TY - JOUR
T1 - Multi-cohort cerebrospinal fluid proteomics identifies robust molecular signatures across the Alzheimer disease continuum
AU - Fundació ACE Alzheimer Center Barcelona (FACE)
AU - Barcelona-1
AU - Stanford Alzheimer Disease Research Center (Stanford ADRC)
AU - Knight Alzheimer Disease Research Center (Knight ADRC)
AU - Alzheimer Disease Neuroimaging Initiative (ADNI)
AU - Ali, Muhammad
AU - Timsina, Jigyasha
AU - Western, Daniel
AU - Liu, Menghan
AU - Beric, Aleksandra
AU - Budde, John
AU - Do, Anh
AU - Heo, Gyujin
AU - Wang, Lihua
AU - Gentsch, Jen
AU - Schindler, Suzanne E.
AU - Morris, John C.
AU - Holtzman, David M.
AU - Ruiz, Agustin
AU - Alvarez, Ignacio
AU - Aguilar, Miquel
AU - Pastor, Pau
AU - Rutledge, Jarod
AU - Oh, Hamilton
AU - Wilson, Edward N.
AU - Guen, Yann Le
AU - Khalid, Rana R.
AU - Robins, Chloe
AU - Pulford, David J.
AU - Tarawneh, Rawan
AU - Ibanez, Laura
AU - Wyss-Coray, Tony
AU - Sung, Yun Ju
AU - Cruchaga, Carlos
N1 - Publisher Copyright:
© 2025 The Author(s)
PY - 2025/5/7
Y1 - 2025/5/7
N2 - Changes in β-amyloid (Aβ) and hyperphosphorylated tau (T) in brain and cerebrospinal fluid (CSF) precede Alzheimer's disease (AD) symptoms, making the CSF proteome a potential avenue to understand disease pathophysiology and facilitate reliable diagnostics and therapies. Using the AT framework and a three-stage study design (discovery, replication, and meta-analysis), we identified 2,173 analytes (2,029 unique proteins) dysregulated in AD. Of these, 865 (43%) were previously reported, and 1,164 (57%) are novel. The identified proteins cluster in four different pseudo-trajectories groups spanning the AD continuum and were enriched in pathways including neuronal death, apoptosis, and tau phosphorylation (early stages), microglia dysregulation and endolysosomal dysfunction (mid stages), brain plasticity and longevity (mid stages), and microglia-neuron crosstalk (late stages). Using machine learning, we created and validated highly accurate and replicable (area under the curve [AUC] > 0.90) models that predict AD biomarker positivity and clinical status. These models can also identify people that will convert to AD.
AB - Changes in β-amyloid (Aβ) and hyperphosphorylated tau (T) in brain and cerebrospinal fluid (CSF) precede Alzheimer's disease (AD) symptoms, making the CSF proteome a potential avenue to understand disease pathophysiology and facilitate reliable diagnostics and therapies. Using the AT framework and a three-stage study design (discovery, replication, and meta-analysis), we identified 2,173 analytes (2,029 unique proteins) dysregulated in AD. Of these, 865 (43%) were previously reported, and 1,164 (57%) are novel. The identified proteins cluster in four different pseudo-trajectories groups spanning the AD continuum and were enriched in pathways including neuronal death, apoptosis, and tau phosphorylation (early stages), microglia dysregulation and endolysosomal dysfunction (mid stages), brain plasticity and longevity (mid stages), and microglia-neuron crosstalk (late stages). Using machine learning, we created and validated highly accurate and replicable (area under the curve [AUC] > 0.90) models that predict AD biomarker positivity and clinical status. These models can also identify people that will convert to AD.
KW - ATN
KW - Alzheimer disease
KW - CSF
KW - SomaScan
KW - biomarkers
KW - dementia progression
KW - machine learning
KW - proteomics
KW - pseudo-trajectory
UR - http://www.scopus.com/inward/record.url?scp=105000159073&partnerID=8YFLogxK
U2 - 10.1016/j.neuron.2025.02.014
DO - 10.1016/j.neuron.2025.02.014
M3 - Article
C2 - 40088886
AN - SCOPUS:105000159073
SN - 0896-6273
VL - 113
SP - 1363-1379.e9
JO - Neuron
JF - Neuron
IS - 9
ER -