic and Michael Vacher and Pierrick Bourgeat and Vincent Doré and Rosita Shishegar and Paul Maruff and Christopher C. Rowe and Victor L. Villemagne and Tenielle Porter and Simon M. Laws and Stephanie R. Rainey-Smith and Julia Bomke and Belinda M. Brown and Scott Ayton and Ashley I. Bush and Carolyn Chadunow and Steven Collins and James Doecke and Kathryn A. Ellis and Lis Evered and Amir Fazlollahi and Jurgen Fripp and Samantha L. Gardener and Simon Gibson and Robert Grenfell and Elise Harrison and Liang Jin and Adrian Kamer and Fiona Lamb and Nicola T. Lautenschlager and Qiao-Xin Li and Lucy Lim and Yen Ying Lim and Andrea Louey and Lucy Mackintosh and Ralph N. Martins and Kelly Pertile and Morgan Radler and Joanne Robertson and Mark Rodrigues and Rebecca Rumble and Olivier Salvado and Greg Savage and Brendan Silbert and Magdalene Soh and Hamid R. Sohrabi and Kevin Taddei and Tania Taddei},
journal = {Scientific Reports},
year = {2026},
month = oct,
doi = {10.1038/s41598-026-74186-z},
url = {https://www.nature.com/articles/s41598-026-74186-z},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - A cell-based multivariate blood test (iCAP) for early detection of Alzheimer’s disease capturing non-amyloid-β biology
AU - Yijun Qi
AU - Leslie Rae Miller
AU - Mark D. D’Ascenzo
AU - Jason D. Berndt
AU - G. Adam Whitney
AU - Fergal Duffy
AU - Samuel A. Danziger
AU - Elaine Peskind
AU - Ge Li
AU - Colin L. Masters
AU - Christopher Fowler
AU - Australian Imaging Biomarkers and Lifestyle Study of Ageing (AIBL) Research Group
AU - Lidija Milicic
AU - Michael Vacher
AU - Pierrick Bourgeat
AU - Vincent Doré
AU - Rosita Shishegar
AU - Paul Maruff
AU - Christopher C. Rowe
AU - Victor L. Villemagne
AU - Tenielle Porter
AU - Simon M. Laws
AU - Stephanie R. Rainey-Smith
AU - Julia Bomke
AU - Belinda M. Brown
AU - Scott Ayton
AU - Ashley I. Bush
AU - Carolyn Chadunow
AU - Steven Collins
AU - James Doecke
AU - Kathryn A. Ellis
AU - Lis Evered
AU - Amir Fazlollahi
AU - Jurgen Fripp
AU - Samantha L. Gardener
AU - Simon Gibson
AU - Robert Grenfell
AU - Elise Harrison
AU - Liang Jin
AU - Adrian Kamer
AU - Fiona Lamb
AU - Nicola T. Lautenschlager
AU - Qiao-Xin Li
AU - Lucy Lim
AU - Yen Ying Lim
AU - Andrea Louey
AU - Lucy Mackintosh
AU - Ralph N. Martins
AU - Kelly Pertile
AU - Morgan Radler
AU - Joanne Robertson
AU - Mark Rodrigues
AU - Rebecca Rumble
AU - Olivier Salvado
AU - Greg Savage
AU - Brendan Silbert
AU - Magdalene Soh
AU - Hamid R. Sohrabi
AU - Kevin Taddei
AU - Tania Taddei
PY - 2026
DA - 2026/10/17
JO - Scientific Reports
DO - 10.1038/s41598-026-74186-z
UR - https://www.nature.com/articles/s41598-026-74186-z
AB - The indicator cell assay platform (iCAP) is a blood-based diagnostic approach that uses standardized cells as biosensors to transduce complex circulating signals into cell-based gene-expression profiles for multivariate disease classification. We developed an iCAP for early detection of Alzheimer’s disease (AD-iCAP) by incubating plasma from patients with early-stage AD (mild cognitive impairment or mild dementia) and non-affected controls with standardized neurons and training classifiers on transcriptomic responses. Modeling features were restricted to a predefined 84-gene panel derived independently by analyzing 5xFAD mouse plasma in the AD-iCAP. In this exploratory study, a model was trained and tested using 191 retrospectively collected human plasma samples across three cohorts. The classifier achieved AUC = 0.64 (95% CI 0.51–0.78) in an external validation set during model development (n = 82) and AUC = 0.77 (95% CI 0.57–0.96) in a blind test set (n = 23). The multivariate model incorporated 5 genes including AKT3 , GPR50 , PALLD , RGMA , and PCDH10 , implicated in AD, neuronal signaling and/or cytoskeletal dynamics. The cell-based approach is orthogonal to direct detection of circulating amyloid and tau, and these exploratory findings support further evaluation of AD-iCAP in prospective studies for combinatorial diagnostics and patient stratification for clinical trials.
SN - 2045-2322
ER -