Plate IV.5 · Publications

A Community-Driven Single-Cell PBMC Reference Integrating Landmark Datasets Spanning Health and Disease

Preprint in bioRxiv, 25 September 2026.

PreprintOpen accessResearch area: Cell Atlas, Integration

Authors

  1. Ana-Maria Cujba
  2. Sergio Aguilar-Fernandez
  3. Adrien Antoinette
  4. Wamia Said
  5. Michaela F. Mueller
  6. Kian Hong Kock
  7. Jacquelyn Nestor
  8. Radhika Sonthalia
  9. Eliora V. Buyamin
  10. Pragya Rawat
  11. Alexander Predeus
  12. Lorenz Kretschmer
  13. Lijiang Fei
  14. Kamil Slowikowski
  15. Pritha Sen
  16. Christopher V. Cosgriff
  17. MGH COVID-19 Collection & Processing Team
  18. Olli Dufva
  19. Mohamad Askari
  20. Kyle Kimler
  21. Mary Futey
  22. Ida Zucchi
  23. Arsenios Chatzigeorgiou
  24. Parisa Nejad
  25. Liying Jin
  26. Blake Bowen
  27. Andrian Yang
  28. Rik G. H. Lindeboom
  29. Rachelly Normand
  30. Stathis Megas
  31. Yoshinari Ando
  32. Ankita Chatterjee
  33. Jong-Eun Park
  34. Partha P. Majumder
  35. Ponpan Matangkasombut
  36. Varodom Charoensawan
  37. Jay W. Shin
  38. Woong-Yang Park
  39. Asian Immune Diversity Atlas (AIDA) Network
  40. Stephen Sansom
  41. Berthold Göttgens
  42. Joseph E. Powell
  43. Lloyd Bod
  44. Holger Heyn
  45. Fabian J. Theis
  46. Sarah A. Teichmann
  47. Malte D. Luecken
  48. Shyam Prabhakar
  49. Alexandra-Chloé Villani
  50. Gary Reynolds

Abstract

Blood provides an accessible window into human health, yet the absence of a peripheral blood mononuclear cells (PBMCs) reference with standardized immune cell annotations has constrained comparisons between single-cell RNA sequencing (scRNAseq) studies. Here, we present HARP (H uman Cell A tlas R eference for P BMCs), an integrated atlas of ∼9 million PBMCs from >2,600 donors across 15 studies spanning four continents, encompassing diverse populations, neonates to 97 years, across health and diverse immune-related diseases. We developed optimized integration workflows, including novel label-free metrics to assess integration quality, and generated community-driven consensus annotations for 192 immune cell subsets, identifying rare populations representing as few as 0.004% of PBMCs. HARP reveals coordinated cellular modules associated with age, sex, and disease, identifies female-biased interferon and inflammatory gene programs and their perturbation by COVID-19, and uncovers a novel sexual dimorphism in prostaglandin signaling. Finally, we introduce scTiger, a hierarchical label-transfer framework that accurately projects these 192 cell annotations onto ∼18 million additional PBMCs, providing a robust and transferable reference for harmonizing future PBMC studies. HARP provides a high-resolution community-driven reference atlas for PBMC annotation and analysis, as a basis for emerging clinical applications of single-cell genomics.

Cite

@misc{cujba2026community,
  title = {{A Community-Driven Single-Cell PBMC Reference Integrating Landmark Datasets Spanning Health and Disease}},
  author = {Cujba, Ana-Maria and Aguilar-Fernandez, Sergio and Antoinette, Adrien and Said, Wamia and Mueller, Michaela F. and Kock, Kian Hong and Nestor, Jacquelyn and Sonthalia, Radhika and Buyamin, Eliora V. and Rawat, Pragya and Predeus, Alexander and Kretschmer, Lorenz and Fei, Lijiang and Slowikowski, Kamil and Sen, Pritha and Cosgriff, Christopher V. and MGH COVID-19 Collection \& Processing Team and Dufva, Olli and Askari, Mohamad and Kimler, Kyle and Futey, Mary and Zucchi, Ida and Chatzigeorgiou, Arsenios and Nejad, Parisa and Jin, Liying and Bowen, Blake and Yang, Andrian and Lindeboom, Rik G. H. and Normand, Rachelly and Megas, Stathis and Ando, Yoshinari and Chatterjee, Ankita and Park, Jong-Eun and Majumder, Partha P. and Matangkasombut, Ponpan and Charoensawan, Varodom and Shin, Jay W. and Park, Woong-Yang and Asian Immune Diversity Atlas (AIDA) Network and Sansom, Stephen and Göttgens, Berthold and Powell, Joseph E. and Bod, Lloyd and Heyn, Holger and Theis, Fabian J. and Teichmann, Sarah A. and Luecken, Malte D. and Prabhakar, Shyam and Villani, Alexandra-Chloé and Reynolds, Gary},
  howpublished = {bioRxiv},
  publisher = {openRxiv},
  year = {2026},
  month = sep,
  doi = {10.64898/2026.09.21.749940},
  url = {https://doi.org/10.64898/2026.09.21.749940},
  note = {Preprint}
}
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