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Updated: Nov 4, 2025

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Perspectives in systems nephrology.

Maja T Lindenmeyer1, Fadhl Alakwaa2, Michael Rose2

  • 1III. Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. m.lindenmeyer@uke.de.

Cell and Tissue Research
|May 24, 2021
PubMed
Summary
This summary is machine-generated.

Chronic kidney disease (CKD) affects 10% of the global population. A systems biology approach integrating multi-omics and clinical data offers a transformative, mechanism-based strategy for improved CKD classification and targeted therapies.

Keywords:
Chronic kidney diseasesPrecision medicineSystem nephrology

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Area of Science:

  • Nephrology
  • Systems Biology
  • Computational Biology

Background:

  • Chronic kidney diseases (CKD) represent a significant global health burden, impacting approximately 10% of the world's population.
  • Current CKD classification relies on descriptive clinical or histopathological findings, which are limited in predicting disease mechanisms, prognosis, and treatment responses.
  • The heterogeneity of CKD pathophysiology necessitates advanced approaches beyond reductionist methods.

Purpose of the Study:

  • To explore the transformative potential of a systems biology approach for a deeper understanding of CKD.
  • To identify the molecular underpinnings of CKD subtypes and individual patient disease drivers.
  • To enable mechanism-based patient stratification for improved diagnostics and novel therapeutic discovery.

Main Methods:

  • Integration of comprehensive multi-omics data (genomics, proteomics, metabolomics, etc.).
  • Incorporation of clinical phenotypic information and clinicopathological parameters.
  • Application of advanced mathematical, statistical, computational, and artificial intelligence methods for big data analysis.

Main Results:

  • Identification of molecular determinants underlying CKD heterogeneity.
  • Development of a holistic framework for analyzing complex CKD datasets.
  • Mapping of diverse biological and clinical data to reveal disease mechanisms.

Conclusions:

  • A systems biology approach provides transformative insights into CKD pathophysiology.
  • Mechanism-based classification of CKD patients will enhance prognostic and predictive capabilities.
  • This approach is crucial for discovering novel, molecularly targeted therapies for specific CKD subtypes.