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The implications of relationships between human diseases and metabolic subpathways.

Li X, Li C, Shang D, Li J, Han J, Miao Y, Wang Y, Wang Q, Li W, Wu C, Zhang Y, Li X, Yao Q - PLoS ONE (2011)

Bottom Line: We also tested correlations between network topology and genes within disease-related metabolic subpathways, and found that within a disease-related subpathway in the DMSPN, the ratio of disease genes and the ratio of tissue-specific genes significantly increased as the number of diseases caused by the subpathway increased.Surprisingly, the ratio of essential genes significantly decreased and the ratio of housekeeping genes remained relatively unchanged.The results indicated that those genes intensely influenced by disease genes, including essential genes and tissue-specific genes, might be significantly associated with the disease diversity of subpathways, suggesting that different kinds of genes within a disease-related subpathway may play significantly differential roles on the diversity of diseases caused by the corresponding subpathway.

View Article: PubMed Central - PubMed

Affiliation: Bio-Pharmaceutical Key Laboratory of Heilongjiang Province, and College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. lixia@hrbmu.edu.cn

ABSTRACT
One of the challenging problems in the etiology of diseases is to explore the relationships between initiation and progression of diseases and abnormalities in local regions of metabolic pathways. To gain insight into such relationships, we applied the "k-clique" subpathway identification method to all disease-related gene sets. For each disease, the disease risk regions of metabolic pathways were then identified and considered as subpathways associated with the disease. We finally built a disease-metabolic subpathway network (DMSPN). Through analyses based on network biology, we found that a few subpathways, such as that of cytochrome P450, were highly connected with many diseases, and most belonged to fundamental metabolisms, suggesting that abnormalities of fundamental metabolic processes tend to cause more types of diseases. According to the categories of diseases and subpathways, we tested the clustering phenomenon of diseases and metabolic subpathways in the DMSPN. The results showed that both disease nodes and subpathway nodes displayed slight clustering phenomenon. We also tested correlations between network topology and genes within disease-related metabolic subpathways, and found that within a disease-related subpathway in the DMSPN, the ratio of disease genes and the ratio of tissue-specific genes significantly increased as the number of diseases caused by the subpathway increased. Surprisingly, the ratio of essential genes significantly decreased and the ratio of housekeeping genes remained relatively unchanged. Furthermore, the coexpression levels between disease genes and other types of genes were calculated for each subpathway in the DMSPN. The results indicated that those genes intensely influenced by disease genes, including essential genes and tissue-specific genes, might be significantly associated with the disease diversity of subpathways, suggesting that different kinds of genes within a disease-related subpathway may play significantly differential roles on the diversity of diseases caused by the corresponding subpathway.

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Correlations between network topology and genes within disease-related metabolic subpathways.For each subpathway in the DMSPN, the degree of the subpathway and the ratio of different types of genes within the subpathway were calculated. Gray “×” symbols represent subpathways. Black horizontal lines are the average of the ratio of genes. Color points correspond to the binned ratio values and error bars correspond to the standard deviations of the binned ratio values. The linear regression model was used to test the trends in correlations and the significance of these trends was estimated. (A) The ratio of disease genes divided by all genes within the subpathways. (B) The ratio of essential genes divided by all genes in the subpathways. (C) The ratio of housekeeping genes divided by all genes in the subpathways. (D) The ratio of tissue-specific genes divided by all genes in the subpathways.
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pone-0021131-g006: Correlations between network topology and genes within disease-related metabolic subpathways.For each subpathway in the DMSPN, the degree of the subpathway and the ratio of different types of genes within the subpathway were calculated. Gray “×” symbols represent subpathways. Black horizontal lines are the average of the ratio of genes. Color points correspond to the binned ratio values and error bars correspond to the standard deviations of the binned ratio values. The linear regression model was used to test the trends in correlations and the significance of these trends was estimated. (A) The ratio of disease genes divided by all genes within the subpathways. (B) The ratio of essential genes divided by all genes in the subpathways. (C) The ratio of housekeeping genes divided by all genes in the subpathways. (D) The ratio of tissue-specific genes divided by all genes in the subpathways.

Mentions: Many diseases, especially complex diseases, are usually related to disruption of underlying functions in metabolic subpathways. Most of the biological functions of a metabolic subpathway are carried out by biochemical interactions between gene products within subpathways. Therefore, involvement of a high proportion of disease genes in a subpathway might increase the possibility of disruption of the corresponding subpathway, finally leading to more diseases. To examine this, we measured the ratio of the number of disease genes to the number of total genes within each subpathway of the DMSPN. We found that the ratio significantly increased as the degree of a subpathway increased (P-value<2.2e–16; Figure 6A). Moreover, there were on average 20 disease genes in a disease-related subpathway, representing 36.3% of the total genes in a subpathway. These suggested that subpathways associated with more diseases tend to contain higher ratios of disease genes. Similarly, metabolic subpathway regions with a high ratio of disease genes also tend to cause more types of diseases due to the high positive correlation between degree and disease diversity of the subpathway node (see Figure S3).


The implications of relationships between human diseases and metabolic subpathways.

Li X, Li C, Shang D, Li J, Han J, Miao Y, Wang Y, Wang Q, Li W, Wu C, Zhang Y, Li X, Yao Q - PLoS ONE (2011)

Correlations between network topology and genes within disease-related metabolic subpathways.For each subpathway in the DMSPN, the degree of the subpathway and the ratio of different types of genes within the subpathway were calculated. Gray “×” symbols represent subpathways. Black horizontal lines are the average of the ratio of genes. Color points correspond to the binned ratio values and error bars correspond to the standard deviations of the binned ratio values. The linear regression model was used to test the trends in correlations and the significance of these trends was estimated. (A) The ratio of disease genes divided by all genes within the subpathways. (B) The ratio of essential genes divided by all genes in the subpathways. (C) The ratio of housekeeping genes divided by all genes in the subpathways. (D) The ratio of tissue-specific genes divided by all genes in the subpathways.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3117879&req=5

pone-0021131-g006: Correlations between network topology and genes within disease-related metabolic subpathways.For each subpathway in the DMSPN, the degree of the subpathway and the ratio of different types of genes within the subpathway were calculated. Gray “×” symbols represent subpathways. Black horizontal lines are the average of the ratio of genes. Color points correspond to the binned ratio values and error bars correspond to the standard deviations of the binned ratio values. The linear regression model was used to test the trends in correlations and the significance of these trends was estimated. (A) The ratio of disease genes divided by all genes within the subpathways. (B) The ratio of essential genes divided by all genes in the subpathways. (C) The ratio of housekeeping genes divided by all genes in the subpathways. (D) The ratio of tissue-specific genes divided by all genes in the subpathways.
Mentions: Many diseases, especially complex diseases, are usually related to disruption of underlying functions in metabolic subpathways. Most of the biological functions of a metabolic subpathway are carried out by biochemical interactions between gene products within subpathways. Therefore, involvement of a high proportion of disease genes in a subpathway might increase the possibility of disruption of the corresponding subpathway, finally leading to more diseases. To examine this, we measured the ratio of the number of disease genes to the number of total genes within each subpathway of the DMSPN. We found that the ratio significantly increased as the degree of a subpathway increased (P-value<2.2e–16; Figure 6A). Moreover, there were on average 20 disease genes in a disease-related subpathway, representing 36.3% of the total genes in a subpathway. These suggested that subpathways associated with more diseases tend to contain higher ratios of disease genes. Similarly, metabolic subpathway regions with a high ratio of disease genes also tend to cause more types of diseases due to the high positive correlation between degree and disease diversity of the subpathway node (see Figure S3).

Bottom Line: We also tested correlations between network topology and genes within disease-related metabolic subpathways, and found that within a disease-related subpathway in the DMSPN, the ratio of disease genes and the ratio of tissue-specific genes significantly increased as the number of diseases caused by the subpathway increased.Surprisingly, the ratio of essential genes significantly decreased and the ratio of housekeeping genes remained relatively unchanged.The results indicated that those genes intensely influenced by disease genes, including essential genes and tissue-specific genes, might be significantly associated with the disease diversity of subpathways, suggesting that different kinds of genes within a disease-related subpathway may play significantly differential roles on the diversity of diseases caused by the corresponding subpathway.

View Article: PubMed Central - PubMed

Affiliation: Bio-Pharmaceutical Key Laboratory of Heilongjiang Province, and College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. lixia@hrbmu.edu.cn

ABSTRACT
One of the challenging problems in the etiology of diseases is to explore the relationships between initiation and progression of diseases and abnormalities in local regions of metabolic pathways. To gain insight into such relationships, we applied the "k-clique" subpathway identification method to all disease-related gene sets. For each disease, the disease risk regions of metabolic pathways were then identified and considered as subpathways associated with the disease. We finally built a disease-metabolic subpathway network (DMSPN). Through analyses based on network biology, we found that a few subpathways, such as that of cytochrome P450, were highly connected with many diseases, and most belonged to fundamental metabolisms, suggesting that abnormalities of fundamental metabolic processes tend to cause more types of diseases. According to the categories of diseases and subpathways, we tested the clustering phenomenon of diseases and metabolic subpathways in the DMSPN. The results showed that both disease nodes and subpathway nodes displayed slight clustering phenomenon. We also tested correlations between network topology and genes within disease-related metabolic subpathways, and found that within a disease-related subpathway in the DMSPN, the ratio of disease genes and the ratio of tissue-specific genes significantly increased as the number of diseases caused by the subpathway increased. Surprisingly, the ratio of essential genes significantly decreased and the ratio of housekeeping genes remained relatively unchanged. Furthermore, the coexpression levels between disease genes and other types of genes were calculated for each subpathway in the DMSPN. The results indicated that those genes intensely influenced by disease genes, including essential genes and tissue-specific genes, might be significantly associated with the disease diversity of subpathways, suggesting that different kinds of genes within a disease-related subpathway may play significantly differential roles on the diversity of diseases caused by the corresponding subpathway.

Show MeSH
Related in: MedlinePlus