Park Jiwoon, De Gregorio Roberto, Hissong Erika, Ozcelik Elif, Bartelo Nicholas, Dezem Felipe Segato, Zhang Luke, Marção Maycon, Chasteen Hannah, Zheng Yimin, Abila Ernesto, Kim Junbum, Proszynski Jacqueline, Agyemang Akua A, Arikatla Mohith Reddy, Wani Arjumand, Liu Yutian, Metzger Evelyn, Rogers Stefan, Divakar Prajan, Dulai Parambir S, Reeves Jason, Liang Yan, Pan Liuliu, Bhattacharjee Sayani, Patrick Michael, Young Kimberly, Heck Ashley, Korukonda Mithra, McGuire Dan, Wu Lidan, Wardhani Aster, Beechem Joseph, Church George, Lipkin Steven M, Patel Sanjay, Socciarelli Fabio, Chandwani Rohit, Monette Sebastien, Robinson Brian, Loda Massimo, Elemento Olivier, Martelotto Luciano, Plummer Jasmine, Rendeiro André F, Alonso Alicia, Schwartz Robert E, Houlihan Shauna Lee, Mason Christopher E
Weill Cornell Medicine, New York, NY, USA.
Harvard Medical School, Boston, MA, USA.
bioRxiv. 2025 Jun 19:2025.06.16.658716. doi: 10.1101/2025.06.16.658716.
The Spatial Atlas of Human Anatomy (SAHA) represents the first multimodal, subcellular-resolution reference of healthy adult human tissues across multiple organ systems. Integrating spatial transcriptomics, proteomics, and histological features across over 15 million cells from more than 100 donors, SAHA maps conserved and organ-specific cellular niches in gastrointestinal and immune tissues. High-resolution profiling using CosMx SMI, 10x Xenium, RNAscope, GeoMx DSP, and single-nucleus RNA-seq reveals spatially organized cell states, rare adaptive immune populations, and tissue-specific cell-cell interactions. Comparative analyses with colorectal cancer and inflammatory bowel disease demonstrate the power of SAHA to detect disease-associated spatial disruptions, including crypt dedifferentiation, perineural invasion, and therapy-resistant immune remodeling. All data are openly accessible through a FAIR-compliant interactive portal to support exploration, benchmarking, and machine learning model training. Through SAHA, we provide a foundational framework for spatial diagnostics and next-generation precision medicine grounded in a comprehensive human tissue atlas.
《人体解剖学空间图谱》(SAHA)是首个跨多个器官系统的健康成年人体组织的多模态、亚细胞分辨率参考图谱。SAHA整合了来自100多名捐赠者的超过1500万个细胞的空间转录组学、蛋白质组学和组织学特征,绘制了胃肠道和免疫组织中保守的和器官特异性的细胞生态位。使用CosMx SMI、10x Xenium、RNAscope、GeoMx DSP和单核RNA测序进行的高分辨率分析揭示了空间组织的细胞状态、罕见的适应性免疫群体以及组织特异性的细胞间相互作用。与结直肠癌和炎症性肠病的比较分析证明了SAHA检测疾病相关空间破坏的能力,包括隐窝去分化、神经周围浸润和抗治疗性免疫重塑。所有数据均可通过一个符合FAIR原则的交互式门户公开获取,以支持探索、基准测试和机器学习模型训练。通过SAHA,我们为基于全面人体组织图谱的空间诊断和下一代精准医学提供了一个基础框架。