Socioeconomic position, lifestyle habits and biomarkers of epigenetic aging: a multi-cohort analysis

Fiorito, Giovanni; McCrory, Cathal; Robinson, Oliver; Carmeli, Cristian; Ochoa‐Rosales, Carolina; Zhang, Yan; Colicino, Elena; Dugué, Pierre Antoine; Artaud, Fanny; McKay, Gareth J.; Jeong, Ayoung; Mishra, Pashupati P.; Nøst, Therese Haugdahl; Krogh, Vittorio; Panico, Salvatore; Sacerdote, Carlotta; Tumino, Rosario; Palli, Domenico; Matullo, Giuseppe; Guarrera, Simonetta; Gandini, Martina; Bochud, Murielle; Dermitzakis, Emmanouil T.; Muka, Taulant; Schwartz, Joel; Vokonas, Pantel; Just, Allan C.; Hodge, Allison; Giles, Graham G.; Southey, Melissa C.; Hurme, Mikko; Young, Ian S.; McKnight, Amy Jayne; Kunze, Sonja; Waldenberger, Mélanie; Peters, Annette; Schwettmann, Lars; Lund, Eiliv; Baccarelli, Andrea A.; Milne, Roger L.; Kenny, Rose Anne; Elbaz, Alexis; Brenner, Hermann; Kee, Frank; Voortman, Trudy; Probst-Hensch, Nicole; Lehtimäki, Terho; Elliot, Paul; Stringhini, Silvia; Víneis, Paolo; Polidoro, Silvia

doi:10.18632/aging.101900

Cited by 172 publications

(195 citation statements)

References 56 publications

(56 reference statements)

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“…Age-adjusted measures of DNAm Telomere Length associated with incidence of ischemic heart disease. Our results replicate previous cross-sectional findings between DNAm PhenoAge and BMI, diabetes (19) and socioeconomic position (in a basic model) (26).…”

Section: Discussionsupporting

confidence: 90%

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Epigenetic clocks predict prevalence and incidence of leading causes of death and disease burden

Hillary

Stevenson

McCartney

et al. 2020

Preprint

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Individuals of the same chronological age display different rates of biological ageing. A number of measures of biological age have been proposed which harness age-related changes in DNA methylation profiles. These include methylation-based predictors of chronological age (HorvathAge, HannumAge), all-cause mortality (DNAm PhenoAge, DNAm GrimAge) and telomere length (DNAm Telomere Length). In this study, we test the association between these epigenetic markers of ageing and the prevalence and incidence of the leading causes of disease burden and mortality in highincome countries. Furthermore, we test the clocks' relationships with phenotypic measures associated with these conditions, including spirometric and biochemical traits. We carry out these analyses in 9,537 individuals from the Generation Scotland: Scottish Family Health Study. We find that DNAm GrimAge outperforms other epigenetic clocks in its associations with self-report disease prevalence and related clinical traits. DNAm GrimAge associates with chronic obstructive pulmonary disease (COPD) prevalence (Odds Ratio = 3.29, P = 3.0 x 10 -4 ) and pulmonary spirometry tests (β = [-0.10 to -0.15], P = [1.4 x 10 -4 to 1.4 x 10 -6 ]) at study baseline after adjusting for possibly confounding risk factors including alcohol, body mass index, deprivation, education and smoking. After adjusting for these confounding risk factors, DNAm GrimAge, DNAm PhenoAge and DNAm Telomere Length, measured at study baseline, predict incidence of ICD-10-coded disease states including COPD, type 2 diabetes and cardiovascular disease after thirteen years of follow-up (Hazard Ratios = [0.80 (telomere length)to 2.19 (GrimAge)], P = [9.9 x 10 -4 , 1.9 x 10 -14 ]). Our data show that despite accounting for several possible confounding variables, epigenetic markers of ageing predict incidence of common disease.This may have significant implications for their potential utility in clinical settings to complement goldstandard methods of clinical assessment and management.

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Section: Discussionsupporting

confidence: 90%

“…HannumAge) (23)(24)(25)(26)(27). However, no study has compared all major epigenetic clocks with respect to their association with a broad range of common health conditions.…”

Section: Introductionmentioning

confidence: 99%

Epigenetic clocks predict prevalence and incidence of leading causes of death and disease burden

Hillary

Stevenson

McCartney

et al. 2020

Preprint

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“…In addition, we found mixed evidence regarding the association of DNA methylation outlier burden and lifestyle variables. DNA methylation outlier burden has previously been linked to smoking [19] but not to BMI [12,19]. In Generation Scotland, higher DNA methylation outlier burden was found to be significantly positively associated with smoking pack-years and significantly negatively associated with BMI.…”

Section: Dna Methylation Outlier Burden Health and Survivalmentioning

confidence: 86%

“…Finally, we did not run analyses separately on outliers based on their direction, that is, 'high' outliers with abnormally high methylation levels and 'low' outliers with lower than average methylation levels [13]. We also did not investigate the functional pathways in which outliers may cluster (some work on this reported in [13,14,19]).…”

Section: Strengths and Limitationsmentioning

confidence: 99%

DNA methylation outlier burden, health, and ageing in Generation Scotland and the Lothian Birth Cohorts of 1921 and 1936

et al. 2020

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Background: DNA methylation outlier burden has been suggested as a potential marker of biological age. An outlier is typically defined as DNA methylation levels at any one CpG site that are three times beyond the interquartile range from the 25th or 75th percentiles compared to the rest of the population. DNA methylation outlier burden (the number of such outlier sites per individual) increases exponentially with age. However, these findings have been observed in small samples. Results: Here, we showed an association between age and log 10 -transformed DNA methylation outlier burden in a large cross-sectional cohort, the Generation Scotland Family Health Study (N = 7010, β = 0.0091, p < 2 × 10 −16 ), and in two longitudinal cohort studies, the Lothian Birth Cohorts of 1921 (N = 430, β = 0.033, p = 7.9 × 10 −4 ) and 1936 (N = 898, β = 0.0079, p = 0.074). Significant confounders of both cross-sectional and longitudinal associations between outlier burden and age included white blood cell proportions, body mass index (BMI), smoking, and batch effects. In Generation Scotland, the increase in epigenetic outlier burden with age was not purely an artefact of an increase in DNA methylation level variability with age (epigenetic drift). Log 10 -transformed DNA methylation outlier burden in Generation Scotland was not related to self-reported, or family history of, age-related diseases, and it was not heritable (SNP-based heritability of 4.4%, p = 0.18). Finally, DNA methylation outlier burden was not significantly related to survival in either of the Lothian Birth Cohorts individually or in the meta-analysis after correction for multiple testing (HR meta = 1.12; 95% CI meta = [1.02; 1.21]; p meta = 0.021).Conclusions: These findings suggest that, while it does not associate with ageing-related health outcomes, DNA methylation outlier burden does track chronological ageing and may also relate to survival. DNA methylation outlier burden may thus be useful as a marker of biological ageing.

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“…Epigenetic clocks raise hopes as a biomarker in forensic medicine, to determine donor age of an unknown specimen or of a person with allegedly unknown age (Horvath and Raj 2018). On the other hand, accelerated epigenetic aging has been shown to be associated with shorter life expectancy (Marioni et al 2015;Lin et al 2016;Zhang et al 2017;Lu et al 2019;Lund et al 2019), and it is liable to be affected by environmental exposure, gender, specific mutations and diseases (Fiorito et al 2019;Jeffries et al 2019;Martin-Herranz et al 2019). Therefore, epigenetic clocks seem to reflect aspects of biological age, which opens perspectives as a surrogate for intervention studies.…”

Section: Introductionmentioning

confidence: 99%

New Targeted Approaches for Epigenetic Age Predictions

Han

Franzen

Stiehl

et al. 2019

Preprint

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Aging causes epigenetic modifications, which are utilized as a biomarker for the aging process.While genome-wide DNA methylation profiles enable robust age-predictors by integration of many age-associated CG dinucleotides (CpGs), there are various alternative approaches for targeted measurements at specific CpGs that better support standardized and cost-effective highthroughput analysis. In this study, we utilized 4,650 Illumina BeadChip datasets of blood to select the best suited CpG sites for targeted analysis. DNA methylation analysis at these sites with either pyrosequencing or droplet digital PCR (ddPCR) revealed a high correlation with chronological age.In comparison, bisulfite barcoded amplicon sequencing (BBA-seq) gave slightly lower precision at individual CpGs. However, BBA-seq data revealed that the correlation of methylation levels with age at neighboring CpG sites follows a bell-shaped curve, often accompanied by a CTCF binding site at the peak. We demonstrate that within individual BBA-seq reads the DNA methylation at neighboring CpGs is not coherently modified but reveals a stochastic pattern. Based on this, we have developed an alternative model for epigenetic age predictions based on the binary sequel of methylated and non-methylated sites in individual reads, which reflects heterogeneity in epigenetic aging within a sample. Thus, the stochastic evolution of age-associated DNA methylation patterns, which seems to resemble epigenetic drift, enables epigenetic clocks for individual DNA strands.

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Socioeconomic position, lifestyle habits and biomarkers of epigenetic aging: a multi-cohort analysis

Cited by 172 publications

References 56 publications

Epigenetic clocks predict prevalence and incidence of leading causes of death and disease burden

Epigenetic clocks predict prevalence and incidence of leading causes of death and disease burden

DNA methylation outlier burden, health, and ageing in Generation Scotland and the Lothian Birth Cohorts of 1921 and 1936

New Targeted Approaches for Epigenetic Age Predictions

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