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Characterization of age signatures of DNA methylation in normal and cancer tissues from multiple studies.

Kim J, Kim K, Kim H, Yoon G, Lee K - BMC Genomics (2014)

Bottom Line: Genes related to the normal signature were enriched for aging-related gene ontology terms including metabolic processes, immune system processes, and cell proliferation.The related gene products of the normal signature had more than the average number of interacting partners in a protein interaction network and had a tendency not to interact directly with each other.The genomic sequences of the normal signature were well conserved and the age-associated DNAm levels could satisfactorily predict the chronological ages of tissues regardless of tissue type.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Informatics, Ajou University School of Medicine, Suwon 443-380, South Korea. kiylee@ajou.ac.kr.

ABSTRACT

Background: DNA methylation (DNAm) levels can be used to predict the chronological age of tissues; however, the characteristics of DNAm age signatures in normal and cancer tissues are not well studied using multiple studies.

Results: We studied approximately 4000 normal and cancer samples with multiple tissue types from diverse studies, and using linear and nonlinear regression models identified reliable tissue type-invariant DNAm age signatures. A normal signature comprising 127 CpG loci was highly enriched on the X chromosome. Age-hypermethylated loci were enriched for guanine-and-cytosine-rich regions in CpG islands (CGIs), whereas age-hypomethylated loci were enriched for adenine-and-thymine-rich regions in non-CGIs. However, the cancer signature comprised only 26 age-hypomethylated loci, none on the X chromosome, and with no overlap with the normal signature. Genes related to the normal signature were enriched for aging-related gene ontology terms including metabolic processes, immune system processes, and cell proliferation. The related gene products of the normal signature had more than the average number of interacting partners in a protein interaction network and had a tendency not to interact directly with each other. The genomic sequences of the normal signature were well conserved and the age-associated DNAm levels could satisfactorily predict the chronological ages of tissues regardless of tissue type. Interestingly, the age-associated DNAm increases or decreases of the normal signature were aberrantly accelerated in cancer samples.

Conclusion: These tissue type-invariant DNAm age signatures in normal and cancer can be used to address important questions in developmental biology and cancer research.

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Related in: MedlinePlus

Comparison of age-associated CpG loci across different studies with different tissue types. (A) Box plots of average methylation values (y-axis) per CpG unit in normal and cancer tissues across individual studies (x-axis). (B) Box plots of average methylation values per sample unit in normal or cancer tissue across individual studies. P-values were calculated by Kruskal–Wallis tests. (C, D) We checked the degree of overlap of age-associated CpG loci between studies by calculating the number of common CpG loci. We performed 100 age-permutation tests with the samples of individual studies to verify the significance of the degree of overlap. Hierarchical clustering results using the degree of overlap of age-associated CpG loci between different studies with different tissue types in normal (C) and cancer (D). P-value: a Z-test result using the distribution of 10,000 random selections.
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Fig3: Comparison of age-associated CpG loci across different studies with different tissue types. (A) Box plots of average methylation values (y-axis) per CpG unit in normal and cancer tissues across individual studies (x-axis). (B) Box plots of average methylation values per sample unit in normal or cancer tissue across individual studies. P-values were calculated by Kruskal–Wallis tests. (C, D) We checked the degree of overlap of age-associated CpG loci between studies by calculating the number of common CpG loci. We performed 100 age-permutation tests with the samples of individual studies to verify the significance of the degree of overlap. Hierarchical clustering results using the degree of overlap of age-associated CpG loci between different studies with different tissue types in normal (C) and cancer (D). P-value: a Z-test result using the distribution of 10,000 random selections.

Mentions: Individual studies included samples of various tissue types with different age ranges (Additional file 1: Table S1). Therefore, the average DNAm levels per CpG site were quite different between studies in both disease-free normal samples (P < 2.2e–300 using a Kruskal–Wallis test) and cancer samples (P < 2.2e–300) (Figure 3A). Similar results were also observed for the average DNAm levels per sample unit (Figure 3B). However, most study pairs with normal samples showed significantly greater degrees of overlap of age-associated CpG loci than would be expected by chance (Figure 3C). Moreover, the results of hierarchical clustering of the P-values of the degrees of overlap demonstrated that common age-associated CpG loci were independent of tissue or cell type. In the case of cancer samples, the degrees of overlap of age-associated CpG loci between study pairs were also significant, but less so than for normal samples (Figure 3D).Figure 3


Characterization of age signatures of DNA methylation in normal and cancer tissues from multiple studies.

Kim J, Kim K, Kim H, Yoon G, Lee K - BMC Genomics (2014)

Comparison of age-associated CpG loci across different studies with different tissue types. (A) Box plots of average methylation values (y-axis) per CpG unit in normal and cancer tissues across individual studies (x-axis). (B) Box plots of average methylation values per sample unit in normal or cancer tissue across individual studies. P-values were calculated by Kruskal–Wallis tests. (C, D) We checked the degree of overlap of age-associated CpG loci between studies by calculating the number of common CpG loci. We performed 100 age-permutation tests with the samples of individual studies to verify the significance of the degree of overlap. Hierarchical clustering results using the degree of overlap of age-associated CpG loci between different studies with different tissue types in normal (C) and cancer (D). P-value: a Z-test result using the distribution of 10,000 random selections.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4289351&req=5

Fig3: Comparison of age-associated CpG loci across different studies with different tissue types. (A) Box plots of average methylation values (y-axis) per CpG unit in normal and cancer tissues across individual studies (x-axis). (B) Box plots of average methylation values per sample unit in normal or cancer tissue across individual studies. P-values were calculated by Kruskal–Wallis tests. (C, D) We checked the degree of overlap of age-associated CpG loci between studies by calculating the number of common CpG loci. We performed 100 age-permutation tests with the samples of individual studies to verify the significance of the degree of overlap. Hierarchical clustering results using the degree of overlap of age-associated CpG loci between different studies with different tissue types in normal (C) and cancer (D). P-value: a Z-test result using the distribution of 10,000 random selections.
Mentions: Individual studies included samples of various tissue types with different age ranges (Additional file 1: Table S1). Therefore, the average DNAm levels per CpG site were quite different between studies in both disease-free normal samples (P < 2.2e–300 using a Kruskal–Wallis test) and cancer samples (P < 2.2e–300) (Figure 3A). Similar results were also observed for the average DNAm levels per sample unit (Figure 3B). However, most study pairs with normal samples showed significantly greater degrees of overlap of age-associated CpG loci than would be expected by chance (Figure 3C). Moreover, the results of hierarchical clustering of the P-values of the degrees of overlap demonstrated that common age-associated CpG loci were independent of tissue or cell type. In the case of cancer samples, the degrees of overlap of age-associated CpG loci between study pairs were also significant, but less so than for normal samples (Figure 3D).Figure 3

Bottom Line: Genes related to the normal signature were enriched for aging-related gene ontology terms including metabolic processes, immune system processes, and cell proliferation.The related gene products of the normal signature had more than the average number of interacting partners in a protein interaction network and had a tendency not to interact directly with each other.The genomic sequences of the normal signature were well conserved and the age-associated DNAm levels could satisfactorily predict the chronological ages of tissues regardless of tissue type.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Informatics, Ajou University School of Medicine, Suwon 443-380, South Korea. kiylee@ajou.ac.kr.

ABSTRACT

Background: DNA methylation (DNAm) levels can be used to predict the chronological age of tissues; however, the characteristics of DNAm age signatures in normal and cancer tissues are not well studied using multiple studies.

Results: We studied approximately 4000 normal and cancer samples with multiple tissue types from diverse studies, and using linear and nonlinear regression models identified reliable tissue type-invariant DNAm age signatures. A normal signature comprising 127 CpG loci was highly enriched on the X chromosome. Age-hypermethylated loci were enriched for guanine-and-cytosine-rich regions in CpG islands (CGIs), whereas age-hypomethylated loci were enriched for adenine-and-thymine-rich regions in non-CGIs. However, the cancer signature comprised only 26 age-hypomethylated loci, none on the X chromosome, and with no overlap with the normal signature. Genes related to the normal signature were enriched for aging-related gene ontology terms including metabolic processes, immune system processes, and cell proliferation. The related gene products of the normal signature had more than the average number of interacting partners in a protein interaction network and had a tendency not to interact directly with each other. The genomic sequences of the normal signature were well conserved and the age-associated DNAm levels could satisfactorily predict the chronological ages of tissues regardless of tissue type. Interestingly, the age-associated DNAm increases or decreases of the normal signature were aberrantly accelerated in cancer samples.

Conclusion: These tissue type-invariant DNAm age signatures in normal and cancer can be used to address important questions in developmental biology and cancer research.

Show MeSH
Related in: MedlinePlus