Faculty Bibliography

Background: COVID-19 is a heterogenous disease resulting in long-term sequela in predisposed individuals. It is not uncommon that recovering patients endure non-respiratory ill-defined manifestations, including anosmia, and neurological and cognitive deficit persisting beyond recovery"”a constellation of conditions that are grouped under the umbrella of long-term COVID-19 syndrome. Association between COVID-19 and autoimmune responses in predisposed individuals was shown in several studies. Aim and methods: To investigate autoimmune responses against neuronal and CNS autoantigens in SARS-CoV-2-infected patients, we performed a cross-sectional study with 246 participants, including 169 COVID-19 patients and 77 controls. Levels of antibodies against the acetylcholine receptor, glutamate receptor, amyloid β peptide, alpha-synucleins, dopamine 1 receptor, dopamine 2 receptor, tau protein, GAD-65, N-methyl D-aspartate (NMDA) receptor, BDNF, cerebellar, ganglioside, myelin basic protein, myelin oligodendrocyte glycoprotein, S100-B, glial fibrillary acidic protein, and enteric nerve were measured using an Enzyme-Linked Immunosorbent Assay (ELISA). Circulating levels of autoantibodies were compared between healthy controls and COVID-19 patients and then classified by disease severity (mild [n = 74], severe [n = 65], and requiring supplemental oxygen [n = 32]). Results: COVID-19 patients were found to have dysregulated autoantibody levels correlating with the disease severity, e.g., IgG to dopamine 1 receptor, NMDA receptors, brain-derived neurotrophic factor, and myelin oligodendrocyte glycoprotein. Elevated levels of IgA autoantibodies against amyloid β peptide, acetylcholine receptor, dopamine 2 receptor, myelin basic protein, and α-synuclein were detected in COVID-19 patients compared with healthy controls. Lower IgA autoantibody levels against NMDA receptors, and IgG autoantibodies against glutamic acid decarboxylase 65, amyloid β peptide, tau protein, enteric nerve, and S100-B were detected in COVID-19 patients versus healthy controls. Some of these antibodies have known clinical correlations with symptoms commonly reported in the long COVID-19 syndrome. Conclusions: Overall, our study shows a widespread dysregulation in the titer of various autoantibodies against neuronal and CNS-related autoantigens in convalescent COVID-19 patients. Further research is needed to provide insight into the association between these neuronal autoantibodies and the enigmatic neurological and psychological symptoms reported in COVID-19 patients.

The SARS-CoV-2 infection is associated with increased levels of autoantibodies targeting immunological proteins such as cytokines and chemokines. Reports further indicate that COVID-19 patients may develop a broad spectrum of autoimmune diseases due to reasons not fully understood. Even so, the landscape of autoantibodies induced by SARS-CoV-2 infection remains uncharted territory. To gain more insight, we carried out a comprehensive assessment of autoantibodies known to be linked to diverse autoimmune diseases observed in COVID-19 patients in a cohort of 231 individuals, of which 161 were COVID-19 patients (72 with mild, 61 moderate, 28 with severe disease) and 70 were healthy controls. Dysregulated IgG and IgA autoantibody signatures, characterized mainly by elevated concentrations, occurred predominantly in patients with moderate or severe COVID-19 infection. Autoantibody levels often accompanied anti-SARS-CoV-2 antibody concentrations while stratifying COVID-19 severity as indicated by random forest and principal component analyses. Furthermore, while young versus elderly COVID-19 patients showed only slight differences in autoantibody levels, elderly patients with severe disease presented higher IgG autoantibody concentrations than young individuals with severe COVID-19. This work maps the intersection of COVID-19 and autoimmunity by demonstrating the dysregulation of multiple autoantibodies triggered during SARS-CoV-2 infection. Thus, this cross-sectional study suggests that SARS-CoV-2 infection induces autoantibody signatures associated with COVID-19 severity and several autoantibodies that can be used as biomarkers of COVID-19 severity, indicating autoantibodies as potential therapeutical targets for these patients. This article is protected by copyright. All rights reserved.

Cross-reactive immunity between SARS-CoV-2 and other related coronaviruses has been well-documented, and it may play a role in preventing severe COVID-19. Epidemiological studies early in the pandemic showed a geographical association between high influenza vaccination rates and lower incidence of SARS-CoV-2 infection. We, therefore, analyzed whether exposure to influenza A virus (IAV) antigens could influence the T cell repertoire in response to SARS-CoV-2, indicating a heterologous immune response between these 2 unrelated viruses. Using artificial antigen-presenting cells (aAPCs) combined with real-time reverse-transcription PCR (RT-qPCR), we developed a sensitive assay to quickly screen for antigen-specific T cell responses and detected a significant correlation between responses to SARS-CoV-2 epitopes and IAV dominant epitope (M158-66). Further analysis showed that some COVID-19 convalescent donors exhibited both T cell receptor (TCR) specificity and functional cytokine responses to multiple SARS-CoV-2 epitopes and M158-66. Utilizing an aAPC-based stimulation/expansion assay, we detected cross-reactive T cells with specificity to SARS-CoV-2 and IAV. In addition, TCR sequencing of the cross-reactive and IAV-specific T cells revealed similarities between the TCR repertoires of the two populations. These results indicate that heterologous immunity shaped by our exposure to other unrelated endemic viruses may affect our immune response to novel viruses such as SARS-CoV-2.

Pathogenic autoreactive antibodies that may be associated with life-threatening coronavirus disease 2019 (COVID-19) remain to be identified. Here, we show that self-assembled genome-scale libraries of full-length proteins covalently coupled to unique DNA barcodes for analysis by sequencing can be used for the unbiased identification of autoreactive antibodies in plasma samples. By screening 11,076 DNA-barcoded proteins expressed from a sequence-verified human ORFeome library, the method, which we named MIPSA (for Molecular Indexing of Proteins by Self-Assembly), allowed us to detect circulating neutralizing type-I and type-III interferon (IFN) autoantibodies in five plasma samples from 55 patients with life-threatening COVID-19. In addition to identifying neutralizing type-I IFN-α and IFN-ω autoantibodies and other previously known autoreactive antibodies in patient plasma, MIPSA enabled the detection of as yet unidentified neutralizing type-III anti-IFN-λ3 autoantibodies that were not seen in healthy plasma samples or in convalescent plasma from ten non-hospitalized individuals with COVID-19. The low cost and simple workflow of MIPSA will facilitate unbiased high-throughput analyses of protein-antibody, protein-protein and protein-small-molecule interactions.

COVID-19 shares the feature of autoantibody production with systemic autoimmune diseases. In order to understand the role of these immune globulins in the pathogenesis of the disease, it is important to explore the autoantibody spectra. Here we show, by a cross-sectional study of 246 individuals, that autoantibodies targeting G protein-coupled receptors (GPCR) and RAS-related molecules associate with the clinical severity of COVID-19. Patients with moderate and severe disease are characterized by higher autoantibody levels than healthy controls and those with mild COVID-19 disease. Among the anti-GPCR autoantibodies, machine learning classification identifies the chemokine receptor CXCR3 and the RAS-related molecule AGTR1 as targets for antibodies with the strongest association to disease severity. Besides antibody levels, autoantibody network signatures are also changing in patients with intermediate or high disease severity. Although our current and previous studies identify anti-GPCR antibodies as natural components of human biology, their production is deregulated in COVID-19 and their level and pattern alterations might predict COVID-19 disease severity.

BACKGROUND:COVID-19 can cause some individuals to experience chronic symptoms. Rates and predictors of chronic COVID-19 symptoms are not fully elucidated. OBJECTIVE:To examine occurrence and patterns of post-acute sequelae of SARS-CoV2 infection (PASC) symptomatology and their relationship with demographics, acute COVID-19 symptoms and anti-SARS-CoV-2 IgG antibody responses. METHODS:A multi-stage observational study was performed of adults (≥18 years) from 5 US states. Participants completed two rounds of electronic surveys (May-July 2020; April-May 2021) and underwent testing to anti-SARS-CoV-2 nucleocapsid protein IgG antibody testing. Latent Class Analysis was used to identify clusters of chronic COVID-19 symptoms. RESULTS:Overall, 390 adults (median [25%ile, 75%ile] age: 42 [31, 54] years) with positive SARS-CoV-2 antibodies completed the follow-up survey; 92 (24.7%) had ≥1 chronic COVID-19 symptom, with 11-month median duration of persistent symptoms (range: 1-12 months). The most common chronic COVID-19 symptoms were fatigue (11.3%), change in smell (9.5%) or taste (5.6%), muscle or joint aches (5.4%) and weakness (4.6%). There were significantly higher proportions of ≥1 persistent COVID-19 symptom (31.5% vs. 18.6%; Chi-square, P = 0.004), and particularly fatigue (15.8% vs. 7.3%, P = 0.008) and headaches (5.4% vs. 1.0%, P = 0.011) in females compared to males. Chronic COVID-19 symptoms were also increased in individuals with ≥6 acute COVID-19 symptoms, Latent class analysis revealed 4 classes of symptoms. Latent class-1 (change of smell and taste) was associated with lower anti-SARS-CoV-2 antibody levels; class-2 and 3 (multiple chronic symptoms) were associated with higher anti-SARS-CoV-2 antibody levels and more severe acute COVID-19 infection. LIMITATIONS/CONCLUSIONS:Ambulatory cohort with less severe acute disease. CONCLUSION/CONCLUSIONS:Individuals with SARS-CoV-2 infection commonly experience chronic symptoms, most commonly fatigue, changes in smell or taste and muscle/joint aches. Female sex, severity of acute COVID-19 infection, and higher anti-SARS-CoV-2 IgG levels were associated with the highest risk of having chronic COVID-19 symptoms.

BACKGROUND:The complex relationship between clinical manifestations of SARS-CoV-2 and individual immune responses is not fully elucidated. OBJECTIVE:To examine phenotypes of symptomatology and their relationship with positive anti-SARS-CoV-2 IgG antibody responses. METHODS:An observational study was performed of adults (≥18 years) from 5 US states. Participants completed an electronic survey and underwent testing to anti-SARS-CoV-2 nucleocapsid protein IgG antibody between May-July 2020. Latent Class Analysis was used to identify characteristic symptom clusters. RESULTS:Overall, 9,507 adults (mean±SD age: 39.6±15.0 years) completed the survey; 6,665 (70.1%) underwent antibody testing for anti-SARS-CoV-2 IgG. Positive SARS-CoV-2 antibodies were associated with self-reported positive SARS-CoV-2 nasal swab (bivariable logistic regression; OR [CI95]: 5.98 [4.83, 7.41]), household with ≥6 members (1.27 [1.14, 1.41]) and sick contact (3.65 [3.19, 4.17]), and older age (50-69 years: 1.55 [1.37, 1.76]); ≥70 years: 1.52 [1.16, 1.99]), but inversely associated with female sex (0.61 [0.55, 0.68]). Latent class analysis revealed 8 latent classes of symptoms. Latent classes-1 (all symptoms) and 4 (fever, cough, muscle ache, anosmia, dysgeusia, and headache) were associated with the highest proportion (62.0% and 57.4%) of positive antibodies, whereas classes-6 (fever, cough, muscle ache, headache) and 8 (anosmia, dysgeusia) had intermediate proportions (48.2% and 40.5%), and classes-3 (headache, diarrhea, stomach pain) and 7 (no symptoms) had the lowest proportion (7.8% and 8.5%) of positive antibodies. CONCLUSION/CONCLUSIONS:SARS-CoV-2 infections manifest with substantial diversity of symptoms, which are associated with variable anti-SARS-CoV-2 IgG antibody responses. Prolonged fever, anosmia and receiving supplemental oxygen therapy had strongest associations with positive SARS-CoV-2 IgG.

Unbiased antibody profiling can identify the targets of an immune reaction. A number of likely pathogenic autoreactive antibodies have been associated with life-threatening SARS-CoV-2 infection; yet, many additional autoantibodies likely remain unknown. Here we present Molecular Indexing of Proteins by Self Assembly (MIPSA), a technique that produces ORFeome-scale libraries of proteins covalently coupled to uniquely identifying DNA barcodes for analysis by sequencing. We used MIPSA to profile circulating autoantibodies from 55 patients with severe COVID-19 against 11,076 DNA-barcoded proteins of the human ORFeome library. MIPSA identified previously known autoreactivities, and also detected undescribed neutralizing interferon lambda 3 (IFN-λ3) autoantibodies. At-risk individuals with anti-IFN-λ3 antibodies may benefit from interferon supplementation therapies, such as those currently undergoing clinical evaluation.

Importance:Data on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence in the United States are still emerging. Objective:To elucidate SARS-CoV-2 seroprevalence and symptom onset in a culturally linked community across 5 states in the United States. Design, Setting, and Participants:This cross-sectional study included adults (aged ≥18 years) recruited from the orthodox Jewish community across 5 states (California, Connecticut, Michigan, New Jersey, and New York) in 3 geographically distinct areas of the United States between May 13 and July 6, 2020. Participants completed an online survey and underwent SARS-CoV-2 antibody testing. Main Outcomes and Measures:Seroprevalence and date of symptom onset of SARS-CoV-2. Results:Overall, 9507 adults (mean [SD] age, 39.6 [15.0] years; 3777 [39.7%] women) completed the SARS-CoV-2 survey, of whom 6665 (70.1%) had immunoglobin G anti-SARS-CoV-2 antibody levels assessed. A high seroprevalence of SARS-CoV-2 antibodies was observed across all communities, with the highest proportion of positive testing observed in New Jersey (1080 of 3323 [32.5%]) and New York (671 of 2196 [30.6%]). Most individuals with a positive SARS-CoV-2 immunoglobin G antibody test reported a date of symptom-onset between March 9 and March 31, 2020 (California: 135 of 154 [87.7%]; Connecticut: 32 of 34 [94.1%]; Michigan: 44 of 50 [88.0%]; New Jersey: 964 of 1168 [82.5%]; New York: 571 of 677 [84.3%]). This start date was coincident with the Jewish festival of Purim, celebrated March 9 to 10, 2020, with extensive intracommunity spread in the weeks following (mean and mode of peak symptom onset, March 20, 2020), occurring in the absence of strong general and culture-specific public health directives. Conclusions and Relevance:This cross-sectional study of orthodox Jewish adults across the US found that socioculturally bound communities experienced early parallel outbreaks in discrete locations, notably prior to substantive medical and governmental directives. Further research should clarify optimal national, local, community-based, and government policies to prevent outbreaks in social and cultural communities that traditionally gather for holidays, assemblies, and festivals.