Jianhua Yin, Yuhui Zheng, Zhuoli Huang, Wenwen Zhou, Yue Yuan, Pengfei Cai, Yong Bai, Shichen Yang, Yue Gao, Shanshan Duan, Yang Wang, Zekai Xu, W H Zhang, Xinyu Zhang, Yilin Wei, Yaling Huang, Ying Liu, Weikai Wang, Tao Yang, Zhongjin Zhang, Xiaoya Chen, Xiru Zhang, Jingzhi Lv, Fupeng Li, Yan Zhang, Guodan Zeng, Xue Wang, Wen Ma, Guixue Hou, Shijie Hao, Chang Liu, Chang Liu, Yiwei Lai, Panhong Liu, Bo Wang, Yuxiang Li, Wenwei Zhang, Peng Gao, Jun Xie, Miguel A. Esteban, Ying Gu, Xin Liu, Ting Qi, Ting Qi, Boxiang Liu, Hua Wang, Yi Zhao, Xiao Yang, Xiangdong Wang, Runsheng Chen, Jian Yang, Ye Yin, Jian Wang, Yanan Cao, Xun Xu, Longqi Liu, Xin Jin, Chuanyu Liu, Chuanyu Liu
Human peripheral blood exhibits molecular and cellular heterogeneity across populations, yet the underlying mechanisms remain unclear. We present the Chinese Immune Multi-Omics Atlas (CIMA), characterizing molecular variations linked to sex, age, and genetic variants through multi-omics analysis of more than 10 million circulating immune cells from 428 Chinese adults. CIMA established an enhancer-driven gene regulatory network comprising 237 robust regulons; identified 9600 eGenes and 52,361 caPeaks at cell type resolution; and revealed pleiotropic associations among immune-related disease risk loci, cis-expression quantitative trait loci (QTLs), and chromatin accessibility QTLs. Furthermore, the cell language model CIMA-CLM predicted chromatin accessibility and evaluated the effects of noncoding variants from chromatin sequences and gene expression. CIMA provides a comprehensive reference for immune-related disease research.