Previous studies have shown that three DNA methylation (DNAm) based algorithms of aging, DNAm PhenoAge acceleration (AgeAccelPheno), DNAm GrimAge acceleration (AgeAccelGrim), and mortality risk score (MRscore), to be strong predictors of mortality and aging related outcomes. We aimed to investigate if and to what extent these algorithms predict cancer. In four subsets (n = 727, 1003, 910, and 412) of a population-based cohort from Germany, DNA methylation in whole blood was measured using the Infinium Methylation EPIC BeadChip kit or the Infinium HumanMethylation450K BeadChip Assay (Illumina.Inc, San Diego, CA, USA). AgeAccelPheno, AgeAccelGrim, and a revised MRscore based on 8 CpGs only (MRscore-8CpGs), were calculated. Hazard ratios (HRs) were calculated to assess associations of the three DNAm algorithms with total cancer risk and risk of invasive breast, lung, prostate, and colorectal cancer incidence. During 17 years of follow-up, a total of 697 malignant tumors (thereof breast cancer = 75, lung cancer = 146, prostate cancer = 114, colorectal cancer = 155) were observed. All three algorithms showed strong positive associations with lung cancer risk in a dose response manner, with adjusted HRs per SD increase in AgeAccelPheno, AgeAccelGrim, and MRscore-8CpGs, of 1·37 (1·03-1·82), 1·74 (1·11-2·73), and 2·06 (1·39-3·06), respectively. By contrast, strong inverse associations were seen with breast cancer risk [adjusted HRs 0·65 (0·49-0·86), 0·45 (0·25-0·80), and 0·42 (0·25-0·70), respectively]. Weak positive associations of MRscore-8CpGs were seen with total cancer risk. The DNAm algorithms, particularly the MRscore-8CpGs, have potential to contribute to site-specific cancer risk prediction. The ESTHER study was funded by grants from the Baden-Württemberg state Ministry of Science, Research and Arts (Stuttgart, Germany), the Federal Ministry of Education and Research (Berlin, Germany), the Federal Ministry of Family Affairs, Senior Citizens, Women and Youth (Berlin, Germany), and the Saarland State Ministry of Health, Social Affairs, Women and the Family (Saarbrücken, Germany). The work of Xiangwei Li was supported by a grant from Fondazione Cariplo (Bando Ricerca Malattie invecchiamento, #2017-0653).

Three DNA methylation (DNAm) based algorithms, DNAm PhenoAge acceleration (AgeAccelPheno), DNAm GrimAge acceleration (AgeAccelGrim), and mortality risk score (MRscore), based on methylation in 513, 1030, and 10 CpGs, respectively, were established to predict health outcomes and mortality. We aimed to compare and validate the predictive ability of these scores and frailty in relation to mortality in a population-based cohort from Germany. DNA methylation in whole blood was measured by the Infinium Methylation EPIC BeadChip kit (EPIC, Illumina, San Diego, CA, USA) in two random subsets of the ESTHER cohort study (n = 741 and n = 1030). AgeAccelPheno, AgeAccelGrim, and a revised MRscore to adapt EPIC, the MRscore with 8 CpGs (MRscore-8CpGs), were calculated. Frailty was assessed by a frailty index (FI). During 17 years of follow-up, 458 deaths were observed. All DNAm algorithms and FI were positively correlated with each other. AgeAccelPheno, AgeAccelGrim, MRscore, and FI showed independent associations with all-cause mortality [hazard ratio (95% CI) per SD increase = 1·32 (1·19-1·46), 1·47 (1·32-1·64), 1·73 (1·49-2·01), and 1·31 (1·20-1·43), respectively]. Harrell's C-statistic was 0·710 for a model predicting mortality by age, sex, and leukocyte composition and increased to 0·759 in a model including MRscore-8CpGs and FI. The predictive performance was further improved (Harrell's C-statistic = 0·766) when additionally including AgeAccelPheno and AgeAccelGrim into the model. The combination of a DNA methylation score based on 8 CpGs only and an easy to ascertain frailty index may strongly enhance mortality prediction beyond age and sex. The ESTHER study was funded by grants from the Baden-Württemberg state Ministry of Science, Research and Arts (Stuttgart, Germany), the Federal Ministry of Education and Research (Berlin, Germany), the Federal Ministry of Family Affairs, Senior Citizens, Women and Youth (Berlin, Germany), and the Saarland State Ministry of Health, Social Affairs, Women and the Family (Saarbrücken, Germany). The work of Xiangwei Li was supported by a grant from Fondazione Cariplo (Bando Ricerca Malattie invecchiamento, #2017-0653).

Frailty indices (FIs), defined by accumulation of health deficits, have been shown to be strongly related to mortality in older adults. However, previous studies mostly relied on FI measurement at a single point of time. We aimed to investigate the association of frailty with mortality according to longitudinal repeated measurements of FI in a large population-based cohort study in Germany. Among 9912 men and women aged 50–75 years living in Saarland, Germany and recruited in the ESTHER study in 2000–2002, a FI based on 30 deficits was determined at baseline, 2-, 5-, 8-, and 11-year follow-up. Hazard ratios (HRs) were calculated to assess the associations of FI with all-cause mortality and cause-specific mortality during 14 years of follow-up using Cox proportional hazards models that included FI as a time-varying covariate. During the 14-year follow-up, a total of 2483 deaths were observed, of which 859 and 863 were due to cancer and cardiovascular diseases (CVD), respectively. The time-varying FI showed consistently strong associations with mortality throughout 14 years of follow-up, with HRs (95% confidence intervals) for frail (FI≥ 0·35) versus non-frail (FI≤ 0·11) participants of 4·72 (4.05–5.51), 2·55 (1·95–3·34) and 7·52 (5·69–9·94) for all-cause, cancer, and CVD mortality, respectively. Gradually decreasing associations with increasing length of follow-up would have been obtained by using baseline FI only. Longitudinal repeated measures of FI show strong, consistent associations with mortality, especially CVD mortality, throughout extended periods of follow-up among community-dwelling older adults. The ESTHER study was funded by grants from the Baden-Württemberg state Ministry of Science, Research and Arts (Stuttgart, Germany), the Federal Ministry of Education and Research (Berlin, Germany), the Federal Ministry of Family Affairs, Senior Citizens, Women and Youth (Berlin, Germany), and the Saarland State Ministry of Health, Social Affairs, Women and the Family (Saarbrücken, Germany).

DNA methylation (DNAm) patterns in peripheral blood have been shown to be associated with aging related health outcomes. We perform an epigenome-wide screening to identify CpGs related to frailty, defined by a frailty index (FI), in a large population-based cohort of older adults from Germany, the ESTHER study. Sixty-five CpGs are identified as frailty related methylation loci. Using LASSO regression, 20 CpGs are selected to derive a DNAm based algorithm for predicting frailty, the epigenetic frailty risk score (eFRS). The eFRS exhibits strong associations with frailty at baseline and after up to five-years of follow-up independently of established frailty risk factors. These associations are confirmed in another independent population-based cohort study, the KORA-Age study, conducted in older adults. In conclusion, we identify 65 CpGs as frailty-related loci, of which 20 CpGs are used to calculate the eFRS with predictive performance for frailty over long-term follow-up.

Social frailty, a multidimensional construct encompassing various social behaviors, resources, and needs, significantly impacts cognitive health in older adults. Despite existing studies linking specific social factors to cognitive function, the association between social frailty and long-term cognitive trajectories remains underexplored. This study aims to evaluate the longitudinal association between social frailty and trajectory of cognitive function in dementia-free older adults. This prospective cohort study used data from the National Health and Aging Trends Study (NHATS). Social frailty was assessed using the Makizako Social Frailty Index. According to the presence of social components, individuals were categorized into social frailty (≥ 2), pre-social frailty (1), and robust (0), respectively. Cognitive function was annually evaluated through memory, orientation, and executive function tests from 2011 to 2018. Mixed-effects linear models were employed to assess the associations between social frailty and changes in global and domain-specific cognitive function, adjusting for relevant covariates. In this study, 4956 dementia-free older adults (mean age 76.57 [7.41]) with complete at least 2 times of cognitive tests were included. Compared with the robust, social frailty was associated with significantly faster decline in global cognitive function (β = -0.041, 95% CI [-0.047, -0.036] z score per year) and domain-specific cognitive function (βmemory = -0.045, 95% CI [-0.055, -0.036] z score per year; βorientation = -0.027, 95% CI [-0.034, -0.020] z score per year; βexecutive = -0.042, 95% CI [-0.053, -0.032] z score per year) over the follow-up. Additionally, pre social frailty was associated with significantly faster decline in global cognitive function (β = -0.016, 95% CI [-0.021, -0.012] z score per year), memory function (β= -0.045, 95% CI [-0.055, -0.036] z score per year), and orientation function (β= -0.027, 95% CI [-0.034, -0.020] z score per year) over the follow-up. Social frailty is associated with faster decline in cognition in older adults, underscoring the necessity for enhanced social support and engagement to mitigate cognitive deterioration in vulnerable populations.

Background: Several DNA methylation (DNAm) algorithms have recently emerged as robust predictors of aging and adverse health outcomes in older adults, offering valuable insights into cardiovascular disease (CVD) risk stratification. However, their predictive performance for CVD varies significantly. This study aimed to systematically investigate the associations of 12 widely used DNAm algorithms with CVD and mortality risk. Methods: Data from the NHANES (National Health and Nutrition Examination Survey) 1999 to 2002 were used to assess 12 DNAm algorithms (eg, HannumAgeacc, PhenoAgeacc, GrimAgeMortacc, GrimAge2Mortacc) in relation to CVD risk and mortality. Two cohorts were analyzed: one for CVD risk (n=1230) and another for CVD mortality risk (n=1606). DNAm was measured using the Infinium Methylation EPIC BeadChip kit (Illumina). Odds ratios (ORs) and hazard ratios (HRs), along with 95% CIs per SD increase of these DNAm algorithms, were calculated. Results: Significant associations were observed for GrimAgeMortacc and GrimAge2Mortacc with coronary heart disease and heart attack, with multivariable‐adjusted ORs per SD increase ranging from 2.15 to 2.76. However, several algorithms exhibited no significant association with self‐reported prevalent CVD. For mortality risk, HannumAgeacc, PhenoAgeacc, ZhangAgeacc, GrimAgeMortacc, and GrimAge2Mortacc were significantly associated with CVD mortality. The multivariable‐adjusted HRs per SD increase were 1.19 (95% CIs, 1.05–1.34), 1.13 (95% CIs, 1.01–1.26), 1.63 (95% CI, 1.08–2.47), 1.90 (95% CIs, 1.51–2.40), and 1.87 (95% CIs, 1.51–2.32), respectively. These associations were consistent across biological sex, age (≥50 and <65 versus ≥65 years), and race and ethnicity groups. Conclusions: DNAm algorithms, particularly GrimAgeMortacc and GrimAge2Mortacc, may serve as valuable tools for CVD risk stratification and mortality risk assessment.