Temporal patterns of inflammation-related proteins measured in the cerebrospinal fluid of patients with aneurysmal subarachnoid hemorrhage using multiplex Proximity Extension Assay technology

Abstract

Background The complexity of the inflammatory response post subarachnoid hemorrhage (SAH) may require temporal analysis of multiple protein biomarkers simultaneously to be more accurately described. Methods Ventricular cerebrospinal fluid was collected at days 1, 4 and 10 after SAH in 29 patients. Levels of 92 inflammation-related proteins were simultaneously measured using Target 96 Inflammation ® assay (Olink Proteomics, Uppsala, Sweden) based on Proximity Extension Assay (PEA) technology. Twenty-eight proteins were excluded from further analysis due to lack of >50% of measurable values. Temporal patterns of the remaining 64 proteins were analyzed. Repeated measures ANOVA and its nonparametric equivalent Friedman’s ANOVA were used for comparisons of means between time points. Results Four different patterns (Groups A-D) were visually observed with an early peak and gradually decreasing trend (11 proteins), a middle peak (10 proteins), a late peak after a gradually increasing trend (30 proteins) and no specific pattern (13 proteins). Statistically significant early peaks defined as Day 1 > Day 4 values were noticed in 4 proteins; no significant decreasing trends defined as Day 1 > Day 4 > Day 10 values were observed. Two proteins showed significant middle peaks (i.e. Day 1 < Day 4 > Day 10 values). Statistically significant late peaks (i.e. Day 4 < Day 10 values) and increasing trends (i.e. Day 1 < Day 4 < Day 10 values) were observed in 14 and 10 proteins, respectively. Four of Group D proteins showed biphasic peaks and the rest showed stable levels during the observation period. Conclusion The comprehensive data set provided in this explorative study may act as an illustration of an inflammatory profile of the acute phase of SAH showing groups of potential protein biomarkers with similar temporal patterns of activation, thus facilitating further research on their role in the pathophysiology of the disease.

Neuroinflammation and subarachnoid hemorrhage: a revised look at the literature

“…Further understanding of these cytokines along with their levels and timeframes could lead to targeted therapies aimed at preventing SAH complications such as vasospasm and hydrocephalus [ 36 , 52 , 61 ]. Although both the timeframe [ 60 , 61 ] and the levels [ 62 ] of cytokines following SAH have been studied, there remains a lack of consensus on how and when to measure these cytokines following SAH to improve clinical outcomes and develop targeted therapies [ 61 ].…”

“…Whether being secreted from leukocytes [ 66 ] or glial cells [ 63 – 65 ], cytokines play a key role in the response of the brain parenchyma following SAH. Cytokines are directly responsible for the numerous structural and chemical changes that occur minutes to months following SAH [ 62 ]. By better understanding the temporal nature and which cytokines predominate, clinicians may be better equipped to manage and prevent common complications following SAH.…”

Biomarker Associations in Delayed Cerebral Ischemia after Aneurysmal Subarachnoid Hemorrhage

“…Unlike other diseases where serum biomarkers are routinely used, however, there are still no effective serum biomarkers in clinical practice for predicting DCI or monitoring therapeutic efficacy. The study of a single biomarker is not suitable for the complex characterization of the mechanisms underlying DCI, but the analysis of a comprehensive biomarker profile may be more appropriate [ 10 ]. To have a broader view of possible pathophysiological processes, we performed a multiplex serum biomarker analysis.…”

“…To have a broader view of possible pathophysiological processes, we performed a multiplex serum biomarker analysis. The biomarkers measured in this study were selected according to the following criteria: (i) previously their role was investigated in animal models of ischemic stroke or SAH, such as eotaxin [ 11 ], fibroblast growth factor-2 (FGF-2) [ 12 , 13 ], chemokine (C-X3-C motif) ligand-1 (CX3CL1) [ 14 ], or interleukin-1b (Il-1b) [ 15 ]; (ii) its role in the case of SAH has already been investigated, but the studies mainly focused on its level in the CSF, such as monocyte chemotactic protein-3 (MCP-3) [ 10 ]; or (iii) its pathophysiological role was primarily investigated in human ischemic stroke such as Fms related receptor tyrosine kinase-3 ligand (FLT-3L) [ 16 ] and in SAH (interferon gamma-induced protein 10, IP-10) [ 17 , 18 ], macrophage inflammatory protein 1-beta (MIP-1b) [ 17 ], and, further, a more detailed investigation may be promising in the case of SAH. The great variability of temporal patterns of inflammation-related proteins is an indicator of the complexity of the inflammatory response following aSAH.…”

“…The great variability of temporal patterns of inflammation-related proteins is an indicator of the complexity of the inflammatory response following aSAH. Their exact role is not easy to establish, especially considering the fact that many of these substances are described to play both a detrimental and a beneficial role in the disease course depending on the time after bleeding [ 10 ]. We planned to investigate the relationship of the above markers to DCI and the functional outcome and their relationship to each other in the present study.…”