MSACL 2025 Abstract

Targeted Mass Spectrometry Assay for Staging and Predicting Progression of Alzheimer’s Disease using a Novel Cerebrospinal Fluid Protein Panel

Caroline M. Watson (1), Eric B. Dammer (1), Rafi Haque (1), Jiaqi Liu (1), E. Kathleen Carter (2), Duc M. Duong (2), Aliza P. Wingo (3), Thomas S. Wingo (4), Erik C.B. Johnson (1), Andrew J. Saykin (5), Leslie M. Shaw (6,7), Blaine R. Roberts (1), James J. Lah (1), Allan I. Levey (1), Nicholas T. Seyfried (1,2)
(1) Department of Neurology, Emory University School of Medicine, Atlanta, GA, (2) Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, (3) Department of Psychiatry, University of California, Davis, Sacramento, CA, (4) Department of Neurology, University of California, Davis, Sacramento, CA, (5) Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, (6) Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, (7) Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA

Caroline Watson, PhD (Presenter) Emory University School of Medicine

Presenter Bio: As a bioanalytical chemist with years of experience in liquid chromatography mass spectrometry (MS) platforms, I lead proteomic research projects by designing and executing studies, developing, and maintaining compliance documentation, and managing personnel to ensure accurate and timely results. I supervise and train research staff, present findings in peer-reviewed journals and at major conferences and serve as the primary liaison with project sponsors. My expertise includes MS method development in clinical settings, troubleshooting, maintenance, and managing CAP/CLIA compliant method validations.

Relevant Financial Disclosures (within past 24 months, reported on Apr 24, 2025) No relevant financial relationship(s) to disclose.

INTRODUCTION:
Alzheimer’s disease (AD) is the most common form of dementia, with cerebrospinal fluid (CSF) beta-amyloid and tau providing the most sensitive and specific biomarkers for diagnosis. However, these diagnostic biomarkers do not reflect the heterogenous and complex changes in AD brain. We have demonstrated the ability to use targeted LC/MS to quantify additional CSF proteins at different stages of AD.

OBJECTIVE:
To demonstrate the utility of selected reaction monitoring mass spectrometry (SRM-MS) for clinical assessment of cerebrospinal fluid (CSF) proteins reflective of Alzheimer’s disease (AD).

METHODS:
We developed an SRM-MS method with isotopically labeled standards for relative protein quantification in CSF to find protein biomarkers that are robustly measured and related to AD. Two disease-related CSF pools were generated in-house based on Amyloid-Beta and Tau immunoassay levels to create AD-positive and AD-negative quality control (QC) standards. A third CSF QC (QCpool) was generated in-house by pooling approximately 20 individuals with no distinct pathophysiology. The QC pools were processed and analyzed identically to the CSF clinical samples reported. CSF samples from Emory Goizueta Alzheimer’s Disease Research Center (ADRC; N=390), Alzheimer’s Disease Neuroimaging Initiative (ADNI; N=706), and Dominantly Inherited Alzheimer Network (DIAN; N=899), were analyzed using SRM-MS to examine the clinical utility of targeting a novel CSF protein panel for staging and predicting progression of AD.

RESULTS:
Based on the label-free coefficient of variation (CV) of Promega 6 × 5 LC-MS/MS Peptide Reference Mix (50 fmol/µL), we determined the lowest limit of detection for each peptide to be between 1–10 fmole across the gradient profile with a dynamic range spanning 4 orders of magnitude for all peptides except the latest eluting peptide at 13.3 minutes. We found approximately 50 proteins in each cohort that were precisely measured (CV <20%). The ADRC cohort was used to determine which proteins could distinguish CSF biomarker positivity (SMOC1, GDA, 14-3-3 proteins, glycolysis-involved proteins) and cognitive impairment (neuronal proteins; VGF, NPTX2, NPTXR, SCG2). ADNI is a powerful longitudinal study allowing us to use the SRM biomarker proteins to independently predict Amyloid-Beta and Tau status, and disease state with 97% and 94% accuracy, respectively. DIAN is a robust observational study that examines autosomal dominant AD mutation carriers to determine a relatively precise estimated year of disease onset (EYO); we found two proteins (SMOC1 and SPON1) elevated in AD CSF nearly 30 years before the onset of symptoms, and before other biomarkers of AD were significantly changing.

DISCUSSION:
We demonstrate the ability to use high-throughput, targeted MS to quantify CSF proteins at different stages of AD and show the targeted CSF protein panel complements existing AD CSF biomarkers to significantly improve diagnosis and predict future cognitive decline and dementia severity. We have used our SRM-MS method to analyze over 3000 CSF samples from the Emory Goizueta ADRC including longitudinal samples over several years. These data will help establish a targeted proteomic profile for research participants, which is necessary for a precision medicine approach.

REFERENCES:
1. Watson CM, Dammer EB, Ping L, Duong DM, Modeste E, Carter EK, Johnson ECB, Levey AI, Lah JJ, Roberts BR, Seyfried NT. Quantitative Mass Spectrometry Analysis of Cerebrospinal Fluid Protein Biomarkers in Alzheimer’s Disease. Sci Data. 2023;10(1):261.
2. Johnson ECB, Bian S, Haque RU, Carter EK, Watson CM, Gordon BA, Ping L, Duong DM, Epstein MP, McDade E, Barthélemy NR, Karch CM, Xiong C, Cruchaga C, Perrin RJ, Wingo AP, Wingo TS, Chhatwal JP, Day GS, Noble JM, Berman SB, Martins R, Graff-Radford NR, Schofield PR, Ikeuchi T, Mori H, Levin J, Farlow M, Lah JJ, Haass C, Jucker M, Morris JC, Benzinger TLS, Roberts BR, Bateman RJ, Fagan AM, Seyfried NT, Levey AI. Cerebrospinal fluid proteomics define the natural history of autosomal dominant Alzheimer’s disease. Nat Med. 2023;29(8):1979-88.
3. Haque R, Watson CM, Liu J, Carter EK, Duong DM, Lah JJ, Wingo AP, Roberts BR, Johnson ECB, Saykin AJ, Shaw LM, Seyfried NT, Wingo TS, Levey AI. A protein panel in cerebrospinal fluid for diagnostic and predictive assessment of Alzheimer’s disease. Sci Transl Med. 2023;15(712):eadg4122.