Health-promoting effect for students from physical loads of speed and strength orientation.

OBJECTIVE: Aim: To investigate the impact of speed and strength physical loads on promoting health and reducing the biological age of student youth. PATIENTS AND METHODS: Materials and Methods: The research involved 180 students aged 18-19. The first stage provided for the study of the indicators of the biological age of 120 students, and the second stage covered substantiation of the methodology for martial arts training sessions, based on physical loads of speed and strength orientation. To test its effectiveness, 60 students were involved (30 were in the experimental group (EG), 30 - in the control group (CG)). RESULTS: Results: The methodology for martial arts training sessions was developed and tested. In the dynamics of the experiment, there is a tendency to a decrease in the difference between the biological and the passport age, but these changes were unreliable in the CG, while a statistically significant decrease in this difference was recorded in the EG. In addition, there were significant changes in the EG in the following indicators: inspiratory breath holding (11.6 %), subjective health assessment (38.5 %), and static balancing (20.0 %). CONCLUSION: Conclusions: The use of physical loads of speed and strength orientation in the course of martial arts training has established a health-promoting effect and positive dynamics of the biological age indicators of student youth. The results of the research can be implemented in physical education and the process of sports improvement of students in higher educational institutions.

Substantiation of the methodology for assessing the biological age of adolescents.

OBJECTIVE: Aim: To substantiate the methodology for assessing the biological age of adolescent high schoolers (boys and girls). PATIENTS AND METHODS: Materials and Methods: Boys aged 14-15 (n = 102) and girls aged 12-13 (n = 101) were studied. The choice of these age groups is explained by the presence of the most significant individual differences in morphological and functional characteristics in these adolescents. Methods: anthropometry, somatometry, somatoscopy, tonometry, spirometry, dynamometry, Stange's test, Rufier and Robinson indices. The interaction of the results of different methods of assessing biological age was conducted on one sex-age sample using factor analysis (principal components method). RESULTS: Results: It has been established that the biological age of adolescents can be reliably determined using a set of three components: an assessment of the level of physical development, the index of heterochronicity, and the degree of manifestation of secondary sexual characteristics (for boys with a probability of 90.2 %, for girls - 92.1 %). The percentage ratio of these components has sexual peculiarities. Methodologies for assessing biological age for scientific purposes and rapid assessment for use in the practice of physical education and sports have been proposed. The indicators of rapid assessment are body length and the degree of hair development in the axilla. The reliability of the rapid assessment is 81.4 % for boys and 83.2 % for girls. CONCLUSION: Conclusions: Developing adequate physical activities for adolescents of different biological ages will help improve the physical health of the younger generation.

Association of accelerated biological aging with brain volumes: A cross-sectional study.

BACKGROUND: Multiple epidemiological studies have observed the connection between aging and brain volumes. The concept of accelerated biological aging (BA) is more powerful for observing the degree of aging of an individual than chronologic age (CA). The objective of this study is to explore the relationship between BA and brain volumes. METHODS: BA was measured from clinical traits using two blood-chemistry algorithms, the Klemera-Doubal method (KDM) and the PhenoAge. The two age acceleration biomarkers were calculated by the residuals from regressing CA, termed "KDM-acceleration" and "PhenoAge-acceleration". Brain volumes were from brain magnetic resonance imaging (MRI) data. After adjustment for confounding factors, general linear regression models were used to examine associations between KDM-acceleration and PhenoAge-acceleration and brain volumes, respectively. Additionally, we stratified participants by sex, age, and the four quartiles of the Townsend Deprivation Index (TDI) for extra subgroup analysis. RESULTS: 14,725 participants with available information were enrolled. After full adjustment, we observed negative associations between KDM-acceleration and brain volumes, such as gray matter (ß = -0.029), white matter (ß = -0.021), gray and white matter (ß = -0.026), and hippocampus (ß = -0.011 for left and ß = -0.014 for right). There were also negative associations between PhenoAge-acceleration and brain volumes, such as white matter (ß = -0.008), gray and white matter (ß = -0.010), thalamus (ß = -0.012 for left and ß = -0.012 for right). In the subgroup analysis stratified by sex, age, and the four quartiles of TDI, the association between KDM-acceleration and PhenoAge-acceleration and brain volumes still existed. In subgroup analyses, the variation in associations suggests that socioeconomic and biological factors may differentially influence brain aging. CONCLUSIONS: Our research indicated that more advanced BA was associated with less brain tissue.

Clinical biomarker-based biological aging and risk of benign prostatic hyperplasia: A large prospective cohort study.

Objective: Chronological age (CAge), biological age (BAge), and accelerated age (AAge) are all important for aging-related diseases. CAge is a known risk factor for benign prostatic hyperplasia (BPH); However, the evidence of association of BAge and AAge with BPH is limited. This study aimed to evaluate the association of CAge, Bage, and AAge with BPH in a large prospective cohort. Method: A total of 135,933 males without BPH at enrolment were extracted from the UK biobank. We calculated three BAge measures (Klemera-Doubal method, KDM; PhenoAge; homeostatic dysregulation, HD) based on 16 biomarkers. Additionally, we calculated KDM-BAge and PhenoAge-BAge measures based on the Levine method. The KDM-AAge and PhenoAge-AAge were assessed by the difference between CAge and BAge and were standardized (mean = 0 and standard deviation [SD] = 1). Cox proportional hazard models were applied to assess the associations of CAge, Bage, and AAge with incident BPH risk. Results: During a median follow-up of 13.150 years, 11,811 (8.690%) incident BPH were identified. Advanced CAge and BAge measures were associated with an increased risk of BPH, showing threshold effects at a later age (all P for nonlinearity <0.001). Nonlinear relationships between AAge measures and risk of BPH were also found for KDM-AAge (P = 0.041) and PhenoAge-AAge (P = 0.020). Compared to the balance comparison group (-1 SD < AAge < 1 SD), the accelerated aging group (AAge > 2 SD) had a significantly elevated BPH risk with hazard ratio (HR) of 1.115 (95% CI, 1.000-1.223) for KDM-AAge and 1.180 (95% CI, 1.068-1.303) for PhenoAge-AAge, respectively. For PhenoAge-AAge, subgroup analysis of the accelerated aging group showed an increased HR of 1.904 (95% CI, 1.374-2.639) in males with CAge <50 years and 1.233 (95% CI, 1.088-1.397) in those having testosterone levels <12 nmol/L. Moreover, AAge-associated risk of BPH was independent of and additive to genetic risk. Conclusions: Biological aging is an independent and modifiable risk factor for BPH. We suggest performing active health interventions to slow biological aging, which will help mitigate the progression of prostate aging and further reduce the burden of BPH.

Frailty and biological age. Which best describes our aging and longevity?

Frailty and Biological Age are two closely related concepts; however, frailty is a multisystem geriatric syndrome that applies to elderly subjects, whereas biological age is a gerontologic way to describe the rate of aging of each individual, which can be used from the beginning of the aging process, in adulthood. If frailty reaches less consensus on the definition, it is a term much more widely used than this of biological age, which shows a clearer definition but is scarcely employed in social and medical fields. In this review, we suggest that this Biological Age is the best to describe how we are aging and determine our longevity, and several examples support our proposal.

The association between SII and aging: evidence from NHANES 1999-2018.

Background: The study aimed to examine the association between the systemic immune-inflammation index (SII), a contemporary metric of systemic inflammatory response, and biological aging, which are closely interconnected processes. Methods: This cross-sectional study utilized 10 cycles of data from the NHANES database spanning from 1990 to 2018. The study examined the relationship between the SII index, calculated as P * N/L, where P represents preoperative peripheral platelet count, N represents neutrophil count, and L represents lymphocyte count, and biological aging. Biological aging was assessed through various methods, such as phenotypic age, phenotypic age acceleration (PhenoAgeAccel), biological age, and biological age acceleration (BioAgeAccel). Correlations were analyzed using weighted linear regression and subgroup analysis. Results: Among the 7,491 participants analyzed, the average age was 45.26 ± 0.34 years, with 52.16% being female. The average phenotypic and biological ages were 40.06 ± 0.36 and 45.89 ± 0.32 years, respectively. Following adjustment for potential confounders, elevated SII scores were linked to increased phenotypic age, biological age, Phenotypic age acceleration, and Biological age acceleration. Positive correlations were observed between health behavior and health factor scores and biological aging, with stronger associations seen for health factors. In health factor-specific analyses, the ß coefficient was notably higher for high BMI. The robust positive associations between SII scores and both phenotypic age and biological age in the stratified analyses were consistently observed across all strata. Conclusion: The evidence from the NHANES data indicate that SII may serve as a valuable marker for assessing different facets of aging and health outcomes, such as mortality and the aging process. Additional research is warranted to comprehensively elucidate the implications of SII in the aging process and its utility as a clinical instrument for evaluating and addressing age-related ailments.

Does BioAge identify accelerated aging in individuals with bipolar disorder? An exploratory study in the FACE-BD cohort.

BACKGROUND: Individuals with bipolar disorders (BD) have an estimated loss of life expectancy around 10-15 years. Several laboratory-measured biomarkers of accelerated aging exist (e.g., telomere length), however with a questionable transferability to bedside. There is a need for easily and inexpensively measurable markers of aging, usable in routine practice, such as BioAge. METHODS: We calculated BioAge that estimates biological age based on routine blood tests and a physical exam, in a sample of 2220 outpatients with BD. We investigated associations between BioAge Acceleration (BioAgeAccel), which is an indicator of accelerated aging, and sociodemographic variables, clinical variables, and current psychotropic medication use. RESULTS: Mean chronological age was 40.2 (±12.9). Mean BioAge was 39.1 (±12.4). Mean BioAgeAccel was 0.08 (±1.8). A minority of individuals (15%) had a BioAgeAccel above 2 years. Multivariable analyses suggested strong associations between a higher BioAgeAccel and younger age, male sex, overweight and sleep disturbances. Regarding current psychotropic medication use, discrepancies between univariate and multivariate analyses were observed. CONCLUSIONS: A minority of individuals with BD had an accelerated aging as measured by BioAge. We identified associations with potentially modifiable factors, such as higher body mass index and sleep disturbances, that are however nonspecific to BD. These results require replications in independent samples of individuals with BD, and comparisons with a control group matched for age and gender. Longitudinal studies are also required to test whether any change in metabolic health, or sleep might decrease BioAgeAccel.

The Gut and Skin Microbiome and Its Association with Aging Clocks.

Aging clocks are predictive models of biological age derived from age-related changes, such as epigenetic changes, blood biomarkers, and, more recently, the microbiome. Gut and skin microbiota regulate more than barrier and immune function. Recent studies have shown that human microbiomes may predict aging. In this narrative review, we aim to discuss how the gut and skin microbiomes influence aging clocks as well as clarify the distinction between chronological and biological age. A literature search was performed on PubMed/MEDLINE databases with the following keywords: "skin microbiome" OR "gut microbiome" AND "aging clock" OR "epigenetic". Gut and skin microbiomes may be utilized to create aging clocks based on taxonomy, biodiversity, and functionality. The top contributing microbiota or metabolic pathways in these aging clocks may influence aging clock predictions and biological age. Furthermore, gut and skin microbiota may directly and indirectly influence aging clocks through the regulation of clock genes and the production of metabolites that serve as substrates or enzymatic regulators. Microbiome-based aging clock models may have therapeutic potential. However, more research is needed to advance our understanding of the role of microbiota in aging clocks.

The mouse Social Frailty Index (mSFI): a novel behavioral assessment for impaired social functioning in aging mice.

Various approaches exist to quantify the aging process and estimate biological age on an individual level. Frailty indices based on an age-related accumulation of physical deficits have been developed for human use and translated into mouse models. However, declines observed in aging are not limited to physical functioning but also involve social capabilities. The concept of "social frailty" has been recently introduced into human literature, but no index of social frailty exists for laboratory mice yet. To fill this gap, we developed a mouse Social Frailty Index (mSFI) consisting of seven distinct assays designed to quantify social functioning which is relatively simple to execute and is minimally invasive. Application of the mSFI in group-housed male C57BL/6 mice demonstrated a progressively elevated levels of social frailty through the lifespan. Conversely, group-housed females C57BL/6 mice manifested social frailty only at a very old age. Female mice also showed significantly lower mSFI score from 10 months of age onward when compared to males. We also applied the mSFI in male C57BL/6 mice under chronic subordination stress and in chronic isolation, both of which induced larger increases in social frailty compared to age-matched group-housed males. Lastly, we show that the mSFI is enhanced in mouse models that show accelerated biological aging such as progeroid Ercc1-/Δ and Xpg-/- mice of both sexes compared to age matched littermate wild types. In summary, the mSFI represents a novel index to quantify trajectories of biological aging in mice and may help elucidate links between impaired social behavior and the aging process.

The Longevity Med Summit: insights on healthspan from cell to society.

In recent years, there has been a paradigm shift with regards to ageing, challenging its traditional perception as an inevitable and natural process. Researchers have collectively identified hallmarks of ageing, nine of which were initially proposed in 2013 and expanded in 2023 to include disabled macroautophagy, chronic inflammation, and dysbiosis, enhancing our understanding of the ageing process at microscopic, cellular, and system-wide levels. Strategies to manipulate these hallmarks present opportunities for slowing, preventing, or reversing age-related diseases, thereby promoting longevity. The interdependence of these hallmarks underscores the necessity of a comprehensive, systems-based approach to address the complex processes contributing to ageing. As a primary risk factor for various diseases, ageing diminishes healthspan, leading to extended periods of compromised health and multiple age-related conditions towards the end of life. The significant gap between healthspan and lifespan holds substantial economic and societal implications. The inaugural Longevity Med Summit (4-5 May 2023, Cascais, Portugal) provided an international forum to discuss the academic and industry landscape of healthy longevity research, preventive medicine and clinical practice to enhance healthspan.

Co-analysis of methylation platforms for signatures of biological aging in the domestic dog reveals previously unexplored confounding factors.

Chronological age reveals the number of years an individual has lived since birth. By contrast, biological age varies between individuals of the same chronological age at a rate reflective of physiological decline. Differing rates of physiological decline are related to longevity and result from genetics, environment, behavior, and disease. The creation of methylation biological age predictors is a long-standing challenge in aging research due to the lack of individual pre-mortem longevity data. The consistent differences in longevity between domestic dog breeds enable the construction of biological age estimators which can, in turn, be contrasted with methylation measurements to elucidate mechanisms of biological aging. We draw on three flagship methylation studies using distinct measurement platforms and tissues to assess the feasibility of creating biological age methylation clocks in the dog. We expand epigenetic clock building strategies to accommodate phylogenetic relationships between individuals, thus controlling for the use of breed standard metrics. We observe that biological age methylation clocks are affected by population stratification and require heavy parameterization to achieve effective predictions. Finally, we observe that methylation-related markers reflecting biological age signals are rare and do not colocalize between datasets.

Biological aging of different blood cell types.

Biological age (BA) captures detrimental age-related changes. The best-known and most-used BA indicators include DNA methylation-based epigenetic clocks and telomere length (TL). The most common biological sample material for epidemiological aging studies, whole blood, is composed of different cell types. We aimed to compare differences in BAs between blood cell types and assessed the BA indicators' cell type-specific associations with chronological age (CA). An analysis of DNA methylation-based BA indicators, including TL, methylation level at cg16867657 in ELOVL2, as well as the Hannum, Horvath, DNAmPhenoAge, and DunedinPACE epigenetic clocks, was performed on 428 biological samples of 12 blood cell types. BA values were different in the majority of the pairwise comparisons between cell types, as well as in comparison to whole blood (p < 0.05). DNAmPhenoAge showed the largest cell type differences, up to 44.5 years and DNA methylation-based TL showed the lowest differences. T cells generally had the "youngest" BA values, with differences across subsets, whereas monocytes had the "oldest" values. All BA indicators, except DunedinPACE, strongly correlated with CA within a cell type. Some differences such as DNAmPhenoAge-difference between naïve CD4 + T cells and monocytes were constant regardless of the blood donor's CA (range 20-80 years), while for DunedinPACE they were not. In conclusion, DNA methylation-based indicators of BA exhibit cell type-specific characteristics. Our results have implications for understanding the molecular mechanisms underlying epigenetic clocks and underscore the importance of considering cell composition when utilizing them as indicators for the success of aging interventions.

Multinational evaluation of anthropometric age (AnthropoAge) as a measure of biological age in the USA, England, Mexico, Costa Rica, and China: a population-based longitudinal study.

OBJECTIVE: To validate AnthropoAge, a new metric of biological age (BA), for prediction of all-cause mortality and age-related outcomes and characterize population-specific aging patterns using multinational longitudinal cohorts. METHODS: We analyzed harmonized multinational data from the Gateway to Global Aging, including studies from the US, England, Mexico, Costa Rica, and China. We used body mass index and waist-to-height ratio to estimate AnthropoAge and AnthropoAgeAccel in participants aged 50-90 years old as proxies of BA and age acceleration, respectively. We compared the predictive capacity for all-cause mortality of AnthropoAge and chronological age (CA) using Cox models, described aging trends in all countries and explored the utility of longitudinal assessments of AnthropoAgeAccel to predict new-onset functional decline and age-related diseases using generalized estimating equations (GEE). FINDINGS: Using data from 55,628 participants, we found AnthropoAge (c-statistic 0.772) outperformed CA (0.76) for prediction of mortality independently of comorbidities, sex, race/ethnicity, education, and lifestyle; this result was replicated in most countries individually except for Mexico. Individuals with accelerated aging had a ~39% higher risk of death, and AnthropoAge also identified trends of faster biological aging per year. In longitudinal analyses, higher AnthropoAgeAccel values were independently predictive of self-reported health deterioration and new-onset deficits in basic/instrumental activities of daily living (ADL/IADL), diabetes, hypertension, cancer, chronic lung disease, myocardial infarction, and stroke. CONCLUSIONS: AnthropoAge is a robust and reproducible BA metric associated with age-related outcomes. Its implementation could facilitate modeling trends of biological aging acceleration in different populations, although recalibration may enhance its utility in underrepresented populations such as individuals from Latin America.

Role of Mesenchymal Stem/Stromal Cells (MSCs) and MSC-Derived Extracellular Vesicles (EVs) in Prevention of Telomere Length Shortening, Cellular Senescence, and Accelerated Biological Aging.

Biological aging is defined as a progressive decline in tissue function that eventually results in cell death. Accelerated biologic aging results when the telomere length is shortened prematurely secondary to damage from biological or environmental stressors, leading to a defective reparative mechanism. Stem cells therapy may have a potential role in influencing (counteract/ameliorate) biological aging and maintaining the function of the organism. Mesenchymal stem cells, also called mesenchymal stromal cells (MSCs) are multipotent stem cells of mesodermal origin that can differentiate into other types of cells, such as adipocytes, chondrocytes, and osteocytes. MSCs influence resident cells through the secretion of paracrine bioactive components such as cytokines and extracellular vesicles (EVs). This review examines the changes in telomere length, cellular senescence, and normal biological age, as well as the factors contributing to telomere shortening and accelerated biological aging. The role of MSCs-especially those derived from gestational tissues-in prevention of telomere shortening (TS) and accelerated biological aging is explored. In addition, the strategies to prevent MSC senescence and improve the antiaging therapeutic application of MSCs and MSC-derived EVs in influencing telomere length and cellular senescence are reviewed.

Factors Associated with Subjective Aging Among Older Outpatients In Northern - India.

Objectives: The objective of the study was to investigate factors associated with subjective aging among older patients visiting a geriatric medicine outpatient department in Northern-India. Methods: The study is a cross-sectional study. Patients were categorized into three groups: whether they felt younger, equal, or older than their peers of same age. Factors such as fall, incontinence, anorexia, hand grip strength, cognition, depression, vision, hearing, cardiopulmonary function and immunization were assessed. Multinominal logistic regression was used to investigate the associated factors of subjective aging. Results: We assessed 184 older patients with a median age of 66.5 years (IQR 63.0 -78.8). Chronological age and hand grip strength were the significant factors associated with subjective aging. With one year increase in age, odds of feeling older than peers of same age decreased by 8.9% (OR, 0.911; 95% CI, 0.831-0.999, p = 0.047). With one kilogram increase in hand grip strength, odds of feeling younger than peers of same age increased by 7.3% (OR, 1.073; 95% CI, 1.01-1.14, p = 0.032). Conclusion: Chronological age and hand grip strength are the factors associated with subjective aging in Northern-Indian older adults. Further longitudinal multi-center studies are needed to confirm our findings.

[Markers of inflammation with decreased functionality in the cognitive and psychological domains of individual vitality in middle-aged and elderly patients with metabolic syndrome.]

Metabolic syndrome is a group of disorders that are closely related to both the risk of developing type 2 diabetes mellitus and cardiovascular diseases, and generally leading to the phenomenon of premature aging of the body. Excessive accumulation of adipose tissue contributes to the development of chronic immune inflammation and oxidative stress, which are both precursors to various disorders, such as insulin resistance, arterial hypertension and dyslipidemia, but also trigger inflammatory processes in patients. An increasing number of studies support the importance of chronic immune inflammation in the pathogenesis of metabolic syndrome, as pro-inflammatory markers such as TNF-α, IL-1ß, IL-6, monocyte chemotactic protein-1 and growth of vascular endothelium. Among a wide range of cytokines, monocyte chemotactic protein-1 is considered one of the most important chemokines, which activates monocytes and other immune cells actively involved in inflammation. Another important point of chronic immune inflammation is its impact on the mental health of patients with metabolic syndrome. Increased levels of anxiety and depression are associated with levels of pro-inflammatory cytokines produced by adipose tissue, which ultimately has an adverse effect on the cognitive status of patients.

Mini-encyclopedia of mitochondria-relevant nutraceuticals protecting health in primary and secondary care-clinically relevant 3PM innovation.

Despite their subordination in humans, to a great extent, mitochondria maintain their independent status but tightly cooperate with the "host" on protecting the joint life quality and minimizing health risks. Under oxidative stress conditions, healthy mitochondria promptly increase mitophagy level to remove damaged "fellows" rejuvenating the mitochondrial population and sending fragments of mtDNA as SOS signals to all systems in the human body. As long as metabolic pathways are under systemic control and well-concerted together, adaptive mechanisms become triggered increasing systemic protection, activating antioxidant defense and repair machinery. Contextually, all attributes of mitochondrial patho-/physiology are instrumental for predictive medical approach and cost-effective treatments tailored to individualized patient profiles in primary (to protect vulnerable individuals again the health-to-disease transition) and secondary (to protect affected individuals again disease progression) care. Nutraceuticals are naturally occurring bioactive compounds demonstrating health-promoting, illness-preventing, and other health-related benefits. Keeping in mind health-promoting properties of nutraceuticals along with their great therapeutic potential and safety profile, there is a permanently growing demand on the application of mitochondria-relevant nutraceuticals. Application of nutraceuticals is beneficial only if meeting needs at individual level. Therefore, health risk assessment and creation of individualized patient profiles are of pivotal importance followed by adapted nutraceutical sets meeting individual needs. Based on the scientific evidence available for mitochondria-relevant nutraceuticals, this article presents examples of frequent medical conditions, which require protective measures targeted on mitochondria as a holistic approach following advanced concepts of predictive, preventive, and personalized medicine (PPPM/3PM) in primary and secondary care.

Shorter donor leukocyte telomere length is associated with poor peripheral blood stem cell mobilization induced by granulocyte colony-stimulating factor.

BACKGROUND/PURPOSE: Insufficient numbers of peripheral blood stem cells (PBSC) after granulocyte colony-stimulating factor (G-CSF) mobilization occurs in a significant proportion of PBSC collections, often from older age donors. Telomere length (TL) is often used as an indicator of an individual's biological age. This study aimed to investigate the relationship between donors' leukocyte TL and the outcome of G-CSF-induced PBSC mobilization in healthy unrelated donors. METHODS: Donors' leukocyte TLs and the outcome of G-CSF-induced PBSC mobilization, as assessed by pre-harvest CD34+ cell counts, were analyzed in 39 healthy PBSC donors. TL in a non-mobilized general population (n = 90) was included as a control group. G-CSF mobilization effect was categorized into three groups according to pre-harvest CD34+ cell count: poor (≤25/µL, PMD), intermediate (between 25 and 180/µL), and good (≥180/µl, GMD). RESULTS: Leukocyte TL of PBSC donors correlated well with pre-harvest CD34+ cell counts (r = 0.645, p < 0.001). Leukocyte TLs of PMDs (n = 8) were significantly shorter than those of GMDs (n = 9) and non-mobilization controls (p < 0.05). Moreover, all PMD TLs were below the 50th percentile, and 62.5% of PMDs had TLs below the 10th percentile of age-matched control participants. In contrast, no GMD TLs were below the 10th percentile; in fact, 33.3% (3/9) of them were above the 90th percentile. CONCLUSION: Our results indicate that shorter donor leukocyte TL is associated with poor G-CSF-induced PBSC mobilization. TL, which represents a donor's biological age, could be a potential predictor for mobilization outcome.

DNA Methylation Mediates the Association Between Cardiometabolic Risk Factors and Cognition: Findings From the Health and Retirement Study.

The association between cardiometabolic risk factors and cognitive function has been well documented, but the underlying mechanisms are not fully understood. This longitudinal study aimed to investigate the potential mediating role of DNA methylation in this association. We conducted the analyses in 3 708 participants (mean [standard deviation {SD}] age: 67.3 [9.5], women: 57.9%) from the Health and Retirement Study who were assessed in the 2014-2020 waves, had Infinium Methylation EPIC BeadChip methylation assays from the 2016 Venous Blood Study, and had cognitive assessment between 2016 and 2020. Causal mediation analyses were used to test the mediation role of DNA methylation in the associations between cardiometabolic risk factors and cognition, adjusting for demographic, socioeconomic, and lifestyle factors. Hypertension (-0.061 in composite cognitive z-score; 95% confidence interval [CI: -0.119, -0.004]) and diabetes (-0.134; 95% CI: [-0.198, -0.071]) were significantly associated with worse cognitive function while abnormal body weight and hypercholesterolemia were not. An increased number of cardiometabolic risk factors was associated with worse cognitive function (p = .002). DNA methylation significantly mediated the association of hypertension (mediated effect on composite cognitive z-score: -0.023; 95% CI: -0.033, -0.014), diabetes (-0.022; 95% CI: -0.032, -0.014), and obesity (-0.021; 95% CI: -0.033, -0.011) with cognitive function, whereas the mediation effect was not observed for having hypercholesterolemia. The estimated proportions mediated were 37.4% for hypertension and 16.7% for diabetes. DNA methylation may be an important mediator linking cardiometabolic risk factors to worse cognition and might even provide a potential target for dementia prevention.

[Novel integrative multi-omics strategies of human's biological age computation.]

Multi-omics methods for analysing postgenomic data have become firmly established in the tools of molecular gerontology only in recent years, since previously there were no comprehensive integrative approaches adequate to the task of calculating biological age. This paper provides an overview of existing papers on multi-omics integrative approaches in calculating the biological age of a human. An analysis of the most common options for integrating methylomic, transcriptomic, proteomic, microbiomic and metabolomic datasets was carried out. We defined (1) concatenation (machine learning), in which models are developed using a concatenated data matrix, formed by combining multiple omics data sets; (2) fusion model approaches that create multiple intermediate submodels for different omics data to then build a final integrated model from the various intermediate submodels; and (3) transformation methods (via artificial intelligence) that first transform each of the single omics data sets into core plots or matrices, and then combine them all into one graph before building an integral complex model. It is unlikely that multi-omics approaches will find application in anti-aging personalized medicine, but they will undoubtedly deepen and expand the understanding of the fundamental processes standing behind the phenomenon of the biological aging clocks.