Variations in the transcriptome of Alzheimer's disease reveal molecular networks involved in cardiovascular diseases - PubMed (original) (raw)
Variations in the transcriptome of Alzheimer's disease reveal molecular networks involved in cardiovascular diseases
Monika Ray et al. Genome Biol. 2008.
Abstract
Background: Because of its polygenic nature, Alzheimer's disease is believed to be caused not by defects in single genes, but rather by variations in a large number of genes and their complex interactions. A systems biology approach, such as the generation of a network of co-expressed genes and the identification of functional modules and cis-regulatory elements, to extract insights and knowledge from microarray data will lead to a better understanding of complex diseases such as Alzheimer's disease. In this study, we perform a series of analyses using co-expression networks, cis-regulatory elements, and functions of co-expressed gene modules to analyze single-cell gene expression data from normal and Alzheimer's disease-affected subjects.
Results: We identified six co-expressed gene modules, each of which represented a biological process perturbed in Alzheimer's disease. Alzheimer's disease-related genes, such as APOE, A2M, PON2 and MAP4, and cardiovascular disease-associated genes, including COMT, CBS and WNK1, all congregated in a single module. Some of the disease-related genes were hub genes while many of them were directly connected to one or more hub genes. Further investigation of this disease-associated module revealed cis-regulatory elements that match to the binding sites of transcription factors involved in Alzheimer's disease and cardiovascular disease.
Conclusion: Our results show the extensive links between Alzheimer's disease and cardiovascular disease at the co-expression and co-regulation levels, providing further evidence for the hypothesis that cardiovascular disease and Alzheimer's disease are linked. Our results support the notion that diseases in which the same set of biochemical pathways are affected may tend to co-occur with each other.
Figures
Figure 1
Steps taken to analyze Alzheimer's disease using laser capture microdissected microarray data. Sequence of steps taken to analyze incipient Alzheimer's disease from single cell expression data. We apply co-expression network analysis, EASE and WordSpy (motif finding method) in an integrated manner to study Alzheimer's disease and reveal connections to other conditions such as cardiovascular diseases and diabetes.
Figure 2
Unsupervised classification by principal component analysis. Principal component analysis was used to classify the 33 samples. The blue spheres refer to controls and the red correspond to affected subjects. This demonstrated that the samples were distinguishable based on the expression profiles of 1,663 differentially expressed genes.
Figure 3
Adjacency matrix of co-expression network. The adjacency matrix representation of the co-expression network. Modules are labeled c1, c2, c3, c4, c5 and c6. The dots refer to the intra- and inter-module edges between the genes. The graphical representation of this matrix is in Additional data file 4.
Figure 4
Pearson correlation coefficient between 1,663 genes. This figure shows the strength of correlation between pairs of genes. The genes are organized by modules - c1, c2, c3, c4, c5 and c6. The top leftmost red block on the diagonal corresponds to module c1 and the bottom rightmost red block on the same diagonal refers to module c6. Modules c1 and c2 contain upregulated genes and modules c3 through c6 comprise downregulated genes.
Figure 5
Sub-network in module 1 illustrating the 18 disease associated genes and their connections. This sub-network shows the 18 disease associated genes (colored yellow) and the genes that they are connected to within module 1. The hub genes are represented as triangle nodes. Disease genes MAP4, PON2 and ATP1A2 were also hub genes. Only the hub genes that connect to disease genes are shown here. Module 1 consists of 22 hub genes in total.
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