The Spatial Atlas of Human Anatomy (SAHA): A Multimodal Subcellular-Resolution Reference Across Human Organs.
| Publication Type | Preprint |
| Authors | Park J, Gregorio R, Hissong E, Ozcelik E, Bartelo N, Dezem F, Zhang L, Marção M, Chasteen H, Zheng Y, Abila E, Kim J, Nelson T, Proszynski J, Agyemang A, Arikatla M, Wani A, Liu Y, Metzger E, Rogers S, Divakar P, Dulai P, Reeves J, Liang Y, Pan L, Bhattacharjee S, Patrick M, Young K, Heck A, Korukonda M, McGuire D, Wu L, Wardhani A, Beechem J, Church G, Lipkin S, Berliner A, Patel S, Socciarelli F, Krumsiek J, Chandwani R, Monette S, Robinson B, Loda M, Elemento O, Martelotto L, Plummer J, Rendeiro A, Alonso A, Schwartz R, Houlihan S, Mason C |
| Journal | bioRxiv |
| Date Published | 11/05/2025 |
| ISSN | 2692-8205 |
| Abstract | 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 and ligand-receptor pairs. 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, enabling the development of context-aware models that simulate tissue behavior, decode complex pathologies, and accelerate therapeutic innovation at unprecedented scale. |
| DOI | 10.1101/2025.06.16.658716 |
| PubMed ID | 40611896 |
| PubMed Central ID | PMC12224548 |