Toward the quantification of α-synuclein aggregates with digital seed amplification assays.

The quantification and characterization of aggregated α-synuclein in clinical samples offer immense potential toward diagnosing, treating, and better understanding neurodegenerative synucleinopathies. Here, we developed digital seed amplification assays to detect single α-synuclein aggregates by partitioning the reaction into microcompartments. Using pre-formed α-synuclein fibrils as reaction seeds, we measured aggregate concentrations as low as 4 pg/mL. To improve our sensitivity, we captured aggregates on antibody-coated magnetic beads before running the amplification reaction. By first characterizing the pre-formed fibrils with transmission electron microscopy and size exclusion chromatography, we determined the specific aggregates targeted by each assay platform. Using brain tissue and cerebrospinal fluid samples collected from patients with Parkinson's Disease and multiple system atrophy, we demonstrated that the assay can detect endogenous pathological α-synuclein aggregates. Furthermore, as another application for these assays, we studied the inhibition of α-synuclein aggregation in the presence of small-molecule inhibitors and used a custom image analysis pipeline to quantify changes in aggregate growth and filament morphology.

Current and new frontiers in hereditary cancer surveillance: Opportunities for liquid biopsy.

At least 5% of cancer diagnoses are attributed to a causal pathogenic or likely pathogenic germline genetic variant (hereditary cancer syndrome-HCS). These individuals are burdened with lifelong surveillance monitoring organs for a wide spectrum of cancers. This is associated with substantial uncertainty and anxiety in the time between screening tests and while the individuals are awaiting results. Cell-free DNA (cfDNA) sequencing has recently shown potential as a non-invasive strategy for monitoring cancer. There is an opportunity for high-yield cancer early detection in HCS. To assess clinical validity of cfDNA in individuals with HCS, representatives from eight genetics centers from across Canada founded the CHARM (cfDNA in Hereditary and High-Risk Malignancies) Consortium in 2017. In this perspective, we discuss operationalization of this consortium and early data emerging from the most common and well-characterized HCSs: hereditary breast and ovarian cancer, Lynch syndrome, Li-Fraumeni syndrome, and Neurofibromatosis type 1. We identify opportunities for the incorporation of cfDNA sequencing into surveillance protocols; these opportunities are backed by examples of earlier cancer detection efficacy in HCSs from the CHARM Consortium. We seek to establish a paradigm shift in early cancer surveillance in individuals with HCSs, away from highly centralized, regimented medical screening visits and toward more accessible, frequent, and proactive care for these high-risk individuals.

Ultrasensitive Protein Detection Technologies for Extracellular Vesicle Measurements.

Extracellular vesicles (EVs) are nanoscopic, heterogenous, lipid-rich particles that carry a multitude of cargo biomolecules including proteins, nucleic acids, and metabolites. Although historically EVs were regarded as cellular debris with no intrinsic value, growing understanding of EV biogenesis has led to the realization that EVs facilitate intercellular communication and are sources of liquid biomarkers. EVs can be isolated and analyzed from a wide variety of accessible biofluids for biomarker discovery and diagnostic applications. There is a diversity of EVs from different biological compartments (e.g., cells and tissues), and some of these EVs are present at extremely low concentrations. Consequently, a challenge in the field is to find appropriate markers that enable selective isolation of these rare EVs. Many conventional protein detection technologies have limited sensitivity to detect low abundance biomarkers in EVs, limiting their use in EV research. Advances in ultrasensitive detection technologies are needed to harness the potential of EVs for clinical application. This Perspective highlights current EV research focusing on ultrasensitive detection technologies, their limitations, and areas of potential growth in the future.

L1CAM is not associated with extracellular vesicles in human cerebrospinal fluid or plasma.

L1CAM is a transmembrane protein expressed on neurons that was presumed to be found on neuron-derived extracellular vesicles (NDEVs) in human biofluids. We developed a panel of single-molecule array assays to evaluate the use of L1CAM for NDEV isolation. We demonstrate that L1CAM is not associated with extracellular vesicles in human plasma or cerebrospinal fluid and therefore recommend against its use as a marker in NDEV isolation protocols.

Stay at home: implementation and impact of virtualising cancer genetic services during COVID-19.

The COVID-19 pandemic has led to the rapid adoption of virtual clinic processes and healthcare delivery. Herein, we examine the impact of virtualising genetics services at Canada's largest cancer centre. A retrospective review was conducted to evaluate relevant metrics during the 12 weeks prior to and during virtual care, including referral and clinic volumes, patient wait times and genetic testing uptake. The number of appointments and new patients seen were maintained during virtual care. Likewise, there was a significant increase in the number of patients offered testing during virtual care who did not provide a blood sample (176/180 (97.7%) vs 180/243 (74.1%); p<0.001), and a longer median time from the date of pretest genetic counselling to the date a sample was given (0 vs 11 days; p<0.001). Referral volumes significantly decreased during virtual care (35 vs 22; p<0.001), which was accompanied by a decreased median wait time for first appointment (55 days vs 30 days; p<0.001). The rapid virtualisation of cancer genetic services allowed the genetics clinic to navigate the COVID-19 pandemic without compromising clinical volumes or access to genetic testing. There was a decrease in referral volumes and uptake of genetic testing, which may be attributable to pandemic-related clinical restrictions.

High-Sensitivity Single Molecule Array Assays for Pathological Isoforms in Parkinson's Disease.

BACKGROUND: Clinical trials for neurodegenerative diseases are increasingly utilizing measurements of post-translational modifications (PTMs) and pathological isoforms as surrogate markers of target engagement and therapeutic efficacy. These isoforms, however, tend to exist at femtomolar concentrations, well below the detection limit of conventional immunoassays. Therefore, highly sensitive and well-validated assays for these isoforms are needed. METHODS: We developed a novel panel of single molecule array assays for pathological isoforms and PTMs implicated in the development and pathophysiology of Parkinson's disease. We validated this panel by measuring these analytes in the cerebrospinal fluid of a cross-sectional cohort of 100 patients with Parkinson's disease and 100 healthy controls. RESULTS: When comparing patients with Parkinson's disease to healthy controls, alpha synuclein, pSer129 alpha synuclein, DJ-1, and C-reactive protein were shown to be reduced in patients with Parkinson's disease while p396 tau and neurofilament light chain were shown to be increased. A random forest analysis produced an area under the curve of 0.70 for the panel. CONCLUSIONS: Measurement of post-translational modifications and pathological isoforms in patients with Parkinson's disease improved diagnostic accuracy above that of total protein measurements, demonstrating the potential utility of these assays for monitoring patients in clinical trials.

Evaluation of serological lateral flow assays for severe acute respiratory syndrome coronavirus-2.

BACKGROUND: COVID-19 has resulted in significant morbidity and mortality worldwide. Lateral flow assays can detect anti-Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) antibodies to monitor transmission. However, standardized evaluation of their accuracy and tools to aid in interpreting results are needed. METHODS: We evaluated 20 IgG and IgM assays selected from available tests in April 2020. We evaluated the assays' performance using 56 pre-pandemic negative and 56 SARS-CoV-2-positive plasma samples, collected 10-40 days after symptom onset, confirmed by a molecular test and analyzed by an ultra-sensitive immunoassay. Finally, we developed a user-friendly web app to extrapolate the positive predictive values based on their accuracy and local prevalence. RESULTS: Combined IgG + IgM sensitivities ranged from 33.9 to 94.6%, while combined specificities ranged from 92.6 to 100%. The highest sensitivities were detected in Lumiquick for IgG (98.2%), BioHit for both IgM (96.4%), and combined IgG + IgM sensitivity (94.6%). Furthermore, 11 LFAs and 8 LFAs showed perfect specificity for IgG and IgM, respectively, with 15 LFAs showing perfect combined IgG + IgM specificity. Lumiquick had the lowest estimated limit-of-detection (LOD) (0.1 µg/mL), followed by a similar LOD of 1.5 µg/mL for CareHealth, Cellex, KHB, and Vivachek. CONCLUSION: We provide a public resource of the accuracy of select lateral flow assays with potential for home testing. The cost-effectiveness, scalable manufacturing process, and suitability for self-testing makes LFAs an attractive option for monitoring disease prevalence and assessing vaccine responsiveness. Our web tool provides an easy-to-use interface to demonstrate the impact of prevalence and test accuracy on the positive predictive values.

Ultra-Sensitive Serial Profiling of SARS-CoV-2 Antigens and Antibodies in Plasma to Understand Disease Progression in COVID-19 Patients with Severe Disease.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected over 21 million people worldwide since August 16, 2020. Compared to PCR and serology tests, SARS-CoV-2 antigen assays are underdeveloped, despite their potential to identify active infection and monitor disease progression. METHODS: We used Single Molecule Array (Simoa) assays to quantitatively detect SARS-CoV-2 spike, S1 subunit, and nucleocapsid antigens in the plasma of patients with coronavirus disease (COVID-19). We studied plasma from 64 patients who were COVID-19 positive, 17 who were COVID-19 negative, and 34 prepandemic patients. Combined with Simoa anti-SARS-CoV-2 serological assays, we quantified changes in 31 SARS-CoV-2 biomarkers in 272 longitudinal plasma samples obtained for 39 patients with COVID-19. Data were analyzed by hierarchical clustering and were compared to longitudinal RT-PCR test results and clinical outcomes. RESULTS: SARS-CoV-2 S1 and N antigens were detectable in 41 out of 64 COVID-19 positive patients. In these patients, full antigen clearance in plasma was observed a mean ± 95% CI of 5 ± 1 days after seroconversion and nasopharyngeal RT-PCR tests reported positive results for 15 ± 5 days after viral-antigen clearance. Correlation between patients with high concentrations of S1 antigen and ICU admission (77%) and time to intubation (within 1 day) was statistically significant. CONCLUSIONS: The reported SARS-CoV-2 Simoa antigen assay is the first to detect viral antigens in the plasma of patients who were COVID-19 positive to date. These data show that SARS-CoV-2 viral antigens in the blood are associated with disease progression, such as respiratory failure, in COVID-19 cases with severe disease.

Early Cancer Detection in Li-Fraumeni Syndrome with Cell-Free DNA.

People with Li-Fraumeni syndrome (LFS) harbor a germline pathogenic variant in the TP53 tumor suppressor gene, face a near 100% lifetime risk of cancer, and routinely undergo intensive surveillance protocols. Liquid biopsy has become an attractive tool for a range of clinical applications, including early cancer detection. Here, we provide a proof-of-principle for a multimodal liquid biopsy assay that integrates a targeted gene panel, shallow whole-genome, and cell-free methylated DNA immunoprecipitation sequencing for the early detection of cancer in a longitudinal cohort of 89 LFS patients. Multimodal analysis increased our detection rate in patients with an active cancer diagnosis over uni-modal analysis and was able to detect cancer-associated signal(s) in carriers prior to diagnosis with conventional screening (positive predictive value = 67.6%, negative predictive value = 96.5%). Although adoption of liquid biopsy into current surveillance will require further clinical validation, this study provides a framework for individuals with LFS. SIGNIFICANCE: By utilizing an integrated cell-free DNA approach, liquid biopsy shows earlier detection of cancer in patients with LFS compared with current clinical surveillance methods such as imaging. Liquid biopsy provides improved accessibility and sensitivity, complementing current clinical surveillance methods to provide better care for these patients. See related commentary by Latham et al., p. 23. This article is featured in Selected Articles from This Issue, p. 5.

Framework for rapid comparison of extracellular vesicle isolation methods.

Extracellular vesicles (EVs) are released by all cells into biofluids and hold great promise as reservoirs of disease biomarkers. One of the main challenges in studying EVs is a lack of methods to quantify EVs that are sensitive enough and can differentiate EVs from similarly sized lipoproteins and protein aggregates. We demonstrate the use of ultrasensitive, single-molecule array (Simoa) assays for the quantification of EVs using three widely expressed transmembrane proteins: the tetraspanins CD9, CD63, and CD81. Using Simoa to measure these three EV markers, as well as albumin to measure protein contamination, we were able to compare the relative efficiency and purity of several commonly used EV isolation methods in plasma and cerebrospinal fluid (CSF): ultracentrifugation, precipitation, and size exclusion chromatography (SEC). We further used these assays, all on one platform, to improve SEC isolation from plasma and CSF. Our results highlight the utility of quantifying EV proteins using Simoa and provide a rapid framework for comparing and improving EV isolation methods from biofluids.

Evaluation of Three Commercial and Two Non-Commercial Immunoassays for the Detection of Prior Infection to SARS-CoV-2.

BACKGROUND: Serological testing provides a record of prior infection with SARS-CoV-2, but assay performance requires independent assessment. METHODS: We evaluated 3 commercial (Roche Diagnostics pan-IG, and Epitope Diagnostics IgM and IgG) and 2 non-commercial (Simoa and Ragon/MGH IgG) immunoassays against 1083 unique samples that included 251 PCR-positive and 832 prepandemic samples. RESULTS: The Roche assay registered the highest specificity 99.6% (3/832 false positives), the Ragon/MGH assay 99.5% (4/832), the primary Simoa assay model 99.0% (8/832), and the Epitope IgG and IgM 99.0% (8/830) and 99.5% (4/830), respectively. Overall sensitivities for the Simoa, Roche pan-IG, Epitope IgG, Ragon/MGH IgG, and Epitope IgM were 92.0%, 82.9%, 82.5%, 64.5% and 47.0%, respectively. The Simoa immunoassay demonstrated the highest sensitivity among samples stratified by days postsymptom onset (PSO), <8 days PSO (57.69%) 8-14 days PSO (93.51%), 15-21 days PSO (100%), and > 21 days PSO (95.18%). CONCLUSIONS: All assays demonstrated high to very high specificities while sensitivities were variable across assays.

Ultra-Sensitive High-Resolution Profiling of Anti-SARS-CoV-2 Antibodies for Detecting Early Seroconversion in COVID-19 Patients.

The COVID-19 pandemic continues to infect millions of people worldwide. In order to curb its spread and reduce morbidity and mortality, it is essential to develop sensitive and quantitative methods that identify infected individuals and enable accurate population-wide screening of both past and present infection. Here we show that Single Molecule Array assays detect seroconversion in COVID-19 patients as soon as one day after symptom onset using less than a microliter of blood. This multiplexed assay format allows us to quantitate IgG, IgM and IgA immunoglobulins against four SARS-CoV-2 targets, thereby interrogating 12 antibody isotype-viral protein interactions to give a high resolution profile of the immune response. Using a cohort of samples collected prior to the outbreak as well as samples collected during the pandemic, we demonstrate a sensitivity of 86% and a specificity of 100% during the first week of infection, and 100% sensitivity and specificity thereafter. This assay should become the gold standard for COVID19 serological profiling and will be a valuable tool for answering important questions about the heterogeneity of clinical presentation seen in the ongoing pandemic.

Evaluation of two commercial and two non-commercial immunoassays for the detection of prior infection to SARS-CoV-2.

Background Seroepidemiology is an important tool to characterize the epidemiology and immunobiology of SARS-CoV-2 but many immunoassays have not been externally validated raising questions about reliability of study findings. To ensure meaningful data, particularly in a low seroprevalence population, assays need to be rigorously characterized with high specificity. Methods We evaluated two commercial (Roche Diagnostics and Epitope Diagnostics IgM/IgG) and two non-commercial (Simoa and Ragon/MGH IgG) immunoassays against 68 confirmed positive and 232 pre-pandemic negative controls. Sensitivity was stratified by time from symptom onset. The Simoa multiplex assay applied three pre-defined algorithm models to determine sample result. Results The Roche and Ragon/MGH IgG assays each registered 1/232 false positive, the primary Simoa model registered 2/232 false positives, and the Epitope registered 2/230 and 3/230 false positives for the IgG and IgM assays respectively. Sensitivity >21 days post symptom-onset was 100% for all assays except Epitope IgM, but lower and/or with greater variability between assays for samples collected 9-14 days (67-100%) and 15-21 days (69-100%) post-symptom onset. The Simoa and Epitope IgG assays demonstrated excellent sensitivity earlier in the disease course. The Roche and Ragon/MGH IgG assays were less sensitive during early disease, particularly among immunosuppressed individuals. Conclusions The Epitope IgG demonstrated good sensitivity and specificity. The Roche and Ragon/MGH IgG assays registered rare false positives with lower early sensitivity. The Simoa assay primary model had excellent sensitivity and few false positives.

Ultrasensitive high-resolution profiling of early seroconversion in patients with COVID-19.

Sensitive assays are essential for the accurate identification of individuals infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, we report a multiplexed assay for the fluorescence-based detection of seroconversion in infected individuals from less than 1 µl of blood, and as early as the day of the first positive nucleic acid test after symptom onset. The assay uses dye-encoded antigen-coated beads to quantify the levels of immunoglobulin G (IgG), IgM and IgA antibodies against four SARS-CoV-2 antigens. A logistic regression model trained using samples collected during the pandemic and samples collected from healthy individuals and patients with respiratory infections before the first outbreak of coronavirus disease 2019 (COVID-19) was 99% accurate in the detection of seroconversion in a blinded validation cohort of samples collected before the pandemic and from patients with COVID-19 five or more days after a positive nasopharyngeal test by PCR with reverse transcription. The high-throughput serological profiling of patients with COVID-19 allows for the interrogation of interactions between antibody isotypes and viral proteins, and should help us to understand the heterogeneity of clinical presentations.