Evaluation of harmonization methods to mitigate assay and cohort effects in plasma p-tau217.
5 affiliations
- 1Department of Biostatistics and Health Data Science University of Pittsburgh School of Public Health Pittsburgh Pennsylvania USA.
- 2Department of Psychiatry University of Pittsburgh School of Medicine Pittsburgh Pennsylvania USA.
- 3Department of Radiology University of Pittsburgh School of Medicine Pittsburgh Pennsylvania USA.
- 4Department of Neurology University of Pittsburgh School of Medicine Pittsburgh Pennsylvania USA.
- 5Alzheimer's Disease Research Center University of Pittsburgh Pittsburgh Pennsylvania USA.
Abstract
Introduction
The growing number of assay platforms measuring blood-based biomarkers (BBMs) for Alzheimer's disease (AD) has introduced challenges in interpretability and comparability across assays. Differences across studies also limit comparability of data. To address these challenges, a systematic evaluation of harmonization methods is needed to support BBM data integration within or across studies.Methods
Two multisite studies, Alzheimer's Disease Neuroimaging Initiative (ADNI, n = 219) and Human Connectome Project (HCP, n = 111), were used to evaluate harmonization methods for mitigating assay and cohort effects in plasma phosphorylated tau 217 (p-tau217) measurements. Methods included various normalization, regression, and standardization approaches, including the recently developed CentiMarker. Assay effects were evaluated using repeated-measures data across assay platforms within each cohort, whereas cohort effects were assessed using pooled ADNI and HCP data. Harmonization performance was evaluated using distributional statistics and downstream modeling of p-tau217.Results
Quantile normalization and quantile mapping methods were most effective for mitigating assay effects, whereas conditional quantile mapping performed best for pooled multi-cohort data. These methods also preserved biological variability. In contrast, simple means adjustment and reference-based Z-score standardization were least effective for mitigating assay effects, whereas simple means adjustment, Z-score standardization, and quantile normalization were least effective for mitigating cohort effects. CentiMarker had minimal impact on assay or cohort effects.Discussion
Based on our evaluation, we recommend (conditional) quantile mapping for p-tau217 studies integrating data across multiple assays or cohorts. In contrast, we caution against using CentiMarker and Z-score-based methods, as they limit comparability and do not effectively mitigate technical variability.
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BibTeX
@article{zhang2026evaluation,
title = {{Evaluation of harmonization methods to mitigate assay and cohort effects in plasma p-tau217.}},
author = {Vivian Z Zhang and Pamela C L Ferreira and Yiwen Dong and Davneet Minhas and Guilherme Povala and Bruna Bellaver and Alzheimer's Disease Neuroimaging Initiative and Tharick A Pascoal and Xuemei Zeng and Thomas K Karikari and Ann D Cohen and Rebecca A Deek and Qiong Wu and Dana L Tudorascu},
journal = {Alzheimer's \& dementia (Amsterdam, Netherlands)},
year = {2026},
month = oct,
doi = {10.1002/dad2.70518},
url = {https://europepmc.org/article/MED/42921107},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Evaluation of harmonization methods to mitigate assay and cohort effects in plasma p-tau217.
AU - Vivian Z Zhang
AU - Pamela C L Ferreira
AU - Yiwen Dong
AU - Davneet Minhas
AU - Guilherme Povala
AU - Bruna Bellaver
AU - Alzheimer's Disease Neuroimaging Initiative
AU - Tharick A Pascoal
AU - Xuemei Zeng
AU - Thomas K Karikari
AU - Ann D Cohen
AU - Rebecca A Deek
AU - Qiong Wu
AU - Dana L Tudorascu
PY - 2026
DA - 2026/10/23
JO - Alzheimer's & dementia (Amsterdam, Netherlands)
DO - 10.1002/dad2.70518
UR - https://europepmc.org/article/MED/42921107
AB - Introduction The growing number of assay platforms measuring blood-based biomarkers (BBMs) for Alzheimer's disease (AD) has introduced challenges in interpretability and comparability across assays. Differences across studies also limit comparability of data. To address these challenges, a systematic evaluation of harmonization methods is needed to support BBM data integration within or across studies.Methods Two multisite studies, Alzheimer's Disease Neuroimaging Initiative (ADNI, n = 219) and Human Connectome Project (HCP, n = 111), were used to evaluate harmonization methods for mitigating assay and cohort effects in plasma phosphorylated tau 217 (p-tau217) measurements. Methods included various normalization, regression, and standardization approaches, including the recently developed CentiMarker. Assay effects were evaluated using repeated-measures data across assay platforms within each cohort, whereas cohort effects were assessed using pooled ADNI and HCP data. Harmonization performance was evaluated using distributional statistics and downstream modeling of p-tau217.Results Quantile normalization and quantile mapping methods were most effective for mitigating assay effects, whereas conditional quantile mapping performed best for pooled multi-cohort data. These methods also preserved biological variability. In contrast, simple means adjustment and reference-based Z-score standardization were least effective for mitigating assay effects, whereas simple means adjustment, Z-score standardization, and quantile normalization were least effective for mitigating cohort effects. CentiMarker had minimal impact on assay or cohort effects.Discussion Based on our evaluation, we recommend (conditional) quantile mapping for p-tau217 studies integrating data across multiple assays or cohorts. In contrast, we caution against using CentiMarker and Z-score-based methods, as they limit comparability and do not effectively mitigate technical variability.
SN - 2352-8729
ER -