Biomarkers - Epigenetics & Biological Ageing
Epigenetics & Biological Ageing
This section documents molecular biomarkers related to biological ageing, including genome-wide DNA methylation and telomere length.
Epigenetics & Biological Ageing Biomarkers
Click each heading to expand details of this biomarker.
Overview
What is it? DNA methylation (DNAm) is an epigenetic modification involving the addition of methyl groups to DNA, predominantly at cytosine-phosphate-guanine (CpG) sites. It can influence gene regulation without altering the underlying DNA sequence. DNAm patterns vary across the genome and can change with age, environmental exposures, lifestyle and disease processes.
Research relevance: Genome-wide DNAm data can be used to investigate epigenetic variation and biological ageing, including epigenome-wide association studies (EWAS), epigenetic clocks and age acceleration, epigenetic surrogate biomarkers and stochastic epigenetic mutations. These measures can be examined in relation to exposures and ageing outcomes such as physical and cognitive function, frailty, disability and mortality.
Sample type: DNA extracted from frozen K2EDTA buffy coat
Sample Collection / Handling
DNA was extracted from 1 mL frozen K2EDTA buffy coat isolated from 10 mL of fresh whole blood. Whole blood was maintained at 2–4°C for 24–48 hours after collection before the buffy coat was frozen at −80°C.
Assay / Measurement
Method: Genome-wide DNA methylation profiling using the Illumina Infinium MethylationEPIC BeadChip (EPIC v1/850K or EPIC v2/950K). Data were pre-processed and quality controlled using the minfi package in R. Following quality control and restriction to CpG sites common to EPIC v1 and v2 arrays, 697,684 CpG sites were retained for analysis. Methylation at individual CpG sites is represented by beta values ranging from 0 (unmethylated) to 1 (fully methylated).
Equipment / analyser: Illumina Infinium MethylationEPIC BeadChip (EPIC v1/850K and EPIC v2/950K)
Laboratory: Italian Institute for Genomic Medicine, Turin, Italy (Wave 1 subset); Edinburgh Innovations, University of Edinburgh, Scotland (Waves 1, 3 and 6)
Measurement Characteristics
| Characteristic | Value |
|---|---|
| Units | Beta value (0–1; unitless) |
Collection Waves
| Biomarker | Wave 1 | Wave 2 | Wave 3 | Wave 4 | Wave 5 | Wave 6 |
|---|---|---|---|---|---|---|
| DNA Methylation | X | X | X |
Reference
- Jones, M.J., Goodman, S.J. and Kobor, M.S. (2015) ‘DNA methylation and healthy human aging’, Aging Cell, 14(6), pp. 924–932. doi:10.1111/acel.12349.
Example TILDA Papers
- McCrory C, McLoughlin S, O’Halloran AM. Socio-Economic Position Under the Microscope: Getting ‘Under the Skin’ and into the Cells. Curr Epidemiol Rep 6, 403–411 (2019). https://doi.org/10.1007/s40471-019-00217-1.
- McCrory C, Fiorito G, Hernandez B, et al. GrimAge Outperforms Other Epigenetic Clocks in the Prediction of Age-Related Clinical Phenotypes and All-Cause Mortality. J Gerontol A Biol Sci Med Sci. 2021;76(5):741-749. https://doi.org/10.1093/gerona/glaa286
- McCrory C, Fiorito G, O’Halloran AM, Polidoro S, Vineis P, Kenny RA. Early life adversity and age acceleration at mid-life and older ages indexed using the next-generation GrimAge and Pace of Aging epigenetic clocks. Psychoneuroendocrinology. 2022 Mar;137:105643. https://doi.org/10.1016/j.psyneuen.2021.105643
- Fiorito G, Polidoro S, Dugué PA, Kivimaki M, Ponzi E, Matullo G, Guarrera S, Assumma MB, Georgiadis P, Kyrtopoulos SA, Krogh V, Palli D, Panico S, Sacerdote C, Tumino R, Chadeau-Hyam M, Stringhini S, Severi G, Hodge AM, Giles GG, Marioni R, Karlsson Linnér R, O’Halloran AM, Kenny RA, Layte R, Baglietto L, Robinson O, McCrory C, Milne RL, Vineis P. Social adversity and epigenetic aging: a multi-cohort study on socioeconomic differences in peripheral blood DNA methylation. Sci Rep. 2017 Nov 24;7(1):16266. https://doi.org/10.1038/s41598-017-16391-5
Overview
What is it? Telomeres are repetitive DNA sequences located at the ends of chromosomes that help protect chromosome ends and maintain genomic stability. Telomeres generally shorten with successive cell divisions and with advancing age. Leukocyte telomere length (LTL) provides an estimate of telomere length in circulating white blood cells and is widely investigated as a marker of cellular and biological ageing.
Research relevance: Can be used to investigate cellular ageing and inter-individual differences in biological ageing. In ageing research, LTL can be examined in relation to chronological age, psychosocial and environmental exposures, socioeconomic factors, physical and cognitive function, chronic disease, frailty and mortality.
Sample type: DNA extracted from frozen K2EDTA buffy coat
Sample Collection / Handling
DNA was extracted from 1 mL frozen K2EDTA buffy coat isolated from 10 mL of fresh whole blood. Whole blood was maintained at 2–4°C for 24–48 hours after collection before the buffy coat was frozen at −80°C. Extracted DNA was dried and shipped to the IIGM laboratory for analysis.
Assay / Measurement
Method: Leukocyte telomere length was measured using monochrome multiplex quantitative PCR (MMQPCR), adapted to a 384-well plate format from Cawthon (2009). Telomere and albumin single-copy gene signals were quantified in triplicate and LTL was calculated as the mean telomere-to-single-copy-gene (T/S) ratio, providing an estimate of average telomere length per cell. Samples with replicate coefficients of variation >10% or unusually high or low results were repeated.
Equipment / analyser: CFX384 Touch Real-Time PCR Detection System (Bio-Rad); CFX Maestro Software (Bio-Rad)
Laboratory: Italian Institute for Genomic Medicine (IIGM), Turin, Italy
Measurement Characteristics
| Characteristic | Value |
|---|---|
| Units | T/S ratio (unitless) |
Collection Waves
| Biomarker | Wave 1 | Wave 2 | Wave 3 | Wave 4 | Wave 5 | Wave 6 |
|---|---|---|---|---|---|---|
| Telomere Length | X |
Reference
- Blackburn, E.H., Epel, E.S. and Lin, J. (2015) ‘Human telomere biology: a contributory and interactive factor in aging, disease risks, and protection’, Science, 350(6265), pp. 1193–1198. doi:10.1126/science.aab3389.
Example TILDA Papers
- De Looze C, McCrory C, O’Halloran A, Polidoro S, Kenny RA, Feeney J. Mind versus body: Perceived stress and biological stress are independently related to cognitive decline. Brain Behav Immun. 2024;115:696-704. https://doi.org/10.1016/j.bbi.2023.10.017
- McCrory C, McLoughlin S, O’Halloran AM. Socio-Economic Position Under the Microscope: Getting ‘Under the Skin’ and into the Cells. Curr Epidemiol Rep 6, 403–411 (2019). https://doi.org/10.1007/s40471-019-00217-1.