A Multi-site In-depth Evaluation of the Quanterix Simoa from a User’s Perspective

JAK/STAT signaling in rheumatoid arthritis leukocytes is uncoupled from serum cytokines in a subset of patients

OBJECTIVE

Rheumatoid Arthritis (RA) is a systemic autoimmune disease involving pro-inflammatory cytokines that can be therapeutically targeted by antibodies or kinase inhibitors. Nevertheless, these drugs fail in a subset of patients independent of the abundance of the targeted cytokines. We aim to explore the cellular basis of this phenomenon by analyzing the relation of cytokine abundance and activation of downstream signaling pathways in RA.

METHODS

The study included 62 RA patients and 9 healthy controls (HC). Phosphorylation of STAT 1-6 in various immune cell subsets was determined ex vivo using a novel robust flow cytometry-based protocol. Serum concentrations of IL-6, IL-10, IL-12p70, IL-17 A, interferon gamma, and TNFα in the same samples were measured using highly sensitive single molecule array (SIMOA).

RESULTS

We found an increase in circulating cytokines in RA patients, while STAT activity was lower in RA patients compared to HC. Based on STAT activity we determined three endotypes in active RA patients (cDAI>10, n = 28): 1) those with active STAT5a/b signaling in T cells (n = 7/28), 2) those with a low STAT activity in all assessed cell types (n = 14/28), and 3) those with active STAT1 and STAT3 signaling mainly in myeloid cells (n = 7/28). Integrating intracellular STAT activation and cytokine analysis revealed diminished JAK/STAT signaling in a subset of patients (n = 8/20) despite elevated serum cytokine concentrations.

CONCLUSION

Diminished JAK/STAT signaling in active RA may partly explain unresponsiveness to therapy targeting cytokine signaling. Analysis of JAK/STAT phosphorylation may identify patients at risk for non-response to these therapies.

Fluid-Based Protein Biomarkers in Traumatic Brain Injury: The View from the Bedside

There has been an explosion of research into biofluid (blood, cerebrospinal fluid, CSF)-based protein biomarkers in traumatic brain injury (TBI) over the past decade. The availability of very large datasets, such as CENTRE-TBI and TRACK-TBI, allows for correlation of blood- and CSF-based molecular (protein), radiological (structural) and clinical (physiological) marker data to adverse clinical outcomes. The quality of a given biomarker has often been framed in relation to the predictive power on the outcome quantified from the area under the Receiver Operating Characteristic (ROC) curve. However, this does not in itself provide clinical utility but reflects a statistical association in any given population between one or more variables and clinical outcome. It is not currently established how to incorporate and integrate biofluid-based biomarker data into patient management because there is no standardized role for such data in clinical decision making. We review the current status of biomarker research and discuss how we can integrate existing markers into current clinical practice and what additional biomarkers do we need to improve diagnoses and to guide therapy and to assess treatment efficacy. Furthermore, we argue for employing machine learning (ML) capabilities to integrate the protein biomarker data with other established, routinely used clinical diagnostic tools, to provide the clinician with actionable information to guide medical intervention.

Association between Cerebrospinal Fluid and Serum Biomarker Levels and Diagnosis, Injury Severity, and Short-Term Outcomes in Patients with Acute Traumatic Spinal Cord Injury

Acute traumatic spinal cord injury (SCI) is recognized as a global problem that can lead to a range of acute and secondary complications impacting morbidity and mortality. There is still a lack of reliable diagnostic and prognostic biomarkers in patients with SCI that could help guide clinical care and identify novel therapeutic targets for future drug discovery. The aim of this prospective controlled study was to determine the cerebral spinal fluid (CSF) and serum profiles of 10 biomarkers as indicators of SCI diagnosis, severity, and prognosis to aid in assessing appropriate treatment modalities. CSF and serum samples of 15 SCI and ten healthy participants were included in the study. The neurological assessments were scored on admission and at discharge from the hospital using the American Spinal Injury Association Impairment Score (AIS) grades. The CSF and serum concentrations of SBDP150, S100B, GFAP, NF-L, UCHL-1, Tau, and IL-6 were significantly higher in SCI patients when compared with the control group. The CSF GBDP 38/44K, UCHL-L1, S100B, GFAP, and Tau levels were significantly higher in the AIS A patients. This study demonstrated a strong correlation between biomarker levels in the diagnosis and injury severity of SCI but no association with short-term outcomes. Future prospective controlled studies need to be done to support the results of this study.

Development of an electrochemical impedance spectroscopy based biosensor for detection of ubiquitin C-Terminal hydrolase L1

Year over year, the incidence of traumatic brain injury (TBI) in the population is dramatically increasing; thus, timely diagnosis is crucial for improving patient outcomes in the clinic. Ubiquitin C-terminal hydrolase L1 (UCH-L1), a blood-based biomarker, has been approved by the FDA as a promising quantitative indicator of mild TBI that arises in blood serum shortly after injury. Current gold standard techniques for its quantitation are time-consuming and require specific laboratory equipment. Hence, development of a hand-held device is an attractive alternative. In this study, we report a novel system for rapid, one-step electrochemical UCH-L1 detection. Electrodes were functionalized with anti-UCH-L1 antibody, which was used as a molecular recognition element for selective sensing of UCH-L1. Electrochemical impedance spectroscopy (EIS) was used as a transduction method to quantify its binding. When the electrode was incubated with different concentrations of UCH-L1, impedance signal increased against a concentration gradient with high logarithmic correlation. Upon single-frequency analysis, a second calibration curve with greater signal to noise was obtained, which was used to distinguish physiologically relevant concentrations of UCH-L1. Notably, our system could detect UCH-L1 within 5 min, without a washing step nor bound/free separation, and had resolution across concentrations ranging from 1 pM to 1000 pM within an artificial serum sample. These attributes, together with the miniaturization potential afforded by an impedimetric sensing platform, make this platform an attractive candidate for scale-up as a device for rapid, on-site detection of TBI. These findings may aid in the future development of sensing systems for quantitative TBI detection.

Practical application of Alzheimer's Disease Neuroimaging Initiative plasma P-tau181 reference data to support diagnosis of Alzheimer's disease

OBJECTIVES

To assess plasma phosphorylated tau181 (p-tau181) levels in Alzheimer's disease (AD), cognitively impaired non-AD participants (CI non-AD) and Control participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset that could potentially act as reference data for clinic diagnoses of AD.

METHODS

Data from 1558 participants (649 AD participants, 445 CI non-AD participants and 464 controls) were examined, comparing p-tau181 levels between Controls, AD and other dementias, stratified by age.

RESULTS

There were significant differences in plasma p-tau181 values between Controls and those with AD at all ages up to 85 years. There were also significant differences between AD and CI non-AD participants up to the age of 85 years.

CONCLUSIONS

Plasma P-tau181 may be a useful tool in the diagnosis of AD in those clinical settings where biomarkers have traditionally been less used. P-tau181 may be less useful as an aid to diagnosis in the very oldest-old. Further work is needed to establish the feasibility and utility of this biomarker within dementia diagnosis services not led by Neurologists, such as UK National Health Service Memory Services.

Network-Based Approaches for Drug Repositioning

With deep learning creeping up into the ranks of big data, new models based on deep learning and massive data have made great leaps forward rapidly in the field of drug repositioning. However, there is no relevant review to summarize the transformations and development process of models and their data in the field of drug repositioning. Among all the computational methods, network-based methods play an extraordinary role. In view of these circumstances, understanding and comparing existing network-based computational methods applied in drug repositioning will help us recognize the cutting-edge technologies and offer valuable information for relevant researchers. Therefore, in this review, we present an interpretation of the series of important network-based methods applied in drug repositioning, together with their comparisons and development process.

The Current State of Traumatic Brain Injury Biomarker Measurement Methods

Traumatic brain injury (TBI) is associated with high rates of morbidity and mortality partially due to the limited tools available for diagnosis and classification. Measuring panels of protein biomarkers released into the bloodstream after injury has been proposed to diagnose TBI, inform treatment decisions, and monitor the progression of the injury. Being able to measure these protein biomarkers at the point-of-care would enable assessment of TBIs from the point-of-injury to the patient's hospital bedside. In this review, we provide a detailed discussion of devices reported in the academic literature and available on the market that have been designed to measure TBI protein biomarkers in various biofluids and contexts. We also assess the challenges associated with TBI biomarker measurement devices and suggest future research directions to encourage translation of these devices to clinical use.

Serum glial fibrillary acidic protein is a predictor of brain metastases in patients with metastatic breast cancer

In patients with metastatic breast cancer (MBC), brain metastases (BM) are associated with high morbidity and mortality. However, there is no validated serum biomarker that accurately predicts BM occurrence in these patients, and the role of serum biomarkers for prognosis remains unclear. Here, we evaluated the association of neurofilament light chain (NfL), ubiquitin C-terminal hydrolase L1 (UCHL1), glial fibrillary acidic protein (GFAP) and tau serum levels with BM presence and prognosis in patients with MBC. In serum samples from patients with MBC with (n = 100) and without BM (n = 47), we measured the biomarker serum levels using single molecule array (Simoa) technology (Neurology-4-Plex assay). To evaluate their accuracy to identify patients with BM, we determined the receiver operating characteristic curve and the area under the curve (AUC) for each biomarker and calculated their sensitivity and specificity. The median serum levels of NfL, UCHL1, tau and GFAP were significantly higher in patients with BM. The AUC for GFAP (0.82, 95% confidence interval [CI] 0.75-0.88) was significantly higher than those of the other biomarkers considered independently. Using the medians as cutoff values, elevated serum levels of NfL, UCHL1, tau and GFAP were associated with BM in univariate analysis, but only high GFAP levels in multivariate analysis (odd ratio 23.4, 95% CI 6.8-80.5, P < .001). Elevated serum GFAP levels were independently associated with poor outcome. GFAP outperforms NfL, UCHL1 and tau as diagnostic and prognostic factor of BM in patients with MBC. These results must now be validated in an independent cohort of patients.

Development and Validation of a Simoa Assay for Determination of Recombinant Batroxobin in Human Serum

Recombinant batroxobin (S3101) is a thrombin-like serine protease that binds to fibrinogen or is taken up by the reticuloendothelial system. A literature survey showed no adequate method that could determine sufficient concentrations to evaluate pharmacokinetic parameters for phase I clinical studies. Therefore, a sensitive method is urgently needed to support the clinical pharmacokinetic evaluation of S3101. In this study, a sensitive bioanalytical method was developed and validated, using a Quanterix single molecular array (Simoa) assay. Moreover, to thoroughly assess the platform, enzyme-linked immunosorbent assay and electrochemiluminescence assay were also developed, and their performance was compared with that of this novel technology platform. The assay was validated in compliance with the current guidelines. Measurements with the Simoa assay were precise and accurate, presenting a valid assay range from 6.55 to 4000 pg/mL. The intra- and inter-run accuracy and precision were within -19.3% to 15.3% and 5.5% to 17.0%, respectively. S3101 was stable in human serum for 280 days at -20°C and -70°C, for 2 h prior to pre-treatment and 24 h post pre-treatment at room temperature (22°C-28°C), respectively, and after five and two freeze-thaw cycles at -70°C and -20°C, respectively. The Simoa assay also demonstrated sufficient dilution linearity, assay sensitivity, and parallelism for quantifying S3101 in human serum. The Simoa assay is a sensitive and adequate method for evaluating the pharmacokinetic parameters of S3101 in human serum.

Cross-platform comparison of highly sensitive immunoassay technologies for cytokine markers: Platform performance in post-traumatic stress disorder and Parkinson's disease

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Cross-platform comparisons were conducted across five leading immunoassay platforms.

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Plasma and serum were obtained from healthy controls and clinical populations.

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Analytic parameters included sensitivity, precision, and performance correlation.

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Platform performance was highly variable, particularly for low-abundant cytokines.

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Findings highlight certain immunoassays should be prioritized in future research.

There is mounting evidence of systemic inflammation in post-traumatic stress disorder (PTSD) and Parkinson’s disease (PD), yet inconsistency and a lack of replicability in findings of putative biological markers have delayed progress in this space. Variability in performance between platforms may contribute to the lack of consensus in the biomarker literature, as has been seen for a number of psychiatric disorders, including PTSD. Thus, there is a need for high-performance, scalable, and validated platforms for the discovery and development of biomarkers of inflammation for use in drug development and as clinical diagnostics. To identify the best platform for use in future biomarker discovery efforts, we conducted a comprehensive cross-platform and cross-assay evaluation across five leading platform technologies. This initial assessment focused on four cytokines that have been implicated PTSD – interleukin (IL)-1β, IL-6, tumor necrosis factor (TNF)-α, and interferon (IFN)-γ. To assess platform performance and understand likely measurements in individuals with brain disorders, serum and plasma samples were obtained from individuals with PTSD (n = 13) or Parkinson’s Disease (n = 14) as well as healthy controls (n = 5). We compared platform performance across a number of common analytic parameters, including assay precision, sensitivity, frequency of endogenous analyte detection (FEAD), correlation between platforms, and parallelism in measurement of cytokines using a serial dilution series. The single molecule array (Simoa™) ultra-sensitive platform (Quanterix), MESO V-Plex (Mesoscale Discovery), and Luminex xMAP® (Myriad) were conducted by their respective vendors, while Luminex® and Quantikine® high-sensitivity ELISA assays were evaluated by R&D System’s Biomarker Testing Services. The assay with the highest sensitivity in detecting endogenous analytes across all analytes and clinical populations (i.e. the highest FEAD), was the Simoa™ platform. In contrast, more variable performance was observed for MESO V-plex, R&D Luminex® and Quantikine®, while Myriad’s Luminex xMAP® exhibited low FEAD across all analytes and samples. Simoa™ also demonstrated high precision in detecting endogenous cytokines, as reflected in < 20 percent coefficient of variance (%CV) across replicate runs for samples from the healthy controls, PTSD patients, and PD patients. In contrast, MESO V-Plex, R&D Luminex® and Quantikine® had variable performance in terms of precision across cytokines. Myriad Luminex xMAP® could not be included in precision estimates because the vendor did not run samples in duplicate. For cross-platform performance comparisons, the highest cross-platform correlations were observed for IL-6 such that all platforms – except for Myriad’s Luminex xMAP® – had strong correlations with one another in measurements of IL-6 (r range = 0.59 – 0.86). For the other cytokines, there was low to no correlation across platforms, such that reported measurements of IL-1β, TNF-α, and IFN-γ varied across assays. Taken together, these findings provide novel evidence that the choice of immunoassay could greatly impact reported cytokine findings. The current study provides crucial information on the variability in performance between platforms and across immunoassays that may help inform the selection of assay in future research studies. Further, the results emphasize the need for performing comparative evaluations of immunoassays as new technologies emerge over time, particularly given the lack of reference standards for the quantitative assessments of cytokines.

Magnetic Particles: Their Applications from Sample Preparations to Biosensing Platforms

The growing interest in magnetic materials as a universal tool has been shown by an increasing number of scientific publications regarding magnetic materials and its various applications. Substantial progress has been recently made on the synthesis of magnetic iron oxide particles in terms of size, chemical composition, and surface chemistry. In addition, surface layers of polymers, silica, biomolecules, etc., on magnetic particles, can be modified to obtain affinity to target molecules. The developed magnetic iron oxide particles have been significantly utilized for diagnostic applications, such as sample preparations and biosensing platforms, leading to the selectivity and sensitivity against target molecules and the ease of use in the sensing systems. For the process of sample preparations, the magnetic particles do assist in target isolation from biological environments, having non-specific molecules and undesired molecules. Moreover, the magnetic particles can be easily applied for various methods of biosensing devices, such as optical, electrochemical, and magnetic phenomena-based methods, and also any methods combined with microfluidic systems. Here we review the utilization of magnetic materials in the isolation/preconcentration of various molecules and cells, and their use in various techniques for diagnostic biosensors that may greatly contribute to future innovation in point-of-care and high-throughput automation systems.

Bioanalytical challenges in development of ultrasensitive Home Brew assays: a case study using IL-13

Aim: IL-13 is a biomarker of type 2 inflammation that plays a critical role in asthma. IL-13 is present in serum at subpicogram levels. Methods: Simoa HD-1 technology was evaluated for the detection and quantitation of IL-13 by using a commercially available IL-13 kit and compared with a Simoa HomeBrew (HB) IL-13 assay as well as Immunological Multi-Parameter Chip Technology (IMPACT), an internal Roche platform. Performance of the assays was evaluated based on preset criteria for sensitivity, standard curve and controls' accuracy and precision, reproducibility and parallelism of endogenous analyte in serum samples. Results: The Simoa platform offered high assay sensitivity for evaluation of IL-13. Conclusion: This paper discusses the challenges and considerations when evaluating kits and/or developing HomeBrew assays using ultrasensitive platforms.

Plasma alpha-synuclein detected by single molecule array is increased in PD

We utilized ultrasensitive single molecule technology to measure plasma alpha-synuclein in 221 subjects (51 controls, 170 PD). Plasma alpha-synuclein levels were significantly higher in PD than controls (15506.3 vs. 13057.0 pg/mL, P = 0.037), adjusting for age and gender. In PD, alpha-synuclein levels did not vary by H&Y stage or UPDRS motor scores but were significantly higher in PD patients with poorer cognition (MMSE ≤ 25) than controls (P = 0.016, Bonferroni corrected P = 0.047). Alpha-synuclein levels quantified using ultrasensitive single molecule technology discriminate PD from controls and correlate with cognitive severity. These preliminary findings require independent validation to determine the utility of this assay.

General methods for quantitative interpretation of results of digital variable-volume assays

In digital assays, devices typically require precisely controlled volumes since variation can cause biases in concentration estimates. Here, we develop methods to correct bias when compartment volumes are variable.