Age and life expectancy clocks based on machine learning analysis of mouse frailty

Frailty in rodents: Models, underlying mechanisms, and management

Frailty is a clinical geriatric syndrome characterized by decreased multisystem function and increased vulnerability to adverse outcomes. Although numerous studies have been conducted on frailty, the underlying mechanisms and management strategies remain unclear. As rodents share homology with humans, they are used extensively as animal models to study human diseases. Rodent frailty models can be classified broadly into the genetic modification and non-genetic modification models, the latter of which include frailty assessment models (based on the Fried frailty phenotype and frailty index methods) and induced frailty models. Such models were developed for use in investigating frailty-related physiological changes at the gene, cellular, molecular, and system levels, including the organ system level. Furthermore, exercise, diet, and medication interventions, in addition to their combinations, could improve frailty status in rodents. Rodent frailty models provide novel and effective tools for frailty research. In the present paper, we review research progress in rodent frailty models, mechanisms, and management, which could facilitate and guide further clinical research on frailty in older adults.

Ageing and cancer: a research gap to fill

The complex mechanisms of ageing biology are increasingly understood. Interventions to reduce or delay ageing‐associated diseases are emerging. Cancer is one of the diseases promoted by tissue ageing. A clockwise mutational signature is identified in many tumours. Ageing might be a modifiable cancer risk factor. To reduce the incidence of ageing‐related cancer and to detect the disease at earlier stages, we need to understand better the links between ageing and tumours. When a cancer is established, geriatric assessment and measures of biological age might help to generate evidence‐based therapeutic recommendations. In this approach, patients and caregivers would include the respective weight to give to the quality of life and survival in the therapeutic choices. The increasing burden of cancer in older patients requires new generations of researchers and geriatric oncologists to be trained, to properly address disease complexity in a multidisciplinary manner, and to reduce health inequities in this population of patients. In this review, we propose a series of research challenges to tackle in the next few years to better prevent, detect and treat cancer in older patients while preserving their quality of life.

Prediction of Chronological Age in Healthy Elderly Subjects with Machine Learning from MRI Brain Segmentation and Cortical Parcellation

Normal aging is associated with changes in volumetric indices of brain atrophy. A quantitative understanding of age-related brain changes can shed light on successful aging. To investigate the effect of age on global and regional brain volumes and cortical thickness, 3514 magnetic resonance imaging scans were analyzed using automated brain segmentation and parcellation methods in elderly healthy individuals (69–88 years of age). The machine learning algorithm extreme gradient boosting (XGBoost) achieved a mean absolute error of 2 years in predicting the age of new subjects. Feature importance analysis showed that the brain-to-intracranial-volume ratio is the most important feature in predicting age, followed by the hippocampi volumes. The cortical thickness in temporal and parietal lobes showed a superior predictive value than frontal and occipital lobes. Insights from this approach that integrate model prediction and interpretation may help to shorten the current explanatory gap between chronological age and biological brain age.

Physiological Systems in Promoting Frailty

Frailty is a complex syndrome affecting a growing sector of the global population as medical developments have advanced human mortality rates across the world. Our current understanding of frailty is derived from studies conducted in the laboratory as well as the clinic, which have generated largely phenotypic information. Far fewer studies have uncovered biological underpinnings driving the onset and progression of frailty, but the stage is set to advance the field with preclinical and clinical assessment tools, multiomics approaches together with physiological and biochemical methodologies. In this article, we provide comprehensive coverage of topics regarding frailty assessment, preclinical models, interventions, and challenges as well as clinical frameworks and prevalence. We also identify central biological mechanisms that may be at play including mitochondrial dysfunction, epigenetic alterations, and oxidative stress that in turn, affect metabolism, stress responses, and endocrine and neuromuscular systems. We review the role of metabolic syndrome, insulin resistance and visceral obesity, focusing on glucose homeostasis, adenosine monophosphate-activated protein kinase (AMPK), mammalian target of rapamycin (mTOR), and nicotinamide adenine dinucleotide (NAD+ ) as critical players influencing the age-related loss of health. We further focus on how immunometabolic dysfunction associates with oxidative stress in promoting sarcopenia, a key contributor to slowness, weakness, and fatigue. We explore the biological mechanisms involved in stem cell exhaustion that affect regeneration and may contribute to the frailty-associated decline in resilience and adaptation to stress. Together, an overview of the interplay of aging biology with genetic, lifestyle, and environmental factors that contribute to frailty, as well as potential therapeutic targets to lower risk and slow the progression of ongoing disease is covered. © 2022 American Physiological Society. Compr Physiol 12:1-46, 2022.

FGF21 is required for protein restriction to extend lifespan and improve metabolic health in male mice

Dietary protein restriction is increasingly recognized as a unique approach to improve metabolic health, and there is increasing interest in the mechanisms underlying this beneficial effect. Recent work indicates that the hormone FGF21 mediates the metabolic effects of protein restriction in young mice. Here we demonstrate that protein restriction increases lifespan, reduces frailty, lowers body weight and adiposity, improves physical performance, improves glucose tolerance, and alters various metabolic markers within the serum, liver, and adipose tissue of wildtype male mice. Conversely, mice lacking FGF21 fail to exhibit metabolic responses to protein restriction in early life, and in later life exhibit early onset of age-related weight loss, reduced physical performance, increased frailty, and reduced lifespan. These data demonstrate that protein restriction in aging male mice exerts marked beneficial effects on lifespan and metabolic health and that a single metabolic hormone, FGF21, is essential for the anti-aging effect of this dietary intervention.

Applying the AFRAID and FRIGHT clocks to novel preclinical mouse models of polypharmacy

The Frailty Inferred Geriatric Health Timeline (FRIGHT) and Analysis of Frailty and Death (AFRAID) clocks were developed to predict biological age and lifespan, respectively, in mice. Their utility within the context of polypharmacy (≥5 medications), which is very common in older adults, is unknown. In male C57BL/6J(B6) mice administered chronic polypharmacy, monotherapy, and undergoing treatment cessation (deprescribing), we aimed to compare these clocks between treatment groups; investigate whether treatment affected correlation of these clocks with mortality; and explore factors that may explain variation in predictive performance. Treatment (control, polypharmacy, or monotherapy) commenced from age 12 months. At age 21 months, each treatment group was subdivided to continue treatment or have it deprescribed. Frailty index was assessed and informed calculation of the clocks. AFRAID, FRIGHT, frailty index, and mortality age did not differ between continued treatment groups and control. Compared to continued treatment, deprescribing some treatments had inconsistent negative impacts on some clocks and mortality. FRIGHT and frailty index, but not AFRAID, were associated with mortality. The bias and precision of AFRAID as a predictor of mortality varied between treatment groups. Effects of deprescribing some drugs on elements of the clocks, particularly on weight loss, contributed to bias. Overall, in this cohort, FRIGHT and AFRAID measures identified no treatment effects and limited deprescribing effects (unsurprising as very few effects on frailty or mortality), with variable prediction of mortality. These clocks have utility, but context is important. Future work should refine them for intervention studies to reduce bias from specific intervention effects.

The Frailty Puzzle: Searching for Immortality or for Knowledge Survival?

What is the value of assessing the biological age and frailty and predicting residual lifespan and health status? The benefit is obvious if we have means to alter the pace of aging and the development of frailty. So far, limited but increasing examples of interventions altering the predicted status indicate that, at least in some cases, this is possible through interventions spanning from the economic-social through drug treatments. Thus, why searching for biological markers, when some clinical and socio-economic indicators do already provide sufficiently accurate predictions? Indeed, the search of frailty biomarkers and of their biological clocks helps to build up a mechanistic frame that may orientate the design of interventions and the time window of their efficacy. Among the candidate biomarkers identified, several studies converge to indicate epigenetic clocks as a promising sensitive biomarker of the aging process. Moreover, it will help to establish the relationship between personal aging and health trajectories and to individuate the check points beyond which biological changes are irreversible.

How to Slow down the Ticking Clock: Age-Associated Epigenetic Alterations and Related Interventions to Extend Life Span

Epigenetic alterations pose one major hallmark of organismal aging. Here, we provide an overview on recent findings describing the epigenetic changes that arise during aging and in related maladies such as neurodegeneration and cancer. Specifically, we focus on alterations of histone modifications and DNA methylation and illustrate the link with metabolic pathways. Age-related epigenetic, transcriptional and metabolic deregulations are highly interconnected, which renders dissociating cause and effect complicated. However, growing amounts of evidence support the notion that aging is not only accompanied by epigenetic alterations, but also at least in part induced by those. DNA methylation clocks emerged as a tool to objectively determine biological aging and turned out as a valuable source in search of factors positively and negatively impacting human life span. Moreover, specific epigenetic signatures can be used as biomarkers for age-associated disorders or even as targets for therapeutic approaches, as will be covered in this review. Finally, we summarize recent potential intervention strategies that target epigenetic mechanisms to extend healthy life span and provide an outlook on future developments in the field of longevity research.

Aerobic Exercise Attenuates Frailty in Aging Male and Female C57Bl/6 Mice and Effects Systemic Cytokines Differentially by Sex

Aerobic exercise is a promising intervention to attenuate frailty, but preclinical studies have used only male animals. We investigated the impact of voluntary aerobic exercise on frailty, biological age (FRailty Inferred Geriatric Health Timeline [FRIGHT] clock), predicted life expectancy (Analysis of FRAIlty and Death [AFRAID] clock), and mortality in both sexes and determined whether exercise was associated with changes in inflammation. Older (21-23 months) male (n = 12) and female (n = 22) C57Bl/6 mice matched for baseline frailty scores were randomized into exercise (running wheel) and sedentary (no wheel) groups. Frailty index scores were measured biweekly (13 weeks), and 23 serum cytokines were measured at midpoint and end point. Exercise levels varied between mice but not between the sexes. Exercise had no effect on mortality, but it attenuated the development of frailty in both sexes (female = 0.32 ± 0.04 vs 0.21 ± 0.01; p = .005; male = 0.30 ± 0.02 vs 0.22 ± 0.02; p = .042) and reduced frailty in older females after 10 weeks. FRIGHT scores were unaffected by exercise but increased with time in sedentary males indicating increased biological age. Exercise prevented the age-associated decline in AFRAID scores in older females such that exercised females had a longer life expectancy. We investigated whether aerobic exercise was associated with changes in systemic inflammation. Cytokine levels were not affected by exercise in males, but levels of pro-inflammatory cytokines were positively correlated with the frequency of exercise in females. Despite increases in systemic inflammation, exercise reduced frailty and increased life span in older females. Thus, voluntary aerobic exercise, even late in life, has beneficial effects on health in both sexes but may be especially helpful in older females.

Bridging the Gap: A Geroscience Primer for Neuroscientists With Potential Collaborative Applications

While neurodegenerative diseases can strike at any age, the majority of afflicted individuals are diagnosed at older ages. Due to the important impact of age in disease diagnosis, the field of neuroscience could greatly benefit from the many of the theories and ideas from the biology of aging-now commonly referred as geroscience. As discussed in our complementary perspective on the topic, there is often a "silo-ing" between geroscientists who work on understanding the mechanisms underlying aging and neuroscientists who are studying neurodegenerative diseases. While there have been some strong collaborations between the biology of aging and neuroscientists, there is still great potential for enhanced collaborative effort between the 2 fields. To this end, here, we review the state of the geroscience field, discuss how neuroscience could benefit from thinking from a geroscience perspective, and close with a brief discussion on some of the "missing links" between geroscience and neuroscience and how to remedy them. Notably, we have a corresponding, concurrent review from the neuroscience perspective. Our overall goal is to "bridge the gap" between geroscience and neuroscience such that more efficient, reproducible research with translational potential can be conducted.

Emerging rejuvenation strategies-Reducing the biological age

Several interventions have recently emerged that were proposed to reverse rather than just attenuate aging, but the criteria for what it takes to achieve rejuvenation remain controversial. Distinguishing potential rejuvenation therapies from other longevity interventions, such as those that slow down aging, is challenging, and these anti-aging strategies are often referred to interchangeably. We suggest that the prerequisite for a rejuvenation intervention is a robust, sustained, and systemic reduction in biological age, which can be assessed by biomarkers of aging, such as epigenetic clocks. We discuss known and putative rejuvenation interventions and comparatively analyze them to explore underlying mechanisms.

PathoClock and PhysioClock in mice recapitulate human multimorbidity and heterogeneous aging

BACKGROUND

Multimorbidity is a public health concern and an essential component of aging and healthspan but understudied because investigative tools are lacking that can be translatable to capture similarities and differences of the aging process across species and variability between individuals and individual organs.

METHODS

To help address this need, body organ disease number (BODN) borrowed from human studies was applied to C57BL/6 (B6) and CB6F1 mouse strains at 8, 16, 24, and 32 months of age, as a measure of systems morbidity based on pathology lesions to develop a mouse PathoClock resembling clinically-based Body Clock in humans, using Bayesian inference. A mouse PhysioClock was also developed based on measures of physiological domains including cardiovascular, neuromuscular, and cognitive function in the same two mouse strains so that alignment with BODN was predictable.

RESULTS

Between- and within-age variabilities in PathoClock and PhysioClock, as well as between-strain variabilities. Both PathoClock and PhysioClock correlated with chronological age more strongly in CB6F1 than C57BL/6. Prediction models were then developed, designated as PathoAge and PhysioAge, using regression models of pathology and physiology measures on chronological age. PathoAge better predicted chronological age than PhysioAge as the predicted chronological and observed chronological age for PhysioAge were complex rather than linear.

CONCLUSION

PathoClock and PhathoAge can be used to capture biological changes that predict BODN, a metric developed in humans, and compare multimorbidity across species. These mouse clocks are potential translational tools that could be used in aging intervention studies.

Modeling aging and its impact on cellular function and organismal behavior

Aging is a complex phenomenon of functional decay in a biological organism. Although the effects of aging are readily recognizable in a wide range of organisms, the cause(s) of aging are ill defined and poorly understood. Experimental methods on model organisms have driven significant insight into aging as a process, but have not provided a complete model of aging. Computational biology offers a unique opportunity to resolve this gap in our knowledge by generating extensive and testable models that can help us understand the fundamental nature of aging, identify the presence and characteristics of unaccounted aging factor(s), demonstrate the mechanics of particular factor(s) in driving aging, and understand the secondary effects of aging on biological function. In this review, we will address each of the above roles for computational biology in aging research. Concurrently, we will explore the different applications of computational biology to aging in single-celled versus multicellular organisms. Given the long history of computational biogerontological research on lower eukaryotes, we emphasize the key future goals of gradually integrating prior models into a holistic map of aging and translating successful models to higher-complexity organisms.

Sex Differences in the Relation Between Frailty and Endothelial Dysfunction in Old Mice

Vascular endothelial function declines with age on average, but there is high variability in the magnitude of this decline within populations. Measurements of frailty, known as frailty index (FI), can be used as surrogates for biological age, but it is unknown if frailty relates to the age-related decline in vascular function. To examine this relation, we studied young (4-9 months) and old (23-32 months) C57BL6 mice of both sexes. We found that FI was greater in old compared with young mice, but did not differ between old male and female mice. Middle cerebral artery (MCA) and mesenteric artery endothelium-dependent dilation (EDD) also did not differ between old male and female mice; however, there were sex differences in the relations between FI and EDD. For the MCA, FI was inversely related to EDD among old female mice, but not old male mice. In contrast, for the mesenteric artery, FI was inversely related to EDD among old male mice, but not old female mice. A higher FI was related to a greater improvement in EDD with the superoxide scavenger TEMPOL in the MCAs for old female mice and in the mesenteric arteries for old male mice. FI related to mesenteric artery gene expression negatively for extracellular superoxide dismutase (Sod3) and positively for interleukin-1β (Il1b). In summary, we found that the relation between frailty and endothelial function is dependent on sex and the artery examined. Arterial oxidative stress and pro-inflammatory signaling are potential mediators of the relations of frailty and endothelial function.

Epigenetic clock and methylation studies in cats

Human DNA methylation profiles have been used successfully to develop highly accurate biomarkers of aging ("epigenetic clocks"). Although these human epigenetic clocks are not immediately applicable to all species of the animal kingdom, the principles underpinning them appear to be conserved even in animals that are evolutionarily far removed from humans. This is exemplified by recent development of epigenetic clocks for mice and other mammalian species. Here, we describe epigenetic clocks for the domestic cat (Felis catus), based on methylation profiles of CpGs with flanking DNA sequences that are highly conserved between multiple mammalian species. Methylation levels of these CpGs are measured using a custom-designed Infinium array (HorvathMammalMethylChip40). From these, we present 3 epigenetic clocks for cats; of which, one applies only to blood samples from cats, while the remaining two dual-species human-cat clocks apply both to cats and humans. We demonstrate that these domestic cat clocks also lead to high age correlations in cheetahs, tigers, and lions. It is expected that these epigenetic clocks for cats possess the potential to be further developed for monitoring feline health as well as being used for identifying and validating anti-aging interventions.

Gut Microbiota Predicts Healthy Late-Life Aging in Male Mice

Calorie restriction (CR) extends lifespan and retards age-related chronic diseases in most species. There is growing evidence that the gut microbiota has a pivotal role in host health and age-related pathological conditions. Yet, it is still unclear how CR and the gut microbiota are related to healthy aging. Here, we report findings from a small longitudinal study of male C57BL/6 mice maintained on either ad libitum or mild (15%) CR diets from 21 months of age and tracked until natural death. We demonstrate that CR results in a significantly reduced rate of increase in the frailty index (FI), a well-established indicator of aging. We observed significant alterations in diversity, as well as compositional patterns of the mouse gut microbiota during the aging process. Interrogating the FI-related microbial features using machine learning techniques, we show that gut microbial signatures from 21-month-old mice can predict the healthy aging of 30-month-old mice with reasonable accuracy. This study deepens our understanding of the links between CR, gut microbiota, and frailty in the aging process of mice.

Pan-Tissue Aging Clock Genes That Have Intimate Connections with the Immune System and Age-Related Disease

In our recent transcriptomic meta-analysis, we used random forest machine learning to accurately predict age in human blood, bone, brain, heart, and retina tissues given gene inputs. Although each tissue-specific model utilized a unique number of genes for age prediction, we found that the following six genes were prioritized in all five tissues: CHI3L2, CIDEC, FCGR3A, RPS4Y1, SLC11A1, and VTCN1. Since being selected for age prediction in multiple tissues is unique, we decided to explore these pan-tissue clock genes in greater detail. In the present study, we began by performing over-representation and network topology-based enrichment analyses in the Gene Ontology Biological Process database. These analyses revealed that the immunological terms "response to protozoan," "immune response," and "positive regulation of immune system process" were significantly enriched by these clock inputs. Expression analyses in mouse and human tissues identified that these inputs are frequently upregulated or downregulated with age. A detailed literature search showed that all six genes had noteworthy connections to age-related disease. For example, mice deficient in Cidec are protected against various metabolic defects, while suppressing VTCN1 inhibits age-related cancers in mouse models. Using a large multitissue transcriptomic dataset, we additionally generate a novel, minimalistic aging clock that can predict human age using just these six genes as inputs. Taken all together, these six genes are connected to diverse aspects of aging.

miR-21 and miR-146a: The microRNAs of inflammaging and age-related diseases

The first paper on "inflammaging" published in 2001 paved the way for a unifying theory on how and why aging turns out to be the main risk factor for the development of the most common age-related diseases (ARDs). The most exciting challenge on this topic was explaining how systemic inflammation steeps up with age and why it shows different rates among individuals of the same chronological age. The "epigenetic revolution" in the past twenty years conveyed that the assessment of the individual genetic make-up is not enough to depict the trajectories of age-related inflammation. Accordingly, others and we have been focusing on the role of non-coding RNA, i.e. microRNAs (miRNAs), in inflammaging. The results obtained in the latest 10 years underpinned the key role of a miRNA subset that we have called inflammamiRs, owing to their ability to master (NF-κB)-driven inflammatory pathways. In this review, we will focus on two inflammamiRs, i.e. miR-21-5p and miR-146a-5p, which target a variety of molecules belonging to the NF-κB/NLRP3 pathways. The interplay between miR-146a-5p and IL-6 in the context of aging and ARDs will also be highlighted. We will also provide the most relevant evidence suggesting that circulating inflammamiRs, along with IL-6, can measure the degree of inflammaging.

The protein inputs of an ultra-predictive aging clock represent viable anti-aging drug targets

Machine learning models capable of predicting age given a set of inputs are referred to as aging clocks. We recently developed an aging clock that utilizes 491 plasma protein inputs, has an exceptional accuracy, and is capable of measuring biological age. Here, we demonstrate that this clock is extremely predictive (r = 0.95) when used to measure age in a novel plasma proteomic dataset derived from 370 human subjects aged 18-69 years. Over-representation analyses of the proteins that make up this clock in the Gene Ontology and Reactome databases predominantly implicated innate and adaptive immune system processes. Immunological drugs and various age-related diseases were enriched in the DrugBank and GLAD4U databases. By performing an extensive literature review, we find that at least 269 (54.8 %) of these inputs regulate lifespan and/or induce changes relevant to age-related disease when manipulated in an animal model. We also show that, in a large plasma proteomic dataset, the majority (57.2 %) of measurable clock proteins significantly change their expression level with human age. Different subsets of proteins were overlapped with distinct epigenetic, transcriptomic, and proteomic aging clocks. These findings indicate that the inputs of this age predictor likely represent a rich source of anti-aging drug targets.

The degree of frailty as a translational measure of health in aging

Frailty is a multiply determined, age-related state of increased risk for adverse health outcomes. We review how the degree of frailty conditions the development of late-life diseases and modifies their expression. The risks for frailty range from subcellular damage to social determinants. These risks are often synergistic-circumstances that favor damage also make repair less likely. We explore how age-related damage and decline in repair result in cellular and molecular deficits that scale up to tissue, organ and system levels, where they are jointly expressed as frailty. The degree of frailty can help to explain the distinction between carrying damage and expressing its usual clinical manifestations. Studying people-and animals-who live with frailty, including them in clinical trials and measuring the impact of the degree of frailty are ways to better understand the diseases of old age and to establish best practices for the care of older adults.

Determination of Biological Age: Geriatric Assessment vs Biological Biomarkers

Purpose of Review

Biological age is the concept of using biophysiological measures to more accurately determine an individual’s age-related risk of adverse outcomes. Grading of the degree of frailty and measuring biomarkers are distinct methods of measuring biological age. This review compares these strategies for estimating biological age for clinical purposes.

Recent Findings

The degree of frailty predicts susceptibility to adverse outcomes independently of chronological age. The utility of this approach has been demonstrated across a range of clinical contexts. Biomarkers from various levels of the biological aging process are improving in accuracy, with the potential to identify aberrant aging trajectories before the onset of clinically manifest frailty.

Summary

Grading of frailty is a demonstrably, clinically, and research-relevant proxy estimate of biological age. Emerging biomarkers can supplement this approach by identifying accelerated aging before it is clinically apparent. Some biomarkers may even offer a means by which interventions to reduce the rate of aging can be developed.

Pinpointing a Role for Vitamin D in Frailty: A Time for Animal Models?

Frailty is a condition marked by greater susceptibility to adverse outcomes, including disability and mortality, which affects up to 50% of those 80 years of age and older. Concurrently, serum vitamin D insufficiency and deficiency, for which as many as 70% of older adults may be at risk, potentially play an important role in frailty onset and progression. Large population driven studies have uncovered associations between low serum vitamin D levels and higher incidence of frailty. However, attempts to apply vitamin D therapeutically to treat and/or prevent frailty have not yielded consistent support for benefits. Given the complexity and inconsistency arising from human studies involving vitamin D, our research group has recently published on animal models of vitamin D insufficiency. Combining our model with the emerging development of animal frailty assessment, we identified that higher than standard levels of vitamin D supplementation may delay frailty in mice. In this viewpoint article, we will discuss current knowledge regarding the importance of vitamin D in frailty progression, the emerging significance of animal models in addressing these relationships, and the future for pre-clinical and clinical research.

Modeling the human aging transcriptome across tissues, health status, and sex

Aging in humans is an incredibly complex biological process that leads to increased susceptibility to various diseases. Understanding which genes are associated with healthy aging can provide valuable insights into aging mechanisms and possible avenues for therapeutics to prolong healthy life. However, modeling this complex biological process requires an enormous collection of high‐quality data along with cutting‐edge computational methods. Here, we have compiled a large meta‐analysis of gene expression data from RNA‐Seq experiments available from the Sequence Read Archive. We began by reprocessing more than 6000 raw samples—including mapping, filtering, normalization, and batch correction—to generate 3060 high‐quality samples spanning a large age range and multiple different tissues. We then used standard differential expression analyses and machine learning approaches to model and predict aging across the dataset, achieving an R² value of 0.96 and a root‐mean‐square error of 3.22 years. These models allow us to explore aging across health status, sex, and tissue and provide novel insights into possible aging processes. We also explore how preprocessing parameters affect predictions and highlight the reproducibility limits of these machine learning models. Finally, we develop an online tool for predicting the ages of human transcriptomic samples given raw gene expression counts. Together, this study provides valuable resources and insights into the transcriptomics of human aging.

ARDD 2020: from aging mechanisms to interventions

Aging is emerging as a druggable target with growing interest from academia, industry and investors. New technologies such as artificial intelligence and advanced screening techniques, as well as a strong influence from the industry sector may lead to novel discoveries to treat age-related diseases. The present review summarizes presentations from the 7th Annual Aging Research and Drug Discovery (ARDD) meeting, held online on the 1st to 4th of September 2020. The meeting covered topics related to new methodologies to study aging, knowledge about basic mechanisms of longevity, latest interventional strategies to target the aging process as well as discussions about the impact of aging research on society and economy. More than 2000 participants and 65 speakers joined the meeting and we already look forward to an even larger meeting next year. Please mark your calendars for the 8th ARDD meeting that is scheduled for the 31st of August to 3rd of September, 2021, at Columbia University, USA.