The effect of preanalytical factors on cerebrospinal fluid and plasma proteomics: a systematic experimental study

Abstract Background Preanalytical variations (PAVs) are a major source of irreproducibility in biomarker studies. While their effects on blood have been widely examined, their impact on cerebrospinal fluid (CSF) proteomics remains less well characterized. We systematically evaluated common PAVs to inform biobanking and biomarker research. Methods CSF and plasma samples were collected at an ISO 20387–accredited biobank. For each condition, three or four independent paired samples were analyzed. PAVs included storage temperature, processing delay, centrifugation speed, storage tube type, freeze–thaw cycles, and blood contamination. Protein abundance was quantified using SomaScan. Selected analytes were further evaluated using orthogonal immunoassays. Fold changes were calculated as linear RFU ratios relative to baseline. Paired t-tests with false discovery rate (FDR) correction were performed. Analytes showing detectable or larger changes were defined based on predefined fold-change thresholds with nominal p < 0.05. Results Plasma proteomes were highly sensitive to delays and temperature, with 969 analytes showing large changes after 24 h at 25 °C (counts refer to large changes), compared to 26 analytes in CSF. At 4 °C, CSF remained stable for 24 h (4 changes), whereas plasma showed extensive changes after 24 h (465) and 72 h (813). Storage at − 20 °C caused substantial shifts in both matrices (CSF: 144; plasma: 1,164), whereas no analytes differed in plasma stored at − 50 °C relative to − 80 °C. Freeze–thaw cycles up to three resulted in few altered analytes, whereas 11 cycles led to pronounced changes (CSF: 198; plasma: 21). Hemolysis in plasma induced 28 changes, whereas CSF blood contamination ≤ 500 cells/mm 3 was associated with few changes. After FDR correction, no analytes remained significant in CSF, whereas multiple analytes remained significant in plasma under selected conditions. Conclusions Storage temperature and processing delay were the most influential PAVs, with plasma more susceptible than CSF. For optimal quality, CSF should be processed within 4 h or kept at 4 °C, plasma within 2 h, and both stored at ≤ − 80 °C. Freeze–thaw cycles should be limited to three.

Authors

Institutions

Publication Details

Journal
Clinical Proteomics
Published
2026-05-22
DOI
https://doi.org/10.1186/s12014-026-09604-5
Primary Topic
Advanced Proteomics Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The effect of preanalytical factors on cerebrospinal fluid and plasma proteomics: a systematic experimental study

Shinsuke Hidese, Megumi Tatsumi, Hiroshi Kunugi, Kosuke Saito et al.
Clinical Proteomics
Advanced Proteomics Techniques and Applications
article

The effect of preanalytical factors on cerebrospinal fluid and plasma proteomics: a systematic experimental study

Shinsuke Hidese, Megumi Tatsumi, Hiroshi Kunugi, Kosuke Saito, Kotaro Hattori, Takako Enokida, Yuichi Goto, Tomoko Miyakawa, Haruna Kaneko, Yuji Takahashi
article en

Abstract

Abstract Background Preanalytical variations (PAVs) are a major source of irreproducibility in biomarker studies. While their effects on blood have been widely examined, their impact on cerebrospinal fluid (CSF) proteomics remains less well characterized. We systematically evaluated common PAVs to inform biobanking and biomarker research. Methods CSF and plasma samples were collected at an ISO 20387–accredited biobank. For each condition, three or four independent paired samples were analyzed. PAVs included storage temperature, processing delay, centrifugation speed, storage tube type, freeze–thaw cycles, and blood contamination. Protein abundance was quantified using SomaScan. Selected analytes were further evaluated using orthogonal immunoassays. Fold changes were calculated as linear RFU ratios relative to baseline. Paired t-tests with false discovery rate (FDR) correction were performed. Analytes showing detectable or larger changes were defined based on predefined fold-change thresholds with nominal p < 0.05. Results Plasma proteomes were highly sensitive to delays and temperature, with 969 analytes showing large changes after 24 h at 25 °C (counts refer to large changes), compared to 26 analytes in CSF. At 4 °C, CSF remained stable for 24 h (4 changes), whereas plasma showed extensive changes after 24 h (465) and 72 h (813). Storage at − 20 °C caused substantial shifts in both matrices (CSF: 144; plasma: 1,164), whereas no analytes differed in plasma stored at − 50 °C relative to − 80 °C. Freeze–thaw cycles up to three resulted in few altered analytes, whereas 11 cycles led to pronounced changes (CSF: 198; plasma: 21). Hemolysis in plasma induced 28 changes, whereas CSF blood contamination ≤ 500 cells/mm 3 was associated with few changes. After FDR correction, no analytes remained significant in CSF, whereas multiple analytes remained significant in plasma under selected conditions. Conclusions Storage temperature and processing delay were the most influential PAVs, with plasma more susceptible than CSF. For optimal quality, CSF should be processed within 4 h or kept at 4 °C, plasma within 2 h, and both stored at ≤ − 80 °C. Freeze–thaw cycles should be limited to three.

Clinical Proteomics
National Center of Neurology and Psychiatry (JP), National Institute of Occupational Safety and Health (JP), National Institute of Health Sciences (JP), Teikyo University (JP)
Japan Agency for Medical Research and Development
Openalex Percentile: Top 10%
Advanced Proteomics Techniques and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.