27Multi-omics data driven analyses of the human immune systemStudies of the immune system have been conducted primarily in mouse models. However, it has been reported that many drug discoveries using the mouse immune system have not been as effective as expected when tested in humans. It is becoming also clear that there are numerous differences between mice and humans in both innate and acquired immunity. Further, human populations are much more diverse compared to experimental mouse models. Therefore, we really need “human immunology,” in which the human immune system itself is directly studied.We are focusing on individual genetic variants and the microbiome as an environmental factor that generate diversity in human immune function, as well as various measurable factors such as the epigenome (open chromatin and histone modifications), gene expression (transcriptome), proteome, lipidome, metabolome, etc., as a multi-omics dataset. By integrating and analyzing these datasets with statistical genetics and artificial intelligence (AI) analyses, we ex-pect to be able to understand the detailed mechanisms of functional expression and regulation of individual molecules, as well as the “big picture” of immune functions, disease mechanisms and predictions, and repair methods.These studies are based on the collaborative efforts of more than ten teams at IMS. As one of the core teams, we are responsible for the collection of im-mune cell and microflora analysis samples from healthy individuals and vaccine recipients, as well as PBMC subset isolation and cell stimulation correspond-ing to each subset, genomic analysis, epigenomic analysis, and gene expression analysis. We also provide samples of lymphocyte subsets for the teams in charge of proteomic, lipidome, and metabolomic analyses as well as measured data for the teams in charge of data processing and analysis.The collaborative laboratories on this project: the Laboratories for Human Immunogenetics, Systems Genetics, Cancer Genomics, Intestinal Ecosystem, Metabolomics, Integrative Genomics, Immunotherapy, Statistical and Transla-tional Genetics, Large-Scale Biomedical Data Technology and the YCI unit for Proteome Homeostasis.Figure: Immune cell subsets used for advanced multi-omics studies for the evaluation of human immune function Recent Major PublicationsOta M, Nakano M, Nagafuchi Y, Kobayashi S, Hatano H, Yoshida R, Akutsu Y, Itamiya T, Ban N, Tsuchida Y, Shoda H, Yamamoto K, Ishigaki K, Okamura T, Fujio K. Multimodal repertoire analysis unveils B cell biology in immune-mediated diseases. Ann Rheum Dis 82, 1455-1463 (2023)Yamamoto K, Ishigaki K, Okada Y. How can genetics analysis allow early detection of rheumatoid arthritis. Semin Arthritis Rheum 22, 152323 (2023)Ono C, Tanaka S, Myouzen K, Iwasaki T, Ueda M, Oda Y, Yamamoto K, Kochi Y, Baba Y. Upregulated Fcrl5 disrupts B cell anergy causes autoimmune disease. Front Immu-nol 14, 1276014 (2023)Invited presentationsYamamoto K, Ishigaki K. “Advances in biological targets in RA” Asia-Pacific League of Associations for Rheuma-tology (APLAR) (Chiang Mai, Thailand) December 2023Yamamoto K. “Data-driven functional analyses of hu-man lymphocytes” Cell Research Symposium (Taizhou, China) October 2023Yamamoto K. “How to apply genetic information to autoimmune research” KAI International Meeting 2023 (KAI 2023)(Incheon, Korea) September 2023Yamamoto K. “How to apply genetic information to autoimmune research” International Societies for Inves-tigative Dermatology Meeting 2023 (Tokyo, Japan) May 2023Yamamoto K, Ishigaki K, Okada Y. “How can genetics analysis allow early detection of rheumatoid arthritis” The Advances in Targeted Therapies Conference (ATT) (Nice, France) March 2023Laboratory for Autoimmune DiseasesTeam Leader: Kazuhiko Yamamoto
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