Dataset Information

Quantitative proteomics of delirium cerebrospinal fluid.

ABSTRACT: Delirium is a common cause and complication of hospitalization in older people, being associated with higher risk of future dementia and progression of existing dementia. However relatively little data are available on which biochemical pathways are dysregulated in the brain during delirium episodes, whether there are protein expression changes common among delirium subjects and whether there are any changes which correlate with the severity of delirium. We now present the first proteomic analysis of delirium cerebrospinal fluid (CSF), and one of few studies exploring protein expression changes in delirium. More than 270 proteins were identified in two delirium cohorts, 16 of which were dysregulated in at least 8 of 17 delirium subjects compared with a mild Alzheimer's disease neurological control group, and 31 proteins were significantly correlated with cognitive scores (mini-mental state exam and acute physiology and chronic health evaluation III). Bioinformatics analyses revealed expression changes in several protein family groups, including apolipoproteins, secretogranins/chromogranins, clotting/fibrinolysis factors, serine protease inhibitors and acute-phase response elements. These data not only provide confirmatory evidence that the inflammatory response is a component of delirium, but also reveal dysregulation of protein expression in a number of novel and unexpected clusters of proteins, in particular the granins. Another surprising outcome of this work is the level of similarity of CSF protein profiles in delirium patients, given the diversity of causes of this syndrome. These data provide additional elements for consideration in the pathophysiology of delirium as well as potential biomarker candidates for delirium diagnosis.

SUBMITTER: Poljak A

PROVIDER: S-EPMC4259987 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Quantitative proteomics of delirium cerebrospinal fluid.

Poljak A A Hill M M Hall R J RJ MacLullich A M AM Raftery M J MJ Tai J J Yan S S Caplan G A GA

Translational psychiatry 20141104

Delirium is a common cause and complication of hospitalization in older people, being associated with higher risk of future dementia and progression of existing dementia. However relatively little data are available on which biochemical pathways are dysregulated in the brain during delirium episodes, whether there are protein expression changes common among delirium subjects and whether there are any changes which correlate with the severity of delirium. We now present the first proteomic analys ...[more]

PMID: 25369144

Similar Datasets

Project description:Delirium is a common postoperative complication among older patients with many adverse outcomes. Due to lack of validated biomarkers, prediction and monitoring of delirium by biological testing is not currently feasible. Circulating proteins in cerebrospinal fluid (CSF) may reflect biological processes causing delirium. Our goal was to discover and investigate candidate protein biomarkers in preoperative CSF that were associated with development of postoperative delirium in older surgical patients. We employed a nested case–control study design coupled with high multiplex affinity proteomics analysis to measure 1305 proteins in preoperative CSF. Twenty-four matched delirium cases and non-delirium controls were selected from the Healthier Postoperative Recovery (HiPOR) cohort and the associations between preoperative protein levels and postoperative delirium were assessed using t-test statistics with further analysis by systems biology to elucidate delirium pathophysiology. Proteomics analysis identified 32 proteins in preoperative CSF that significantly associate with delirium (t-test p<0.05). Due to the limited sample size these proteins did not remain significant by multiple hypothesis testing using the Benjamini-Hochberg correction and q-value method. Three algorithms were applied to separate delirium cases from non-delirium controls. Hierarchical clustering classified 40/48 case-control samples correctly, principal components analysis separated 43/48. The receiver operating characteristic curve yielded an area under the curve [95% confidence interval] of 0.91 [0.80-0.97]. Systems biology analysis identified several key pathways associated with risk of delirium: inflammation, immune cell migration, apoptosis, angiogenesis, synaptic depression and neuronal cell death. Proteomics analysis of preoperative CSF identifies 32 proteins that might discriminate individuals who subsequently develop postoperative delirium from matched control samples. These proteins are potential candidate biomarkers for delirium and may play a role in its pathophysiology.

Project description:The analysis of cerebrospinal fluid (CSF) is used in biomarker discovery studies for various neurodegenerative central nervous system (CNS) disorders. However, little is known about variation of CSF proteins and metabolites between patients without neurological disorders. A baseline for a large number of CSF compounds appears to be lacking. To analyze the variation in CSF protein and metabolite abundances in a number of well-defined individual samples of patients undergoing routine, non-neurological surgical procedures, we determined the variation of various proteins and metabolites by multiple analytical platforms. A total of 126 common proteins were assessed for biological variations between individuals by ESI-Orbitrap. A large spread in inter-individual variation was observed (relative standard deviations [RSDs] ranged from 18 to 148%) for proteins with both high abundance and low abundance. Technical variation was between 15 and 30% for all 126 proteins. Metabolomics analysis was performed by means of GC-MS and nuclear magnetic resonance (NMR) imaging and amino acids were specifically analyzed by LC-MS/MS, resulting in the detection of more than 100 metabolites. The variation in the metabolome appears to be much more limited compared with the proteome: the observed RSDs ranged from 12 to 70%. Technical variation was less than 20% for almost all metabolites. Consequently, an understanding of the biological variation of proteins and metabolites in CSF of neurologically normal individuals appears to be essential for reliable interpretation of biomarker discovery studies for CNS disorders because such results may be influenced by natural inter-individual variations. Therefore, proteins and metabolites with high variation between individuals ought to be assessed with caution as candidate biomarkers because at least part of the difference observed between the diseased individuals and the controls will not be caused by the disease, but rather by the natural biological variation between individuals.

Project description:BACKGROUND: There is little knowledge concerning the content and the mechanisms of filling of arachnoid cysts. The aim of this study was to compare the protein content of arachnoid cysts and cerebrospinal fluid by quantitative proteomics to increase the understanding of arachnoid cysts. METHODS: Arachnoid cyst fluid and cerebrospinal fluid from five patients were analyzed by quantitative proteomics in two separate experiments.In a label-free experiment arachnoid cyst fluid and cerebrospinal fluid samples from individual patients were trypsin digested and analyzed by Orbitrap mass spectrometry in a label-free manner followed by data analysis using the Progenesis software.In the second proteomics experiment, a patient sample pooling strategy was followed by MARS-14 immunodepletion of high abundant proteins, trypsin digestion, iTRAQ labelling, and peptide separation by mix-phase chromatography followed by Orbitrap mass spectrometry analysis. The results from these analyzes were compared to previously published mRNA microarray data obtained from arachnoid membranes. RESULTS: We quantified 348 proteins by the label-free individual patient approach and 1425 proteins in the iTRAQ experiment using a pool from five patients of arachnoid cyst fluid and cerebrospinal fluid. This is by far the largest number of arachnoid cyst fluid proteins ever identified, and the first large-scale quantitative comparison between the protein content of arachnoid cyst fluid and cerebrospinal fluid from the same patients at the same time. Consistently in both experiment, we found 22 proteins with significantly increased abundance in arachnoid cysts compared to cerebrospinal fluid and 24 proteins with significantly decreased abundance. We did not observe any molecular weight gradient over the arachnoid cyst membrane. Of the 46 proteins we identified as differentially abundant in our study, 45 were also detected from the mRNA expression level study. None of them were previously reported as differentially expressed. We did not quantify any of the proteins corresponding to gene products from the ten genes previously reported as differentially abundant between arachnoid cysts and control arachnoid membranes. CONCLUSIONS: From our experiments, the protein content of arachnoid cyst fluid and cerebrospinal fluid appears to be similar. There were, however, proteins that were significantly differentially abundant between arachnoid cyst fluid and cerebrospinal fluid. This could reflect the possibility that these proteins are affected by the filling mechanism of arachnoid cysts or are shed from the membranes into arachnoid cyst fluid. Our results do not support the proposed filling mechanisms of oncotic pressure or valves.

Dataset Information

Quantitative proteomics of delirium cerebrospinal fluid.

Publications

Quantitative proteomics of delirium cerebrospinal fluid.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets