Multi-cohort cerebrospinal fluid proteomics identifies robust molecular signatures across the Alzheimer disease continuum

Muhammad Ali; Jigyasha Timsina; Daniel Western; Menghan Liu; Aleksandra Beric; John Budde; Anh Do; Gyujin Heo; Lihua Wang; Jen Gentsch; Suzanne E Schindler; John C Morris; David M Holtzman; Agustin Ruiz; Ignacio Alvarez; Miquel Aguilar; Pau Pastor; Jarod Rutledge; Hamilton Oh; Edward N Wilson; Yann Le Guen; Rana R Khalid; Knight Alzheimer Disease Research Center (Knight ADRC); Alzheimer Disease Neuroimaging Initiative (ADNI); Fundació ACE Alzheimer Center Barcelona (FACE); Barcelona-1; Stanford Alzheimer Disease Research Center (Stanford ADRC); Chloe Robins; David J Pulford; Rawan Tarawneh; Laura Ibanez; Tony Wyss-Coray; Yun Ju Sung; Carlos Cruchaga

doi:10.1016/j.neuron.2025.02.014

Multi-cohort cerebrospinal fluid proteomics identifies robust molecular signatures across the Alzheimer disease continuum

Neuron. 2025 Mar 12:S0896-6273(25)00132-1. doi: 10.1016/j.neuron.2025.02.014. Online ahead of print.

Authors

Muhammad Ali¹, Jigyasha Timsina¹, Daniel Western¹, Menghan Liu¹, Aleksandra Beric¹, John Budde¹, Anh Do¹, Gyujin Heo¹, Lihua Wang¹, Jen Gentsch¹, Suzanne E Schindler², John C Morris², David M Holtzman², Agustin Ruiz³, Ignacio Alvarez⁴, Miquel Aguilar⁴, Pau Pastor⁴, Jarod Rutledge⁵, Hamilton Oh⁵, Edward N Wilson⁵, Yann Le Guen⁵, Rana R Khalid⁶; Knight Alzheimer Disease Research Center (Knight ADRC)⁷; Alzheimer Disease Neuroimaging Initiative (ADNI); Fundació ACE Alzheimer Center Barcelona (FACE); Barcelona-1; Stanford Alzheimer Disease Research Center (Stanford ADRC); Chloe Robins⁸, David J Pulford⁸, Rawan Tarawneh⁹, Laura Ibanez¹, Tony Wyss-Coray⁵, Yun Ju Sung¹, Carlos Cruchaga¹⁰

Affiliations

¹ Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63130, USA.
² Department of Neurology, Washington University in St. Louis, St. Louis, MO 63130, USA.
³ ACE Alzheimer Center Barcelona, Barcelona, Spain.
⁴ Fundació Docència i Recerca Mútua de Terrassa, Terrassa, Barcelona, Spain.
⁵ Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA 94305, USA.
⁶ NCB, Quaid-i-Azam University, Islamabad, Pakistan.
⁷ Knight Alzheimer's Disease Research Center, Washington University, St. Louis, MO 63110, USA.
⁸ Genomic Sciences, GSK Pharma R&D, 1250 S Collegeville Rd., Collegeville, PA 19426, USA.
⁹ The University of New Mexico, Albuquerque, NM 87131, USA.
¹⁰ Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63130, USA; Knight Alzheimer's Disease Research Center, Washington University, St. Louis, MO 63110, USA. Electronic address: cruchagac@wustl.edu.

PMID: 40088886
DOI: 10.1016/j.neuron.2025.02.014

Abstract

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.

Keywords: ATN; Alzheimer disease; CSF; SomaScan; biomarkers; dementia progression; machine learning; proteomics; pseudo-trajectory.

Abstract

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