Multi-omics profiling identifies IL-13 signaling as a key mediator in Dupilumab-associated severe corneal injury

Multi-omics profiling identifies IL-13 signaling as a key mediator in Dupilumab-associated severe corneal injury | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Multi-omics profiling identifies IL-13 signaling as a key mediator in Dupilumab-associated severe corneal injury Yi-bo Wang, Yuan-hao Li, Xiu-fen Liu, Xue-jun Wang, Zi-han Tang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9212855/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective To explore the epidemiological profile of Dupilumab-associated severe corneal injury (DASCI) using large-scale real-world evidence, and to investigate its underlying molecular mechanisms through integrated single-cell transcriptomic and network analysis. Methods A retrospective pharmacovigilance analysis focusing on Dupilumab was carried out utilizing the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) database, covering data from first quarter of 2022 to the third quarter of 2025 (Q1 2022 to Q3 2025). A disproportionality analysis was conducted to quantify safety signals using the Reporting Odds Ratio (ROR) and Information Component (IC), with Upadacitinib and Tralokinumab serving as active comparators to strengthen the findings. The molecular mechanisms underlying Dupilumab's effects were investigated by performing single-cell RNA sequencing on human ocular surface cells, supplemented by protein-protein interaction (PPI) network analysis and Gene Ontology (GO) enrichment analysis. Results A total of 817 cases of DASCI identified from Q1 2022 to Q3 2025 exhibited a distinct epidemiological profile, characterized by an upward temporal trend, female predominance, and peak incidence among working-age and middle-aged adults. Severity assessment indicated that the majority of reported cases (74.4%) were classified as "medically significant," while an additional 19.7% required hospitalization. Time-to-event analysis revealed rapid disease progression, with median times of 38 days from initiation to mild conjunctivitis and 57 days to severe corneal damage. Disproportionality analysis confirmed a drug-specific risk signal for Dupilumab, which was absent for Upadacitinib; in contrast, Tralokinumab exhibited an even stronger signal. Single-cell transcriptomics delineated a compartmentalized IL-13 signaling network across the human ocular surface, highlighting critical roles of limbal epithelial cells, goblet cells, and macrophages. Subsequent PPI and GO enrichment analyses further established signal transducer and activator of transcription 6 (STAT6) as the central hub of this network. Furthermore, immunological reprogramming toward a Th2-to-Th1 shift may contribute to DASCI pathogenesis. Conclusion Dupilumab constitutes a significant risk factor for severe corneal injury, characterized by distinct pharmacoepidemiological and rapid progression features. Mechanistically, DASCI is triggered by IL-13 pathway blockade, mediated through a STAT6-centered network, and driven by a pathological Th2-to-Th1 shift. Dupilumab corneal injury pharmacovigilance IL13 signaling pathway homeostasis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Dupilumab, a fully human monoclonal antibody specifically targeting the interleukin-4 receptor alpha (IL-4Rα) subunit, has profoundly transformed the therapeutic landscape for a variety of type 2 inflammatory disorders through its simultaneous inhibition of interleukin-4 (IL-4) and interleukin-13 (IL-13) signaling pathways[ 1 , 2 ]. Despite its established efficacy across diverse indications, Dupilumab is frequently associated with a distinct profile of ocular surface diseases (OSD)[ 3 , 4 ]. Although the majority of these ocular adverse events are typically mild and manageable, accumulating real-world evidence indicates that a subset of patients progresses to severe, sight-threatening structural injuries, encompassing corneal stromal melting, perforation, and limbal stem cell deficiency (LSCD). In contrast to the reversible nature of drug-induced conjunctivitis, LSCD represents a profound disruption of corneal epithelial homeostasis, characterized by irreversible attrition of limbal epithelial progenitor cells and a potential progression to chronic visual impairment[ 5 , 6 ]. The progression from transient ocular surface inflammation to irreversible tissue destruction represents a critical transition in disease pathogenesis, indicating a fundamental and often sustained disruption of ocular surface homeostasis. Under physiological conditions, this homeostasis is maintained by a delicate balance of tear film dynamics, epithelial barrier integrity, and immunoregulatory mechanisms[ 7 , 8 ]. However, persistent inflammatory insults can overwhelm these compensatory systems, leading to pathological dysregulation[ 9 , 10 ]. The molecular drivers underlying this harmful progression are multifaceted. Chronic inflammation, driven by pro-inflammatory cytokines, can directly activate tissue-degrading pathways, particularly the matrix metalloproteinase (MMP) cascade, which disrupts the extracellular matrix and impairs tissue integrity[ 11 , 12 ]. Within the context of targeted biologic therapies, this mechanistic framework raises pivotal safety questions. Although pharmacovigilance studies have characterized the safety profile for the IL-4/IL-13 inhibitor Dupilumab[ 13 – 16 ], a key unresolved question is whether these severe ocular events are attributable merely to the underlying systemic type 2 inflammatory burden or directly result from the pharmacological blockade of specific cytokines, which may lead to a fundamental disruption in immune homeostasis. Additionally, the relative contributions of IL-4 and IL-13 inhibition to this pathology have not been fully elucidated. As the therapeutic landscape expands, clarifying these pathway-specific ocular risks becomes increasingly urgent. To address these gaps, this study employed a multi-dimensional approach to systematically elucidate the epidemiological characteristics, temporal progression, and molecular mechanisms of DASCI, with the aim to accurately define the Dupilumab-specific toxicity risk and provide an evidence-based foundation for developing targeted management strategies. 2. Methods 2.1. Data source and pharmacovigilance analysis 2.1.1. Data source and processing This retrospective pharmacovigilance study utilized data from FAERS. Specifically, quarterly ASCII data files from Q1 2022 to Q3 2025 were extracted. Data from the fourth quarter of 2025 were excluded to avoid potential reporting delays and ensure data maturity for the most recent reporting quarter. Adverse events were coded using the Medical Dictionary for Regulatory Activities (MedDRA) terminology. To ensure data integrity, a standardized workflow (Fig. 1 ) was followed, encompassing data extraction, cleaning (including deduplication), and case selection. Duplicate reports were removed by retaining the most recent submission for each unique CASEID (prioritizing the latest FDA_DT). The final dataset comprised cases where “DUPILUMAB” was explicitly listed as the Primary Suspectdrug. Given that the data analyzed in this study were fully anonymized and publicly accessible, the study was considered exempt from Institutional Review Board (IRB) approval in accordance with institutional guidelines. 2.1.2. Case definition for severe corneal injury A dual-filter strategy was applied to identify cases of severe corneal injury (Fig. 1 ). First, reports with highly specific MedDRA Preferred Terms (PTs) indicating structural damage—Corneal perforation, Corneal ulcer, and LSCD—were included directly (Route A). Second, for reports with broader, non-specific ocular surface PTs (Keratitis, Dry eye), inclusion was conditional upon association with a serious outcome, defined as hospitalization (HO), disability (DS), life-threatening (LT), or other medically important condition (OT) in the FAERS outcome file (Route B). This yielded the final study population (n = 817). Identical criteria were applied to extract comparator cases for Upadacitinib, Tralokinumab, Methotrexate, and Omalizumab. 2.1.3. Statistical analysis Disproportionality analyses were conducted using the full FAERS database as the background. The Reporting Odds Ratio (ROR) with 95% confidence intervals (95% CI) and the Bayesian Information Component (IC) with the lower limit of 95% credibility interval (IC025) were calculated. A significant safety signal was defined as a lower 95% CI of the ROR > 1.0 and/or an IC025 > 0. All analyses were performed using R software (version 4.5.1). 2.2. Exploration of molecular mechanisms 2.2.1. Single-cell RNA sequencing data analysis Publicly available single-cell RNA sequencing (scRNA-seq) data of the human ocular surface were obtained from the Broad Institute Single Cell Portal. Cell populations of interest-including corneal epithelial, limbal epithelial, goblet cells, and macrophages-were analyzed for the expression of key components within the IL-4/IL-13 signaling axis (IL4, IL13, IL4R, IL13RA1). Expression patterns were visualized to identify putative cellular sources and targets. 2.2.2. Network and functional enrichment analysis A PPI network was constructed using the STRING database (v12.0), focusing on core components of the IL-13 pathway (e.g., IL4R and IL13RA1) and downstream effectors implicated in corneal integrity. Interactions with a confidence score > 0.400 were retained. Subsequently, GO enrichment analysis for Biological Processes was performed on the network genes using the STRING platform, with a False Discovery Rate (FDR) < 0.05 considered significant. 3. Results 3.1. Epidemiological profile of DASCI A total of 817 cases of DASCI were identified from Q1 2022 to Q3 2025 (Table 1 ). The annual case number showed a consistent upward trend, paralleling the rise in Dupilumab prescriptions, and stabilized at a high level in 2024 and 2025 (Fig. 2 A). Geographically, the majority of reports originated from the United States (n = 644), accounting for the largest proportion of the dataset (Fig. 2 B). A notable female predominance was observed with females comprising 65.0% of the cases, compared to 31.6% for males, resulting in an approximate 2:1 female-to-male ratio (Table 1 ). Demographically, the affected population mainly consisted of working-age and middle-aged adults (Fig. 2 C). Table 1 Baseline demographic and clinical characteristics of patients with DASCI (n = 817) Characteristic Value Total No. of cases 817 Sex Male 258 (31.6%) Female 531 (65.0%) Age (years) Mean (SD) 54.3 (18.3) Median (min-max) 57.0 (2–97) Missing data 156 (19.1%) Reporting year 2022 167 (20.4%) 2023 159 (19.5%) 2024 247 (30.2%) 2025 244 (29.9%) Serious outcomes (overlapping) Other medically important (OT) 717 (87.8%) Hospitalization (HO) 165 (20.2%) Disability (DS) 41 (5.0%) Life-threatening (LT) 2 (0.2%) Death (DE) 5 (0.6%) 3.2. Severity distribution of DASCI​ To ensure accurate statistical analysis by eliminating double counting and ambiguous categorization, we employed a mutually exclusive classification framework, assigning each patient to a single, most severe clinical endpoint. This method is essentially different from the overlapping event counting presented in Table 1 . As shown in Fig. 3 A, the majority of severe corneal injuries were categorized as "other medically important" (74.4%), followed by those requiring hospitalization (19.7%), reflecting a 3.8-fold difference between the two categories. This distribution pattern suggests that the primary clinical burden associated with Dupilumab arises from severe, sight-threatening diseases that are predominantly managed in high-urgent outpatient settings rather than through routine inpatient admissions. A detailed analysis of the critical (severe) cases further revealed that disability was the most common severe outcome (n = 41, 85.4% of critical cases), followed by death (n = 5, 10.4%) and life-threatening events (n = 2, 4.2%) (Fig. 3 B). 3.3. Temporal association between mild conjunctivitis and severe corneal damage in Dupilumab-treated patients Since drug-induced ocular toxicity generally initiates as an inflammatory process, we conducted a comparison of the time to onset between Dupilumab-associated mild conjunctivitis and severe structural damage. Both conditions were concentrated in the early treatment phase, with the median time to onset being 38 days for mild conjunctivitis and 57 days for severe structural damage (Fig. 4 A). This relatively narrow 19-day interval defines a clinically significant window, indicating that inadequately controlled surface inflammation can advance to tissue destruction within approximately three weeks. The early risk profile was further validated by cumulative incidence curves (Fig. 4 B). Both groups demonstrated a sharp initial increase within the first 100 days, indicating rapid risk accumulation shortly after treatment initiation. Notably, the trajectory of severe structural damage closely paralleled that of mild conjunctivitis, indicating a strong temporal association between the two groups. 3.4. Verification of the drug-specific nature of DASCI To characterize the drug-specific toxicity profile of Dupilumab, we performed a comparative pharmacovigilance analysis involving five therapeutic agents (Fig. 5 , Table 2 ). Dupilumab demonstrated a toxicity signal with statistical significance. In contrast, Upadacitinib -a JAK inhibitor- exhibited no significant safety signal, thereby dissociating the observed toxicity from the background disease burden. Notably, Tralokinumab, a selective IL-13 inhibitor, displayed an even stronger toxicity signal. Methodologically, assay validity was confirmed using external benchmarks: Methotrexate (a positive control) yielded a high ROR, demonstrating analytical sensitivity, whereas Omalizumab (a biologic negative control) showed no signal, ruling out non-specific immunogenic responses to monoclonal antibody therapy. Table 2 Signals of ocular toxicity associated with biologics and small molecule drugs Drug n_Cases n_Exposed ROR CI_Lower CI_Upper Signal Dupilumab 817 299250 1.79 1.66 1.92 YES Upadacitinib 99 54726 1.14 0.93 1.39 NO Tralokinumab 14 3971 2.22 1.31 3.75 YES Methotrexate 249 46083 3.47 3.06 3.94 YES Omalizumab 48 26471 1.14 0.86 1.51 NO n_Cases: number of cases; n_Exposed: number of exposed; ROR: reporting odds ratio; CI_Lowe: lower limit of confidence interval; CI_Upper: Upper limit of confidence interval. 3.5. Integrated multi-omics profiling from single-cell transcriptomics to network analysis Single-cell transcriptomic mapping of the human ocular surface IL-4/IL-13 axis revealed distinct cellular sources for its ligands and receptors (Fig. 6 A). IL-13 is primarily produced by limbal epithelial superficial cells and goblet cells, whereas IL-4 is predominantly expressed by trabecular meshwork fibroblasts. Receptor analysis identified choriocapillaris venous endothelial cells and macrophages as the primary sites of IL-4R and IL-13RA1 expression, respectively. Notably, macrophages also showed strong IL-4R co-expression. Additionally, all ligands and receptors were also expressed at variable levels across other corneal and limbal epithelial cells. PPI network analysis using STRING identified STAT6 as the central hub of the IL-13 signaling axis (Fig. 6 B). The analysis revealed that STAT6 integrates upstream signals from the ligand-receptor complex and directly regulates key effector molecules, including mucin 5AC (MUC5AC), arginase-1 (ARG1), matrix metallopeptidase 9 (MMP9), and tight junction protein 1 (TJP1). Finally, GO enrichment analysis showed significant enrichment of pathways directly associated with Th2 immunity, including "interleukin-4-mediated signaling pathway" and "regulation of type 2 immune response". Notably, "T-helper 1 (Th1) cell differentiation" was also enriched (Fig. 6 C). 4. Discussion Our large-scale pharmacovigilance analysis of 817 DASCI cases identified between Q1 2022 and Q3 2025 revealed a strong temporal correlation between Dupilumab prescription volumes and adverse event reports. This temporal association suggests that the risk of DASCI is directly linked to drug exposure rather than a sporadic occurrence. Furthermore, DASCI is distinguished from typical degenerative corneal pathologies by a pronounced female predominance and a concentration of cases among working-age and middle-aged adults, in contrast to the elderly-predominant, non-sex-specific profile of the latter. This demographic profile implies an inherent, sex-based susceptibility, potentially mediated by sex hormone-regulated Th2 cytokine pathways—a mechanism supported by study showing that estrogen enhances, whereas androgens suppress, Th2-polarized immune responses[ 17 ]. We therefore hypothesize that the observed female predominance results from a more severe homeostatic disruption following IL-4/IL-13 pathway blockade, potentially due to a stronger baseline Th2 polarization in females which, upon inhibition, leads to a more pronounced immunological imbalance. One of the most clinically relevant observations of our study was the identification of a critical 19-day window between the onset of mild conjunctivitis (median, 38 days) and the development of severe structural damage (median, 57 days). This narrow interval supports the concept that DASCI represents a pathogenic continuum, wherein initial superficial inflammation triggers rapid barrier dysfunction, culminating in irreversible tissue damage. Consistent with this, Phylactou et al. demonstrate that superficial ocular inflammation can induce rapid barrier disruption and irreversible corneal structural alterations[ 18 ]. This finding reinforces the paradigm of a rapid and irreversible disease course in DASCI. Our comparative safety signal analysis reveals that Dupilumab, which blocks both IL-4 and IL-13 signaling, exhibits a significant safety signal. In contrast, Upadacitinib, a JAK inhibitor used in the same patient population, does not show a safety signal. The absence of a safety signal for Upadacitinib suggests that the underlying disease burden is not the primary driver of these severe corneal events. Notably, the selective IL-13 inhibitor Tralokinumab exhibits an even stronger toxicity signal, reinforcing the hypothesis that IL-13 blockade, rather than IL-4 inhibition, is more central to the pathogenesis. This observation is consistent with prior clinical observations that IL-13 plays a pivotal role in ocular surface homeostasis[ 19 ]. Furthermore, our single-cell transcriptomic analysis of the human ocular surface provides a cellular basis for this drug-specific effect, challenging the traditional view that IL-13 originates primarily from immune infiltrates[ 20 ]. We identified a dual-source expression pattern in which goblet cells and limbal epithelial cells co-express IL13 and its receptors (IL4R, IL13RA1). This finding suggests the existence of a pivotal IL-13-mediated autocrine/paracrine signaling loop essential for goblet cell-mediated maintenance of ocular surface integrity. This concept is well-supported, as IL-13 is known to be essential for the maintenance and function of goblet cells, which are the key producers of mucins for barrier integrity, and its inhibition leads to both goblet cell loss and barrier dysfunction [ 21 , 22 ]. The limbal region hosts the stem cell niche critical for corneal epithelial regeneration [ 23 ]. Our analysis further identified IL-13 and its receptors are broadly expressed in key cell types within this region, including limbal epithelial superficial, basal, and wing cells. This spatial organization implies a critical IL-13 signaling network within the limbal niche that is essential for epithelial renewal and barrier function. Consequently, pharmacological blockade of this pathway by Dupilumab would be expected to disrupt these homeostatic processes, impairing limbal epithelial regeneration and corneal barrier integrity. Mechanistically, our PPI network analysis identified STAT6 as a central hub in the downstream network of IL-13 signaling. It regulates the transcription of MUC5AC while also coordinating the expression of key effectors such as MMP9 and TJP1, underscoring the essential role of the IL-13/STAT6 pathway in maintaining ocular surface integrity. The IL-13/STAT6 pathway is reported to play a pivotal role in supporting limbal stem cell proliferation and differentiation, thereby sustaining the limbal niche[ 24 ]. Conversely, disruption of IL-13/STAT6 signaling unravels this coordinated network, leading to goblet cell dysfunction, reduced mucin production, and compromised tear film stability-a well-documented early manifestation of Dupilumab therapy[ 14 ]. Furthermore, dysregulated MMP9 expression likely drives extracellular matrix degradation, whereas disrupted TJP1 expression impairs barrier integrity, collectively facilitating the progression from inflammation to tissue damage[ 25 , 26 ]. Our GO analysis revealed co-enrichment in both Th2 and Th1 differentiation pathways. This finding implies a potential immunological reprogramming within the ocular microenvironment under DASCI conditions, which is consistent with studies indicating that while IL-13 blockade suppresses Th2 responses, it can elicit a compensatory shift toward Th1 polarization. Consequently, this shift could amplify pro-inflammatory cascades and further disrupt the ocular surface[ 4 ]. Furthermore, our STRING network analysis demonstrated that STAT6 regulates the expression of the M2 macrophage marker ARG1[ 27 ]. Under physiological conditions, the IL-13/STAT6 signaling axis is critical for promoting macrophage polarization toward a tissue-reparative (M2) phenotype. Notably, macrophage-derived IL-13, together with the subsequent M2 polarization, can suppress the activation and function of Th1 cells[ 28 ]. Our single-cell data revealed a distinctly strong co-expression of IL-4R and IL13RA1 in macrophages compared to other ocular surface cells, identifying them as the primary target of Dupilumab. We hypothesize that IL-13 pathway blockade by Dupilumab skews macrophage polarization towards a pro-inflammatory (M1) phenotype. This phenotypic shift not only compromises tissue repair capacity but also promotes the substantial release of proteolytic enzymes such as MMP9[ 29 , 30 ]. Collectively, our study unveils a pathophysiological cascade underlying DASCI, centered on the disruption of a critical IL-13 autocrine/paracrine signaling loop. This cascade evolves through a multistep process: (1) goblet cell dysfunction and subsequent mucin loss; (2) limbal stem cell niche damage and barrier failure; and (3) immune dysregulation characterized by a pro-inflammatory shift toward Th1 immunity, which ultimately drives irreversible corneal damage. This model establishes a foundational framework for DASCI, highlighting the critical need for early detection and mechanism-based interventions in patients undergoing Dupilumab treatment. Declarations CRediT authorship contribution statement Yi-bo Wang: Writing - original draft, Data curation, Formal analysis. Yuan-hao Li: Data curation. Xiu-fen Liu: Formal analysis. Xue-jun Wang: Formal analysis. Zi-han Tang: Data curation, Methodology. Cheng-wei Lu: Supervision, Writing - review & editing, Methodology, Conceptualization. Funding This research was funded by the National Natural Science Foundation of China under Grant (grant number 82471045). Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Data Availability This retrospective study utilized publicly accessible data from the FAERS, specifically individual case safety reports (ICSRs) regarding ADEs. Given that the research relied solely on secondary data analysis without direct human subject involvement, institutional review board (IRB) or ethical approval was waived. The dataset can be accessed via the FAERS Public Dashboard. References Le Floc'h A, Allinne J, Nagashima K, et al. Dual blockade of IL-4 and IL-13 with dupilumab, an IL-4Rα antibody, is required to broadly inhibit type 2 inflammation. Allergy 2020;75:1188-1204. McCann MR, Kosloski MP, Xu C, et al. Dupilumab: Mechanism of action, clinical, and translational science. Clin Transl Sci 2024;17:e13899. Chen J, Li H, Zhang H, et al. 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Innate immune regulation by STAT-mediated transcriptional mechanisms. Immunol Rev 2014;261:84-101. Eapen MS, Hansbro PM, McAlinden K, et al. Abnormal M1/M2 macrophage phenotype profiles in the small airway wall and lumen in smokers and chronic obstructive pulmonary disease (COPD). Sci Rep 2017;7:13392. Harb H, Chatila TA. Mechanisms of Dupilumab. Clin Exp Allergy 2020;50:5-14. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9212855","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":612518821,"identity":"ff015005-d742-4a3e-9ca8-b9892fa22b70","order_by":0,"name":"Yi-bo Wang","email":"","orcid":"","institution":"the First Hospital of Jilin University","correspondingAuthor":false,"prefix":"","firstName":"Yi-bo","middleName":"","lastName":"Wang","suffix":""},{"id":612518822,"identity":"e2ae046d-ea33-425e-992e-704b5fcaba08","order_by":1,"name":"Yuan-hao Li","email":"","orcid":"","institution":"the First Hospital of Jilin University","correspondingAuthor":false,"prefix":"","firstName":"Yuan-hao","middleName":"","lastName":"Li","suffix":""},{"id":612518823,"identity":"3e2d59ed-79cf-4269-b920-1cb133659320","order_by":2,"name":"Xiu-fen Liu","email":"","orcid":"","institution":"the First Hospital of Jilin University","correspondingAuthor":false,"prefix":"","firstName":"Xiu-fen","middleName":"","lastName":"Liu","suffix":""},{"id":612518824,"identity":"6256a198-83b1-4c88-9b59-97dda34698b4","order_by":3,"name":"Xue-jun Wang","email":"","orcid":"","institution":"the First Hospital of Jilin University","correspondingAuthor":false,"prefix":"","firstName":"Xue-jun","middleName":"","lastName":"Wang","suffix":""},{"id":612518825,"identity":"def8831c-f617-49a1-a70d-c87abb38c194","order_by":4,"name":"Zi-han Tang","email":"","orcid":"","institution":"the First Hospital of Jilin University","correspondingAuthor":false,"prefix":"","firstName":"Zi-han","middleName":"","lastName":"Tang","suffix":""},{"id":612518826,"identity":"a31fd22b-2686-405b-a8aa-50d211a62a8a","order_by":5,"name":"Cheng-wei Lu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6UlEQVRIiWNgGAWjYBACPiBmZjBgYOBnZmx8IFEAEkvAr4UNpkWyvfmwgYQB0VqAwODMsTQJBqK0sJ8x/FxQcEdeckaOWYWFwWEGfvYcA4afO/Bo4ckxlp5h8MywXyLH7IYEUItkzxsDxt4zeLRI8G5j5jE4zDhzBlSLwY0cA2bGNsJa7DfcyDErAGmxJ1ZL4gag9xnAtkgQ0sKT/1kaqCV5JjCQJSQM0nkkzjwrONiLRws/+7HEzzx/Dtv2A6Pys0SFtRx/e/LGBz/xaEEBzBIMDDwgxgEiNTAwMH4gWukoGAWjYBSMJAAA22tJA8mrTp8AAAAASUVORK5CYII=","orcid":"","institution":"the First Hospital of Jilin University","correspondingAuthor":true,"prefix":"","firstName":"Cheng-wei","middleName":"","lastName":"Lu","suffix":""}],"badges":[],"createdAt":"2026-03-24 13:54:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9212855/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9212855/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105621290,"identity":"a0f0d18f-ba25-4618-8979-4eaf6eac90c7","added_by":"auto","created_at":"2026-03-28 08:28:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":898776,"visible":true,"origin":"","legend":"\u003cp\u003eThe workflow of standardized data cleaning and processing. LSCD: limbal stem cell deficiency; HO: hospitalization, OT: other medically important condition; DS: disability; LT: life-threatening; ROR: reporting odds ratio; IC025: lower limit of 95% credibility interval.\u003c/p\u003e","description":"","filename":"fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-9212855/v1/6c43efa36d5a7faed935eb51.png"},{"id":105621293,"identity":"1354c3b1-fa9f-4b06-a0bd-d926758a2d61","added_by":"auto","created_at":"2026-03-28 08:28:49","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":419936,"visible":true,"origin":"","legend":"\u003cp\u003eEpidemiological profile of DASCI reports (Q1 2022 to Q3 2025). (A)​Temporal trend in annual case reports (red bars, left y-axis) in relation to dupilumab prescription volume (blue line, right y-axis). (B) Geographical distribution of reported cases. (C) Age and sex distribution of the affected population.\u003c/p\u003e","description":"","filename":"fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-9212855/v1/432a9f9013c27f104512a9dc.png"},{"id":105728202,"identity":"e5c88989-a499-4b77-8dfc-451ebbb0cbf3","added_by":"auto","created_at":"2026-03-30 11:10:52","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":350987,"visible":true,"origin":"","legend":"\u003cp\u003eSeverity distribution of DASCI cases. (A) Overall distribution by primary severity category. (B) Detailed composition of the severe cases.\u0026nbsp;\u003c/p\u003e","description":"","filename":"fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-9212855/v1/98d003992697387ea609dd1c.png"},{"id":105728396,"identity":"cf19a8f5-257e-4fbf-afda-f1e49e7e9816","added_by":"auto","created_at":"2026-03-30 11:11:42","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":121239,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal association between mild conjunctivitis and severe corneal damage in Dupilumab-treated patients. (A) The time-to-onset distribution. (B) Cumulative incidence curves.\u003c/p\u003e","description":"","filename":"fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-9212855/v1/1b5e8a9fdaaf11347dc7705d.png"},{"id":105728563,"identity":"2817f288-daa6-4140-b8f8-83e52254fdce","added_by":"auto","created_at":"2026-03-30 11:12:09","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":135317,"visible":true,"origin":"","legend":"\u003cp\u003e95% CI of ocular toxicity associated with biologics and small molecule drugs. ROR: reporting odds ratio; CI: confidence interval.\u003c/p\u003e","description":"","filename":"fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-9212855/v1/5606f1ae9e5e74512fe20b22.png"},{"id":105621292,"identity":"3a6ba65d-f043-4675-b888-86dcc9d499b9","added_by":"auto","created_at":"2026-03-28 08:28:49","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1495695,"visible":true,"origin":"","legend":"\u003cp\u003eMulti-omic profiling from single-cell transcriptomics to network analysis. (A) Single-cell transcriptomic analysis of the human ocular surface. (B) PPI network of the IL13 signaling pathway and associated molecules. (C) GO enrichment analysis of the differentially regulated gene set. IL-4: interleukin-4; IL-4R: interleukin-4 receptor; IL-13: interleukin-13; IL13-RA1: interleukin-13 receptor alpha 1; K: korneal (corneal); Epi: epithelial; Conj: conjunctival; TM: trabecular meshwork; CC: choriocapillaris; Fibro: fibroblast; Endo: endothelial cell; VenEndo: venous endothelial cell; min:minimum; max:maximum.\u003c/p\u003e","description":"","filename":"fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-9212855/v1/22dbc42cfe61a87da9931c3d.png"},{"id":106959880,"identity":"2ab1f6a7-d4d4-4755-980a-a4627f0627bb","added_by":"auto","created_at":"2026-04-15 09:16:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3954584,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9212855/v1/5c3e2e78-9559-40c2-8e01-32c1e0951125.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Multi-omics profiling identifies IL-13 signaling as a key mediator in Dupilumab-associated severe corneal injury","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eDupilumab, a fully human monoclonal antibody specifically targeting the interleukin-4 receptor alpha (IL-4Rα) subunit, has profoundly transformed the therapeutic landscape for a variety of type 2 inflammatory disorders through its simultaneous inhibition of interleukin-4 (IL-4) and interleukin-13 (IL-13) signaling pathways[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Despite its established efficacy across diverse indications, Dupilumab is frequently associated with a distinct profile of ocular surface diseases (OSD)[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Although the majority of these ocular adverse events are typically mild and manageable, accumulating real-world evidence indicates that a subset of patients progresses to severe, sight-threatening structural injuries, encompassing corneal stromal melting, perforation, and limbal stem cell deficiency (LSCD). In contrast to the reversible nature of drug-induced conjunctivitis, LSCD represents a profound disruption of corneal epithelial homeostasis, characterized by irreversible attrition of limbal epithelial progenitor cells and a potential progression to chronic visual impairment[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe progression from transient ocular surface inflammation to irreversible tissue destruction represents a critical transition in disease pathogenesis, indicating a fundamental and often sustained disruption of ocular surface homeostasis. Under physiological conditions, this homeostasis is maintained by a delicate balance of tear film dynamics, epithelial barrier integrity, and immunoregulatory mechanisms[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, persistent inflammatory insults can overwhelm these compensatory systems, leading to pathological dysregulation[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The molecular drivers underlying this harmful progression are multifaceted. Chronic inflammation, driven by pro-inflammatory cytokines, can directly activate tissue-degrading pathways, particularly the matrix metalloproteinase (MMP) cascade, which disrupts the extracellular matrix and impairs tissue integrity[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWithin the context of targeted biologic therapies, this mechanistic framework raises pivotal safety questions. Although pharmacovigilance studies have characterized the safety profile for the IL-4/IL-13 inhibitor Dupilumab[\u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], a key unresolved question is whether these severe ocular events are attributable merely to the underlying systemic type 2 inflammatory burden or directly result from the pharmacological blockade of specific cytokines, which may lead to a fundamental disruption in immune homeostasis. Additionally, the relative contributions of IL-4 and IL-13 inhibition to this pathology have not been fully elucidated. As the therapeutic landscape expands, clarifying these pathway-specific ocular risks becomes increasingly urgent. To address these gaps, this study employed a multi-dimensional approach to systematically elucidate the epidemiological characteristics, temporal progression, and molecular mechanisms of DASCI, with the aim to accurately define the Dupilumab-specific toxicity risk and provide an evidence-based foundation for developing targeted management strategies.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Data source and pharmacovigilance analysis\u003c/h2\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e2.1.1. Data source and processing\u003c/h2\u003e \u003cp\u003eThis retrospective pharmacovigilance study utilized data from FAERS. Specifically, quarterly ASCII data files from Q1 2022 to Q3 2025 were extracted. Data from the fourth quarter of 2025 were excluded to avoid potential reporting delays and ensure data maturity for the most recent reporting quarter. Adverse events were coded using the Medical Dictionary for Regulatory Activities (MedDRA) terminology. To ensure data integrity, a standardized workflow (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) was followed, encompassing data extraction, cleaning (including deduplication), and case selection. Duplicate reports were removed by retaining the most recent submission for each unique CASEID (prioritizing the latest FDA_DT). The final dataset comprised cases where \u0026ldquo;DUPILUMAB\u0026rdquo; was explicitly listed as the Primary Suspectdrug. Given that the data analyzed in this study were fully anonymized and publicly accessible, the study was considered exempt from Institutional Review Board (IRB) approval in accordance with institutional guidelines.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.1.2. Case definition for severe corneal injury\u003c/h2\u003e \u003cp\u003eA dual-filter strategy was applied to identify cases of severe corneal injury (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). First, reports with highly specific MedDRA Preferred Terms (PTs) indicating structural damage\u0026mdash;Corneal perforation, Corneal ulcer, and LSCD\u0026mdash;were included directly (Route A). Second, for reports with broader, non-specific ocular surface PTs (Keratitis, Dry eye), inclusion was conditional upon association with a serious outcome, defined as hospitalization (HO), disability (DS), life-threatening (LT), or other medically important condition (OT) in the FAERS outcome file (Route B). This yielded the final study population (n\u0026thinsp;=\u0026thinsp;817). Identical criteria were applied to extract comparator cases for Upadacitinib, Tralokinumab, Methotrexate, and Omalizumab.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.1.3. Statistical analysis\u003c/h2\u003e \u003cp\u003eDisproportionality analyses were conducted using the full FAERS database as the background. The Reporting Odds Ratio (ROR) with 95% confidence intervals (95% CI) and the Bayesian Information Component (IC) with the lower limit of 95% credibility interval (IC025) were calculated. A significant safety signal was defined as a lower 95% CI of the ROR\u0026thinsp;\u0026gt;\u0026thinsp;1.0 and/or an IC025\u0026thinsp;\u0026gt;\u0026thinsp;0. All analyses were performed using R software (version 4.5.1).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Exploration of molecular mechanisms\u003c/h2\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1. Single-cell RNA sequencing data analysis\u003c/h2\u003e \u003cp\u003ePublicly available single-cell RNA sequencing (scRNA-seq) data of the human ocular surface were obtained from the Broad Institute Single Cell Portal. Cell populations of interest-including corneal epithelial, limbal epithelial, goblet cells, and macrophages-were analyzed for the expression of key components within the IL-4/IL-13 signaling axis (IL4, IL13, IL4R, IL13RA1). Expression patterns were visualized to identify putative cellular sources and targets.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2. Network and functional enrichment analysis\u003c/h2\u003e \u003cp\u003eA PPI network was constructed using the STRING database (v12.0), focusing on core components of the IL-13 pathway (e.g., IL4R and IL13RA1) and downstream effectors implicated in corneal integrity. Interactions with a confidence score\u0026thinsp;\u0026gt;\u0026thinsp;0.400 were retained. Subsequently, GO enrichment analysis for Biological Processes was performed on the network genes using the STRING platform, with a False Discovery Rate (FDR)\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered significant.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Epidemiological profile of DASCI\u003c/h2\u003e \u003cp\u003eA total of 817 cases of DASCI were identified from Q1 2022 to Q3 2025 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The annual case number showed a consistent upward trend, paralleling the rise in Dupilumab prescriptions, and stabilized at a high level in 2024 and 2025 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Geographically, the majority of reports originated from the United States (n\u0026thinsp;=\u0026thinsp;644), accounting for the largest proportion of the dataset (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). A notable female predominance was observed with females comprising 65.0% of the cases, compared to 31.6% for males, resulting in an approximate 2:1 female-to-male ratio (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Demographically, the affected population mainly consisted of working-age and middle-aged adults (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline demographic and clinical characteristics of patients with DASCI (n\u0026thinsp;=\u0026thinsp;817)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal No. of cases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e817\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e258 (31.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e531 (65.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.3 (18.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian (min-max)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57.0 (2\u0026ndash;97)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e156 (19.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReporting year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e167 (20.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e159 (19.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e247 (30.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e244 (29.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerious outcomes (overlapping)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther medically important (OT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e717 (87.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitalization (HO)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e165 (20.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisability (DS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (5.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLife-threatening (LT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeath (DE)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (0.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Severity distribution of DASCI​\u003c/h2\u003e \u003cp\u003eTo ensure accurate statistical analysis by eliminating double counting and ambiguous categorization, we employed a mutually exclusive classification framework, assigning each patient to a single, most severe clinical endpoint. This method is essentially different from the overlapping event counting presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, the majority of severe corneal injuries were categorized as \"other medically important\" (74.4%), followed by those requiring hospitalization (19.7%), reflecting a 3.8-fold difference between the two categories. This distribution pattern suggests that the primary clinical burden associated with Dupilumab arises from severe, sight-threatening diseases that are predominantly managed in high-urgent outpatient settings rather than through routine inpatient admissions. A detailed analysis of the critical (severe) cases further revealed that disability was the most common severe outcome (n\u0026thinsp;=\u0026thinsp;41, 85.4% of critical cases), followed by death (n\u0026thinsp;=\u0026thinsp;5, 10.4%) and life-threatening events (n\u0026thinsp;=\u0026thinsp;2, 4.2%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Temporal association between mild conjunctivitis and severe corneal damage in Dupilumab-treated patients\u003c/h2\u003e \u003cp\u003eSince drug-induced ocular toxicity generally initiates as an inflammatory process, we conducted a comparison of the time to onset between Dupilumab-associated mild conjunctivitis and severe structural damage. Both conditions were concentrated in the early treatment phase, with the median time to onset being 38 days for mild conjunctivitis and 57 days for severe structural damage (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). This relatively narrow 19-day interval defines a clinically significant window, indicating that inadequately controlled surface inflammation can advance to tissue destruction within approximately three weeks. The early risk profile was further validated by cumulative incidence curves (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Both groups demonstrated a sharp initial increase within the first 100 days, indicating rapid risk accumulation shortly after treatment initiation. Notably, the trajectory of severe structural damage closely paralleled that of mild conjunctivitis, indicating a strong temporal association between the two groups.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Verification of the drug-specific nature of DASCI\u003c/h2\u003e \u003cp\u003eTo characterize the drug-specific toxicity profile of Dupilumab, we performed a comparative pharmacovigilance analysis involving five therapeutic agents (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Dupilumab demonstrated a toxicity signal with statistical significance. In contrast, Upadacitinib -a JAK inhibitor- exhibited no significant safety signal, thereby dissociating the observed toxicity from the background disease burden. Notably, Tralokinumab, a selective IL-13 inhibitor, displayed an even stronger toxicity signal. Methodologically, assay validity was confirmed using external benchmarks: Methotrexate (a positive control) yielded a high ROR, demonstrating analytical sensitivity, whereas Omalizumab (a biologic negative control) showed no signal, ruling out non-specific immunogenic responses to monoclonal antibody therapy.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSignals of ocular toxicity associated with biologics and small molecule drugs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrug\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en_Cases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en_Exposed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eROR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCI_Lower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCI_Upper\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSignal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDupilumab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e817\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e299250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUpadacitinib\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54726\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTralokinumab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMethotrexate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOmalizumab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003en_Cases: number of cases; n_Exposed: number of exposed; ROR: reporting odds ratio; CI_Lowe: lower limit of confidence interval; CI_Upper: Upper limit of confidence interval.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Integrated multi-omics profiling from single-cell transcriptomics to network analysis\u003c/h2\u003e \u003cp\u003eSingle-cell transcriptomic mapping of the human ocular surface IL-4/IL-13 axis revealed distinct cellular sources for its ligands and receptors (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). IL-13 is primarily produced by limbal epithelial superficial cells and goblet cells, whereas IL-4 is predominantly expressed by trabecular meshwork fibroblasts. Receptor analysis identified choriocapillaris venous endothelial cells and macrophages as the primary sites of IL-4R and IL-13RA1 expression, respectively. Notably, macrophages also showed strong IL-4R co-expression. Additionally, all ligands and receptors were also expressed at variable levels across other corneal and limbal epithelial cells.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePPI network analysis using STRING identified STAT6 as the central hub of the IL-13 signaling axis (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). The analysis revealed that STAT6 integrates upstream signals from the ligand-receptor complex and directly regulates key effector molecules, including mucin 5AC (MUC5AC), arginase-1 (ARG1), matrix metallopeptidase 9 (MMP9), and tight junction protein 1 (TJP1). Finally, GO enrichment analysis showed significant enrichment of pathways directly associated with Th2 immunity, including \"interleukin-4-mediated signaling pathway\" and \"regulation of type 2 immune response\". Notably, \"T-helper 1 (Th1) cell differentiation\" was also enriched (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC).\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eOur large-scale pharmacovigilance analysis of 817 DASCI cases identified between Q1 2022 and Q3 2025 revealed a strong temporal correlation between Dupilumab prescription volumes and adverse event reports. This temporal association suggests that the risk of DASCI is directly linked to drug exposure rather than a sporadic occurrence. Furthermore, DASCI is distinguished from typical degenerative corneal pathologies by a pronounced female predominance and a concentration of cases among working-age and middle-aged adults, in contrast to the elderly-predominant, non-sex-specific profile of the latter. This demographic profile implies an inherent, sex-based susceptibility, potentially mediated by sex hormone-regulated Th2 cytokine pathways\u0026mdash;a mechanism supported by study showing that estrogen enhances, whereas androgens suppress, Th2-polarized immune responses[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. We therefore hypothesize that the observed female predominance results from a more severe homeostatic disruption following IL-4/IL-13 pathway blockade, potentially due to a stronger baseline Th2 polarization in females which, upon inhibition, leads to a more pronounced immunological imbalance. One of the most clinically relevant observations of our study was the identification of a critical 19-day window between the onset of mild conjunctivitis (median, 38 days) and the development of severe structural damage (median, 57 days). This narrow interval supports the concept that DASCI represents a pathogenic continuum, wherein initial superficial inflammation triggers rapid barrier dysfunction, culminating in irreversible tissue damage. Consistent with this, Phylactou et al. demonstrate that superficial ocular inflammation can induce rapid barrier disruption and irreversible corneal structural alterations[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. This finding reinforces the paradigm of a rapid and irreversible disease course in DASCI.\u003c/p\u003e \u003cp\u003eOur comparative safety signal analysis reveals that Dupilumab, which blocks both IL-4 and IL-13 signaling, exhibits a significant safety signal. In contrast, Upadacitinib, a JAK inhibitor used in the same patient population, does not show a safety signal. The absence of a safety signal for Upadacitinib suggests that the underlying disease burden is not the primary driver of these severe corneal events. Notably, the selective IL-13 inhibitor Tralokinumab exhibits an even stronger toxicity signal, reinforcing the hypothesis that IL-13 blockade, rather than IL-4 inhibition, is more central to the pathogenesis. This observation is consistent with prior clinical observations that IL-13 plays a pivotal role in ocular surface homeostasis[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Furthermore, our single-cell transcriptomic analysis of the human ocular surface provides a cellular basis for this drug-specific effect, challenging the traditional view that IL-13 originates primarily from immune infiltrates[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. We identified a dual-source expression pattern in which goblet cells and limbal epithelial cells co-express IL13 and its receptors (IL4R, IL13RA1). This finding suggests the existence of a pivotal IL-13-mediated autocrine/paracrine signaling loop essential for goblet cell-mediated maintenance of ocular surface integrity. This concept is well-supported, as IL-13 is known to be essential for the maintenance and function of goblet cells, which are the key producers of mucins for barrier integrity, and its inhibition leads to both goblet cell loss and barrier dysfunction [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The limbal region hosts the stem cell niche critical for corneal epithelial regeneration [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Our analysis further identified IL-13 and its receptors are broadly expressed in key cell types within this region, including limbal epithelial superficial, basal, and wing cells. This spatial organization implies a critical IL-13 signaling network within the limbal niche that is essential for epithelial renewal and barrier function. Consequently, pharmacological blockade of this pathway by Dupilumab would be expected to disrupt these homeostatic processes, impairing limbal epithelial regeneration and corneal barrier integrity.\u003c/p\u003e \u003cp\u003eMechanistically, our PPI network analysis identified STAT6 as a central hub in the downstream network of IL-13 signaling. It regulates the transcription of MUC5AC while also coordinating the expression of key effectors such as MMP9 and TJP1, underscoring the essential role of the IL-13/STAT6 pathway in maintaining ocular surface integrity. The IL-13/STAT6 pathway is reported to play a pivotal role in supporting limbal stem cell proliferation and differentiation, thereby sustaining the limbal niche[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Conversely, disruption of IL-13/STAT6 signaling unravels this coordinated network, leading to goblet cell dysfunction, reduced mucin production, and compromised tear film stability-a well-documented early manifestation of Dupilumab therapy[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Furthermore, dysregulated MMP9 expression likely drives extracellular matrix degradation, whereas disrupted TJP1 expression impairs barrier integrity, collectively facilitating the progression from inflammation to tissue damage[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Our GO analysis revealed co-enrichment in both Th2 and Th1 differentiation pathways. This finding implies a potential immunological reprogramming within the ocular microenvironment under DASCI conditions, which is consistent with studies indicating that while IL-13 blockade suppresses Th2 responses, it can elicit a compensatory shift toward Th1 polarization. Consequently, this shift could amplify pro-inflammatory cascades and further disrupt the ocular surface[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Furthermore, our STRING network analysis demonstrated that STAT6 regulates the expression of the M2 macrophage marker ARG1[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Under physiological conditions, the IL-13/STAT6 signaling axis is critical for promoting macrophage polarization toward a tissue-reparative (M2) phenotype. Notably, macrophage-derived IL-13, together with the subsequent M2 polarization, can suppress the activation and function of Th1 cells[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Our single-cell data revealed a distinctly strong co-expression of IL-4R and IL13RA1 in macrophages compared to other ocular surface cells, identifying them as the primary target of Dupilumab. We hypothesize that IL-13 pathway blockade by Dupilumab skews macrophage polarization towards a pro-inflammatory (M1) phenotype. This phenotypic shift not only compromises tissue repair capacity but also promotes the substantial release of proteolytic enzymes such as MMP9[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCollectively, our study unveils a pathophysiological cascade underlying DASCI, centered on the disruption of a critical IL-13 autocrine/paracrine signaling loop. This cascade evolves through a multistep process: (1) goblet cell dysfunction and subsequent mucin loss; (2) limbal stem cell niche damage and barrier failure; and (3) immune dysregulation characterized by a pro-inflammatory shift toward Th1 immunity, which ultimately drives irreversible corneal damage. This model establishes a foundational framework for DASCI, highlighting the critical need for early detection and mechanism-based interventions in patients undergoing Dupilumab treatment.\u003c/p\u003e \u003cp\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCRediT authorship contribution statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYi-bo Wang: Writing - original draft, Data curation, Formal analysis.\u0026nbsp;Yuan-hao Li: Data curation.\u0026nbsp;Xiu-fen Liu: Formal analysis.\u0026nbsp;Xue-jun Wang: Formal analysis.\u0026nbsp;Zi-han Tang: Data curation, Methodology. Cheng-wei Lu: Supervision, Writing - review \u0026amp; editing, Methodology, Conceptualization. \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the National Natural Science Foundation of China under Grant (grant number 82471045).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis retrospective study utilized publicly accessible data from the FAERS, specifically individual case safety reports (ICSRs) regarding ADEs. Given that the research relied solely on secondary data analysis without direct human subject involvement, institutional review board (IRB) or ethical approval was waived. The dataset can be accessed via the FAERS Public Dashboard.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLe Floc\u0026apos;h A, Allinne J, Nagashima K, et al. Dual blockade of IL-4 and IL-13 with dupilumab, an IL-4R\u0026alpha; antibody, is required to broadly inhibit type 2 inflammation. Allergy 2020;75:1188-1204.\u003c/li\u003e\n\u003cli\u003eMcCann MR, Kosloski MP, Xu C, et al. Dupilumab: Mechanism of action, clinical, and translational science. Clin Transl Sci 2024;17:e13899.\u003c/li\u003e\n\u003cli\u003eChen J, Li H, Zhang H, et al. Dupilumab induced ocular surface diseases: an analysis of FAERS database, literature review and disease-gene interaction networks. Expert Opin Drug Saf 2025:1-12.\u003c/li\u003e\n\u003cli\u003eThormann K, L\u0026uuml;thi AS, Deniau F, et al. Dupilumab-associated ocular surface disease is characterized by a shift from Th2/Th17 toward Th1/Th17 inflammation. Allergy 2024;79:937-948.\u003c/li\u003e\n\u003cli\u003eMehta U, Farid M. Dupilumab Induced Limbal Stem Cell Deficiency. Int Med Case Rep J 2021;14:275-278.\u003c/li\u003e\n\u003cli\u003eArdern-Jones MR, Brown SJ, Flohr C, et al. An expert consensus on managing dupilumab-related ocular surface disorders in people with atopic dermatitis 2024. Br J Dermatol 2024;191:865-885.\u003c/li\u003e\n\u003cli\u003eCraig JP, Nichols KK, Akpek EK, et al. TFOS DEWS II Definition and Classification Report. Ocul Surf 2017;15:276-283.\u003c/li\u003e\n\u003cli\u003eGipson IK. The ocular surface: the challenge to enable and protect vision: the Friedenwald lecture. Invest Ophthalmol Vis Sci 2007;48:4390-4398.\u003c/li\u003e\n\u003cli\u003eBron AJ, de Paiva CS, Chauhan SK, et al. TFOS DEWS II pathophysiology report. Ocul Surf 2017;15:438-510.\u003c/li\u003e\n\u003cli\u003eNiederkorn JY. See no evil, hear no evil, do no evil: the lessons of immune privilege. Nat Immunol 2006;7:354-359.\u003c/li\u003e\n\u003cli\u003eLjubimov AV, Saghizadeh M. Progress in corneal wound healing. Prog Retin Eye Res 2015;49:17-45.\u003c/li\u003e\n\u003cli\u003eGarc\u0026iacute;a-L\u0026oacute;pez C, Rodr\u0026iacute;guez-Calvo-de-Mora M, Borroni D, et al. The role of matrix metalloproteinases in infectious corneal ulcers. Surv Ophthalmol 2023;68:929-939.\u003c/li\u003e\n\u003cli\u003eGao H, Cao L, Liu C. Analysis and mining of Dupilumab adverse events based on FAERS database. Sci Rep 2025;15:8597.\u003c/li\u003e\n\u003cli\u003eBakker DS, Ariens LFM, van Luijk C, et al. Goblet cell scarcity and conjunctival inflammation during treatment with dupilumab in patients with atopic dermatitis. Br J Dermatol 2019;180:1248-1249.\u003c/li\u003e\n\u003cli\u003eFukuda K, Kishimoto T, Sumi T, et al. Biologics for allergy: therapeutic potential for ocular allergic diseases and adverse effects on the eye. Allergol Int 2023;72:234-244.\u003c/li\u003e\n\u003cli\u003eWilson MM, Roberts PK, Daniell M. Dupilumab-associated ulcerative keratitis. Int J Ophthalmol 2022;15:1020-1022.\u003c/li\u003e\n\u003cli\u003eKlein SL, Flanagan KL. Sex differences in immune responses. Nat Rev Immunol 2016;16:626-638.\u003c/li\u003e\n\u003cli\u003ePhylactou M, Jabbour S, Ahmad S, et al. Corneal Perforation in Patients Under Treatment With Dupilumab for Atopic Dermatitis. Cornea 2022;41:981-985.\u003c/li\u003e\n\u003cli\u003eBannier-H\u0026eacute;laou\u0026euml;t M, Korving J, Ma Z, et al. Human conjunctiva organoids to study ocular surface homeostasis and disease. Cell Stem Cell 2024;31:227-243.e12.\u003c/li\u003e\n\u003cli\u003eWynn TA. Type 2 cytokines: mechanisms and therapeutic strategies. Nat Rev Immunol 2015;15:271-282.\u003c/li\u003e\n\u003cli\u003eTukler Henriksson J, Coursey TG, Corry DB, et al. IL-13 Stimulates Proliferation and Expression of Mucin and Immunomodulatory Genes in Cultured Conjunctival Goblet Cells. Invest Ophthalmol Vis Sci 2015;56:4186-4197.\u003c/li\u003e\n\u003cli\u003eDe Paiva CS, Raince JK, McClellan AJ, et al. Homeostatic control of conjunctival mucosal goblet cells by NKT-derived IL-13. Mucosal Immunol 2011;4:397-408.\u003c/li\u003e\n\u003cli\u003eSchermer A, Galvin S, Sun TT. Differentiation-related expression of a major 64K corneal keratin in vivo and in culture suggests limbal location of corneal epithelial stem cells. J Cell Biol 1986;103:49-62.\u003c/li\u003e\n\u003cli\u003eTrosan P, Cabral JV, Smeringaiova I, et al. Interleukin-13 increases the stemness of limbal epithelial stem cells cultures. PLoS One 2022;17:e0272081.\u003c/li\u003e\n\u003cli\u003eChotikavanich S, de Paiva CS, Li de Q, et al. Production and activity of matrix metalloproteinase-9 on the ocular surface increase in dysfunctional tear syndrome. Invest Ophthalmol Vis Sci 2009;50:3203-3209.\u003c/li\u003e\n\u003cli\u003eMantelli F, Mauris J, Arg\u0026uuml;eso P. The ocular surface epithelial barrier and other mechanisms of mucosal protection: from allergy to infectious diseases. Curr Opin Allergy Clin Immunol 2013;13:563-568.\u003c/li\u003e\n\u003cli\u003eDeng C, Huo M, Chu H, et al. Exosome circATP8A1 induces macrophage M2 polarization by regulating the miR-1-3p/STAT6 axis to promote gastric cancer progression. Mol Cancer 2024;23:49.\u003c/li\u003e\n\u003cli\u003eLi HS, Watowich SS. Innate immune regulation by STAT-mediated transcriptional mechanisms. Immunol Rev 2014;261:84-101.\u003c/li\u003e\n\u003cli\u003eEapen MS, Hansbro PM, McAlinden K, et al. Abnormal M1/M2 macrophage phenotype profiles in the small airway wall and lumen in smokers and chronic obstructive pulmonary disease (COPD). Sci Rep 2017;7:13392.\u003c/li\u003e\n\u003cli\u003eHarb H, Chatila TA. Mechanisms of Dupilumab. Clin Exp Allergy 2020;50:5-14.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Dupilumab, corneal injury, pharmacovigilance, IL13 signaling pathway, homeostasis","lastPublishedDoi":"10.21203/rs.3.rs-9212855/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9212855/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo explore the epidemiological profile of Dupilumab-associated severe corneal injury (DASCI) using large-scale real-world evidence, and to investigate its underlying molecular mechanisms through integrated single-cell transcriptomic and network analysis.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA retrospective pharmacovigilance analysis focusing on Dupilumab was carried out utilizing the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) database, covering data from first quarter of 2022 to the third quarter of 2025 (Q1 2022 to Q3 2025). A disproportionality analysis was conducted to quantify safety signals using the Reporting Odds Ratio (ROR) and Information Component (IC), with Upadacitinib and Tralokinumab serving as active comparators to strengthen the findings. The molecular mechanisms underlying Dupilumab's effects were investigated by performing single-cell RNA sequencing on human ocular surface cells, supplemented by protein-protein interaction (PPI) network analysis and Gene Ontology (GO) enrichment analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 817 cases of DASCI identified from Q1 2022 to Q3 2025 exhibited a distinct epidemiological profile, characterized by an upward temporal trend, female predominance, and peak incidence among working-age and middle-aged adults. Severity assessment indicated that the majority of reported cases (74.4%) were classified as \"medically significant,\" while an additional 19.7% required hospitalization. Time-to-event analysis revealed rapid disease progression, with median times of 38 days from initiation to mild conjunctivitis and 57 days to severe corneal damage. Disproportionality analysis confirmed a drug-specific risk signal for Dupilumab, which was absent for Upadacitinib; in contrast, Tralokinumab exhibited an even stronger signal. Single-cell transcriptomics delineated a compartmentalized IL-13 signaling network across the human ocular surface, highlighting critical roles of limbal epithelial cells, goblet cells, and macrophages. Subsequent PPI and GO enrichment analyses further established signal transducer and activator of transcription 6 (STAT6) as the central hub of this network. Furthermore, immunological reprogramming toward a Th2-to-Th1 shift may contribute to DASCI pathogenesis.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eDupilumab constitutes a significant risk factor for severe corneal injury, characterized by distinct pharmacoepidemiological and rapid progression features. Mechanistically, DASCI is triggered by IL-13 pathway blockade, mediated through a STAT6-centered network, and driven by a pathological Th2-to-Th1 shift.\u003c/p\u003e","manuscriptTitle":"Multi-omics profiling identifies IL-13 signaling as a key mediator in Dupilumab-associated severe corneal injury","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-28 08:28:44","doi":"10.21203/rs.3.rs-9212855/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"55bcca95-c747-4b56-b0f3-4011911f8cf9","owner":[],"postedDate":"March 28th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-10T12:26:12+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-28 08:28:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9212855","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9212855","identity":"rs-9212855","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}