Technical performance of a proximity extension assay inflammation biomarker panel with synovial fluid
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PROVIDER: S-EPMC9718077 | biostudies-literature | 2022 Jul
REPOSITORIES: biostudies-literature
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Project description:The core Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers; amyloid-β (Aß), total tau (t-tau), and phosphorylated tau (p-tau181), are strong indicators of the presence of AD pathology, but do not correlate well with disease progression, and can be difficult to implement in longitudinal studies where repeat biofluid sampling is required. As a result, blood-based biomarkers are increasingly being sought as alternatives. In this study, we aimed to evaluate a promising blood biomarker discovery technology, Olink Proximity Extension Assays for technical reproducibility characteristics in order to highlight the advantages and disadvantages of using this technology in biomarker discovery in AD. We evaluated the performance of five Olink Proteomic multiplex proximity extension assays (PEA) in plasma samples. Three technical control samples included on each plate allowed calculation of technical variability. Biotemporal stability was measured in three sequential annual samples from 54 individuals with and without AD. Coefficients of variation (CVs), analysis of variance (ANOVA), and variance component analyses were used to quantify technical and individual variation over time. We show that overall, Olink assays are technically robust, with the largest experimental variation stemming from biological differences between individuals for most analytes. As a powerful illustration of one of the potential pitfalls of using a multi-plexed technology for discovery, we performed power calculations using the baseline samples to demonstrate the size of study required to overcome the need for multiple test correction with this technology. We show that the power of moderate effect size proteins was strongly reduced, and as a result investigators should strongly consider pooling resources to perform larger studies using this multiplexed technique where possible.
| S-EPMC9207419 | biostudies-literature
Project description:BackgroundThe complexity of the inflammatory response post subarachnoid hemorrhage (SAH) may require temporal analysis of multiple protein biomarkers simultaneously to be more accurately described.MethodsVentricular 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.ResultsFour 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.ConclusionThe 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.
| S-EPMC8947082 | biostudies-literature
Project description:There is a lack of reliable biomarkers for disorders of the central nervous system (CNS), and diagnostics still heavily rely on symptoms that are both subjective and difficult to quantify. The cerebrospinal fluid (CSF) is a promising source of biomarkers due to its close connection to the CNS. Extracellular vesicles are actively secreted by cells, and proteomic analysis of CSF extracellular vesicles (EVs) and their molecular composition likely reflects changes in the CNS to a higher extent compared with total CSF, especially in the case of neuroinflammation, which could increase blood-brain barrier permeability and cause an influx of plasma proteins into the CSF. We used proximity extension assay for proteomic analysis due to its high sensitivity. We believe that this methodology could be useful for de novo biomarker discovery for several CNS diseases. We compared four commercially available kits for EV isolation: MagCapture and ExoIntact (based on magnetic beads), EVSecond L70 (size-exclusion chromatography), and exoEasy (membrane affinity). The isolated EVs were characterized by nanoparticle tracking analysis, ELISA (CD63, CD81 and albumin), and proximity extension assay (PEA) using two different panels, each consisting of 92 markers. The exoEasy samples did not pass the built-in quality controls and were excluded from downstream analysis. The number of detectable proteins in the ExoIntact samples was considerably higher (~150% for the cardiovascular III panel and ~320% for the cell regulation panel) compared with other groups. ExoIntact also showed the highest intersample correlation with an average Pearson's correlation coefficient of 0.991 compared with 0.985 and 0.927 for MagCapture and EVSecond, respectively. The median coefficient of variation was 5%, 8%, and 22% for ExoIntact, MagCapture, and EVSecond, respectively. Comparing total CSF and ExoIntact samples revealed 70 differentially expressed proteins in the cardiovascular III panel and 17 in the cell regulation panel. To our knowledge, this is the first time that CSF EVs were analyzed by PEA. In conclusion, analysis of CSF EVs by PEA is feasible, and different isolation kits give distinct results, with ExoIntact showing the highest number of identified proteins with the lowest variability.
| S-EPMC7763352 | biostudies-literature
Project description:Cerebral protein profiling in traumatic brain injury (TBI) is needed to better comprehend secondary injury pathways. Cerebral microdialysis (CMD), in combination with the proximity extension assay (PEA) technique, has great potential in this field. By using PEA, we have previously screened >500 proteins from CMD samples collected from TBI patients. In this study, we customized a PEA panel prototype of 21 selected candidate protein biomarkers, involved in inflammation (13), neuroplasticity/-repair (six), and axonal injury (two). The aim was to study their temporal dynamics and relation to age, structural injury, and clinical outcome. Ten patients with severe TBI and CMD monitoring, who were treated in the Neurointensive Care Unit, Uppsala University Hospital, Sweden, were included. Hourly CMD samples were collected for up to 7 days after trauma and analyzed with the 21-plex PEA panel. Seventeen of the 21 proteins from the CMD sample analyses showed significantly different mean levels between days. Early peaks (within 48 h) were noted with interleukin (IL)-1β, IL-6, IL-8, granulocyte colony-stimulating factor, transforming growth factor alpha, brevican, junctional adhesion molecule B, and neurocan. C-X-C motif chemokine ligand 10 peaked after 3 days. Late peaks (>5 days) were noted with interleukin-1 receptor antagonist (IL-1ra), monocyte chemoattractant protein (MCP)-2, MCP-3, urokinase-type plasminogen activator, Dickkopf-related protein 1, and DRAXIN. IL-8, neurofilament heavy chain, and TAU were biphasic. Age (above/below 22 years) interacted with the temporal dynamics of IL-6, IL-1ra, vascular endothelial growth factor, MCP-3, and TAU. There was no association between radiological injury (Marshall grade) or clinical outcome (Extended Glasgow Outcome Scale) with the protein expression pattern. The PEA method is a highly sensitive molecular tool for protein profiling from cerebral tissue in TBI. The novel TBI dedicated 21-plex panel showed marked regulation of proteins belonging to the inflammation, plasticity/repair, and axonal injury families. The method may enable important insights into complex injury processes on a molecular level that may be of value in future efforts to tailor pharmacological TBI trials to better address specific disease processes and optimize timing of treatments.
| S-EPMC9886191 | biostudies-literature
Project description:ObjectiveTo validate a quantitative high performance liquid chromatography (HPLC) assay for chondroitin sulfate (CS) and hyaluronic acid (HA) in synovial fluid, and to analyze glycan-patterns in patient samples.DesignSynovial fluid from osteoarthritis (OA, n = 25) and knee-injury (n = 13) patients, a synovial fluid pool (SF-control) and purified aggrecan, were chondroitinase digested and together with CS- and HA-standards fluorophore labelled prior to quantitative HPLC analysis. N-glycan profiles of synovial fluid and aggrecan were assessed by mass spectrometry.ResultsUnsaturated uronic acid and sulfated-N-acetylgalactosamine (ΔUA-GalNAc4S and ΔUA-GalNAc6S) contributed to 95% of the total CS-signal in the SF-control sample. For HA and the CS variants in SF-control the intra- and inter-experiment coefficient of variation was between 3-12% and 11-19%, respectively; tenfold dilution gave recoveries between 74 and 122%, and biofluid stability test (room temperature storage and freeze-thaw cycles) showed recoveries between 81 and 140%. Synovial fluid concentrations of the CS variants ΔUA-GalNAc6S and ΔUA2S-GalNAc6S were three times higher in the recent injury group compared to the OA group, while HA was four times lower. Sixty-one different N-glycans were detected in the synovial fluid samples, but there were no differences in levels of N-glycan classes between patient groups. The CS-profile (levels of ΔUA-GalNAc4S and ΔUA-GalNAc6S) in synovial fluid resembled that of purified aggrecan from corresponding samples; the contribution to the N-glycan profile in synovial fluid from aggrecan was low.ConclusionsThe HPLC-assay is suitable for analyzing CS variants and HA in synovial fluid samples, and the GAG-pattern differs between OA and recently knee injured subjects.
| S-EPMC10322674 | biostudies-literature
Project description: Not available
| S-BSST935 | biostudies-other
Project description:A comprehensive characterization of blood proteome profiles in cancer patients can contribute to a better understanding of the disease etiology, resulting in earlier diagnosis, risk stratification and better monitoring of the different cancer subtypes. Here, we describe the use of next generation protein profiling to explore the proteome signature in blood across patients representing many of the major cancer types. Plasma profiles of 1463 proteins from more than 1400 cancer patients are measured in minute amounts of blood collected at the time of diagnosis and before treatment. An open access Disease Blood Atlas resource allows the exploration of the individual protein profiles in blood collected from the individual cancer patients. We also present studies in which classification models based on machine learning have been used for the identification of a set of proteins associated with each of the analyzed cancers. The implication for cancer precision medicine of next generation plasma profiling is discussed.
| S-EPMC10354027 | biostudies-literature
Project description:Targeted proteomics utilizing antibody-based proximity extension assays provides sensitive and highly specific quantifications of plasma protein levels. Multivariate analysis of this data is hampered by frequent missing values (random or left censored), calling for imputation approaches. While appropriate missing-value imputation methods exist, benchmarks of their performance in targeted proteomics data are lacking. Here, we assessed the performance of two methods for imputation of values missing completely at random, the previously top-benchmarked 'missForest' and the recently published 'GSimp' method. Evaluation was accomplished by comparing imputed with remeasured relative concentrations of 91 inflammation related circulating proteins in 86 samples from a cohort of 645 patients with venous thromboembolism. The median Pearson correlation between imputed and remeasured protein expression values was 69.0% for missForest and 71.6% for GSimp (p = 5.8e-4). Imputation with missForest resulted in stronger reduction of variance compared to GSimp (median relative variance of 25.3% vs. 68.6%, p = 2.4e-16) and undesired larger bias in downstream analyses. Irrespective of the imputation method used, the 91 imputed proteins revealed large variations in imputation accuracy, driven by differences in signal to noise ratio and information overlap between proteins. In summary, GSimp outperformed missForest, while both methods show good overall imputation accuracy with large variations between proteins.
| S-EPMC7735586 | biostudies-literature
Project description:Conventional cytotoxic therapies for synovial sarcoma provide limited benefit. Drugs specifically targeting the product of its driver translocation are currently unavailable, in part because the SS18-SSX oncoprotein functions via aberrant interactions within multiprotein complexes. Proximity ligation assay is a recently-developed method that assesses protein-protein interactions in situ. Here we report use of the proximity ligation assay to confirm the oncogenic association of SS18-SSX with its co-factor TLE1 in multiple human synovial sarcoma cell lines and in surgically-excised human tumor tissue. SS18-SSX/TLE1 interactions are disrupted by class I HDAC inhibitors and novel small molecule inhibitors. This assay can be applied in a high-throughput format for drug discovery in fusion-oncoprotein associated cancers where key effector partners are known.
| S-EPMC5085163 | biostudies-literature
Project description:BackgroundMany components in follicular fluid (FF), such as peptide hormones, cytokines, and steroids, undergo dynamic changes during folliculogenesis and have important roles in follicular development. Because systemic inflammation has also been found to contribute to diminished ovarian reserve (DOR) in previous studies, do certain serum/FF inflammatory biomarkers affect both follicular development and ovarian function?MethodsSerum samples from the menstruation phase (n=26), serum samples from the ovulation phase (n=26), FF samples of mature oocytes (n=26), and FF samples of immature oocytes (n=10) were collected. Olink proteomic proximity extension assay (PEA) technology was used to compare the differentially expressed proteins (DEPs), and patients were divided into two subgroups-the normal ovarian reserve (NOR) group and the DOR group-for further bioinformatics analysis and verification by enzyme-linked immunosorbent assay (ELISA).ResultsIn total, 16 DEPs were detected between the mature group and the immature group (FF), and 11 DEPs were detected between the ovulation group and the menstruation group (serum). Further subdivision of the ovarian reserve subgroups revealed 22 DEPs in FF and 3 DEPs in serum. Among all four comparisons, only the expression of oncostatin M (OSM) significantly differed. The OSM signaling pathway, the IL-10 anti-inflammatory signaling pathway, and the PI3K-Akt signaling pathway are three notable pathways involved in affecting ovarian reserve capacity according to bioinformatics analysis. In addition, the concentration of estradiol on the hCG day was slightly but positively correlated with OSM (r=0.457, P=0.029). A significantly greater level of OSM (5.41 ± 2.65 vs. 3.94 ± 1.23 pg/mL, P=0.007) was detected in the serum of NOR patients via ELISA verification, and the sensitivity and specificity of ovarian reserve division were 50.00% and 83.33%, respectively.ConclusionThis study proposed that immunological changes assessed by PEA technology affect ovarian function in humans and that OSM may serve as a potential inflammatory biomarker for ovarian function in serum, thus revealing alterations in FF.
| S-EPMC11847672 | biostudies-literature