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Selection for Function in Complex Distributed Pathological Systems.

Frédéric Thomas1, Antoine M Dujon1,2, Daniel Vaiman3

  • 1CREEC/CANECEV, MIVEGEC (CREES) Department University of Montpellier, CNRS, IRD Montpellier France.

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Summary
This summary is machine-generated.

Many diseases persist as complex systems, not just localized issues. This framework views conditions like cancer metastases and autoimmune disorders as evolving pathological systems selected for persistence.

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Area of Science:

  • Evolutionary Medicine
  • Pathology
  • Systems Biology

Background:

  • Traditional views of disease focus on localized origins.
  • Emerging evidence suggests many diseases function as interconnected, multi-site systems.
  • This perspective is crucial for understanding disease persistence and progression.

Purpose of the Study:

  • To propose a new framework for understanding diseases as complex, evolving pathological systems.
  • To apply the principle of 'selection for function' to explain the persistence of various diseases.
  • To reframe pathology beyond isolated breakdowns to emergent system properties.

Main Methods:

  • Conceptual framework integrating selection for function with systems biology.
  • Analysis of diseases like metastases, amyloidoses, fibroses, and autoimmune syndromes.
  • Examination of local-systemic interactions and feedback loops in disease persistence.

Main Results:

  • Diseases can be understood as complex evolving pathological systems where local units interact systemically.
  • Local lesions can trigger systemic changes, creating self-reinforcing cycles of disease persistence.
  • This systemic view unifies disparate conditions under the principle of 'system persistence'.

Conclusions:

  • Pathology can be viewed as an emergent property of pathological systems, not just localized failures.
  • This reframing has implications for disease classification and therapeutic strategies in evolutionary medicine.
  • Future research should focus on disrupting pathological connectivity and monitoring systemic biomarkers.