Alzheimer's disease (AD) is characterized by complex immune interactions, yet the role of antibody-mediated responses remains poorly understood. Recent advances in high-throughput epitope screening enable the identification of disease-associated epitopes that may play a role in AD pathogenesis. We previously developed a computational pipeline to detect disease-related epitopes from high-throughput epitope profiling data, and extend this approach to AD to identify potential antibody responses to pathogenic or autoantigenic epitopes in cerebrospinal fluid (CSF) samples. We performed IgG epitope profiling on CSF samples from 625 individuals, including 359 AD patients, 97 mild cognitive impairment (MCI) controls, and 158 cognitively normal controls. The remaining samples did not fit these categories and were excluded from subgroup analyses. CSF samples were screened using Serimmune's Serum Epitope Repertoire Analysis (SERA) platform, which profiles IgG binding to a random 12-mer bacterial display library. Sequencing of enriched 12-mers produced approximately 3 million reads per sample. K-mers (k=5,6) were extracted, and enrichment scores were calculated based on expected amino acid distributions. Identified k-mers were mapped to human and viral proteomes using protein tiling and permutation analysis to assess statistical enrichment. Epitopes were identified via peak calling, clustered using complete-linkage clustering, and scored for disease association using an outlier sum statistic. Multiple hypothesis correction was performed using the Benjamini-Hochberg method. Comparison of AD patients to cognitively normal controls revealed 12 distinct epitopes from 12 viral proteins, spanning multiple viral families (Table 1). These epitopes originated from 9 viruses, with a notable overrepresentation of herpesviruses (HHV8P, HHV6U, EBVB9, HCMVM). Additionally, we identified 42 CNS-expressed autoantigens associated with AD (Table 2). These included ion channels (SCN1A_HUMAN, SCN3A_HUMAN, ASIC4_HUMAN), neurotransmitter receptors (NTRK2_HUMAN, GRIA1_HUMAN), synaptic and neurodevelopmental proteins (SV2B_HUMAN, ASTN1_HUMAN), and immune-regulatory proteins (PD1L1_HUMAN, P2Y10_HUMAN), suggesting a potential autoimmune component in AD pathology. Our computational approach successfully identifies putative AD-associated epitopes, with a significant overrepresentation of herpesvirus-derived epitopes and CNS autoantigens in AD cases. These findings support a growing body of evidence implicating viral infections and potential autoimmune mechanisms in AD pathology. Further validation and mechanistic studies are warranted to explore the potential role of these epitopes in AD progression.

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

INTRODUCTION:While there may be microbial contributions to Alzheimer's disease (AD), findings have been inconclusive. We recently reported an AD-associated CD83(+) microglia subtype associated with increased immunoglobulin G4 (IgG4) in the transverse colon (TC). METHODS:We used immunohistochemistry (IHC), IgG4 repertoire profiling, and brain organoid experiments to explore this association. RESULTS:CD83(+) microglia in the superior frontal gyrus (SFG) are associated with elevated IgG4 and human cytomegalovirus (HCMV) in the TC, anti-HCMV IgG4 in cerebrospinal fluid, and both HCMV and IgG4 in the SFG and vagal nerve. This association was replicated in an independent AD cohort. HCMV-infected cerebral organoids showed accelerated AD pathophysiological features (Aβ42 and pTau-212) and neuronal death. DISCUSSION:Findings indicate complex, cross-tissue interactions between HCMV and the adaptive immune response associated with CD83(+) microglia in persons with AD. This may indicate an opportunity for antiviral therapy in persons with AD and biomarker evidence of HCMV, IgG4, or CD83(+) microglia. HIGHLIGHTS:Cross-tissue interaction between HCMV and the adaptive immune response in a subset of persons with AD. Presence of CD83(+) microglial associated with IgG4 and HCMV in the gut. CD83(+) microglia are also associated presence of HCMV and IgG4 in the cortex and vagal nerve. Replication of key association in an independent cohort of AD subjects. HCMV infection of cerebral organoids accelerates the production of AD neuropathological features.

369 Background: Kidney cancer (renal cell carcinoma, RCC), the 8th most common U.S. cancer, is in need for better cure rates through early detection (5-year relative survival for stage I RCC: ̃95%; for stage IV RCC ̃19%). Autoantibodies are common in cancer and result from the altered expression, localization, or post-translational modification of endogenous proteins in tumor cells (autoantigens) and from the expression of mutated genes that give rise to new proteins (neoantigens). In contrast to cellular immune responses in cancer, autoantibodies are less well characterized, yet hold promise to enable cancer early detection by immune amplification of the ‘cancer signal’ while retaining specificity to cancer types including RCC. Autoantibodies may therefore be useful for kidney cancer early detection and diagnosis. Our goal was to profile the autoantibody repertoire in blood from patients with clear cell RCC (ccRCC), the most common form of RCC, in order to: 1) determine if autoantibodies can be detected in patients with early-stage and late-stage ccRCC; 2) identify common epitopes amongst ccRCC patients that could suggest common RCC antigens; and 3) determine specificity and sensitivity of potential autoantibody biomarkers for ccRCC vs. other non-cancer conditions. Methods: We use the SERA platform (https://serimmune.com/publications/) to compare putative autoantibody signal in blood from 177 patients with ccRCC, 23 with benign kidney lesions, and ̃800 healthy controls. SERA utilizes a random bacterial display 12mer peptide library of 1010 diversity in conjunction with next-generation sequencing to ascertain epitope enrichment across the entire human proteome. Results: We find significant differences in epitope repertoires in ccRCC compared to the healthy human cohort. Patients with ccRCC exhibit a rich repertoire of rare, enriched epitopes which may comprise putative autoantibody signal. This epitope signal is present with high abundance in all ccRCC stages, including stage I ccRCC. In contrast, healthy controls and patients with benign kidney lesions demonstrate more restricted repertoires. However, we do not find evidence of common ccRCC antigens: epitopes are not conserved across large subsets of ccRCC patients. Conclusions: Our initial results suggest that each patient may develop an individualized tumor-associated antibody response. Whether assessing a select epitope panel in a patient’s blood could be useful for ccRCC early detection, or even epitope diversity without needing to identify specific epitopes, warrants further study.

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.

Winston A. Haynes, Kathy Kamath, Joel Bozekowski, Elisabeth Baum-Jones, Melissa 3 Campbell, Arnau Casanovas-Massana, Patrick S. Daugherty, Charles S. Dela Cruz, 4 Abhilash Dhal, Shelli F. Farhadian, Lynn Fitzgibbons, John Fournier, Michael Jhatro, 5 Gregory Jordan, Debra Kessler, Jon Klein, Carolina Lucas, Larry L. Luchsinger, Brian 6 Martinez, Mary C. Muenker, Lauren Pischel, Jack Reifert, Jaymie R. Sawyer, Rebecca 7 Waitz, Elsio A. Wunder Jr., Minlu Zhang, Yale IMPACT Team, Akiko Iwasaki, Albert I. Ko, 8 John C. Shon 9 10 1 Serimmune, Inc., Goleta, CA, USA 11 2 Department of Pediatrics, Section of Pediatric Infectious Diseases, Yale School of Medicine, 12 New Haven, CT, USA 13 3 Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, 14 CT, USA 15 4 Department of Medicine, Section of Pulmonary, Critical Care and Sleep Medicine, Yale School 16 of Medicine, New Haven, CT, USA 17 5 Department of Medicine, Section of Infectious Diseases, Yale School of Medicine, New Haven, 18 CT, USA 19 6 Santa Barbara Cottage Hospital, Santa Barbara, CA, USA 20 7 New York Blood Center, New York, NY, USA 21 8 Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA 22 9 Howard Hughes Medical Institute, Chevy Chase, MD, USA 23 † These authors contributed equally 24 * Correspondence to: john.shon@serimmune.com 25 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint The copyright holder for this this version posted November 26, 2020. ; https://doi.org/10.1101/2020.11.23.20235002 doi: medRxiv preprint

Fine scale delineation of epitopes recognized by the antibody response to SARS-CoV-2 infection will be critical to understanding disease heterogeneity and informing development of safe and effective vaccines and therapeutics. The Serum Epitope Repertoire Analysis (SERA) platform leverages a high diversity random bacterial display library to identify epitope binding specificities with single amino acid resolution. We applied SERA broadly, across human, viral and viral strain proteomes in multiple cohorts with a wide range of outcomes from SARS-CoV-2 infection. We identify dominant epitope motifs and profiles which effectively classify COVID-19, distinguish mild from severe disease, and relate to neutralization activity. We identify a repertoire of epitopes shared by SARS-CoV-2 and endemic human coronaviruses and determine that a region of amino acid sequence identity shared by the SARS-CoV-2 furin cleavage site and the host protein ENaC-alpha is a potential cross-reactive epitope. Finally, we observe decreased epitope signal for mutant strains which points to reduced antibody response to mutant SARS-CoV-2. Together, these findings indicate that SERA enables high resolution of antibody epitopes that can inform data-driven design and target selection for COVID-19 diagnostics, therapeutics and vaccines.