Genetic Regulation of Physical Fitness in Children: A Twin Study of 15 Tests from Eurofit and Fitnessgram Test Batteries.

PURPOSE: To analyze the shared genetic background of physical fitness tests in children. METHODS: Physical fitness was assessed in 198 Portuguese twin pairs (6-18 years old, 40% monozygotic) through 15 tests from the Eurofit and Fitnessgram test batteries. Genetic twin modeling was used to estimate the heritability of each test and the genetic correlations between them. RESULTS: Girls performed better than boys in flexibility, while boys performed better than girls in cardiorespiratory endurance and muscular strength. No sex differences were found in the influence of genetic factors on the physical fitness tests or their mutual correlations. Genetic factors explained 52% (standing long jump) to 79% (sit and reach) of the individual variation in motor performance, whereas individual-specific environmental factors explained the remaining variation. Most of the tests showed modest to moderate genetic correlations. Out of all 105 genetic correlations, 65% ranged from 0.2 to 0.6 indicating that they shared from 4% to 36% of genetic variation. The correlations between individual-specific environmental factors were mostly negligible. CONCLUSIONS: Tests measuring the strength of different muscle groups showed only modest correlations, but moderate correlations were found between tests measuring explosive strength, running speed/agility, and cardiorespiratory endurance. Genetic factors explained a major portion of the variation in tests included in the Eurofit and Fitnessgram test batteries and explained the correlations between them. The modest to moderate genetic correlations indicated that there is little redundancy of tests in either Eurofit or Fitnessgram test batteries.

Adolescent Cardiorespiratory Fitness and Risk of Cancer in Late Adulthood: Nationwide Sibling-Controlled Cohort Study.

Objective: To investigate whether the higher risks of certain cancers associated with high cardiorespiratory fitness can be explained by increased detection and unobserved confounders. Design: Nationwide sibling-controlled cohort study of adolescents. Setting: Sweden. Participants: 1 124 049 men of which 477 453 were full siblings, who underwent mandatory military conscription examinations between 1972 and 1995 at a mean age of 18.3 years. Main outcome measures: Hazard ratios (HR) and 95% confidence intervals (CI) of overall cancer diagnosis and cancer mortality, and 14 site-specific cancers (diagnosis or death), as recorded in the Swedish National Patient Register or Cause of Death Register until 31 December 2023, modelled using flexible parametric regressions. Results: Participants were followed until a median (maximum) age of 55.9 (73.5) years, during which 98 410 were diagnosed with cancer and 16 789 had a cancer-related death (41 293 and 6908 among full siblings respectively). The most common cancers were non-melanoma skin (27 105 diagnoses & 227 deaths) and prostate cancer (24 211 diagnoses & 869 deaths). In cohort analysis, those in the highest quartile of cardiorespiratory fitness had a higher risk of prostate (adjusted HR 1.10; 95% CI: 1.05 to 1.16) and skin cancer (e.g., non-melanoma HR 1.44; 1.37 to 1.50) compared to those in the lowest quartile, which led to a higher risk of any type of cancer diagnosis (HR 1.08; 1.06 to 1.11). However, those in the highest quartile had a lower risk of cancer mortality (HR 0.71; 0.67 to 0.76). When comparing full siblings, and thereby controlling for all behavioural, environmental, and genetic factors they share, the excess risk of prostate (HR 1.01; 0.90 to 1.13) and skin cancer (e.g., non-melanoma HR 1.09; 0.99 to 1.20) attenuated to the null. In contrast, the lower risk of overall cancer mortality was still statistically significant after control for such shared confounders (HR 0.78; 0.68 to 0.89). For other site-specific cancers, the influence of such confounding tended to vary, but none showed the same excess risk as prostate and non-melanoma skin cancer. Conclusions: The association between high levels of adolescent cardiorespiratory fitness and excess risk of some cancers, such as prostate and non-melanoma skin cancer, appears to be fully explained by unobserved confounders shared between full siblings. However, the protective association with cancer mortality persists even after control for such confounding.

Genetic Liability to Cardiovascular Disease, Physical Activity, and Mortality: Findings from the Finnish Twin Cohort.

PURPOSE: We investigated whether longitudinally assessed physical activity (PA) and adherence specifically to World Health Organization PA guidelines mitigates or moderates mortality risk regardless of genetic liability to cardiovascular disease (CVD). We also estimated the causality of the PA-mortality association. METHODS: The study used the older Finnish Twin Cohort (FTC) with 4,897 participants aged 33-60 years (54.3% women). Genetic liability to coronary heart disease, systolic and diastolic blood pressure was estimated with polygenic risk scores (PRSs) derived from the Pan-UK Biobank (N ≈ 400,000; > 1,000,000 genetic variants). Leisure-time PA was assessed with validated and structured questionnaires three times during 1975-1990. The main effects of adherence to PA guidelines and the PRS × PA interactions were evaluated with Cox proportional hazards models against all-cause and CVD mortality. A co-twin control design with 180 monozygotic twin pairs discordant for meeting the guidelines was used for causal inference. RESULTS: During the 17.4-year (mean) follow-up (85,136 person-years), 1,195 participants died, with 389 CVD deaths. One standard deviation higher PRSs were associated with a 17%-24% higher CVD mortality risk but not with all-cause mortality except for the PRS for diastolic blood pressure. Adherence to PA guidelines did not show significant independent main effects or interactions with all-cause or CVD mortality. Twins whose activity levels adhered to PA guidelines over a 15-year period did not have statistically significantly reduced mortality risk compared to their less active identical twin sibling. The findings were similar among high, intermediate, and low genetic risk levels for CVD. CONCLUSIONS: The genetically informed FTC data could not confirm that adherence to PA guidelines either mitigates or moderates genetic CVD risk or causally reduces mortality risk.

Circulating miRNA Signature Predicts Cancer Incidence in Lynch Syndrome-A Pilot Study.

Lynch syndrome (LS) is the most common autosomal dominant cancer syndrome and is characterized by high genetic cancer risk modified by lifestyle factors. This study explored whether a circulating miRNA (c-miR) signature predicts LS cancer incidence within a 4-year prospective surveillance period. To gain insight how lifestyle behavior could affect LS cancer risk, we investigated whether the cancer-predicting c-miR signature correlates with known risk-reducing factors such as physical activity, body mass index (BMI), dietary fiber, or NSAID usage. The study included 110 c-miR samples from LS carriers, 18 of whom were diagnosed with cancer during a 4-year prospective surveillance period. Lasso regression was utilized to find c-miRs associated with cancer risk. Individual risk sum derived from the chosen c-miRs was used to develop a model to predict LS cancer incidence. This model was validated using 5-fold cross-validation. Correlation and pathway analyses were applied to inspect biological functions of c-miRs. Pearson correlation was used to examine the associations of c-miR risk sum and lifestyle factors. hsa-miR-10b-5p, hsa-miR-125b-5p, hsa-miR-200a-3p, hsa-miR-3613-5p, and hsa-miR-3615 were identified as cancer predictors by Lasso, and their risk sum score associated with higher likelihood of cancer incidence (HR 2.72, 95% confidence interval: 1.64-4.52, C-index = 0.72). In cross-validation, the model indicated good concordance with the average C-index of 0.75 (0.6-1.0). Coregulated hsa-miR-10b-5p, hsa-miR-125b-5p, and hsa-miR-200a-3p targeted genes involved in cancer-associated biological pathways. The c-miR risk sum score correlated with BMI (r = 0.23, P < 0.01). In summary, BMI-associated c-miRs predict LS cancer incidence within 4 years, although further validation is required. PREVENTION RELEVANCE: The development of cancer risk prediction models is key to improving the survival of patients with LS. This pilot study describes a serum miRNA signature-based risk prediction model that predicts LS cancer incidence within 4 years, although further validation is required.

Genome-Wide Polygenic Score for Muscle Strength Predicts Risk for Common Diseases and Lifespan: A Prospective Cohort Study.

BACKGROUND: We used a polygenic score for hand grip strength (PGS HGS) to investigate whether genetic predisposition for higher muscle strength predicts age-related noncommunicable diseases, survival from acute adverse health events, and mortality. METHODS: This study consisted of 342 443 Finnish biobank participants from FinnGen Data Freeze 10 (53% women) aged 40-108 with combined genotype and health registry data. Associations between PGS HGS and a total of 27 clinical endpoints were explored with linear or Cox regression models. RESULTS: A higher PGS HGS was associated with a reduced risk of selected common noncommunicable diseases and mortality by 2%-10%. The risk for these medical conditions decreased by 5%-23% for participants in the highest PGS HGS quintile compared to those in the lowest PGS HGS quintile. A 1 standard deviation (SD) increase in the PGS HGS predicted a lower body mass index (ß = -0.112 kg/m2, standard error [SE] = 0.017, p = 1.69E-11) in women but not in men (ß = 0.004 kg/m2, p = .768). PGS HGS was not associated with better survival after acute adverse health events compared to the nondiseased period. CONCLUSIONS: The genotype that supports higher muscle strength appears to protect against future health adversities, albeit with modest effect sizes. Further research is needed to investigate whether or how a favorable lifestyle modifies this intrinsic capacity to resist diseases, and if the impacts of lifestyle behavior on health differs due to genetic predisposition for muscle strength.

Metabolic syndrome and epigenetic aging: a twin study.

BACKGROUND: Metabolic syndrome (MetS) is associated with premature aging, but whether this association is driven by genetic or lifestyle factors remains unclear. METHODS: Two independent discovery cohorts, consisting of twins and unrelated individuals, were examined (N = 268, aged 23-69 years). The findings were replicated in two cohorts from the same base population. One consisted of unrelated individuals (N = 1 564), and the other of twins (N = 293). Participants' epigenetic age, estimated using blood DNA methylation data, was determined using the epigenetic clocks GrimAge and DunedinPACE. The individual-level linear regression models for investigating the associations of MetS and its components with epigenetic aging were followed by within-twin-pair analyses using fixed-effects regression models to account for genetic factors. RESULTS: In individual-level analyses, GrimAge age acceleration was higher among participants with MetS (N = 56) compared to participants without MetS (N = 212) (mean 2.078 [95% CI = 0.996,3.160] years vs. -0.549 [-1.053,-0.045] years, between-group p = 3.5E-5). Likewise, the DunedinPACE estimate was higher among the participants with MetS compared to the participants without MetS (1.032 [1.002,1.063] years/calendar year vs. 0.911 [0.896,0.927] years/calendar year, p = 4.8E-11). An adverse profile in terms of specific MetS components was associated with accelerated aging. However, adjustments for lifestyle attenuated these associations; nevertheless, for DunedinPACE, they remained statistically significant. The within-twin-pair analyses suggested that genetics explains these associations fully for GrimAge and partly for DunedinPACE. The replication analyses provided additional evidence that the association between MetS components and accelerated aging is independent of the lifestyle factors considered in this study, however, suggesting that genetics is a significant confounder in this association. CONCLUSIONS: The results of this study suggests that MetS is associated with accelerated epigenetic aging, independent of physical activity, smoking or alcohol consumption, and that the association may be explained by genetics.

Associations of polygenic inheritance of physical activity with aerobic fitness, cardiometabolic risk factors and diseases: the HUNT study.

Physical activity (PA), aerobic fitness, and cardiometabolic diseases (CMD) are highly heritable multifactorial phenotypes. Shared genetic factors may underlie the associations between higher levels of PA and better aerobic fitness and a lower risk for CMDs. We aimed to study how PA genotype associates with self-reported PA, aerobic fitness, cardiometabolic risk factors and diseases. PA genotype, which combined variation in over one million of gene variants, was composed using the SBayesR polygenic scoring methodology. First, we constructed a polygenic risk score for PA in the Trøndelag Health Study (N = 47,148) using UK Biobank single nucleotide polymorphism-specific weights (N = 400,124). The associations of the PA PRS and continuous variables were analysed using linear regression models and with CMD incidences using Cox proportional hazard models. The results showed that genotypes predisposing to higher amount of PA were associated with greater self-reported PA (Beta [B] = 0.282 MET-h/wk per SD of PRS for PA, 95% confidence interval [CI] = 0.211, 0.354) but not with aerobic fitness. These genotypes were also associated with healthier cardiometabolic profile (waist circumference [B = -0.003 cm, 95% CI = -0.004, -0.002], body mass index [B = -0.002 kg/m2, 95% CI = -0.004, -0.001], high-density lipoprotein cholesterol [B = 0.004 mmol/L, 95% CI = 0.002, 0.006]) and lower incidence of hypertensive diseases (Hazard Ratio [HR] = 0.97, 95% CI = 0.951, 0.990), stroke (HR = 0.94, 95% CI = 0.903, 0.978) and type 2 diabetes (HR = 0.94, 95 % CI = 0.902, 0.970). Observed associations were independent of self-reported PA. These results support earlier findings suggesting small pleiotropic effects between PA and CMDs and provide new evidence about associations of polygenic inheritance of PA and intermediate cardiometabolic risk factors.

The associations of long-term physical activity in adulthood with later biological ageing and all-cause mortality - a prospective twin study.

Objectives: The association between leisure-time physical activity (LTPA) and a lower risk of mortality is susceptible to bias from multiple sources. We investigated the potential of biological ageing to mediate the association between long-term LTPA and mortality and whether the methods used to account for reverse causality affect the interpretation of this association. Methods: Study participants were twins from the older Finnish Twin Cohort (n=22,750; 18-50 years at baseline). LTPA was assessed using questionnaires in 1975, 1981 and 1990. The mortality follow-up lasted until 2020 and biological ageing was assessed using epigenetic clocks in a subsample (n=1,153) with blood samples taken during the follow-up. Using latent profile analysis, we identified classes with distinct longitudinal LTPA patterns and studied differences in biological ageing between these classes. We employed survival models to examine differences in total, short-term and long-term all-cause mortality, and multilevel models for twin data to control for familial factors. Results: We identified four classes of long-term LTPA: sedentary, moderately active, active and highly active. Although biological ageing was accelerated in sedentary and highly active classes, after adjusting for other lifestyle-related factors, the associations mainly attenuated. Physically active classes had a maximum 7% lower risk of total mortality over the sedentary class, but this association was consistent only in the short term and could largely be accounted for by familial factors. LTPA exhibited less favourable associations when prevalent diseases were exclusion criteria rather than covariate. Conclusion: Being active may reflect a healthy phenotype instead of causally reducing mortality.

Mortality Associations With DNA Methylation-Based Biological Aging and Physical Functioning Measures Across a 20-Year Follow-up Period.

BACKGROUND: Measures of biological aging range from DNA methylation (DNAm)-based estimates to measures of physical abilities. The purpose of this study was to compare DNAm- and physical functioning-based measures of biological aging in predicting mortality. METHODS: We studied 63- to 76-year-old women (N = 395) from the Finnish Twin Study on Aging (FITSA). Participants' biological age (epigenetic clocks DNAm GrimAge and DunedinPACE) was estimated using blood DNAm data. Tests of physical functioning conducted under standardized laboratory conditions included the Timed Up and Go (TUG) test and 10-m walk test. Mortality hazard ratios were calculated per every 1 standard deviation (SD) increase in the predictor. Cox regression models were conducted for individuals and twin pairs, the latter controlling for underlying genetic effects. The models were adjusted for known lifestyle predictors of mortality. RESULTS: During the follow-up period (mean 17.0 years, range 0.2-20.3), 187 participants died. In both the individual-based and pairwise analyses, GrimAge and both functional biomarkers of aging were associated with mortality independent of family relatedness, chronological age, physical activity, body mass index, smoking, education, or chronic diseases. In a model including both the DNAm-based measures and functional biomarkers of aging, GrimAge and TUG remained predictive. CONCLUSIONS: The findings suggest that DNAm GrimAge and the TUG test are strong predictors of mortality independent of each others and genetic influences. DNAm-based measures and functional tests capture different aspects of the aging process and thus complement each other as measures of biological aging in predicting mortality.

Systemic circulating microRNA landscape in Lynch syndrome.

Circulating microRNAs (c-miRs) are small noncoding RNA molecules that migrate throughout the body and regulate gene expression. Global c-miR expression patterns (c-miRnomes) change with sporadic carcinogenesis and have predictive potential in early detection of cancers. However, there are no studies that have assessed whether c-miRnomes display similar potential in carriers of inherited pathogenic mismatch-repair gene variants (path_MMR), known as Lynch syndrome (LS), who are predisposed to highly increased cancer risk. Using high-throughput sequencing and bioinformatic approaches, we conducted an exploratory analysis to characterize systemic c-miRnomes of path_MMR carriers, sporadic rectal cancer patients and non-LS controls. We showed for the first time that cancer-free path_MMR carriers have a systemic c-miRnome of 40 differentially expressed c-miRs that can distinguish them from non-LS controls. The systemic c-miRnome of cancer-free path_MMR carriers also resembles the systemic c-miRnomes of cancer patients with or without path_MMR. Our pathway analysis linked the found differentially expressed c-miRs to carcinogenesis. A total of 508 putative target genes were identified for 32 out of 40 differentially expressed c-miRs, and 238 of them were enriched in cancer-related pathways. The most enriched c-miR-target genes include well-known oncogenes and tumor suppressor genes such as BCL2, AKT3, PIK3CA, KRAS, NRAS, CDKN1A and PIK3R1. Taken together, our findings suggest that LS and sporadic carcinogenesis share common biological pathways and alterations in these pathways can produce a c-miR signature which can track potential oncogenic stress in cancer-free path_MMR carriers. Therefore, c-miRs hold potential in monitoring the LS risk stratification patterns during clinical surveillance or cancer management.

The role of adolescent lifestyle habits in biological aging: A prospective twin study.

Background: Adolescence is a stage of fast growth and development. Exposures during puberty can have long-term effects on health in later life. This study aims to investigate the role of adolescent lifestyle in biological aging. Methods: The study participants originated from the longitudinal FinnTwin12 study (n = 5114). Adolescent lifestyle-related factors, including body mass index (BMI), leisure-time physical activity, smoking, and alcohol use, were based on self-reports and measured at ages 12, 14, and 17 years. For a subsample, blood-based DNA methylation (DNAm) was used to assess biological aging with six epigenetic aging measures in young adulthood (21-25 years, n = 824). A latent class analysis was conducted to identify patterns of lifestyle behaviors in adolescence, and differences between the subgroups in later biological aging were studied. Genetic and environmental influences on biological aging shared with lifestyle behavior patterns were estimated using quantitative genetic modeling. Results: We identified five subgroups of participants with different adolescent lifestyle behavior patterns. When DNAm GrimAge, DunedinPoAm, and DunedinPACE estimators were used, the class with the unhealthiest lifestyle and the class of participants with high BMI were biologically older than the classes with healthier lifestyle habits. The differences in lifestyle-related factors were maintained into young adulthood. Most of the variation in biological aging shared with adolescent lifestyle was explained by common genetic factors. Conclusions: These findings suggest that an unhealthy lifestyle during pubertal years is associated with accelerated biological aging in young adulthood. Genetic pleiotropy may largely explain the observed associations. Funding: This work was supported by the Academy of Finland (213506, 265240, 263278, 312073 to J.K., 297908 to M.O. and 341750, 346509 to E.S.), EC FP5 GenomEUtwin (J.K.), National Institutes of Health/National Heart, Lung, and Blood Institute (grant HL104125), EC MC ITN Project EPITRAIN (J.K. and M.O.), the University of Helsinki Research Funds (M.O.), Sigrid Juselius Foundation (J.K. and M.O.), Yrjö Jahnsson Foundation (6868), Juho Vainio Foundation (E.S.) and Päivikki and Sakari Sohlberg foundation (E.S.).

For most animals, events that occur early in life can have a lasting impact on individuals' health. In humans, adolescence is a particularly vulnerable time when rapid growth and development collide with growing independence and experimentation. An unhealthy lifestyle during this period of rapid cell growth can contribute to later health problems like heart disease, lung disease, and premature death. This is due partly to accelerated biological aging, where the body deteriorates faster than what would be expected for an individual's chronological age. One way to track the effects of lifestyle on biological aging is by measuring epigenetic changes. Epigenetic changes consist on adding or removing chemical 'tags' on genes. These tags can switch the genes on or off without changing their sequences. Scientists can measure certain epigenetic changes by measuring the levels of methylated DNA ­ DNA with a chemical 'tag' known as a methyl group ­ in blood samples. Several algorithms ­ known as 'epigenetic clocks' ­ are available that estimate how fast an individual is aging biologically based on DNA methylation. Kankaanpää et al. show that unhealthy lifestyles during adolescence may lead to accelerated aging in early adulthood. For their analysis, Kankaanpää et al. used data on the levels of DNA methylation in blood samples from 824 twins between 21 and 25 years old. The twins were participants in the FinnTwin12 study and had completed a survey about their lifestyles at ages 12, 14, and 17. Kankaanpää et al. classified individuals into five groups depending on their lifestyles. The first three groups, which included most of the twins, contained individuals that led relatively healthy lives. The fourth group contained individuals with a higher body mass index based on their height and weight. Finally, the last group included individuals with unhealthy lifestyles who binge drank, smoked and did not exercise. After estimating the biological ages for all of the participants, Kankaanpää et al. found that both the individuals with higher body mass indices and those in the group with unhealthy lifestyles aged faster than those who reported healthier lifestyles. However, the results varied depending on which epigenetic clock Kankaanpää et al. used to measure biological aging: clocks that had been developed earlier showed fewer differences in aging between groups; while newer clocks consistently found that individuals in the higher body mass index and unhealthy groups were older. Kankaanpää et al. also showed that shared genetic factors explained both unhealthy lifestyles and accelerated biological aging. The experiments performed by Kankaanpää et al. provide new insights into the vital role of an individual's genetics in unhealthy lifestyles and cellular aging. These insights might help scientists identify at risk individuals early in life and try to prevent accelerated aging.

Methylation status of VTRNA2-1/nc886 is stable across populations, monozygotic twin pairs and in majority of tissues.

Aims & methods: The aim of this study was to characterize the methylation level of a polymorphically imprinted gene, VTRNA2-1/nc886, in human populations and somatic tissues.48 datasets, consisting of more than 30 tissues and >30,000 individuals, were used. Results: nc886 methylation status is associated with twin status and ethnic background, but the variation between populations is limited. Monozygotic twin pairs present concordant methylation, whereas ∼30% of dizygotic twin pairs present discordant methylation in the nc886 locus. The methylation levels of nc886 are uniform across somatic tissues, except in cerebellum and skeletal muscle. Conclusion: The nc886 imprint may be established in the oocyte, and, after implantation, the methylation status is stable, excluding a few specific tissues.

A Polygenic Risk Score for Hand Grip Strength Predicts Muscle Strength and Proximal and Distal Functional Outcomes among Older Women.

PURPOSE: Hand grip strength (HGS) is a widely used indicator of overall muscle strength and general health. We computed a polygenic risk score (PRS) for HGS and examined whether it predicted muscle strength, functional capacity, and disability outcomes. METHODS: Genomewide association study summary statistics for HGS from the Pan-UK Biobank was used. PRS were calculated in the Finnish Twin Study on Aging ( N = 429 women, 63-76 yr). Strength tests included HGS, isometric knee extension, and ankle plantarflexion strength. Functional capacity was examined with the Timed Up and Go, 6-min and 10-m walk tests, and dual-task tests. Disabilities in the basic activities of daily living (ADL) and instrumental ADL (IADL) were investigated with questionnaires. The proportion of variation in outcomes accounted for by PRS HGS was examined using linear mixed models and extended logistic regression. RESULTS: The measured HGS increased linearly over increasing PRS ( ß = 4.8, SE = 0.93, P < 0.001). PRS HGS independently accounted for 6.1% of the variation in the measured HGS ( ß = 14.2, SE = 3.1, P < 0.001), 5.4% of the variation in knee extension strength ( ß = 19.6, SE = 4.7, P < 0.001), 1.2% of the variation in ankle plantarflexion strength ( ß = 9.4, SE = 4.2, P = 0.027), and 0.1%-1.5% of the variation in functional capacity tests ( P = 0.016-0.133). Further, participants with higher PRS HGS were less likely to have ADL/IADL disabilities (odds ratio = 0.74-0.76). CONCLUSIONS: Older women with genetic risk for low muscle strength were significantly weaker than those with genetic susceptibility for high muscle strength. PRS HGS was also systematically associated with overall muscle strength and proximal and distal functional outcomes that require muscle strength.

Do Epigenetic Clocks Provide Explanations for Sex Differences in Life Span? A Cross-Sectional Twin Study.

BACKGROUND: The sex gap in life expectancy has been narrowing in Finland over the past 4-5 decades; however, on average, women still live longer than men. Epigenetic clocks are markers for biological aging which predict life span. In this study, we examined the mediating role of lifestyle factors on the association between sex and biological aging in younger and older adults. METHODS: Our sample consists of younger and older twins (21‒42 years, n = 1 477; 50‒76 years, n = 763) including 151 complete younger opposite-sex twin pairs (21‒30 years). Blood-based DNA methylation was used to compute epigenetic age acceleration by 4 epigenetic clocks as a measure of biological aging. Path modeling was used to study whether the association between sex and biological aging is mediated through lifestyle-related factors, that is, education, body mass index, smoking, alcohol use, and physical activity. RESULTS: In comparison to women, men were biologically older and, in general, they had unhealthier life habits. The effect of sex on biological aging was partly mediated by body mass index and, in older twins, by smoking. Sex was directly associated with biological aging and the association was stronger in older twins. CONCLUSIONS: Previously reported sex differences in life span are also evident in biological aging. Declining smoking prevalence among men is a plausible explanation for the narrowing of the difference in life expectancy between the sexes. Data generated by the epigenetic clocks may help in estimating the effects of lifestyle and environmental factors on aging and in predicting aging in future generations.

Polygenic Score for Physical Activity Is Associated with Multiple Common Diseases.

INTRODUCTION: Genetic pleiotropy, in which the same genes affect two or more traits, may partially explain the frequently observed associations between high physical activity (PA) and later reduced morbidity or mortality. This study investigated associations between PA polygenic risk scores (PRS) and cardiometabolic diseases among the Finnish population. METHODS: PRS for device-measured overall PA were adapted to a FinnGen study cohort of 218,792 individuals with genomewide genotyping and extensive digital longitudinal health register data. Associations between PA PRS and body mass index, diseases, and mortality were analyzed with linear and logistic regression models. RESULTS: A high PA PRS predicted a lower body mass index (ß = -0.025 kg·m-2 per one SD change in PA PRS, SE = 0.013, P = 1.87 × 10-80). The PA PRS also predicted a lower risk for diseases that typically develop later in life or not at all among highly active individuals. A lower disease risk was systematically observed for cardiovascular diseases (odds ratio [OR] per 1 SD change in PA PRS = 0.95, P = 9.5 × 10-19) and, for example, hypertension [OR = 0.93, P = 2.7 × 10-44), type 2 diabetes (OR = 0.91, P = 4.1 × 10-42), and coronary heart disease (OR = 0.95, P = 1.2 × 10-9). Participants with high PA PRS had also lower mortality risk (OR = 0.97, P = 0.0003). CONCLUSIONS: Genetically less active persons are at a higher risk of developing cardiometabolic diseases, which may partly explain the previously observed associations between low PA and higher disease and mortality risk. The same inherited physical fitness and metabolism-related mechanisms may be associated both with PA levels and with cardiometabolic disease risk.

Maintenance of high quality of life as an indicator of resilience during COVID-19 social distancing among community-dwelling older adults in Finland.

PURPOSE: Social distancing during the COVID-19 pandemic reduced possibilities for activities of choice potentially threatening quality of life (QoL). We defined QoL resilience as maintaining high quality of life and studied whether walking speed, absence of loneliness, living arrangement, and stress-coping ability predict QoL resilience among older people. METHODS: Community-dwelling 75-, 80-, and 85-year-old persons (n = 685) were interviewed and examined in 2017-2018 and were followed up during COVID-19 social distancing in 2020. We assessed QoL using the OPQOL-brief scale and set a cut-off for 'constant high' based on staying in the highest baseline quartile over the follow-up and categorized all others as having 'low/moderate'. Perceived restrictiveness of the social distancing recommendations was examined with one item and was categorized as 'yes' or 'no' restrictiveness. RESULTS: Better stress-coping ability (OR 1.21, 95% CI 1.14-1.28) and not being lonely (OR 2.67, 95% CI 1.48-4.63) increased the odds for constant high QoL from before to amid social distancing, and the odds did not differ according to the perceived restrictiveness of the social distancing recommendations. Higher walking speed predicted constant high QoL only among those perceiving restrictiveness (OR 1.16, 95% CI 1.07-1.27). Living arrangement did not predict constant high QoL. CONCLUSION: During social distancing, psychosocial resources helped to maintain good QoL regardless how restrictive the social distancing recommendations were perceived to be. Better physical capacity was important for constant high QoL only among those perceiving restrictiveness presumably because it enabled replacing blocked activities with open outdoor physical activities.

The Association Between Epigenetic Clocks and Physical Functioning in Older Women: A 3-Year Follow-up.

BACKGROUND: Epigenetic clocks are composite markers developed to predict chronological age or mortality risk from DNA methylation (DNAm) data. The present study investigated the associations between 4 epigenetic clocks (Horvath's and Hannum's DNAmAge and DNAm GrimAge and PhenoAge) and physical functioning during a 3-year follow-up. METHOD: We studied 63- to 76-year-old women (N = 413) from the Finnish Twin Study on Aging. DNAm was measured from blood samples at baseline. Age acceleration (AgeAccel), that is, discrepancy between chronological age and DNAm age, was determined as residuals from linear model. Physical functioning was assessed under standardized laboratory conditions at baseline and at follow-up. A cross-sectional analysis was performed with path models, and a longitudinal analysis was conducted with repeated measures linear models. A nonrandom missing data analysis was performed. RESULTS: In comparison to the other clocks, GrimAgeAccel was more strongly associated with physical functioning. At baseline, GrimAgeAccel was associated with lower performance in the Timed Up and Go (TUG) test and the 6-minute walk test. At follow-up, significant associations were observed between GrimAgeAccel and lowered performance in the TUG, 6-minute and 10-m walk tests, and knee extension and ankle plantar flexion strength tests. CONCLUSIONS: The DNAm GrimAge, a novel estimate of biological aging, associated with decline in physical functioning over the 3-year follow-up in older women. However, associations between chronological age and physical function phenotypes followed similar pattern. Current epigenetic clocks do not provide strong benefits in predicting the decline of physical functioning at least during a rather short follow-up period and restricted age range.

Does the epigenetic clock GrimAge predict mortality independent of genetic influences: an 18 year follow-up study in older female twin pairs.

BACKGROUND: Epigenetic clocks are based on DNA methylation (DNAm). It has been suggested that these clocks are useable markers of biological aging and premature mortality. Because genetic factors explain variations in both epigenetic aging and mortality, this association could also be explained by shared genetic factors. We investigated the influence of genetic and lifestyle factors (smoking, alcohol consumption, physical activity, chronic diseases, body mass index) and education on the association of accelerated epigenetic aging with mortality using a longitudinal twin design. Utilizing a publicly available online tool, we calculated the epigenetic age using two epigenetic clocks, Horvath DNAmAge and DNAm GrimAge, in 413 Finnish twin sisters, aged 63-76 years, at the beginning of the 18-year mortality follow-up. Epigenetic age acceleration was calculated as the residuals from a linear regression model of epigenetic age estimated on chronological age (AAHorvath, AAGrimAge, respectively). Cox proportional hazard models were conducted for individuals and twin pairs. RESULTS: The results of the individual-based analyses showed an increased mortality hazard ratio (HR) of 1.31 (CI95: 1.13-1.53) per one standard deviation (SD) increase in AAGrimAge. The results indicated no significant associations of AAHorvath with mortality. Pairwise mortality analyses showed an HR of 1.50 (CI95: 1.02-2.20) per 1 SD increase in AAGrimAge. However, after adjusting for smoking, the HR attenuated substantially and was statistically non-significant (1.29; CI95: 0.84-1.99). Similarly, in multivariable adjusted models the HR (1.42-1.49) was non-significant. In AAHorvath, the non-significant HRs were lower among monozygotic pairs in comparison to dizygotic pairs, while in AAGrimAge there were no systematic differences by zygosity. Further, the pairwise analysis in quartiles showed that the increased within pair difference in AAGrimAge was associated with a higher all-cause mortality risk. CONCLUSIONS: In conclusion, the findings suggest that DNAm GrimAge is a strong predictor of mortality independent of genetic influences. Smoking, which is known to alter DNAm levels and is built into the DNAm GrimAge algorithm, attenuated the association between epigenetic aging and mortality risk.

Blood and skeletal muscle ageing determined by epigenetic clocks and their associations with physical activity and functioning.

The aim of this study was to investigate the correspondence of different biological ageing estimates (i.e. epigenetic age) in blood and muscle tissue and their associations with physical activity (PA), physical function and body composition. Two independent cohorts (N = 139 and N = 47) were included, whose age span covered adulthood (23-69 years). Whole blood and m. vastus lateralis samples were collected, and DNA methylation was analysed. Four different DNA methylation age (DNAmAge) estimates were calculated using genome-wide methylation data and publicly available online tools. A novel muscle-specific methylation age was estimated using the R-package 'MEAT'. PA was measured with questionnaires and accelerometers. Several tests were conducted to estimate cardiorespiratory fitness and muscle strength. Body composition was estimated by dual-energy X-ray absorptiometry. DNAmAge estimates from blood and muscle were highly correlated with chronological age, but different age acceleration estimates were weakly associated with each other. The monozygotic twin within-pair similarity of ageing pace was higher in blood (r = 0.617-0.824) than in muscle (r = 0.523-0.585). Associations of age acceleration estimates with PA, physical function and body composition were weak in both tissues and mostly explained by smoking and sex. The muscle-specific epigenetic clock MEAT was developed to predict chronological age, which may explain why it did not associate with functional phenotypes. The Horvath's clock and GrimAge were weakly associated with PA and related phenotypes, suggesting that higher PA would be linked to accelerated biological ageing in muscle. This may, however, be more reflective of the low capacity of epigenetic clock algorithms to measure functional muscle ageing than of actual age acceleration. Based on our results, the investigated epigenetic clocks have rather low value in estimating muscle ageing with respect to the physiological adaptations that typically occur due to ageing or PA. Thus, further development of methods is needed to gain insight into muscle tissue-specific ageing and the underlying biological pathways.