Evaluating assay performance and freeze-thaw stability in cerebrospinal fluid samples using High-Throughput Proximity Extension Assay Platform

Analysis of cerebrospinal fluid (CSF) facilitates the understanding of brain-specific molecular changes that may associate with disease progression. Proximity extension assays (PEA) have been deployed in several CSF studies, however the evaluation of the assay and impact of freeze-thaw cycles on the protein signal has not been documented. We sought to (1) assess the technical performance of the PEA platform and (2) evaluate the effect of freeze-thaw cycles on the detectability of analytes on the PEA platform. We have evaluated the PEA with Next Generation Sequencing (NGS) readout assay and report on the detectability and coefficient of variation observed in CSF samples. We have also evaluated proteomic signals with a minimum of 3 and a maximum of 9 freeze thaw cycles and detected very minimal change in signal with increasing cycle number. Our study is the first to evaluate the performance of PEA using NGS readout platform with CSF samples. We report lower protein detection rates and higher variability in the expansion panels compared to the original 4 panels, with acceptable variation above detectability threshold. In addition, our work demonstrates that the proteomic signal is robust and continues to be stable across multiple freeze thaw cycles. This is highly impactful to the processing and analysis of clinical samples and facilitates the investigation of samples with variable pre-analytical conditions.

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Journal
BMC Biotechnology
Published
2026-10-22
DOI
https://doi.org/10.1186/s12896-026-01144-y
Primary Topic
Advanced Biosensing Techniques and Applications
Type
article
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article

Evaluating assay performance and freeze-thaw stability in cerebrospinal fluid samples using High-Throughput Proximity Extension Assay Platform

Xiyun Chai, Michael L. Cunningham, Marieta Hyde, Aparna Vasanthakumar et al.
BMC Biotechnology
Advanced Biosensing Techniques and Applications
article

Evaluating assay performance and freeze-thaw stability in cerebrospinal fluid samples using High-Throughput Proximity Extension Assay Platform

Xiyun Chai, Michael L. Cunningham, Marieta Hyde, Aparna Vasanthakumar, Mengfei Peng, Hengcheng Alvis Hu, Charles Lu
article en

Abstract

Analysis of cerebrospinal fluid (CSF) facilitates the understanding of brain-specific molecular changes that may associate with disease progression. Proximity extension assays (PEA) have been deployed in several CSF studies, however the evaluation of the assay and impact of freeze-thaw cycles on the protein signal has not been documented. We sought to (1) assess the technical performance of the PEA platform and (2) evaluate the effect of freeze-thaw cycles on the detectability of analytes on the PEA platform. We have evaluated the PEA with Next Generation Sequencing (NGS) readout assay and report on the detectability and coefficient of variation observed in CSF samples. We have also evaluated proteomic signals with a minimum of 3 and a maximum of 9 freeze thaw cycles and detected very minimal change in signal with increasing cycle number. Our study is the first to evaluate the performance of PEA using NGS readout platform with CSF samples. We report lower protein detection rates and higher variability in the expansion panels compared to the original 4 panels, with acceptable variation above detectability threshold. In addition, our work demonstrates that the proteomic signal is robust and continues to be stable across multiple freeze thaw cycles. This is highly impactful to the processing and analysis of clinical samples and facilitates the investigation of samples with variable pre-analytical conditions.

BMC Biotechnology
AbbVie (United States) (US)
Good health and well-being
Openalex Percentile: Top 24%
Advanced Biosensing Techniques and Applications
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Evaluating assay performance and freeze-thaw stability in cerebrospinal fluid samples using High-Throughput Proximity Extension Assay Platform — Xiyun Chai, Michael L. Cunningham, et al. · BMC Biotechnology (2026) | TGRS Research Map | TGRS