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Frailty in aging marks a state of decreased reserves resulting in increased vulnerability to adverse outcomes when exposed to stressors. This Perspective synthesizes the evidence on the aging-related pathophysiology underpinning the clinical presentation of physical frailty as a phenotype of a clinical syndrome that is distinct from the cumulative-deficit-based frailty index. We focus on integrating the converging evidence on the conceptualization of physical frailty as a state, largely independent of chronic diseases, that emerges when the dysregulation of multiple interconnected physiological and biological systems crosses a threshold to critical dysfunction, severely compromising homeostasis. Our exegesis posits that the physiology underlying frailty is a critically dysregulated complex dynamical system. This conceptual framework implies that interventions such as physical activity that have multisystem effects are more promising to remedy frailty than interventions targeted at replenishing single systems. We then consider how this framework can drive future research to further understanding, prevention and treatment of frailty, which will likely preserve health and resilience in aging populations. Linda Fried and colleagues argue that physical frailty reflects the dysregulation of a complex dynamical system underpinning health and resilience, and discuss the implications for new prevention and treatment approaches.

The immune system is the most important protective physiological system of the organism. It has many connections with other systems and is, in fact, often considered as part of the larger neuro-endocrine-immune axis. Most experimental data on immune changes with aging show a decline in many immune parameters when compared to young healthy subjects. The bulk of these changes is termed immunosenescence. Immunosenescence has been considered for some time as detrimental because it often leads to subclinical accumulation of pro-inflammatory factors and inflamm-aging. Together, immunosenescence and inflamm-aging are suggested to stand at the origin of most of the diseases of the elderly, such as infections, cancer, autoimmune disorders, and chronic inflammatory diseases. However, an increasing number of immune-gerontologists have challenged this negative interpretation of immunosenescence with respect to its significance in aging-related alterations of the immune system. If one considers these changes from an evolutionary perspective, they can be viewed preferably as adaptive or remodeling rather than solely detrimental. Whereas it is conceivable that global immune changes may lead to various diseases, it is also obvious that these changes may be needed for extended survival/longevity. Recent cumulative data suggest that, without the existence of the immunosenescence/inflamm-aging duo (representing two sides of the same phenomenon), human longevity would be greatly shortened. This review summarizes recent data on the dynamic reassessment of immune changes with aging. Accordingly, attempts to intervene on the aging immune system by targeting its rejuvenation, it may be more suitable to aim to maintain general homeostasis and function by appropriately improving immune-inflammatory-functions.

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.

Mechanisms maintaining honesty of sexual signals are far from resolved, limiting our understanding of sexual selection and potential important parts of physiology. Carotenoid pigmented visual signals are among the most extensively studied sexual displays, but evidence regarding hypotheses on how carotenoids ensure signal honesty is mixed. Using a phylogenetically controlled meta-analysis of 357 effect sizes across 88 different species of birds, we tested two prominent hypotheses in the field: that carotenoid-dependent coloration signals i) immunocompetence and/or ii) oxidative stress state. Separate meta-analyses were performed for the relationships of trait coloration and circulating carotenoid level with different measures of immunocompetence and oxidative stress state. For immunocompetence we find that carotenoid levels (r = 0.20) and trait color intensity (r = 0.17) are significantly positively related to PHA response. Additionally we find that carotenoids are significantly positively related to antioxidant capacity (r = 0.10), but not significantly related to oxidative damage (r = -0.02). Thus our analyses provide support for both hypotheses, in that at least for some aspects of immunity and oxidative stress state the predicted correlations were found. Furthermore, we tested for differences in effect size between experimental and observational studies; a larger effect in observational studies would indicate that co-variation might not be causal. However, we detected no significant difference, suggesting that the relationships we found are causal. The overall effect sizes we report are modest and we discuss potential factors contributing to this, including differences between species. We suggest complementary mechanisms maintaining honesty rather than the involvement of carotenoids in immune function and oxidative stress and suggest experiments on how to test these.

Mitochondrial disease (MitoD), a clinical condition caused by genetic mitochondrial defects, affects cellular energy transformation and alters multiple dimensions of health. Recently, we collected a longitudinal saliva proteomics data set consisting of six healthy controls and six MitoD subjects throughout the awakening response process. We undertook three independent unsupervised or inferential approaches to characterize proteome dynamics and assessed their ability to separate MitoD individuals from controls. First, we designed a permutation test to detect the global difference in the proteomic co-regulation structure between healthy and unhealthy subjects. Second, we performed non-linear embedding and cluster analysis on elasticity to capture a more complicated relationship between health and the proteome. Third, we developed a machine learning algorithm to extract low-dimensional representations of the proteome dynamic and use them to cluster subjects into healthy and unhealthy groups without any knowledge of their true status. All three methods showed clear differences between MitoD individuals and controls. Our results revealed a significant and consistent association between MitoD status and the saliva proteome at multiple levels during the awakening response, including its dynamic change, co-regulation structure, and elasticity. Pipelines such as those shown here are the first step toward establishing interpretable and accurate framework for detecting signals related to mitochondrial disease progression from proteome dynamics.

National malaria death rates are difficult to assess because reliably diagnosed malaria is likely to be cured, and deaths in the community from undiagnosed malaria could be misattributed in retrospective enquiries to other febrile causes of death, or vice-versa. We aimed to estimate plausible ranges of malaria mortality in India, the most populous country where the disease remains common. Full-time non-medical field workers interviewed families or other respondents about each of 122 000 deaths during 2001–03 in 6671 randomly selected areas of India, obtaining a half-page narrative plus answers to specific questions about the severity and course of any fevers. Each field report was sent to two of 130 trained physicians, who independently coded underlying causes, with discrepancies resolved either via anonymous reconciliation or adjudication. Of all coded deaths at ages 1 month to 70 years, 2681 (3·6%) of 75 342 were attributed to malaria. Of these, 2419 (90%) were in rural areas and 2311 (86%) were not in any health-care facility. Death rates attributed to malaria correlated geographically with local malaria transmission ratesderived independently from the Indian malaria control programme. The adjudicated results show 205 000 malaria deaths per year in India before age 70 years (55 000 in early childhood, 30 000 at ages 5–14 years, 120 000 at ages 15–69 years); 1·8% cumulative probability of death from malaria before age 70 years. Plausible lower and upper bounds (on the basis of only the initial coding) were 125 000–277 000. Malaria accounted for a substantial minority of about 1·3 million unattended rural fever deaths attributed to infectious diseases in people younger than 70 years. Despite uncertainty as to which unattended febrile deaths are from malaria, even the lower bound greatly exceeds the WHO estimate of only 15 000 malaria deaths per year in India (5000 early childhood, 10 000 thereafter). This low estimate should be reconsidered, as should the low WHO estimate of adult malaria deaths worldwide. US National Institutes of Health, Canadian Institute of Health Research, Li Ka Shing Knowledge Institute.

Many studies of aging examine biomarkers one at a time, but complex systems theory and network theory suggest that interpretations of individual markers may be context-dependent. Here, we attempted to detect underlying processes governing the levels of many biomarkers simultaneously by applying principal components analysis to 43 common clinical biomarkers measured longitudinally in 3694 humans from three longitudinal cohort studies on two continents (Women's Health and Aging I & II, InCHIANTI, and the Baltimore Longitudinal Study on Aging). The first axis was associated with anemia, inflammation, and low levels of calcium and albumin. The axis structure was precisely reproduced in all three populations and in all demographic sub-populations (by sex, race, etc.); we call the process represented by the axis \"integrated albunemia.\" Integrated albunemia increases and accelerates with age in all populations, and predicts mortality and frailty--but not chronic disease--even after controlling for age. This suggests a role in the aging process, though causality is not yet clear. Integrated albunemia behaves more stably across populations than its component biomarkers, and thus appears to represent a higher-order physiological process emerging from the structure of underlying regulatory networks. If this is correct, detection of this process has substantial implications for physiological organization more generally.

Evolutionary studies often assume that energy is the primary resource (i.e. \"currency\") at the heart of the survival-reproduction trade-off, despite recent evidence to the contrary. The evolutionary consequences of having a single trade-off currency versus multiple competing currencies are unknown. Using simulations, we modeled the evolution of either a single physiological currency between reproduction and survival, or of multiple such currencies. For a wide array of model specifications varying functional forms and strengths of the trade-offs, we show that the presence of multiple currencies (e.g. nutrients, time) generally results in the evolution of higher lifetime reproductive success through partial circumvention of such trade-offs. Evolution of the underlying physiology is also more highly contingent with multiple currencies. These results challenge the paradigm of a single survival-reproduction trade-off as central to life history evolution, suggesting greater roles for physiological constraints and contingency, and implying potential selection for evolution of multiple trade-off currencies.

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.

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.