Shared multicellular injury programs of acute and chronic kidney disease enable mechanistic patient stratification

Robin Fallegger1, Sergio A Gomez-Ochoa2, Charlotte Boys1

  • 1Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Heidelberg, Germany.

Insights

Acute kidney injury (AKI) and chronic kidney disease (CKD) share molecular mechanisms, revealed by single nucleus transcriptomics. These findings link kidney injury molecular programs to non-invasive protein signatures predicting patient outcomes.

Area of Science:

  • Nephrology
  • Genomics
  • Molecular Biology

Background:

  • Acute kidney injury (AKI) and chronic kidney disease (CKD) are distinct yet interconnected conditions with complex clinical trajectories.
  • Recent advances in transcriptomics offer insights into kidney cellular diversity in health and disease.

Purpose of the Study:

  • To investigate molecular diversity and commonalities in kidney biopsies from AKI and CKD patients using single nucleus transcriptomics.
  • To identify shared molecular mechanisms underlying acute and chronic kidney damage.

Main Methods:

  • Employed single nucleus transcriptomics on over 150 kidney biopsies from the Kidney Precision Medicine Project (KPMP).
  • Utilized unsupervised approaches to identify multi-cellular programs associated with acute injury and chronic damage.
  • Mapped molecular programs to urinary and plasma protein profiles and validated in the UK Biobank.

Main Results:

  • Identified two distinct multi-cellular programs linked to acute injury and chronic damage, expressed across both AKI and CKD patients.
  • Revealed shared molecular mechanisms rather than distinct pathways for AKI and CKD.
  • Discovered that these molecular programs reflect tubular epithelial cell repair states and cellular stress.
  • Identified NFkB, AP-1, and STAT family members as potential upstream regulators.
  • Established a link between molecular injury signatures and non-invasive protein profiles predictive of renal outcomes.

Conclusions:

  • Unbiased identification of cellular programs in kidney disease provides a unified view of injury mechanisms across AKI and CKD.
  • Non-invasive protein signatures derived from molecular data can predict long-term renal outcomes.
  • This research advances precision medicine by linking molecular insights to clinical trajectories and patient outcomes.

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