title: A methylome-wide study of aging using massively parallel sequencing of the methyl-CpG-enriched genomic fraction from blood in over 700 subjects.
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.
authors.affiliation: Center for Biomarker Research and Personalized Medicine, Virginia Commonwealth University, Richmond, VA 23298, USA.
authors.forename: Joseph L
authors.initials: JL
authors.lastname: McClay
authors.forename: Karolina A
authors.initials: KA
authors.lastname: Aberg
authors.forename: Shaunna L
authors.initials: SL
authors.lastname: Clark
authors.forename: Srilaxmi
authors.initials: S
authors.lastname: Nerella
authors.forename: Gaurav
authors.initials: G
authors.lastname: Kumar
authors.forename: Lin Y
authors.initials: LY
authors.lastname: Xie
authors.forename: Alexandra D
authors.initials: AD
authors.lastname: Hudson
authors.forename: Aki
authors.initials: A
authors.lastname: Harada
authors.forename: Christina M
authors.initials: CM
authors.lastname: Hultman
authors.forename: Patrik K E
authors.initials: PK
authors.lastname: Magnusson
authors.forename: Patrick F
authors.initials: PF
authors.lastname: Sullivan
authors.forename: Edwin J C G
authors.initials: EJ
authors.lastname: Van Den Oord
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000235:genetics*; D019295:Computational Biology; D018899:CpG Islands; D004247:DNA / Q000235:genetics / Q000378:metabolism; D019175:DNA Methylation; D004268:DNA-Binding Proteins / Q000378:metabolism; D044127:Epigenesis, Genetic; D057890:Epigenomics; D005260:Female; D053263:Gene Regulatory Networks; D055106:Genome-Wide Association Study; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D008297:Male; D008875:Middle Aged; D011485:Protein Binding; D060066:Protein Interaction Maps; D012737:Sex Factors; D015398:Signal Transduction; D014157:Transcription Factors / Q000378:metabolism
chemical_list: D004268:DNA-Binding Proteins; C066141:MBD1 protein, human; D014157:Transcription Factors; D004247:DNA