Based on single-cell transcriptome and epigenome data of tens of millions of peripheral blood immune cells, as well as multi omics data such as plasma lipidomics and metabolomics, a joint research team including the National Key Laboratory of Genomic Multidimensional Analysis Technology has successfully identified 73 subtypes of immune cells, including rare cells that account for less than one thousandth of the total in the blood. The related research was published on January 9th in the international journal Science. It is reported that traditional research on immune cells mostly stays at the level of major cell types, such as T cells. This study conducted a systematic multi omics in-depth analysis of over 10 million peripheral blood immune cells from a cohort of 428 Chinese individuals, and created a high-resolution population immune multi omics atlas (CIMA), discovering 73 new subtypes of immune cells. The map also establishes detailed "identity cards" for each type of cell, recording their distribution and gene expression characteristics. Researcher Liu Chuanyu from the National Key Laboratory of Genomic Multidimensional Analysis Technology and the Huada Institute of Life Sciences stated that rare cells were previously difficult to capture, but through single-cell data "screening," the team found that they play a key role in specific immune responses. AI solutions greatly improve research efficiency and successfully predict the functional effects of multiple disease-related non coding variants. Taking asthma as an example, this study identified a key variant that plays a regulatory role in the expression of related genes, revealing the reasons for the high risk of asthma in specific populations. Based on the graph, the team will continue to expand disease cohort research and explore new targets. Ning Guang, an academician of the CAE Member and president of Ruijin Hospital affiliated to the School of Medicine of Shanghai Jiaotong University, believes that CIMA provides a vital immunologic perspective and data support for the mechanism research and precise prevention of complex diseases in the population. Cheng Tao, an academician of the CAE Member and president of the Institute of Hematology Hospital (Institute of Hematology) of the Chinese Academy of Medical Sciences, said that the cell language model developed by the team provides a new tool for predicting chromatin status from sequence and expression information and evaluating non coding mutation function. (New Society)