CMAISE: Establishing the longitudinal multi-omics cohort for sepsis precision medicine
image: (A) Geographic distribution of participating clinical centers across China for Version 1.0 (Left) and Version 2.0 (Right). The map illustrates the spatial layout of clinical sites, with the overall distribution centered for comparison. Bubble sizes are proportional to the center capacity, reflecting the scale of research resources at each location. The transition from the left (Version 1.0) to the right (Version 2.0) highlights the expansion and evolution of the clinical network.(B) Landscape of major global sepsis databases from 2006 to 2026. Bubble plot comparing CMAISE and public datasets by release year (x-axis) and log sample size (y-axis), with bubble area scaled to sample size.(C) Composition of multi-omics data in CMAISE, including transcriptomics, proteomics (DIA and Olink), metabolomics, and scRNA-seq. (D) Cumulative patient enrollment timeline.
Credit: Jie Yang, Suibi Yang, Jiajun Cai, Songzan Qian, Shuping Song, Jun Guo, Yang Wang, Jinyan Xing, Bo Zhang, Zhihao Wang, Shengze Wu, Xinhao Jin, Bowen Tan, Dongdong Yang, Yao Yan, Haoran Chen, Changlin Sun, Kang Zou, Yuxin Leng, Jingye Pan, Tianlong Zhang, Yiming Shao, Lina Xian, Hongjun Kang, Zhen Wang, Ruilan Wang, Nan Wang, Lvyin Yan, Kun Cheng, Songqiao Liu, Lin Chen, Caibao Hu, Fuhong Su, Qian Gao, Yi Yang, Zhongheng Zhang, On behalf of Chinese
Sepsis remains a leading cause of mortality worldwide due to its profound biological heterogeneity. While multi-omics approaches offer promise for precision medicine, existing datasets often lack longitudinal granularity or comprehensive clinical integration. We present the Chinese Multi-omics Advances In Sepsis (CMAISE) cohort, a prospective, multicenter initiative integrating high-resolution multi-omics (transcriptomics, proteomics, metabolomics, scRNA-seq) with deep clinical phenotyping. By combining molecular trajectories with continuous vital signs and laboratory data, CMAISE provides an unprecedented resource to decode sepsis complexity. This correspondence outlines the cohort design, data resources, and its potential to accelerate the discovery of treatable traits.