Educational Mobility, Pace of Aging, and Lifespan Among Participants in the Framingham Heart Study.

Importance: People who complete more education live longer lives with better health. New evidence suggests that these benefits operate through a slowed pace of biological aging. If so, measurements of the pace of biological aging could offer intermediate end points for studies of how interventions to promote education will affect healthy longevity. Objective: To test the hypothesis that upward educational mobility is associated with a slower pace of biological aging and increased longevity. Design, Setting, and Participants: This prospective cohort study analyzed data from 3 generations of participants in the Framingham Heart Study: (1) the original cohort, enrolled beginning in 1948; (2) the Offspring cohort, enrolled beginning in 1971; and (3) the Gen3 cohort, enrolled beginning in 2002. A 3-generation database was constructed to quantify intergenerational educational mobility. Mobility data were linked with blood DNA-methylation data collected from the Offspring cohort in 2005 to 2008 (n = 1652) and the Gen3 cohort in 2009 to 2011 (n = 1449). Follow-up is ongoing. Data analysis was conducted from June 2022 to November 2023 using data obtained from the National Institutes of Health database of Genotypes and Phenotypes (dbGaP). Exposure: Educational mobility was measured by comparing participants' educational outcomes with those of their parents. Main Outcomes and Measures: The pace of biological aging was measured from whole-blood DNA-methylation data using the DunedinPACE epigenetic clock. For comparison purposes, the analysis was repeated using 4 other epigenetic clocks. Survival follow-up was conducted through 2019. Results: This study analyzed data from 3101 participants from the Framingham Heart Study; 1652 were in the Offspring cohort (mean [SD] age, 65.57 [9.22] years; 764 [46.2%] male) and 1449 were in the Gen3 cohort (mean [SD] age, 45.38 [7.83] years; 691 [47.7%] male). Participants who were upwardly mobile in educational terms tended to have slower pace of aging in later life (r = -0.18 [95% CI, -0.23 to -0.13]; P < .001). This pattern of association was similar across generations and held in within-family sibling comparisons. There were 402 Offspring cohort participants who died over the follow-up period. Upward educational mobility was associated with lower mortality risk (hazard ratio, 0.89 [95% CI, 0.81 to 0.98]; P = .01). Slower pace of aging accounted for approximately half of this association. Conclusions and Relevance: This cohort study's findings support the hypothesis that interventions to promote educational attainment may slow the pace of biological aging and promote longevity. Epigenetic clocks have potential as near-term outcome measures of intervention effects on healthy aging. Experimental evidence is needed to confirm findings.

A blood biomarker of the pace of aging is associated with brain structure: replication across three cohorts.

Biological aging is the correlated decline of multi-organ system integrity central to the etiology of many age-related diseases. A novel epigenetic measure of biological aging, DunedinPACE, is associated with cognitive dysfunction, incident dementia, and mortality. Here, we tested for associations between DunedinPACE and structural MRI phenotypes in three datasets spanning midlife to advanced age: the Dunedin Study (age=45 years), the Framingham Heart Study Offspring Cohort (mean age=63 years), and the Alzheimer's Disease Neuroimaging Initiative (mean age=75 years). We also tested four additional epigenetic measures of aging: the Horvath clock, the Hannum clock, PhenoAge, and GrimAge. Across all datasets (total N observations=3380; total N individuals=2322), faster DunedinPACE was associated with lower total brain volume, lower hippocampal volume, greater burden of white matter microlesions, and thinner cortex. Across all measures, DunedinPACE and GrimAge had the strongest and most consistent associations with brain phenotypes. Our findings suggest that single timepoint measures of multi-organ decline such as DunedinPACE could be useful for gauging nervous system health.

Diet, Pace of Biological Aging, and Risk of Dementia in the Framingham Heart Study.

OBJECTIVE: People who eat healthier diets are less likely to develop dementia, but the biological mechanism of this protection is not well understood. We tested the hypothesis that healthy diet protects against dementia because it slows the pace of biological aging. METHODS: We analyzed Framingham Offspring Cohort data. We included participants ≥60 years-old, free of dementia and having dietary, epigenetic, and follow-up data. We assessed healthy diet as long-term adherence to the Mediterranean-Dash Intervention for Neurodegenerative Delay diet (MIND, over 4 visits spanning 1991-2008). We measured the pace of aging from blood DNA methylation data collected in 2005-2008 using the DunedinPACE epigenetic clock. Incident dementia and mortality were defined using study records compiled from 2005 to 2008 visit through 2018. RESULTS: Of n = 1,644 included participants (mean age 69.6, 54% female), n = 140 developed dementia and n = 471 died over 14 years of follow-up. Greater MIND score was associated with slower DunedinPACE and reduced risks for dementia and mortality. Slower DunedinPACE was associated with reduced risks for dementia and mortality. In mediation analysis, slower DunedinPACE accounted for 27% of the diet-dementia association and 57% of the diet-mortality association. INTERPRETATION: Findings suggest that slower pace of aging mediates part of the relationship of healthy diet with reduced dementia risk. Monitoring pace of aging may inform dementia prevention. However, a large fraction of the diet-dementia association remains unexplained and may reflect direct connections between diet and brain aging that do not overlap other organ systems. Investigation of brain-specific mechanisms in well-designed mediation studies is warranted. ANN NEUROL 2024.

Social isolation, loneliness, and inflammation: A multi-cohort investigation in early and mid-adulthood.

Social isolation and loneliness have been associated with poor health and increased risk for mortality, and inflammation might explain this link. We used data from the Danish TRIAGE Study of acutely admitted medical patients (N = 6,144, mean age 60 years), and from two population-representative birth cohorts: the New Zealand Dunedin Longitudinal Study (N = 881, age 45) and the UK Environmental Risk (E-Risk) Longitudinal Twin Study (N = 1448, age 18), to investigate associations of social isolation with three markers of systemic inflammation: C-reactive protein (CRP), interleukin-6 (IL-6), and a newer inflammation marker, soluble urokinase plasminogen activator receptor (suPAR), which is thought to index systemic chronic inflammation. In the TRIAGE Study, socially isolated patients (those living alone) had significantly higher median levels of suPAR (but not CRP or IL-6) compared with patients not living by themselves. Social isolation prospectively measured in childhood was longitudinally associated with higher CRP, IL-6, and suPAR levels in adulthood (at age 45 in the Dunedin Study and age 18 in the E-Risk Study), but only suPAR remained associated after controlling for covariates. Dunedin Study participants who reported loneliness at age 38 or age 45 had elevated suPAR at age 45. In contrast, E-Risk Study participants reporting loneliness at age 18 did not show any elevated markers of inflammation. In conclusion, social isolation was robustly associated with increased inflammation in adulthood, both in medical patients and in the general population. It was associated in particular with systemic chronic inflammation, evident from the consistently stronger associations with suPAR than other inflammation biomarkers.

Accelerated Pace of Aging in Schizophrenia: Five Case-Control Studies.

BACKGROUND: Schizophrenia is associated with increased risk of developing multiple aging-related diseases, including metabolic, respiratory, and cardiovascular diseases, and Alzheimer's and related dementias, leading to the hypothesis that schizophrenia is accompanied by accelerated biological aging. This has been difficult to test because there is no widely accepted measure of biological aging. Epigenetic clocks are promising algorithms that are used to calculate biological age on the basis of information from combined cytosine-phosphate-guanine sites (CpGs) across the genome, but they have yielded inconsistent and often negative results about the association between schizophrenia and accelerated aging. Here, we tested the schizophrenia-aging hypothesis using a DNA methylation measure that is uniquely designed to predict an individual's rate of aging. METHODS: We brought together 5 case-control datasets to calculate DunedinPACE (Pace of Aging Calculated from the Epigenome), a new measure trained on longitudinal data to detect differences between people in their pace of aging over time. Data were available from 1812 psychosis cases (schizophrenia or first-episode psychosis) and 1753 controls. Mean chronological age was 38.9 (SD = 13.6) years. RESULTS: We observed consistent associations across datasets between schizophrenia and accelerated aging as measured by DunedinPACE. These associations were not attributable to tobacco smoking or clozapine medication. CONCLUSIONS: Schizophrenia is accompanied by accelerated biological aging by midlife. This may explain the wide-ranging risk among people with schizophrenia for developing multiple different age-related physical diseases, including metabolic, respiratory, and cardiovascular diseases, and dementia. Measures of biological aging could prove valuable for assessing patients' risk for physical and cognitive decline and for evaluating intervention effectiveness.

A blood biomarker of accelerated aging in the body associates with worse structural integrity in the brain: replication across three cohorts.

Biological aging is the correlated decline of multi-organ system integrity central to the etiology of many age-related diseases. A novel epigenetic measure of biological aging, DunedinPACE, is associated with cognitive dysfunction, incident dementia, and mortality. Here, we tested for associations between DunedinPACE and structural MRI phenotypes in three datasets spanning midlife to advanced age: the Dunedin Study (age=45 years), the Framingham Heart Study Offspring Cohort (mean age=63 years), and the Alzheimer's Disease Neuroimaging Initiative (mean age=75 years). We also tested four additional epigenetic measures of aging: the Horvath clock, the Hannum clock, PhenoAge, and GrimAge. Across all datasets (total N observations=3,380; total N individuals=2,322), faster DunedinPACE was associated with lower total brain volume, lower hippocampal volume, and thinner cortex. In two datasets, faster DunedinPACE was associated with greater burden of white matter hyperintensities. Across all measures, DunedinPACE and GrimAge had the strongest and most consistent associations with brain phenotypes. Our findings suggest that single timepoint measures of multi-organ decline such as DunedinPACE could be useful for gauging nervous system health.

Diet, pace of biological aging, and risk of dementia in the Framingham Heart Study.

INTRODUCTION: We tested the hypothesis that healthy diet protects against dementia because it slows the pace of biological aging. METHODS: We analyzed Framingham Offspring Cohort data (≥60y). We measured healthy diet using the Dietary Guideline for Americans (DGA, 3 visits 1991-2008), pace of aging using the DunedinPACE epigenetic clock (2005-2008), and incident dementia and mortality using records (compiled 2005-2018). RESULTS: Of n=1,525 included participants (mean age 69.7, 54% female), n=129 developed dementia and n=432 died over follow-up. Greater DGA adherence was associated with slower DunedinPACE and reduced risks for dementia and mortality. Slower DunedinPACE was associated with reduced risks for dementia and mortality. Slower DunedinPACE accounted for 15% of the DGA association with dementia and 39% of the DGA association with mortality. DISCUSSION: Findings suggest that slower pace of aging mediates part of the relationship of healthy diet with reduced dementia risk. Monitoring pace of aging may inform dementia prevention.

Genetic associations with parental investment from conception to wealth inheritance in six cohorts.

Genetic inheritance is not the only way parents' genes may affect children. It is also possible that parents' genes are associated with investments into children's development. We examined evidence for links between parental genetics and parental investments, from the prenatal period through to adulthood, using data from six population-based cohorts in the UK, US and New Zealand, together totalling 36,566 parents. Our findings revealed associations between parental genetics-summarized in a genome-wide polygenic score-and parental behaviour across development, from smoking in pregnancy, breastfeeding in infancy, parenting in childhood and adolescence, to leaving a wealth inheritance to adult children. Effect sizes tended to be small at any given time point, ranging from RR = 1.12 (95% confidence interval (95%CI) 1.09, 1.15) to RR = 0.76 (95%CI 0.72, 0.80) during the prenatal period and infancy; ß = 0.07 (95%CI 0.04, 0.11) to ß = 0.29 (95%CI 0.27, 0.32) in childhood and adolescence, and RR = 1.04 (95%CI 1.01, 1.06) to RR = 1.11 (95%CI 1.07, 1.15) in adulthood. There was evidence for accumulating effects across development, ranging from ß = 0.15 (95%CI 0.11, 0.18) to ß = 0.23 (95%CI 0.16, 0.29) depending on cohort. Our findings are consistent with the interpretation that parents pass on advantages to offspring not only via direct genetic transmission or purely environmental paths, but also via genetic associations with parental investment from conception to wealth inheritance.

A comparison of feature selection methodologies and learning algorithms in the development of a DNA methylation-based telomere length estimator.

BACKGROUND: The field of epigenomics holds great promise in understanding and treating disease with advances in machine learning (ML) and artificial intelligence being vitally important in this pursuit. Increasingly, research now utilises DNA methylation measures at cytosine-guanine dinucleotides (CpG) to detect disease and estimate biological traits such as aging. Given the challenge of high dimensionality of DNA methylation data, feature-selection techniques are commonly employed to reduce dimensionality and identify the most important subset of features. In this study, our aim was to test and compare a range of feature-selection methods and ML algorithms in the development of a novel DNA methylation-based telomere length (TL) estimator. We utilised both nested cross-validation and two independent test sets for the comparisons. RESULTS: We found that principal component analysis in advance of elastic net regression led to the overall best performing estimator when evaluated using a nested cross-validation analysis and two independent test cohorts. This approach achieved a correlation between estimated and actual TL of 0.295 (83.4% CI [0.201, 0.384]) on the EXTEND test data set. Contrastingly, the baseline model of elastic net regression with no prior feature reduction stage performed less well in general-suggesting a prior feature-selection stage may have important utility. A previously developed TL estimator, DNAmTL, achieved a correlation of 0.216 (83.4% CI [0.118, 0.310]) on the EXTEND data. Additionally, we observed that different DNA methylation-based TL estimators, which have few common CpGs, are associated with many of the same biological entities. CONCLUSIONS: The variance in performance across tested approaches shows that estimators are sensitive to data set heterogeneity and the development of an optimal DNA methylation-based estimator should benefit from the robust methodological approach used in this study. Moreover, our methodology which utilises a range of feature-selection approaches and ML algorithms could be applied to other biological markers and disease phenotypes, to examine their relationship with DNA methylation and predictive value.

Cross-National and Cross-Generational Evidence That Educational Attainment May Slow the Pace of Aging in European-Descent Individuals.

OBJECTIVES: Individuals with more education are at lower risk of developing multiple, different age-related diseases than their less-educated peers. A reason for this might be that individuals with more education age slower. There are 2 complications in testing this hypothesis. First, there exists no definitive measure of biological aging. Second, shared genetic factors contribute toward both lower educational attainment and the development of age-related diseases. Here, we tested whether the protective effect of educational attainment was associated with the pace of aging after accounting for genetic factors. METHODS: We examined data from 5 studies together totaling almost 17,000 individuals with European ancestry born in different countries during different historical periods, ranging in age from 16 to 98 years old. To assess the pace of aging, we used DunedinPACE, a DNA methylation algorithm that reflects an individual's rate of aging and predicts age-related decline and Alzheimer's disease and related disorders. To assess genetic factors related to education, we created a polygenic score based on the results of a genome-wide association study of educational attainment. RESULTS: Across the 5 studies, and across the life span, higher educational attainment was associated with a slower pace of aging even after accounting for genetic factors (meta-analysis effect size = -0.20; 95% confidence interval [CI]: -0.30 to -0.10; p = .006). Further, this effect persisted after taking into account tobacco smoking (meta-analysis effect size = -0.13; 95% CI: -0.21 to -0.05; p = .01). DISCUSSION: These results indicate that higher levels of education have positive effects on the pace of aging, and that the benefits can be realized irrespective of individuals' genetics.

Socioenvironmental Adversity and Adolescent Psychotic Experiences: Exploring Potential Mechanisms in a UK Longitudinal Cohort.

BACKGROUND AND HYPOTHESIS: Children exposed to socioenvironmental adversities (eg, urbanicity, pollution, neighborhood deprivation, crime, and family disadvantage) are more likely to subsequently develop subclinical psychotic experiences during adolescence (eg, hearing voices, paranoia). However, the pathways through which this occurs have not been previously investigated. We hypothesized that cognitive ability and inflammation would partly explain this association. STUDY DESIGN: Data were utilized from the Environmental-Risk Longitudinal Twin Study, a cohort of 2232 children born in 1994-1995 in England and Wales and followed to age 18. Socioenvironmental adversities were measured from birth to age 10 and classified into physical risk (defined by high urbanicity and air pollution) and socioeconomic risk (defined by high neighborhood deprivation, neighborhood disorder, and family disadvantage). Cognitive abilities (overall, crystallized, fluid, and working memory) were assessed at age 12; and inflammatory markers (C-reactive protein, interleukin-6, soluble urokinase plasminogen activator receptor) were measured at age 18 from blood samples. Participants were interviewed at age 18 regarding psychotic experiences. STUDY RESULTS: Higher physical risk and socioeconomic risk were associated with increased odds of psychotic experiences in adolescence. The largest mediation pathways were from socioeconomic risk via overall cognitive ability and crystallized ability, which accounted for ~11% and ~19% of the association with psychotic experiences, respectively. No statistically significant pathways were found via inflammatory markers in exploratory (partially cross-sectional) analyses. CONCLUSIONS: Cognitive ability, especially crystallized ability, may partly explain the association between childhood socioenvironmental adversity and adolescent psychotic experiences. Interventions to support cognitive development among children living in disadvantaged settings could buffer them against developing subclinical psychotic phenomena.

Are macular drusen in midlife a marker of accelerated biological ageing?

CLINICAL RELEVANCE: Macular drusen are associated with age-related maculopathy but are not an ocular manifestation or biomarker of systemic ageing. BACKGROUND: Macular drusen are the first sign of age-related maculopathy, an eye disease for which age is the strongest risk factor. The aim of this cohort study was to investigate whether macular drusen in midlife - a sign of the earliest stages of age-related macular degeneration (AMD) - are associated with accelerated biological ageing more generally. METHODS: Members of the long-running Dunedin Multidisciplinary Health and Development Study (hereafter the Dunedin Study, n = 1037) underwent retinal photography at their most recent assessment at the age of 45 years. Images were graded for the presence of AMD using a simplified scale from the Age-Related Eye Disease Study (AREDS). Accelerated ageing was assessed by (i) a measure of Pace of Ageing defined from a combination of clinical and serum biomarkers obtained at ages 26, 32, 38, and 45 years and (ii) Facial Ageing, defined from photographs obtained at age 38 and 45 years. RESULTS: Of the 938 participants who participated at the age 45 assessments, 834 had gradable retinal photographs, and of these 165 (19.8%) had macular drusen. There was no significant difference in Pace of Ageing (p = .743) or Facial Ageing (p = .945) among participants with and without macular drusen. CONCLUSIONS: In this representative general population sample, macular drusen in midlife were not associated with accelerated ageing. Future studies tracking longitudinal changes in drusen number and severity at older ages may reveal whether drusen are a biomarker of accelerated ageing.

Uncovering the genetic architecture of broad antisocial behavior through a genome-wide association study meta-analysis.

Despite the substantial heritability of antisocial behavior (ASB), specific genetic variants robustly associated with the trait have not been identified. The present study by the Broad Antisocial Behavior Consortium (BroadABC) meta-analyzed data from 28 discovery samples (N = 85,359) and five independent replication samples (N = 8058) with genotypic data and broad measures of ASB. We identified the first significant genetic associations with broad ASB, involving common intronic variants in the forkhead box protein P2 (FOXP2) gene (lead SNP rs12536335, p = 6.32 × 10-10). Furthermore, we observed intronic variation in Foxp2 and one of its targets (Cntnap2) distinguishing a mouse model of pathological aggression (BALB/cJ strain) from controls (BALB/cByJ strain). Polygenic risk score (PRS) analyses in independent samples revealed that the genetic risk for ASB was associated with several antisocial outcomes across the lifespan, including diagnosis of conduct disorder, official criminal convictions, and trajectories of antisocial development. We found substantial genetic correlations of ASB with mental health (depression rg = 0.63, insomnia rg = 0.47), physical health (overweight rg = 0.19, waist-to-hip ratio rg = 0.32), smoking (rg = 0.54), cognitive ability (intelligence rg = -0.40), educational attainment (years of schooling rg = -0.46) and reproductive traits (age at first birth rg = -0.58, father's age at death rg = -0.54). Our findings provide a starting point toward identifying critical biosocial risk mechanisms for the development of ASB.

Improving risk indexes for Alzheimer's disease and related dementias for use in midlife.

Knowledge of a person's risk for Alzheimer's disease and related dementias (ADRDs) is required to triage candidates for preventive interventions, surveillance, and treatment trials. ADRD risk indexes exist for this purpose, but each includes only a subset of known risk factors. Information missing from published indexes could improve risk prediction. In the Dunedin Study of a population-representative New Zealand-based birth cohort followed to midlife (N = 938, 49.5% female), we compared associations of four leading risk indexes with midlife antecedents of ADRD against a novel benchmark index comprised of nearly all known ADRD risk factors, the Dunedin ADRD Risk Benchmark (DunedinARB). Existing indexes included the Cardiovascular Risk Factors, Aging, and Dementia index (CAIDE), LIfestyle for BRAin health index (LIBRA), Australian National University Alzheimer's Disease Risk Index (ANU-ADRI), and risks selected by the Lancet Commission on Dementia. The Dunedin benchmark was comprised of 48 separate indicators of risk organized into 10 conceptually distinct risk domains. Midlife antecedents of ADRD treated as outcome measures included age-45 measures of brain structural integrity [magnetic resonance imaging-assessed: (i) machine-learning-algorithm-estimated brain age, (ii) log-transformed volume of white matter hyperintensities, and (iii) mean grey matter volume of the hippocampus] and measures of brain functional integrity [(i) objective cognitive function assessed via the Wechsler Adult Intelligence Scale-IV, (ii) subjective problems in everyday cognitive function, and (iii) objective cognitive decline measured as residualized change in cognitive scores from childhood to midlife on matched Weschler Intelligence scales]. All indexes were quantitatively distributed and proved informative about midlife antecedents of ADRD, including algorithm-estimated brain age (ß's from 0.16 to 0.22), white matter hyperintensities volume (ß's from 0.16 to 0.19), hippocampal volume (ß's from -0.08 to -0.11), tested cognitive deficits (ß's from -0.36 to -0.49), everyday cognitive problems (ß's from 0.14 to 0.38), and longitudinal cognitive decline (ß's from -0.18 to -0.26). Existing indexes compared favourably to the comprehensive benchmark in their association with the brain structural integrity measures but were outperformed in their association with the functional integrity measures, particularly subjective cognitive problems and tested cognitive decline. Results indicated that existing indexes could be improved with targeted additions, particularly of measures assessing socioeconomic status, physical and sensory function, epigenetic aging, and subjective overall health. Existing premorbid ADRD risk indexes perform well in identifying linear gradients of risk among members of the general population at midlife, even when they include only a small subset of potential risk factors. They could be improved, however, with targeted additions to more holistically capture the different facets of risk for this multiply determined, age-related disease.

Association of Pace of Aging Measured by Blood-Based DNA Methylation With Age-Related Cognitive Impairment and Dementia.

BACKGROUND AND OBJECTIVES: DNA methylation algorithms are increasingly used to estimate biological aging; however, how these proposed measures of whole-organism biological aging relate to aging in the brain is not known. We used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Framingham Heart Study (FHS) Offspring Cohort to test the association between blood-based DNA methylation measures of biological aging and cognitive impairment and dementia in older adults. METHODS: We tested 3 "generations" of DNA methylation age algorithms (first generation: Horvath and Hannum clocks; second generation: PhenoAge and GrimAge; and third generation: DunedinPACE, Dunedin Pace of Aging Calculated from the Epigenome) against the following measures of cognitive impairment in ADNI: clinical diagnosis of dementia and mild cognitive impairment, scores on Alzheimer disease (AD) / Alzheimer disease and related dementias (ADRD) screening tests (Alzheimer's Disease Assessment Scale, Mini-Mental State Examination, and Montreal Cognitive Assessment), and scores on cognitive tests (Rey Auditory Verbal Learning Test, Logical Memory test, and Trail Making Test). In an independent replication in the FHS Offspring Cohort, we further tested the longitudinal association between the DNA methylation algorithms and the risk of developing dementia. RESULTS: In ADNI (N = 649 individuals), the first-generation (Horvath and Hannum DNA methylation age clocks) and the second-generation (PhenoAge and GrimAge) DNA methylation measures of aging were not consistently associated with measures of cognitive impairment in older adults. By contrast, a third-generation measure of biological aging, DunedinPACE, was associated with clinical diagnosis of Alzheimer disease (beta [95% CI] = 0.28 [0.08-0.47]), poorer scores on Alzheimer disease/ADRD screening tests (beta [Robust SE] = -0.10 [0.04] to 0.08[0.04]), and cognitive tests (beta [Robust SE] = -0.12 [0.04] to 0.10 [0.03]). The association between faster pace of aging, as measured by DunedinPACE, and risk of developing dementia was confirmed in a longitudinal analysis of the FHS Offspring Cohort (N = 2,264 individuals, hazard ratio [95% CI] = 1.27 [1.07-1.49]). DISCUSSION: Third-generation blood-based DNA methylation measures of aging could prove valuable for measuring differences between individuals in the rate at which they age and in their risk for cognitive decline, and for evaluating interventions to slow aging.

Mother's and children's ADHD genetic risk, household chaos and children's ADHD symptoms: A gene-environment correlation study.

BACKGROUND: Chaotic home environments may contribute to children's attention-deficit hyperactivity disorder (ADHD) symptoms. However, ADHD genetic risk may also influence household chaos. This study investigated whether children in chaotic households had more ADHD symptoms, if mothers and children with higher ADHD genetic risk lived in more chaotic households, and the joint association of genetic risk and household chaos on the longitudinal course of ADHD symptoms across childhood. METHODS: Participants were mothers and children from the Environmental Risk (E-Risk) Longitudinal Twin Study, a UK population-representative birth cohort of 2,232 twins. Children's ADHD symptoms were assessed at ages 5, 7, 10 and 12 years. Household chaos was rated by research workers at ages 7, 10 and 12, and by mother's and twin's self-report at age 12. Genome-wide ADHD polygenic risk scores (PRS) were calculated for mothers (n = 880) and twins (n = 1,999); of these, n = 871 mothers and n = 1,925 children had information on children's ADHD and household chaos. RESULTS: Children in more chaotic households had higher ADHD symptoms. Mothers and children with higher ADHD PRS lived in more chaotic households. Children's ADHD PRS was associated with household chaos over and above mother's PRS, suggesting evocative gene-environment correlation. Children in more chaotic households had higher baseline ADHD symptoms and a slower rate of decline in symptoms. However, sensitivity analyses estimated that gene-environment correlation accounted for a large proportion of the association of household chaos on ADHD symptoms. CONCLUSIONS: Children's ADHD genetic risk was independently associated with higher levels of household chaos, emphasising the active role of children in shaping their home environment. Our findings suggest that household chaos partly reflects children's genetic risk for ADHD, calling into question whether household chaos directly influences children's core ADHD symptoms. Our findings highlight the importance of considering parent and child genetic risk in relation to apparent environmental exposures.

Lifetime marijuana use and epigenetic age acceleration: A 17-year prospective examination.

AIMS: This study was designed to assess links between lifetime levels of marijuana use and accelerated epigenetic aging. DESIGN: Prospective longitudinal study, following participants annually from age 13 to age 30. SETTING AND PARTICIPANTS: A community sample of 154 participants recruited from a small city in the Southeastern United States. MEASUREMENTS: Participants completed annual assessments of marijuana use from age 13 to age 29 and provided blood samples that yielded two indices of epigenetic aging (DNAmGrimAge and DunedinPoAm) at age 30. Additional covariates examined included history of cigarette smoking, anxiety and depressive symptoms, childhood illness, gender, adolescent-era family income, and racial/ethnic minority status. FINDINGS: Lifetime marijuana use predicted accelerated epigenetic aging, with effects remaining even after covarying cell counts, demographic factors and chronological age (ß's = 0.32 & 0.27, p's < 0.001, 95% CI's = 0.21-0.43 & 0.16-0.39 for DNAmGrimAge and DunedinPoAm, respectively). Predictions remained after accounting for cigarette smoking (ß's = 0.25 & 0.21, respectively, p's < 0.001, 95% CI's = 0.14-0.37 & 0.09-0.32 for DNAmGrimAge and DunedinPoAm, respectively). A dose-response effect was observed and there was also evidence that effects were dependent upon recency of use. Effects of marijuana use appeared to be fully mediated by hypomethylation of a site linked to effects of hydrocarbon inhalation (cg05575921). CONCLUSIONS: Marijuana use predicted epigenetic changes linked to accelerated aging, with evidence suggesting that effects may be primarily due to hydrocarbon inhalation among marijuana smokers. Further research is warranted to explore mechanisms underlying this linkage.

DunedinPACE, a DNA methylation biomarker of the pace of aging.

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 1972-1973 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.

Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation.

Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype-phenotype map than previously anticipated.

Identical twins carry a persistent epigenetic signature of early genome programming.

Monozygotic (MZ) twins and higher-order multiples arise when a zygote splits during pre-implantation stages of development. The mechanisms underpinning this event have remained a mystery. Because MZ twinning rarely runs in families, the leading hypothesis is that it occurs at random. Here, we show that MZ twinning is strongly associated with a stable DNA methylation signature in adult somatic tissues. This signature spans regions near telomeres and centromeres, Polycomb-repressed regions and heterochromatin, genes involved in cell-adhesion, WNT signaling, cell fate, and putative human metastable epialleles. Our study also demonstrates a never-anticipated corollary: because identical twins keep a lifelong molecular signature, we can retrospectively diagnose if a person was conceived as monozygotic twin.