Protein-Based Immunome Wide Association Studies (PIWAS) for the Discovery of Significant Disease-Associated Antigens

Profiling antibody epitopes induced by mRNA-1273 vaccination and boosters

Background

Characterizing the antibody epitope profiles of messenger RNA (mRNA)-based vaccines against SARS-CoV-2 can aid in elucidating the mechanisms underlying the antibody-mediated immune responses elicited by these vaccines.

Methods

This study investigated the distinct antibody epitopes toward the SARS-CoV-2 spike (S) protein targeted after a two-dose primary series of mRNA-1273 followed by a booster dose of mRNA-1273 or a variant-updated vaccine among serum samples from clinical trial adult participants.

Results

Multiple S-specific epitopes were targeted after primary vaccination; while signal decreased over time, a booster dose after >6 months largely revived waning antibody signals. Epitope identity also changed after booster vaccination in some subjects, with four new S-specific epitopes detected with stronger signals after boosting than with primary vaccination. Notably, the strength of antibody responses after booster vaccination differed by the exact vaccine formulation, with variant-updated mRNA-1273.211 and mRNA-1273.617.2 booster formulations inducing significantly stronger S-specific signals than a mRNA-1273 booster.

Conclusion

Overall, these results identify key S-specific epitopes targeted by antibodies induced by mRNA-1273 primary and variant-updated booster vaccination.

Distinguishing features of long COVID identified through immune profiling

Post-acute infection syndromes may develop after acute viral disease1. Infection with SARS-CoV-2 can result in the development of a post-acute infection syndrome known as long COVID. Individuals with long COVID frequently report unremitting fatigue, post-exertional malaise, and a variety of cognitive and autonomic dysfunctions2-4. However, the biological processes that are associated with the development and persistence of these symptoms are unclear. Here 275 individuals with or without long COVID were enrolled in a cross-sectional study that included multidimensional immune phenotyping and unbiased machine learning methods to identify biological features associated with long COVID. Marked differences were noted in circulating myeloid and lymphocyte populations relative to the matched controls, as well as evidence of exaggerated humoral responses directed against SARS-CoV-2 among participants with long COVID. Furthermore, higher antibody responses directed against non-SARS-CoV-2 viral pathogens were observed among individuals with long COVID, particularly Epstein-Barr virus. Levels of soluble immune mediators and hormones varied among groups, with cortisol levels being lower among participants with long COVID. Integration of immune phenotyping data into unbiased machine learning models identified the key features that are most strongly associated with long COVID status. Collectively, these findings may help to guide future studies into the pathobiology of long COVID and help with developing relevant biomarkers.

Detection of Antibodies against Endemic and SARS-CoV-2 Coronaviruses with Short Peptide Epitopes

(1) Background: Coronavirus proteins are quite conserved amongst endemic strains (eCoV) and SARS-CoV-2. We aimed to evaluate whether peptide epitopes might serve as useful diagnostic biomarkers to stratify previous infections and COVID-19. (2) Methods: Peptide epitopes were identified at an amino acid resolution that applied a novel statistical approach to generate data sets of potential antibody binding peptides. (3) Results: Data sets from more than 120 COVID-19 or eCoV-infected patients, as well as vaccinated persons, have been used to generate data sets that have been used to search in silico for potential epitopes in proteins of SARS-CoV-2 and eCoV. Peptide epitopes were validated with >300 serum samples in synthetic peptide micro arrays and epitopes specific for different viruses, in addition to the identified cross reactive epitopes. (4) Conclusions: Most patients develop antibodies against non-structural proteins, which are useful general markers for recent infections. However, there are differences in the epitope patterns of COVID-19, and eCoV, and the S-protein vaccine, which can only be explained by a high degree of cross-reactivity between the viruses, a pre-existing immune response against some epitopes, and even an alternate processing of the vaccine proteins.

Modeling the sequence dependence of differential antibody binding in the immune response to infectious disease

Past studies have shown that incubation of human serum samples on high density peptide arrays followed by measurement of total antibody bound to each peptide sequence allows detection and discrimination of humoral immune responses to a variety of infectious diseases. This is true even though these arrays consist of peptides with near-random amino acid sequences that were not designed to mimic biological antigens. This "immunosignature" approach, is based on a statistical evaluation of the binding pattern for each sample but it ignores the information contained in the amino acid sequences that the antibodies are binding to. Here, similar array-based antibody profiles are instead used to train a neural network to model the sequence dependence of molecular recognition involved in the immune response of each sample. The binding profiles used resulted from incubating serum from 5 infectious disease cohorts (Hepatitis B and C, Dengue Fever, West Nile Virus and Chagas disease) and an uninfected cohort with 122,926 peptide sequences on an array. These sequences were selected quasi-randomly to represent an even but sparse sample of the entire possible combinatorial sequence space (~1012). This very sparse sampling of combinatorial sequence space was sufficient to capture a statistically accurate representation of the humoral immune response across the entire space. Processing array data using the neural network not only captures the disease-specific sequence-binding information but aggregates binding information with respect to sequence, removing sequence-independent noise and improving the accuracy of array-based classification of disease compared with the raw binding data. Because the neural network model is trained on all samples simultaneously, a highly condensed representation of the differential information between samples resides in the output layer of the model, and the column vectors from this layer can be used to represent each sample for classification or unsupervised clustering applications.

Plasmodium infection is associated with cross-reactive antibodies to carbohydrate epitopes on the SARS-CoV-2 Spike protein

Sero-surveillance can monitor and project disease burden and risk. However, SARS-CoV-2 antibody test results can produce false positive results, limiting their efficacy as a sero-surveillance tool. False positive SARS-CoV-2 antibody results are associated with malaria exposure, and understanding this association is essential to interpret sero-surveillance results from malaria-endemic countries. Here, pre-pandemic samples from eight malaria endemic and non-endemic countries and four continents were tested by ELISA to measure SARS-CoV-2 Spike S1 subunit reactivity. Individuals with acute malaria infection generated substantial SARS-CoV-2 reactivity. Cross-reactivity was not associated with reactivity to other human coronaviruses or other SARS-CoV-2 proteins, as measured by peptide and protein arrays. ELISAs with deglycosylated and desialated Spike S1 subunits revealed that cross-reactive antibodies target sialic acid on N-linked glycans of the Spike protein. The functional activity of cross-reactive antibodies measured by neutralization assays showed that cross-reactive antibodies did not neutralize SARS-CoV-2 in vitro. Since routine use of glycosylated or sialated assays could result in false positive SARS-CoV-2 antibody results in malaria endemic regions, which could overestimate exposure and population-level immunity, we explored methods to increase specificity by reducing cross-reactivity. Overestimating population-level exposure to SARS-CoV-2 could lead to underestimates of risk of continued COVID-19 transmission in sub-Saharan Africa.

Distinguishing features of Long COVID identified through immune profiling

SARS-CoV-2 infection can result in the development of a constellation of persistent sequelae following acute disease called post-acute sequelae of COVID-19 (PASC) or Long COVID 1-3 . Individuals diagnosed with Long COVID frequently report unremitting fatigue, post-exertional malaise, and a variety of cognitive and autonomic dysfunctions 1-3 ; however, the basic biological mechanisms responsible for these debilitating symptoms are unclear. Here, 215 individuals were included in an exploratory, cross-sectional study to perform multi-dimensional immune phenotyping in conjunction with machine learning methods to identify key immunological features distinguishing Long COVID. Marked differences were noted in specific circulating myeloid and lymphocyte populations relative to matched control groups, as well as evidence of elevated humoral responses directed against SARS-CoV-2 among participants with Long COVID. Further, unexpected increases were observed in antibody responses directed against non-SARS-CoV-2 viral pathogens, particularly Epstein-Barr virus. Analysis of circulating immune mediators and various hormones also revealed pronounced differences, with levels of cortisol being uniformly lower among participants with Long COVID relative to matched control groups. Integration of immune phenotyping data into unbiased machine learning models identified significant distinguishing features critical in accurate classification of Long COVID, with decreased levels of cortisol being the most significant individual predictor. These findings will help guide additional studies into the pathobiology of Long COVID and may aid in the future development of objective biomarkers for Long COVID.

High-resolution epitope mapping and characterization of SARS-CoV-2 antibodies in large cohorts of subjects with COVID-19

As Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to spread, characterization of its antibody epitopes, emerging strains, related coronaviruses, and even the human proteome in naturally infected patients can guide the development of effective vaccines and therapies. Since traditional epitope identification tools are dependent upon pre-defined peptide sequences, they are not readily adaptable to diverse viral proteomes. The Serum Epitope Repertoire Analysis (SERA) platform leverages a high diversity random bacterial display library to identify proteome-independent epitope binding specificities which are then analyzed in the context of organisms of interest. When evaluating immune response in the context of SARS-CoV-2, we identify dominant epitope regions and motifs which demonstrate potential to classify mild from severe disease and relate to neutralization activity. We highlight SARS-CoV-2 epitopes that are cross-reactive with other coronaviruses and demonstrate decreased epitope signal for mutant SARS-CoV-2 strains. Collectively, the evolution of SARS-CoV-2 mutants towards reduced antibody response highlight the importance of data-driven development of the vaccines and therapies to treat COVID-19.

Longitudinal immune profiling of a SARS-CoV-2 reinfection in a solid organ transplant recipient

BACKGROUND

The underlying immunologic deficiencies enabling SARS-CoV-2 reinfection are currently unknown. We describe deep longitudinal immune profiling of a transplant recipient hospitalized twice for COVID-19.

METHODS

A 66-year-old male renal transplant recipient was hospitalized with COVID-19 March 2020 then readmitted to the hospital with COVID-19 233 days after initial diagnosis. Virologic and immunologic investigation were performed on samples from the primary and secondary infections.

RESULTS

Whole viral genome sequencing and phylogenic analysis revealed that viruses causing both infections were caused by distinct genetic lineages without evidence of immune escape mutations. Longitudinal comparison of cellular and humoral responses during primary SARS-CoV-2 infection revealed that this patient responded to the primary infection with low neutralization titer anti-SARS-CoV-2 antibodies that were likely present at the time of reinfection.

DISCUSSION

The development of neutralizing antibodies and humoral memory responses in this patient failed to confer protection against reinfection, suggesting that they were below a neutralizing titer threshold or that additional factors may be required for efficient prevention of SARS-CoV-2 reinfection. Development of poorly neutralizing antibodies may have been due to profound and relatively specific reduction in naïve CD4 T-cell pools. Seropositivity alone may not be a perfect correlate of protection in immunocompromised patients.

Immunogenic amino acid motifs and linear epitopes of COVID-19 mRNA vaccines

Reverse vaccinology is an evolving approach for improving vaccine effectiveness and minimizing adverse responses by limiting immunizations to critical epitopes. Towards this goal, we sought to identify immunogenic amino acid motifs and linear epitopes of the SARS-CoV-2 spike protein that elicit IgG in COVID-19 mRNA vaccine recipients. Paired pre/post vaccination samples from N = 20 healthy adults, and post-vaccine samples from an additional N = 13 individuals were used to immunoprecipitate IgG targets expressed by a bacterial display random peptide library, and preferentially recognized peptides were mapped to the spike primary sequence. The data identify several distinct amino acid motifs recognized by vaccine-induced IgG, a subset of those targeted by IgG from natural infection, which may mimic 3-dimensional conformation (mimotopes). Dominant linear epitopes were identified in the C-terminal domains of the S1 and S2 subunits (aa 558-569, 627-638, and 1148-1159) which have been previously associated with SARS-CoV-2 neutralization in vitro and demonstrate identity to bat coronavirus and SARS-CoV, but limited homology to non-pathogenic human coronavirus. The identified COVID-19 mRNA vaccine epitopes should be considered in the context of variants, immune escape and vaccine and therapy design moving forward.

Phase Ib study of patients with metastatic castrate-resistant prostate cancer treated with different sequencing regimens of atezolizumab and sipuleucel-T

Background

Combining an immune checkpoint inhibitor with a tumor vaccine may modulate the immune system to leverage complementary mechanisms of action that lead to sustained T-cell activation and a potent prolonged immunotherapeutic response in metastatic castration resistant prostate cancer (mCRPC).

Methods

Subjects with asymptomatic or minimally symptomatic mCRPC were randomly assigned in a 1:1 ratio to receive either atezolizumab followed by sipuleucel-T (Arm 1) or sipuleucel-T followed by atezolizumab (Arm 2). The primary endpoint was safety, while secondary endpoints included preliminary clinical activity such as objective tumor response and systemic immune responses that could identify key molecular and immunological changes associated with sequential administration of atezolizumab and sipuleucel-T.

Results

A total of 37 subjects were enrolled. The median age was 75.0 years, median prostate specific antigen (PSA) was 21.9 ng/mL, and subjects had a median number of three prior treatments. Most subjects (83.8%) had at least one treatment-related adverse event. There were no grade 4 or 5 toxicities attributed to either study drug. Immune-related adverse events and infusion reactions occurred in 13.5% of subjects, and all of which were grade 1 or 2. Of 23 subjects with Response Evaluation Criteria in Solid Tumors measurable disease, only one subject in Arm 2 had a partial response (PR) and four subjects overall had stable disease (SD) at 6 months reflecting an objective response rate of 4.3% and a disease control rate of 21.7%. T-cell receptor diversity was higher in subjects with a response, including SD. Immune response to three novel putative antigens (SIK3, KDM1A/LSD1, and PIK3R6) appeared to increase with treatment.

Conclusions

Overall, regardless of the order in which they were administered, the combination of atezolizumab with sipuleucel-T appears to be safe and well tolerated with a comparable safety profile to each agent administered as monotherapy. Correlative immune studies may suggest the combination to be beneficial; however, further studies are needed.

Trial registration number

NCT03024216.

Plasmodium infection induces cross-reactive antibodies to carbohydrate epitopes on the SARS-CoV-2 Spike protein

Individuals with acute malaria infection generated high levels of antibodies that cross-react with the SARS-CoV-2 Spike protein. Cross-reactive antibodies specifically recognized the sialic acid moiety on N-linked glycans of the Spike protein and do not neutralize in vitro SARS-CoV-2. Sero-surveillance is critical for monitoring and projecting disease burden and risk during the pandemic; however, routine use of Spike protein-based assays may overestimate SARS-CoV-2 exposure and population-level immunity in malaria-endemic countries.

Longitudinal immune profiling of a SARS-CoV-2 reinfection in a solid organ transplant recipient

The underlying immunologic deficiencies enabling SARS-CoV-2 reinfections are currently unknown. Here we describe a renal-transplant recipient who developed recurrent, symptomatic SARS-CoV-2 infection 7 months after primary infection. To elucidate the immunological mechanisms responsible for reinfection, we performed longitudinal profiling of cellular and humoral responses during both primary and recurrent SARS-CoV-2 infection. We found that the patient responded to the primary infection with transient, poor-quality adaptive immune responses that was further compromised by intervening treatment for acute rejection of the renal allograft prior to reinfection. Importantly, we identified the development of neutralizing antibodies and humoral memory responses prior to SARS-CoV-2 reinfection. However, these neutralizing antibodies failed to confer protection against reinfection, suggesting that additional factors are required for efficient prevention of SARS-CoV-2 reinfection. Further, we found no evidence supporting viral evasion of primary adaptive immune responses, suggesting that susceptibility to reinfection may be determined by host factors rather than pathogen adaptation.