71Disease StratificationGenomeTranscriptome/MicrobiomePrediction of Treatment EffectClinical dataDrug DiscoveryDietaryVitamin B1ILC2Gut microbialElaidateGut microbialmonosaccharidessuppression of tight junction genesgut barrierdysfunctioninsulin resistanceIL‐4+ILC2systemic low‐gradeinflammationobesity, insulin resistanceTreatment AGoodModestGut microbessecondary progressivemultiple sclerosisPoorinteractions deeply impact host physiology and pathology. There are several ongoing research projects on this theme in IMS.Type 2 diabetes mellitus (T2D) is prevalent worldwide, in-cluding in Japan. It is estimated that about 1 in 5 Japanese suffer from diabetic or prediabetic conditions. Thus, prevention of T2D and control of its progression are important and urgent, not only medically but also socially and economically. As one of the center projects involving quite a few IMS laboratories, we tried to iden-tify gut microbial biomarkers involved in the insulin resistant (i.e. prediabetic) condition in humans, in collaboration with the Uni-versity of Tokyo Hospital. This is described more in detail in the Research Highlights section.The Laboratory for Gut Homeostasis has also been working on the host-gut microbiome interaction, especially focusing on the impact of gut bacteria and diet on the host’s immune system. The Laboratory for Symbiotic Microbiome Sciences, a lab newly established in 2023, is studying the complex interactions between disease. This study aims to clarify the diverse pathophysiol-ogy of human AD by integrating and analyzing the genome, tran-scriptome and multimodal clinical information of AD patients, and to establish a foundation for personalized predictive medi-cine according to the pathophysiology of the disease.These analysis revealed that different molecular dynamics underlie the pathogenesis of erythema (redness of the skin) and papules (raised blemishes), two symptoms characteristic of AD. Furthermore, a one-year longitudinal analysis showed different patterns of disease and gene expression that were shown to be linked to patients’ treatment histories. (Sekita, et al. Nat Commun. 2023.) In addition, we are promoting research to identify molecu-lar markers from skin tissue and blood that can be used to predict the therapeutic effects of immunotherapeutic drugs, with the aim of realizing precision medicine. We also developed MeDIA (Med-symbiotic microbial ecosystems and their hosts by advancing metagenomics-based observational techniques. They specially focus on identifying microorganisms that contribute to modify the status of various diseases, including multiple sclerosis. The Laboratory for Intestinal Ecosystem has also been working on the host-gut microbiome interactions. In this year, they have identi-fied the gut microbial metabolites involved in the pathogenesis of obesity and type 2 diabetes, as well as pediatric bronchial asthma. Please refer to the Lab Activities pages of each laboratory for de-tails.ical Data Integration Assistant), a software that facilitates data management and integration to promote clinical research charac-terized by large scale, multi-modal, and multi-center studies. We then proposed best practices for clinical data management flow that we learned from the development and implementation of MeDIA.(Ohta, et al. Allergology International. in press.)Further-more, research on the practical application of seed compounds discovered from the integration of human and mouse model data is being conducted in collaboration with the University of Tokyo, Keio University School of Medicine, and RIKEN DMP.Figure: The impact of gut microbiome and diet on the host immune sys-tem and diseasesExamples of the impact of gut microbes and their metabolites, as well as dietary com-ponents, on the host immune system and disease pathogenesis.Figure: Study workflow: Data driven research for Atopic DermatitisCombining cross-sectional and longitudinal studies, genomic, transcriptome/microbiome data and clinical multimodal data were collected from col-laborating clinical research institutions (in collaboration with Keio University School of Medicine). These will be used to develop useful markers for disease stratification and disease monitoring/prediction of treatment efficacy using machine learning and mathematical methods. Furthermore, these data will be analyzed in combination with animal models to identify new therapeutic targets and develop new therapeutic agents.Research on the host-gut microbiome interactionsAccumulating evidence indicates that host-gut microbiota Atopic dermatitisAtopic dermatitis (AD) is a heterogeneous and multifactorial
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