ABSTRACT
The effects of mutations in continuously emerging variants of SARS-CoV-2 are a major concern for the performance of rapid antigen tests. To evaluate the impact of mutations on 17 antibodies used in 11 commercially available antigen tests with emergency use authorization, we measured antibody binding for all possible Nucleocapsid point mutations using a mammalian surface-display platform and deep mutational scanning. The results provide a complete map of the antibodies' epitopes and their susceptibility to mutational escape. Our data predict no vulnerabilities for detection of mutations found in variants of concern. We confirm this using the commercial tests and sequence-confirmed COVID-19 patient samples. The antibody escape mutational profiles generated here serve as a valuable resource for predicting the performance of rapid antigen tests against past, current, as well as any possible future variants of SARS-CoV-2, establishing the direct clinical and public health utility of our system.
Subject(s)
COVID-19 , SARS-CoV-2 , Animals , Antibodies, Neutralizing , Antibodies, Viral , Epitopes/genetics , Humans , Mammals , Mutation , Nucleocapsid , SARS-CoV-2/geneticsABSTRACT
We conducted a serological study to define correlates of immunity against SARS-CoV-2. Compared to those with mild coronavirus disease 2019 (COVID-19) cases, individuals with severe disease exhibited elevated virus-neutralizing titers and antibodies against the nucleocapsid (N) and the receptor binding domain (RBD) of the spike protein. Age and sex played lesser roles. All cases, including asymptomatic individuals, seroconverted by 2 weeks after PCR confirmation. Spike RBD and S2 and neutralizing antibodies remained detectable through 5-7 months after onset, whereas α-N titers diminished. Testing 5,882 members of the local community revealed only 1 sample with seroreactivity to both RBD and S2 that lacked neutralizing antibodies. This fidelity could not be achieved with either RBD or S2 alone. Thus, inclusion of multiple independent assays improved the accuracy of antibody tests in low-seroprevalence communities and revealed differences in antibody kinetics depending on the antigen. We conclude that neutralizing antibodies are stably produced for at least 5-7 months after SARS-CoV-2 infection.
Subject(s)
Betacoronavirus/immunology , Clinical Laboratory Techniques/methods , Coronavirus Infections/epidemiology , Coronavirus Infections/immunology , Immunity, Humoral , Pneumonia, Viral/epidemiology , Pneumonia, Viral/immunology , Adolescent , Adult , Aged , Aged, 80 and over , Antibodies, Neutralizing/blood , Antibodies, Viral/blood , Arizona/epidemiology , Betacoronavirus/isolation & purification , COVID-19 , COVID-19 Testing , Coronavirus Infections/blood , Coronavirus Infections/diagnosis , Coronavirus Nucleocapsid Proteins , Female , Humans , Male , Middle Aged , Nucleocapsid Proteins/immunology , Pandemics , Phosphoproteins , Pneumonia, Viral/blood , Pneumonia, Viral/diagnosis , Prevalence , Protein Interaction Domains and Motifs , SARS-CoV-2 , Seroepidemiologic Studies , Spike Glycoprotein, Coronavirus/chemistry , Spike Glycoprotein, Coronavirus/immunology , Young AdultABSTRACT
Gene-based burden tests are a popular and powerful approach for analysis of exome-wide association studies. These approaches combine sets of variants within a gene into a single burden score that is then tested for association. Typically, a range of burden scores are calculated and tested across a range of annotation classes and frequency bins. Correlation between these tests can complicate the multiple testing correction and hamper interpretation of the results. We introduce a method called the sparse burden association test (SBAT) that tests the joint set of burden scores under the assumption that causal burden scores act in the same effect direction. The method simultaneously assesses the significance of the model fit and selects the set of burden scores that best explain the association at the same time. Using simulated data, we show that the method is well calibrated and highlight scenarios where the test outperforms existing gene-based tests. We apply the method to 73 quantitative traits from the UK Biobank, showing that SBAT is a valuable additional gene-based test when combined with other existing approaches. This test is implemented in the REGENIE software.
Subject(s)
Genome-Wide Association Study , Humans , Genome-Wide Association Study/methods , Least-Squares Analysis , Software , Models, Genetic , Exome/genetics , Genetic Variation , Computer SimulationABSTRACT
The genome of an individual from an admixed population consists of segments originated from different ancestral populations. Most existing ancestry inference approaches focus on calling these segments for the extant individual. In this paper, we present a general ancestry inference approach for inferring recent ancestors from an extant genome. Given the genome of an individual from a recently admixed population, our method can estimate the proportions of the genomes of the recent ancestors of this individual that originated from some ancestral populations. The key step of our method is the inference of ancestors (called founders) right after the formation of an admixed population. The inferred founders can then be used to infer the ancestry of recent ancestors of an extant individual. Our method is implemented in a computer program called PedMix2. To the best of our knowledge, there is no existing method that can practically infer ancestors beyond grandparents from an extant individual's genome. Results on both simulated and real data show that PedMix2 performs well in ancestry inference.
Subject(s)
Genetics, Population , Grandparents , Humans , Software , Genome, Human/geneticsABSTRACT
Critical state and continuum plasticity theories have been used in research and engineering practice in soil and rock mechanics for decades. These theories rely on postulated relationships between material stresses and strains. Some classical postulates include coaxiality between stress and strain rates, stress-dilatancy relationships, and kinematic assumptions in shear bands. Although numerical and experimental data have quantified the strains and grain kinematics in such experiments, little data quantifying grain stresses are available. Here, we report the first-known grain stress and local strain measurements in triaxial compression tests on synthetic quartz sands using synchrotron X-ray tomography and 3D X-ray diffraction. We use these data to examine the micromechanics of shear banding, with a focus on coaxiality, stress-dilatancy, and kinematics within bands. Our results indicate the following: 1) elevated deviatoric stress, strain, and stress ratios in shear bands throughout experiments; 2) coaxial principal compressive stresses and strains throughout samples; 3) significant contraction along shear bands; 4) vanishing volumetric strain but nonvanishing stress fluctuations throughout samples at all stages of deformation. Our results provide some of the first-known in situ stress and strain measurements able to aid in critically evaluating postulates employed in continuum plasticity and strain localization theories for sands.
ABSTRACT
Genetic factors play a fundamental role in disease development. Studying the genetic association with clinical outcomes is critical for understanding disease biology and devising novel treatment targets. However, the frequencies of genetic variations are often low, making it difficult to examine the variants one-by-one. Moreover, the clinical outcomes are complex, including patients' survival time and other binary or continuous outcomes such as recurrences and lymph node count, and how to effectively analyze genetic association with these outcomes remains unclear. In this article, we proposed a structured test statistic for testing genetic association with mixed types of survival, binary, and continuous outcomes. The structured testing incorporates known biological information of variants while allowing for their heterogeneous effects and is a powerful strategy for analyzing infrequent genetic factors. Simulation studies show that the proposed test statistic has correct type I error and is highly effective in detecting significant genetic variants. We applied our approach to a uterine corpus endometrial carcinoma study and identified several genetic pathways associated with the clinical outcomes.
ABSTRACT
BACKGROUND: A hypothetical concern has been raised that sacubitril/valsartan might cause cognitive impairment because neprilysin is one of several enzymes degrading amyloid-ß peptides in the brain, some of which are neurotoxic and linked to Alzheimer-type dementia. To address this, we examined the effect of sacubitril/valsartan compared with valsartan on cognitive function in patients with heart failure with preserved ejection fraction in a prespecified substudy of PARAGON-HF (Prospective Comparison of Angiotensin Receptor Neprilysin Inhibitor With Angiotensin Receptor Blocker Global Outcomes in Heart Failure With Preserved Ejection Fraction). METHODS: In PARAGON-HF, serial assessment of cognitive function was conducted in a subset of patients with the Mini-Mental State Examination (MMSE; score range, 0-30, with lower scores reflecting worse cognitive function). The prespecified primary analysis of this substudy was the change from baseline in MMSE score at 96 weeks. Other post hoc analyses included cognitive decline (fall in MMSE score of ≥3 points), cognitive impairment (MMSE score <24), or the occurrence of dementia-related adverse events. RESULTS: Among 2895 patients included in the MMSE substudy with baseline MMSE score measured, 1453 patients were assigned to sacubitril/valsartan and 1442 to valsartan. Their mean age was 73 years, and the median follow-up was 32 months. The mean±SD MMSE score at randomization was 27.4±3.0 in the sacubitril/valsartan group, with 10% having an MMSE score <24; the corresponding numbers were nearly identical in the valsartan group. The mean change from baseline to 96 weeks in the sacubitril/valsartan group was -0.05 (SE, 0.07); the corresponding change in the valsartan group was -0.04 (0.07). The mean between-treatment difference at week 96 was -0.01 (95% CI, -0.20 to 0.19; P=0.95). Analyses of a ≥3-point decline in MMSE, decrease to a score <24, dementia-related adverse events, and combinations of these showed no difference between sacubitril/valsartan and valsartan. No difference was found in the subgroup of patients tested for apolipoprotein E ε4 allele genotype. CONCLUSIONS: Patients with heart failure with preserved ejection fraction in PARAGON-HF had relatively low baseline MMSE scores. Cognitive change, measured by MMSE, did not differ between treatment with sacubitril/valsartan and treatment with valsartan in patients with heart failure with preserved ejection fraction. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01920711.
Subject(s)
Aminobutyrates , Angiotensin Receptor Antagonists , Biphenyl Compounds , Cognition , Drug Combinations , Heart Failure , Stroke Volume , Tetrazoles , Valsartan , Humans , Biphenyl Compounds/therapeutic use , Valsartan/therapeutic use , Valsartan/adverse effects , Aminobutyrates/therapeutic use , Aminobutyrates/adverse effects , Male , Heart Failure/drug therapy , Heart Failure/physiopathology , Female , Aged , Cognition/drug effects , Stroke Volume/drug effects , Angiotensin Receptor Antagonists/therapeutic use , Angiotensin Receptor Antagonists/adverse effects , Middle Aged , Tetrazoles/therapeutic use , Tetrazoles/adverse effects , Prospective Studies , Neprilysin/antagonists & inhibitors , Treatment Outcome , Cognitive Dysfunction/drug therapy , Aged, 80 and overABSTRACT
Tree tests like the Kishino-Hasegawa (KH) test and chi-square test suffer a selection bias that tests like the Shimodaira-Hasegawa (SH) test and approximately unbiased test were intended to correct. We investigate tree-testing performance in the presence of severe selection bias. The SH test is found to be very conservative and, surprisingly, its uncorrected analog, the KH test has low Type I error even in the presence of extreme selection bias, leading to a recommendation that the SH test be abandoned. A chi-square test is found to usually behave well and but to require correction in extreme cases. We show how topology testing procedures can be used to get support values for splits and compare the likelihood-based support values to the approximate likelihood ratio test (aLRT) support values. We find that the aLRT support values are reasonable even in settings with severe selection bias that they were not designed for. We also show how they can be used to construct tests of topologies and, in doing so, point out a multiple comparisons issue that should be considered when looking at support values for splits.
Subject(s)
Likelihood Functions , Phylogeny , Selection BiasABSTRACT
A challenge in standard genetic studies is maintaining good power to detect associations, especially for low prevalent diseases and rare variants. The traditional methods are most powerful when evaluating the association between variants in balanced study designs. Without accounting for family correlation and unbalanced case-control ratio, these analyses could result in inflated type I error. One cost-effective solution to increase statistical power is exploitation of available family history (FH) that contains valuable information about disease heritability. Here, we develop methods to address the aforementioned type I error issues while providing optimal power to analyze aggregates of rare variants by incorporating additional information from FH. With enhanced power in these methods exploiting FH and accounting for relatedness and unbalanced designs, we successfully detect genes with suggestive associations with Alzheimer disease, dementia, and type 2 diabetes by using the exome chip data from the Framingham Heart Study.
Subject(s)
Diabetes Mellitus, Type 2 , Case-Control Studies , Diabetes Mellitus, Type 2/genetics , Exome , Genetic Variation/genetics , Humans , Longitudinal Studies , Models, Genetic , Exome SequencingABSTRACT
Over the past years, progress made in next-generation sequencing technologies and bioinformatics have sparked a surge in association studies. Especially, genome-wide association studies (GWASs) have demonstrated their effectiveness in identifying disease associations with common genetic variants. Yet, rare variants can contribute to additional disease risk or trait heterogeneity. Because GWASs are underpowered for detecting association with such variants, numerous statistical methods have been recently proposed. Aggregation tests collapse multiple rare variants within a genetic region (e.g. gene, gene set, genomic loci) to test for association. An increasing number of studies using such methods successfully identified trait-associated rare variants and led to a better understanding of the underlying disease mechanism. In this review, we compare existing aggregation tests, their statistical features and scope of application, splitting them into the five classical classes: burden, adaptive burden, variance-component, omnibus and other. Finally, we describe some limitations of current aggregation tests, highlighting potential direction for further investigations.
Subject(s)
Genetic Variation , Genome-Wide Association Study , Humans , Phenotype , Case-Control Studies , Models, GeneticABSTRACT
Throughout the SARS-CoV-2 pandemic, limited diagnostic capacities prevented sentinel testing, demonstrating the need for novel testing infrastructures. Here, we describe the setup of a cost-effective platform that can be employed in a high-throughput manner, which allows surveillance testing as an acute pandemic control and preparedness tool, exemplified by SARS-CoV-2 diagnostics in an academic environment. The strategy involves self-sampling based on gargling saline, pseudonymized sample handling, automated RNA extraction, and viral RNA detection using a semiquantitative multiplexed colorimetric reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay with an analytical sensitivity comparable with RT-qPCR. We provide standard operating procedures and an integrated software solution for all workflows, including sample logistics, analysis by colorimetry or sequencing, and communication of results. We evaluated factors affecting the viral load and the stability of gargling samples as well as the diagnostic sensitivity of the RT-LAMP assay. In parallel, we estimated the economic costs of setting up and running the test station. We performed > 35,000 tests, with an average turnover time of < 6 h from sample arrival to result announcement. Altogether, our work provides a blueprint for fast, sensitive, scalable, cost- and labor-efficient RT-LAMP diagnostics, which is independent of potentially limiting clinical diagnostics supply chains.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/genetics , COVID-19/diagnosis , COVID-19/epidemiology , COVID-19 Testing , Clinical Laboratory Techniques/methods , Pandemics/prevention & control , Sensitivity and Specificity , RNA, Viral/geneticsABSTRACT
The recent outbreaks related to Mayaro virus (MAYV) infection in the Americas have brought this neglected virus as a potential threat to global public health. Given the range of symptoms that can be associated with MAYV infection, it can be challenging to diagnose individuals based on clinical signs, especially in countries with simultaneous circulation of other mosquito-borne viruses, such as dengue virus (DENV) and chikungunya virus (CHIKV). With this challenge in mind, laboratory-based diagnosis assumes a critical role in the introduction of measures to help prevent virus dissemination and to adequately treat patients. In this review, we provide an overview of the clinical features reported in infected patients and currently available laboratory tools that are used for MAYV diagnosis, discussing their advances, advantages, and limitations to apply in the field. Moreover, we explore novel point-of-care (PoC) diagnostic platforms that can provide de-centralised diagnostics for use in areas with limited laboratory infrastructure.
Subject(s)
Chikungunya virus , Animals , Humans , Disease Outbreaks , Clinical Laboratory TechniquesABSTRACT
OBJECTIVE: This document addresses the clinical application of next-generation sequencing (NGS) technologies for prenatal genetic diagnosis and aims to establish clinical practice recommendations in Spain to ensure uniformity in implementing these technologies into prenatal care. METHODS: A joint committee of expert obstetricians and geneticists was created to review the existing literature on fetal NGS for genetic diagnosis and to make recommendations for Spanish healthcare professionals. RESULTS: This guideline summarises technical aspects of NGS technologies, clinical indications in prenatal setting, considerations regarding findings to be reported, genetic counselling considerations as well as data storage and protection policies. CONCLUSIONS: This document provides updated recommendations for the use of NGS diagnostic tests in prenatal diagnosis. These recommendations should be periodically reviewed as our knowledge of the clinical utility of NGS technologies, applied during pregnancy, may advance.
Subject(s)
High-Throughput Nucleotide Sequencing , Prenatal Diagnosis , Humans , Prenatal Diagnosis/methods , Prenatal Diagnosis/standards , Pregnancy , High-Throughput Nucleotide Sequencing/methods , High-Throughput Nucleotide Sequencing/standards , Female , Spain , Genetic Testing/methods , Genetic Testing/standards , Genetic Counseling/methods , Genetic Counseling/standards , Obstetrics/standards , Obstetrics/methods , Gynecology/standardsABSTRACT
Accurate biomarkers are a crucial and necessary precondition for precision medicine, yet existing ones are often unspecific and new ones have been very slow to enter the clinic. Mass spectrometry (MS)-based proteomics excels by its untargeted nature, specificity of identification, and quantification, making it an ideal technology for biomarker discovery and routine measurement. It has unique attributes compared to affinity binder technologies, such as OLINK Proximity Extension Assay and SOMAscan. In in a previous review in 2017, we described technological and conceptual limitations that had held back success. We proposed a 'rectangular strategy' to better separate true biomarkers by minimizing cohort-specific effects. Today, this has converged with advances in MS-based proteomics technology, such as increased sample throughput, depth of identification, and quantification. As a result, biomarker discovery studies have become more successful, producing biomarker candidates that withstand independent verification and, in some cases, already outperform state-of-the-art clinical assays. We summarize developments over the last years, including the benefits of large and independent cohorts, which are necessary for clinical acceptance. Shorter gradients, new scan modes, and multiplexing are about to drastically increase throughput, cross-study integration, and quantification, including proxies for absolute levels. We have found that multiprotein panels are inherently more robust than current single analyte tests and better capture the complexity of human phenotypes. Routine MS measurement in the clinic is fast becoming a viable option. The full set of proteins in a body fluid (global proteome) is the most important reference and the best process control. Additionally, it increasingly has all the information that could be obtained from targeted analysis although the latter may be the most straightforward way to enter regular use. Many challenges remain, not least of a regulatory and ethical nature, but the outlook for MS-based clinical applications has never been brighter.
Subject(s)
Body Fluids , Proteomics , Humans , Proteomics/methods , Mass Spectrometry/methods , Biomarkers/analysis , Proteome/metabolism , Body Fluids/chemistry , Body Fluids/metabolismABSTRACT
The exhaled breath represents an ideal matrix for non-invasive biomarker discovery, and exhaled metabolomics have the potential to be clinically useful in the era of precision medicine. In this concise translational review we will specifically address volatile organic compounds in the breath, with a view towards fulfilling the promise of these as actionable biomarkers, in particular for lung diseases. We review the literature paying attention to seminal work linked to key milestones in breath research; discuss potential applications for breath biomarkers across disease areas and healthcare systems, including the perspectives of industry; and outline critical aspects of study design that will need to be considered for any pivotal research going forward, if breath analysis is to provide robust validated biomarkers that meet the requirements for future clinical implementation.
ABSTRACT
RATIONALE: The European Respiratory Society (ERS) and the American Thoracic Society (ATS) recommend using z-scores, and the ATS has recommended using Global Lung Initiative (GLI)- "Global" race-neutral reference equations for spirometry interpretation. However, these recommendations have been variably implemented and the impact has not been widely assessed, both in clinical and research settings. OBJECTIVES: We evaluated the ERS/ATS airflow obstruction severity classification. METHODS: In the COPDGene Study (n = 10,108), airflow obstruction has been defined as a forced expiratory volume in one second to forced vital capacity (FEV1/FVC) ratio <0.70, with spirometry severity graded from class 1 to 4 based on race-specific percent predicted (pp) FEV1 cut-points as recommended by the Global Initiative for Chronic Obstructive Lung Disease (GOLD). We compared the GOLD approach, using NHANES III race-specific equations, to the application of GLI-Global equations using the ERS/ATS definition of airflow obstruction as FEV1/FVC ratio < lower limit of normal (LLN) and z-FEV1 cut-points of -1.645, -2.5, and -4 ("zGLI Global"). We tested the four-tier severity scheme for association with COPD outcomes. MEASUREMENTS AND MAIN RESULTS: The lowest agreement between ERS/ATS with zGLI Global and the GOLD classification was observed in individuals with milder disease (56.9% and 42.5% in GOLD 1 and 2) and race was a major determinant of redistribution. After adjustment for relevant covariates, zGLI Global distinguished all-cause mortality risk between normal spirometry and the first grade of COPD (Hazard Ratio 1.23, 95% CI 1.04-1.44, p=0.014), and showed a linear increase in exacerbation rates with increasing disease severity, in comparison to GOLD. CONCLUSIONS: The zGLI Global severity classification outperformed GOLD in the discrimination of survival, exacerbations, and imaging characteristics.
ABSTRACT
RATIONALE: Early identification of children with poorly controlled asthma is imperative for optimizing treatment strategies. The analysis of exhaled volatile organic compounds (VOCs) is an emerging approach to identify prognostic and diagnostic biomarkers in pediatric asthma. OBJECTIVES: To assess the accuracy of gas chromatography-mass spectrometry based exhaled metabolite analysis to differentiate between controlled and uncontrolled pediatric asthma. METHODS: This study encompassed a discovery (SysPharmPediA) and validation phase (U-BIOPRED, PANDA). Firstly, exhaled VOCs that discriminated asthma control levels were identified. Subsequently, outcomes were validated in two independent cohorts. Patients were classified as controlled or uncontrolled, based on asthma control test scores and number of severe attacks in the past year. Additionally, potential of VOCs in predicting two or more future severe asthma attacks in SysPharmPediA was evaluated. MEASUREMENTS AND MAIN RESULTS: Complete data were available for 196 children (SysPharmPediA=100, U-BIOPRED=49, PANDA=47). In SysPharmPediA, after randomly splitting the population into training (n=51) and test sets (n=49), three compounds (acetophenone, ethylbenzene, and styrene) distinguished between uncontrolled and controlled asthmatics. The area under the receiver operating characteristic curve (AUROCC) for training and test sets were respectively: 0.83 (95% CI: 0.65-1.00) and 0.77 (95% CI: 0.58-0.96). Combinations of these VOCs resulted in AUROCCs of 0.74 ±0.06 (UBIOPRED) and 0.68 ±0.05 (PANDA). Attacks prediction tests, resulted in AUROCCs of 0.71 (95% CI 0.51-0.91) and 0.71 (95% CI 0.52-0.90) for training and test sets. CONCLUSIONS: Exhaled metabolites analysis might enable asthma control classification in children. This should stimulate further development of exhaled metabolites-based point-of-care tests in asthma.
ABSTRACT
BACKGROUND: Despite their central role in peanut allergy, human monoclonal IgE antibodies have eluded characterization. OBJECTIVE: We sought to define the sequences, affinities, clonality, and functional properties of human monoclonal IgE antibodies in peanut allergy. METHODS: We applied our single-cell RNA sequencing-based SEQ SIFTER discovery platform to samples from allergic individuals who varied by age, sex, ethnicity, and geographic location in order to understand commonalities in the human IgE response to peanut allergens. Select antibodies were then recombinantly expressed and characterized for their allergen and epitope specificity, affinity, and functional properties. RESULTS: We found striking convergent evolution of IgE monoclonal antibodies (mAbs) from several clonal families comprising both memory B cells and plasmablasts. These antibodies bound with subnanomolar affinity to the immunodominant peanut allergen Ara h 2, specifically a linear, repetitive motif. Further characterization of these mAbs revealed their ability to single-handedly cause affinity-dependent degranulation of human mast cells and systemic anaphylaxis on peanut allergen challenge in humanized mice. Finally, we demonstrated that these mAbs, reengineered as IgGs, inhibit significant, but variable, amounts of Ara h 2- and peanut-mediated degranulation of mast cells sensitized with allergic plasma. CONCLUSIONS: Convergent evolution of IgE mAbs in peanut allergy is a common phenomenon that can reveal immunodominant epitopes on major allergenic proteins. Understanding the functional properties of these molecules is key to developing therapeutics, such as competitive IgG inhibitors, that are able to stoichiometrically outcompete endogenous IgE for allergen and thereby prevent allergic cascade in cases of accidental allergen exposure.
Subject(s)
Peanut Hypersensitivity , Humans , Animals , Mice , Immunodominant Epitopes , Antigens, Plant , Glycoproteins , Immunoglobulin E , Epitopes , Antibodies, Monoclonal , Allergens , Arachis , 2S Albumins, PlantABSTRACT
BACKGROUND: Existing therapeutic strategies are challenged by long times to achieve effect and often require frequent administration. Peanut-allergic individuals would benefit from a therapeutic that provides rapid protection against accidental exposure within days of administration while carrying little risk of adverse reactions. OBJECTIVE: Guided by the repertoire of human IgE mAbs from allergic individuals, we sought to develop a treatment approach leveraging the known protective effects of allergen-specific IgG4 antibodies. METHODS: We applied our single-cell RNA-sequencing SEQ SIFTER platform (IgGenix, Inc, South San Francisco, Calif) to whole blood samples from peanut-allergic individuals to discover IgE mAbs. These were then class-switched by replacing the IgE constant region with IgG4 while retaining the allergen-specific variable regions. In vitro mast cell activation tests, basophil activation tests, ELISAs, and an in vivo peanut allergy mouse model were used to evaluate the specificity, affinity, and activity of these recombinant IgG4 mAbs. RESULTS: We determined that human peanut-specific IgE mAbs predominantly target immunodominant epitopes on Ara h 2 and Ara h 6 and that recombinant IgG4 mAbs effectively block these epitopes. IGNX001, a mixture of 2 such high-affinity IgG4 mAbs, provided robust protection against peanut-mediated mast cell activation in vitro as well as against anaphylaxis upon intragastric peanut challenge in a peanut allergy mouse model. CONCLUSIONS: We developed a peanut-specific IgG4 antibody therapeutic with convincing preclinical efficacy starting from a large repertoire of human IgE mAbs from demographically and geographically diverse individuals. These results warrant further clinical investigation of IGNX001 and underscore the opportunity for the application of this therapeutic development strategy in other food and environmental allergies.
ABSTRACT
BACKGROUND: The eustachian tube (ET), a critical conduit connecting the middle ear and nasopharynx, is essential for normal middle ear function. However, it remains one of the least understood anatomical structures due to its complexity and the challenges of in vitro manipulation. Historically, these challenges have hindered research into the morphology and function development of the ET. This study elucidates the spatiotemporal relationship of ET morpho-functional maturation in mice, identifying key periods and factors that lay the theoretical foundation for exploring the molecular mechanisms of ET-related diseases. RESULTS: We comprehensively characterized the ET development in C57BL/6 mice from embryonic day (E) 12.5 to postnatal day (P) 30, focusing on the development of cilia, secretory cells, surrounding glands, and macrophages. Immunostaining identified the localization and secretion patterns of the mucins Muc5b and Muc5ac within the ET. Additionally, using improved ET function assessment tools, we evaluated the developmental features of ET mucociliary clearance and ventilation functions. CONCLUSIONS: In C57BL/6 mice, E16.5 marks a critical period for middle ear cavity and ET formation. Muc5b plays a foundational role during early stages, while Muc5ac enhances function in later stages. During P7-11, despite morphological maturity, ET function remains underdeveloped but continues to improve with growth.