Deep phenotyping and lifetime trajectories reveal limited effects of longevity regulators on the aging process in C57BL/6J mice

Intermittent fasting boosts sexual behavior by limiting the central availability of tryptophan and serotonin

Aging affects reproductive capabilities in males through physiological and behavioral alterations, including endocrine changes and decreased libido. In this study, we investigated the influence of intermittent fasting (IF) on these aging-related declines, using male C57BL/6J mice. Our findings revealed that IF significantly preserved reproductive success in aged mice, not by improving traditional reproductive metrics such as sperm quality or endocrine functions but by enhancing mating behavior. This behavioral improvement was attributed to IF's ability to counter age-dependent increases in serotonergic inhibition, primarily through the decreased supply of the serotonin precursor tryptophan from the periphery to the brain. Our research underscores the potential of dietary interventions like IF in mitigating age-associated declines in male reproductive health and suggests a novel approach to managing conditions related to reduced sexual desire, highlighting the complex interplay between diet, metabolism, and reproductive behavior.

Dynamic changes in gene expression through aging in Drosophila melanogaster heads

Work in many systems has shown large-scale changes in gene expression during aging. However, many studies employ just 2 arbitrarily chosen timepoints to measure expression and can only observe an increase or a decrease in expression between "young" and "old" animals, failing to capture any dynamic, nonlinear changes that occur throughout the aging process. We used RNA sequencing to measure expression in male head tissue at 15 timepoints through the lifespan of an inbred Drosophila melanogaster strain. We detected >6,000 significant, age-related genes, nearly all of which have been seen in previous Drosophila aging expression studies and that include several known to harbor lifespan-altering mutations. We grouped our gene set into 28 clusters via their temporal expression change, observing a diversity of trajectories; some clusters show a linear change over time, while others show more complex, nonlinear patterns. Notably, reanalysis of our dataset comparing the earliest and latest timepoints-mimicking a 2-timepoint design-revealed fewer differentially expressed genes (around 4,500). Additionally, those genes exhibiting complex expression trajectories in our multitimepoint analysis were most impacted in this reanalysis; their identification, and the inferred change in gene expression with age, was often dependent on the timepoints chosen. Informed by our trajectory-based clusters, we executed a series of gene enrichment analyses, identifying enriched functions/pathways in all clusters, including the commonly seen increase in stress- and immune-related gene expression with age. Finally, we developed a pair of accessible Shiny apps to enable exploration of our differential expression and gene enrichment results.

Loss of Ten1 in mice induces telomere shortening and models human dyskeratosis congenita

Telomere length regulation is essential for genome stability as short telomeres can trigger cellular senescence and apoptosis constituting an integral aspect of biological aging. Telomere biology disorders (TBDs) such as dyskeratosis congenita (DC) are rare, inherited diseases with known mutations in at least 16 different genes encoding components of the telomere maintenance complexes. The precise role of TEN1, part of the CST complex (CTC1, STN1, and TEN1), and the consequences of its loss of function in vivo are not yet known. We investigated the first viable murine model of Ten1 deficiency created by CRISPR-Cas9-mediated exon 3 deletion. Ten1 homozygous knockout mice present with telomere attrition, short life span, skin hyperpigmentation, aplastic anemia, and cerebellar hypoplasia. Molecular analyses revealed a reduction of proliferating cells, increased apoptosis, and stem cell depletion with activation of the p53/p21 signaling pathway. Our data demonstrate that Ten1 deficiency causes telomere shortening and associates with accelerated aging.

Compression of morbidity by interventions that steepen the survival curve

Longevity research aims to extend the healthspan while minimizing the duration of disability and morbidity, known as the sickspan. Most longevity interventions in model organisms extend healthspan, but it is not known whether they compress sickspan relative to the lifespan. Here, we present a theory that predicts which interventions compress relative sickspan, based on the shape of the survival curve. Interventions such as caloric restriction that extend mean lifespan while preserving the shape of the survival curve, are predicted to extend the sickspan proportionally, without compressing it. Conversely, a subset of interventions that extend lifespan and steepen the shape of the survival curve are predicted to compress the relative sickspan. We explain this based on the saturating-removal mathematical model of aging, and present evidence from longitudinal health data in mice, Caenorhabditis elegans and Drosophila melanogaster. We apply this theory to identify potential interventions for compressing the sickspan in mice, and to combinations of longevity interventions. This approach offers potential strategies for compressing morbidity and extending healthspan.

Trends of genetic contributions on epigenetic clocks and related methylation sites with aging: A population-based adult twin study

Several crucial acceleration periods exist during aging process. Epigenetic clocks, serving as indicators of aging, are influenced by genetic factors. Investigating how the genetic contributions on these clocks change with age may provide novel insights into the aging process. In this study, based on 1084 adult twins from the Chinese National Twin Registry (CNTR), we established structural equation models (SEMs) to evaluate the trends in genetic influence with aging for epigenetic clocks, which include PC-Horvath, PC-Hannum, PC-PhenoAge, PC-GrimAge, and DunedinPACE. A decline in overall heritability was observed for all five clocks from ages 31 to 70, with a relatively stable trend at first. Subsequently, apart from PC-GrimAge, the other four clocks displayed a more evident drop in heritability: DunedinPACE and PC-PhenoAge experienced a clear decline between 55 and 65 years, while PC-Horvath and PC-Hannum showed a similar decrease between 60 and 70 years. In contrast, the heritability of PC-GrimAge remained stable throughout. An analysis of methylation sites (CpGs) from these clocks identified 41, 26, 4, and 36 CpG sites potentially underlying heritability changes in DunedinPACE, PC-Horvath, PC-Hannum, and PC-PhenoAge, respectively. Data from the CNTR were collected through two surveys in 2013 and 2018. Based on 308 twins with longitudinal data, declines in genetic components were observed at follow-up compared to baseline, with significant decreases in the four PC-clocks. DunedinPACE peaked in 5-year longitudinal genetic contribution changes at age 55-60, while PC-clocks consistently peaked at age 50-55. These findings may offer novel insights into the role of genetic variations in aging.

Dynamic Changes in Gene Expression Through Aging in Drosophila melanogaster Heads

Work in many systems has shown large-scale changes in gene expression during aging. However, many studies employ just two, arbitrarily-chosen timepoints at which to measure expression, and can only observe an increase or a decrease in expression between "young" and "old" animals, failing to capture any dynamic, non-linear changes that occur throughout the aging process. We used RNA sequencing to measure expression in male head tissue at 15 timepoints through the lifespan of an inbred Drosophila melanogaster strain. We detected >6,000 significant, age-related genes, nearly all of which have been seen in previous fly aging expression studies, and which include several known to harbor lifespan-altering mutations. We grouped our gene set into 28 clusters via their temporal expression change, observing a diversity of trajectories; some clusters show a linear change over time, while others show more complex, non-linear patterns. Notably, re-analysis of our dataset comparing the earliest and latest timepoints - mimicking a two-timepoint design - revealed fewer differentially-expressed genes (around 4,500). Additionally, those genes exhibiting complex expression trajectories in our multi-timepoint analysis were most impacted in this re-analysis; Their identification, and the inferred change in gene expression with age, was often dependent on the timepoints chosen. Informed by our trajectory-based clusters, we executed a series of gene enrichment analyses, identifying enriched functions/pathways in all clusters, including the commonly seen increase in stress- and immune-related gene expression with age. Finally, we developed a pair of accessible shiny apps to enable exploration of our differential expression and gene enrichment results.

Longitudinal fragility phenotyping contributes to the prediction of lifespan and age-associated morbidity in C57BL/6 and Diversity Outbred mice

Aging studies in mammalian models often depend on natural lifespan data as a primary outcome. Tools for lifespan prediction could accelerate these studies and reduce the need for veterinary intervention. Here, we leveraged large-scale longitudinal frailty and lifespan data on two genetically distinct mouse cohorts to evaluate noninvasive strategies to predict life expectancy in mice. We applied a modified frailty assessment, the Fragility Index, derived from existing frailty indices with additional deficits selected by veterinarians. We developed an ensemble machine learning classifier to predict imminent mortality (95% proportion of life lived [95PLL]). Our algorithm represented improvement over previous predictive criteria but fell short of the level of reliability that would be needed to make advanced prediction of lifespan and thus accelerate lifespan studies. Highly sensitive and specific frailty-based predictive endpoint criteria for aged mice remain elusive. While frailty-based prediction falls short as a surrogate for lifespan, it did demonstrate significant predictive power and as such must contain information that could be used to inform the conclusion of aging experiments. We propose a frailty-based measure of healthspan as an alternative target for aging research and demonstrate that lifespan and healthspan criteria reveal distinct aspects of aging in mice.

Animal Models Relevant for Geroscience: Current Trends and Future Perspectives in Biomarkers, and Measures of Biological Aging

For centuries, aging was considered inevitable and immutable. Geroscience provides the conceptual framework to shift this focus toward a new view that regards aging as an active biological process, and the biological age of an individual as a modifiable entity. Significant steps forward have been made toward the identification of biomarkers for and measures of biological age, yet knowledge gaps in geroscience are still numerous. Animal models of aging are the focus of this perspective, which discusses how experimental design can be optimized to inform and refine the development of translationally relevant measures and biomarkers of biological age. We provide recommendations to the field, including: the design of longitudinal studies in which subjects are deeply phenotyped via repeated multilevel behavioral/social/molecular assays; the need to consider sociobehavioral variables relevant for the species studied; and finally, the importance of assessing age of onset, severity of pathologies, and age-at-death. We highlight approaches to integrate biomarkers and measures of functional impairment using machine learning approaches designed to estimate biological age as well as to predict future health declines and mortality. We expect that advances in animal models of aging will be crucial for the future of translational geroscience but also for the next chapter of medicine.

Design and validation of novel flow cytometry panels to analyze a comprehensive range of peripheral immune cells in mice

The use of flow cytometry in mice is constrained by several factors, including the limited availability of mouse-specific antibodies and the need to work with small volumes of peripheral blood. This is particularly challenging for longitudinal studies, as serial blood samples should not exceed 10% of the total blood volume in mice. To address this, we have developed two novel flow cytometry panels designed to extensively analyze immune cell populations in mice during longitudinal studies, using only 50 µL of peripheral blood per panel. Additionally, a third panel has been designed to conduct a more detailed analysis of cytotoxic and inhibitory markers at the end point. These panels have been validated on a lipopolysaccharide (LPS)-induced lung inflammation model. Two experiments were conducted to 1) validate the panels' sensitivity to immune challenges (n=12) and 2) to assess intrinsic variability of measurements (n=5). In both experiments, we collected 50 µL of peripheral blood for each cytometry panel from the maxillary venous sinus. All antibodies were titrated to identify the optimal concentration that maximized the signal from the positive population while minimizing the signal from the negative population. Samples were processed within 1 hour of collection using a MACSQuant Analyzer 16 cytometer. Our results demonstrate that these immunological panels are sensitive enough to detect changes in peripheral blood after LPS induction. Moreover, our findings help determine the sample size needed based on the immune population variability. In conclusion, the panels we have designed enable a comprehensive analysis of the murine immune system with a low blood volume requirement, enabling the measure of both absolute values and relative percentages effectively. This approach provides a robust platform for longitudinal studies in mice and can be used to uncover significant insights into immune responses.

Late-in-life Exercise Ameliorates the Aging Trajectory Metabolism Programmed by Maternal Obesity in Rats: It is Never Too Late

BACKGROUND

Maternal obesity (MO) has been shown to adversely affect metabolic, oxidative, reproductive, and cognitive function in offspring. However, it is unclear whether lifestyle modification can ameliorate the metabolic and organ dysfunction programmed by MO and prevent the effects of metabolic syndrome in adulthood. This study aimed to evaluate whether moderate voluntary exercise in the offspring of rats born to obese mothers can ameliorate the adverse effects of MO programming on metabolism and liver function in mid-adulthood.

METHODS

Offspring of control (CF1) and MOF1 mothers were fed with a control diet from weaning. Adult males and females participated in 15 min exercise sessions five days/week. Metabolic parameters were analyzed before and after the exercise intervention. Liver oxidative stress biomarkers and antioxidant enzymes were analyzed before and after the intervention.

RESULTS

Males showed that CF1ex ran more than MOF1ex and increased the distance covered. In contrast, females in both groups ran similar distances and remained constant but ran more distance than males. At PND 300 and 450, male and female MOF1 had higher leptin, triglycerides, insulin, and HOMA-IR levels than CF1. However, male MOF1ex had lower triglycerides, insulin, and HOMA-IR levels than MOF1. Improvements in liver fat and antioxidant enzymes were observed in CF1ex and MOF1ex males and females compared to their respective CF1 and MOF1 groups.

CONCLUSION

These findings suggest that moderate voluntary exercise, even when started in mid-adulthood, can improve metabolic outcomes and delay accelerated metabolic aging in MO-programmed rats in a sex-dependent manner.

A patient-enriched MEIS1 coding variant causes a restless legs syndrome-like phenotype in mice

Restless legs syndrome (RLS) is a neurological disorder characterized by uncomfortable or unpleasant sensations in the legs during rest periods. To relieve these sensations, patients move their legs, causing sleep disruption. While the pathogenesis of RLS has yet to be resolved, there is a strong genetic association with the MEIS1 gene. A missense variant in MEIS1 is enriched sevenfold in people with RLS compared to non-affected individuals. We generated a mouse line carrying this mutation (p.Arg272His/c.815G>A), referred to herein as Meis1R272H/R272H (Meis1 point mutation), to determine whether it would phenotypically resemble RLS. As women are more prone to RLS, driven partly by an increased risk of developing RLS during pregnancy, we focused on female homozygous mice. We evaluated RLS-related outcomes, particularly sensorimotor behavior and sleep, in young and aged mice. Compared to noncarrier littermates, homozygous mice displayed very few differences. Significant hyperactivity occurred before the lights-on (rest) period in aged female mice, reflecting the age-dependent incidence of RLS. Sensory experiments involving tactile feedback (rotarod, wheel running, and hotplate) were only marginally different. Overall, RLS-like phenomena were not recapitulated except for the increased wake activity prior to rest. This is likely due to the focus on young mice. Nevertheless, the Meis1R272H mouse line is a potentially useful RLS model, carrying a clinically relevant variant and showing an age-dependent phenotype.

Targeting mitochondrial dysfunction using methylene blue or mitoquinone to improve skeletal aging

Methylene blue (MB) is a well-established antioxidant that has been shown to improve mitochondrial function in both in vitro and in vivo settings. Mitoquinone (MitoQ) is a selective antioxidant that specifically targets mitochondria and effectively reduces the accumulation of reactive oxygen species. To investigate the effect of long-term administration of MB on skeletal morphology, we administered MB to aged (18 months old) female C57BL/J6 mice, as well as to adult male and female mice with a genetically diverse background (UM-HET3). Additionally, we used MitoQ as an alternative approach to target mitochondrial oxidative stress during aging in adult female and male UM-HET3 mice. Although we observed some beneficial effects of MB and MitoQ in vitro, the administration of these compounds in vivo did not alter the progression of age-induced bone loss. Specifically, treating 18-month-old female mice with MB for 6 or 12 months did not have an effect on age-related bone loss. Similarly, long-term treatment with MB from 7 to 22 months or with MitoQ from 4 to 22 months of age did not affect the morphology of cortical bone at the mid-diaphysis of the femur, trabecular bone at the distal-metaphysis of the femur, or trabecular bone at the lumbar vertebra-5 in UM-HET3 mice. Based on our findings, it appears that long-term treatment with MB or MitoQ alone, as a means to reduce skeletal oxidative stress, is insufficient to inhibit age-associated bone loss. This supports the notion that interventions solely with antioxidants may not provide adequate protection against skeletal aging.

On standardization of controls in lifespan studies

The search for interventions to slow down and even reverse aging is a burgeoning field. The literature cites hundreds of supposedly beneficial pharmacological and genetic interventions in model organisms: mice, rats, flies and worms, where research into physiology is routinely accompanied by lifespan data. However, when experimental animals from one article live as long as controls from another article, comparing the results of interventions across studies can yield misleading outcomes. Theoretically, all lifespan data are ripe for re-analysis: we could contrast the molecular targets and pathways across studies and help focus the further search for interventions. Alas, the results of most longevity studies are difficult to compare. This is in part because there are no clear, universally accepted standards for conducting such experiments or even for reporting such data. The situation is worsened by the fact that the authors often do not describe experimental conditions completely. As a result, works on longevity make up a set of precedents, each of which might be interesting in its own right, yet incoherent and incomparable at least for the reason that in a general context, it may indicate, for example, not prolonging the life of an average organism, but compensating for any genetic abnormalities of a particular sample or inappropriate living conditions. Here we point out specific issues and propose solutions for quality control by checking both inter- and intra-study consistency of lifespan data.

Longitudinal Fragility Phenotyping Predicts Lifespan and Age-Associated Morbidity in C57BL/6 and Diversity Outbred Mice

Aging studies in mammalian models often depend on natural lifespan data as a primary outcome. Tools for lifespan prediction could accelerate these studies and reduce the need for veterinary intervention. Here, we leveraged large-scale longitudinal frailty and lifespan data on two genetically distinct mouse cohorts to evaluate noninvasive strategies to predict life expectancy in mice. We applied a modified frailty assessment, the Fragility Index, derived from existing frailty indices with additional deficits selected by veterinarians. We developed an ensemble machine learning classifier to predict imminent mortality (95% proportion of life lived [95PLL]). Our algorithm represented improvement over previous predictive criteria but fell short of the level of reliability that would be needed to make advanced prediction of lifespan and thus accelerate lifespan studies. Highly sensitive and specific frailty-based predictive endpoint criteria for aged mice remain elusive. While frailty-based prediction falls short as a surrogate for lifespan, it did demonstrate significant predictive power and as such must contain information that could be used to inform the conclusion of aging experiments. We propose a frailty-based measure of healthspan as an alternative target for aging research and demonstrate that lifespan and healthspan criteria reveal distinct aspects of aging in mice.

Distinguishing between driver and passenger mechanisms of aging

Understanding why we age is a long-standing question, and many mechanistic theories of aging have been proposed. Owing to limitations in studying the aging process, including a lack of adequate quantitative measurements, its mechanistic basis remains a subject of debate. Here, I explore theories of aging from the perspective of causal relationships. Many aging-related changes have been observed and touted as drivers of aging, including molecular changes in the genome, telomeres, mitochondria, epigenome and proteins and cellular changes affecting stem cells, the immune system and senescent cell buildup. Determining which changes are drivers and not passengers of aging remains a challenge, however, and I discuss how animal models and human genetic studies have been used empirically to infer causality. Overall, our understanding of the drivers of human aging is still inadequate; yet with a global aging population, elucidating the causes of aging has the potential to revolutionize biomedical research.

Diet-Stimulated Marrow Adiposity Fails to Worsen Early, Age-Related Bone Loss

INTRODUCTION

Longitudinal effect of diet-induced obesity on bone is uncertain. Prior work showed both no effect and a decrement in bone density or quality when obesity begins prior to skeletal maturity. We aimed to quantify long-term effects of obesity on bone and bone marrow adipose tissue (BMAT) in adulthood.

METHODS

Skeletally mature, female C57BL/6 mice (n = 70) aged 12 weeks were randomly allocated to low-fat diet (LFD; 10% kcal fat; n = 30) or high-fat diet (HFD; 60% kcal fat; n = 30), with analyses at 12, 15, 18, and 24 weeks (n = 10/group). Tibial microarchitecture was analyzed by µCT, and volumetric BMAT was quantified via 9.4T MRI/advanced image analysis. Histomorphometry of adipocytes and osteoclasts, and qPCR were performed.

RESULTS

Body weight and visceral white adipose tissue accumulated in response to HFD started in adulthood. Trabecular bone parameters declined with advancing experimental age. BV/TV declined 22% in LFD (p = 0.0001) and 17% in HFD (p = 0.0022) by 24 weeks. HFD failed to appreciably alter BV/TV and had negligible impact on other microarchitecture parameters. Both dietary intervention and age accounted for variance in BMAT, with regional differences: distal femoral BMAT was more responsive to diet, while proximal femoral BMAT was more attenuated by age. BMAT increased 60% in the distal metaphysis in HFD at 18 and 24 weeks (p = 0.0011). BMAT in the proximal femoral diaphysis, unchanged by diet, decreased 45% due to age (p = 0.0002). Marrow adipocyte size via histomorphometry supported MRI quantification. Osteoclast number did not differ between groups. Tibial qPCR showed attenuation of some adipose, metabolism, and bone genes. A regulator of fatty acid β-oxidation, cytochrome C (CYCS), was 500% more abundant in HFD bone (p < 0.0001; diet effect). CYCS also increased due to age, but to a lesser extent. HFD mildly increased OCN, TRAP, and SOST.

CONCLUSIONS

Long-term high fat feeding after skeletal maturity, despite upregulation of visceral adiposity, body weight, and BMAT, failed to attenuate bone microarchitecture. In adulthood, we found aging to be a more potent regulator of microarchitecture than diet-induced obesity.

Responses to Many Anti-Aging Interventions Are Sexually Dimorphic

There is increasing appreciation that sex differences are not limited to reproductive organs or traits related to reproduction and that sex is an important biological variable in most characteristics of a living organism. The biological process of aging and aging-related traits are no exception and exhibit numerous, often major, sex differences. This article explores one aspect of these differences, namely sex differences in the responses to anti-aging interventions. Aging can be slowed down and/or postponed by a variety of environmental ("lifestyle"), genetic or pharmacological interventions. Although many, particularly older studies utilized only one sex of experimental animals, there is considerable evidence that responses to these interventions can be very different in females and males. Calorie restriction (CR), that is reducing food intake without malnutrition can extend longevity in both sexes, but specific metabolic alterations and health benefits induced by CR are not the same in women and men. In laboratory mice, several of the genetic alterations that reduce insulin-like growth factor I (IGF-1) signaling extend longevity more effectively in females or in females only. Beneficial effects of rapamycin, an inhibitor of mTOR signaling, on mouse longevity are greater in females. In contrast, several anti-aging compounds, including a weak estrogen, 17 alpha estradiol, extend longevity of male, but not female, mice. Apparently, fundamental mechanisms of aging are not identical in females and males and it is essential to use both sexes in studies aimed at identifying novel anti-aging interventions. Recommendations for lifestyle modifications, drugs, and dietary supplements to maintain good health and functionality into advanced age and to live longer will likely need to be tailored to the sex of the user.

How is Big Data reshaping preclinical aging research?

The exponential scientific and technological progress during the past 30 years has favored the comprehensive characterization of aging processes with their multivariate nature, leading to the advent of Big Data in preclinical aging research. Spanning from molecular omics to organism-level deep phenotyping, Big Data demands large computational resources for storage and analysis, as well as new analytical tools and conceptual frameworks to gain novel insights leading to discovery. Systems biology has emerged as a paradigm that utilizes Big Data to gain insightful information enabling a better understanding of living organisms, visualized as multilayered networks of interacting molecules, cells, tissues and organs at different spatiotemporal scales. In this framework, where aging, health and disease represent emergent states from an evolving dynamic complex system, context given by, for example, strain, sex and feeding times, becomes paramount for defining the biological trajectory of an organism. Using bioinformatics and artificial intelligence, the systems biology approach is leading to remarkable advances in our understanding of the underlying mechanism of aging biology and assisting in creative experimental study designs in animal models. Future in-depth knowledge acquisition will depend on the ability to fully integrate information from different spatiotemporal scales in organisms, which will probably require the adoption of theories and methods from the field of complex systems. Here we review state-of-the-art approaches in preclinical research, with a focus on rodent models, that are leading to conceptual and/or technical advances in leveraging Big Data to understand basic aging biology and its full translational potential.

The Cutting Edge of Epigenetic Clocks: In Search of Mechanisms Linking Aging and Mental Health

Individuals with psychiatric disorders are at increased risk of age-related diseases and early mortality. Recent studies demonstrate that this link between mental health and aging is reflected in epigenetic clocks, aging biomarkers based on DNA methylation. The reported relationships between epigenetic clocks and mental health are mostly correlational, and the mechanisms are poorly understood. Here, we review recent progress concerning the molecular and cellular processes underlying epigenetic clocks as well as novel technologies enabling further studies of the causes and consequences of epigenetic aging. We then review the current literature on how epigenetic clocks relate to specific aspects of mental health, such as stress, medications, substance use, health behaviors, and symptom clusters. We propose an integrated framework where mental health and epigenetic aging are each broken down into multiple distinct processes, which are then linked to each other, using stress and schizophrenia as examples. This framework incorporates the heterogeneity and complexity of both mental health conditions and aging, may help reconcile conflicting results, and provides a basis for further hypothesis-driven research in humans and model systems to investigate potentially causal mechanisms linking aging and mental health.

Ageing-associated phenotypes in mice

Ageing is a continuous process in life featuring progressive damage accumulation that leads to physiological decline, functional deterioration and ultimately death of an organism. Based on the relatively close anatomical and physiological similarity to humans, the mouse has been proven as a valuable model organism in ageing research over the last decades. In this review, we survey methods and tools currently in use to assess ageing phenotypes in mice. We summarize a range of ageing-associated alterations detectable at two major levels of analysis: (1) physiology and pathophysiology and (2) molecular biomarkers. Age-sensitive phenotypes provided in this article may serve to inform future studies targeting various aspects of organismal ageing in mice. In addition, we discuss conceptual and technical challenges faced by previous ageing studies in mice and, where possible, provide recommendations on how to resolve some of these issues.

On standardization of controls in lifespan studies

The search for interventions to slow down and even reverse aging is a burgeoning field. The literature cites hundreds of supposedly beneficial pharmacological and genetic interventions in model organisms: mice, rats, flies and worms, where research into physiology is routinely accompanied by lifespan data. Naturally the negative results are more frequent, yet scientifically quite valuable if analyzed systematically. Yet, there is a strong "discovery bias", i.e. results of interventions which turn out not to be beneficial remain unpublished. Theoretically, all lifespan data is ripe for re-analysis: we could contrast the molecular targets and pathways across studies and help focus the further search for interventions. Alas, the results of most longevity studies are difficult to compare. This is in part because there are no clear, universally accepted standards for conducting such experiments or even for reporting such data. The situation is worsened by the fact that the authors often do not describe experimental conditions completely. As a result, works on longevity make up a set of precedents, each of which might be interesting in its own right, yet incoherent and incomparable. Here we point out specific issues and propose solutions for quality control by checking both inter- and intra-study consistency of lifespan data.

Aging - what it is and how to measure it

The current understanding of the biology of aging is largely based on research aimed at identifying factors that influence lifespan. However, lifespan as a sole proxy measure of aging has limitations because it can be influenced by specific pathologies (not generalized physiological deterioration in old age). Hence, there is a great need to discuss and design experimental approaches that are well-suited for studies targeting the biology of aging, rather than the biology of specific pathologies that restrict the lifespan of a given species. For this purpose, we here review various perspectives on aging, discuss agreement and disagreement among researchers on the definition of aging, and show that while slightly different aspects are emphasized, a widely accepted feature, shared across many definitions, is that aging is accompanied by phenotypic changes that occur in a population over the course of an average lifespan. We then discuss experimental approaches that are in line with these considerations, including multidimensional analytical frameworks as well as designs that facilitate the proper assessment of intervention effects on aging rate. The proposed framework can guide discovery approaches to aging mechanisms in all key model organisms (e.g., mouse, fish models, D. melanogaster, C. elegans) as well as in humans.

A review of standardized high-throughput cardiovascular phenotyping with a link to metabolism in mice

Cardiovascular diseases cause a high mortality rate worldwide and represent a major burden for health care systems. Experimental rodent models play a central role in cardiovascular disease research by effectively simulating human cardiovascular diseases. Using mice, the International Mouse Phenotyping Consortium (IMPC) aims to target each protein-coding gene and phenotype multiple organ systems in single-gene knockout models by a global network of mouse clinics. In this review, we summarize the current advances of the IMPC in cardiac research and describe in detail the diagnostic requirements of high-throughput electrocardiography and transthoracic echocardiography capable of detecting cardiac arrhythmias and cardiomyopathies in mice. Beyond that, we are linking metabolism to the heart and describing phenotypes that emerge in a set of known genes, when knocked out in mice, such as the leptin receptor (Lepr), leptin (Lep), and Bardet-Biedl syndrome 5 (Bbs5). Furthermore, we are presenting not yet associated loss-of-function genes affecting both, metabolism and the cardiovascular system, such as the RING finger protein 10 (Rfn10), F-box protein 38 (Fbxo38), and Dipeptidyl peptidase 8 (Dpp8). These extensive high-throughput data from IMPC mice provide a promising opportunity to explore genetics causing metabolic heart disease with an important translational approach.

Ageing as a software design flaw

Ageing is inherent to all human beings, yet why we age remains a hotly contested topic. Most mechanistic explanations of ageing posit that ageing is caused by the accumulation of one or more forms of molecular damage. Here, I propose that we age not because of inevitable damage to the hardware but rather because of intrinsic design flaws in the software, defined as the DNA code that orchestrates how a single cell develops into an adult organism. As the developmental software runs, its sequence of events is reflected in shifting cellular epigenetic states. Overall, I suggest that to understand ageing we need to decode our software and the flow of epigenetic information throughout the life course.

Dietary restriction in senolysis and prevention and treatment of disease

Aging represents a key risk factor for a plethora of diseases. Targeting detrimental processes which occur during aging, especially before onset of age-related disease, could provide drastic improvements in healthspan. There is increasing evidence that dietary restriction (DR), including caloric restriction, fasting, or fasting-mimicking diets, extend both lifespan and healthspan. This has sparked interest in the use of dietary regimens as a non-pharmacological means to slow aging and prevent disease. Here, we review the current evidence on the molecular mechanisms underlying DR-induced health improvements, including removal of senescent cells, metabolic reprogramming, and epigenetic rejuvenation.