Abstract
Modern network science has been used to reveal new and often fundamental aspects of brain network organization in physiological as well as pathological conditions. As a consequence, these discoveries, which relate to network hierarchy, hubs and network interactions, have begun to change the paradigms of neurodegenerative disorders. In this paper, we explore the use of thermodynamics for protein–protein network interactions in Alzheimer’s disease (AD), Parkinson’s disease (PD), multiple sclerosis (MS), traumatic brain injury and epilepsy. To assess the validity of using network interactions in neurological diseases, we investigated the relationship between network thermodynamics and molecular systems biology for these neurological disorders. In order to uncover whether there was a correlation between network organization and biological outcomes, we used publicly available RNA transcription data from individual patients with these neurological conditions, and correlated these molecular profiles with their respective individual disability scores. We found a linear correlation (Pearson correlation of −0.828) between disease disability (a clinically validated measurement of a person’s functional status) and Gibbs free energy (a thermodynamic measure of protein–protein interactions). In other words, we found an inverse relationship between disease disability and thermodynamic energy. Because a larger degree of disability correlated with a larger negative drop in Gibbs free energy in a linear disability-dependent fashion, it could be presumed that the progression of neuropathology such as is seen in Alzheimer’s disease could potentially be prevented by therapeutically correcting the changes in Gibbs free energy.
Highlights
Even though neurological impairment and its sequelae constitute over 6% of the global burden of disease [1], the management of neurological disorders has not significantly changed in the past few decades, and the mainstay of therapy remains focused on symptomatic management
We focus on proving that thermodynamics, i.e., the molecular changes defined by Gibbs free energy, can be correlated with disease state and progression
We have provided early evidence for using expression data, and connectivity/topology data obtained from the associated protein–protein interaction network (PPIN) for analysis of genomic information in neurodegenerative diseases
Summary
The treatment and management of neurological dysfunction/neurodegeneration is an area of great medical need. The World Health Organization (WHO) estimates that neurological disorders contribute 10.9% and 8.7% of the global disease burden in high- and medium-income countries, respectively [1]. As the average age of the populations in developed countries will increase in the coming decades, it is expected that the disease burden will continue to increase. The present treatment of neurological diseases constitutes, by and large, the management of disease symptoms, because the etiology remains unclear. In Alzheimer’s disease, for example, the earlier etiological hypothesis that amyloid deposits are caused by environmental stimuli is being supplanted by a growing
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