Introduction:Systemic Lupus Erythematosus (SLE) exhibits a pronounced sex bias, affecting females approximately nine times more frequently than males; however, males tend to experience a more severe clinical course yet the molecular basis for these differences remains unclear. Methods:Leveraging epigenomic, transcriptomic, and proteomic data from the whole blood of 720 SLE patients (679 females, 41males) and 84 healthy controls (77 females, 7 males), we conducted comprehensive multi-omic analyses to identify sex-specific molecular features of this disease. Specifically, differential expression analysis for each modality was conducted using a factorial design to identify differences between disease and healthy controls (SLE-HC) for each sex, as well as the interaction effects between sex and disease ([Male SLE - Male HC] - [Female SLE - Female HC]). Benjamini & Hochberg false discovery rate (FDR) was used for multiple test correction. Results:The strongest signal differentiating males and females with SLE was the aberrant expression of the long non-coding RNA, XIST, in males. This XIST expression in males with SLE was bimodal, with 54% of males having elevated XIST expression, and correlated with disease severity. Males with SLE also exhibited significant hypermethylation of the X chromosome and transcriptional silencing of X-linked genes - hallmarks of X-chromosome inactivation (XCI), a process typically restricted to females. Conclusion:These results suggest that X-chromosome silencing by XIST may contribute to SLE disease in males.

Formation of anti-drug antibodies (ADA) and, in particular, neutralizing antibodies (NAb), is a major risk to the development of biotherapeutics. Cell-based assays, which can reflect the mechanistic interactions among the drug, target, and NAb, are often most suitable for the detection of NAb. We report the development and validation of cell-based platform assays for a class of incretin molecules. An affinity capture elution step was employed to improve drug tolerance of a cell-based cyclic adenosine monophosphate (cAMP) assay. Assay conditions and procedures, including acid elution, cell density, and TAG labeled cAMP (cAMP-TAG) incubation time and concentration, were thoroughly optimized. Delta percent (Δ

Anti-drug antibodies (ADAs) against biotherapeutics remain difficult to predict, limiting efforts to assess and mitigate immunogenicity risk prior to clinical development. Existing immunogenicity data are fragmented across disparate sources and reported using inconsistent definitions, creating a major barrier to understanding the drivers of ADA formation. To address this challenge, we established the Immunogenicity Database Collaborative (IDC), launched its public website (https://www.immunogenicitydb.org), and developed the first release of the Immunogenicity Dataset (IDC DS V1), a structured clinical immunogenicity dataset integrating therapeutic characteristics, amino acid sequence information, and patient cohort-level clinical data curated from publicly available sources. The IDC DS V1 contains 4,146 ADA-related datapoints spanning 1,788 cohorts, 727 clinical trials, and 218 therapeutics. Analysis of the dataset highlights trends in ADA frequency, reveals important sources of variability across clinical contexts, and identifies key factors associated with immunogenicity risk. The IDC provides a foundational resource to standardize clinical immunogenicity data and support immunogenicity risk assessment across the biopharmaceutical industry. In addition to the current dataset release, it establishes an extensible data architecture and framework for future community-driven expansion into additional areas of immunogenicity research.

SARS-CoV-2 infections lead to a wide-range of outcomes from mild or asymptomatic illness to serious complications and death. While many studies have characterized hospitalized SARS-CoV-2 patient immune responses, we were interested in whether serious complications of SARS-CoV-2 infection could be predicted early in ambulatory subjects. To that end, we used samples from SARS-CoV-2-infected individuals from the placebo arm of the BLAZE-1 clinical trial who progressed to hospitalization or death compared to individuals in the same study who did not require medical intervention and investigated whether baseline serum cytokines and chemokines could predict severe outcome. High-risk demographic factors at baseline, including age, nasal pharyngeal viral load, duration from symptom onset, and BMI provide significant predictive capacity for a hospitalization or death with an AUC of ROC = 0.77. The predictive performance of our outcome modeling increased when baseline serum protein markers were included. In fact, the one-marker model indicated that there were 51 individual proteins (including known markers of inflammation like IL-6, MCP-3, CXCL10, IL-1Ra, and PTX3) that significantly increased the AUC of ROC beyond high-risk patient demographics alone to range between 0.78 to 0.88. Moreover, a two-marker model incorporating levels of both IL-6 and PTX3 further improved the prediction over the addition of a single protein marker to an AUC of ROC = 0.91. While the analytes identified in this study have been well-documented to be altered in SARS-CoV-2 infection, this analysis demonstrates the potential value of their use in predicting hospitalization or death in ambulatory participants infected with SARS-CoV-2 and could guide early treatment decisions.

Ixekizumab (IXE), an IL-17A antagonist, and guselkumab (GUS), an IL-23p19 antagonist, are common psoriasis treatments. This longitudinal analysis assessed gene expression profiles in IXE- and GUS-treated patients with plaque psoriasis through week 4. In IXORA-R (NCT03573323), a head-to-head phase 4 study, adults with moderate-to-severe plaque psoriasis were assigned 1:1 to receive IXE or GUS. RNA expression was assessed in lesional tissue (n=72) from IXE-treated patients, GUS-treated patients, and healthy control groups (199 samples in total). Empirical Bayes was used to model RNA-sequencing data; differential expression was analyzed by tissue type, treatment, and time point, correcting for random effects. At week 1, lesions from IXE-treated patients had greater numbers of differentially expressed genes (392 upregulated, 696 downregulated) than those from GUS-treated patients (0 upregulated 0 downregulated). By week 4, the numbers of differentially expressed genes increased in both groups (IXE: 1882 upregulated, 1649 downregulated; GUS: 318 upregulated, 131 downregulated). Molecular shifts from baseline to week 4 occurred earlier with greater magnitude in IXE- than in GUS-treated patients. Rapid normalization of transcriptomic changes in patients receiving an IL-17A antagonist reflected downregulation of key inflammatory genes in psoriatic epidermis. Differentially expressed genes involved in epidermal IL-17A and IL-36 responses correlated with PASI 100 response.

PT022 / #742 Topic: AS12 - Genetics, Epigenetics, Transcriptomics POSTER TOUR 05: SLE PATHOGENESIS 24-05-2025 10:00 AM - 10:20 AM Systemic lupus erythematosus (SLE) exhibits a pronounced female-biased imbalance in disease prevalence, with a female-to-male ratio of 9:1. Although the exact mechanisms remain unclear, the significant role of X-chromosome dosage is supported by karyotypic risks associated with SLE. This study utilizes paired transcriptomic (RNAseq), proteomic (Olink), and epigenomic (EMSeq) data from large phase 3 trials to gain mechanistic insights into the drivers behind the sexual bias in SLE. Baseline RNAseq, Olink, and EMseq data were collected from the whole blood of 722 SLE patients (680 female, 42 male) and 84 healthy controls (77 female, 7 male) from 2 phase 3 clinical trials (NCT03616964, NCT03616912). Differential expression analysis was performed using a factorial design to calculate the following comparisons for each modality: i) SLE vs healthy controls in females, ii) SLE vs healthy controls in males, and iii) interaction between sex and disease. Gene set enrichment analysis (GSEA) of patient subsets was conducted using Gene Ontology (GO) biological process terms. To ensure our cohort did not contain erroneous results due to Klinefelter’s males, we inferred X-chromosome heterozygosity by calculating the read depth of the X-chromosome from the EMseq bam files. To validate our results, we performed similar differential expression analysis on EMseq data from an independent cohort of SLE patients (241 females, 13 males) from 2 additional phase 3 clinical trials (NCT01205438, NCT01196091). The strongest changes differentiating how sexes respond to disease were observed in the expression of lncRNA XIST (X-inactive specific transcript) and epigenetics. Specifically, we noted an increased expression of XIST in males with SLE compared to healthy controls (Figure 1A), with this expression exhibiting a bimodal distribution (Figure 1B). GSEA indicated that males with high XIST expression exhibit enrichment in biological processes (GO) related to metabolism and immunoglobulin production, such as oxidative phosphorylation, B cell mediated immunity, and immunoglobulin production compared to XIST low males. Consistent with XIST’s known role in X-chromosome inactivation, we observed corresponding hypermethylation of the X-chromosome and downregulation of X-linked genes in males with SLE (Figure 1C). Lastly, we observed similar patterns of X-chromosome hypermethylation using EMseq data from an independent cohort of SLE patients. A) Violin plots of XIST expression (RNAseq) in women (left) and men (right). B) Density plot of the bimodal expression of XIST in men with SLE. Dashed red line indicates the separation between XIST high and XIST low groups. C) Distribution plots of significant changes (|FC| > 1.5; FDR < 0.1) in gene methylation (top), promoter methylation (middle), and gene expression (bottom) on the X chromosome in females (pink), XIST high males (green), and XIST low males (blue) compared to healthy controls. Figure 1. Partial X-chromosome inactivation in males with SLE. This study, which includes the most comprehensive and largest dataset of male SLE patients to date, shows that males with SLE express significantly higher levels of XIST, accompanied by hypermethylation of the X-chromosome and downregulation of X-linked genes compared to healthy controls, suggesting partial X-chromosome inactivation in males with SLE. Importantly, we have confirmed that these changes are not artifacts of Klinefelter’s patients within the cohort. We hypothesize that this X-chromosome inactivation may be driving SLE via several mechanisms, including: i) inactivation of immunoregulatory molecules, ii) inducing development of SLE autoantibodies, and/or iii) driving interferon production via TLR7.

O026 / #740 Topic:AS22 - SLE Heterogeneity Late-Breaking Abstract ABSTRACT CONCURRENT SESSION 04: ADVANCING LUPUS THERAPIES AND INSIGHTS 22-05-2025 1:40 PM - 2:40 PM Integrative omics approaches offer a powerful strategy to dissect the complex biological networks and pathways involved in disease pathophysiology. However, integrating diverse data types with varying scales, biological contexts, and feature numbers poses significant challenges. This study aims to: i) identify molecular subtypes of SLE patients via a multi-omic integrative approach, ii) characterize these clusters using molecular and clinical data, and iii) identify the most discriminant subset of features for patient classification. Similarity Network Fusion (SNF) was used to integrate baseline transcriptomic (RNAseq), proteomic (Olink), and epigenomic (EMseq) data from the whole blood of 722 SLE patients that were randomized to placebo plus standard of care in phase 3 clinical trials (NCT03616964,NCT03616912), and 84 healthy controls. Patient subgroups were identified via spectral clustering, and cluster robustness was determine using a bootstrapping approach (n = 30). Clusters were characterized with omics data via differential expression and gene set enrichment analysis (GSEA). Clusters were also characterized with clinical metrics via t-tests and random forest analysis. Finally, we utilized Data Integration Analysis for Biomarker Discovery using Latent cOmponents (DIABLO) modeling to identify potential biomarkers associated with these SLE classes. Integration of the omics datatypes identified 3 distinct clusters of individuals: cluster 1 (n = 176), cluster 2 (n = 299), and cluster 3 (n = 331). All 84 healthy controls were grouped within cluster 2 (Figure 1A). Notably, clustering based on individual datatypes failed to reproduce these distinct clusters. Clinical data revealed that SLE patients in cluster 2 exhibited significantly lower dsDNA, IFI44L, and SLEDAI scores, along with higher complement (C3) levels compared to the other clusters (Figure 1B), indicating a milder form of SLE. This is consistent with the fact that these SLE patients clustered with the healthy controls. Additional clinical measurements (Figure 1C) and pathway enrichment analysis (Figure 1D) revealed distinct signatures in the other 2 clusters: cluster 3 displayed an elevated adaptive immunity signature, while cluster 1 was characterized by innate immunity signatures. Finally, integrating all 3 datatypes using the DIABLO modeling approach identified 3 latent components with a minimal set of discriminating biomarkers for each cluster. A) Spectral clustering of patient-patient similarities calculated from the SNF-fused data. B) Distribution of conventional SLE metrics among the 3 SNF clusters (excluding healthy patients). Significant differences assessed with a t-test and false discover rate (FDR). C) Significant clinical differences between Cluster 1 and Cluster 3 using t-test and FDR. Fold change (C1/C3) greater than 1 indicates increased measurements in Custer 1 compared to Cluster 3. D) Normalized Enrichment Score (NES) of select GO terms from a GSEA analysis comparing C1 vs C3 using RNAseq. Positive NES indicates increased activity in C1, and vice-versa. Figure 1. SLE patient clusters and characterization. Multi-omic integration revealed 3 molecularly distinct clusters of SLE patients. Using orthogonal datatypes (clinical and omics), we characterized these clusters into 3 novel classifications: mild, innate-driven, and adaptive-driven immunity. This work helps our understanding of the complex heterogenous nature of SLE and will guide targeted treatment approaches with innate or adaptive involvement.

An essential criterion for understanding the immunogenicity potential of biotherapeutic proteins is defining the set of peptides processed and presented by human leukocyte antigen (HLA) class II molecules. The heterozygotic state of most individuals and the extreme polymorphic nature of these molecules preclude efforts to define both the precise sequences presented by various alleles and the percentage of patients that are subject to immune responses that can negate clinical benefit and/or result in adverse events. We have developed a diverse, robust, and reproducible monoallelic HLA-DRB1 system in professional antigen presenting cells capable of examining the immunogenic potential of any human IgG. Determination of the allelic restriction of adalimumab CD4 T cell epitopes for two distinct geographic populations underscores the vitality of this system as a central component of a preclinical immunogenicity risk assessment strategy.

OBJECTIVE:Neutrophils play an important role in regulating immune and inflammatory responses in patients with rheumatoid arthritis (RA). We assessed whether baricitinib, a JAK1/JAK2 inhibitor, could reduce neutrophil activation and whether a neutrophil activation score could predict treatment response. METHODS:Markers of neutrophil activation, calprotectin, and neutrophil extracellular traps (NETs) were analyzed using enzyme-linked immunosorbent assay in plasma from patients with RA (n = 271) and healthy controls (n = 39). For patients with RA, neutrophil activation markers were measured at baseline, 12 weeks, and 24 weeks after receiving placebo and 2 and 4 mg baricitinib. Whole-blood RNA analyses from multiple randomized baricitinib RA trials were performed to study neutrophil-related transcripts (n = 1,651). RESULTS:Baseline levels of plasma neutrophil markers were elevated in patients with RA compared to healthy controls (P < 0.001). Receiving baricitinib reduced levels of soluble calprotectin at 12 and 24 weeks, especially in patients with RA responding to treatment, as determined by American College of Rheumatology 20% improvement criteria. Whole-blood RNA analysis revealed similar changes in the predominant neutrophil markers calprotectin and Fcα receptor I upon reception of baricitinib in three randomized clinical trials involving patients with at various stages of disease-modifying therapy. Clustering analysis of plasma activation markers showed elevated levels of calprotectin and NETs (eg, a neutrophil activation score, at baseline, could predict treatment response to baricitinib). In contrast, C-reactive protein levels could not distinguish between responders and nonresponders. CONCLUSION:Neutrophil activation markers may add clinical value in predicting treatment response to baricitinib and other drugs targeting RA. This study supports personalized medicine in treating patients with RA, not only based on symptoms but also based on immunophenotyping.

MOTIVATION:On-target gene knockdown, using siRNA, ideally results from binding fully complementary regions in mRNA transcripts to induce direct cleavage. Off-target siRNA gene knockdown can occur through several modes, one being a seed-mediated mechanism mimicking miRNA gene regulation. Seed-mediated off-target effects occur when the ∼8 nucleotides at the 5' end of the guide strand, called a seed region, bind the 3' untranslated regions of mRNA, causing reduced translation. Experiments using siRNA knockdown paired with RNA-seq can be used to detect siRNA sequences with off-target effects driven by the seed region. However, there are limited computational tools designed specifically for detecting siRNA off-target effects mediated by the seed region in differential gene expression experiments.RESULTS:SeedMatchR is an R package developed to provide users a single, unified resource for detecting and visualizing seed-mediated off-target effects of siRNA using RNA-seq experiments. SeedMatchR is designed to extend current differential expression analysis tools, such as DESeq2, by annotating results with predicted seed matches. Using publicly available data, we demonstrate the ability of SeedMatchR to detect cumulative changes in differential gene expression attributed to siRNA seed region activity.AVAILABILITY:SeedMatchR is available on CRAN. Documentation and example workflows are available through the SeedMatchR GitHub page at https://github.com/tacazares/SeedMatchR.

Biologic drugs (therapeutic proteins or peptides) have become one of the most important therapeutic modalities over the past few decades. Drug-induced immunogenicity is a significant concern as it may affect safety, tolerability, and efficacy. With more sensitive and drug-tolerant screening assays in use today, reliable estimation of anti-drug-antibody (ADA) titer has become more important for understanding clinically relevant ADA levels. Titer is commonly defined as the dilution factor resulting in an assay signal equal to a pre-specified cut point factor. Given its influence on the resulting titer precision, the choice of a titer cut point factor warrants careful consideration. In this paper, we discuss the theoretical dilution model, investigate how titer variability depends on the cut point factor and propose a standardized cut point factor to increase precision of titer estimates. Additionally, we demonstrate that non-linear regression-based titer estimation provides both improved precision and implementation efficiency relative to commonly used estimation approaches.

As part of the non-clinical safety package characterizing bamlanivimab (SARS-CoV-2 neutralizing monoclonal antibody), the risk profile for antibody-dependent enhancement of infection (ADE) was evaluated in vitro and in an African green monkey (AGM) model of COVID-19. In vitro ADE assays in primary human macrophage, Raji, or THP-1 cells were used to evaluate enhancement of viral infection. Bamlanivimab binding to C1q, FcR, and cell-based effector activity was also assessed. In AGMs, the impact of bamlanivimab pretreatment on viral loads and clinical and histological pathology was assessed to evaluate enhanced SARS-CoV-2 replication or pathology. Bamlanivimab did not increase viral replication in vitro, despite a demonstrated effector function. In vivo, no significant differences were found among the AGM groups for weight, temperature, or food intake. Treatment with bamlanivimab reduced viral loads in nasal and oral swabs and BAL fluid relative to control groups. Viral antigen was not detected in lung tissue from animals treated with the highest dose of bamlanivimab. Bamlanivimab did not induce ADE of SARS-CoV-2 infection in vitro or in an AGM model of infection at any dose evaluated. The findings suggest that high-affinity monoclonal antibodies pose a low risk of mediating ADE in patients and support their safety profile as a treatment of COVID-19 disease.

INTRODUCTION: Mirikizumab, an anti-interleukin-23p19 monoclonal antibody, demonstrated efficacy in phase 2 and 3 randomized clinical trials of patients with moderate-to-severe ulcerative colitis (UC). Previous results have shown that 12 weeks of mirikizumab treatment downregulated transcripts associated with UC disease activity and tumor necrosis factor inhibitor resistance. We assessed week-52 gene expression from week-12 responders receiving mirikizumab or placebo. METHODS: In the phase 2 AMAC study (NCT02589665), mirikizumab-treated patients achieving week-12 clinical response were rerandomized to mirikizumab 200 mg subcutaneous every 4 or 12 weeks through week 52 (N = 31). Week-12 placebo responders continued placebo through week 52 (N = 7). The limma R package clustered transcript changes in colonic mucosa biopsies from baseline to week 12 into differentially expressed genes (DEGs). Among DEGs, similarly expressed genes (DEGSEGs) maintaining week-12 expression through week 52 were identified. RESULTS: Of 89 DEGSEGs, 63 (70.8%) were present only in mirikizumab induction responders, 5 (5.6%) in placebo responders, and 21 (23.6%) in both. Week-12 magnitudes and week-52 consistency of transcript changes were greater in mirikizumab than in placebo responders (log2FC > 1). DEGSEG clusters (from 84 DEGSEGs identified in mirikizumab and mirikizumab/placebo responders) correlated to modified Mayo score (26/84 with Pearson correlation coefficient [PCC] >0.5) and Robarts Histopathology Index (55/84 with PCC >0.5), sustained through week 52. DISCUSSION: Mirikizumab responders had broader, more sustained transcriptional changes of greater magnitudes at week 52 vs placebo. Mirikizumab responder DEGSEGs suggest a distinct molecular healing pathway associated with mirikizumab interleukin-23 inhibition. The cluster's correlation with disease activity illustrates relationships between clinical, endoscopic, and molecular healing in UC.

INTRODUCTION:Mirikizumab, a monoclonal antibody targeting the p19 subunit of interleukin (IL)-23, demonstrated efficacy and was well-tolerated in a phase 2 randomized clinical trial in patients with moderate-to-severe ulcerative colitis (UC) (NCT02589665). We explored gene expression changes in colonic tissue from study patients and their association with clinical outcomes. METHODS:Patients were randomized to receive intravenous placebo or 3 mirikizumab induction doses. Patient biopsies were collected at baseline and week 12, and differential gene expression was measured using a microarray platform and compared in all treatment groups to determine differential expression values between baseline and week 12. RESULTS:The greatest improvement in clinical outcomes and placebo-adjusted change from baseline in transcripts at week 12 was observed in the 200 mg mirikizumab group. Transcripts significantly modified by mirikizumab correlate with key UC disease activity indices (modified Mayo score, Geboes score, and Robarts Histopathology Index) and include MMP1, MMP3, S100A8, and IL1β. Changes in transcripts associated with increased disease activity were decreased after 12 weeks of mirikizumab treatment. Mirikizumab treatment affected transcripts associated with resistance to current therapies, including IL-1β, OSMR, FCGR3A and FCGR3B, and CXCL6, suggesting that anti-IL23p19 therapy modulates biological pathways involved in resistance to antitumor necrosis factor and Janus kinase inhibitors. DISCUSSION:This is the first large-scale gene expression study of inflamed mucosa from patients with UC treated with anti-IL23p19 therapy. These results provide molecular evidence for mucosal healing from an extensive survey of changes in transcripts that improve our understanding of the molecular effects of IL-23p19 inhibition in UC.

Background Based on interim analyses and modeling data, lower doses of bamlanivimab and etesevimab together (700/1400 mg) were investigated to determine optimal dose and expand availability of treatment. Methods This Phase 3 portion of the BLAZE-1 trial characterized the effect of bamlanivimab with etesevimab on overall patient clinical status and virologic outcomes in ambulatory patients >= 12 years old, with mild-to-moderate coronavirus disease 2019 (COVID-19), and >= 1 risk factor for progressing to severe COVID-19 and/or hospitalization. Bamlanivimab and etesevimab together (700/1400 mg) or placebo were infused intravenously within 3 days of patients' first positive COVID-19 test. Results In total, 769 patients were infused (median age [range]; 56.0 years [12, 93], 30.3% of patients >= 65 years of age and median duration of symptoms; 4 days). By day 29, 4/511 patients (0.8%) in the antibody treatment group had a COVID-19-related hospitalization or any-cause death, as compared with 15/258 patients (5.8%) in the placebo group (Delta[95% confidence interval {CI}]=-5.0 [-8.0, -2.1], P <.001). No deaths occurred in the bamlanivimab and etesevimab group compared with 4 deaths (all COVID-19-related) in the placebo group. Patients receiving antibody treatment had a greater mean reduction in viral load from baseline to Day 7 (Delta[95% CI]=-0.99 [-1.33, -.66], P <.0001) compared with those receiving placebo. Persistently high viral load at Day 7 correlated with COVID-19-related hospitalization or any-cause death by Day 29 in all BLAZE-1 cohorts investigated. Conclusions These data support the use of bamlanivimab and etesevimab (700/1400 mg) for ambulatory patients at high risk for severe COVID-19. Evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants will require continued monitoring to determine the applicability of this treatment. Clinical Trials Registration NCT04427501. Bamlanivimab and etesevimab together (700 mg plus 1400 mg) reduced coronavirus disease 2019 (COVID-19)-related hospitalizations and viral load in patients with mild-to-moderate COVID-19, with persistently high viral load correlating with COVID-19-related hospitalizations or any-cause death.

Abstract Background We have previously shown that treatment with mirikizumab (miri), a p19-directed IL-23 antibody, significantly downregulates inflammatory genes associated with disease activity and upregulates genes expressing epithelial transporter proteins in colonic tissue in patients with ulcerative colitis (UC). Here we explored the correlation between the expression of colonic mucosa genes and stool frequency (SF), a symptom reflective of disease activity, during the 12-week induction period of a Phase 2 study of patients with moderately to severely active UC (NCT02589665). Methods Patients were randomised 1:1:1:1 to receive intravenous placebo (PBO), miri 50mg or 200mg with possibility of exposure-based dose increases, or fixed miri 600mg every 4 weeks for 12 weeks. SF was reported daily by patients and transformed on a 4-level ordinal scale [0–3] representing increased SF above their normal or healthy baseline (BL). Patient colonic biopsies (PBO N=58, miri 50mg N=52, 200mg N=51, 600mg N=54) were collected at BL and Week (W)12, and gene expression measured using an Affymetrix HTA2.0 microarray workflow. BL and W12 gene expression or SF values were pooled and associations identified based on non-parametric Kendall’s tau. Pathway analysis (Hallmark and Reactome) of correlated genes was performed using over-representation analysis. p values of enrichment were determined by hypergeometric distribution test and adjusted for multi-testing with Benjamini-Hochberg procedure. Differential gene expression after miri treatment was determined by paired t-test comparing expression levels at BL and at W12 using data from the 200mg treatment group. Results A total of 267 genes were correlated with SF (|tau| >0.3 and qval <0.001). Of these, 212 were positively correlated (high expression associated with high SF) and 55 were negatively correlated (high expression associated with low SF). The 212 transcripts that were positively correlated with SF were uniformly and consistently downregulated with miri treatment, while the 55 transcripts that negatively correlated with SF, were consistently upregulated with miri treatment (Table 1). Biological pathways significantly associated with the miri-responsive transcripts that correlated with SF included inflammatory response, extracellular matrix dysregulation, neutrophil degranulation and cytokine signaling pathways, especially TNF and IL6 pathways (Table 2). Conclusion This is the first study to identify colon-based transcripts that correlate with a clinical disease activity measure, stool frequency, and it demonstrates that treatment with miri may upregulate genes associated with normalization of SF and down regulate genes associated with inflammation in colonic tissue samples of patients with UC.

Background A thorough understanding of a patient’s inflammatory response to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection is crucial to discerning the associated, underlying immunological processes and to the selection and implementation of treatment strategies. Defining peripheral blood biomarkers relevant to SARS-CoV-2 infection is fundamental to detecting and monitoring this systemic disease. This safety-focused study aims to monitor and characterize the immune response to SARS-CoV-2 infection via analysis of peripheral blood and nasopharyngeal swab samples obtained from patients hospitalized with Coronavirus disease 2019 (COVID-19), in the presence or absence of bamlanivimab treatment. Methods 23 patients hospitalized with COVID-19 were randomized to receive a single dose of the neutralizing monoclonal antibody, bamlanivimab (700 mg, 2800 mg or 7000 mg) or placebo, at study initiation (Clinical Trial; NCT04411628). Serum samples and nasopharyngeal swabs were collected at multiple time points over 1 month. A Proximity Extension Array was used to detect inflammatory profiles from protein biomarkers in the serum of hospitalized COVID-19 patients relative to age/sex-matched healthy controls. RNA sequencing was performed on nasopharyngeal swabs. A Luminex serology assay and Elecsys® Anti-SARS-CoV-2 immunoassay were used to detect endogenous antibody formation and to monitor seroconversion in each cohort over time. A mixed model for repeated measures approach was used to analyze changes in serology and serum proteins over time. Results Levels of IL-6, CXCL10, CXCL11, IFNγ and MCP-3 were > fourfold higher in the serum of patients with COVID-19 versus healthy controls and linked with observations of inflammatory and viral-induced interferon response genes detected in nasopharyngeal swab samples from the same patients. While IgA and IgM titers peaked around 7 days post-dose, IgG titers remained high, even after 28 days. Changes in biomarkers over time were not significantly different between the bamlanivimab and placebo groups. Conclusions Similarities observed between nasopharyngeal gene expression patterns and peripheral blood biomarker profiles reveal a connection between the circulation and processes in the nasopharyngeal cavity, reinforcing the potential utility of systemic blood biomarker profiling for therapeutic monitoring of patient response. Serological antibody responses in patients correlated closely with reductions in the COVID-19 inflammatory protein biomarker signature. Bamlanivimab did not affect the biomarker dynamics in this hospitalized patient population.

As the coronavirus disease 2019 (COVID-19) pandemic evolves and vaccine rollout progresses, the availability and demand for monoclonal antibodies for the prevention and treatment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are also accelerating. This longitudinal serological study evaluated the magnitude and potency of the endogenous antibody response to COVID-19 vaccination in participants who first received a COVID-19 monoclonal antibody in a prevention study. Over the course of 6 months, serum samples were collected from a population of nursing home residents and staff enrolled in a clinical trial who were randomized to either bamlanivimab treatment or placebo. In an unplanned component of this trial, a subset of these participants was subsequently fully vaccinated with two doses of either SpikeVax (Moderna) or Comirnaty (BioNTech/Pfizer) COVID-19 mRNA vaccines. This post hoc analysis assessed the immune response to vaccination for 135 participants without prior SARS-CoV-2 infection. Antibody titers and potency were assessed using three assays against SARS-CoV-2 proteins that bamlanivimab does not efficiently bind to, thereby reflecting the endogenous antibody response. All bamlanivimab and placebo recipients mounted a robust immune response to full COVID-19 vaccination, irrespective of age, risk category, and vaccine type with any observed differences of uncertain clinical importance. These findings are pertinent for informing public health policy with results that suggest that the benefit of receiving COVID-19 vaccination at the earliest opportunity outweighs the minimal effect on the endogenous immune response due to prior prophylactic COVID-19 monoclonal antibody infusion.