Trajectory and genetic correlation mapping of cross-disease risks following incident type 2 inflammatory diseases

Type 2 inflammatory diseases (T2IDs) such as atopic dermatitis (AD), asthma, food allergy, eosinophilic esophagitis (EoE), chronic sinusitis (CS), and others, are immune-mediated conditions that frequently co-occur across organ systems and contribute to substantial disease burden. While the atopic march has long served as a conceptual model for T2ID progression, it remains unclear whether this linear sequence captures the broader comorbidity structure of T2IDs. In this study, we systematically analyzed comorbidity patterns across nine T2IDs using two complementary methodological approaches: Large-scale real-world data (RWD) from over 129 million electronic health records and genome-wide genetic correlation, including data from three novel (asthma, chronic sinusitis and allergic rhinitis) metanalyses of genome-wide association studies. Retrospective matched cohort analyses revealed a highly interconnected disease network in which CS emerged as a central driver of downstream comorbidities, increasing the risk of multiple other T2IDs across diverse patient populations. AD, food allergy, and vasomotor and allergic rhinitis also showed strong cross-disease effects. Subgroup analyses uncovered notable age-, sex-, and race-specific disparities. Genetic correlation analyses supported shared heritability among many disease pairs and integration with RWD allowed to infer directionality. While some disease pairs showed discordant findings between genetic correlation and RWD, most associations aligned across both methodologies. Together, our results highlight that T2ID progression extends beyond the atopic march and is shaped by a complex and heterogeneous network of interactions. This work provides a data-driven framework to guide risk stratification, inform early preventive strategies, and prioritize upstream disease targets within the type 2 inflammatory spectrum.