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Assessing the preanalytical variability of plasma and cerebrospinal fluid processing and its effects on inflammation-related protein biomarkers.

ABSTRACT: Proteomics studies are important for the discovery of new biomarkers as clinical tools for diagnosis and disease monitoring. However, preanalytical variations caused by differences in sample handling protocol pose challenges for assessing biomarker reliability and comparability between studies. The purpose of this study was to examine the effects of delayed centrifuging on measured protein levels in plasma and CSF. Blood from healthy individuals and patients with multiple sclerosis along with CSF from patients with suspected neurological disorders were left at room temperature for different time periods (blood: 1, 24, 48, 72 hours; CSF: 1 and 6 hours) prior to centrifuging. Ninety-one inflammation-related proteins were analyzed using a proximity extension assay, a high sensitivity multiplex immunoassay. Additional metabolic and neurology related markers were also investigated in CSF. In summary, many proteins, particularly in plasma, had increased levels with longer delays in processing likely due in part to intracellular leakage. Levels of CASP-8, IL-8, IL-18, SIRT2, and ST1A1 increased 2-10 fold in plasma after 24 hours at room temperature. Similarly, levels of CTSH, ENTPD5, and WWP2 differentiated in CSF with <6 hour delay in processing. However, the rate of change for many proteins was relatively consistent, therefore, we were able to characterize biomarkers for detecting sample handling variability. Our findings highlight the importance of timely and consistent sample collection and the need for increased awareness of protein susceptibility to sample handling bias. In addition, suggested biomarkers may be used in certain situations to detect and correct for preanalytical variation in future studies.

SUBMITTER: Huang J

PROVIDER: S-EPMC8554621 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The identification of molecular biomarkers in CSF from individuals affected by Huntington disease may help improve predictions of disease onset, better define disease progression and could facilitate the evaluation of potential therapies. The primary objective of our study was to investigate novel CSF protein candidates and replicate previously reported protein biomarker changes in CSF from Huntington disease mutation carriers and healthy controls. Our secondary objective was to compare the discriminatory potential of individual protein analytes and combinations of CSF protein markers for stratifying individuals based on the severity of Huntington disease. We conducted a hypothesis-driven analysis of 26 pre-specified protein analytes in CSF from 16 manifest Huntington disease subjects, eight premanifest Huntington disease mutation carriers and eight healthy control individuals using parallel-reaction monitoring mass spectrometry. In addition to reproducing reported changes in previously investigated CSF biomarkers (NEFL, PDYN, and PENK), we also identified novel exploratory CSF proteins (C1QB, CNR1, GNAL, IDO1, IGF2, and PPP1R1B) whose levels were altered in Huntington disease mutation carriers and/or across stages of disease. Moreover, we report strong associations of select CSF proteins with clinical measures of disease severity in manifest Huntington disease subjects (C1QB, CNR1, NEFL, PDYN, PPP1R1B, and TTR) and with years to predicted disease onset in premanifest Huntington disease mutation carriers (ALB, C4B, CTSD, IGHG1, and TTR). Using receiver operating characteristic curve analysis, we identified PENK as being the most discriminant CSF protein for stratifying Huntington disease mutation carriers from controls. We also identified exploratory multi-marker CSF protein panels that improved discrimination of premanifest Huntington disease mutation carriers from controls (PENK, ALB and NEFL), early/mid-stage Huntington disease from premanifest mutation carriers (PPP1R1B, TTR, CHI3L1, and CTSD), and late-stage from early/mid-stage Huntington disease (CNR1, PPP1R1B, BDNF, APOE, and IGHG1) compared with individual CSF proteins. In this study, we demonstrate that combinations of CSF proteins can outperform individual markers for stratifying individuals based on Huntington disease mutation status and disease severity. Moreover, we define exploratory multi-marker CSF protein panels that, if validated, may be used to improve the accuracy of disease-onset predictions, complement existing clinical and imaging biomarkers for monitoring the severity of Huntington disease, and potentially for assessing therapeutic response in clinical trials. Additional studies with CSF collected from larger cohorts of Huntington disease mutation carriers are needed to replicate these exploratory findings.

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Assessing the preanalytical variability of plasma and cerebrospinal fluid processing and its effects on inflammation-related protein biomarkers.

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