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Application of spatial-omics to the classification of kidney biopsy samples in transplantation

Nature Reviews Nephrology (2024)Cite this article

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Abstract

Improvement of long-term outcomes through targeted treatment is a primary concern in kidney transplant medicine. Currently, the validation of a rejection diagnosis and subsequent treatment depends on the histological assessment of allograft biopsy samples, according to the Banff classification system. However, the lack of (early) disease-specific tissue markers hinders accurate diagnosis and thus timely intervention. This challenge mainly results from an incomplete understanding of the pathophysiological processes underlying late allograft failure. Integration of large-scale multimodal approaches for investigating allograft biopsy samples might offer new insights into this pathophysiology, which are necessary for the identification of novel therapeutic targets and the development of tailored immunotherapeutic interventions. Several omics technologies — including transcriptomic, proteomic, lipidomic and metabolomic tools (and multimodal data analysis strategies) — can be applied to allograft biopsy investigation. However, despite their successful application in research settings and their potential clinical value, several barriers limit the broad implementation of many of these tools into clinical practice. Among spatial-omics technologies, mass spectrometry imaging, which is under-represented in the transplant field, has the potential to enable multi-omics investigations that might expand the insights gained with current clinical analysis technologies.

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Fig. 1: Current practice in post-transplant allograft monitoring.
Fig. 2: MSI data generation and visualization.
Fig. 3: Multiomics data integration strategies.
Fig. 4: Potential future practice in post-transplant allograft monitoring.

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Acknowledgements

This project is funded by the Dutch Kidney Foundation, projects 17OKG23 and 21OK + 015. The authors used ChatGPT from OpenAI for language editing of the initial draft manuscript; the tool was not used for creation of any original content or concepts, and the authors take full accountability for the work.

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Author notes

  1. These authors jointly supervised this work: Aiko P.J. de Vries and Jesper Kers.

Authors and Affiliations

  1. Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, the Netherlands

    Paola Tasca & Bram Heijs

  2. Leiden Transplant Center, Leiden University Medical Center, Leiden, the Netherlands

    Paola Tasca, Cees van Kooten, Aiko P. J. de Vries & Jesper Kers

  3. Department of Pathology, Leiden University Medical Center, Leiden, the Netherlands

    Paola Tasca & Jesper Kers

  4. Department of Internal Medicine, Division of Nephrology, Einthoven Laboratory of Vascular and Regenerative Medicine, Leiden University Medical Center, Leiden, the Netherlands

    Bernard M. van den Berg, Ton J. Rabelink, Gangqi Wang, Cees van Kooten & Aiko P. J. de Vries

  5. The Novo Nordisk Foundation Center for Stem Cell Medicine (Renew), Leiden University Medical Center, Leiden, the Netherlands

    Ton J. Rabelink & Gangqi Wang

  6. Bruker Daltonics GmbH & Co. KG, Bremen, Germany

    Bram Heijs

  7. Department of Pathology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands

    Jesper Kers

  8. Center for Analytical Sciences Amsterdam, Van’t Hoff Institute for Molecular Sciences, University of Amsterdam, Amsterdam, the Netherlands

    Jesper Kers

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Contributions

A.P.J.dV., P.T., B.H. and J.K. researched data for the article. A.P.J.dV., P.T., B.M.vdB., B.H. and J.K. made substantial contributions to discussions of the content of the article. A.P.J.dV., P.T., B.H. and J.K. wrote the manuscript. All authors reviewed or edited the manuscript before submission.

Corresponding author

Correspondence to Aiko P. J. de Vries.

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Competing interests

J.K. is a consultant for Aiosyn B.V. and Alentis Pharmaceuticals AG, coordinates a central biopsy review commission (SIRIUS-LN trial) for Novartis AG and receives speaker fees from Chiesi pharma. B.H. is employed by Bruker Daltonics GmbH & Co. KG, which is a vendor of analytical equipment and associated software. The other authors declare no competing interests.

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Nature Reviews Nephrology thanks Andrew F. Malone, Isabella Piga and Candice Roufosse for their contribution to the peer review of this work.

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Tasca, P., van den Berg, B.M., Rabelink, T.J. et al. Application of spatial-omics to the classification of kidney biopsy samples in transplantation. Nat Rev Nephrol (2024). https://doi.org/10.1038/s41581-024-00861-x

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