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. 2009 Sep;5(9):e1000521.
doi: 10.1371/journal.pcbi.1000521. Epub 2009 Sep 25.

Disease-aging network reveals significant roles of aging genes in connecting genetic diseases

Jiguang Wang  1 , Shihua Zhang, Yong Wang, Luonan Chen, Xiang-Sun Zhang
Affiliations

Disease-aging network reveals significant roles of aging genes in connecting genetic diseases

Jiguang Wang et al. PLoS Comput Biol. 2009 Sep.

Abstract

One of the challenging problems in biology and medicine is exploring the underlying mechanisms of genetic diseases. Recent studies suggest that the relationship between genetic diseases and the aging process is important in understanding the molecular mechanisms of complex diseases. Although some intricate associations have been investigated for a long time, the studies are still in their early stages. In this paper, we construct a human disease-aging network to study the relationship among aging genes and genetic disease genes. Specifically, we integrate human protein-protein interactions (PPIs), disease-gene associations, aging-gene associations, and physiological system-based genetic disease classification information in a single graph-theoretic framework and find that (1) human disease genes are much closer to aging genes than expected by chance; and (2) diseases can be categorized into two types according to their relationships with aging. Type I diseases have their genes significantly close to aging genes, while type II diseases do not. Furthermore, we examine the topological characters of the disease-aging network from a systems perspective. Theoretical results reveal that the genes of type I diseases are in a central position of a PPI network while type II are not; (3) more importantly, we define an asymmetric closeness based on the PPI network to describe relationships between diseases, and find that aging genes make a significant contribution to associations among diseases, especially among type I diseases. In conclusion, the network-based study provides not only evidence for the intricate relationship between the aging process and genetic diseases, but also biological implications for prying into the nature of human diseases.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. The disease-aging network (DAN) and its topological properties.
(A) A protein-protein interaction network connecting aging and disease. Non-disease aging genes are colored in grey and disease genes are colored by their types. MD in the figure means that the genes are involved in multiple gene sets. Refer to Materials and Methods for detailed information about aging genes and classification of disease genes. (B–D) Basic network features of disease aging network. Refer to Materials and Methods for detailed information about definition of network features. (E) Box plot for closeness centrality of disease and aging genes in DAN. Refer to Materials and Methods for detailed information about definition of different network centrality measures.
Figure 2
Figure 2. The further analysis of disease aging network (DAN).
(A) The number of vertexes of DAN is significantly larger than that of degree-conserved random networks (p-value <1.0e-6). (B) The number of edges of DAN is significantly larger than that of degree-conserved random networks (p-value <1.0e-10). The procedure to generate the random networks is described in Materials and Methods. (C) Comparison of average lengths of shortest paths among aging genes, disease genes, aging or disease genes, aging and disease genes, and random genes in the human protein interaction network from HPRD database. The normal distribution is used to fit the distance between genes. (D) Classification of aging genes by their supporting evidences in GenAge database. All aging genes are classified into eight types (x-axis). Types 1–6 are supported by direct and high-confident evidences while Types 7 and 8 are supported by indirect evidences. Given a particular type of aging gene, the difference of its percentages (y-axis) in the aging-disease overlap gene set and whole aging gene set indicates whether or not the aging gene set possesses potential bias to diseases.
Figure 3
Figure 3. The core network.
(A) The core network of DAN. Each node in the network is both related to aging and some kind of diseases. (B) The number of overlapping genes between aging and diseases in the human PPI network. (C) Pie graph to show number of genes in different diseases. (D) Grouping diseases into two groups: significant age-related diseases and others. Fold enrichment ratio (FER) is also marked when some disease is observed to be significant. Refer to Materials and Methods for detail. (E) Age-related diseases (ARD) show higher closeness centrality than non-age-related disease (NARD) genes. “Disease” means all disease genes, and “all genes” means all genes in the human PPI network. “mean hprd cc” stands for mean closeness centrality in the human PPI network.
Figure 4
Figure 4. Bridgeness of aging genes.
(A) The bridgeness of aging genes in every pair of diseases. Here, diseases are ordered by their FER (fold enrichment ratio), and minus 10-based logarithm p-value is showed in the figure where values larger than four set to be four. (B–C) Examples show the important functions of aging genes in connecting diseases. MD means that the genes are involved in multiple gene sets.
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