There is growing interest in the use of molecular features as predictors of age, age-related disease risk and mortality. A major shortcoming of this field, however, is the lack of suitable translational research models to identify and understand the underlying mechanisms of these predictive biomarkers in human populations. In particular, we lack a system which, like humans, is genetically variable, lives in diverse environments, and experiences age-related chronic conditions treated in the context of a sophisticated health care system. Here, we present results from our analysis of data from the Dog Aging Project (DAP), a long-term longitudinal study of aging in companion dogs. Using longitudinal survival models on data from 937 dogs of the deeply phenotyped Precision Cohort within the DAP, we present the striking finding of a strong, highly significant positive correlation between the effect of individual metabolites on all-cause mortality in humans, and the association of those same metabolites on all-cause mortality in dogs. We also find that across these independent human studies, the biomarkers identified are also highly correlated, strongly suggesting a general signature of mortality within the plasma metabolome across humans, and now in dogs as well. Given the many similarities between dogs and humans with respect to genetics, environment, disease, and disease treatment, and the fact that dogs are so much shorter lived than humans, we argue that dogs represent an extremely valuable translational model in our ongoing effort to understand the underlying molecular causes and consequences of age-related morbidity and mortality in humans.

The over 300 currently recognized breeds of domesticated dogs are the culmination of centuries of intense artificial selection and recurrent population bottlenecks. While breed labels are widely used in genetic and veterinary studies, inferring breed identity from genomic data remains challenging due to the high dimensionality of genotype data, uneven sampling across breeds, and admixture resulting in mixed-breed individuals. Here, we present an interpretable machine learning framework to infer dog breed labels from genome-wide SNP data. Our approach combines dimensionality reduction with a multi-output random forest model that maps genetic variation to a continuous representation of breed membership, enabling both classification and mixed-breed inference. We apply this framework to the Dog Aging Project (DAP) dataset of 6,572 purebred and mixed-breed dogs across 100 breed classes, achieving 91.7% accuracy with an overlap-based metric, outperforming an ADMIXTURE-based benchmark that achieved 87.8% accuracy. Notably, we find that as few as 150 informative SNPs are sufficient to achieve near-maximal predictive performance, highlighting the highly structured nature of canine genetic variation. We also introduce a SNP importance score metric that links model predictions back to individual genetic variants. Analysis of top-ranked variants reveals loci previously associated with morphological, pigmentation, and behavioral traits, as well as candidate loci lacking prior phenotypic annotation, supporting both the biological relevance and discovery potential of the framework. Together, these results demonstrate that our framework provides an accurate, flexible, and interpretable approach to predict breed ancestry, with applications in veterinary genomics, canine population genetics, and the identification of loci underlying hallmark breed phenotypes.

Companion dogs (Canis lupus familiaris) offer a unique model for studying the gut microbiome and its relation to aging due to their cohabitation with humans, sharing similar environments, diets, and healthcare practices. Here, we present the Dog Aging Project (DAP) Precision cohort, a large population-wide study of the canine gut microbiome. This cohort encompasses over 900 dogs of diverse breeds, environments, and demographics living across the United States. Coupling fecal shotgun metagenomic sequencing with phenotypic and environmental surveys and clinical lab tests, we explore the intricate relationships between microbiome composition, aging, and key factors such as health and living conditions. Our analyses identify multiple factors associated with microbiome composition, including dietary preferences such as commercial versus home cooked nutrition, and behaviors such as coprophagy (feces eating). In addition, we find age-associated gradual shifts in microbiome composition, supporting the development of a metagenomics-based population-level model for canine age prediction based on microbial signatures. We further examined which age-associated microbial patterns observed in humans are recapitulated in dogs by comparing our cohort with the Lifelines-DEEP cohort. Overall, these findings offer insights into the role the gut microbiome plays in our four-legged companions, with potential implications for veterinary medicine and translational aging research.

Within a species, larger individuals often have shorter lives and higher rates of age-related disease. Despite this well-known link, we still know little about underlying age-related epigenetic differences, which could help us better understand inter-individual variation in aging and the etiology, onset, and progression of age-associated disease. Dogs exhibit this negative correlation between size, health, and longevity and thus represent an excellent system in which to test the underlying mechanisms. Here, we quantified genome-wide DNA methylation in a cohort of 864 dogs in the Dog Aging Project. Age strongly patterned the dog epigenome, with the majority (66% of age-associated loci) of regions associating age-related loss of methylation. These age effects were non-randomly distributed in the genome and differed depending on genomic context. We found the LINE1 (long interspersed elements) class of TEs (transposable elements) were the most frequently hypomethylated with age (FDR < 0.05, 40% of all LINE1 regions). This LINE1 pattern differed in magnitude across breeds of different sizes- the largest dogs lost 0.26% more LINE1 methylation per year than the smallest dogs. This suggests that epigenetic regulation of TEs, particularly LINE1s, may contribute to accelerated age and disease phenotypes within a species. Since our study focused on the methylome of immune cells, we looked at LINE1 methylation changes in golden retrievers, a breed highly susceptible to hematopoietic cancers, and found they have accelerated age-related LINE1 hypomethylation compared to other breeds. We also found many of the LINE1s hypomethylated with age are located on the X chromosome and are, when considering X chromosome inactivation, counter-intuitively more methylated in males. These results have revealed the demethylation of LINE1 transposons as a potential driver of intra-species, demographic-dependent aging variation.

Companion dogs have emerged as a valuable model in the study of cognitive aging, but assessments of cognitive function in large, diverse, and geographically distributed samples of dogs are challenging to obtain. We developed two novel functional assessments of short-term spatial memory that were administered by community science participants in a sample of 6,753 dogs through the Dog Aging Project. We compared data generated by community scientists to those gathered by research professionals, estimated relationships between age and task performance, and tested the hypothesis that associations between age and cognitive performance vary by dog body mass, as a proxy for expected lifespan. Community scientists generated similar data to research professionals and both cognitive tasks were sensitive to age-related deficits, beginning in midlife. Relationships between age and cognitive function were highly similar across small and large dogs and, for both tasks, comparison of models with and without an interaction between age and body mass yielded decisive evidence for the model without the interaction. Large dogs exhibit accelerated aging across many traits, and so the lack of evidence for accelerated cognitive aging raises the possibility that their large size confers a neuroprotective advantage. We consider possible mechanisms underlying this effect and address how experimental studies of dog cognition using community science methods can support future research on mechanisms of brain and cognitive aging.

Comorbidity and its association with age are of great interest in geroscience. However, there are few model organisms that are well-suited to study comorbidities that will have high relevance to humans. In this light, we turn our attention to the companion dog. The companion dog shares many morbidities with humans. Thus, a better understanding of canine comorbidity relationships could benefit both humans and dogs. We present an analysis of canine comorbidity networks from the Dog Aging Project, a large epidemiological cohort study of companion dogs in the United States. We included owner-reported health conditions that occurred in at least 60 dogs (n=160) and included only dogs that had at least one of those health conditions (n=26,614). We constructed an undirected comorbidity network using a Poisson binomial test, adjusting for age, sex, sterilization status, breed background (i.e., purebred vs. mixed-breed), and weight. The comorbidity network reveals well-documented comorbidities, such as diabetes with cataracts and blindness, and hypertension with chronic kidney disease (CKD). In addition, this network also supports less well-studied comorbidity relationships, such as proteinuria with anemia. A directed comorbidity network accounting for time of reported condition onset suggests that diabetes precedes cataracts, elbow/hip dysplasia before osteoarthritis, and keratoconjunctivitis sicca before corneal ulcer, which are consistent with the canine literature. Analysis of age-stratified networks reveals that global centrality measures increase with age and are the highest in the Senior group compared to the Young Adult and Mature Adult groups. Only the Senior group identified the association between hypertension and CKD. Our results suggest that comorbidity network analysis is a promising method to enhance clinical knowledge and canine healthcare management.

Sex plays a crucial role in aging, influencing health trajectories, longevity, and disease susceptibility. Understanding the underlying mechanisms of these sex differences, and the extent to which they are evolutionarily conserved, remains a key challenge in aging research. Metabolites, the small molecules that mediate biochemical processes and link genetic variation with phenotypic traits, offer a powerful lens through which to explore sex-specific biology. Using a comparative framework across 11 Drosophila species, representing 50 million years of evolution, we investigate sex differences in the metabolome of young and old flies to identify patterns of age- and sex-related metabolomic changes. We find that male and female metabolomic profiles are highly correlated with each other across species, with this correlation weakening slightly with age. Despite this, numerous metabolites remain consistently sexually dimorphic across species and age groups, suggesting that sex-specific metabolic regulation is deeply evolutionarily conserved. We propose that endophenotypes like the metabolome can provide valuable insights into the mechanisms underlying sex differences in diverse traits such as age-related morbidity and mortality. Moreover, conserved and species-specific patterns can reveal why these differences have arisen and been maintained over evolutionary time.

The companion dog is an exceptional translational model for understanding the causes and consequences of aging. Among breeds, we observe high levels of variation not only in morphology and behavior, but also in lifespan and the risk of specific diseases, many of which are common in humans. Dogs share our environment and, like us, have a sophisticated healthcare system. Their shorter lifespan relative to humans means that lessons that might take decades to learn from human longitudinal studies can be gleaned in just a few years by observing aging in dogs. Here, we share recent findings from the Dog Aging Project, a long-term longitudinal study designed to identify the genetic and environmental factors that influence healthy aging in dogs and the mechanisms by which they do so. As part of the Dog Aging Project, we collect annual measures of the plasma metabolome for nearly 1,000 dogs from across the United States. Age-related changes in the metabolome point to underlying mechanisms that might account for breed variation in lifespan. We have also identified individual metabolites that predict mortality risk and found that the sign and magnitude of their effects are significantly correlated with patterns observed in comparable human studies. Finally, we discuss how metabolome profiles can serve as a bridge linking upstream genetic and environmental factors with downstream traits related to aging. As such, metabolome profiles provide a more complete picture of the causes and consequences of aging and related disease.

A significant challenge in multi-omic geroscience research is the collection of high quality, fit-for-purpose biospecimens from a diverse and well-characterized study population with sufficient sample size to detect age-related changes in physiological biomarkers. The Dog Aging Project designed the precision cohort to study the mechanisms underlying age-related change in the metabolome, microbiome, and epigenome in companion dogs, an emerging model system for translational geroscience research. One thousand dog-owner pairs were recruited into cohort strata based on life stage, sex, size, and geography. We designed and built a novel implementation of the REDCap electronic data capture system to manage study participants, logistics, and biospecimen and survey data collection in a secure online platform. In collaboration with primary care veterinarians, we collected and processed blood, urine, fecal, and hair samples from 976 dogs. The resulting data include complete blood count, chemistry profile, immunophenotyping by flow cytometry, metabolite quantification, fecal microbiome characterization, epigenomic profile, urinalysis, and associated metadata characterizing sample conditions at collection and during lab processing. The project, which has already begun collecting second- and third-year samples from precision cohort dogs, demonstrates that scientifically useful biospecimens can be collected from a geographically dispersed population through collaboration with private veterinary clinics and downstream labs. The data collection infrastructure developed for the precision cohort can be leveraged for future studies. Most important, the Dog Aging Project is an open data project. We encourage researchers around the world to apply for data access and utilize this rich, constantly growing dataset in their own work.

Sex has a major effect on the metabolome. However, we do not yet understand the degree to which differences in metabolism are associated with anatomical dimorphism and modulated by sex-specific tissues. In the fruit fly, Drosophila melanogaster, knocking out doublesex (dsx) gives rise to adults with intermediate sex characteristics. Here, we sought to determine the degree to which this key node in sexual development leads to sex differences (SD) in the metabolome. We measured 91 metabolites across three tissues, comparing sex-dimorphic flies with those of reduced dimorphism: dsx null flies. The abundance of 51% of metabolites (46/91) differed between wildtype XX and XY flies in at least one tissue. However, in dsx flies, we only observed a sex difference in kynurenate, suggesting that dsx plays a major role in SD in fly metabolism. Kynurenate was consistently higher in XX flies in both dsx flies and controls. We also observed tissue-specific effects in dsx flies. Sex dimorphism manifests in part through dimorphic growth of organs, and we find that dimorphic metabolites across the fly enriched the growth-related branched-chain amino acid and mammalian target of rapamycin pathways. Our findings demonstrate that sex dimorphism is accompanied by substantial effects on the metabolome throughout the body.

Companion dogs are a powerful model for aging research given their morphologic and genetic variability, risk for age-related disease, and habitation of the human environment. In addition, the shorter life expectancy of dogs compared to human beings provides a unique opportunity for an accelerated timeline to test interventions that might extend healthy lifespan. The Test of Rapamycin In Aging Dogs (TRIAD) randomized clinical trial is a parallel-group, double-masked, randomized, placebo-controlled, multicenter trial that will test the ability of rapamycin to prolong lifespan and improve several healthspan metrics in healthy, middle-aged dogs recruited from Dog Aging Project participants. Here, we describe the rationale, design, and goals of the TRIAD randomized clinical trial, the first rigorous test of a pharmacologic intervention against biological aging with lifespan and healthspan metrics as endpoints to be performed outside of the laboratory in any species.

S-adenosylmethionine (SAM), produced by SAM synthases, is critical for various cellular regulatory pathways and the synthesis of diverse metabolites. Studies have often equated the effects of knocking down one synthase with broader SAM-dependent outcomes such as histone methylation or phosphatidylcholine (PC) production. Humans and many other organisms express multiple SAM synthases. Evidence in Caenorhabditis elegans, which possesses four SAM synthase genes, suggest that the enzymatic source of SAM impacts its function. For instance, loss of sams-1 leads to enhanced heat shock survival and increased lifespan, whereas reducing sams-4 adversely affects heat stress survival. Here, we show that SAMS-1 contributes to a variety of intermediary metabolic pathways, whereas SAMS-4 is more important to generate SAM for methylation reactions. We demonstrate that loss of sams-1 exerts age-dependent effects on nuclear-encoded mitochondrial gene expression, mitochondrial metabolites, and may induce mitophagy. We propose a mechanistic model where reduced SAM from SAMS-1 acts through PC to impact mitochondria, thereby enhancing survival during heat stress.

Advances in public health, medicine, and technology since the mid-19th century have redefined what is considered "natural" for human beings. This article situates contemporary geroscience in that historical context. The development of gerotherapies must be guided by historical insight, ethical foresight, and a commitment to justice. Since extending lifespans has important societal consequences, how aging research will affect future generations should be prioritized. Equitable access to gerotherapies, as well as an emphasis on social responsibility and the influence of community on health and longevity, must remain central to any vision of the future of aging.

Inflammaging, the chronic, progressive proinflammatory state associated with aging, has been associated with multiple negative health outcomes in humans. The pathophysiology of inflammaging is complex; however, it is often characterized by high serum concentrations of inflammatory mediators such as tumor necrosis factor alpha (TNF-α), interleukin (IL)-6, and C-reactive protein (CRP). Few studies have evaluated the effects of age on inflammatory cytokines in companion dogs, and most of these studies included dogs of a single breed. In this cross-sectional study, we measured multiple circulating inflammatory markers and hematological parameters in banked serum samples from 47 healthy companion dogs of various breeds enrolled in the Dog Aging Project. Using univariate linear models, we investigated the association of each of these markers with age, sex, body weight, and body condition score (BCS), a measure of obesity in the dog. Serum IL-6, IL-8, and TNF-α concentrations were all positively associated with age. Lymphocyte count was negatively associated with age. Platelet count had a negative association with body weight. IL-2, albumin, cholesterol, triglyceride, bilirubin, S100A12, and NMH concentrations were not associated with age, weight, BCS, or sex after adjustment for multiple comparisons. Our findings replicate previous findings in humans, including increases in IL-6 and TNF-α with age, giving more evidence to the strength of the companion dog as a model for human aging.

To gain insight into how researchers of aging perceive the process they study, we conducted a survey among experts in the field. While highlighting some common features of aging, the survey exposed broad disagreement on the foundational issues. What is aging? What causes it? When does it begin? What constitutes rejuvenation? Not only was there no consensus on these and other core questions, but none of the questions received a majority opinion-even regarding the need for consensus itself. Despite many researchers believing they understand aging, their understanding diverges considerably. Importantly, as different processes are labeled as "aging" by researchers, different experimental approaches are prioritized. The survey shed light on the need to better define which aging processes this field should target and what its goals are. It also allowed us to categorize contemporary views on aging and rejuvenation, revealing critical, yet largely unanswered, questions that appear disconnected from the current research focus. Finally, we discuss ways to address the disagreement, which we hope will ultimately aid progress in the field.

Companion dogs are a valuable model for aging research, including studies of cognitive decline and dementia. With advanced age, some dogs spontaneously develop cognitive impairments and neuropathology resembling features of Alzheimer’s disease. These processes have been studied extensively in laboratory beagles, but the cognitive assays used in that context—which rely on time-consuming operant procedures—are not easily scalable to large samples of community-dwelling companion dogs. We developed a battery of five short-form tasks targeting three aspects of cognition that are impaired in Alzheimer’s disease: spatial memory, executive functions, and social cognition. In Experiment 1, we tested a cross-sectional sample of dogs (N = 123) and estimated associations between age and task performance. Older dogs scored lower on measures of spatial learning, memory, and response flexibility, and spent less time near, but more time gazing at, the experimenter. We found no differences in associations between age and performance across dogs of different body masses, a proxy for expected lifespan. In Experiment 2, we demonstrated the feasibility of these measures in clinical settings (N = 35). Dogs meeting clinical criteria for moderate or severe cognitive impairment scored lower, on average, than dogs characterized as mildly impaired and healthy agers, although these distributions overlapped. However, few dogs in our study cohort met the criteria for moderate or severe impairment. The measures presented here show promise for deployment in large-scale longitudinal studies of companion dogs, such as the Dog Aging Project.

Our understanding of age-related physiology and metabolism has grown through the study of systems biology, including transcriptomics, single-cell analysis, proteomics and metabolomics. Studies in lab organisms in controlled environments, while powerful and complex, fall short of capturing the breadth of genetic and environmental variation in nature. Thus, there is now a major effort in geroscience to identify aging biomarkers and to develop aging interventions that might be applied across the diversity of humans and other free-living species. To meet this challenge, the Dog Aging Project (DAP) is designed to identify cross-sectional and longitudinal patterns of aging in complex systems, and how these are shaped by the diversity of genetic and environmental variation among companion dogs. Here we surveyed the plasma metabolome from the first year of sampling of the Precision Cohort of the DAP. By incorporating extensive metadata and whole genome sequencing information, we were able to overcome the limitations inherent in breed-based estimates of genetic and physiological effects, and to probe the physiological and dietary basis of the age-related metabolome. We identified a significant effect of age on approximately 40% of measured metabolites. Among other insights, we discovered a potentially novel biomarker of age in the post-translationally modified amino acids (ptmAAs). The ptmAAs, which can only be generated by protein hydrolysis, covaried both with age and with other biomarkers of amino acid metabolism, and in a way that was robust to diet. Clinical measures of kidney function mediated about half of the higher ptmAA levels in older dogs. This work identifies ptmAAs as robust indicators of age in dogs, and points to kidney function as a physiological mediator of age-associated variation in the plasma metabolome.

Dietary restriction (DR) is a potent method to enhance lifespan and healthspan, but individual responses are influenced by genetic variations. Understanding how metabolism-related genetic differences impact longevity and healthspan are unclear. To investigate this, we used metabolites as markers to reveal how different genotypes respond to diet to influence longevity and healthspan traits. We analyzed data from Drosophila Genetic Reference Panel (DGRP) strains raised under AL and DR conditions, combining metabolomic, phenotypic, and genome-wide information. We employed two computational and complementary methods across species—random forest modeling within the DGRP as our primary analysis and Mendelian randomization in human cohorts as a secondary analysis. We pinpointed key traits with cross-species relevance as well as underlying heterogeneity and pleiotropy that influence lifespan and healthspan. Notably, orotate was linked to parental age at death in humans and blocked the DR lifespan extension in flies, while threonine supplementation extended lifespan, in a strain- and sex-specific manner. Thus, utilizing natural genetic variation data from flies and humans, we employed a systems biology approach to elucidate potential therapeutic pathways and metabolomic targets for diet-dependent changes in lifespan and healthspan. Here, the authors use multi-organism machine learning to identify conserved metabolites modulating aging and healthspan in flies and humans. Threonine showed protective effects across species, while orotate levels were detrimental to lifespan.

Age in dogs is associated with the risk of many diseases, and canine size is a major factor in that risk. However, the size patterns are complex. While small size dogs tend to live longer, some diseases are more prevalent among small dogs. In this study we seek to quantify how the pattern of disease history varies across the spectrum of dog size, dog age, and their interaction. Utilizing owner-reported data on disease history from a substantial number of companion dogs enrolled in the Dog Aging Project, we investigate how body size, as measured by weight, associates with the lifetime prevalence of a reported condition and its pattern across age for various disease categories. We found significant positive associations between dog size and the lifetime prevalence of skin, bone/orthopedic, gastrointestinal, ear/nose/throat, cancer/tumor, brain/neurologic, endocrine, and infectious diseases. Similarly, dog size was negatively associated with lifetime prevalence of ocular, cardiac, liver/pancreas, and respiratory disease categories. Kidney/urinary disease prevalence did not vary by size. We also found that the association between age and lifetime disease prevalence varied by dog size for many conditions including ocular, cardiac, orthopedic, ear/nose/throat, and cancer. Controlling for sex, purebred vs. mixed-breed status, and geographic region made little difference in all disease categories we studied. Our results align with the reduced lifespan in larger dogs for most of the disease categories and suggest potential avenues for further examination.

Across mammals, the epigenome is highly predictive of chronological age. These “epigenetic clocks,” most of which have been built using DNA methylation (DNAm) profiles, have gained traction as biomarkers of aging and organismal health. While the ability of DNAm to predict chronological age has been repeatedly demonstrated, the ability of other epigenetic features to predict age remains unclear. Here, we use two types of epigenetic information—DNAm, and chromatin accessibility as measured by ATAC-seq—to develop age predictors in peripheral blood mononuclear cells sampled from a population of domesticated dogs. We measured DNAm and ATAC-seq profiles for 71 dogs, building separate predictive clocks from each, as well as the combined dataset. We also use fluorescence-assisted cell sorting to quantify major lymphoid populations for each sample. We found that chromatin accessibility can accurately predict chronological age (R 2 ATAC  = 26%), though less accurately than the DNAm clock (R 2 DNAm  = 33%), and the clock built from the combined datasets was comparable to both (R 2 combined  = 29%). We also observed various populations of CD62L+ T cells significantly correlated with dog age. Finally, we found that all three clocks selected features that were in or near at least two protein-coding genes: BAIAP2 and SCARF2 , both previously implicated in processes related to cognitive or neurological impairment. Taken together, these results highlight the potential of chromatin accessibility as a complementary epigenetic resource for modeling and investigating biologic age.