PMC:4718081 / 1184-6194 JSONTXT

{"target":"https://pubannotation.org/docs/sourcedb/PMC/sourceid/4718081","sourcedb":"PMC","sourceid":"4718081","source_url":"https://www.ncbi.nlm.nih.gov/pmc/4718081","text":"Introduction\nAlzheimer's disease (AD), the most common form of dementia, is characterized by a decline in cognitive ability (Ewers et al., 2012; Farah, 2014). Current estimates suggest that 36 million people worldwide have AD and the number is expected to almost triple in the next few decades (Grammas and Martinez, 2014). Since the symptomatic drugs currently on the market for AD have limited efficacy and only provides symptomatic relief without long-term cure, an important area to understand the disease progression and identify the potential vital pathological biomarkers for the progression has recently received increasing attention (Zhou et al., 2013; Salem et al., 2014).\nNeuropsychological tests such as Mini Mental State Examination (MMSE) and Clinical Dementia Rating (CDR) are widely used in the clinical evaluation of patients with suspected dementia (Powell et al., 2006). However, neuropsychological tests alone are inadequate to diagnose AD at the early stages (Zamrini et al., 2004). The biomarker-based assessment of AD has been proposed to enhance the clinical detection of AD in early prodromal stages of the disease (Dubois et al., 2007). The use of biomarkers in clinical diagnostics may help us to determine whether some mild cognitive impairment (MCI) symptoms are due to AD (Ewers et al., 2012).† Several researches have suggested that cerebrospinal fluid (CSF) based biomarkers are high precision risk factors in the disease process (Blennow and Hampel, 2003; Brys et al., 2009).\nAD has two major pathological hallmarks in CSF including senile plaques and neurofibrillary tangles (NFT) (Kimura et al., 2014). NFTs make up from intracellular aggregates of hyperphosphorylated tau protein (P-tau) and senile plaques consist mainly of amyloid β peptide (Aβ) (Small, 2008; Kimura et al., 2014). Previous researches have shown the interaction of tau, P-tau, and Aβ (Figure 1). On one hand, P-tau can increase activity of acetyl-cholinesterase (AChE). Then the increased AChE activity can elevate Aβ production by modulating the levels of the γ-secretase catalytic subunit presenilin-1 (PS1) (García-Ayllón et al., 2011). On the other hand, Aβ may affect the level of P-tau through two pathways. Firstly, Aβ can raise the activity of AChE which can activate the tau kinase glycogen synthase kinase-3β (GSK-3β) inducing tau hyperphosphorylation (García-Ayllón et al., 2011). Secondly, Aβ can activate the voltage-dependent Ca2+ channels (VVCD) and N-methyl-D-aspartic acid (NMDA) receptors which results in the release of intracellular Ca2+ (Shen et al., 2006; Bezprozvanny and Mattson, 2008). Then the increased levels of intracellular Ca2+ might initiate a signal transduction pathway to activate Ca2+-sensitive protein kinases which are responsible for the hyperphosphorylation of tau (Shen et al., 2006). Furthermore, previous researches have expounded the role of Aβ and tau pathology. On one hand, Aβ plays a vital role in progression of AD which may lead in turn to a series of downstream events ranging from synapse loss to plaque deposition to inflammation to the triggering of tau hyperphosphorylation to the death of susceptible neurons (Herrup, 2010). On the other hand, tau pathology plays a complicated role in the progression of AD. Tau pathology may affect DNA repair, neuronal activity, and inter-neuronal signaling (Hanger et al., 2014). Though the mechanism and roles of tau pathology are not yet fully elucidated, a consensus that the tau pathology can enhance cognitive decline and cause dementia is widely accepted (Salminen et al., 2011).\nFigure 1 The interaction of Aβ, tau, and P-tau. In this study, a cross-talk network is established by integrating the interactions among CSF biomarkers. As a complex biology system, cross-talk network has two properties. The first is small-worldness which means that most pairs of nodes can be linked to each other by relatively short chains (Maslov and Ispolatov, 2007; Zhao et al., 2010). Secondly, robustness is the capacity of keeping homeostasis under a range of condition which may be disrupted by disease (He et al., 2013; Nijhout and Reed, 2014).\nThe aim of this research is to provide novel insight into the progression from the perspective of crosstalk network disruption. Nevertheless, cross-talk network is a large complicated system, evaluating the entire network robustness is less practical. To address this issue, a simplified cross-talk network termed as mini network is established. The widely accepted key markers are selected to form the skeleton of the mini network. The cross-talk among key markers is modeled by transit compartments model. Robustness and the integral variation of the mini network are proposed to be used as a good proxy for complex disease progression. In our model, three mini network integral disruption parameters U, K, and φ are introduced to evaluate integral variation of the network and mini network disruption probability is employed to measure the robustness of mini 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