Analysis of cascading failure in gene networks

What causes sudden death in patients with chronic heart failure and a reduced ejection fraction?

Sudden death characterizes the mode of demise in 30–50% of patients with chronic heart failure and a reduced ejection fraction. Occasionally, these events have an identifiable pathophysiological trigger, e.g. myocardial infarction, catecholamine surges, or electrolyte imbalances, but in most circumstances, there is no acute precipitating mechanism. Instead, adverse left ventricular remodelling and fibrosis creates an exceptionally fragile and highly vulnerable substrate, which can be characterized using the model developed in theoretical physics of ‘self-organizing criticality’. This framework has been applied to describe the genesis of avalanches, nodes of traffic congestion unrelated to an accident, the abrupt system-wide failure of electrical grids, and the initiation of cancer and neurodegenerative diseases. Self-organizing criticality within the ventricular myocardium relies on complex adaptations to progressive stress and stretch, which evolve inevitably to an abrupt end (termed ‘cascading failure’), even though the rate of deterioration of the underlying disease process has not changed. The result is acute circulatory collapse (i.e. sudden death) in the absence of an identifiable triggering event. Cascading failure in a severely remodelled or fibrotic heart can become manifest electrically as a first-time ventricular tachyarrhythmia that is responsive to the shock delivered by an implantable cardioverter-defibrillator (ICD). Alternatively, it may present as an acute mechanical failure, which is manifest as (i) asystole, bradyarrhythmia, or electromechanical dissociation; or (ii) incessant ventricular fibrillation that persists despite repetitive ICD discharges; in both instances, the sudden deaths cannot be prevented by an ICD. This conceptual framework explains why anti-remodelling and antifibrotic interventions (i.e. neurohormonal antagonists and cardiac resynchronization) reduce the risk of sudden death in patients with heart failure in the absence of an ICD and provide incremental benefits in those with an ICD. The adoption of anti-remodelling and antifibrotic treatments may explain why the incidence of sudden death in clinical trials of heart failure has declined dramatically over the past 10–15 years, independent of the use of ICDs.

Hierarchical closeness efficiently predicts disease genes in a directed signaling network

BACKGROUND

Many structural centrality measures were proposed to predict putative disease genes on biological networks. Closeness is one of the best-known structural centrality measures, and its effectiveness for disease gene prediction on undirected biological networks has been frequently reported. However, it is not clear whether closeness is effective for disease gene prediction on directed biological networks such as signaling networks.

RESULTS

In this paper, we first show that closeness does not significantly outperform other well-known centrality measures such as Degree, Betweenness, and PageRank for disease gene prediction on a human signaling network. In addition, we observed that prediction accuracy by the closeness measure was worse than that by a reachability measure, but closeness could efficiently predict disease genes among a set of genes with the same reachability value. Based on this observation, we devised a novel structural measure, hierarchical closeness, by combining reachability and closeness such that all genes are first ranked by the degree of reachability and then the tied genes are further ranked by closeness. We discovered that hierarchical closeness outperforms other structural centrality measures in disease gene prediction. We also found that the set of highly ranked genes in terms of hierarchical closeness is clearly different from that of hub genes with high connectivity. More interestingly, these findings were consistently reproduced in a random Boolean network model. Finally, we found that genes with relatively high hierarchical closeness are significantly likely to encode proteins in the extracellular matrix and receptor proteins in a human signaling network, supporting the fact that half of all modern medicinal drugs target receptor-encoding genes.

CONCLUSION

Taken together, hierarchical closeness proposed in this study is a novel structural measure to efficiently predict putative disease genes in a directed signaling network.