Identifying critical transitions in complex diseases

Abstract

Mortality and the burden of diseases worldwide continue to reach substantial numbers with societal development and urbanization. In the face of decline in human health, early detection of complex diseases is indispensable, albeit challenging. In this review, we document the research carried out thus far on the appearance of complex diseases marked by a critical transition or a sudden shift from a healthy state to a disease state. The theory of resilience and critical slowing down can provide practical tools to forecast the onset of various fatal and perpetuating diseases. However, critical transitions in diseases across diverse temporal and spatial scales may not always be preceded by critical slowing down. In this backdrop, an in-depth study of the underlying molecular mechanisms provides dynamic network biomarkers that can forecast potential critical transitions. We have put together the theory of complex diseases and resilience, and have discussed the need for advanced research in developing early warning signals in the field of medicine and health care. We conclude the review with a few open questions and prospects for research in this emerging field.

Systematic analysis and optimization of early warning signals for critical transitions using distribution data

“…Our results can be readily tested and applied on real-world monitoring systems and can inform the development of new indicators to address specific problems like cancer onset, much like previous studies 22 did using less performing measurements. Our results can be further applied to a range of other diseases to detect their onset, from diabetes 101 and other complex diseases 22 to epidemics. 28 In addition, leveraging the sensitivity of indicators’ trends to noise type and parameter dynamics can provide new methods to infer the latter from empirical data.…”

AZIN1-centric dynamic network biomarker of tipping point in non-small cell lung cancer metastasis

“…Metastasis is a complex process that involves dynamic interactions among multiple genes [36,37]. The previous studies indicated that DNBs play a key role in the initiation and development of many diseases by occupying an important position in regulatory pathways and modulating their outcomes [38][39][40]. To establish the connection of AZIN1 with NSCLC metastasis, AZIN1-centred network with its six neighboring genes was mapped and the nodes of this network were weighted according to the z-score transformed data of their real gene expression across the six stages [Figure 5].…”

Mitochondrial background can explain variable costs of immune deployment

“…Further work is clearly needed to disentangle the physiological basis of this genetic association. It also suggests that the proportion of time spent active while alive offers a potential useful early warning signal for death [47][48][49].…”