![]() ![]() ![]() This array has been reported to have low technical variability and high reproducibility ( 13), although a number of issues have been pointed out ( 14). ![]() In the present study of leukocyte DNA methylation among 24 healthy women, we examined CpG-site–specific intraindividual variation in DNA methylation and analyzed short-term temporal changes in DNA methylation using Illumina HumanMethylation450 BeadChip ( 13). A number of studies ( 8–11) have analyzed within-person variability of different blood biomarkers however, we are unaware of any reports on that in DNA methylation, although the importance of this aspect for epigenome-wide association studies has been recognized ( 12). Low values of ICC signify lower data reliability and may affect validity of analysis results. The ICC varies between 0 and 1, with high (low) proportion of within-person variation represented by values close to 0 (respectively, 1). The relative proportion of between- and within-person variability in the total variability is typically described by the intraclass correlation coefficient (ICC). Research into the role of DNA methylation in disease is affected by variability in measured methylation levels, which can be attributed to a number of sources: differences among study participants due to demographic, environmental and genetic factors random and systematic variation between samples taken from the same individual, which may result from differences in tissue sample composition or timing of sample collection technical variability due to measurement error and limited precision of analytic tools. Furthermore, the acquisition of methylation changes during aging could underlie the development of age-related pathologic conditions ( 7). Important cancer-related genes become hypermethylated during aging, including key developmental genes and those encoding the estrogen receptor, insulin growth factor, and E-cadherin ( 1, 6). A link has also been established between age-related and cancer-related methylation changes. Changes of methylation patterns have been seen in normal human aging process, and aberrant methylation changes in tissues such as blood have been linked to a number of diseases, including cancer ( 1–5). DNA methylation profile is established at neonatal stage and undergoes rapid change at the early age and further modifications throughout lifespan. DNA methylation marks are stable indicators of tissue lineage thus, different tissues have fundamentally different methylation patterns. ©2014 AACR.Įpigenetic modifications such as DNA methylation of cytosine residues at CpG dinucleotides have been extensively examined for their potential association with disease and aging in humans. Cancer Epidemiol Biomarkers Prev 24(3) 490–7. Impact: This study shows that one measurement can reliably assess methylation of differentially methylated CpG 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. More samples per subject are needed for low-variability and unmethylated loci. Statistically significant trend was observed in 10.9% CpG loci before adjustment for cell-type composition and in 3.4% loci after adjustment.Ĭonclusions: For CpG loci differentially methylated across subjects, methylation levels can be reliably assessed with one blood sample. Among CpG loci with high variability between participants, more than 99% had ICC > 0.8. There was little difference in ICC profiles by genomic region and probe type. Results: The median ICC was 0.36 across nonsex chromosomes and 0.80 on the X chromosome. Intraclass correlation coefficients (ICC) and trend estimates were summarized by genomic location and probe type. Illumina HumanMethylation450 BeadChip was used to measure methylation. ![]() 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. Temporal change is one source of within-person variation in DNA methylation that has been linked to aging and disease. Background: Between- and within-person variation in DNA methylation levels are important parameters to be considered in epigenome-wide association studies. ![]()
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