Combined healthy lifestyle score and risk of epigenetic aging: a discordant monozygotic twin study

"When does human life begin?" teaching human embryology in the context of the American abortion debate

The Dobbs decision of the United States Supreme Court and the actions of several state legislatures have made it risky, if not outright dangerous, to teach factual material concerning human embryology. At some state universities, for instance, if a professor's lecture is felt to teach or discuss abortion (as it might when teaching about tubal pregnancies, hydatidiform moles, or eneuploidy), that instructor risks imprisonment for up to 14 years (Gyori, 2023). Some states' new censorship rules have thus caused professors to drop modules on abortion from numerous science and humanities courses. In most states, instructors can still teach about human embryonic development and not risk putting their careers or livelihoods in jeopardy. However, even in many of these institutions, students can bring a professor to a disciplinary hearing by claiming that the instructor failed to provide ample trigger warnings on such issues. This essay attempts to provide some strategies wherein human embryology and the ethical issues surrounding it might be taught and students may be given resources to counter unscientific falsehoods about fertilization and human development. This essay provides evidence for teaching the following propositions. Mis-information about human biology and medicine is rampant on the internet, and there are skills that can be taught to students that will help them determine which sites should trusted. This is a skill that needs to be taught as part of science courses.

Active longevity and aging: dissecting the impacts of physical and sedentary behaviors on longevity and age acceleration

BACKGROUND

To examine the associations of physical activity (PA) and sedentary behavior (SB) with longevity and age acceleration (AA) using observational and Mendelian randomization (MR) studies, and quantify the mediating effects of lipids.

METHODS

In Guangzhou Biobank Cohort Study (GBCS), PA and SB were assessed by the Chinese Version of the International Physical Activity Questionnaire. Longevity was defined as participants whose age at follow-up or at death was at or above the 90th age percentile. AA was defined as the residual resulting from a linear model that regressed phenotypic age against chronological age. Linear regression and Poisson regression with robust error variance were used to assess the associations of total and specific PA in different intensities, and SB with AA and longevity, yielding βs or relative risks (RRs) and 95% confidence intervals (CIs). Two-sample MR was conducted to examine the causal effects. Mediation analysis was used to assess the mediating effects of lipids.

RESULTS

Of 20,924 participants aged 50 + years in GBCS, during an average follow-up of 15.0 years, compared with low PA, moderate and high PA were associated with higher likelihood of longevity (RR (95% CI): 1.56 (1.16, 2.11), 1.66 (1.24, 2.21), respectively), and also cross-sectionally associated with lower AA (β (95% CI): -1.43 (-2.41, -0.45), -2.09 (-3.06, -1.11) years, respectively). Higher levels of moderate PA (MPA) were associated with higher likelihood of longevity and lower AA, whereas vigorous PA (VPA) showed opposite effects. The association of PA with longevity observed in GBCS was mediated by low-density lipoprotein cholesterol (LDL-C) by 8.23% (95% CI: 3.58-39.61%), while the association with AA was mediated through LDL-C, triglycerides and total cholesterol by 5.13% (3.94-7.30%), 7.81% (5.98-11.17%), and 3.37% (2.59-4.80%), respectively. Additionally, in two-sample MR, SB was positively associated with AA (β (95% CI): 1.02 (0.67, 1.36) years).

CONCLUSIONS

PA showed protective effects on longevity and AA, with the effects being partly mediated through lipids. Conversely, SB had a detrimental impact on AA. MPA was associated with higher likelihood of longevity and reduced AA, whereas VPA showed adverse effects. Our findings reinforce the recommendation of "sit less and move more" to promote healthy longevity, and highlight the potential risks associated with VPA in the elderly.

Investigating the association of measures of epigenetic age with COVID-19 severity: evidence from secondary analyses of open access data

BACKGROUND

Epigenetic modifications may contribute to inter-individual variation that is unexplainable by presently known risk factors for COVID-19 severity (e.g., age, excess weight, or other health conditions). Estimates of youth capital (YC) reflect the difference between an individual's epigenetic - or biological - age and chronological age, and may quantify abnormal aging due to lifestyle or other environmental exposures, providing insights that could inform risk-stratification for severe COVID-19 outcomes. This study aims to thereby a) assess the association between YC and epigenetic signatures of lifestyle exposures with COVID-19 severity, and b) to assess whether the inclusion of these signatures in addition to a signature of COVID-19 severity (EPICOVID) improved the prediction of COVID-19 severity.

METHODS

This study uses data from two publicly-available studies accessed via the Gene Expression Omnibus (GEO) platform (accession references: GSE168739 and GSE174818). The GSE168739 is a retrospective, cross-sectional study of 407 individuals with confirmed COVID-19 across 14 hospitals in Spain, while the GSE174818 sample is a single-center observational study of individuals admitted to the hospital for COVID-19 symptoms (n = 102). YC was estimated using the (a) Gonseth-Nusslé, (b) Horvath, (c) Hannum, and (d) PhenoAge estimates of epigenetic age. Study-specific definitions of COVID-19 severity were used, including hospitalization status (yes/no) (GSE168739) or vital status at the end of follow-up (alive/dead) (GSE174818). Logistic regression models were used to assess the association between YC, lifestyle exposures, and COVID-19 severity.

RESULTS

Higher YC as estimated using the Gonseth-Nusslé, Hannum and PhenoAge measures was associated with reduced odds of severe symptoms (OR = 0.95, 95% CI = 0.91-1.00; OR = 0.81, 95% CI = 0.75 - 0.86; and OR = 0.85, 95% CI = 0.81-0.88, respectively) (adjusting for chronological age and sex). In contrast, a one-unit increase in the epigenetic signature for alcohol consumption was associated with 13% increased odds of severe symptoms (OR = 1.13, 95% CI = 1.05-1.23). Compared to the model including only age, sex and the EPICOVID signature, the additional inclusion of PhenoAge and the epigenetic signature for alcohol consumption improved the prediction of COVID-19 severity (AUC = 0.94, 95% CI = 0.91-0.96 versus AUC = 0.95, 95% CI = 0.93-0.97; p = 0.01). In the GSE174818 sample, only PhenoAge was associated with COVID-related mortality (OR = 0.93, 95% CI = 0.87-1.00) (adjusting for age, sex, BMI and Charlson comorbidity index).

CONCLUSIONS

Epigenetic age is a potentially useful tool in primary prevention, particularly as an incentive towards lifestyle changes that target reducing the risk of severe COVID-19 symptoms. However, additional research is needed to establish potential causal pathways and the directionality of this effect.

Targeted DNA methylation analysis and prediction of smoking habits in blood based on massively parallel sequencing

Tobacco smoking is a frequent habit sustained by > 1.3 billion people in 2020 and the leading preventable factor for health risk and premature mortality worldwide. In the forensic context, predicting smoking habits from biological samples may allow broadening DNA phenotyping. In this study, we aimed to implement previously published smoking habit classification models based on blood DNA methylation at 13 CpGs. First, we developed a matching lab tool based on bisulfite conversion and multiplex PCR followed by amplification-free library preparation and targeted paired-end massively parallel sequencing (MPS). Analysis of six technical duplicates revealed high reproducibility of methylation measurements (Pearson correlation of 0.983). Artificially methylated standards uncovered marker-specific amplification bias, which we corrected via bi-exponential models. We then applied our MPS tool to 232 blood samples from Europeans of a wide age range, of which 90 were current, 71 former and 71 never smokers. On average, we obtained 189,000 reads/sample and 15,000 reads/CpG, without marker drop-out. Methylation distributions per smoking category roughly corresponded to previous microarray analysis, showcasing large inter-individual variation but with technology-driven bias. Methylation at 11 out of 13 smoking-CpGs correlated with daily cigarettes in current smokers, while solely one was weakly correlated with time since cessation in former smokers. Interestingly, eight smoking-CpGs correlated with age, and one displayed weak but significant sex-associated methylation differences. Using bias-uncorrected MPS data, smoking habits were relatively accurately predicted using both two- (current/non-current) and three- (never/former/current) category model, but bias correction resulted in worse prediction performance for both models. Finally, to account for technology-driven variation, we built new, joint models with inter-technology corrections, which resulted in improved prediction results for both models, with or without PCR bias correction (e.g. MPS cross-validation F₁-score > 0.8; 2-categories). Overall, our novel assay takes us one step closer towards the forensic application of viable smoking habit prediction from blood traces. However, future research is needed towards forensically validating the assay, especially in terms of sensitivity. We also need to further shed light on the employed biomarkers, particularly on the mechanistics, tissue specificity and putative confounders of smoking epigenetic signatures.

Dauer vs. Intensität in der Trainingstherapie

Bewegungsinterventionen sind in Gesundheitsförderung und Prävention sowie Therapie und Rehabilitation essenziell, da Bewegung positiv und multidimensional auf die Gesundheit wirkt. Zur Bewertung der Wirkungsweise von Bewegungsinterventionen werden bisher oft Messmethoden herangezogen, welche lediglich einen oberflächlichen Anteil der erzielbaren Effekte abbilden. Eine Voraussetzung für eine erfolgreiche Bewegungsintervention sind eine gute Adhärenz sowie ein adäquates Dosis-Wirkungs-Prinzip. Wie die objektiven und subjektiven Messgrößen in Zusammenhang mit der Adhärenz und infolgedessen mit dem Dosis-Wirkungs-Prinzip stehen, ist nicht ausreichend untersucht. In einer retrospektiven Datenanalyse von 66,988 chronischen Rückenschmerzpatienten, die zwischen 1992 und 2021 an der FPZ RückenTherapie teilgenommen haben, wurden die Zusammenhänge im Ursachen- und Wirkungsdreieck zwischen Therapieadhärenz beziehungsweise Dosis der verabreichten Trainingsreize und damit der benötigten Dauer für ein Programm mit festgelegter Einheit an Trainingseinheiten, dem Zugewinn an isometrischer Maximalkraft der Rumpfmuskulatur sowie dem Gewinn an gesunden Lebensjahren untersucht. Es zeigt sich, dass der Kraftzuwachs abhängig von der Zeit ist, die für die Therapie benötigt wird. Eine andere zeitliche Abhängigkeit zeigt der Gewinn an gesunden Lebensjahren mit steigendem Zeitrahmen, in dem die 24 Einheiten wahrgenommen wurden. Kein Zusammenhang lässt sich dagegen zwischen dem relativen Gewinn an isometrischer Maximalkraft und dem Gewinn an gesunden Lebensjahren feststellen. Die Ergebnisse dieser Studie zeigen wichtige Zusammenhänge zwischen dem zeitlichen Ablauf einer Therapie sowie den angewandten Messparametern auf und sind damit wegweisend für zukünftige Therapieformen. Bisherige Messmethoden müssen ergänzt werden, um die Wirkungsweise von Bewegung und deren multidimensionale Effekte in Gänze abbilden zu können.

Human age reversal: Fact or fiction?

Although chronological age correlates with various age-related diseases and conditions, it does not adequately reflect an individual's functional capacity, well-being, or mortality risk. In contrast, biological age provides information about overall health and indicates how rapidly or slowly a person is aging. Estimates of biological age are thought to be provided by aging clocks, which are computational models (e.g., elastic net) that use a set of inputs (e.g., DNA methylation sites) to make a prediction. In the past decade, aging clock studies have shown that several age-related diseases, social variables, and mental health conditions associate with an increase in predicted biological age relative to chronological age. This phenomenon of age acceleration is linked to a higher risk of premature mortality. More recent research has demonstrated that predicted biological age is sensitive to specific interventions. Human trials have reported that caloric restriction, a plant-based diet, lifestyle changes involving exercise, a drug regime including metformin, and vitamin D3 supplementation are all capable of slowing down or reversing an aging clock. Non-interventional studies have connected high-quality sleep, physical activity, a healthy diet, and other factors to age deceleration. Specific molecules have been associated with the reduction or reversal of predicted biological age, such as the antihypertensive drug doxazosin or the metabolite alpha-ketoglutarate. Although rigorous clinical trials are needed to validate these initial findings, existing data suggest that aging clocks are malleable in humans. Additional research is warranted to better understand these computational models and the clinical significance of lowering or reversing their outputs.

Predictive Utility of Mortality by Aging Measures at Different Hierarchical Levels and the Response to Modifiable Life Style Factors: Implications for Geroprotective Programs

Background

Aging, as a multi-dimensional process, can be measured at different hierarchical levels including biological, phenotypic, and functional levels. The aims of this study were to: (1) compare the predictive utility of mortality by three aging measures at three hierarchical levels; (2) develop a composite aging measure that integrated aging measures at different hierarchical levels; and (3) evaluate the response of these aging measures to modifiable life style factors.

Methods

Data from National Health and Nutrition Examination Survey 1999–2002 were used. Three aging measures included telomere length (TL, biological level), Phenotypic Age (PA, phenotypic level), and frailty index (FI, functional level). Mortality information was collected until December 2015. Cox proportional hazards regression and multiple linear regression models were performed.

Results

A total of 3,249 participants (20–84 years) were included. Both accelerations (accounting for chronological age) of PA and FI were significantly associated with mortality, with HRs of 1.67 [95% confidence interval (CI) = 1.41–1.98] and 1.59 (95% CI = 1.35–1.87), respectively, while that of TL showed non-significant associations. We thus developed a new composite aging measure (named PC1) integrating the accelerations of PA and FI, and demonstrated its better predictive utility relative to each single aging measure. PC1, as well as the accelerations of PA and FI, were responsive to several life style factors including smoking status, body mass index, alcohol consumption, and leisure-time physical activity.

Conclusion

This study demonstrates that both phenotypic (i.e., PA) and functional (i.e., FI) aging measures can capture mortality risk and respond to modifiable life style factors, despite their inherent differences. Furthermore, the PC1 that integrated phenotypic and functional aging measures outperforms in predicting mortality risk in comparison with each single aging measure, and strongly responds to modifiable life style factors. The findings suggest the complementary of aging measures at different hierarchical levels and highlight the potential of life style-targeted interventions as geroprotective programs.

Integrating DNA Methylation Measures of Biological Aging into Social Determinants of Health Research

PURPOSE OF REVIEW

Acceleration of biological processes of aging is hypothesized to drive excess morbidity and mortality in socially disadvantaged populations. DNA methylation measures of biological aging provide tools for testing this hypothesis.

RECENT FINDINGS

Next-generation DNA methylation measures of biological aging developed to predict mortality risk and physiological decline are more predictive of morbidity and mortality than the original epigenetic clocks developed to predict chronological age. These new measures show consistent evidence of more advanced and faster biological aging in people exposed to socioeconomic disadvantage and may be able to record the emergence of socially determined health inequalities as early as childhood. Next-generation DNA methylation measures of biological aging also indicate race/ethnic disparities in biological aging. More research is needed on these measures in samples of non-Western and non-White populations. New DNA methylation measures of biological aging open opportunities for refining inference about the causes of social disparities in health and devising policies to eliminate them. Further refining measures of biological aging by including more diversity in samples used for measurement development is a critical priority for the field.