A methylome-wide study of aging using massively parallel sequencing of the methyl-CpG-enriched genomic fraction from blood in over 700 subjects
The central importance of epigenetics to the aging process is increasingly being recognized. Here we perform a methylome-wide association study (MWAS) of aging in whole blood DNA from 718 individuals, aged 25-92 years (mean = 55). We sequenced the methyl-CpG-enriched genomic DNA fraction, averaging...
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| Veröffentlicht in: | Human molecular genetics 2014-03, Vol.23 (5), p.1175-1185 |
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| creator | McClay, Joseph L Aberg, Karolina A Clark, Shaunna L Nerella, Srilaxmi Kumar, Gaurav Xie, Lin Y Hudson, Alexandra D Harada, Aki Hultman, Christina M Magnusson, Patrik K E Sullivan, Patrick F Van Den Oord, Edwin J C G |
| description | The central importance of epigenetics to the aging process is increasingly being recognized. Here we perform a methylome-wide association study (MWAS) of aging in whole blood DNA from 718 individuals, aged 25-92 years (mean = 55). We sequenced the methyl-CpG-enriched genomic DNA fraction, averaging 67.3 million reads per subject, to obtain methylation measurements for the ∼27 million autosomal CpGs in the human genome. Following extensive quality control, we adaptively combined methylation measures for neighboring, highly-correlated CpGs into 4 344 016 CpG blocks with which we performed association testing. Eleven age-associated differentially methylated regions (DMRs) passed Bonferroni correction (P-value < 1.15 × 10(-8)). Top findings replicated in an independent sample set of 558 subjects using pyrosequencing of bisulfite-converted DNA (min P-value < 10(-30)). To examine biological themes, we selected 70 DMRs with false discovery rate of |
| doi_str_mv | 10.1093/hmg/ddt511 |
| format | Article |
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Here we perform a methylome-wide association study (MWAS) of aging in whole blood DNA from 718 individuals, aged 25-92 years (mean = 55). We sequenced the methyl-CpG-enriched genomic DNA fraction, averaging 67.3 million reads per subject, to obtain methylation measurements for the ∼27 million autosomal CpGs in the human genome. Following extensive quality control, we adaptively combined methylation measures for neighboring, highly-correlated CpGs into 4 344 016 CpG blocks with which we performed association testing. Eleven age-associated differentially methylated regions (DMRs) passed Bonferroni correction (P-value < 1.15 × 10(-8)). Top findings replicated in an independent sample set of 558 subjects using pyrosequencing of bisulfite-converted DNA (min P-value < 10(-30)). To examine biological themes, we selected 70 DMRs with false discovery rate of <0.1. Of these, 42 showed hypomethylation and 28 showed hypermethylation with age. Hypermethylated DMRs were more likely to overlap with CpG islands and shores. Hypomethylated DMRs were more likely to be in regions associated with polycomb/regulatory proteins (e.g. EZH2) or histone modifications H3K27ac, H3K4m1, H3K4m2, H3K4m3 and H3K9ac. Among genes implicated by the top DMRs were protocadherins, homeobox genes, MAPKs and ryanodine receptors. Several of our DMRs are at genes with potential relevance for age-related disease. This study successfully demonstrates the application of next-generation sequencing to MWAS, by interrogating a large proportion of the methylome and returning potentially novel age DMRs, in addition to replicating several loci implicated in previous studies using microarrays.</description><identifier>ISSN: 0964-6906</identifier><identifier>EISSN: 1460-2083</identifier><identifier>DOI: 10.1093/hmg/ddt511</identifier><identifier>PMID: 24135035</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Adult ; Aged ; Aged, 80 and over ; Aging - genetics ; Computational Biology ; CpG Islands ; DNA - genetics ; DNA - metabolism ; DNA Methylation ; DNA-Binding Proteins - metabolism ; Epigenesis, Genetic ; Epigenomics ; Female ; Gene Regulatory Networks ; Genome-Wide Association Study ; High-Throughput Nucleotide Sequencing ; Humans ; Male ; Middle Aged ; Protein Binding ; Protein Interaction Maps ; Sex Factors ; Signal Transduction ; Transcription Factors - metabolism</subject><ispartof>Human molecular genetics, 2014-03, Vol.23 (5), p.1175-1185</ispartof><rights>The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com 2013</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c515t-a4c5ea154f8cb6f70d24622c05d45f078deece2add9936f7084235403dbfafe13</citedby><cites>FETCH-LOGICAL-c515t-a4c5ea154f8cb6f70d24622c05d45f078deece2add9936f7084235403dbfafe13</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,550,776,780,881,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24135035$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttp://kipublications.ki.se/Default.aspx?queryparsed=id:128383625$$DView record from Swedish Publication Index$$Hfree_for_read</backlink></links><search><creatorcontrib>McClay, Joseph L</creatorcontrib><creatorcontrib>Aberg, Karolina A</creatorcontrib><creatorcontrib>Clark, Shaunna L</creatorcontrib><creatorcontrib>Nerella, Srilaxmi</creatorcontrib><creatorcontrib>Kumar, Gaurav</creatorcontrib><creatorcontrib>Xie, Lin Y</creatorcontrib><creatorcontrib>Hudson, Alexandra D</creatorcontrib><creatorcontrib>Harada, Aki</creatorcontrib><creatorcontrib>Hultman, Christina M</creatorcontrib><creatorcontrib>Magnusson, Patrik K E</creatorcontrib><creatorcontrib>Sullivan, Patrick F</creatorcontrib><creatorcontrib>Van Den Oord, Edwin J C G</creatorcontrib><title>A methylome-wide study of aging using massively parallel sequencing of the methyl-CpG-enriched genomic fraction from blood in over 700 subjects</title><title>Human molecular genetics</title><addtitle>Hum Mol Genet</addtitle><description>The central importance of epigenetics to the aging process is increasingly being recognized. Here we perform a methylome-wide association study (MWAS) of aging in whole blood DNA from 718 individuals, aged 25-92 years (mean = 55). We sequenced the methyl-CpG-enriched genomic DNA fraction, averaging 67.3 million reads per subject, to obtain methylation measurements for the ∼27 million autosomal CpGs in the human genome. Following extensive quality control, we adaptively combined methylation measures for neighboring, highly-correlated CpGs into 4 344 016 CpG blocks with which we performed association testing. Eleven age-associated differentially methylated regions (DMRs) passed Bonferroni correction (P-value < 1.15 × 10(-8)). Top findings replicated in an independent sample set of 558 subjects using pyrosequencing of bisulfite-converted DNA (min P-value < 10(-30)). To examine biological themes, we selected 70 DMRs with false discovery rate of <0.1. Of these, 42 showed hypomethylation and 28 showed hypermethylation with age. Hypermethylated DMRs were more likely to overlap with CpG islands and shores. Hypomethylated DMRs were more likely to be in regions associated with polycomb/regulatory proteins (e.g. EZH2) or histone modifications H3K27ac, H3K4m1, H3K4m2, H3K4m3 and H3K9ac. Among genes implicated by the top DMRs were protocadherins, homeobox genes, MAPKs and ryanodine receptors. Several of our DMRs are at genes with potential relevance for age-related disease. This study successfully demonstrates the application of next-generation sequencing to MWAS, by interrogating a large proportion of the methylome and returning potentially novel age DMRs, in addition to replicating several loci implicated in previous studies using microarrays.</description><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Aging - genetics</subject><subject>Computational Biology</subject><subject>CpG Islands</subject><subject>DNA - genetics</subject><subject>DNA - metabolism</subject><subject>DNA Methylation</subject><subject>DNA-Binding Proteins - metabolism</subject><subject>Epigenesis, Genetic</subject><subject>Epigenomics</subject><subject>Female</subject><subject>Gene Regulatory Networks</subject><subject>Genome-Wide Association Study</subject><subject>High-Throughput Nucleotide Sequencing</subject><subject>Humans</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Protein Binding</subject><subject>Protein Interaction Maps</subject><subject>Sex Factors</subject><subject>Signal Transduction</subject><subject>Transcription Factors - metabolism</subject><issn>0964-6906</issn><issn>1460-2083</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>D8T</sourceid><recordid>eNqFks1q3DAUhUVpaKbTbvoARctScKNf_2wKYUiTQiCbdC1k6cpWaltTyZ4wT5FXroaZhmaVje5F59NB93IQ-kTJN0oaftGP3YW1s6T0DVpRUZKCkZq_RSvSlKIoG1Keo_cpPRBCS8Grd-icCcol4XKFni7xCHO_H8IIxaO3gNO82D0ODuvOTx1e0uEcdUp-B8Meb3XUwwADTvBngckc1AzPPZyMis32uoApetODxR1MYfQGu6jN7MOUmzDidgjBYj_hsIOIK0JwWtoHMHP6gM6cHhJ8PNU1-vXj6n5zU9zeXf_cXN4WRlI5F1oYCZpK4WrTlq4ilomSMUOkFdKRqrYABpi2tmn4Qa8F41IQblunHVC-RsXRNz3CdmnVNvpRx70K2qvT1e_cgZKspNljjb4f-ayMYA1Mc97Di2cvlcn3qgs7xRvaEMqywZeTQQx5cWlWo08GhkFPEJakqCSSC0alfB0VTUN5xeo6o1-PqIkhpQju-UeUqEM4VA6HOoYjw5__n-EZ_ZcG_hd1QLoT</recordid><startdate>20140301</startdate><enddate>20140301</enddate><creator>McClay, Joseph L</creator><creator>Aberg, Karolina A</creator><creator>Clark, Shaunna L</creator><creator>Nerella, Srilaxmi</creator><creator>Kumar, Gaurav</creator><creator>Xie, Lin Y</creator><creator>Hudson, Alexandra D</creator><creator>Harada, Aki</creator><creator>Hultman, Christina M</creator><creator>Magnusson, Patrik K E</creator><creator>Sullivan, Patrick F</creator><creator>Van Den Oord, Edwin J C G</creator><general>Oxford University Press</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>RC3</scope><scope>5PM</scope><scope>ADTPV</scope><scope>AOWAS</scope><scope>D8T</scope><scope>ZZAVC</scope></search><sort><creationdate>20140301</creationdate><title>A methylome-wide study of aging using massively parallel sequencing of the methyl-CpG-enriched genomic fraction from blood in over 700 subjects</title><author>McClay, Joseph L ; Aberg, Karolina A ; Clark, Shaunna L ; Nerella, Srilaxmi ; Kumar, Gaurav ; Xie, Lin Y ; Hudson, Alexandra D ; Harada, Aki ; Hultman, Christina M ; Magnusson, Patrik K E ; Sullivan, Patrick F ; Van Den Oord, Edwin J C G</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c515t-a4c5ea154f8cb6f70d24622c05d45f078deece2add9936f7084235403dbfafe13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Aging - genetics</topic><topic>Computational Biology</topic><topic>CpG Islands</topic><topic>DNA - genetics</topic><topic>DNA - metabolism</topic><topic>DNA Methylation</topic><topic>DNA-Binding Proteins - metabolism</topic><topic>Epigenesis, Genetic</topic><topic>Epigenomics</topic><topic>Female</topic><topic>Gene Regulatory Networks</topic><topic>Genome-Wide Association Study</topic><topic>High-Throughput Nucleotide Sequencing</topic><topic>Humans</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Protein Binding</topic><topic>Protein Interaction Maps</topic><topic>Sex Factors</topic><topic>Signal Transduction</topic><topic>Transcription Factors - metabolism</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>McClay, Joseph L</creatorcontrib><creatorcontrib>Aberg, Karolina A</creatorcontrib><creatorcontrib>Clark, Shaunna L</creatorcontrib><creatorcontrib>Nerella, Srilaxmi</creatorcontrib><creatorcontrib>Kumar, Gaurav</creatorcontrib><creatorcontrib>Xie, Lin Y</creatorcontrib><creatorcontrib>Hudson, Alexandra D</creatorcontrib><creatorcontrib>Harada, Aki</creatorcontrib><creatorcontrib>Hultman, Christina M</creatorcontrib><creatorcontrib>Magnusson, Patrik K E</creatorcontrib><creatorcontrib>Sullivan, Patrick F</creatorcontrib><creatorcontrib>Van Den Oord, Edwin J C G</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><collection>SwePub</collection><collection>SwePub Articles</collection><collection>SWEPUB Freely available online</collection><collection>SwePub Articles full text</collection><jtitle>Human molecular genetics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>McClay, Joseph L</au><au>Aberg, Karolina A</au><au>Clark, Shaunna L</au><au>Nerella, Srilaxmi</au><au>Kumar, Gaurav</au><au>Xie, Lin Y</au><au>Hudson, Alexandra D</au><au>Harada, Aki</au><au>Hultman, Christina M</au><au>Magnusson, Patrik K E</au><au>Sullivan, Patrick F</au><au>Van Den Oord, Edwin J C G</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A methylome-wide study of aging using massively parallel sequencing of the methyl-CpG-enriched genomic fraction from blood in over 700 subjects</atitle><jtitle>Human molecular genetics</jtitle><addtitle>Hum Mol Genet</addtitle><date>2014-03-01</date><risdate>2014</risdate><volume>23</volume><issue>5</issue><spage>1175</spage><epage>1185</epage><pages>1175-1185</pages><issn>0964-6906</issn><eissn>1460-2083</eissn><abstract>The central importance of epigenetics to the aging process is increasingly being recognized. Here we perform a methylome-wide association study (MWAS) of aging in whole blood DNA from 718 individuals, aged 25-92 years (mean = 55). We sequenced the methyl-CpG-enriched genomic DNA fraction, averaging 67.3 million reads per subject, to obtain methylation measurements for the ∼27 million autosomal CpGs in the human genome. Following extensive quality control, we adaptively combined methylation measures for neighboring, highly-correlated CpGs into 4 344 016 CpG blocks with which we performed association testing. Eleven age-associated differentially methylated regions (DMRs) passed Bonferroni correction (P-value < 1.15 × 10(-8)). Top findings replicated in an independent sample set of 558 subjects using pyrosequencing of bisulfite-converted DNA (min P-value < 10(-30)). To examine biological themes, we selected 70 DMRs with false discovery rate of <0.1. Of these, 42 showed hypomethylation and 28 showed hypermethylation with age. Hypermethylated DMRs were more likely to overlap with CpG islands and shores. Hypomethylated DMRs were more likely to be in regions associated with polycomb/regulatory proteins (e.g. EZH2) or histone modifications H3K27ac, H3K4m1, H3K4m2, H3K4m3 and H3K9ac. Among genes implicated by the top DMRs were protocadherins, homeobox genes, MAPKs and ryanodine receptors. Several of our DMRs are at genes with potential relevance for age-related disease. This study successfully demonstrates the application of next-generation sequencing to MWAS, by interrogating a large proportion of the methylome and returning potentially novel age DMRs, in addition to replicating several loci implicated in previous studies using microarrays.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>24135035</pmid><doi>10.1093/hmg/ddt511</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Adult Aged Aged, 80 and over Aging - genetics Computational Biology CpG Islands DNA - genetics DNA - metabolism DNA Methylation DNA-Binding Proteins - metabolism Epigenesis, Genetic Epigenomics Female Gene Regulatory Networks Genome-Wide Association Study High-Throughput Nucleotide Sequencing Humans Male Middle Aged Protein Binding Protein Interaction Maps Sex Factors Signal Transduction Transcription Factors - metabolism |
| title | A methylome-wide study of aging using massively parallel sequencing of the methyl-CpG-enriched genomic fraction from blood in over 700 subjects |
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