Project description:Since their introduction, epigenetic clocks have been extensively used in aging and human disease research. In this study, we reveal an intriguing pattern: epigenetic age predictions display a 24-hour periodicity. These paradoxical age oscillations can be attributed to variations in blood cell type composition and epigenomes, both of which demonstrate circadian rhythmicity. This discovery emphasizes the significance of factoring-in the time of day to obtain accurate estimates of epigenetic age.
Project description:Since their introduction, epigenetic clocks have been extensively used in aging and human disease research. In this study, we reveal an intriguing pattern: epigenetic age predictions display a 24-hour periodicity. These paradoxical age oscillations can be attributed to variations in blood cell type composition and epigenomes, both of which demonstrate circadian rhythmicity. This discovery emphasizes the significance of factoring-in the time of day to obtain accurate estimates of epigenetic age.
Project description:Since their introduction, epigenetic clocks have been extensively used in aging and human disease research. In this study, we reveal an intriguing pattern: epigenetic age predictions display a 24-hour periodicity. These paradoxical age oscillations can be attributed to variations in blood cell type composition and epigenomes, both of which demonstrate circadian rhythmicity. This discovery emphasizes the significance of factoring-in the time of day to obtain accurate estimates of epigenetic age.
Project description:Since their introduction, epigenetic clocks have been extensively used in aging, human disease, and rejuvenation studies. In this article, we report an intriguing pattern: epigenetic age predictions display a 24-h periodicity. We tested a circadian blood sample collection using 17 epigenetic clocks addressing different aspects of aging. Thirteen clocks exhibited significant oscillations with the youngest and oldest age estimates around midnight and noon, respectively. In addition, daily oscillations were consistent with the changes of epigenetic age across different times of day observed in an independant populational dataset. While these oscillations can in part be attributed to variations in white blood cell type composition, cell count correction methods might not fully resolve the issue. Furthermore, some epigenetic clocks exhibited 24-h periodicity even in the purified fraction of neutrophils pointing at plausible contributions of intracellular epigenomic oscillations. Evidence for circadian variation in epigenetic clocks emphasizes the importance of the time-of-day for obtaining accurate estimates of epigenetic age.
Project description:Cannabis use has been controversial, largely having been designated a controlled substance over the last century. The link between cannabis smoking and disease pathogenesis may best be explored through DNA methylation, an epigentic mechanism. We investigated the relationship between epigenetic age and cannabis smoking in participants within the Canadian Cohort of Obstructive Lung Disease (CanCOLD) cohort (n=93) (ClinicalTrials.gov identifier NCT00920348). Blood samples were profiled for DNA methylation using the Illumina MethylationEPIC BeadChipv1 at two separate laboratories and the blood epigenetic age of each sample was calculated using the Clock Foundation tool (https://dnamage.clockfoundation.org). An ANOVA was used to identify differences in the age acceleration residuals associated with cannabis smoking status (never, former, and current), adjusted for chronological age, sex, body mass index (BMI), batch, cigarette smoking status, and the first two principal components of blood cell proportions. Our observations indicated that current cannabis smoking and higher joint-years exposure are associated with epigenetic age acceleration; cessation, however, may help to normalize in part this age acceleration.
Project description:In this study, we have optimized and directly compared epigenetic age predictors based on pyrosequencing, ddPCR and BBA-seq of specific age-associated regions. Bisulfite barcoded amplicon sequencing (BBA-seq) was performed on 9 genomic region of 77 human blood DNA and 11 genomic regions of 95 buccal swab DNA to measure age-associated regions for epigenetic age prediction. Furthermore, our data indicate that the correlation of age-associated DNAm with chronological age peaks close to CTCF binding sites. Age-associated DNAm is not coherently modified on individual DNA strands and this enabled alternative single-read age-predictors that reflect heterogeneity in epigenetic aging within a specimen.