An epigenetic map of age-associated autosomal loci in northern European families at high risk for the metabolic syndrome
Background The prevalence of chronic diseases such as cancer, type 2 diabetes, metabolic syndrome (MetS), and cardiovascular disease increases with age in all populations. Epigenetic features are hypothesized to play important roles in the pathophysiology of age-associated diseases, but a map of the...
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          | Published in | Clinical epigenetics Vol. 7; no. 1; p. 12 | 
|---|---|
| Main Authors | , , , , , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        London
          BioMed Central
    
        20.02.2015
     BioMed Central Ltd  | 
| Subjects | |
| Online Access | Get full text | 
| ISSN | 1868-7075 1868-7083 1868-7083  | 
| DOI | 10.1186/s13148-015-0048-6 | 
Cover
| Abstract | Background
The prevalence of chronic diseases such as cancer, type 2 diabetes, metabolic syndrome (MetS), and cardiovascular disease increases with age in all populations. Epigenetic features are hypothesized to play important roles in the pathophysiology of age-associated diseases, but a map of these markers is lacking. We searched for genome-wide age-associated methylation signatures in peripheral blood of individuals at high risks for MetS by profiling 485,000 CpG sites in 192 individuals of Northern European ancestry using the Illumina HM450 array. Subjects (ages 6–85 years) were part of seven extended families, and 73% of adults and 32% of children were overweight or obese.
Results
We found 22,122 genome-wide significant age-associated CpG sites (
P
α=0.05
 = 3.65 × 10
−7
after correction for multiple testing) of which 14,155 are positively associated with age while 7,967 are negatively associated. By applying a positional density-based clustering algorithm, we generated a map of epigenetic ‘hot-spots’ of age-associated genomic segments, which include 290 age-associated differentially methylated CpG clusters (aDMCs), of which 207 are positively associated with age. Gene/pathway enrichment analyses were performed on these clusters using FatiGO. Genes localized to both the positively (
n
 = 241) and negatively (
n
 = 16) age-associated clusters are significantly enriched in specific KEGG pathways and GO terms. The most significantly enriched pathways are the hedgehog signaling pathway (adjusted
P
 = 3.96 × 10
−3
) and maturity-onset diabetes of the young (MODY) (adjusted
P
 = 6.26 × 10
−3
) in the positive aDMCs and type I diabetes mellitus (adjusted
P
 = 3.69 × 10
−7
) in the negative aDMCs. We also identified several epigenetic loci whose age-associated change rates differ between subjects diagnosed with MetS and those without.
Conclusion
We conclude that in a family cohort at high risk for MetS, age-associated epigenetic features enrich in biological pathways important for determining the fate of fat cells and for insulin production. We also observe that several genes known to be related to MetS show differential epigenetic response to age in individuals with and without MetS. | 
    
|---|---|
| AbstractList | The prevalence of chronic diseases such as cancer, type 2 diabetes, metabolic syndrome (MetS), and cardiovascular disease increases with age in all populations. Epigenetic features are hypothesized to play important roles in the pathophysiology of age-associated diseases, but a map of these markers is lacking. We searched for genome-wide age-associated methylation signatures in peripheral blood of individuals at high risks for MetS by profiling 485,000 CpG sites in 192 individuals of Northern European ancestry using the Illumina HM450 array. Subjects (ages 6-85 years) were part of seven extended families, and 73% of adults and 32% of children were overweight or obese.
We found 22,122 genome-wide significant age-associated CpG sites (P α=0.05 = 3.65 × 10(-7) after correction for multiple testing) of which 14,155 are positively associated with age while 7,967 are negatively associated. By applying a positional density-based clustering algorithm, we generated a map of epigenetic 'hot-spots' of age-associated genomic segments, which include 290 age-associated differentially methylated CpG clusters (aDMCs), of which 207 are positively associated with age. Gene/pathway enrichment analyses were performed on these clusters using FatiGO. Genes localized to both the positively (n = 241) and negatively (n = 16) age-associated clusters are significantly enriched in specific KEGG pathways and GO terms. The most significantly enriched pathways are the hedgehog signaling pathway (adjusted P = 3.96 × 10(-3)) and maturity-onset diabetes of the young (MODY) (adjusted P = 6.26 × 10(-3)) in the positive aDMCs and type I diabetes mellitus (adjusted P = 3.69 × 10(-7)) in the negative aDMCs. We also identified several epigenetic loci whose age-associated change rates differ between subjects diagnosed with MetS and those without.
We conclude that in a family cohort at high risk for MetS, age-associated epigenetic features enrich in biological pathways important for determining the fate of fat cells and for insulin production. We also observe that several genes known to be related to MetS show differential epigenetic response to age in individuals with and without MetS. The prevalence of chronic diseases such as cancer, type 2 diabetes, metabolic syndrome (MetS), and cardiovascular disease increases with age in all populations. Epigenetic features are hypothesized to play important roles in the pathophysiology of age-associated diseases, but a map of these markers is lacking. We searched for genome-wide age-associated methylation signatures in peripheral blood of individuals at high risks for MetS by profiling 485,000 CpG sites in 192 individuals of Northern European ancestry using the Illumina HM450 array. Subjects (ages 6-85 years) were part of seven extended families, and 73% of adults and 32% of children were overweight or obese.BACKGROUNDThe prevalence of chronic diseases such as cancer, type 2 diabetes, metabolic syndrome (MetS), and cardiovascular disease increases with age in all populations. Epigenetic features are hypothesized to play important roles in the pathophysiology of age-associated diseases, but a map of these markers is lacking. We searched for genome-wide age-associated methylation signatures in peripheral blood of individuals at high risks for MetS by profiling 485,000 CpG sites in 192 individuals of Northern European ancestry using the Illumina HM450 array. Subjects (ages 6-85 years) were part of seven extended families, and 73% of adults and 32% of children were overweight or obese.We found 22,122 genome-wide significant age-associated CpG sites (P α=0.05 = 3.65 × 10(-7) after correction for multiple testing) of which 14,155 are positively associated with age while 7,967 are negatively associated. By applying a positional density-based clustering algorithm, we generated a map of epigenetic 'hot-spots' of age-associated genomic segments, which include 290 age-associated differentially methylated CpG clusters (aDMCs), of which 207 are positively associated with age. Gene/pathway enrichment analyses were performed on these clusters using FatiGO. Genes localized to both the positively (n = 241) and negatively (n = 16) age-associated clusters are significantly enriched in specific KEGG pathways and GO terms. The most significantly enriched pathways are the hedgehog signaling pathway (adjusted P = 3.96 × 10(-3)) and maturity-onset diabetes of the young (MODY) (adjusted P = 6.26 × 10(-3)) in the positive aDMCs and type I diabetes mellitus (adjusted P = 3.69 × 10(-7)) in the negative aDMCs. We also identified several epigenetic loci whose age-associated change rates differ between subjects diagnosed with MetS and those without.RESULTSWe found 22,122 genome-wide significant age-associated CpG sites (P α=0.05 = 3.65 × 10(-7) after correction for multiple testing) of which 14,155 are positively associated with age while 7,967 are negatively associated. By applying a positional density-based clustering algorithm, we generated a map of epigenetic 'hot-spots' of age-associated genomic segments, which include 290 age-associated differentially methylated CpG clusters (aDMCs), of which 207 are positively associated with age. Gene/pathway enrichment analyses were performed on these clusters using FatiGO. Genes localized to both the positively (n = 241) and negatively (n = 16) age-associated clusters are significantly enriched in specific KEGG pathways and GO terms. The most significantly enriched pathways are the hedgehog signaling pathway (adjusted P = 3.96 × 10(-3)) and maturity-onset diabetes of the young (MODY) (adjusted P = 6.26 × 10(-3)) in the positive aDMCs and type I diabetes mellitus (adjusted P = 3.69 × 10(-7)) in the negative aDMCs. We also identified several epigenetic loci whose age-associated change rates differ between subjects diagnosed with MetS and those without.We conclude that in a family cohort at high risk for MetS, age-associated epigenetic features enrich in biological pathways important for determining the fate of fat cells and for insulin production. We also observe that several genes known to be related to MetS show differential epigenetic response to age in individuals with and without MetS.CONCLUSIONWe conclude that in a family cohort at high risk for MetS, age-associated epigenetic features enrich in biological pathways important for determining the fate of fat cells and for insulin production. We also observe that several genes known to be related to MetS show differential epigenetic response to age in individuals with and without MetS. Background The prevalence of chronic diseases such as cancer, type 2 diabetes, metabolic syndrome (MetS), and cardiovascular disease increases with age in all populations. Epigenetic features are hypothesized to play important roles in the pathophysiology of age-associated diseases, but a map of these markers is lacking. We searched for genome-wide age-associated methylation signatures in peripheral blood of individuals at high risks for MetS by profiling 485,000 CpG sites in 192 individuals of Northern European ancestry using the Illumina HM450 array. Subjects (ages 6-85 years) were part of seven extended families, and 73% of adults and 32% of children were overweight or obese. Results We found 22,122 genome-wide significant age-associated CpG sites (P.sub.[alpha]=0.05 = 3.65 x 10.sup.-7 after correction for multiple testing) of which 14,155 are positively associated with age while 7,967 are negatively associated. By applying a positional density-based clustering algorithm, we generated a map of epigenetic 'hot-spots' of age-associated genomic segments, which include 290 age-associated differentially methylated CpG clusters (aDMCs), of which 207 are positively associated with age. Gene/pathway enrichment analyses were performed on these clusters using FatiGO. Genes localized to both the positively (n = 241) and negatively (n = 16) age-associated clusters are significantly enriched in specific KEGG pathways and GO terms. The most significantly enriched pathways are the hedgehog signaling pathway (adjusted P = 3.96 x 10.sup.-3) and maturity-onset diabetes of the young (MODY) (adjusted P = 6.26 x 10.sup.-3) in the positive aDMCs and type I diabetes mellitus (adjusted P = 3.69 x 10.sup.-7) in the negative aDMCs. We also identified several epigenetic loci whose age-associated change rates differ between subjects diagnosed with MetS and those without. Conclusion We conclude that in a family cohort at high risk for MetS, age-associated epigenetic features enrich in biological pathways important for determining the fate of fat cells and for insulin production. We also observe that several genes known to be related to MetS show differential epigenetic response to age in individuals with and without MetS. Keywords: Age, Epigenetics, MetS, T2D, Family study The prevalence of chronic diseases such as cancer, type 2 diabetes, metabolic syndrome (MetS), and cardiovascular disease increases with age in all populations. Epigenetic features are hypothesized to play important roles in the pathophysiology of age-associated diseases, but a map of these markers is lacking. We searched for genome-wide age-associated methylation signatures in peripheral blood of individuals at high risks for MetS by profiling 485,000 CpG sites in 192 individuals of Northern European ancestry using the Illumina HM450 array. Subjects (ages 6-85 years) were part of seven extended families, and 73% of adults and 32% of children were overweight or obese. We found 22,122 genome-wide significant age-associated CpG sites (P.sub.[alpha]=0.05 = 3.65 x 10.sup.-7 after correction for multiple testing) of which 14,155 are positively associated with age while 7,967 are negatively associated. By applying a positional density-based clustering algorithm, we generated a map of epigenetic 'hot-spots' of age-associated genomic segments, which include 290 age-associated differentially methylated CpG clusters (aDMCs), of which 207 are positively associated with age. Gene/pathway enrichment analyses were performed on these clusters using FatiGO. Genes localized to both the positively (n = 241) and negatively (n = 16) age-associated clusters are significantly enriched in specific KEGG pathways and GO terms. The most significantly enriched pathways are the hedgehog signaling pathway (adjusted P = 3.96 x 10.sup.-3) and maturity-onset diabetes of the young (MODY) (adjusted P = 6.26 x 10.sup.-3) in the positive aDMCs and type I diabetes mellitus (adjusted P = 3.69 x 10.sup.-7) in the negative aDMCs. We also identified several epigenetic loci whose age-associated change rates differ between subjects diagnosed with MetS and those without. We conclude that in a family cohort at high risk for MetS, age-associated epigenetic features enrich in biological pathways important for determining the fate of fat cells and for insulin production. We also observe that several genes known to be related to MetS show differential epigenetic response to age in individuals with and without MetS. Background The prevalence of chronic diseases such as cancer, type 2 diabetes, metabolic syndrome (MetS), and cardiovascular disease increases with age in all populations. Epigenetic features are hypothesized to play important roles in the pathophysiology of age-associated diseases, but a map of these markers is lacking. We searched for genome-wide age-associated methylation signatures in peripheral blood of individuals at high risks for MetS by profiling 485,000 CpG sites in 192 individuals of Northern European ancestry using the Illumina HM450 array. Subjects (ages 6–85 years) were part of seven extended families, and 73% of adults and 32% of children were overweight or obese. Results We found 22,122 genome-wide significant age-associated CpG sites ( P α=0.05 = 3.65 × 10 −7 after correction for multiple testing) of which 14,155 are positively associated with age while 7,967 are negatively associated. By applying a positional density-based clustering algorithm, we generated a map of epigenetic ‘hot-spots’ of age-associated genomic segments, which include 290 age-associated differentially methylated CpG clusters (aDMCs), of which 207 are positively associated with age. Gene/pathway enrichment analyses were performed on these clusters using FatiGO. Genes localized to both the positively ( n = 241) and negatively ( n = 16) age-associated clusters are significantly enriched in specific KEGG pathways and GO terms. The most significantly enriched pathways are the hedgehog signaling pathway (adjusted P = 3.96 × 10 −3 ) and maturity-onset diabetes of the young (MODY) (adjusted P = 6.26 × 10 −3 ) in the positive aDMCs and type I diabetes mellitus (adjusted P = 3.69 × 10 −7 ) in the negative aDMCs. We also identified several epigenetic loci whose age-associated change rates differ between subjects diagnosed with MetS and those without. Conclusion We conclude that in a family cohort at high risk for MetS, age-associated epigenetic features enrich in biological pathways important for determining the fate of fat cells and for insulin production. We also observe that several genes known to be related to MetS show differential epigenetic response to age in individuals with and without MetS.  | 
    
| ArticleNumber | 12 | 
    
| Audience | Academic | 
    
| Author | Kent, Jack W Carless, Melanie A Ali, Omar Zhang, Yi Blangero, John Cerjak, Diana James, Roland  | 
    
| Author_xml | – sequence: 1 givenname: Omar surname: Ali fullname: Ali, Omar organization: Department of Pediatrics, Medical College of Wisconsin – sequence: 2 givenname: Diana surname: Cerjak fullname: Cerjak, Diana organization: TOPS Obesity and Metabolic Research Center, Department of Medicine, Medical College of Wisconsin, Human and Molecular Genetics Center, Medical College of Wisconsin – sequence: 3 givenname: Jack W surname: Kent fullname: Kent, Jack W organization: Department of Genetics, Texas Biomedical Research Institute – sequence: 4 givenname: Roland surname: James fullname: James, Roland organization: TOPS Obesity and Metabolic Research Center, Department of Medicine, Medical College of Wisconsin, Human and Molecular Genetics Center, Medical College of Wisconsin – sequence: 5 givenname: John surname: Blangero fullname: Blangero, John organization: Department of Genetics, Texas Biomedical Research Institute – sequence: 6 givenname: Melanie A surname: Carless fullname: Carless, Melanie A organization: Department of Genetics, Texas Biomedical Research Institute – sequence: 7 givenname: Yi surname: Zhang fullname: Zhang, Yi email: yzhang@mcw.edu organization: TOPS Obesity and Metabolic Research Center, Department of Medicine, Medical College of Wisconsin, Human and Molecular Genetics Center, Medical College of Wisconsin  | 
    
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/25806089$$D View this record in MEDLINE/PubMed | 
    
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| Copyright | Ali et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( ) applies to the data made available in this article, unless otherwise stated. COPYRIGHT 2015 BioMed Central Ltd. Ali et al.; licensee BioMed Central. 2015  | 
    
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| Keywords | Epigenetics MetS Family study Age T2D  | 
    
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| PublicationDateYYYYMMDD | 2015-02-20 | 
    
| PublicationDate_xml | – month: 02 year: 2015 text: 2015-02-20 day: 20  | 
    
| PublicationDecade | 2010 | 
    
| PublicationPlace | London | 
    
| PublicationPlace_xml | – name: London – name: Germany  | 
    
| PublicationSubtitle | The official journal of the Clinical Epigenetics Society | 
    
| PublicationTitle | Clinical epigenetics | 
    
| PublicationTitleAbbrev | Clin Epigenet | 
    
| PublicationTitleAlternate | Clin Epigenetics | 
    
| PublicationYear | 2015 | 
    
| Publisher | BioMed Central BioMed Central Ltd  | 
    
| Publisher_xml | – name: BioMed Central – name: BioMed Central Ltd  | 
    
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| Snippet | Background
The prevalence of chronic diseases such as cancer, type 2 diabetes, metabolic syndrome (MetS), and cardiovascular disease increases with age in all... The prevalence of chronic diseases such as cancer, type 2 diabetes, metabolic syndrome (MetS), and cardiovascular disease increases with age in all... Background The prevalence of chronic diseases such as cancer, type 2 diabetes, metabolic syndrome (MetS), and cardiovascular disease increases with age in all...  | 
    
| SourceID | unpaywall pubmedcentral proquest gale pubmed crossref springer  | 
    
| SourceType | Open Access Repository Aggregation Database Index Database Enrichment Source Publisher  | 
    
| StartPage | 12 | 
    
| SubjectTerms | Biomedical and Life Sciences Biomedicine Cardiovascular diseases Chronic diseases Epigenetic inheritance Gene Function Genomes Genomics Human Genetics Methylation Type 2 diabetes  | 
    
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| Title | An epigenetic map of age-associated autosomal loci in northern European families at high risk for the metabolic syndrome | 
    
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