Healthy Aging in Times of Extreme Temperatures: Biomedical Approaches.

Climate extremes and rising energy prices present interconnected global health risks. Technical solutions can be supplemented with biomedical approaches to promote healthy longevity in hot and cold conditions. In summer, reducing basal metabolic rate through mild caloric restriction or CR mimetics, such as resveratrol, can potentially be used to lower body temperature. In winter, activating brown adipose tissue (BAT) for non-shivering thermogenesis and improved metabolic health can help adaptation to colder environments. Catechins found in green tea and in other food could be alternatives to drugs for these purposes. This review examines and discusses the biomedical evidence supporting the use of CR mimetics and BAT activators for health benefits amid increasingly extreme temperatures.

Uncoupling protein 2 deficiency of non-cancerous tissues inhibits the progression of pancreatic cancer in mice.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a disease of the elderly mostly because its development from preneoplastic lesions depends on the accumulation of gene mutations and epigenetic alterations over time. How aging of non-cancerous tissues of the host affects tumor progression, however, remains largely unknown. METHODS: We took advantage of a model of accelerated aging, uncoupling protein 2-deficient (Ucp2 knockout, Ucp2 KO) mice, to investigate the growth of orthotopically transplanted Ucp2 wild-type (WT) PDAC cells (cell lines Panc02 and 6606PDA) in vivo and to study strain-dependent differences of the PDAC microenvironment. RESULTS: Measurements of tumor weights and quantification of proliferating cells indicated a significant growth advantage of Panc02 and 6606PDA cells in WT mice compared to Ucp2 KO mice. In tumors in the knockout strain, higher levels of interferon-γ mRNA despite similar numbers of tumor-infiltrating T cells were observed. 6606PDA cells triggered a stronger stromal reaction in Ucp2 KO mice than in WT animals. Accordingly, pancreatic stellate cells from Ucp2 KO mice proliferated at a higher rate than cells of the WT strain when they were incubated with conditioned media from PDAC cells. CONCLUSIONS: Ucp2 modulates PDAC microenvironment in a way that favors tumor progression and implicates an altered stromal response as one of the underlying mechanisms.

Protein Biomarkers in Blood Reflect the Interrelationships Between Stroke Outcome, Inflammation, Coagulation, Adhesion, Senescence and Cancer.

The most important predictors for outcomes after ischemic stroke, that is, for health deterioration and death, are chronological age and stroke severity; gender, genetics and lifestyle/environmental factors also play a role. Of all these, only the latter can be influenced after the event. Recurrent stroke may be prevented by antiaggregant/anticoagulant therapy, angioplasty of high-grade stenoses, and treatment of cardiovascular risk factors. Blood cell composition and protein biomarkers such as C-reactive protein or interleukins in serum are frequently considered as biomarkers of outcome. Here we aim to provide an up-to-date protein biomarker signature that allows a maximum of mechanistic understanding, to predict health deterioration following stroke. We thus surveyed protein biomarkers that were reported to be predictive for outcome after ischemic stroke, specifically considering biomarkers that predict long-term outcome (≥ 3 months) and that are measured over the first days following the event. We classified the protein biomarkers as immune­inflammatory, coagulation-related, and adhesion-related biomarkers. Some of these biomarkers are closely related to cellular senescence and, in particular, to the inflammatory processes that can be triggered by senescent cells. Moreover, the processes that underlie inflammation, hypercoagulation and cellular senescence connect stroke to cancer, and biomarkers of cancer-associated thromboembolism, as well as of sarcopenia, overlap strongly with the biomarkers discussed here. Finally, we demonstrate that most of the outcome-predicting protein biomarkers form a close-meshed functional interaction network, suggesting that the outcome after stroke is partially determined by an interplay of molecular processes relating to inflammation, coagulation, cell adhesion and cellular senescence.

Biomarkers of geroprotection and cardiovascular health: An overview of omics studies and established clinical biomarkers in the context of diet.

The slowdown, inhibition, or reversal of age-related decline (as a composite of disease, dysfunction, and, ultimately, death) by diet or natural compounds can be defined as dietary geroprotection. While there is no single reliable biomarker to judge the effects of dietary geroprotection, biomarker signatures based on omics (epigenetics, gene expression, microbiome composition) are promising candidates. Recently, omic biomarkers started to supplement established clinical ones such as lipid profiles and inflammatory cytokines. In this review, we focus on human data. We first summarize the current take on genetic biomarkers based on epidemiological studies. However, most of the remaining biomarkers that we describe, whether omics-based or clinical, are related to intervention studies. Then, because of their promising potential in the context of dietary geroprotection, we focus on the effects of berry-based interventions, which up to now have been mostly described employing clinical markers. We provide an aggregation and tabulation of all the recent systematic reviews and meta-analyses that we could find related to this topic. Finally, we present evidence for the importance of the "nutribiography," that is, the influence that an individual's history of diet and natural compound consumption can have on the effects of dietary geroprotection.Supplemental data for this article is available online at https://doi.org/10.1080/10408398.2021.1975638.

Transfer learning of clinical outcomes from preclinical molecular data, principles and perspectives.

Accurate transfer learning of clinical outcomes from one cellular context to another, between cell types, developmental stages, omics modalities or species, is considered tremendously useful. When transferring a prediction task from a source domain to a target domain, what counts is the high quality of the predictions in the target domain, requiring states or processes common to both the source and the target that can be learned by the predictor reflected by shared denominators. These may form a compendium of knowledge that is learned in the source to enable predictions in the target, usually with few, if any, labeled target training samples to learn from. Transductive transfer learning refers to the learning of the predictor in the source domain, transferring its outcome label calculations to the target domain, considering the same task. Inductive transfer learning considers cases where the target predictor is performing a different yet related task as compared with the source predictor. Often, there is also a need to first map the variables in the input/feature spaces and/or the variables in the output/outcome spaces. We here discuss and juxtapose various recently published transfer learning approaches, specifically designed (or at least adaptable) to predict clinical (human in vivo) outcomes based on preclinical (mostly animal-based) molecular data, towards finding the right tool for a given task, and paving the way for a comprehensive and systematic comparison of the suitability and accuracy of transfer learning of clinical outcomes.

An explanation of how mutant and wild-type mitochondria might stably co-exist in inherited mitochondrial diseases.

Mitochondria are cellular organelles of crucial relevance for the survival of metazoan organisms. Damage to the mitochondrial DNA can give rise to a variety of mitochondrial diseases and is thought also to be involved in the aging process. The fate of mtDNA mutants is controlled by their synthesis as well as degradation and mathematical models can help to better understand this complex interplay. We present here a model that combines a replicative advantage for mtDNA mutants with selective degradation enabled by mitochondrial fission and fusion processes. The model not only shows that the cell has efficient means to deal with (many) types of mutants but, surprisingly, also predicts that under certain conditions a stable co-existence of mutant and wild-type mtDNAs is possible. We discuss how this new finding might explain how mitochondria can be at the heart of processes with such different phenotypes as mitochondrial diseases and aging.

Senolytics and the compression of late-life mortality.

Senescent cells play an important role in mammalian ageing and in the etiology of age-related diseases. Treatment of mice with senolytics - drugs that selectively remove senescent cells - causes an extension of median lifespan but has little effect on maximum lifespan. Postponement of some mortality to later ages, without a corresponding increase in maximum mortality, can be termed 'compression of mortality'. When we fit the standard Gompertz mortality model to the survival data following senolytic treatment, we find an increase in the slope parameter, commonly described as the 'actuarial ageing rate'. These observations raise important questions about the actions of senolytic treatments and their effects on health and survival, which are not yet sufficiently understood. To explore how the survival data from senolytics experiments might be explained, we combine a recent exploration of the evolutionary basis of cellular senescence with theoretical consideration of the molecular processes that might be involved. We perform numerical simulations of senescent cell accumulation and senolytic treatment in an ageing population. The simulations suggest that while senolytics diminish the burden of senescent cells, they may also impair the general repair capacity of the organism, leading to a faster accumulation post-treatment of new senescent cells. Our results suggest a framework to address the benefits and possible side effects of senolytic therapies, with the potential to aid in the design of optimal treatment regimens.

Towards biomarkers for outcomes after pancreatic ductal adenocarcinoma and ischaemic stroke, with focus on (co)-morbidity and ageing/cellular senescence (SASKit): protocol for a prospective cohort study.

INTRODUCTION: Ageing-related processes such as cellular senescence are believed to underlie the accumulation of diseases in time, causing (co)morbidity, including cancer, thromboembolism and stroke. Interfering with these processes may delay, stop or reverse morbidity. The aim of this study is to investigate the link between (co)morbidity and ageing by exploring biomarkers and molecular mechanisms of disease-triggered deterioration in patients with pancreatic ductal adenocarcinoma (PDAC) and (thromboembolic) ischaemic stroke (IS). METHODS AND ANALYSIS: We will recruit 50 patients with PDAC, 50 patients with (thromboembolic) IS and 50 controls at Rostock University Medical Center, Germany. We will gather routine blood data, clinical performance measurements and patient-reported outcomes at up to seven points in time, alongside in-depth transcriptomics and proteomics at two of the early time points. Aiming for clinically relevant biomarkers, the primary outcome is a composite of probable sarcopenia, clinical performance (described by ECOG Performance Status for patients with PDAC and the Modified Rankin Scale for patients with stroke) and quality of life. Further outcomes cover other aspects of morbidity such as cognitive decline and of comorbidity such as vascular or cancerous events. The data analysis is comprehensive in that it includes biostatistics and machine learning, both following standard role models and additional explorative approaches. Prognostic and predictive biomarkers for interventions addressing senescence may become available if the biomarkers that we find are specifically related to ageing/cellular senescence. Similarly, diagnostic biomarkers will be explored. Our findings will require validation in independent studies, and our dataset shall be useful to validate the findings of other studies. In some of the explorative analyses, we shall include insights from systems biology modelling as well as insights from preclinical animal models. We anticipate that our detailed study protocol and data analysis plan may also guide other biomarker exploration trials. ETHICS AND DISSEMINATION: The study was approved by the local ethics committee (Ethikkommission an der Medizinischen Fakultät der Universität Rostock, A2019-0174), registered at the German Clinical Trials Register (DRKS00021184), and results will be published following standard guidelines.

On the evolution of cellular senescence.

The idea that senescent cells are causally involved in aging has gained strong support from findings that the removal of such cells alleviates many age-related diseases and extends the life span of mice. While efforts proceed to make therapeutic use of such discoveries, it is important to ask what evolutionary forces might have been behind the emergence of cellular senescence, in order better to understand the biology that we might seek to alter. Cellular senescence is often regarded as an anti-cancer mechanism, since it limits the division potential of cells. However, many studies have shown that senescent cells often also have carcinogenic properties. This is difficult to reconcile with the simple idea of an anti-cancer mechanism. Furthermore, other studies have shown that cellular senescence is involved in wound healing and tissue repair. Here, we bring these findings and ideas together and discuss the possibility that these functions might be the main reason for the evolution of cellular senescence. Furthermore, we discuss the idea that senescent cells might accumulate with age because the immune system had to strike a balance between false negatives (overlooking some senescent cells) and false positives (destroying healthy body cells).

Single-cell analyses of aging, inflammation and senescence.

Single-cell gene expression (transcriptomics) data are becoming robust and abundant, and are increasingly used to track organisms along their life-course. This allows investigation into how aging affects cellular transcriptomes, and how changes in transcriptomes may underlie aging, including chronic inflammation (inflammaging), immunosenescence and cellular senescence. We compiled and tabulated aging-related single-cell datasets published to date, collected and discussed relevant findings, and inspected some of these datasets ourselves. We specifically note insights that cannot (or not easily) be based on bulk data. For example, in some datasets, the fraction of cells expressing p16 (CDKN2A), one of the most prominent markers of cellular senescence, was reported to increase, in addition to its upregulated mean expression over all cells. Moreover, we found evidence for inflammatory processes in most datasets, some of these driven by specific cells of the immune system. Further, single-cell data are specifically useful to investigate whether transcriptional heterogeneity (also called noise or variability) increases with age, and many (but not all) studies in our review report an increase in such heterogeneity. Finally, we demonstrate some stability of marker gene expression patterns across closely similar studies and suggest that single-cell experiments may hold the key to provide detailed insights whenever interventions (countering aging, inflammation, senescence, disease, etc.) are affecting cells depending on cell type.

The preventive strategy for pandemics in the elderly is to collect in advance samples & data to counteract chronic inflammation (inflammaging).

Fighting the current COVID-19 pandemic, we must not forget to prepare for the next. Since elderly and frail people are at high risk, we wish to predict their vulnerability, and intervene if possible. For example, it would take little effort to take additional swabs or dried blood spots. Such minimally-invasive sampling, exemplified here during screening for potential COVID-19 infection, can yield the data to discover biomarkers to better handle this and the next respiratory disease pandemic. Longitudinal outcome data can then be combined with other epidemics and old-age health data, to discover the best biomarkers to predict (i) coping with infection & inflammation and thus hospitalization or intensive care, (ii) long-term health challenges, e.g. deterioration of lung function after intensive care, and (iii) treatment & vaccination response. Further, there are universal triggers of old-age morbidity & mortality, and the elimination of senescent cells improved health in pilot studies in idiopathic lung fibrosis & osteoarthritis patients alike. Biomarker studies are needed to test the hypothesis that resilience of the elderly during a pandemic can be improved by countering chronic inflammation and/or removing senescent cells. Our review suggests that more samples should be taken and saved systematically, following minimum standards, and data be made available, to maximize healthspan & minimize frailty, leading to savings in health care, gains in quality of life, and preparing us better for the next pandemic, all at the same time.

Resolving the Enigma of the Clonal Expansion of mtDNA Deletions.

Mitochondria are cell organelles that are special since they contain their own genetic material in the form of mitochondrial DNA (mtDNA). Damage and mutations of mtDNA are not only involved in several inherited human diseases but are also widely thought to play an important role during aging. In both cases, point mutations or large deletions accumulate inside cells, leading to functional impairment once a certain threshold has been surpassed. In most cases, it is a single type of mutant that clonally expands and out-competes the wild type mtDNA, with different mutant molecules being amplified in different cells. The challenge is to explain where the selection advantage for the accumulation comes from, why such a large range of different deletions seem to possess this advantage, and how this process can scale to species with different lifespans such as those of rats and man. From this perspective, we provide an overview of current ideas, present an update of our own proposal, and discuss the wider relevance of the phenomenon for aging.

Can aging be programmed? A critical literature review.

The evolution of the aging process has long been a biological riddle, because it is difficult to explain the evolution of a trait that has apparently no benefit to the individual. Over 60 years ago, Medawar realized that the force of natural selection declines with chronological age because of unavoidable environmental risks. This forms the basis of the mainstream view that aging arises as a consequence of a declining selection pressure to maintain the physiological functioning of living beings forever. Over recent years, however, a number of articles have appeared that nevertheless propose the existence of specific aging genes; that is, that the aging process is genetically programmed. If this view were correct, it would have serious implications for experiments to understand and postpone aging. Therefore, we studied in detail various specific proposals why aging should be programmed. We find that not a single one withstands close scrutiny of its assumptions or simulation results. Nonprogrammed aging theories based on the insight of Medawar (as further developed by Hamilton and Charlesworth) are still the best explanation for the evolution of the aging process. We hope that this analysis helps to clarify the problems associated with the idea of programmed aging.

Evolutionary significance of ageing in the wild.

Human lifespan has risen dramatically over the last 150 years, leading to a significant increase in the fraction of aged people in the population. Until recently it was believed that this contrasted strongly with the situation in wild populations of animals, where the likelihood of encountering demonstrably senescent individuals was believed to be negligible. Over the recent years, however, a series of field studies has appeared that shows ageing can also be observed for many species in the wild. We discuss here the relevance of this finding for the different evolutionary theories of ageing, since it has been claimed that ageing in the wild is incompatible with the so-called non-adaptive (non-programmed) theories, i.e. those in which ageing is presumed not to offer a direct selection benefit. We show that a certain proportion of aged individuals in the population is fully compatible with the antagonistic pleiotropy and the disposable soma theories, while it is difficult to reconcile with the mutation accumulation theory. We also quantify the costs of ageing using life history data from recent field studies and a range of possible metrics. We discuss the merits and problems of the different metrics and also introduce a new metric, yearly death toll, that aims directly at quantifying the deaths caused by the ageing process.

Telomere Length in Peripheral Blood Mononuclear Cells of Patients on Chronic Hemodialysis Is Related With Telomerase Activity and Treatment Duration.

Telomere shortening to a critical limit is associated with replicative senescence. This process is prevented by the enzyme telomerase. Oxidative stress and chronic inflammation are factors accelerating telomere loss. Chronic hemodialysis, typically accompanied by oxidative stress and inflammation, may be also associated with replicative senescence. To test this hypothesis, we determined telomere length and telomerase activity in peripheral blood mononuclear cells (PBMCs) in a cross-sectional study. Hemodialysis patients at the University Hospital Larissa and healthy controls were studied. Telomere length was determined by the TeloTAGGG Telomere Length Assay and telomerase activity by Telomerase PCR-ELISA (Roche Diagnostics GmbH, Mannheim, Germany). We enrolled 43 hemodialysis patients (17 females; age 65.0 ± 12.7 years) and 23 controls (six females; age 62.1 ± 15.7 years). Between the two groups, there was no difference in telomere length (6.95 ± 3.25 vs. 7.31 ± 1.96 kb; P = 0.244) or in telomerase activity (1.82 ± 2.91 vs. 2.71 ± 3.0; P = 0.085). Telomere length correlated inversely with vintage of hemodialysis (r = -0.332, P = 0.030). In hemodialysis patients, positive telomerase activity correlated with telomere length (r = 0.443, P = 0.030). Only age, and neither telomere length nor telomerase activity, was an independent survival predictor (hazard ratio 1.116, 95% confidence interval 1.009-1.234, P = 0.033). In this study, telomere length and telomerase activity in PBMCs are not altered in hemodialysis patients compared with healthy controls. Long duration of hemodialysis treatment is associated with telomere shortening and positive telomerase activity with an increased telomere length in PBMCs of hemodialysis patients. The underlying mechanism and clinical implications of our findings require further investigation.

Mathematical models of mitochondrial aging and dynamics.

Research on the role of mitochondria in aging and disease is rapidly growing. Furthermore, in recent years, it also became clear that mitochondria are dynamic structures undergoing constant and rapid cycles of fusion and fission. The involvement of mitochondria in multiple complex processes makes them a prime target for mathematical and computational modeling. This review consists of two parts. In the first (Section 2), we provide a detailed introduction to the underlying concepts of mathematical modeling to help the reader who is not so familiar with these techniques to judge the requirements and results that can be obtained through modeling. In the second part (Section 3), we review existing mathematical and computational models that investigate mitochondrial dynamics and the role of mitochondria for the aging process.

Quality matters: how does mitochondrial network dynamics and quality control impact on mtDNA integrity?

Mammalian mtDNA encodes for 13 core proteins of oxidative phosphorylation. Mitochondrial DNA mutations and deletions cause severe myopathies and neuromuscular diseases. Thus, the integrity of mtDNA is pivotal for cell survival and health of the organism. We here discuss the possible impact of mitochondrial fusion and fission on mtDNA maintenance as well as positive and negative selection processes. Our focus is centred on the important question of how the quality of mtDNA nucleoids can be assured when selection and mitochondrial quality control works on functional and physiological phenotypes constituted by oxidative phosphorylation proteins. The organelle control theory suggests a link between phenotype and nucleoid genotype. This is discussed in the light of new results presented here showing that mitochondrial transcription factor A/nucleoids are restricted in their intramitochondrial mobility and probably have a limited sphere of influence. Together with recent published work on mitochondrial and mtDNA heteroplasmy dynamics, these data suggest first, that single mitochondria might well be internally heterogeneous and second, that nucleoid genotypes might be linked to local phenotypes (although the link might often be leaky). We discuss how random or site-specific mitochondrial fission can isolate dysfunctional parts and enable their elimination by mitophagy, stressing the importance of fission in the process of mtDNA quality control. The role of fusion is more multifaceted and less understood in this context, but the mixing and equilibration of matrix content might be one of its important functions.

Transcription could be the key to the selection advantage of mitochondrial deletion mutants in aging.

The mitochondrial theory of aging is widely popular but confronted by several apparent inconsistencies. On the one hand, mitochondrial energy production is of central importance to the health and proper functioning of cells, and single-cell studies have shown that mtDNA deletion mutants accumulate in a clonal fashion in various mammalian species, displacing the wild-type mtDNAs. On the other hand, no explanation exists yet for the clonal expansion of mtDNA mutants that is compatible with experimental observations. We present here a new idea based on the distinctive connection between transcription and replication of metazoan mtDNA. Bioinformatic analysis of mtDNA deletion spectra strongly supports the predictions of this hypothesis and identifies specific candidates for proteins involved in transcriptional control of mtDNA replication. Computer simulations show the mechanism to be compatible with the available data from short- and long-lived mammalian species.

Mitochondrial mutations and ageing: can mitochondrial deletion mutants accumulate via a size based replication advantage?

The mitochondrial theory of ageing is one of the main contenders to explain the biochemical basis of the ageing process. An important line of support comes from the observation that mtDNA deletions accumulate over the life course in post-mitotic cells of many species. A single mutant expands clonally and finally replaces the wild-type population of a whole cell. One proposal to explain the driving force behind this accumulation states that the reduced size leads to a shorter replication time, which provides a selection advantage. However, this idea has been questioned on the grounds that the mitochondrial half-life is much longer than the replication time, so that the latter cannot be a rate limiting step. To clarify this question, we modelled this process mathematically and performed extensive deterministic and stochastic computer simulations to study the effects of replication time, mitochondrial half-life and deletion size. Our study shows that the shorter size does in principle provide a selection advantage, which can lead to an accumulation of the deletion mutant. However, this selection advantage diminishes the shorter is the replication time of wt mtDNA in relation to its half-life. Using generally accepted literature values, the resulting time frame for the accumulation of mutant mtDNAs is only compatible with the ageing process in very long lived species like humans, but could not reasonably explain ageing in short lived species like mice and rats.

Mitochondrial mutations and aging: random drift is insufficient to explain the accumulation of mitochondrial deletion mutants in short-lived animals.

Mitochondrial DNA deletions accumulate over the life course in post-mitotic cells of many species and may contribute to aging. Often a single mutant expands clonally and finally replaces the wild-type population of a whole cell. One proposal to explain the driving force behind this accumulation states that random drift alone, without any selection advantage, is sufficient to explain the clonal accumulation of a single mutant. Existing mathematical models show that such a process might indeed work for humans. However, to be a general explanation for the clonal accumulation of mtDNA mutants, it is important to know whether random drift could also explain the accumulation process in short-lived species like rodents. To clarify this issue, we modelled this process mathematically and performed extensive computer simulations to study how different mutation rates affect accumulation time and the resulting degree of heteroplasmy. We show that random drift works for lifespans of around 100 years, but for short-lived animals, the resulting degree of heteroplasmy is incompatible with experimental observations.