The Power of a Complex Systems Perspective to Elucidate Aging.

It is becoming highly accepted that aging, age-related diseases, and geriatric healthcare can move forward if reductionist research is complemented by integrative research uniting knowledge on specific aging mechanisms, multiple biomedical, social, psychological, lifestyle, and environmental factors and their interactions. In this special issue, we present exciting papers that illustrate how complexity science theory and practice can be applied to aging research and provide a better understanding and quantification of healthy aging and vulnerability to disease. Recent insights on biomarkers, clocks of aging, frailty, and resilience are covered and studied in interaction with a dynamic multiscale perspective. The editorial and closing viewpoint guide you through basic principles of gerontological complexity science and shed light on new research horizons, including innovative systems-based interventions.

The brain-body energy conservation model of aging.

Aging involves seemingly paradoxical changes in energy metabolism. Molecular damage accumulation increases cellular energy expenditure, yet whole-body energy expenditure remains stable or decreases with age. We resolve this apparent contradiction by positioning the brain as the mediator and broker in the organismal energy economy. As somatic tissues accumulate damage over time, costly intracellular stress responses are activated, causing aging or senescent cells to secrete cytokines that convey increased cellular energy demand (hypermetabolism) to the brain. To conserve energy in the face of a shrinking energy budget, the brain deploys energy conservation responses, which suppress low-priority processes, producing fatigue, physical inactivity, blunted sensory capacities, immune alterations and endocrine 'deficits'. We term this cascade the brain-body energy conservation (BEC) model of aging. The BEC outlines (1) the energetic cost of cellular aging, (2) how brain perception of senescence-associated hypermetabolism may drive the phenotypic manifestations of aging and (3) energetic principles underlying the modifiability of aging trajectories by stressors and geroscience interventions.

Challenges and recommendations for the translation of biomarkers of aging.

Biomarkers of aging (BOA) are quantitative parameters that predict biological age and ideally its changes in response to interventions. In recent years, many promising molecular and omic BOA have emerged with an enormous potential for translational geroscience and improving healthspan. However, clinical translation remains limited, in part due to the gap between preclinical research and the application of BOA in clinical research and other translational settings. We surveyed experts in these areas to better understand current challenges for the translation of aging biomarkers. We identified six key barriers to clinical translation and developed guidance for the field to overcome them. Core recommendations include linking BOA to clinically actionable insights, improving affordability and availability to broad populations and validation of biomarkers that are robust and responsive at the level of individuals. Our work provides key insights and practical recommendations to overcome barriers impeding clinical translation of BOA.

Brain-body mitochondrial distribution patterns lack coherence and point to tissue-specific and individualized regulatory mechanisms.

Energy transformation capacity is generally assumed to be a coherent individual trait driven by genetic and environmental factors. This predicts that some individuals should have high and others low mitochondrial oxidative phosphorylation (OxPhos) capacity across organ systems. Here, we test this assumption using multi-tissue molecular and enzymatic activities in mice and humans. Across up to 22 mouse tissues, neither mitochondrial OxPhos capacity nor mtDNA density were correlated between tissues (median r = -0.01-0.16), indicating that animals with high mitochondrial capacity in one tissue can have low capacity in other tissues. Similarly, the multi-tissue correlation structure of RNAseq-based indices of mitochondrial gene expression across 45 tissues from 948 women and men (GTEx) showed small to moderate coherence between only some tissues (regions of the same brain), but not between brain-body tissue pairs in the same person (median r = 0.01). Mitochondrial DNA copy number (mtDNAcn) also lacked coherence across organs and tissues. Mechanistically, tissue-specific differences in mitochondrial gene expression were attributable in part to i) tissue-specific activation of canonical energy sensing pathways including the transcriptional coactivator PGC-1 and the integrated stress response (ISR), and ii) proliferative activity across tissues. Finally, we identify subgroups of individuals with high mitochondrial gene expression in some tissues (e.g., heart) but low expression in others (e.g., skeletal muscle) who display different clinical phenotypic patterns. Taken together, these data raise the possibility that tissue-specific energy sensing pathways may contribute to the idiosyncratic mitochondrial distribution patterns associated with the inter-organ heterogeneity and phenotypic diversity among individuals.

Application of early warning signs to physiological contexts: a comparison of multivariate indices in patients on long-term hemodialysis.

Early warnings signs (EWSs) can anticipate abrupt changes in system state, known as "critical transitions," by detecting dynamic variations, including increases in variance, autocorrelation (AC), and cross-correlation. Numerous EWSs have been proposed; yet no consensus on which perform best exists. Here, we compared 15 multivariate EWSs in time series of 763 hemodialyzed patients, previously shown to present relevant critical transition dynamics. We calculated five EWSs based on AC, six on variance, one on cross-correlation, and three on AC and variance. We assessed their pairwise correlations, trends before death, and mortality predictive power, alone and in combination. Variance-based EWSs showed stronger correlations (r = 0.663 ± 0.222 vs. 0.170 ± 0.205 for AC-based indices) and a steeper increase before death. Two variance-based EWSs yielded HR95 > 9 (HR95 standing for a scale-invariant metric of hazard ratio), but combining them did not improve the area under the receiver-operating curve (AUC) much compared to using them alone (AUC = 0.798 vs. 0.796 and 0.791). Nevertheless, the AUC reached 0.825 when combining 13 indices. While some indicators did not perform overly well alone, their addition to the best performing EWSs increased the predictive power, suggesting that indices combination captures a broader range of dynamic changes occurring within the system. It is unclear whether this added benefit reflects measurement error of a unified phenomenon or heterogeneity in the nature of signals preceding critical transitions. Finally, the modest predictive performance and weak correlations among some indices call into question their validity, at least in this context.

Validation of biomarkers of aging.

The search for biomarkers that quantify biological aging (particularly 'omic'-based biomarkers) has intensified in recent years. Such biomarkers could predict aging-related outcomes and could serve as surrogate endpoints for the evaluation of interventions promoting healthy aging and longevity. However, no consensus exists on how biomarkers of aging should be validated before their translation to the clinic. Here, we review current efforts to evaluate the predictive validity of omic biomarkers of aging in population studies, discuss challenges in comparability and generalizability and provide recommendations to facilitate future validation of biomarkers of aging. Finally, we discuss how systematic validation can accelerate clinical translation of biomarkers of aging and their use in gerotherapeutic clinical trials.

Rethinking the pros and cons of randomized controlled trials and observational studies in the era of big data and advanced methods: a panel discussion.

Randomized controlled trials (RCTs) have traditionally been considered the gold standard for medical evidence. However, in light of emerging methodologies in data science, many experts question the role of RCTs. Within this context, experts in the USA and Canada came together to debate whether the primacy of RCTs as the gold standard for medical evidence, still holds in light of recent methodological advances in data science and in the era of big data. The purpose of this manuscript, aims to raise awareness of the pros and cons of RCTs and observational studies in order to help guide clinicians, researchers, students, and decision-makers in making informed decisions on the quality of medical evidence to support their work. In particular, new and underappreciated advantages and disadvantages of both designs are contrasted. Innovations taking place in both of these research methodologies, which can blur the lines between the two, are also discussed. Finally, practical guidance for clinicians and future directions in assessing the quality of evidence is offered.

Effect of Extra Virgin Olive Oil on Anthropometric Indices, Inflammatory and Cardiometabolic Markers: a Systematic Review and Meta-Analysis of Randomized Clinical Trials.

BACKGROUND: A large body of literature associated extra virgin olive oil (EVOO) consumption with low risk of cardiovascular disease and mortality. However, findings from clinical trials related to EVOO consumption on blood pressure, lipid profile, and anthropometric and inflammation parameters are not univocal. OBJECTIVES: The aim of this systematic review and meta-analysis was to evaluate the effect of EVOO consumption on cardiometabolic risk factors and inflammatory mediators. METHODS: We searched PubMed/MEDLINE, Scopus, and Cochrane up through 31 March, 2023, without any particular language limitations, in order to identify randomized controlled trials (RCTs) that examined the effects of EVOO consumption on cardiometabolic risk factors, inflammatory mediators, and anthropometric indices. Outcomes were summarized as standardized mean difference (SMD) with 95% confidence intervals (CIs) estimated from Hedge's g and random-effects modeling. Heterogeneity was assessed by Cochran Q-statistic and quantified (I2). RESULTS: Thirty-three trials involving 2020 participants were included. EVOO consumption was associated with a significant decrease in insulin (n = 10; SMD: -0.28; 95% CI: -0.51, -0.05; I2 = 48.57%) and homeostasis model assessment of insulin resistance levels (HOMA-IR) (n = 9; SMD: -0.19; 95% CI: -0.35, -0.03; I2 = 00.00%). This meta-analysis indicated no significant effect of consuming EVOO on fasting blood glucose, triglycerides, total cholesterol, low density lipoproteins, very low density lipoproteins, high density lipoproteins, Apolipoprotein (Apo) A-I and B, lipoprotein a, blood pressure, body mass index, waist circumference, waist to hip ratio, C-reactive protein, interleukin-6, interleukin-10, and tumor necrosis factor α levels (P > 0.05). CONCLUSIONS: The present evidence supports a beneficial effect of EVOO consumption on serum insulin levels and HOMA-IR. However, larger well-designed RCTs are still required to evaluate the effect of EVOO on cardiometabolic risk biomarkers. This study was registered in PROSPERO as CRD42023409125.

Accelerated aging mediates the associations of unhealthy lifestyles with cardiovascular disease, cancer, and mortality.

BACKGROUND: With two well-validated aging measures capturing mortality and morbidity risk, this study examined whether and to what extent aging mediates the associations of unhealthy lifestyles with adverse health outcomes. METHODS: Data were from 405,944 adults (40-69 years) from UK Biobank (UKB) and 9972 adults (20-84 years) from the US National Health and Nutrition Examination Survey (NHANES). An unhealthy lifestyles score (range: 0-5) was constructed based on five factors (smoking, drinking, physical inactivity, unhealthy body mass index, and unhealthy diet). Two aging measures, Phenotypic Age Acceleration (PhenoAgeAccel) and Biological Age Acceleration (BioAgeAccel) were calculated using nine and seven blood biomarkers, respectively, with a higher value indicating the acceleration of aging. The outcomes included incident cardiovascular disease (CVD), incident cancer, and all-cause mortality in UKB; CVD mortality, cancer mortality, and all-cause mortality in NHANES. A general linear regression model, Cox proportional hazards model, and formal mediation analysis were performed. RESULTS: The unhealthy lifestyles score was positively associated with PhenoAgeAccel (UKB: ß = 0.741; NHANES: ß = 0.874, all p < 0.001). We further confirmed the respective associations of PhenoAgeAccel and unhealthy lifestyles with the outcomes in UKB and NHANES. The mediation proportion of PhenoAgeAccel in associations of unhealthy lifestyles with incident CVD, incident cancer, and all-cause mortality were 20.0%, 17.8%, and 26.6% (all p < 0.001) in UKB, respectively. Similar results were found in NHANES. The findings were robust when using another aging measure-BioAgeAccel. CONCLUSIONS: Accelerated aging partially mediated the associations of lifestyles with CVD, cancer, and mortality in UK and US populations. The findings reveal a novel pathway and the potential of geroprotective programs in mitigating health inequality in late life beyond lifestyle interventions.

Physiological Dysregulation Proceeds and Predicts Health Outcomes Similarly in Chinese and Western Populations.

BACKGROUND: A decade ago, we proposed an index of physiological dysregulation based on Mahalanobis distance (DM) that measures how far from the norm an individual biomarker profile is. While extensive validation has been performed, focus was mostly on Western populations with little comparison to developing countries, particularly at a physiological system level. The degree to which the approach would work in other sociocultural contexts and the similarity of dysregulation signatures across diverse populations are still open questions. METHODS: Using 2 data sets from China and 3 from Western countries (United States, United Kingdom, and Italy), we calculated DM globally and per physiological system. We assessed pairwise correlations among systems, difference with age, prediction of mortality and age-related diseases, and sensitivity to interchanging data sets with one another as the reference in DM calculation. RESULTS: Overall, results were comparable across all data sets. Different physiological systems showed distinct dysregulation processes. Association with age was moderate and often nonlinear, similarly for all populations. Mahalanobis distance predicted most health outcomes, although differently by physiological system. Using a Chinese population as the reference when calculating DM for Western populations, or vice versa, led to similar associations with health outcomes, with a few exceptions. CONCLUSIONS: While small differences were noticeable, they did not systematically emerge between Chinese and Western populations, but rather diffusively across all data sets. These findings suggest that DM presents similar properties, notwithstanding sociocultural backgrounds, and that it is equally effective in capturing the loss of homeostasis that occurs during aging in diverse industrial human populations.

Evidence for protein leverage on total energy intake, but not body mass index, in a large cohort of older adults.

BACKGROUND: Protein leverage (PL) is the phenomenon of consuming food until absolute intake of protein approaches a 'target value', such that total energy intake (TEI) varies passively with the ratio of protein: non-protein energy (fat + carbohydrate) in the diet. The PL hypothesis (PLH) suggests that the dilution of protein in energy-dense foods, particularly those rich in carbohydrates and fats, combines with protein leverage to contribute to the global obesity epidemic. Evidence for PL has been reported in younger adults, children and adolescents. This study aimed to test for PL and the protein leverage hypothesis (PLH) in a cohort of older adults. METHODS: We conducted a retrospective analysis of dietary intake in a cohort of 1699 community-dwelling older adults aged 67-84 years from the NuAge cohort. We computed TEI and the energy contribution (EC) from each macronutrient. The strength of leverage of macronutrients was assessed through power functions ( TEI = µ * EC L ). Body mass index (BMI) was calculated, and mixture models were fitted to predict TEI and BMI from macronutrients' ECs. RESULTS: In this cohort of older adults, 53% of individuals had obesity and 1.5% had severe cases. The mean TEI was 7673 kJ and macronutrients' ECs were 50.4%, 33.2% and 16.4%, respectively for carbohydrates, fat, and protein. There was a strong negative association (L = -0.37; p < 0.001) between the protein EC and TEI. Each percent of energy intake from protein reduced TEI by 77 kJ on average, ceteris paribus. However, BMI was unassociated with TEI in this cohort. CONCLUSIONS: Findings indicate clear evidence for PL on TEI, but not on BMI, likely because of aging, body composition, sarcopenia, or protein wasting.

Biomarkers of aging for the identification and evaluation of longevity interventions.

With the rapid expansion of aging biology research, the identification and evaluation of longevity interventions in humans have become key goals of this field. Biomarkers of aging are critically important tools in achieving these objectives over realistic time frames. However, the current lack of standards and consensus on the properties of a reliable aging biomarker hinders their further development and validation for clinical applications. Here, we advance a framework for the terminology and characterization of biomarkers of aging, including classification and potential clinical use cases. We discuss validation steps and highlight ongoing challenges as potential areas in need of future research. This framework sets the stage for the development of valid biomarkers of aging and their ultimate utilization in clinical trials and practice.

Viruses - a major cause of amyloid deposition in the brain.

INTRODUCTION: Clinically, Alzheimer's disease (AD) is a syndrome with a spectrum of various cognitive disorders. There is a complete dissociation between the pathology and the clinical presentation. Therefore, we need a disruptive new approach to be able to prevent and treat AD. AREAS COVERED: In this review, the authors extensively discuss the evidence why the amyloid beta is not the pathological cause of AD which makes therefore the amyloid hypothesis not sustainable anymore. They review the experimental evidence underlying the role of microbes, especially that of viruses, as a trigger/cause for the production of amyloid beta leading to the establishment of a chronic neuroinflammation as the mediator manifesting decades later by AD as a clinical spectrum. In this context, the emergence and consequences of the infection/antimicrobial protection hypothesis are described. The epidemiological and clinical data supporting this hypothesis are also analyzed. EXPERT OPINION: For decades, we have known that viruses are involved in the pathogenesis of AD. This discovery was ignored and discarded for a long time. Now we should accept this fact, which is not a hypothesis anymore, and stimulate the research community to come up with new ideas, new treatments, and new concepts.

Which interventions with youths counter ageism toward older adults? Results from a realist review.

Age-related social biases - ageism - are developed at an early age. Interventions to counter ageism have been identified but little is known about their mechanisms, particularly in children. This study aimed to provide a comprehensive understanding of which interventions in youths are most effective, under which circumstances, how, and with what outcomes. Using 46 keywords in 6 databases, a realist review identified 24 studies published between 2000 and 2022 targeting youths under 18. A content analysis of these studies led to the construction of a Context-Mechanisms-Outcomes explanatory model. Contextual facilitators triggering mechanisms for changing stereotypes, prejudices and discrimination were: 1) enhancing knowledge about aging and older adults by providing nuanced information, 2) improving the quality of intergenerational contacts, 3) increasing opportunities to apply previously acquired knowledge in intergenerational interactions, and 4) promoting reflective thinking about experiences with older adults. However, stereotypes and prejudices appeared to be resistant and changes difficult to generalize. Insufficiently advanced cognitive development in children or viewing healthy and socially engaged older adults as unrepresentative of their age group were obstacles that reduced intervention effectiveness. Future studies should explore how advancing age influences interventions as well as the characteristics of older adults involved.

Intercorrelated variability in blood and hemodynamic biomarkers reveals physiological network in hemodialysis patients.

Increased intra-individual variability of a variety of biomarkers is generally associated with poor health and reflects physiological dysregulation. Correlations among these biomarker variabilities should then represent interactions among heterogeneous biomarker regulatory systems. Herein, in an attempt to elucidate the network structure of physiological systems, we probed the inter-variability correlations of 22 biomarkers. Time series data on 19 blood-based and 3 hemodynamic biomarkers were collected over a one-year period for 334 hemodialysis patients, and their variabilities were evaluated by coefficients of variation. The network diagram exhibited six clusters in the physiological systems, corresponding to the regulatory domains for metabolism, inflammation, circulation, liver, salt, and protein. These domains were captured as latent factors in exploratory and confirmatory factor analyses (CFA). The 6-factor CFA model indicates that dysregulation in each of the domains manifests itself as increased variability in a specific set of biomarkers. Comparison of a diabetic and non-diabetic group within the cohort by multi-group CFA revealed that the diabetic cohort showed reduced capacities in the metabolism and salt domains and higher variabilities of the biomarkers belonging to these domains. The variability-based network analysis visualizes the concept of homeostasis and could be a valuable tool for exploring both healthy and pathological conditions.

Newfound Coding Potential of Transcripts Unveils Missing Members of Human Protein Communities.

Recent proteogenomic approaches have led to the discovery that regions of the transcriptome previously annotated as non-coding regions [i.e., untranslated regions (UTRs), open reading frames overlapping annotated coding sequences in a different reading frame, and non-coding RNAs] frequently encode proteins, termed alternative proteins (altProts). This suggests that previously identified protein-protein interaction (PPI) networks are partially incomplete because altProts are not present in conventional protein databases. Here, we used the proteogenomic resource OpenProt and a combined spectrum- and peptide-centric analysis for the re-analysis of a high-throughput human network proteomics dataset thereby revealing the presence of 261 altProts in the network. We found 19 genes encoding both an annotated (reference) and an alternative protein interacting with each other. Of the 117 altProts encoded by pseudogenes, 38 are direct interactors of reference proteins encoded by their respective parental gene. Finally, we experimentally validate several interactions involving altProts. These data improve the blueprints of the human PPI network and suggest functional roles for hundreds of altProts.

Multidimensional associations between nutrient intake and healthy ageing in humans.

BACKGROUND: Little is known about how normal variation in dietary patterns in humans affects the ageing process. To date, most analyses of the problem have used a unidimensional paradigm, being concerned with the effects of a single nutrient on a single outcome. Perhaps then, our ability to understand the problem has been complicated by the fact that both nutrition and the physiology of ageing are highly complex and multidimensional, involving a high number of functional interactions. Here we apply the multidimensional geometric framework for nutrition to data on biological ageing from 1560 older adults followed over four years to assess on a large-scale how nutrient intake associates with the ageing process. RESULTS: Ageing and age-related loss of homeostasis (physiological dysregulation) were quantified via the integration of blood biomarkers. The effects of diet were modelled using the geometric framework for nutrition, applied to macronutrients and 19 micronutrients/nutrient subclasses. We observed four broad patterns: (1) The optimal level of nutrient intake was dependent on the ageing metric used. Elevated protein intake improved/depressed some ageing parameters, whereas elevated carbohydrate levels improved/depressed others; (2) There were non-linearities where intermediate levels of nutrients performed well for many outcomes (i.e. arguing against a simple more/less is better perspective); (3) There is broad tolerance for nutrient intake patterns that don't deviate too much from norms ('homeostatic plateaus'). (4) Optimal levels of one nutrient often depend on levels of another (e.g. vitamin E and vitamin C). Simpler linear/univariate analytical approaches are insufficient to capture such associations. We present an interactive tool to explore the results in the high-dimensional nutritional space. CONCLUSION: Using multidimensional modelling techniques to test the effects of nutrient intake on physiological dysregulation in an aged population, we identified key patterns of specific nutrients associated with minimal biological ageing. Our approach presents a roadmap for future studies to explore the full complexity of the nutrition-ageing landscape.

Associations between exposure to adverse childhood experiences and biological aging: Evidence from the Canadian Longitudinal Study on Aging.

People exposed to adverse childhood experiences (ACEs) suffer from an increased risk of chronic disease and shorter lifespan. These individuals also tend to exhibit accelerated reproductive development and show signs of advanced cellular aging as early as childhood. These observations suggest that ACEs may accelerate biological processes of aging through direct or indirect mechanisms; however, few population-based studies have data to test this hypothesis. We analysed ACEs and biological aging data from the Canadian Longitudinal Study on Aging (CLSA; n = 23,354 adults aged 45-85) and used the BioAge R package to compute three indices of biological aging from blood-chemistry and organ-function data: Klemera-Doubal method (KDM) biological age, phenotypic age (PA), and homeostatic dysregulation (HD). Adults with ACEs tended to be biologically older than those with no ACEs, although the observed effect-sizes were small (Cohen's d<0.15), with the exception of neglect (d=0.35 for KDM and PA). Associations were similar for men and women and tended to be smaller for older as compared to midlife participants. Subtypes of ACEs perceived as being more severe (e.g., being pushed or kicked, experiencing forced sexual activity, witnessing physical violence) and more frequent and diverse exposures were associated with relatively larger effect-sizes. These findings support the hypothesis that ACEs contribute to accelerated biological aging, although replication is needed in studies with access to prospective records of ACEs and cellular-level measurements of biological aging. Furthermore, future work to better understand the degree to which associations between ACEs and biological aging are moderated by specific life-course pathways, and mediated by lifestyle and socioeconomic factors is warranted.

Synchrony of biomarker variability indicates a critical transition: Application to mortality prediction in hemodialysis.

Critical transition theory suggests that complex systems should experience increased temporal variability just before abrupt state changes. We tested this hypothesis in 763 patients on long-term hemodialysis, using 11 biomarkers collected every two weeks and all-cause mortality as a proxy for critical transitions. We find that variability-measured by coefficients of variation (CVs)-increases before death for all 11 clinical biomarkers, and is strikingly synchronized across all biomarkers: the first axis of a principal component analysis on all CVs explains 49% of the variance. This axis then generates powerful predictions of mortality (HR95 = 9.7, p < 0.0001, where HR95 is a scale-invariant metric of hazard ratio; AUC up to 0.82) and starts to increase markedly ∼3 months prior to death. Our results provide an early warning sign of physiological collapse and, more broadly, a quantification of joint system dynamics that opens questions of how system modularity may break down before critical transitions.