Identification of brain-enriched proteins in CSF as biomarkers of relapsing remitting multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) is a clinically and biologically heterogenous disease with currently unpredictable progression and relapse. After the development and success of neurofilament as a cerebrospinal fluid (CSF) biomarker, there is reinvigorated interest in identifying other markers of or contributors to disease. The objective of this study is to probe the predictive potential of a panel of brain-enriched proteins on MS disease progression and subtype.

METHODS

This study includes 40 individuals with MS and 14 headache controls. The MS cohort consists of 20 relapsing remitting (RR) and 20 primary progressive (PP) patients. The CSF of all individuals was analyzed for 63 brain enriched proteins using a method of liquid-chromatography tandem mass spectrometry. Wilcoxon rank sum test, Kruskal-Wallis one-way ANOVA, logistic regression, and Pearson correlation were used to refine the list of candidates by comparing relative protein concentrations as well as relation to known imaging and molecular biomarkers.

RESULTS

We report 30 proteins with some relevance to disease, clinical subtype, or severity. Strikingly, we observed widespread protein depletion in the disease CSF as compared to control. We identified numerous markers of relapsing disease, including KLK6 (kallikrein 6, OR = 0.367, p < 0.05), which may be driven by active disease as defined by MRI enhancing lesions. Other oligodendrocyte-enriched proteins also appeared at reduced levels in relapsing disease, namely CNDP1 (carnosine dipeptidase 1), LINGO1 (leucine rich repeat and Immunoglobin-like domain-containing protein 1), MAG (myelin associated glycoprotein), and MOG (myelin oligodendrocyte glycoprotein). Finally, we identified three proteins-CNDP1, APLP1 (amyloid beta precursor like protein 1), and OLFM1 (olfactomedin 1)-that were statistically different in relapsing vs. progressive disease raising the potential for use as an early biomarker to discriminate clinical subtype.

CONCLUSIONS

We illustrate the utility of targeted mass spectrometry in generating potential targets for future biomarker studies and highlight reductions in brain-enriched proteins as markers of the relapsing remitting disease stage.

Glial fibrillary acidic protein, neurofilament light, matrix metalloprotease 3 and fatty acid binding protein 4 as non-invasive brain tumor biomarkers

BACKGROUND

Gliomas are aggressive malignant tumors, with poor prognosis. There is an unmet need for the discovery of new, non-invasive biomarkers for differential diagnosis, prognosis, and management of brain tumors. Our objective is to validate four plasma biomarkers - glial fibrillary acidic protein (GFAP), neurofilament light (NEFL), matrix metalloprotease 3 (MMP3) and fatty acid binding protein 4 (FABP4) - and compare them with established brain tumor molecular markers and survival.

METHODS

Our cohort consisted of patients with benign and malignant brain tumors (GBM = 77, Astrocytomas = 26, Oligodendrogliomas = 23, Secondary tumors = 35, Meningiomas = 70, Schwannomas = 15, Pituitary adenomas = 15, Normal individuals = 30). For measurements, we used ultrasensitive electrochemiluminescence multiplexed immunoassays.

RESULTS

High plasma GFAP concentration was associated with GBM, low GFAP and high FABP4 were associated with meningiomas, and low GFAP and low FABP4 were associated with astrocytomas and oligodendrogliomas. NEFL was associated with progression of disease. Several prognostic genetic alterations were significantly associated with all plasma biomarker levels. We found no independent associations between plasma GFAP, NEFL, FABP4 and MMP3, and overall survival. The candidate biomarkers could not reliably discriminate GBM from primary or secondary CNS lymphomas.

CONCLUSIONS

GFAP, NEFL, FABP4 and MMP3 are useful for differential diagnosis and prognosis, and are associated with molecular changes in gliomas.

Computational pathology: an evolving concept

The initial enthusiasm about computational pathology (CP) and artificial intelligence (AI) was that they will replace pathologists entirely on the way to fully automated diagnostics. It is becoming clear that currently this is not the immediate model to pursue. On top of the legal and regulatory complexities surrounding its implementation, the majority of tested machine learning (ML)-based predictive algorithms do not display the exquisite performance needed to render them unequivocal, standalone decision makers for matters with direct implications to human health. We are thus moving into a different model of "computer-assisted diagnostics", where AI is there to provide support, rather than replacing, the pathologist. Herein we focus on the practical aspects of CP, from a pathologist perspective. There is a wide range of potential applications where CP can enhance precision of pathology diagnosis, tailor prognostic and predictive information, as well as save time. There are, however, a number of potential limitations for CP that currently hinder their wider adoption in the clinical setting. We address the key necessary steps towards clinical implementation of computational pathology, discuss the significant obstacles that hinders its adoption in the clinical context and summarize some proposed solutions. We conclude that the advancement of CP in the clinic is a promising resource-intensive endeavour that requires broad and inclusive collaborations between academia, industry, and regulatory bodies.

The relationship between serum astroglial and neuronal markers and AQP4 and MOG autoantibodies

BACKGROUND

Certain demyelinating disorders, such as neuromyelitis optica spectrum disorder (NMOSD) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) exhibit serum autoantibodies against aquaporin-4 (αAQP4) and myelin oligodendrocyte glycoprotein (αMOG). The variability of the autoantibody presentation warrants further research into subtyping each case.

METHODS

To elucidate the relationship between astroglial and neuronal protein concentrations in the peripheral circulation with occurrence of these autoantibodies, 86 serum samples were analyzed using immunoassays. The protein concentration of glial fibrillary acidic protein (GFAP), neurofilament light chain (NFL) and tau protein was measured in 3 groups of subcategories of suspected NMOSD: αAQP4 positive (n = 20), αMOG positive (n = 32) and αMOG/αAQP4 seronegative (n = 34). Kruskal-Wallis analysis, univariate predictor analysis, and multivariate logistic regression with ROC curves were performed.

RESULTS

GFAP and NFL concentrations were significantly elevated in the αAQP4 positive group (p = 0.003; p = 0.042, respectively), and tau was elevated in the αMOG/αAQP4 seronegative group (p < 0.001). A logistic regression model to classify serostatus was able to separate αAQP4 seropositivity using GFAP + tau, and αMOG seropositivity using tau. The areas under the ROC curves (AUCs) were 0.77 and 0.72, respectively. Finally, a combined seropositivity versus negative status logistic regression model was generated, with AUC = 0.80.

CONCLUSION

The 3 markers can univariately and multivariately classify with moderate accuracy the samples with seropositivity and seronegativity for αAQP4 and αMOG.

Transforming diagnostics: The implementation of digital pathology in clinical laboratories

Digital pathology (DP) has emerged as a cutting-edge technology that promises to revolutionise diagnostics in clinical laboratories. This perspective article explores the implementation planning and considerations of DP in a single multicentre institution in Canada, the University Health Network, discussing benefits, challenges, potential implications and considerations for future adopters. We examine the transition from traditional microscopy to digital slide scanning and its impact on pathology practice, patient care and medical research. Furthermore, we address the regulatory, infrastructure and change management considerations for successful integration into clinical laboratories. By highlighting the advantages and addressing concerns, we aim to shed light on the transformative potential of DP and its role in shaping the future of diagnostics.

Multiplex proteomics in the identification of potential biomarkers of very severe sinusoidal obstruction syndrome/veno-occlusive disease (SOS/VOD) in allogeneic hematopoietic cell transplant patients treated with defibrotide

Introduction Despite well-established clinical criteria for diagnosis of SOS/VOD following allogeneic HCT, there is a lack of established diagnostic protein biomarkers. Methods Prospective samples were collected from patients with very severe SOS/VOD at diagnosis and days +3, +7, +14, and +30 post-initiation of defibrotide. Samples from age-matched controls with no VOD were collected at day +14, +30, +60, +90 and +180 following allogeneic HCT. Serum samples were analyzed for 2925 protein levels by antibody-based proximity extension assay (PEA). Mean differences in the log-transformed abundance values were compared using t-tests in a volcano plot. Results Five patients with very severe SOS/VOD and five control patients were compared. Ten proteins were identified that showed a statistically significant and log-transformed 3-fold increase in concentration. They were CALCA, CCL20, GPR37, IGFBP4, IL1RL1, SLC39A14, SPINK4, FABP3, MYL3, and CHCHD10. Four different proteins, namely CD83, LAIR2, CD7, and HEM6 showed a significant decrease with defibrotide treatment. SOS/VOD resolved in 80% (n=4) of patients, while one patient deceased due to SOS/VOD. Conclusion PEA technology identified 10 proteins that were significantly elevated in patients with very severe SOS/VOD. Prospective studies in a larger cohort using this technology may be able to conclusively identify diagnostic protein biomarkers for SOS/VOD.

Diagnostic and progression biomarkers in cerebrospinal fluid of Alzheimer's disease patients

In this commentary, we address a paper published by Johnson et al. by assessing the robustness of their method to discover diagnostic biomarkers in Alzheimer's disease (AD). In addition, we examine how these newly discovered and previously discovered biomarkers, can play a role in assisting patients with AD and those at risk for developing AD, with an emphasis on the translational hurdles that accompany such discoveries.

The relationship between serum astroglial and neuronal markers and AQP4 and MOG autoantibodies

Background

Certain demyelinating disorders, such as neuromyelitis optica spectrum disorder (NMOSD) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) exhibit serum autoantibodies against aquaporin-4 (αAQP4) and myelin oligodendrocyte glycoprotein (αMOG). The variability of the autoantibody presentation warrants further research into subtyping each case.

Methods

To elucidate the relationship between astroglial and neuronal protein concentrations in the peripheral circulation with occurrence of these autoantibodies, 86 serum samples were analyzed using immunoassays. The protein concentration of glial fibrillary acidic protein (GFAP), neurofilament light chain (NFL) and tau protein was measured in 3 groups of subcategories of suspected NMOSD: αAQP4 positive (n = 20), αMOG positive (n = 32) and αMOG/αAQP4 seronegative (n = 34). Kruskal-Wallis analysis, univariate predictor analysis, and multivariate logistic regression with ROC curves were performed.

Results

GFAP and NFL concentrations were significantly elevated in the αAQP4 positive group (p = 0.003; p = 0.042, respectively), and tau was elevated in the αMOG/αAQP4 seronegative group (p < 0.001). A logistic regression model to classify serostatus was able to separate αAQP4 seropositivity using GFAP + tau, and αMOG seropositivity using tau. The areas under the ROC curves (AUCs) were 0.77 and 0.72, respectively. Finally, a combined seropositivity versus negative status logistic regression model was generated, with AUC = 0.80.

Conclusion

The 3 markers can univariately and multivariately classify with moderate accuracy the samples with seropositivity and seronegativity for αAQP4 and αMOG.

Beyond the amyloid hypothesis: how current research implicates autoimmunity in Alzheimer's disease pathogenesis

The amyloid hypothesis has so far been at the forefront of explaining the pathogenesis of Alzheimer's Disease (AD), a progressive neurodegenerative disorder that leads to cognitive decline and eventual death. Recent evidence, however, points to additional factors that contribute to the pathogenesis of this disease. These include the neurovascular hypothesis, the mitochondrial cascade hypothesis, the inflammatory hypothesis, the prion hypothesis, the mutational accumulation hypothesis, and the autoimmunity hypothesis. The purpose of this review was to briefly discuss the factors that are associated with autoimmunity in humans, including sex, the gut and lung microbiomes, age, genetics, and environmental factors. Subsequently, it was to examine the rise of autoimmune phenomena in AD, which can be instigated by a blood-brain barrier breakdown, pathogen infections, and dysfunction of the glymphatic system. Lastly, it was to discuss the various ways by which immune system dysregulation leads to AD, immunomodulating therapies, and future directions in the field of autoimmunity and neurodegeneration. A comprehensive account of the recent research done in the field was extracted from PubMed on 31 January 2022, with the keywords "Alzheimer's disease" and "autoantibodies" for the first search input, and "Alzheimer's disease" with "IgG" for the second. From the first search, 19 papers were selected, because they contained recent research on the autoantibodies found in the biofluids of patients with AD. From the second search, four papers were selected. The analysis of the literature has led to support the autoimmune hypothesis in AD. Autoantibodies were found in biofluids (serum/plasma, cerebrospinal fluid) of patients with AD with multiple methods, including ELISA, Mass Spectrometry, and microarray analysis. Through continuous research, the understanding of the synergistic effects of the various components that lead to AD will pave the way for better therapeutic methods and a deeper understanding of the disease.

Cerebrospinal fluid camk2a levels at baseline predict long-term progression in multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) remains a highly unpredictable disease. Many hope that fluid biomarkers may contribute to better stratification of disease, aiding the personalisation of treatment decisions, ultimately improving patient outcomes.

OBJECTIVE

The objective of this study was to evaluate the predictive value of CSF brain-specific proteins from early in the disease course of MS on long term clinical outcomes.

METHODS

In this study, 34 MS patients had their CSF collected and stored within 5 years of disease onset and were then followed clinically for at least 15 years. CSF concentrations of 64 brain-specific proteins were analyzed in the 34 patient CSF, as well as 19 age and sex-matched controls, using a targeted liquid-chromatography tandem mass spectrometry approach.

RESULTS

We identified six CSF brain-specific proteins that significantly differentiated MS from controls (p < 0.05) and nine proteins that could predict disease course over the next decade. CAMK2A emerged as a biomarker candidate that could discriminate between MS and controls and could predict long-term disease progression.

CONCLUSION

Targeted approaches to identify and quantify biomarkers associated with MS in the CSF may inform on long term MS outcomes. CAMK2A may be one of several candidates, warranting further exploration.

Tachykinins and the potential causal factors for post-COVID-19 condition

The most prevalent symptoms of post-COVID-19 condition are pulmonary dysfunction, fatigue and muscle weakness, anxiety, anosmia, dysgeusia, headaches, difficulty in concentrating, sexual dysfunction, and digestive disturbances. Hence, neurological dysfunction and autonomic impairments predominate in post-COVID-19 condition. Tachykinins including the most studied substance P are neuropeptides expressed throughout the nervous and immune systems, and contribute to many physiopathological processes in the nervous, immune, gastrointestinal, respiratory, urogenital, and dermal systems and participate in inflammation, nociception, and cell proliferation. Substance P is a key molecule in neuroimmune crosstalk; immune cells near the peripheral nerve endings can send signals to the brain with cytokines, which highlights the important role of tachykinins in neuroimmune communication. We reviewed the evidence that relates the symptoms of post-COVID-19 condition to the functions of tachykinins and propose a putative pathogenic mechanism. The antagonism of tachykinins receptors can be a potential treatment target.

Quantitation of neurofilament light chain protein in serum and cerebrospinal fluid from patients with multiple sclerosis using the MSD R-PLEX NfL assay

OBJECTIVES

Neurofilament light (NfL) chain is a marker of neuroaxonal damage in various neurological diseases. Here we quantitated NfL levels in the cerebrospinal fluid (CSF) and serum from patients with multiple sclerosis (MS) and controls, using the R-PLEX NfL assay, which employs advanced Meso Scale Discovery® (MSD) electrochemiluminescence (ECL)-based detection technology.

METHODS

NfL was quantitated in samples from 116 individuals from two sites (Ottawa Hospital Research Institute and Mayo Clinic), consisting of patients with MS (n=71) and age- and sex-matched inflammatory neurological controls (n=13) and non-inflammatory controls (n=32). Correlation of NfL levels between CSF and serum was assessed in paired samples in a subset of MS patients and controls (n=61). Additionally, we assessed the correlation between NfL levels obtained with MSD's R-PLEX® and Quanterix's single molecule array (Simoa®) assays in CSF and serum (n=32).

RESULTS

Using the R-PLEX, NfL was quantitated in 99% of the samples tested, and showed a broad range in the CSF (82-500,000 ng/L) and serum (8.84-2,014 ng/L). Nf-L levels in both biofluids correlated strongly (r=0.81, p<0.0001). Lastly, Nf-L measured by MSD's R-PLEX and Quanterix's Simoa assays were highly correlated for both biofluids (CSF: r=0.94, p<0.0001; serum: r=0.95, p<0.0001).

CONCLUSIONS

We show that MSD's R-PLEX NfL assay can reliably quantitate levels of NfL in the CSF and serum from patients with MS and controls, where levels correlate strongly with Simoa.

B cell profiles, antibody repertoire and reactivity reveal dysregulated responses with autoimmune features in melanoma

B cells are known to contribute to the anti-tumor immune response, especially in immunogenic tumors such as melanoma, yet humoral immunity has not been characterized in these cancers to detail. Here we show comprehensive phenotyping in samples of circulating and tumor-resident B cells as well as serum antibodies in melanoma patients. Memory B cells are enriched in tumors compared to blood in paired samples and feature distinct antibody repertoires, linked to specific isotypes. Tumor-associated B cells undergo clonal expansion, class switch recombination, somatic hypermutation and receptor revision. Compared with blood, tumor-associated B cells produce antibodies with proportionally higher levels of unproductive sequences and distinct complementarity determining region 3 properties. The observed features are signs of affinity maturation and polyreactivity and suggest an active and aberrant autoimmune-like reaction in the tumor microenvironment. Consistent with this, tumor-derived antibodies are polyreactive and characterized by autoantigen recognition. Serum antibodies show reactivity to antigens attributed to autoimmune diseases and cancer, and their levels are higher in patients with active disease compared to post-resection state. Our findings thus reveal B cell lineage dysregulation with distinct antibody repertoire and specificity, alongside clonally-expanded tumor-infiltrating B cells with autoimmune-like features, shaping the humoral immune response in melanoma.

Discovery of novel glioma serum biomarkers by proximity extension assay

BACKGROUND

Gliomas are among the most malignant tumors, with a very poor prognosis. Early diagnosis is highly desirable since it can help implement more effective treatments for smaller tumors, which have not yet extensively metastasized. Improving early diagnosis may facilitate access of patients to clinical trials and prepare them for the future availability of new disease-modifying treatments.

METHODS

We analyzed retrospective samples collected at diagnosis (before therapy initiation), with PEA (Olink Proteomics), quantifying about 3000 proteins. We utilized 30 plasmas from gliomas (20 glioblastomas, 5 anaplastic astrocytomas, 5 anaplastic oligodendrogliomas) and 20 meningiomas (as controls). We then analyzed the data to identify proteins which either alone, or in combination, could discriminate gliomas from meningiomas, or correlate with clinical and molecular alterations.

RESULTS

We identified 8 plasma proteins which were increased in gliomas vs. meningiomas (GFAP, NEFL, EDDM3B, PROK1, MMP3, CTRL, GP2, SPINT3) and 4 proteins which were decreased in gliomas vs. meningiomas (FABP4, ALDH3A1, IL-12B and OXT). Partition algorithms and logistic regression algorithms with two biomarkers (GFAP and FABP4) achieved sensitivity of 83% and 93% at 100% and 90% specificity, respectively. The strongest single marker was GFAP with an area under the ROC curve (AUC) of 0.86. The AUC for the GFAP-FABP4 combination was 0.98.

CONCLUSION

PEA is a powerful new proteomic technology for biomarker discovery. GFAP and a handful of other plasma biomarkers may be useful for early glioma detection and probably, prognosis.

STATEMENT

Detecting gliomas as early as possible is highly desirable since it can significantly improve the chances of effective treatments. Reliable glioma biomarkers can timely inform glioma patients about the efficacy of their prescribed treatment. Our results reveal some novel putative glioma markers that may prove valuable, when used alone or in combination, towards improved clinical care of gliomas. In order to better appreciate the potential usefulness of these markers, their performance needs to be further validated in a larger cohort of samples.

Quantitation of cardiac troponin I in cancer patients treated with immune checkpoint inhibitors: a case-control study

OBJECTIVES

Immune checkpoint inhibitors (ICIs) cause a variety of toxicities, including immune-related adverse events (irAEs), but there are no biomarkers to predict their development. Guidelines recommend measuring circulating cardiac troponin I (cTnI) during ICI therapy to detect related cardiotoxicities. Moreover, elevated cTnI has also been associated with worse outcomes in non-cardiac patients, including cancer. Thus here, we investigated whether cTnI levels were higher in patients with irAEs.

METHODS

The study consisted of three groups; 21 cancer patients undergoing ICI immunotherapies who presented with irAEs, four patients without irAEs, and 20 healthy controls. Patient samples were assessed at baseline (n=25), during ICI treatment (n=25, median=6 weeks of treatment) and at toxicity (n=6, median=13 weeks of treatment). In addition to blood high sensitivity cardiac troponin I (hs-cTnI), anti-thyroglobulin (TG) and anti-thyroid peroxidase (TPO) antibodies were also quantitated to detect thyroid dysfunction, constituting the second leading toxicity (23.8%) after pneumonitis (28.6%).

RESULTS

Four patients with irAEs (n=4/21; 19%) and one without irAEs (n=1/4; 25%) showed higher hs-cTnI levels at any time-point; the remaining had physiological levels. None of these patients developed cardiotoxicity. Concurrent elevated levels of anti-thyroid antibodies and hs-cTnI were detected in one patient with thyroid dysfunction (n=1/5, 20%). However, these antibodies were also elevated in three patients (n=3/16, 19%) with non-thyroid irAEs and in up to 40% of healthy controls.

CONCLUSIONS

hs-cTnI was not elevated in patients with irAEs, but larger studies are needed to confirm these observations.

Multiplex proteomics using proximity extension assay for the identification of protein biomarkers predictive of acute graft-vs.-host disease in allogeneic hematopoietic cell transplantation

OBJECTIVES

Allogeneic hematopoietic cell transplantation (HCT) is associated with acute graft-vs.-host disease (aGVHD). The presented study applied a novel multiplex antibody-based proximity extension assay (PEA) proteomic platform that can detect thousands of serum proteins simultaneously for the identification of potential biomarkers of aGVHD.

METHODS

Serum samples from 28 patients who underwent allogeneic HCT for acute myeloid leukemia (AML) were analyzed; 17 were diagnosed with grade II-IV aGVHD while 11 patients were not. Samples collected on day -6, day 0, +14, +30, +60 and +90 post-HCT were analyzed for the relative concentrations of 552 proteins. The concentration of each protein from baseline to the closest time point before onset of aGVHD, or to the latest time point in control patients, was documented.

RESULTS

Individualized analysis identified 26 proteins demonstrating ≥3-fold increase at aGVHD onset compared to baseline, eliminating proteins with a similar increase in controls. Another approach used paired t-testing and logistic regression that identified a four-marker panel, including SLAMF7, IL-1ra, BTN3A2 and DAB2, where individual log-likelihood ratios ranged from 3.99 to 8.15 (logistic regression, p=0.004-0.046). When combined, the four-marker panel demonstrated an area under the curve (AUC) of 0.90 (95% CI: 0.78-1.00; p=0.0006) with high negative predictive value of 81.8% and positive predictive value of 86.7%. All four markers play a physiological role in immune regulation. Among these, three were also present in the individualized analysis (SLAMF7, IL-1ra and BTN3A2).

CONCLUSIONS

We conclude that serum proteins identified using multiplex proteomics, particularly SLAMF7, IL-1ra, BTN3A2 and DAB2, may potentially predict aGVHD.

The therapeutic relevance of the Kallikrein-Kinin axis in SARS-cov-2-induced vascular pathology

While coronavirus disease 2019 (COVID-19) begins as a respiratory infection, it progresses as a systemic disease involving multiorgan microthromboses that underly the pathology. SARS-CoV-2 enters host cells via attachment to the angiotensin-converting enzyme 2 (ACE2) receptor. ACE2 is widely expressed in a multitude of tissues, including the lung (alveolar cells), heart, intestine, kidney, testis, gallbladder, vasculature (endothelial cells), and immune cells. Interference in ACE2 signaling could drive the aforementioned systemic pathologies, such as endothelial dysfunction, microthromboses, and systemic inflammation, that are typically seen in patients with severe COVID-19. ACE2 is a component of the renin-angiotensin system (RAS) and is intimately associated with the plasma kallikrein-kinin system (KKS). As many papers are published on the role of ACE and ACE2 in COVID-19, we will review the role of bradykinin, and more broadly the KSS, in SARS-CoV-2-induced vascular dysfunction. Furthermore, we will discuss the possible therapeutic interventions that are approved and in development for the following targets: coagulation factor XII (FXII), tissue kallikrein (KLK1), plasma kallikrein (KLKB1), bradykinin (BK), plasminogen activator inhibitor (PAI-1), bradykinin B1 receptor (BKB1R), bradykinin B2 receptor (BKB2R), ACE, furin, and the NLRP3 inflammasome. Understanding these targets may prove of value in the treatment of COVID-19 as well as in other virus-induced coagulopathies in the future.

Sensitive Serology Measurements in the Saliva of Individuals with COVID-19 Symptoms Using a Multiplexed Immunoassay

Background

There are numerous benefits to performing salivary serology measurements for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative pathogen for coronavirus disease 2019 (COVID-19). Here, we used a sensitive multiplex serology assay to quantitate salivary IgG against 4 SARS-CoV-2 antigens: nucleocapsid, receptor-binding domain, spike, and N-terminal domain.

Methods

We used single samples from 90 individuals with COVID-19 diagnosis collected at 0 to 42 days postsymptom onset (PSO) and from 15 uninfected control subjects. The infected individuals were segmented in 4 groups (0–7 days, 8–14 days, 15–21 days, and >21 days) based on days PSO, and values were compared to controls.

Results

Compared to controls, infected individuals showed higher levels of antibodies against all antigens starting from 8 days PSO. When applying cut-offs with at least 93.3% specificity at every time interval segment, nucleocapsid protein serology had the best sensitivity at 0 to 7 days PSO (60% sensitivity [35.75% to 80.18%], ROC area under the curve [AUC] = 0.73, P = 0.034). Receptor-binding domain serology had the best sensitivity at 8 to 14 days PSO (83.33% sensitivity [66.44%–92.66%], ROC AUC = 0.90, P < 0.0001), and all assays except for N-terminal domain had 92% sensitivity (75.03%–98.58%) at >14 days PSO.

Conclusions

This study shows that our multiplexed immunoassay can distinguish infected from uninfected individuals and reliably (93.3% specificity) detect seroconversion (in 60% of infected individuals) as early as the first week PSO, using easy-to-collect saliva samples.

Electronic field effect detection of SARS-CoV-2 N-protein before the onset of symptoms

As part of the efforts to contain the pandemic, researchers around the world have raced to develop testing platforms to detect the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes the Coronavirus disease 2019 (COVID-19). Within the different detection platforms studied, the field effect transistor (FET) is a promising device due to its high sensitivity and fast detection capabilities. In this work, a graphene-based FET which uses a boron and nitrogen co-doped graphene oxide gel (BN-GO gel) transducer functionalized with nucleoprotein antibodies, has been investigated for the detection of SARS-CoV-2 nucleocapsid (N)-protein in buffer. This biosensor was able to detect the viral protein in less than 4 min, with a limit of detection (LOD) as low as 10 ag/mL and a wide linear detection range stretching over 11 orders of magnitude from 10 ag/mL-1 μg/mL. This represents the lowest LOD and widest detection range of any COVID-19 sensor and thus can potentially enable the detection of infected individuals before they become contagious. In addition to its potential use in the COVID-19 pandemic, our device serves as a proof-of-concept of the ability of functionalized BN-GO gel FETs to be used for ultrasensitive yet robust biosensors.

Patients with severe COVID-19 do not have elevated autoantibodies against common diagnostic autoantigens

OBJECTIVES

Infection by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the causative pathogen of coronavirus disease 2019 (COVID-19) presents occasionally with an aberrant autoinflammatory response, including the presence of elevated circulating autoantibodies in some individuals. Whether the development of autoantibodies against self-antigens affects COVID-19 outcomes remains unclear. To better understand the prognostic role of autoantibodies in COVID-19, we quantified autoantibodies against 23 markers that are used for diagnosis of autoimmune disease. To this end, we used serum samples from patients with severe [intensive care unit (ICU)] and moderate (ward) COVID-19, across two to six consecutive time points, and compared autoantibody levels to uninfected healthy and ICU controls.

METHODS

Acute and post-acute serum (from 1 to 26 ICU days) was collected from 18 ICU COVID-19-positive patients at three to six time points; 18 ICU COVID-19-negative patients (sampled on ICU day 1 and 3); 21 ward COVID-19-positive patients (sampled on hospital day 1 and 3); and from 59 healthy uninfected controls deriving from two cohorts. Levels of IgG autoantibodies against 23 autoantigens, commonly used for autoimmune disease diagnosis, were measured in serum samples using MSD^® U-PLEX electrochemiluminescence technology (MSD division Meso Scale Discovery^®), and results were compared between groups.

RESULTS

There were no significant elevations of autoantibodies for any of the markers tested in patients with severe COVID-19.

CONCLUSIONS

Sample collections at longer time points should be considered in future studies, for assessing the possible development of autoantibody responses following infection with SARS-CoV-2.

Ultrasensitive assay for saliva-based SARS-CoV-2 antigen detection

OBJECTIVES

Widespread SARS-CoV-2 testing is invaluable for identifying asymptomatic/pre-symptomatic individuals. There remains a technological gap for highly reliable, easy, and quick SARS-CoV-2 diagnostic tests suitable for frequent mass testing. Compared to nasopharyngeal (NP) swab-based tests, saliva-based methods are attractive due to easier and safer sampling. Current saliva-based SARS-CoV-2 rapid antigen tests (RATs) are hindered by limited analytical sensitivity. Here, we report one of the first ultrasensitive, saliva-based SARS-CoV-2 antigen assays with an analytical sensitivity of <0.32 pg/mL, corresponding to four viral RNA copies/µL, which is comparable to that of PCR-based tests.

METHODS

Using the novel electrochemiluminescence (ECL)-based immunoassay, we measured the SARS-CoV-2 nucleocapsid (N) antigen concentration in 105 salivas, obtained from non-COVID-19 and COVID-19 patients. We then verified the results with a second, independent cohort of 689 patients (3.8% SARS-CoV-2 positivity rate). We also compared our method with a widely used point-of-care rapid test.

RESULTS

In the first cohort, at 100% specificity, the sensitivity was 92%. Our assay correctly identified samples with viral loads up to 35 CT cycles by saliva-based PCR. Paired NP swab-based PCR results were obtained for 86 cases. Our assay showed high concordance with saliva-based and NP swab-based PCR in samples with negative (<0.32 pg/mL) and strongly positive (>2 pg/mL) N antigen concentrations. In the second cohort, at 100% specificity, sensitivity was also 92%. Our assay is about 700-fold more sensitive than the Abbott Panbio Rapid Test.

CONCLUSIONS

We demonstrated the ultrasensitivity and specificity assay and its concordance with PCR. This novel assay is especially valuable when compliance to frequent swabbing may be problematic.

Putative Concussion Biomarkers Identified in Adolescent Male Athletes Using Targeted Plasma Proteomics

Sport concussions can be difficult to diagnose and if missed, they can expose athletes to greater injury risk and long-lasting neurological disabilities. Discovery of objective biomarkers to aid concussion diagnosis is critical to protecting athlete brain health. To this end, we performed targeted proteomics on plasma obtained from adolescent athletes suffering a sports concussion. A total of 11 concussed male athletes were enrolled at our academic Sport Medicine Concussion Clinic, as well as 24 sex-, age- and activity-matched healthy control subjects. Clinical evaluation was performed and blood was drawn within 72 h of injury. Proximity extension assays were performed for 1,472 plasma proteins; a total of six proteins were considered significantly different between cohorts (P < 0.01; five proteins decreased and one protein increased). Receiver operating characteristic curves on the six individual protein biomarkers identified had areas-under-the-curves (AUCs) for concussion diagnosis ≥0.78; antioxidant 1 copper chaperone (ATOX1; AUC 0.81, P = 0.003), secreted protein acidic and rich in cysteine (SPARC; AUC 0.81, P = 0.004), cluster of differentiation 34 (CD34; AUC 0.79, P = 0.006), polyglutamine binding protein 1 (PQBP1; AUC 0.78, P = 0.008), insulin-like growth factor-binding protein-like 1 (IGFBPL1; AUC 0.78, P = 0.008) and cytosolic 5'-nucleotidase 3A (NT5C3A; AUC 0.78, P = 0.009). Combining three of the protein biomarkers (ATOX1, SPARC and NT5C3A), produced an AUC of 0.98 for concussion diagnoses (P < 0.001; 95% CI: 0.95, 1.00). Despite a paucity of studies on these three identified proteins, the available evidence points to their roles in modulating tissue inflammation and regulating integrity of the cerebral microvasculature. Taken together, our exploratory data suggest that three or less novel proteins, which are amenable to a point-of-care immunoassay, may be future candidate biomarkers for screening adolescent sport concussion. Validation with protein assays is required in larger cohorts.