News and Recent Publications
Effect of long-term caloric restriction on DNA methylation measures of biological aging in healthy adults from the CALERIE trial
Waziry & Ryan et al. 2023 Nature Aging
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. Calorie 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 CALERIE™ Trial, a randomized controlled trial in which n=220 adults without obesity were randomized to 25% CR or ad-libitum (AL) control diet for 2 years10. 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.
DunedinPACE, a DNA methylation biomarker of the pace of aging
Belsky et al. 2022 eLife
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.
Socioeconomic Disadvantage and the Pace of Biological Aging in Children
Raffington et al. 2021 Pediatrics
BACKGROUND AND OBJECTIVES: Children who grow up in socioeconomic disadvantage face increased burden of disease and disability throughout their lives. One hypothesized mechanism for this increased burden is that early-life disadvantage accelerates biological processes of aging, increasing vulnerability to subsequent disease. To evaluate this hypothesis and the potential impact of preventive interventions, measures are needed that can quantify early acceleration of biological aging in childhood.
METHODS: Saliva DNA methylation and socioeconomic circumstances were measured in N = 600 children and adolescents aged 8 to 18 years (48% female) participating in the Texas Twin Project. We measured pace of biological aging using the DunedinPoAm DNA methylation algorithm, developed to quantify the pace-of-aging–related decline in system integrity. We tested if children in more disadvantaged families and neighborhoods exhibited a faster pace of aging as compared with children in more affluent contexts.
RESULTS: Children living in more disadvantaged families and neighborhoods exhibited a faster DunedinPoAm-measured pace of aging (r = 0.18; P = .001 for both). Latinx-identifying children exhibited a faster DunedinPoAm-measured pace of aging compared with both White- and Latinx White–identifying children, consistent with higher levels of disadvantage in this group. Children with more advanced pubertal development, higher BMI, and more tobacco exposure exhibited faster a faster DunedinPoAm-measured pace of aging. However, DunedinPoAm-measured pace of aging associations with socioeconomic disadvantage were robust to control for these factors.
CONCLUSIONS: Children growing up under conditions of socioeconomic disadvantage exhibit a faster pace of biological aging. DNA methylation pace of aging might be useful as a surrogate end point in evaluation of programs and policies to address the childhood social determinants of lifelong health disparities.
Social mobility and biological aging among older adults in the United States
Graf et al. 2022 PNAS Nexus
Lower socioeconomic status is associated with faster biological aging, the gradual and progressive decline in system integrity that accumulates with advancing age. Efforts to promote upward social mobility may, therefore, extend healthy lifespan. However, recent studies suggest that upward mobility may also have biological costs related to the stresses of crossing social boundaries. We tested associations of life-course social mobility with biological aging using data from participants in the 2016 Health and Retirement Study (HRS) Venous Blood Study who provided blood-chemistry (n = 9,255) and/or DNA methylation (DNAm) data (n = 3,976). We quantified social mobility from childhood to later-life using data on childhood family characteristics, educational attainment, and wealth accumulation. We quantified biological aging using 3 DNAm “clocks” and 3 blood-chemistry algorithms. We observed substantial social mobility among study participants. Those who achieved upward mobility exhibited less-advanced and slower biological aging. Associations of upward mobility with less-advanced and slower aging were consistent for blood-chemistry and DNAm measures of biological aging, and were similar for men and women and for Black and White Americans (Pearson-r effect-sizes ∼0.2 for blood-chemistry measures and the DNAm GrimAge clock and DunedinPoAm pace-of-aging measures; effect-sizes were smaller for the DNAm PhenoAge clock). Analysis restricted to educational mobility suggested differential effects by racial identity; mediating links between educational mobility and healthy aging may be disrupted by structural racism. In contrast, mobility producing accumulation of wealth appeared to benefit White and Black Americans equally, suggesting economic intervention to reduce wealth inequality may have potential to heal disparities in healthy aging.
Testing Black-White disparities in biological aging in older adults in the United States: analysis of DNA-methylation and blood-chemistry methods
Graf et al. 2021 American Journal of Epidemiology
Biological aging is a proposed mechanism through which social determinants drive health disparities. We conducted proof-of-concept testing of eight DNA-methylation and blood-chemistry quantifications of biological aging as mediators of disparities in healthspan between Black and White participants in the 2016 wave of the United States Health and Retirement Study (HRS; n=9005). We quantified biological aging from four DNA-methylation “clocks” (Horvath, Hannum, PhenoAge, and GrimAge), a DNA-methylation Pace of Aging (DunedinPoAm), and three blood-chemistry measures (PhenoAge, Klemera-Doubal method Biological Age, and homeostatic dysregulation). We quantified Black-White disparities in healthspan from cross-sectional and longitudinal data on physical-performance tests, self-reported activities of daily living (ADL) limitations and physician-diagnosed chronic diseases, self-rated health, and survival. DNA-methylation and blood-chemistry quantifications of biological aging were moderately correlated (Pearson-r range 0.1-0.4). GrimAge, DunedinPoAm and all three blood-chemistry measures were associated with healthspan characteristics (e.g. mortality effect-size range HR=1.71-2.32 per SD of biological aging) and showed evidence of more advanced/faster biological aging in Black compared with White participants (Cohen’s d=.4-.5). These measures accounted for 13-95% of Black-White differences in healthspan-related characteristics. Findings suggest that reducing disparities in biological aging can contribute to building health equity.
Associations of Loneliness and Social Isolation With Health Span and Life Span in the U.S. Health and Retirement Study
Crowe et al. 2021 Journals of Gerontology Series A
Background. Loneliness and social isolation are emerging public health challenges for aging populations.
Methods. We followed N = 11 302 U.S. Health and Retirement Study participants aged 50–95 from 2006 to 2014 to measure persistence of experiences of loneliness and exposure to social isolation. We tested associations of longitudinal loneliness and social isolation phenotypes with disability, morbidity, mortality, and biological aging through 2018.
Results. During follow-up, 18% of older adults met criteria for loneliness, with 6% meeting criteria at 2 or more follow-up assessments. For social isolation, these fractions were 21% and 8%. Health and Retirement Study participants who experienced loneliness and were exposed to social isolation were at increased risk for disease, disability, and mortality. Those experiencing persistent loneliness were at a 57% increased hazard of mortality compared to those who never experienced loneliness. For social isolation, the increase was 28%. Effect sizes were somewhat larger for counts of prevalent activity limitations and somewhat smaller for counts of prevalent chronic diseases. Covariate adjustment for socioeconomic and psychological risks attenuated but did not fully explain associations. Older adults who experienced loneliness and were exposed to social isolation also exhibited physiological indications of advanced biological aging (Cohen’s d for persistent loneliness and social isolation = 0.26 and 0.21, respectively). For loneliness, but not social isolation, persistence was associated with increased risk.
Conclusions. Deficits in social connectedness prevalent in a national sample of U.S. older adults were associated with morbidity, disability, and mortality and with more advanced biological aging. Bolstering social connectedness to interrupt experiences of loneliness may promote healthy aging.
A toolkit for quantification of biological age from blood chemistry and organ function test data: BioAge
Kwon & Belsky 2021 Geroscience
Methods to quantify biological aging are emerging as new measurement tools for epidemiology and population science and have been proposed as surrogate measures for healthy lifespan extension in geroscience clinical trials. Publicly available software packages to compute biological aging measurements from DNA methylation data have accelerated dissemination of these measures and generated rapid gains in knowledge about how different measures perform in a range of datasets. Biological age measures derived from blood chemistry data were introduced at the same time as the DNA methylation measures and, in multiple studies, demonstrate superior performance to these measures in prediction of healthy lifespan. However, their dissemination has been slow by comparison, resulting in a significant gap in knowledge. We developed a software package to help address this knowledge gap. The BioAge R package, available for download at GitHub (http://github.com/dayoonkwon/BioAge), implements three published methods to quantify biological aging based on analysis of chronological age and mortality risk: Klemera-Doubal biological age, PhenoAge, and homeostatic dysregulation. The package allows users to parametrize measurement algorithms using custom sets of biomarkers, to compare the resulting measurements to published versions of the Klemera-Doubal method and PhenoAge algorithms, and to score the measurements in new datasets. We applied BioAge to safety lab data from the CALERIE™ randomized controlled trial, the first-ever human trial of long-term calorie restriction in healthy, non-obese adults, to test effects of intervention on biological aging. Results contribute evidence that CALERIE intervention slowed biological aging. BioAge is a toolkit to facilitate measurement of biological age for geroscience.
Investigating the genetic architecture of noncognitive skills using GWAS-by-subtraction
Demange et al. 2021 Nature Genetics
Little is known about the genetic architecture of traits affecting educational attainment other than cognitive ability. We used genomic structural equation modeling and prior genome-wide association studies (GWASs) of educational attainment (n = 1,131,881) and cognitive test performance (n = 257,841) to estimate SNP associations with educational attainment variation that is independent of cognitive ability. We identified 157 genome-wide-significant loci and a polygenic architecture accounting for 57% of genetic variance in educational attainment. Noncognitive genetics were enriched in the same brain tissues and cell types as cognitive performance, but showed different associations with gray-matter brain volumes. Noncognitive genetics were further distinguished by associations with personality traits, less risky behavior and increased risk for certain psychiatric disorders. For socioeconomic success and longevity, noncognitive and cognitive-performance genetics demonstrated associations of similar magnitude. By conducting a GWAS of a phenotype that was not directly measured, we offer a view of genetic architecture of noncognitive skills influencing educational success.