title: Intraindividual variation and short-term temporal trend in DNA methylation of human blood.
abstract: BACKGROUND
  Between- and within-person variation in DNA methylation levels are important parameters to be considered in epigenome-wide association studies. Temporal change is one source of within-person variation in DNA methylation that has been linked to aging and disease.
  
  
  METHODS
  We analyzed CpG-site-specific intraindividual variation and short-term temporal trend in leukocyte DNA methylation among 24 healthy Chinese women, with blood samples drawn at study entry and after 9 months. Illumina HumanMethylation450 BeadChip was used to measure methylation. Intraclass correlation coefficients (ICC) and trend estimates were summarized by genomic location and probe type.
  
  
  RESULTS
  The median ICC was 0.36 across nonsex chromosomes and 0.80 on the X chromosome. There was little difference in ICC profiles by genomic region and probe type. Among CpG loci with high variability between participants, more than 99% had ICC > 0.8. Statistically significant trend was observed in 10.9% CpG loci before adjustment for cell-type composition and in 3.4% loci after adjustment.
  
  
  CONCLUSIONS
  For CpG loci differentially methylated across subjects, methylation levels can be reliably assessed with one blood sample. More samples per subject are needed for low-variability and unmethylated loci. Temporal changes are largely driven by changes in cell-type composition of blood samples, but temporal trend unrelated to cell types is detected in a small percentage of CpG sites.
  
  
  CONCLUSIONS
  This study shows that one measurement can reliably assess methylation of differentially methylated CpG loci. Cancer Epidemiol Biomarkers Prev; 24(3); 490-7. ©2014 AACR.
authors.affiliation: University of Hawaii Cancer Center, Honolulu, Hawaii. yshvetso@cc.hawaii.edu.
authors.forename: Yurii B
authors.initials: YB
authors.lastname: Shvetsov
authors.affiliation: Comprehensive Cancer Center, Ohio State University and James Cancer Hospital, Columbus, Ohio.
authors.forename: Min-Ae
authors.initials: MA
authors.lastname: Song
authors.affiliation: Division of Epidemiology and Vanderbilt Epidemiology Center, Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee. Vanderbilt-Ingram Cancer Center, Nashville, Tennessee.
authors.forename: Qiuyin
authors.initials: Q
authors.lastname: Cai
authors.affiliation: University of Hawaii Cancer Center, Honolulu, Hawaii.
authors.forename: Maarit
authors.initials: M
authors.lastname: Tiirikainen
authors.affiliation: Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
authors.forename: Yong-Bing
authors.initials: YB
authors.lastname: Xiang
authors.affiliation: Division of Epidemiology and Vanderbilt Epidemiology Center, Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee. Vanderbilt-Ingram Cancer Center, Nashville, Tennessee.
authors.forename: Xiao-Ou
authors.initials: XO
authors.lastname: Shu
authors.affiliation: University of Hawaii Cancer Center, Honolulu, Hawaii.
authors.forename: Herbert
authors.initials: H
authors.lastname: Yu
mesh_terms: D000328:Adult; D000368:Aged; D001774:Blood Chemical Analysis / Q000379:methods*; D015331:Cohort Studies; D018899:CpG Islands; D004247:DNA / Q000097:blood* / Q000235:genetics*; D019175:DNA Methylation; D057890:Epigenomics; D005260:Female; D015894:Genome, Human; D006801:Humans; D008875:Middle Aged; D011446:Prospective Studies
chemical_list: D004247:DNA