Analyzing the genes related to Alzheimer's disease via a network and pathway-based approach

Abstract

Background: Our understanding of the molecular mechanisms underlying Alzheimer's disease (AD) remains incomplete. Previous studies have revealed that genetic factors provide a significant contribution to the pathogenesis and development of AD. In the past years, numerous genes implicated in this disease have been identified via genetic association studies on candidate genes or at the genome-wide level. However, in many cases, the roles of these genes and their interactions in AD are still unclear. A comprehensive and systematic analysis focusing on the biological function and interactions of these genes in the context of AD will therefore provide valuable insights to understand the molecular features of the disease.

Method: In this study, we collected genes potentially associated with AD by screening publications on genetic association studies deposited in PubMed. The major biological themes linked with these genes were then revealed by function and biochemical pathway enrichment analysis, and the relation between the pathways was explored by pathway crosstalk analysis. Furthermore, the network features of these AD-related genes were analyzed in the context of human interactome and an AD-specific network was inferred using the Steiner minimal tree algorithm.

Results: We compiled 430 human genes reported to be associated with AD from 823 publications. Biological theme analysis indicated that the biological processes and biochemical pathways related to neurodevelopment, metabolism, cell growth and/or survival, and immunology were enriched in these genes. Pathway crosstalk analysis then revealed that the significantly enriched pathways could be grouped into three interlinked modules-neuronal and metabolic module, cell growth/survival and neuroendocrine pathway module, and immune response-related module-indicating an AD-specific immune-endocrine-neuronal regulatory network. Furthermore, an AD-specific protein network was inferred and novel genes potentially associated with AD were identified.

Conclusion: By means of network and pathway-based methodology, we explored the pathogenetic mechanism underlying AD at a systems biology level. Results from our work could provide valuable clues for understanding the molecular mechanism underlying AD. In addition, the framework proposed in this study could be used to investigate the pathological molecular network and genes relevant to other complex diseases or phenotypes.

Keywords: Alzheimer’s disease; Functional enrichment analysis; Network analysis; Pathway crosstalk.

Fig. 1

Crosstalk network amid Alzgset-overrepresented pathways. Vertices, biological pathways; lines, crosstalks among pathways. Width of one line (edge) shows direct proportion with the crosstalk level of a given pathway pair. Nodes tagged with numbers represent the following corresponding pathways: 1, intestinal immune network for IgA production; 2, toll-like receptor signaling pathway; 3, cytokine–cytokine receptor interaction; 4, hematopoietic cell lineage; 5, TNF signaling pathway; 6, apoptosis; 7, Fcε RI signaling pathway

Fig. 2

AD-specific protein network built by means of the Steiner minimal tree algorithm, including 496 vertices and 1521 lines. Circular vertices, genes of Alzgset; triangular vertices, expanding genes. Color of a typical vertex designates its corresponding degree under the background of the human protein interactome. Darkness of color for a vertex is directly proportional to the corresponding degree value (Color figure online)

Fig. 3

Main biochemical pathways related to AD. Numbers of genetics-based studies have revealed the fact that AD is actually a complex disorder. These major biochemical pathways involved in AD were connected based on their biological relations