biological aging
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Background: Measures to quantify changes in the pace of biological aging in response to intervention are needed to evaluate geroprotective interventions for humans. Previously we showed that quantification of the pace of biological aging from a DNA-methylation blood test was possible (Belsky et al. 2020). Here we report a next-generation DNA-methylation biomarker of Pace of Aging, DunedinPACE (for Pace of Aging Calculated from the Epigenome).Methods: We used data from the Dunedin Study 1972-3 birth cohort tracking within-individual decline in 19 indicators of organ-system integrity across four time points spanning two decades to model Pace of Aging. We distilled this two-decade Pace of Aging into a single-time-point DNA-methylation blood-test using elastic-net regression and a DNA-methylation dataset restricted to exclude probes with low test-retest reliability. We evaluated the resulting measure, named DunedinPACE, in five additional datasets.Results: DunedinPACE showed high test-retest reliability, was associated with morbidity, disability, and mortality, and indicated faster aging in young adults with childhood adversity. DunedinPACE effect-sizes were similar to GrimAge Clock effect-sizes. In analysis of incident morbidity, disability, and mortality, DunedinPACE and added incremental prediction beyond GrimAge.Conclusions: DunedinPACE is a novel blood biomarker of the pace of aging for gerontology and geroscience.Funding: This research was supported by US-National Institute on Aging grants AG032282, AG061378, AG066887, and UK Medical Research Council grant MR/P005918/1.

Background. Chronological age (CA) is not a perfect proxy for the true biological aging status of the body. A new biological aging measure, phenotypic age (PhenoAge), has been shown to capture morbidity and mortality risk in the general US population and diverse subpopulations. This study was aimed at evaluating the association between PhenoAge and long-term outcome of patients with multivessel coronary artery disease (CAD). Methods. A total of 609 multivessel CAD patients who received PCI attempt and with follow-up were enrolled. The clinical outcome was all-cause mortality on follow-up. PhenoAge was calculated using an equation constructed from CA and 9 clinical biomarkers. Cox proportional hazards regression models and receiver operating characteristic (ROC) curves were performed to evaluate the association between PhenoAge and mortality. Results. Overall, patients with more diseases had older PhenoAge and phenotypic age acceleration (PhenoAgeAccel). After a median follow-up of 33.5 months, those with positive PhenoAgeAccel had a significantly higher incidence of all-cause mortality ( P = 0.001 ). After adjusting for CA, Cox proportional hazards models showed that both PhenoAge and PhenoAgeAccel were significantly associated with all-cause mortality. Even after further adjusting for confounding factors, each 10-year increase in PhenoAge was also associated with a 51% increased mortality risk. ROC curves revealed that PhenoAge, with an area under the curve of 0.705, significantly outperformed CA, the individual clinical chemistry measure, and other risk factors. When reexamining the ROC curves using various combinations of variables, we found that PhenoAge provides additional predictive power to all models. Conclusions. In conclusion, PhenoAge was strongly associated with all-cause mortality even after adjusting for CA. Our findings suggest that PhenoAge measure may be complementary in predicting mortality risk for patients with multivessel CAD.

Protein biomarkers have been identified across many age-related morbidities. However, characterising epigenetic influences could further inform disease predictions. Here, we leverage epigenome-wide data to study links between the DNAm signatures of the circulating proteome and incident diseases. Using data from four cohorts, we trained and tested epigenetic scores (EpiScores) for 953 plasma proteins, identifying 109 scores that explained between 1% and 58% of the variance in protein levels after adjusting for known protein quantitative trait loci (pQTL) genetic effects. By projecting these EpiScores into an independent sample, (Generation Scotland; n=9,537) and relating them to incident morbidities over a follow-up of 14 years, we uncovered 137 EpiScore – disease associations. These associations were largely independent of immune cell proportions, common lifestyle and health factors and biological aging. Notably, we found that our diabetes-associated EpiScores highlighted previous top biomarker associations from proteome-wide assessments of diabetes. These EpiScores for protein levels can therefore be a valuable resource for disease prediction and risk stratification.

Fino and Amontillado are Sherry wines, produced in Marco de Jerez area (southern Spain), and aged in Criaderas y Solera system. Fino Sherry wine follows a biological aging process, under a veil of flor yeasts, while Amontillado Sherry wine shares the same biological aging firstly, followed by oxidative aging, which gives them special features. Organic acids, esters, higher alcohols, phenolic compounds and total dry extract of Sherries evolve during aging due to evaporation processes, physical-chemical reactions, wood contributions and microbiological activity. During aging, Sherry wines improve their organoleptic profile, as could be proved in the tasting sessions. Hierarchical Cluster Analysis and Factor Analysis with factor extraction using Principal Components of Sherry wines studied were carried out and natural groupings of the wines according to the type of aging and their age were observed. A strong correlation between the parameters analyzed and the aging of each wine has been seen in the Multiple Linear Regression studies, establishing two different models, one for each type of Sherry wine, that, with only four of all the variables studied estimated the wine age with more than 99% of confidence. This constitutes a useful tool to control the age of these Sherry wines in the winery.

In humans, age-associated degrading changes, widely observed in molecular and cellular processes underly the time-dependent decline in spatial navigation, time perception, cognitive and psychological abilities, and memory. Cross-talk of biological, cognitive, and psychological clocks provides an integrative contribution to healthy and advanced aging. At the molecular level, genome, proteome, and lipidome instability are widely recognized as the primary causal factors in aging. We narrow attention to the roles of protein aging linked to prevalent amino acids chirality, enzymatic and spontaneous (non-enzymatic) post-translational modifications (PTMs SP), and non-equilibrium phase transitions. The homochirality of protein synthesis, resulting in the steady-state non-equilibrium condition of protein structure, makes them prone to multiple types of enzymatic and spontaneous PTMs, including racemization and isomerization. Spontaneous racemization leads to the loss of the balanced prevalent chirality. Advanced biological aging related to irreversible PTMs SP has been associated with the nontrivial interplay between somatic (molecular aging) and mental (psychological aging) health conditions. Through stress response systems (SRS), the environmental and psychological stressors contribute to the age-associated “collapse” of protein homochirality. The role of prevalent protein chirality and entropy of protein folding in biological aging is mainly overlooked. In a more generalized context, the time-dependent shift from enzymatic to the non-enzymatic transformation of biochirality might represent an important and yet underappreciated hallmark of aging. We provide the experimental arguments in support of the racemization theory of aging.

Biological aging is the strongest factor associated with the clinical phenotype of multiple sclerosis (MS). Relapsing remitting MS (RRMS) typically presents in the third or fourth decade, while the mean age of presentation of progressive MS (pMS) is 45 years old. Here we show that experimental autoimmune encephalomyelitis (EAE), induced by the adoptive transfer of encephalitogenic CD4+ Th17 cells, is more severe, and less like to remit, in middle-aged compared with young adult mice. Donor T cells and neutrophils are more abundant, while B cells are relatively sparse, in central nervous system (CNS) infiltrates of the older mice. Experiments with reciprocal bone marrow chimeras demonstrate that radio-resistant, non-hematopoietic cells play a dominant role in shaping age-related features of the neuroinflammatory response, as well as the clinical course, during EAE. Reminiscent of pMS, EAE in middle-aged adoptive transfer recipients is characterized by widespread microglial activation. Microglia from older mice express a distinctive transcriptomic profile, suggestive of enhanced chemokine synthesis and antigen presentation. Collectively, our findings suggest that drugs that suppress microglial activation, and acquisition or expression of aging-associated properties, may be beneficial in the treatment of progressive forms of inflammatory demyelinating disease.

The aim was to study the influence of personal factors on the index of individual biological aging in men and women of mature age who continue to work and those who no longer work. The participants were 347 people, including 212 women aged 56-65 years and 111 men aged 61-69 years. Measurement of biological age, relative biological aging index, assessment of subjective psychological age, expected retirement age, life path questionnaire. Biological age was estimated using a formula that included indicators of metabolism, the work of the cardiovascular, respiratory, and balance organ systems; a psychological health questionnaire was also used. The lowest index of relative biological aging was found in people who continued to work part-time. There is a relationship between the index of relative biological aging and one's characteristics. For men, the index was lowered by the following factors: changing the place of residence, continuing to work after retirement, a high indicator of the expected retirement age, and increased by living in a large city. For women, the index was lowered by the following factors: changing the place of residence, continuing to work after retirement, a high indicator of the expected retirement age, higher education, creative hobbies, studying after retirement.

Introduction: Biological aging is associated with changes in the metabolic pathways. Leukocyte telomere length (LTL) is a predictive marker of biological aging; however, the underlying metabolic pathways remain largely unknown. The aim of this study was to investigate the metabolic alterations and identify the metabolic predictors of LTL in elite male soccer players.Methods: Levels of 837 blood metabolites and LTL were measured in 126 young elite male soccer players who tested negative for doping abuse at anti-doping laboratory in Italy. Multivariate analysis using orthogonal partial least squares (OPLS), univariate linear models and enrichment analyses were conducted to identify metabolites and metabolic pathways associated with LTL. Generalized linear model followed by receiver operating characteristic (ROC) analysis were conducted to identify top metabolites predictive of LTL.Results: Sixty-seven metabolites and seven metabolic pathways showed significant associations with LTL. Among enriched pathways, lysophospholipids, benzoate metabolites, and glycine/serine/threonine metabolites were elevated with longer LTL. Conversely, monoacylglycerols, sphingolipid metabolites, long chain fatty acids and polyunsaturated fatty acids were enriched with shorter telomeres. ROC analysis revealed eight metabolites that best predict LTL, including glutamine, N-acetylglutamine, xanthine, beta-sitosterol, N2-acetyllysine, stearoyl-arachidonoyl-glycerol (18:0/20:4), N-acetylserine and 3-7-dimethylurate with AUC of 0.75 (0.64–0.87, p < 0.0001).Conclusion: This study characterized the metabolic activity in relation to telomere length in elite soccer players. Investigating the functional relevance of these associations could provide a better understanding of exercise physiology and pathophysiology of elite athletes.