<h2>Summary</h2> With the rapid expansion of aging biology research, the identification and evaluation of longevity interventions in humans have become key goals of this field. Biomarkers of aging are critically important tools in achieving these objectives over realistic time frames. However, the current lack of standards and consensus on the properties of a reliable aging biomarker hinders their further development and validation for clinical applications. Here, we advance a framework for the terminology and characterization of biomarkers of aging, including classification and potential clinical use cases. We discuss validation steps and highlight ongoing challenges as potential areas in need of future research. This framework sets the stage for the development of valid biomarkers of aging and their ultimate utilization in clinical trials and practice. 

Biomarkers of aging for the identification and evaluation of longevity interventions

Biological age is increased by stress and restored upon recovery

The geroscience hypothesis proposes that therapy to slow or reverse molecular changes that occur with aging can delay or prevent multiple chronic diseases and extend healthy lifespan1-3. Caloric restriction (CR), defined as lessening caloric intake without depriving essential nutrients4, results in changes in molecular processes that have been associated with aging, including DNA methylation (DNAm)5-7, and is established to increase healthy lifespan in multiple species8,9. Here we report the results of a post hoc analysis of the influence of CR on DNAm measures of aging in blood samples from the Comprehensive Assessment of Long-term Effects of Reducing Intake of Energy (CALERIE) trial, a randomized controlled trial in which n = 220 adults without obesity were randomized to 25% CR or ad libitum control diet for 2 yr (ref. 10). We found that CALERIE intervention slowed the pace of aging, as measured by the DunedinPACE DNAm algorithm, but did not lead to significant changes in biological age estimates measured by various DNAm clocks including PhenoAge and GrimAge. Treatment effect sizes were small. Nevertheless, modest slowing of the pace of aging can have profound effects on population health11-13. The finding that CR modified DunedinPACE in a randomized controlled trial supports the geroscience hypothesis, building on evidence from small and uncontrolled studies14-16 and contrasting with reports that biological aging may not be modifiable17. Ultimately, a conclusive test of the geroscience hypothesis will require trials with long-term follow-up to establish effects of intervention on primary healthy-aging endpoints, including incidence of chronic disease and mortality18-20. 

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Effect of long-term caloric restriction on DNA methylation measures of biological aging in healthy adults from the CALERIE trial

Validation of biomarkers of aging.

Significance In a nationally representative US adult population, measures of epigenetic age acceleration are associated with concurrent cognitive dysfunction, functional limitations and chronic conditions measured 2 y after DNA methylation measurement, and 4-y mortality. PC-based clocks do not significantly change the relationship between DNAm-based age acceleration and health outcomes. These findings suggest that along with demographic measures, SES, mental health, and health behaviors, epigenetic age acceleration serves as a useful tool to facilitate investigation into the biology of aging and helps in the prediction of later life morbidity and mortality.

Epigenetic-based age acceleration in a representative sample of older Americans: Associations with aging-related morbidity and mortality

Epigenetic clocks are widely used aging biomarkers calculated from DNA methylation data, but this data can be surprisingly unreliable. Here we show that technical noise produces deviations up to 9 years between replicates for six prominent epigenetic clocks, limiting their utility. We present a computational solution to bolster reliability, calculating principal components (PCs) from CpG-level data as input for biological age prediction. Our retrained PC versions of six clocks show agreement between most replicates within 1.5 years, improved detection of clock associations and intervention effects, and reliable longitudinal trajectories in vivo and in vitro. This method entails only one additional step compared to traditional clocks, requires no replicates or previous knowledge of CpG reliabilities for training, and can be applied to any existing or future epigenetic biomarker. The high reliability of PC-based clocks is critical for applications to personalized medicine, longitudinal tracking, in vitro studies and clinical trials of aging interventions. Epigenetic clocks are widely used aging biomarkers, but their utility is limited by technical noise. The authors report a method for producing high-reliability clocks for applications such as longitudinal studies and intervention trials. 

A computational solution for bolstering reliability of epigenetic clocks: implications for clinical trials and longitudinal tracking

Abstract Alzheimer’s disease (AD) risk increases exponentially with age and is associated with multiple molecular hallmarks of aging, one of which is epigenetic alterations. Epigenetic age predictors based on 5’ cytosine methylation (DNAm) have previously suggested that biological age acceleration may occur in AD brain tissue. To further investigate brain epigenetic aging in AD, we generated a novel age predictor termed PCBrainAge that was trained solely in cortical samples. This predictor utilizes a combination of principal components analysis and regularized regression, which reduces technical noise and greatly improves test-retest reliability. For further testing, we generated DNAm data from multiple brain regions in a sample from the Religious Orders Study and Rush Memory &amp; Aging Project. PCBrainAge captures meaningful heterogeneity of aging, calculated according to an individual’s age acceleration beyond expectation. Its acceleration demonstrates stronger associations with clinical AD dementia, pathologic AD, and APOE ε4 carrier status compared to extant epigenetic age predictors. It does so across multiple cortical and subcortical regions. Overall, PCBrainAge is useful for investigating heterogeneity in brain aging, as well as epigenetic alterations underlying AD risk and resilience. 

Aging the Brain: Multi-Region Methylation Principal Component Based Clock in the Context of Alzheimer’s Disease

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A computational solution for bolstering reliability of epigenetic clocks: implications for clinical trials and longitudinal tracking

Aging the Brain: Multi-Region Methylation Principal Component Based Clock in the Context of Alzheimer’s Disease