Symmetric Centipolar Normalized Score (SCeNS): A standardization framework for fluid marker cross‐comparability in Alzheimer's disease
8 affiliations
- 1Department of Psychiatry Washington University School of Medicine St. Louis Missouri USA
- 2NeuroGenomics and Informatics Center Washington University School of Medicine St. Louis Missouri USA
- 3Division of Biology and Biomedical Sciences Washington University School of Medicine St. Louis Missouri USA
- 4Department of Neurology School of Medicine Washington University St. Louis Missouri USA
- 5Division of Biostatistics School of Medicine Washington University St. Louis Missouri USA
- 6Department of Genetics Washington University School of Medicine St. Louis Missouri USA
- 7Hope Center for Neurological Disorders Washington University School of Medicine St. Louis Missouri USA
- 8Vanderbilt Memory and Alzheimer's Center Vanderbilt University Medical Center Nashville Tennessee USA
Abstract
INTRODUCTION: Multiple platforms measure Alzheimer's disease fluid biomarkers, such as amyloid beta (Aβ) and p‐tau, leading to heterogeneous data. Existing harmonization methods are difficult to interpret as they still provide specific cut‐offs and biomarker values are not commaptible between different biomarkers.
METHODS: We propose a standardization approach, Symmetric Centipolar Normalized Score (SCeNS), which uses Gaussian mixture model‐derived cutoffs to rescale biomarker z‐scores onto a −100 to 100 scale, with a constant cut‐off to derive biomarker status, that can be applied to fluid as well as imaging biomakers. The sign (plus or minus) reflects sample's biomarker status. We present the calculation steps and demonstrate how SCeNS enables direct comparison across cohorts, platforms, and tissue types. We also demonstrate a use case of the approach using real‐world data from individuals treated with lecanemab.
RESULTS: SCeNS were calucated using cerebrospinal and plasma AD biomarkers measured in mutliple platforms, demostrating that the SCeNS methods provide a consistent and easy to understand biomarker level. We applied the SCeNS method to the lecanmab‐treated cohort, where we demostrated the SCeNS previde easy to interpert biomkaer changes as p‐tau217 showed highest unit of change, while p‐tau181 had highest conversion (7.57%) to biomarker negative.
DISCUSSION: SCeNS provides a simple, interpretable biomarker metric across platforms.
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BibTeX
@article{timsina2026symmetric,
title = {{Symmetric Centipolar Normalized Score (SCeNS): A standardization framework for fluid marker cross‐comparability in Alzheimer's disease}},
author = {Jigyasha Timsina and Yike Chen and Menghan Liu and Rui Mu and Katherine Gong and John Budde and Guoqiao Wang and Yan Li and Suzanne E. Schindler and John C. Morris and David M. Holtzman and Randall J. Bateman and Timothy J. Hohman and Carlos Cruchaga},
journal = {Alzheimer's \& Dementia : Diagnosis, Assessment \& Disease Monitoring},
year = {2026},
month = oct,
doi = {10.1002/dad2.70516},
url = {https://doi.org/10.1002/dad2.70516},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Symmetric Centipolar Normalized Score (SCeNS): A standardization framework for fluid marker cross‐comparability in Alzheimer's disease
AU - Jigyasha Timsina
AU - Yike Chen
AU - Menghan Liu
AU - Rui Mu
AU - Katherine Gong
AU - John Budde
AU - Guoqiao Wang
AU - Yan Li
AU - Suzanne E. Schindler
AU - John C. Morris
AU - David M. Holtzman
AU - Randall J. Bateman
AU - Timothy J. Hohman
AU - Carlos Cruchaga
PY - 2026
DA - 2026/10/25
JO - Alzheimer's & Dementia : Diagnosis, Assessment & Disease Monitoring
DO - 10.1002/dad2.70516
UR - https://doi.org/10.1002/dad2.70516
AB - INTRODUCTION: Multiple platforms measure Alzheimer's disease fluid biomarkers, such as amyloid beta (Aβ) and p‐tau, leading to heterogeneous data. Existing harmonization methods are difficult to interpret as they still provide specific cut‐offs and biomarker values are not commaptible between different biomarkers. METHODS: We propose a standardization approach, Symmetric Centipolar Normalized Score (SCeNS), which uses Gaussian mixture model‐derived cutoffs to rescale biomarker z‐scores onto a −100 to 100 scale, with a constant cut‐off to derive biomarker status, that can be applied to fluid as well as imaging biomakers. The sign (plus or minus) reflects sample's biomarker status. We present the calculation steps and demonstrate how SCeNS enables direct comparison across cohorts, platforms, and tissue types. We also demonstrate a use case of the approach using real‐world data from individuals treated with lecanemab. RESULTS: SCeNS were calucated using cerebrospinal and plasma AD biomarkers measured in mutliple platforms, demostrating that the SCeNS methods provide a consistent and easy to understand biomarker level. We applied the SCeNS method to the lecanmab‐treated cohort, where we demostrated the SCeNS previde easy to interpert biomkaer changes as p‐tau217 showed highest unit of change, while p‐tau181 had highest conversion (7.57%) to biomarker negative. DISCUSSION: SCeNS provides a simple, interpretable biomarker metric across platforms.
SN - 2352-8729
ER -