From Diagnosing Diseases to Predicting Diseases

Chronic diseases can be considered as perturbations of complex adaptive systems. Transitions from healthy states to chronic diseases are often characterized by sudden and unexpected onset of diseases. These critical transitions or catastrophic shifts have been studied in theoretical and applied physics, ecology, social science, economics and recently also in biomedical applications. If we could understand the underlying mechanisms and the dynamics of critical transitions involved in the development of diseases, we would be better equipped to predict and eventually prevent them from arising. The current paper gives an overview of the potential application of the concept of critical transitions to biomedical applications.

[1]  M. Scheffer,et al.  Global Resilience of Tropical Forest and Savanna to Critical Transitions , 2011, Science.

[2]  P. Swain,et al.  Stochastic Gene Expression in a Single Cell , 2002, Science.

[3]  L. Onsager.  Crystal statistics. I. A two-dimensional model with an order-disorder transition , 1944 .

[4]  Y. Tu,et al.  Adaptation of Living Systems. , 2018, Annual review of condensed matter physics.

[5]  M. Kramer,et al.  Human seizures self-terminate across spatial scales via a critical transition , 2012, Proceedings of the National Academy of Sciences.

[6]  O. Alfieri,et al.  Corrigendum to 'Optimal results immediately after MitraClip therapy or surgical edge-to-edge repair for functional mitral regurgitation: are they really stable at 4 years?' [Eur J Cardiothorac Surg 2016;50:488-494]. , 2017, European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery.

[7]  M. Scheffer,et al.  Catalogue of abrupt shifts in Intergovernmental Panel on Climate Change climate models , 2015, Proceedings of the National Academy of Sciences.

[8]  Marten Scheffer,et al.  Slowing Down of Recovery as Generic Risk Marker for Acute Severity Transitions in Chronic Diseases , 2016, Critical care medicine.

[9]  J. Jefferys,et al.  Loss of neuronal network resilience precedes seizures and determines the ictogenic nature of interictal synaptic perturbations , 2018, Nature Neuroscience.

[10]  M. Scheffer,et al.  Geometric Analysis of Ecological Models with Slow and Fast Processes , 2000, Ecosystems.

[11]  Kazuyuki Aihara,et al.  Quantifying critical states of complex diseases using single-sample dynamic network biomarkers , 2017, PLoS Comput. Biol..

[12]  Kazuyuki Aihara,et al.  Detecting early-warning signals for sudden deterioration of complex diseases by dynamical network biomarkers , 2012, Scientific Reports.

[13]  U. Alon,et al.  Dynamical compensation in physiological circuits , 2016, Molecular systems biology.

[14]  Kazuyuki Aihara,et al.  Identifying critical transitions and their leading biomolecular networks in complex diseases , 2012, Scientific Reports.

[15]  John C. Hall,et al.  One surgeon's philosophy of surgical education. , 2004, American journal of surgery.

[16]  Douglas S. Shafer.  Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering (Steven H. Strogatz) , 1995, SIAM Rev..

[17]  F. Remacle,et al.  Information-theoretic analysis of phenotype changes in early stages of carcinogenesis , 2010, Proceedings of the National Academy of Sciences.

[18]  Marten Scheffer,et al.  Flickering gives early warning signals of a critical transition to a eutrophic lake state , 2012, Nature.

[19]  Asla Pitkänen,et al.  Epilepsy biomarkers , 2013, Epilepsia.

[20]  Christophe Trefois,et al.  Critical transitions in chronic disease: transferring concepts from ecology to systems medicine. , 2015, Current opinion in biotechnology.

[21]  J. Pearl,et al.  The Book of Why: The New Science of Cause and Effect , 2018 .

[22]  C. Granger,et al.  Biomarkers in atrial fibrillation: a clinical review. , 2013, European heart journal.

[23]  J. Kurths,et al.  Understanding migraine using dynamic network biomarkers , 2014, Cephalalgia : an international journal of headache.

[24]  S. Carpenter,et al.  Catastrophic regime shifts in ecosystems: linking theory to observation , 2003 .

[25]  Lei Dai,et al.  Generic Indicators for Loss of Resilience Before a Tipping Point Leading to Population Collapse , 2012, Science.

[26]  Hannah H. Chang,et al.  Cell Fate Decision as High-Dimensional Critical State Transition , 2016, bioRxiv.

[27]  E. Ising.  Beitrag zur Theorie des Ferromagnetismus , 1925 .

[28]  Meiyi Li,et al.  Dynamic network biomarker indicates pulmonary metastasis at the tipping point of hepatocellular carcinoma , 2018, Nature Communications.

[29]  Stephen R. Carpenter,et al.  Early Warnings of Regime Shift When the Ecosystem Structure Is Unknown , 2012, PloS one.

[30]  F. Remacle,et al.  Surprisal Analysis of Glioblastoma Multiform (GBM) MicroRNA Dynamics Unveils Tumor Specific Phenotype , 2014, PloS one.

[31]  M. Rietkerk,et al.  Self-Organized Patchiness and Catastrophic Shifts in Ecosystems , 2004, Science.

[32]  S. Carpenter,et al.  Anticipating Critical Transitions , 2012, Science.

[33]  M. A. Muñoz.  Colloquium: Criticality and dynamical scaling in living systems , 2017, Reviews of Modern Physics.

[34]  Jordi Bascompte,et al.  Disentangling the Web of Life , 2009, Science.

[35]  S. Carpenter,et al.  Catastrophic shifts in ecosystems , 2001, Nature.

[36]  S. Carpenter,et al.  Early-warning signals for critical transitions , 2009, Nature.

[37]  W. Stacey,et al.  On the nature of seizure dynamics. , 2014, Brain : a journal of neurology.

[38]  Devore S. Culver,et al.  Defining and characterizing the critical transition state prior to the type 2 diabetes disease , 2017, PloS one.

[39]  Erik Aurell,et al.  Quasi-potential landscape in complex multi-stable systems , 2012, Journal of The Royal Society Interface.

[40]  M. Rietkerk,et al.  Spatial vegetation patterns and imminent desertification in Mediterranean arid ecosystems , 2007, Nature.

[41]  Alvin Shrier,et al.  Predicting the onset of period-doubling bifurcations in noisy cardiac systems , 2015, Proceedings of the National Academy of Sciences.

[42]  Carl Boettiger,et al.  Quantifying limits to detection of early warning for critical transitions , 2012, Journal of The Royal Society Interface.

[43]  M. Scheffer,et al.  Recovery rates reflect distance to a tipping point in a living system , 2011, Nature.

[44]  Forest M White,et al.  A Thermodynamic-Based Interpretation of Protein Expression Heterogeneity in Different Glioblastoma Multiforme Tumors Identifies Tumor-Specific Unbalanced Processes. , 2016, The journal of physical chemistry. B.

[45]  J. Voskuil.  How difficult is the validation of clinical biomarkers? , 2015, F1000Research.

[46]  T. Lenton.  Early warning of climate tipping points , 2011 .

[47]  Rui Liu,et al.  Detecting tissue-specific early warning signals for complex diseases based on dynamical network biomarkers: study of type 2 diabetes by cross-tissue analysis , 2014, Briefings Bioinform..

[48]  J. Greene,et al.  The burden of disease and the changing task of medicine. , 2012, The New England journal of medicine.

[49]  Didier Sornette,et al.  A Generalized 2D-Dynamical Mean-Field Ising Model with a Rich Set of Bifurcations (Inspired and Applied to Financial Crises) , 2018, Int. J. Bifurc. Chaos.

[50]  S. Carpenter,et al.  Methods for Detecting Early Warnings of Critical Transitions in Time Series Illustrated Using Simulated Ecological Data , 2012, PloS one.

[51]  Juan C. Rocha,et al.  Cascading regime shifts within and across scales , 2018, Science.

[52]  Peter Cox,et al.  Tipping points in open systems: bifurcation, noise-induced and rate-dependent examples in the climate system , 2011, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[53]  Dietmar Plenz,et al.  Critical Slowing Down Governs the Transition to Neuron Spiking , 2015, PLoS Comput. Biol..

[54]  J. Drake,et al.  Early warning signals of extinction in deteriorating environments , 2010, Nature.

[55]  S. Kauffman,et al.  Cancer attractors: a systems view of tumors from a gene network dynamics and developmental perspective. , 2009, Seminars in cell & developmental biology.