scholarly journals Author response: Quantification of the pace of biological aging in humans through a blood test, the DunedinPoAm DNA methylation algorithm

Author(s):  
Daniel W Belsky ◽  
Avshalom Caspi ◽  
Louise Arseneault ◽  
Andrea Baccarelli ◽  
David L Corcoran ◽  
...  
2021 ◽  
Author(s):  
Daniel W Belsky ◽  
Avshalom Caspi ◽  
David L Corcoran ◽  
Karen Sugden ◽  
Richie Poulton ◽  
...  

Measures to quantify changes in the pace of biological aging in response to intervention are needed to evaluate geroprotective interventions for humans. Here, we report an advance on our original method (Belsky et al. 2020). We used data from the Dunedin Study 1972-3 birth cohort tracking within-individual decline in 19 organ-system integrity indicators across four timepoints spanning two decades to model Pace of Aging. We distilled two-decade Pace of Aging into a single-time-point DNA-methylation blood-test using elastic-net regression and DNA-methylation data restricted to exclude probes with low test-retest reliability. The resulting measure, DunedinPACE, showed high test-retest reliability, was associated with functional decline, morbidity, and mortality, and indicated accelerated Pace of Aging in young adults with childhood adversity across five datasets. DunedinPACE effect-sizes were similar to GrimAge-clock effect-sizes and larger than those for other benchmark DNA-methylation-clocks. DunedinPACE is a novel blood biomarker of the pace of aging for gerontology and geroscience


eLife ◽  
2022 ◽  
Vol 11 ◽  
Author(s):  
Daniel W Belsky ◽  
Avshalom Caspi ◽  
David L Corcoran ◽  
Karen Sugden ◽  
Richie Poulton ◽  
...  

Background: Measures to quantify changes in the pace of biological aging in response to intervention are needed to evaluate geroprotective interventions for humans. Previously we showed that quantification of the pace of biological aging from a DNA-methylation blood test was possible (Belsky et al. 2020). Here we report a next-generation DNA-methylation biomarker of Pace of Aging, DunedinPACE (for Pace of Aging Calculated from the Epigenome).Methods: We used data from the Dunedin Study 1972-3 birth cohort tracking within-individual decline in 19 indicators of organ-system integrity across four time points spanning two decades to model Pace of Aging. We distilled this two-decade Pace of Aging into a single-time-point DNA-methylation blood-test using elastic-net regression and a DNA-methylation dataset restricted to exclude probes with low test-retest reliability. We evaluated the resulting measure, named DunedinPACE, in five additional datasets.Results: DunedinPACE showed high test-retest reliability, was associated with morbidity, disability, and mortality, and indicated faster aging in young adults with childhood adversity. DunedinPACE effect-sizes were similar to GrimAge Clock effect-sizes. In analysis of incident morbidity, disability, and mortality, DunedinPACE and added incremental prediction beyond GrimAge.Conclusions: DunedinPACE is a novel blood biomarker of the pace of aging for gerontology and geroscience.Funding: This research was supported by US-National Institute on Aging grants AG032282, AG061378, AG066887, and UK Medical Research Council grant MR/P005918/1.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Daniel L. McCartney ◽  
Josine L. Min ◽  
Rebecca C. Richmond ◽  
Ake T. Lu ◽  
Maria K. Sobczyk ◽  
...  

Abstract Background Biological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field. Results Leveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels. Conclusion This study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.


2020 ◽  
Author(s):  
Lacey W. Heinsberg ◽  
Mitali Ray ◽  
Yvette P. Conley ◽  
James M. Roberts ◽  
Arun Jeyabalan ◽  
...  

ABSTRACTBackgroundPreeclampsia is a leading cause of maternal and neonatal morbidity and mortality. Chronological age and race are associated with increased risk of preeclampsia; however, the pathophysiology of preeclampsia and how these risk factors impact its development, are not entirely understood. This gap precludes clinical interventions to prevent preeclampsia occurrence or to address stark racial disparities in maternal and neonatal outcomes. Of note, cellular aging rates can differ between individuals and chronological age is often a poor surrogate of biological age. DNA methylation age provides a marker of biological aging, and those with a DNA methylation age greater than their chronological age have ‘age acceleration’. Examining age acceleration in the context of preeclampsia status, and race, could strengthen our understanding of preeclampsia pathophysiology, inform future interventions to improve maternal/neonatal outcomes, and provide insight to racial disparities across pregnancy.ObjectivesThe purpose of this exploratory study was to examine associations between age acceleration, preeclampsia status, and race across pregnancy.Study designThis was a longitudinal, observational, case-control study of 56 pregnant individuals who developed preeclampsia (n=28) or were normotensive controls (n=28). Peripheral blood samples were collected at trimester-specific time points and genome-wide DNA methylation data were generated using the Infinium MethylationEPIC Beadchip. DNA methylation age was estimated using the Elastic Net ‘Improved Precision’ clock and age acceleration was computed as Δage, the difference between DNA methylation age and chronological age. DNA methylation age was compared with chronological age using scatterplots and Pearson correlations, while considering preeclampsia status and race. The relationships between preeclampsia status, race, and Δage were formally tested using multiple linear regression, while adjusting for pre-pregnancy body mass index, chronological age, and (chronological age)2. Regressions were performed both with and without consideration of cell-type heterogeneity.ResultsWe observed strong correlations between chronological age and DNA methylation age in all trimesters, ranging from R=0.91-0.95 in cases and R=0.86-0.90 in controls. We observed significantly stronger correlations between chronological age and DNA methylation age in White versus Black participants ranging from R=0.89-0.98 in White participants and R=0.77-0.83 in Black participants. We observed no association between Δage and preeclampsia status within trimesters. However, even while controlling for covariates, Δage was higher in trimester 1 in participants with higher pre-pregnancy BMI (β=0.12, 95% CI=0.02 to 0.22, p=0.02) and lower in Black participants relative to White participants in trimesters 2 (β=−2.68, 95% CI=−4.43 to −0.94, p=0.003) and 3 (β=−2.10, 95% CI=−4.03 to −0.17, p=0.03). When controlling for cell-type heterogeneity, the observations with BMI in trimester 1 and race in trimester 2 persisted.ConclusionsWe report no association between Δage and preeclampsia status, although there were associations with pre-pregnancy BMI and race. In particular, our findings in a small sample demonstrate the need for additional studies to not only investigate the complex pathophysiology of preeclampsia, but also the relationship between race and biological aging, which could provide further insight into racial disparities in pregnancy and birth. Future efforts to confirm these findings in larger samples, including exploration and applications of other epigenetic clocks, is needed.


2021 ◽  
Vol 7 ◽  
pp. 233372142110464
Author(s):  
Trevor Lohman ◽  
Gurinder Bains ◽  
Lee Berk ◽  
Everett Lohman

As healthspan and lifespan research breakthroughs have become more commonplace, the need for valid, practical markers of biological age is becoming increasingly paramount. The accessibility and affordability of biological age predictors that can reveal information about mortality and morbidity risk, as well as remaining years of life, has profound clinical and research implications. In this review, we examine 5 groups of aging biomarkers capable of providing accurate biological age estimations. The unique capabilities of these biomarkers have far reaching implications for the testing of both pharmaceutical and non-pharmaceutical interventions designed to slow or reverse biological aging. Additionally, the enhanced validity and availability of these tools may have increasingly relevant clinical value. The authors of this review explore those implications, with an emphasis on lifestyle modification research, and provide an overview of the current evidence regarding 5 biological age predictor categories: Telomere length, composite biomarkers, DNA methylation “epigenetic clocks,” transcriptional predictors of biological age, and functional age predictors.


2017 ◽  
Author(s):  
Meng Amy Li ◽  
Paulo P Amaral ◽  
Priscilla Cheung ◽  
Jan H Bergmann ◽  
Masaki Kinoshita ◽  
...  

2020 ◽  
Author(s):  
Yiyang Jiang ◽  
Jingfei Fu ◽  
Juan Du ◽  
Zhenhua Luo ◽  
Lijia Guo ◽  
...  

2019 ◽  
Vol 97 (11) ◽  
pp. 1090-1093
Author(s):  
Toyoki Maeda ◽  
Takahiko Horiuchi ◽  
Naoki Makino

Biological aging underlies lifestyle-related diseases. It can be assessed by measuring personal somatic cell telomere length. However, measuring the telomere length is laborious, and its clinical surrogate parameters have not been developed. This study analyzed the correlation between telomere length in peripheral leukocytes and laboratory data to select test items relating closely to biological aging. We established formulas from these clinical data to predict the personal telomere length. The subjects were patients having visited Kyushu University Beppu Hospital from 2012 to 2015. Two hundred and thirty-two patients were enrolled. The blood data were collected and telomere lengths were measured by Southern blotting method. The patients showed significant correlations between the telomere length and several blood test data with a sex-related difference. Candidate formulas are as follows: Predicted telomere length (kb) in men = 8.59 − 0.037 × Age (years) + 0.024 × Hemoglobin (g/dL); Predicted telomere length (kb) in women = 4.83 − 0.019 × Age (years) + 0.23 × Albumin (g/dL) + 0.0001 × White blood cells (/mm3) + 0.0020 × Red blood cells (× 104/mm3) + 0.0032 × Total cholesterol (mg/dL). Thus, the derived formulas allow for the accurate differential prediction of telomeric length in male and female patients.


Author(s):  
Neil Skjodt ◽  
Polina Mamoshina ◽  
Kirilli Kochetov ◽  
Franco Cortese ◽  
Anna Kovalchuk ◽  
...  

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