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. 2024 Sep 23;47(1):61–83. doi: 10.1007/s11357-024-01327-5

Contributions and future potential of animal models for geroscience research on sensory systems

Arthur G Fernandes 1,, Alice C Poirier 1, Carrie C Veilleux 1,2, Amanda D Melin 1,3,4,
PMCID: PMC11872837  PMID: 39312151

Abstract

Sensory systems mediate our social interactions, food intake, livelihoods, and other essential daily functions. Age-related decline and disease in sensory systems pose a significant challenge to healthy aging. Research on sensory decline in humans is informative but can often be difficult, subject to sampling bias, and influenced by environmental variation. Study of animal models, including mice, rats, rabbits, pigs, cats, dogs, and non-human primates, plays a complementary role in biomedical research, offering advantages such as controlled conditions and shorter lifespans for longitudinal study. Various species offer different advantages and limitations but have provided key insights in geroscience research. Here we review research on age-related decline and disease in vision, hearing, olfaction, taste, and touch. For each sense, we provide an epidemiological overview of impairment in humans, describing the physiological processes and diseases for each sense. We then discuss contributions made by research on animal models and ideas for future research. We additionally highlight the need for integrative, multimodal research across the senses as well as across disciplines. Long-term studies spanning multiple generations, including on species with longer life spans, are also highly valuable. Overall, integrative studies of appropriate animal models have high translational potential for clinical applications, the development of novel diagnostics, therapies, and medical interventions and future research will continue to close gaps in these areas. Research on animal models to improve understanding of the biology of the aging senses and improve the healthspan and additional research on sensory systems hold special promise for new breakthroughs.

Keywords: Aging, Nonhuman primates, Geroscience research, Sensory aging

Introduction

Worldwide, populations of aged people are rapidly increasing. In 2020, there were over 1 billion individuals aged 60 and above, with projections indicating a rise to 1.4 billion by 2030 and 2.1 billion by 2050 [1]. This steep escalation is driven by improved healthcare services and advancements in technology, leading to an unprecedented demographic shift that is set to intensify in the coming decades. Healthy lifespans, however, have increased at a slower rate than life expectancy [2, 3]. From 2000 to 2020, life expectancy at birth increased by 6.6 years, but healthy life expectancy at birth increased by only 5.4 years [4], meaning individuals are living longer, but not necessarily in better health.

Age-related sensory dysfunction is an increasingly recognized affliction that leads to numerous physical and psychological difficulties and disabilities [5, 6]. Consequently, one of the primary focal points of the United Nations Decade of Healthy Aging (UNDHA; 2021–2030) proposal involves enhancing the delivery of person-centered, integrated care, and primary health services tailored to the needs of older individuals [7]. This represents a crucial opportunity to tackle the health challenges specific to older adults. The World Health Organization (WHO) underscores the significance of preserving individuals’ functional ability as a key element in healthy aging, including sensory health [8]. Studies in humans and other mammalian species have shown that the loss of sensory capabilities represents an acute challenge to the maintenance of healthy social interactions and relationships during the aging process [9]. Such declines in sensation may not only affect the ability of aged individuals to respond to, but also to produce, social information [9]. Despite the critical role of the senses when forming the interface with the world, sensory research has been routinely overlooked [6].

Existing research on human senses exhibits a bias toward industrialized societies, where the complexities of sensory pollution can interact with the aging process impeding and complicating an understanding of age-related effects on sensory systems. For example, the high-noise level of big cities can cause damage to the ears, increasing hearing loss, and air pollution can intensify anosmia (loss of smell) processes [1012]. Due to these difficulties in collecting sufficient representative data from humans, the study of animal models provides a complementary opportunity to explore the effects of aging as well as the environmental influences on sensory perception.

Research on animal models provides numerous advantages, including an increased ability to control conditions and replicate experiments. Additionally, animals typically have shorter lifespans relative to humans, providing a favorable scenario for longitudinal research, where disease development and outcomes unfold over shorter periods of follow-up time [1315]. Biomedical research has employed animal models since the eighteenth and nineteenth centuries to conduct significant studies on human physiology, anatomy, pathology, and aging [16]. Various animal species, including Drosophila (insects), zebrafish (Danio rerio, fish), Caenorhabditis elegans (nematodes), and Xenopus (frogs), have been useful for understanding fundamental biological processes, development, genetics, and disease mechanisms [17]. Mammals such as mice (Mus musculus), rats (Rattus norvegicus), rabbits (Oryctolagus cuniculus), pigs (Sus domesticus), cats (Felis catus), dogs (Canis familiaris), and non-human primates (NHPs; lemurs, monkeys, and apes) are often chosen for sensory system research due to their phylogenetic proximity and shared traits with humans [17].

Here, we review current research on how the senses of vision, hearing, olfaction, taste, and touch decline with age in human and nonhuman animals. For each sense, we first describe the physiological processes associated with it, provide a general epidemiological overview of impairment in humans, present the main age-related diseases and insights provided by study of animal models, and conclude each section by suggesting promising future directions.

Vision

Introduction, anatomy, and physiological processes

Vision is a key sense to humans and other primates. It plays an important role across various dimensions and stages in an individual’s structural, economic, and social contexts [18]. Visual impairment can impact physical, cognitive, psychological, and social functioning, crucial components of healthy aging [19]. While vision loss itself is not life-threatening, it is a disability that can lead to lower economic, educational, and employment opportunities. Additionally, it can result in a reliance on care and an increased risk of mortality [20, 21]. Moreover, in advanced age, vision loss not only significantly decreases the quality of life, as evidenced by associations with conditions like depression, but also exacerbates comorbidities such as cognitive impairment and the risk of falls [22, 23]. This hinders the pursuit of healthy aging and the maintenance of optimal functional ability [24].

Visual function involves a complex interplay between the eyes and the brain. The process begins as light enters the eye passing through the cornea, onto the lens, which further focuses the light onto the retina [25]. In the retina, specialized photoreceptor cells—rods and cones—convert light into electrical signals through the phototransduction process. In some species, such as the retina contains a specialized area called macula, which enables high-resolution central vision due to its dense concentration of cone photoreceptors. The signals generated in the retina are then transmitted to the optic nerve, with some fibers crossing at the optic chiasm to allow signals from both eyes to reach both hemispheres of the brain. The optic nerve carries these signals to the visual cortex, where the brain processes the information, interpreting shapes, colors, and movement. The brain integrates the visual input from both eyes to create a cohesive three-dimensional perception of the surrounding environment. This intricate process, along with eye movements and higher-level visual processing, contributes to our ability to perceive and interpret the visual world around us [26]. Any disruptive process in the anatomy or physiology compromises the vision process and can lead to visual impairment and blindness.

Aging and age-related diseases in human vision and insights from animal models

Aging is the largest risk factor for visual impairment and blindness, and it is the main responsible for the increasing magnitude of such conditions over the next decades. The 2017 Global Burden of Disease (GBD) Study ranked vision impairment, including blindness, as the third main cause among all impairments for years lived with disability [27]. The financial consequences of vision loss extend beyond the individual, impacting families and communities. Global estimates for vision loss in 2020 project that 18.1 million people experienced blindness, and 142.6 million had moderate to severe vision impairment within the working-age range of 15 to 64 years old, resulting in an approximate annual global productivity loss of US$ 410.7 billion [18]. The Vision Loss Expert Group estimates that 43.3 million people are blind worldwide and 295.3 million people are moderately to severely visually impaired. The main reported causes for blindness are cataracts, glaucoma, uncorrected refractive errors, age-related macular degeneration, and diabetic retinopathy, while the main causes for visual impairment are uncorrected refractive errors, cataract, age-related macular degeneration, glaucoma, and diabetic retinopathy [28]. With the exception of uncorrected refractive errors, the remaining four conditions are strongly associated with aging.

Biomedical research in ophthalmology has frequently used rodents and rabbits as animal models, chosen for their short lifespans, cost-effective maintenance, genomic resource availability, and ease of handling [29, 30]. Companion animals, such as dogs and cats, have also historically been used in eye-related research and serve as valuable models, particularly for glaucoma and diabetic retinopathy studies, due to their disease phenotypes being similar to those seen in human diseases [3133]. These models offer the advantages of lower cost, disease progression on a relatively quick time scale, and the ability to perform genetic manipulation; however, differences in their ocular anatomy from that of humans [34, 35] limit their potential as translational models. NHP models are considered the optimal choice for studying human health and disease due to their genetic similarity and conserved protein sequences with humans [36]. Ocular studies in rhesus macaques (Macaca mulatta), in particular, have demonstrated close anatomical similarities between their visual systems and those of humans, including features of the optic nerve head, retina, and lens [3739]. These primates also exhibit age-related ocular associations like those observed in human aging, such as decreased corneal thickness, increased axial length, and a higher incidence of cataracts and retinal drusen [39, 40]. However, there are also drawbacks to primate studies. Although NHPs offer the closest anatomy to humans, they are quite difficult to manipulate genetically, are costly to maintain, and have a slow time course of disease progression which may limit their potential. Ethical considerations with respect to housing conditions and social environment also add to expenses and difficulty of care for these animals.

Animal models have been useful for understanding the mechanisms associated with the main causes of vision impairment worldwide, as well as with promising therapies and treatments. Cataract, characterized by the intraocular lens opacification that impacts both distance and near sight, is the main cause of visual impairment and blindness worldwide [4143]. Surgery is the primary treatment, so that rather than new treatments, the current focus of cataract research is on disease prevention [44]. Different drug regimens such as N-acetylcysteine amide, N-acetylcarnosine, lutein, sterols, and isolated phytoconstituents have been developed through research in animal models, mostly rats and mice, aiming to avoid the cataract development [4548], an ongoing effort as there is currently no commercially available drug capable of effectively preventing the occurrence and progression of senile cataract.

Glaucoma, the leading cause of irreversible blindness, is characterized by the degeneration of retinal ganglion cell complexes and retinal nerve fiber layers causing changes in the optical nerve head (ONH) and is usually associated with increased intraocular pressure (IOP) [28]. Such changes can cause loss of visual perception, which is irreversible [49, 50]. Studies involving non-human primates have been important for optimizing methods of IOP assessment, identifying ONH deformations in response to IOP elevation, longitudinally assessing ONH changes over time in untreated glaucoma cases, evaluating the relationship between macula retinal ganglion cell density and visual function, testing new clinical and surgical treatment approaches, and more recently, examining the changes in the microstructure of the lamina cribosa in glaucoma eyes [5157].

Age-related macular degeneration (ARMD) is a complex condition that can present as a “dry,” non-neovascular form, leading to geographic atrophy, or a “wet,” neovascular form, characterized by choroidal neovascularization (CNV). Numerous animal models of ARMD such as mice, rats, rabbits, pigs, and NHPs have been developed recreating many of the histological features of ARMD, providing much insight into the underlying pathological mechanisms of this disease. For example, they have helped reveal the roles of chronic oxidative damage, inflammation and immune dysregulation, and lipid metabolism in the development of ARMD. While NHP models are anatomically closer to humans in terms of having macula, it is important to note the rarity of ARMD cases among such groups [58]. Previous studies have found a high prevalence of drusen in older macaques; however, just a few cases have evolved to geographic atrophy or CNV [59, 60]. Other models such as rodents do not have a macula but are genetically manipulable and are considered the most practical model to test the numerous genetic alterations associated with AMD. They have been important to understand pathophysiological processes at cellular level such as the role of complement activation and macrophage chemotaxis, molecular mechanisms of choroidal neovascularization, and the roles of oxidative damage and lipid metabolism [60]. Moreover, different models with induced choroidal neovascularization have served as the backbone for testing new therapies currently available in the market [58, 61].

Diabetic retinopathy (DR) is a progressive disease resulting from diabetes-induced damage to the blood vessels in the retina [62, 63]. The most frequently used models for inducing DR are mice and rats, but dogs, cats, pigs, rabbits, NHPs, and zebrafish are also used, with dogs showing the most similar morphological retinal lesions as those seen in humans [32, 33]. Still, presentation of induced DR pathology is generally slower in larger animals, making rodents and, recently, zebrafish more favored models [64]. The majority of the available models better recapitulate the early stages of the diseases, limiting the availability of models to evaluate comprehensive therapies for DR. Treatments are generally restricted to targeting the early progression of the disease due to the limited available models. Additionally, animal models of retinal neovascularization, without hyperglycemia, have been developed. These models may provide valuable tools to understand pathogenesis and develop appropriate treatment options for late-stage DR disease [33].

In summary, animal models have been indispensable in advancing our understanding of age-related visual impairment and blindness, as well as in the development of therapeutic interventions. While rodent and rabbit models provide valuable insights into the genetic and molecular mechanisms underlying ocular diseases, the mentioned anatomical differences from humans pose some limitations. NHPs, on the other hand, offer closer anatomical and physiological similarities, making them critical for translational research despite the challenges associated with their use, such as higher costs and slower disease progression. The integration of various animal models, each with its unique advantages, is essential for a comprehensive approach to geroscience research in ophthalmology. This multi-model strategy allows researchers to dissect complex visual processes and develop effective treatments for age-related conditions, thereby improving the quality of life and promoting healthy aging in human populations. Future research should continue to refine these models and explore innovative ways to bridge the gap between animal studies and human clinical applications, ensuring that the advancements in geroscience translate into tangible benefits for those affected by visual impairments and blindness.

Hearing

Introduction, anatomy, and physiological processes

Hearing plays a crucial role in interpersonal relations and health-related quality of life. Similar to vision loss, hearing loss is associated with significant psychological and medical morbidities. Individuals with hearing impairment often experience social isolation due to difficulties in communication, which can further contribute to mental health issues, such as depression and anxiety.

The hearing process begins with the reception of sound waves by the outer ear, which then travel through the ear canal to reach the eardrum. The vibrations of the eardrum are transmitted to the three small bones in the middle ear—the malleus, incus, and stapes—amplifying the signals. This mechanical energy is transmitted to the fluid present within the cochlea, the spiral-shaped organ in the inner ear. Inside the cochlea, hair cells, supported by the stria vascularis, convert these mechanical vibrations into electrical signals that are sent to the auditory nerve. The auditory nerve carries these signals to the temporal lobe (auditory cortex), where they are integrated and interpreted as sound [6567].

Aging and age-related diseases in human hearing and insights from animal models

Age-related hearing loss (ARHL), also described as presbycusis, is defined as a speech-frequency pure-tone average (average of hearing thresholds at 0.5, 1, 2, and 4 kHz) greater than 25 dB hearing level [6870]. This is a sensorial disorder characterized as a bilateral, symmetrical, and progressive sensorineural hearing loss consequence of cumulative effects of aging on the complex auditory system. It is the most prevalent sensory deficit in older adults, affecting approximately 50% of adults in their seventh decade severely enough to compromise communication, and it is estimated to be within the top 15 leading causes of burden of disease by 2030 [68, 69]. Previous studies have shown that men are more likely to experience hearing loss than women of the same age [70]. Moreover, different population-based studies have shown that hearing loss is associated with more rapid cognitive and physical aging [71, 72]. Besides the health burden, the economic impact combining direct medical and lost productivity costs attributable to hearing loss in adults aged ≥ 65 years in the USA is estimated to reach $60 billion by 2030 [73].

The physiopathology of ARHL can include both peripheral and central factors. Age-related peripheral changes include degeneration of the mechanotransducing cochlear inner and outer hair cells (sensory presbycusis), reduced function within the stria vascularis (metabolic presbycusis), and degeneration of the auditory nerve (neural presbycusis), with most cases presenting a mix of them [73, 74]. Among age-related central auditory pathways, atrophy of the temporal lobe (auditory cortex) and brain gliosis are the main factors associated with ARHL, often concurrent with atherosclerosis, cardiovascular disease, smoking, and diabetes [75]. Environmental factors such as noise exposure and ototoxic medications can exacerbate the ARHL progression but can also independently cause hearing loss in individuals of any age [76]. Moreover, other lifestyle factors such as smoking habits, alcohol consumption, and high body mass index can influence the occurrence and/or progression of hearing loss [73].

The study of presbycusis in human cohorts, as with study of other senses, is challenging due to the populations heterogeneity in terms of demographics and most importantly lifestyle factors, which can bias the results and confound potential associations. Animal models have been instrumental in evaluating the pathogenesis and genetic factors associated with ARHL. Although no single model fully replicates all human ARHL characteristics, research on rodent models has significantly advanced our understanding of molecular and cellular determinants of cochlear aging.

The animal model most frequently used in ARHL research is the mouse [77]. Besides the benefits that come with their shorter lifespan and faster development of hearing loss, working with mice allows a strict control of intrinsic and extrinsic factors associated with ARHL, such as genetic background, diet, environment noise, and health status. For example, using different inbred mice strains, previous studies have identified more than 20 genetic loci that influence ARHL in laboratory. For example, the cadherin 23 (CDH23) gene was found to be responsible for encoding a component of the mechanoelectrical transduction in the hearing process [73]. However, while a mutation within the CDH23 gene was linked to progressive high-frequency hearing loss in mice, currently there is no convincing evidence associating variants in human CDH23 with ARHL, questioning the translation potential of such models [76]. Speaking to this, a review comparing 50 mouse and 20 human candidate genes that have been proposed to influence ARHL have shown a low concordance, with around one quarter of the proposed human ARHL genes overlapping with the proposed list for mice [78]. Given these limitations, studies with rodents have been expanded to gerbils and chinchillas. Studies with Mongolian gerbils (Meriones unguiculatus), for example, have identified an impairment in hearing sensitivity in older individuals due to decreased endocochlear potential, even without sensory hair cell nor neuron loss. This finding has led gerbils to become one of the main models in which to study metabolic presbycusis [79, 80]. Using the gerbil model, researchers have found that oxidative damage to mitochondria within the strial marginal cells causes reduced ATP production, which in turn reduces Na + ,K + ATPase activity, leading to a reduced EP and elevated auditory thresholds [81]. The long-tailed chinchilla (Chinchilla lanigera) is another model extensively used in hearing loss research due to its similarity in hearing frequency range and sensitivity when compared to humans, and its genetic heterogeneity compared to other rodent models [82, 83]. Chinchillas have a relatively long lifespan of 15–20 years in captivity, which could potentially limit their use for ARHL research. However, the ability to measure and correlate a wide range of anatomical, physiological, and behavioral effects resulting from various noise exposures within the same species has led to their widespread use as a model for noise-induced hearing loss [84]. Over the past years, studies using chinchillas as an animal model have provided new insights into pharmacological approaches for treatment and prevention, employing antioxidants, and other biologically active compounds and drugs with the goal of preventing or mitigating the effects of noise-induced trauma [84].

In the therapeutic field, cochlear implantation (CI) has evolved into a relatively low-risk procedure, contributing to advancements in speech understanding and enhancing the quality of life for individuals with severe ARHL [85]. Once again, rodent studies have led to great advances in developing the efficacy of device or pharmacological interventions aimed at improving hearing preservation [86, 87]. Rodent research has led to improved understanding of the process of hearing repair following trauma and has improved translational solutions for intracochlear drug delivery [88]. However, direct translation from rodent findings to humans is challenging, mainly due to anatomical differences in the cochlea [88]. In that sense, larger animal models may have advances when evaluating CI.

Although NHPs would be ideal candidates as CI models, their use in research is still limited mainly due to space and associated costs [89, 90]. Still, other larger animals have been evaluated to identify the most suitable human-like animal model for inner ear research. Cats, evaluated in the early 1950s, have been one of the predominant non-rodent animal models for studying electrical stimulation and drug delivery in the past decades [88, 91, 92]. Due to the similar dimension of their lower basal turn and their robustness, they were the predominant animal models for many early studies, but despite their great contributions to the knowledge of pathophysiology of presbycusis, their use has been decreasing over time [92]. Recent studies have expanded in scope to include larger animal models. Domestic sheep (Ovis aries) were shown to have cochleae larger than cats and comparable to humans and have demonstrated the near-complete insertion of certain clinical electrodes, enabling preclinical testing of new electrodes and insertion devices for humans [93, 94]. The miniature pig has also shown potential as an alternative large animal model, with full insertion of clinical electrodes, albeit with associated mechanical trauma [95].

In summary, while animal models have provided valuable insights into the pathophysiology and treatment of age-related hearing loss, ongoing research is essential to address the challenges of translating findings across species and to continue developing effective interventions. Smaller animals have been useful on understanding molecular processes associated with the hearing loss but large animal models can effectively evaluate the potential translation of research findings into new treatments and therapies in humans.

Olfaction

Introduction, anatomy, and physiological processes

The olfactory system serves a number of functions in various aspects of life, including food detection and selection, danger avoidance (i.e., predator-, food-, environmental- and microbial-borne hazards), and social communication [9698]. A well-functioning olfactory system enables the detection of suitable and nutritious food sources, while a compromised sense of smell can lead to diminished appetite and unintended weight loss [99]. Additionally, olfaction is vital for recognizing social cues, which can affect reproductive behaviors, territoriality, and social bonding [99, 100]. This system’s ability to perceive and differentiate complex odors is essential for survival, as it aids in avoiding spoiled or toxic food, detecting predators, and navigating environmental challenges [99, 100]. In humans, the olfactory system also contributes to emotional well-being and memory, further emphasizing its importance across a broad spectrum of physiological and psychological functions [99].

Olfaction is enabled by specialized receptors in the nasal cavity, connected neurologically to the brain. Olfactory receptors (ORs) expressed in the olfactory epithelium beneath the nose are able to detect millions of different odorant molecules [101, 102]. OR genes are the largest multigene family in mammals, responsible for the great diversity of receptors produced, although no direct association exists between OR number and olfactory acuity or sensitivity [103]. When ORs bind with a target odorant, a molecular chain is activated through olfactory sensory neurons, which transduces a signal into olfactory-processing brain areas in the olfactory bulb (OB). The OB is a multilayered structure contained in the central nervous system, part of the main olfactory system. This component serves as an intermediate component between the olfactory epithelium and the higher centers of the brain [104]. Most mammals, including humans, also possess an accessory olfactory system, composed of an accessory OB connected to an array of ORs expressed in the vomeronasal organ located above the palate on both sides of the nasal septum. There has been a debate over the functionality of the vomeronasal organ in some species formerly considered to be microsmatic, such as catarrhine primates and humans [105, 106].

Aging and age-related diseases in human olfaction and insights from animal models

Aging is generally accompanied by a decrease of olfactory abilities [107, 108], starting in the fifth decade of life in healthy humans [109]. Olfactory loss is reported in 14–22% of the population over 60 years old [110], and in up to 62–80% of people over 80 years of age [111]. Yet this decrease in olfactory abilities does not appear to be linear [112]; it seems to correspond to different olfactory phenotypes [113] and may be influenced by the cumulative environmental exposures encountered through life [6, 114].

Olfactory loss in the older population derives from a general decrease of the functions of the peripheral and central nervous system associated with the natural process of aging. This involves a decrease in the number of sensory neurons owing to changes in cell functions and environmental determinants [115], and corresponding decline in the volume of olfactory-processing brain areas and in the number of ORs [105, 116, 117]. The decrease in the ability to detect and discriminate odors in the older population is generally not lethal yet may have important repercussions on the quality of life. It may impact nutrition [118], and general health and well-being. The loss of the sense of smell is linked to various individual inherent vulnerabilities (e.g., genetic, cardiovascular, metabolic, and neurological disorders) and risk factors accumulated through life (e.g., chronic sinonasal diseases, past surgeries, smoking habits, pharmacological and alcohol consumption, exposure to pollutants), and general quality of life [107, 119, 120]. In particular, the association between olfactory loss and neurodegenerative diseases has recently gained attention [117, 121]. Olfactory loss has notably affected 90% of patients with Alzheimer’s disease, and 96% of patients with Parkinson’s disease [105]. Signs of olfactory dysfunction could serve as reliable clinical markers for early stages of these diseases, and smell tests are being developed for use in clinical settings [122124].

Animal models are proving useful for furthering our understanding of the morphological, neurological, and genetic changes of the olfactory system with age and their impact on olfactory acuity, although few taxa are so far represented in the literature [13, 116]. Rodents (mice and rats), dogs, and some NHP taxa (mainly strepsirrhines such as mouse lemurs, and platyrrhines such as marmosets) constitute the core of the existing research on the sense of smell in relation to aging. These models have the advantage of providing a range of neurophysiological and behavioral studies of the olfactory system. For instance, a number of experimental studies have investigated age-related deficits in olfactory discrimination in laboratory rats, with differing results. Some studies have found intact olfactory discrimination abilities in older individuals [125, 126], while others report an age-related decline [127129], yet some only for discrimination tasks that involved perceptually similar olfactory stimuli [130], a result also shared by a study on laboratory mice [131]. The divergent results may reflect variation in the nature of the behavioral tests and the stimuli that are employed. Electrophysiological analyses on mice models have further explored the effects of aging on the OB neural circuits. Several studies found evidence of alterations of the OB neural network with age, not in OB volume but at the level of afferent synaptic inputs [132134]. A closer look into the neurophysiology of aging in these rodent models shows that environmental factors appear to be the main cause of the deterioration of the olfactory system. For example, Loo et al. showed that in aged rats, the posterior zone of the olfactory epithelium is well preserved, while the anterior part, which is in contact with the environment, is deteriorated [135]. In addition, olfactory neurogenesis appears reduced in aged mice [131] and rats [136]. In addition, a number of studies point towards olfactory dysfunction as an early biomarker of aging [137, 138], although more research on aging rodent models is necessary to establish patterns of mechanisms and functions. Of particular interest for the human clinical domain, research on rodent models is further exploring the relationship between olfactory dysfunction and neurodegenerative diseases, such as Alzheimer’s disease [139, 140] and Parkinson’s disease [141], potentially opening the way to preclinical assessments of therapeutic targets [142, 143].

Dogs are characterized as super-smellers and have been used extensively in chemical and biological odor detection tasks [144, 145]. A significant effort has been deployed to the study of dogs’ olfactory system and their olfactory dysfunctions, with the aim to optimize the usefulness of this species in olfactory detection research [145147]. A combination of neurophysiological studies [148] and behavioral tests [149, 150] on these companion animals, and questionnaires directed at dog owners [151], are providing an interesting pool of knowledge on the canine olfactory system and associated diseases and dysfunctions, notably in relation to aging [148, 152]. Although the olfactory system of dogs differs to that of humans, canine olfaction research can participate in filling the gap of knowledge in sensory dysfunction in our own species.

While rodents provide valuable insights into the basic mechanisms of olfaction, their reliance on the vomeronasal organ and their more acute sense of smell make them less directly comparable to humans. Dogs are valuable for studying olfactory-driven behaviors and the detection of specific odors, but their olfactory capabilities with larger OBs and higher amount of ORs far exceed those of humans. NPHs offer a closer approximation to the human olfactory system, particularly in studies focused on how smell is processed in the brain and how it interacts with other senses. As our closest relatives, NHPs have a relatively similar olfactory system to ours, and seem to experience comparable aging effects [13, 153]. The largest body of research on olfaction and aging using primate models stems from a few laboratory populations of mouse lemurs (Microcebus spp) [154]. Aujard and Némoz-Bertholet assessed the decline with age in olfactory behavior responsiveness in male gray mouse lemurs (M. murinus) [155]. They measured the physiological response of males to urine odors of pre-estrous females, and found that aged individuals lacked the typical increase in testosterone level primed by the exposure to female odors. Cayetanot et al. further investigated the effect of aging on the central response to odor stimulation in M. murinus by measuring the expression of c-fos, a gene involved in rapid cell proliferation and differentiation after extracellular stimuli, in the olfactory bulbs of adult and aged males following stimulation by female urine odors [156]. They found an increase in the gene expression in adult, but not in aged, males. Collectively, these studies suggest a direct link between the decrease in behavioral discrimination and the impairment of the olfactory system with age in this primate model. The authors also compared detection thresholds of repellent solution in food with age and found that younger mouse lemurs were more sensitive to the repellent solution, avoiding the spiked food more readily than their older counterparts [155]. However, another study on the same model species failed to find such a pronounced age effect in a series of olfactory discrimination tasks [157]. A similar observation was made by Golub et al., who found no evidence for age-related decrease in olfactory discrimination ability in common marmosets (Callithrix jacchus) [158].

The continued exploration of aging effects on the olfactory system from diverse animal models, particularly aged NHPs, is essential for bridging the gap between basic research and clinical applications. Future studies should aim to refine these models, improve our understanding of olfactory aging mechanisms, and translate these findings into practical interventions for enhancing the quality of life for individuals affected by olfactory impairments.

Taste

Introduction, anatomy, and physiological processes

The sense of taste is essential for evaluating food quality, detecting potential toxins, and maintaining electrolyte balance. Taste perception plays a crucial role in daily life by guiding food selection and contributing to the overall enjoyment of eating. Taste can be divided into distinct modalities, including sweet, bitter, umami (savory), salty, sour, and oleogustus (fat), which together help identify flavors that indicate nutritional value and safety, thus influencing dietary choices and ensuring proper nutrient intake.

In mammals, taste is achieved via taste cells located in taste buds on the tongue and palate. Each taste bud contains four major types of taste cells (types I–IV), which exhibit continuous cell turnover in healthy adults every 8–22 days, depending on cell type [159, 160]. Types II and III are primarily involved in taste sensation and contain chemoreceptors for different taste modalities [159, 161, 162]. The receptors for sweetness (T1R2 + T1R3 heterodimer), umami (T1R1 + T1R3 heterodimer), bitter (T2Rs), and sour (OTOP1) have been clearly established [163167], while the salty taste receptors are less well understood in humans [168171]. In general, most type II and III cells are tuned to a single modality; however, multiple types of receptors of the same modality can be coexpressed in a single cell (e.g., different types of bitter T2Rs) [162, 168]. In addition to the taste receptor-containing cells, type I cells have a primarily supportive role, and basal type IV cells eventually differentiate into mature taste cells [159, 161, 162]. The taste buds are clustered in three types of gustatory papillae: circumvallate (large circular structures arranged in a V shape) [172, 173]; foliate (vertical folds on the lateral tongue) [173]; and fungiform (small mushroom-shaped structures scattered across the dorsal surface) [174]. In adults, the density of fungiform papillae is highly variable [174179]. Each fungiform papilla typically houses ~ 3–6 taste buds [175, 177, 179, 180] and its density has been linked with detection thresholds for multiple taste modalities, including sweet, bitter, salty, sour, and the “fat” tasteoleogustus [176, 181184].

Aging and age-related diseases in human taste and insights from animal models

There is clear evidence of age-related decline in taste across at least some human populations [185, 186], which can contribute to negative health outcomes, such as anorexia of aging [187, 188]. Taste impairment is often defined clinically as failing to correctly identify specific taste modalities when presented at suprathreshold concentrations [189191]. Using this approach, the incidence of taste impairment in older adults ranges from 17.3% (40–70 + years old [191]) to 48% (57–85 years old [190]) depending on age range and criteria used. Taste detection thresholds and recognition thresholds are higher in older individuals (indicating decreased sensitivity), although the degree of impairment varies between different taste modalities and between different tastants within a modality [185, 186]. Overall, Schiffman found that the average loss of threshold level across taste compounds and modalities is 4.7—meaning that older individuals (over 65 years old) require 4.7 times more of a tastant present to detect or recognize it compared to younger individuals [186]. A number of factors have been linked to age-related taste decline. Medications, for example, can impact taste function, and medication use is particularly common in older individuals [186, 192]. Impaired or altered taste function is associated with diseases (including cancer, oral diseases like dental caries, and periodontal infections) which are more prevalent in older individuals [186, 193]. However, taste function is impaired in older individuals even in the absence of medication use and disease, suggesting that other anatomical or physiological mechanisms contribute to age-related declines in taste.

There are observed age-related changes in human oral anatomy that may contribute to declining taste function. Both longitudinal and cross-sectional studies indicate that fungiform papillae density decreases with increasing age [174, 176, 177, 184]. There is also evidence of reduced fungiform papilla vascularization and deteriorating papilla shape in older individuals [176]. In contrast, results are mixed on whether the number of taste buds declines with age, depending on methodology and papillae investigated. Some studies have reported no significant age-related differences in the number of taste buds in fungiform papillae [180, 194, 195], while others have found decreased taste bud size and/or density in circumvallate and foliate papillae [196198]. Additionally, the composition and quantity of saliva can impact taste and has also been found to change with increasing age [199202]. Similarly, recent work suggests that the composition of the oral microbiome, which varies with age [203], may also influence taste [204].

Animal models have been critical for investigating potential physiological mechanisms, as molecular and functional studies of human taste cells are rare [201]. Ecologically, the different taste modalities are involved in evaluating food quality (sweet, umami, fat), avoiding toxins and spoilage (bitter, sour), and maintaining electrolyte balance (salty). Taste is a phylogenetically old sense, and human taste is similar in many aspects to that of other mammals [188, 205, 206]. Primates, rodents, carnivorans, and suids all possess three types of gustatory papillae (fungiform, circumvallate, foliate) and developed salivary glands [205, 207]. The most common animal models for human taste (i.e., mice, rats and NHP) share major taste receptor types with humans [163, 164, 206, 208211]. There is also growing interest in the use of pigs as biomedical models, including for aging research [212, 213]. Like rodents and NHP, pigs exhibit the major taste receptor types [214, 215]. They have not yet been used in any study of aging and taste physiology, but may be a promising model for future development.

Laboratory mice and rats have been the most frequently used model in studies investigating age-related changes in taste physiology. In both species, taste thresholds tend to increase with increasing age (as in humans), although effects vary between taste modalities and studies [216218]. However, results are currently mixed regarding the extent of age-related changes in gustatory anatomy and physiology in both species. Researchers have expressed concern over comparing results across studies using different rodent strains or species [218, 219], particularly given evidence of strain-related differences in taste preferences and sensitivities [220222]. Another potentially confounding factor is that studies differ in how they categorize “aged”/ “elderly” animals. For example, in rats, “aged” has been variably categorized as 14–16 months [217, 219], 23–28 months [219, 223, 224], or 28–32 months old [225227]. These differences in age categorization could impact study results—in one study, for example, there were no differences in gustatory anatomy and physiology between 5-month-old and 17-month-old rats, but there were significant differences in several metrics between 5-month-old and 30-month-old rats [227]. Overall, the picture emerging from rodent models suggests that a number of physiological mechanisms may be contributing to age-related declines in taste, including deteriorating papilla morphology, decreased taste bud size and density, reduced epithelial tissue thickness, reduced number of taste cells (including specific taste receptor types), decreased expression of signaling molecules and hormones (e.g., α-gustducin, GLP-1, ghrelin), and changes in serum components [216219, 223229].

Studies of aging and taste using NHP models have been much more limited compared to rodent models, and to date have been anatomical in nature. Bradley and colleagues, for example, investigated gustatory papillae and taste buds in 15 rhesus macaques across 5 age points (4, 8, 13, 24, and 31 years) [230]. They found no significant age effects on the number of taste buds per papillae, number of taste buds total per papillae group, or papilla size for any of the three gustatory papillae types. While they did find that the total number of fungiform papillae decreased in older monkeys, they attributed their results to the fact that most of the older monkeys were missing the entire tongue tip due to trauma [230]. Yamaguchi and colleagues found changes in gustatory anatomy across common marmosets. Although they had a limited sample size (seven monkeys, one per age category), they found that the number of taste buds in each type of gustatory papillae declined after 2 months old, and the percent of taste buds with taste pores tended to decrease in older animals [231]. Together, these results suggest that there likely are age-related changes in gustatory anatomy in NHPs, but more research is needed.

Although these model animals share many aspects of taste with humans, they also differ from humans in other important aspects. For example, there is substantial interspecific variation in the chemical space of compounds activating different taste receptors. Whereas human umami receptors (T1R1 + T1R3) are narrowly tuned to l-glutamate and l-aspartate, the most commonly used animal models (rodents, pigs, neotropical NHPs) have broadly tuned umami receptors that respond to a range of compounds [163, 215, 232], which may influence studies investigating age-related changes in receptor sensitivity. It is important to note that macaques, like humans, have umami receptors narrowly tuned to l-glutamate and l-aspartate [233]. Humans and model species similarly differ in their sensitivity to artificial sweeteners and sweet proteins [164, 215, 232, 234] and bitter compounds [210, 235]. Low serum sodium levels have been linked with fall risk in the elderly [236], suggesting that studies investigating aging effects on the anatomy and physiology of salt taste may be particularly relevant to quality of life. However, current evidence also suggests that the pathways for low concentration (non-aversive) sodium detection may differ between rodents and humans [171, 201]. Further, humans (and NHPs) differ from rodent models in the numbers of different gustatory papillae, numbers of taste buds, and potentially their innervation and/or development [231]. For instance, while humans have 3–12 circumvallate papillae and macaques have 4–6, rodents have a single circumvallate papilla on the posterior tongue. These distinctions could potentially differentially impact aging effects on papilla anatomy. For example, rodent studies have found that the single circumvallate papilla significantly increases in size in aged rats [223, 229]; a similar effect on circumvallate papilla diameter has not been observed in aged humans [172, 198].

Thus, while animal models are critical for investigating the anatomy and physiology of age-related taste decline, current work highlights the importance of selecting appropriate models for the gustatory physiology and anatomy questions being explored.

Somatosensation (touch)

Introduction, anatomy, and physiological processes

Somatosensation plays a critical role in providing feedback about the external environment and internal body state, contributing to the regulation of motor functions, spatial awareness, and protective responses [190, 237]. The diverse types of somatosensory receptors and their specific functions ensure a comprehensive detection and interpretation of various physical stimuli, essential for maintaining bodily integrity and interacting effectively with the environment.

Somatosensation is achieved via specialized receptors located in either the skin (touch, temperature, pain) or muscles and tendons (proprioception) [237]. In the skin, temperature and pain are detected via unmyelinated free nerve endings from thermoreceptors and nocioceptors, respectively, whereas mechanical stimuli are detected via specialized sensory end organs (mechanoreceptors) innervated by myelinated nerve fibers [238]. Glabrous (non-hairy) skin is specialized for discriminative touch, and contains four types of mechanoreceptors that respond to different kinds of mechanical stimuli: Meissner corpuscles (low-frequency vibrations and movement across skin), Pacinian corpuscles (high-frequency vibrations), Ruffini corpuscles (stretch), and Merkel cells (tactile acuity) [238, 239]. By contrast, proprioceptors are embedded in muscles (muscle spindles) or located at the muscle–tendon junction (Golgi tendon organs), and detect muscle movement and tension, respectively [240]. When a stimulus activates a somatosensory receptor, it triggers the transduction process that converts the physical stimulus into electrical signals, which travel along the peripheral nerves to cell bodies in the dorsal root ganglia in the spinal cord. The conduction speed of these peripheral nerves depends on their axonal cross-sectional diameter and degree of myelination [238, 241].

Aging and age-related diseases in human somatosensation and insights from animal models

Age-related declines in function have also been reported for the somatosensory system, which is responsible for detecting cutaneous touch, limb movement (proprioception), temperature, and pain [213]. Overall, the incidence of somatosensory impairment is high, with studies showing up to 70% of surveyed Americans (57–85 years old) with diminished touch sensitivity [190]. Impaired somatosensory function can lead to serious health issues in the elderly population. For example, cutaneous precision touch and proprioception in the leg and foot are critical for postural stability and balance control—impairment in these senses can increase falling risk [242245]. Older adults may also be at increased risk for bruising, burns, or other injuries due to reduced sensitivity to pain, heat, and cold, particularly in peripheral regions like the hands and feet [246, 247]. In general, adults of advanced age exhibit higher detection thresholds for light touch, vibration, temperature, and pain stimuli, lower tactile spatial acuity and discrimination abilities, and impaired joint position sense compared to young adults [242, 247254]. These age-related declines are much higher in more peripheral regions (e.g., hands, feet) compared to more central regions like the trunk or face [248250]. It is estimated that tactile acuity in the fingertips decreases 130% between young adulthood (18–28 years) and elderhood (65–87 years), resulting in a decrease of about 1% per year [248255]. Stevens and Choo [248] observed an even greater decline in the plantar foot, with a 400% decrease in tactile acuity in the big toe. By contrast, only ~ 50% decrease was observed in tactile acuity in the lips across the same time period [248]. Diseases such as diabetes mellitus, which causes peripheral neuropathy, can exacerbate these age-related somatosensory declines [256]. Interestingly, however, several studies have found that engaging in intensive tactile experiences can mediate or eliminate age-related declines in tactile acuity. Work by Legge and colleagues (2008, 2019), for example, found that blind individuals and pianists show no age-related differences in an active touch acuity, in contrast to sighted control individuals [255, 257].

Several functional mechanisms have been proposed to explain age-related declines in the different kinds of somatosensory function, including changes in (1) the morphology and/or density of receptors; (2) the density and/or conduction velocity of nerves; (3) the synthesis, transport, and/or action of neurotransmitters; (4) the elasticity and structure of skin; (5) vascular supply to the skin; and (6) changes in higher processing systems in the brain [250, 254, 258260]. The nerves innervating the different types of somatosensory receptors also vary in structural properties, including axonal diameter, degree of myelination, and nerve conduction velocity [238, 241], which could influence differential aging effects between modalities.

While human participant experiments and donor tissue have been frequently used to investigate aging effects on gross receptor morphology, and receptor and nerve densities [250, 261], animal models have been critical for understanding changes in somatosensory function and physiology [254, 260]. Here, we focus on the use of animal models to study aging on cutaneous touch and proprioception. In general, cutaneous mechanoreceptors appear relatively conserved across mammals, with the same general distinct mechanoreceptor types found in either glabrous (non-hairy) or hairy skin which respond to different kinds of mechanical stimulation (e.g., texture, vibration, pressure, shape, stroking) [239, 262]. Because of this conserved nature, rodent models have been particularly crucial in studies investigating the molecular mechanisms involved in touch transduction [263265]. Knock-out and transgenic mouse models can offer important experimentally based insight into effects of aging on somatosensation in both healthy and disease conditions [260, 266, 267].

Mice and rats are the most common animal model in studies of aging and cutaneous touch [260]. For example, studies have reported changes in mechanoreceptor morphology and density, declines in peripheral nerve conduction velocity, decreases in the density of myelinated nerves innervating the skin, damage to myelin integrity, and changes in dorsal root ganglia neurons with increasing age in mice [266, 268270]. Vaughan and colleagues found similar loss of proprioceptive sensory axons in muscles in both the forelimb and hindlimb, and a reduction in the number of proprioceptive sensory neurons in the dorsal root ganglia of old mice compared to young mice [271]. Aging effects have also been observed in rats, including in proprioception receptors, cutaneous touch sensitivity, and in the somatosensory cortex [272, 273]. Interestingly, one study found that while the representation of the forepaw in the somatosensory cortical map generally was smaller in senescent rats relative to young adults, this difference was less pronounced in animals living in tactilely enriched cages [273], which is similar to the preservation of tactile acuity observed in aged braille readers and pianists [255, 257].

NHP models for aging and somatosensation have been very limited. In one of the few studies performed, Paré and colleagues compared cutaneous innervation (including free nerve endings, Merkel cells, Meissner corpuscles, and Pacinian corpuscles) in the skin of healthy and diabetic rhesus macaques across adult and aged individuals (4–39.9 years old) [274]. Overall, they found decreased levels of innervation, and reduced numbers of tactile mechanoreceptors such as Merkel cells and Meissner corpuscles in older monkeys. These effects were exacerbated in diabetic monkeys, which also were characterized by more abnormal morphology and innervation characteristics [274].

However, there are some aspects of human touch and proprioception that are derived compared to that of commonly used animal models. While anthropoid primates share an evolutionary history of increased emphasis on manual grasping, dexterity, and manual exploration, rodents often explore the environment using their vibrissae. These divergent emphases are reflected in differences in the somatosensory system. For example, the fingers and glabrous skin of the hand make up a disproportionate part of the primary somatosensory cortex in NHPs, while vibrissae are overrepresented in rodent somatosensory maps. Humans and other anthropoids also have more complex Meissner corpuscles and at higher densities in the glabrous skin of the hand compared to rodents or cats [241, 275, 276]. This increase in complexity has led some researchers to differentiate the receptors found in human and NHP glabrous skin as “Meissner corpuscles” and the receptors in other mammals as “Meissner-like corpuscles” [241, 275]. Most studies have focused only on Meissner corpuscles in a comparative context, so it is unclear whether there are similar differences between NHPs and other model animals in the anatomy and/or density of other somatosensory receptors.

Additionally, it is important to note that humans differ from other primates in some aspects of their somatosensory system. As the only obligate bipedal primate, humans have derived foot (e.g., abducted hallux) and vertebral morphology, and elongated hind limbs, and are faced with unique balance challenges compared to other species [277], all of which may affect how aging impacts somatosensation in the lower limb. This transition to bipedality is reflected by differences in representation of the hallux in the somatosensory cortex between humans and other primates [278]. There is some evidence for variation between humans and other primates in mechanoreceptor innervation patterns. For example, one study found that in humans each Meissner corpuscle is innervated by a single axon while macaque Meissner corpuscles can be innervated by multiple axons [275].

Overall, animal models are particularly important for understanding how aging affects somatosensory function and physiology. Research on rodents, in particular, has provided numerous insights into age effects on peripheral nerve myelination and conduction velocity, axon densities, and dorsal root ganglia neurons [266, 268271]. Their relatively short lifespans also permit experimental manipulations to identify factors that may reduce age-related somatosensory declines, such as the use of tactilely-enriched cages [273]. However, it is important to recognize that rodent somatosensation is in some ways inherently different from human somatosensation. Primates have experienced a long evolutionary history of prioritizing somatosensation in the hands that may impact how aging affects this system in humans. In that sense, the investigation of NHPs as models for some aspects of somatosensory research is especially promising.

Future directions

Aging affects our senses, with pervasive repercussions for health and well-being. Studies of animal models are improving our understanding of age-related sensory dysfunctions, with particularly important contributions from research on rodent and NHP models. Important advances in the last few decades include the use of molecular technologies to better characterize disease profiles, the development of models that better reflect human physiopathology, the integration of various areas of study within individual subjects, and the overall improvement in the translational potential of research conducted with animal models [14]. For example, the swift progress in technical developments in genetics are providing researchers with increasingly advanced tools applicable to disease and aging research. Whole-genome and whole-exome sequencing can investigate and identify variants that help to identify specific disease-causing risk factors [61]. With this information, genetic engineering with CRISPR is being employed to select or induce animal models with disease profiles more closely resembling those features observed in human pathology [279].

A number of aspects of sensory research still need further development, for which animal models are likely to be highly valuable. First, there is a need for more integrative, multimodal research across the senses. At present, each sense is often studied individually, both at human clinical level and when using animal models in laboratory settings [103]. In addition, sensory research would benefit from becoming more integrative across disciplines. Moreover, it is necessary to conduct more long-term studies spanning multiple generations, including on species with longer life spans, and the necessary development of less invasive methods and improved analytical methods that will facilitate this goal.

While studies with animals in laboratory settings offer several advantages, such as a controlled environment, social interactions, diet, safety, and precise control of confounding factors, the natural occurrence and progression of disease or normal aging processes can be biased due to the unnatural conditions in captivity. Moreover, the natural history of the disease and the response to treatment might differ between naturally occurring disease cases and those induced by external factors. For example, the progression of age-related hearing impairment might differ in a controlled noise laboratory environment versus the natural habitat of the study subject. Similarly, visual impairment resulting from a case of glaucoma induced by laser or surgical procedures might differ from the one resulting from a naturally occurring disease with intrinsic causes. As another example, captive environments are often less bright than natural conditions. Lack of exposure to sunlight during postnatal visual development, for example, is associated with increased visual impairment in human children and young animals [280, 281]. Conversely, greater sunlight exposure in adulthood has been linked to an increased risk of eye disorders, including age-related macular degeneration and diabetic retinopathy [282284], which suggests that free-ranging animals may also more accurately model the incidence and physiology of some age-related sensory diseases. The range of topographic, tactile, tastant, and odorant stimuli also differ in captive environments. Taken together, animals from free-ranging/natural populations that were raised in and experience naturalistic environments and sensory stimuli may also offer opportunities for studying both healthy and diseased sensory function and aging [285].

Studies conducted on free-ranging populations with naturally occurring diseases have been increasing in recent years. Populations such as the Cayo Santiago rhesus macaque colony in Puerto Rico, which exhibit naturally occurring age-related variation in all sensory systems studied to date, have provided valuable insights into several aspects associated with health, disease, and behavior [9, 15, 39, 286]. For many conditions, however, a population of individuals with naturally occurring and relevant variation might not be readily available. In situations like this, choosing the animal model for the specific age-related condition as well as taking steps to replicate the appropriate environment are anticipated to enhance the translational relevance of the findings to human health.

Finally, the use of animal models for biomedical research is a polemic and complex topic with many important ethical and financial considerations [88]. Worldwide, governmental bodies and institutional review boards have enacted legislation and ethical approval processes to review and oversee animal-based research studies [17, 287]. As participation of animals in research progresses, there is a crucial emphasis on adhering to the “three R’s of animal research: Reduce, Refine, and Replace” [288]. This principle underscores the importance of minimizing the number of animals used, refining experimental procedures to enhance animal welfare, and ultimately striving to replace animal subjects with alternative methods. It is imperative that animals are not subjected to research unnecessarily, that protocols are in place to minimize pain and suffering, and that data obtained from trials are neither wasted nor misrepresented. The ethical use of animals should prioritize minimizing their numbers and embracing alternatives whenever possible [17, 287, 288]. While the knowledge advances through the use of animal models are undeniable, researchers should conduct research ethically and conscientiously.

Conclusions

The use of animal models in biomedical research focused on age-related sensory loss has been instrumental in advancing our understanding of the intricate biological processes underlying health and disease. Research in sensory systems is a rapidly evolving field, offering exciting opportunities to unravel the complexities of how we perceive and interact with the world around us. This research not only sheds light on the fundamental mechanisms of sensory function but also drives the development of innovative diagnostic tools, therapeutic strategies, and medical interventions aimed at mitigating sensory decline in aging populations. Smaller animal models such as rodents have proven invaluable for exploring the molecular and cellular aspects of sensory processing and disease, providing insights that are essential for drug development and safety testing. Larger animals such as non-human primates, with their closer anatomical and physiological similarities to humans, offer distinct advantages in translating research findings into clinical applications. Animal models are particularly crucial for bridging the gap between basic research and practical healthcare solutions, enabling the development of novel treatments that can improve quality of life for individuals experiencing sensory impairments. As the field continues to evolve, it is imperative that research involving animal models adheres to the highest ethical standards, which includes not only following established guidelines for the humane treatment of animals but also embracing a commitment to refining research methodologies. By doing so, we can ensure that the use of animal models remains both ethical and scientifically meaningful, ultimately contributing to the betterment of human health and well-being.

Acknowledgements

This research was supported by the Natural Sciences and Engineering Research Council of Canada (RGPIN-2017-03782), Canada Research Chairs Program (950-231257), The New Frontiers in Research Fund (NFRFE-2018-02159), and the National Institutes of Health (R61-AG078529). Additional support was provided by the University of Calgary Eyes High program. The authors would also like to thank Dr. Marcela Cypel for her valuable input on the medical content of this manuscript.

Data Availability

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Declarations

Competing interests

The authors declare no competing interests.

Footnotes

Publisher's Note

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Contributor Information

Arthur G. Fernandes, Email: arthur.fernandes@ucalgary.ca

Amanda D. Melin, Email: amanda.melin@ucalgary.ca

References

  • 1.World Health Organization. Ageing and health. WHO 2022. https://www.who.int/news-room/fact-sheets/detail/ageing-and-health. Accessed 20 Apr 2024.
  • 2.Crimmins EM. Lifespan and healthspan: past, present, and promise. Gerontologist. 2015;55:901–11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Partridge L, Deelen J, Slagboom PE. Facing up to the global challenges of ageing. Nature. 2018;561:45–56. [DOI] [PubMed] [Google Scholar]
  • 4.World Health Organization. Global Health Estimates: Life expectancy and healthy life expectancy. WHO 2020. https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-life-expectancy-and-healthy-life-expectancy Accessed 05 Apr 2024.
  • 5.Cavazzana A, Röhrborn A, Garthus-Niegel S, Larsson M, Hummel T, Croy I. Sensory-specific impairment among older people. An investigation using both sensory thresholds and subjective measures across the five senses. PLoS One. 2018;13(8):e0202969. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Hoover KC. Sensory disruption and sensory inequities in the Anthropocene. Evol Anthropol. 2021;30(2):128–40. [DOI] [PubMed] [Google Scholar]
  • 7.Cacchione PZ. World Health Organization Leads the 2021 to 2030-Decade of Healthy Ageing. Clin Nurs Res. 2022;31:3–4. [DOI] [PubMed] [Google Scholar]
  • 8.Pan American Health Organization. Salud visual y auditive de las personas mayores en la Región de las Américas. PAHO 2023. https://iris.paho.org/handle/10665.2/57338. Accessed 05 Apr 2024.
  • 9.Siracusa ER, Higham JP, Snyder-Mackler N, Brent LJN. Social ageing: exploring the drivers of late-life changes in social behaviour in mammals. Biol Lett. 2022;18(3):20210643. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Coroneo M. Ultraviolet radiation and the anterior eye. Eye Contact Lens. 2011;37(4):214–24. [DOI] [PubMed] [Google Scholar]
  • 11.Ding T, Yan A, Liu K. What is noise-induced hearing loss? Br J Hosp Med (Lond). 2019;80(9):525–9. [DOI] [PubMed] [Google Scholar]
  • 12.Zhang Z, Rowan NR, Pinto JM, et al. Exposure to particulate matter air pollution and anosmia. JAMA Netw Open. 2021;4(5): e2111606. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Verdier JM, Acquatella I, Lautier C, et al. Lessons from the analysis of nonhuman primates for understanding human aging and neurodegenerative diseases. Front Neurosci. 2015;9:64. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Colman RJ. Non-human primates as a model for aging. Biochim Biophys Acta Mol Basis Dis. 2018;1864(9 Pt A):2733–41. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Chiou KL, Montague MJ, Goldman EA, et al. Rhesus macaques as a tractable physiological model of human ageing. Philos Trans R Soc Lond B Biol Sci. 1811;2020(375):20190612. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Mukherjee P, Roy S, Ghosh D, Nandi SK. Role of animal models in biomedical research: a review. Lab Anim Res. 2022;38(1):18. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Andersen ML, Winter LMF. Animal models in biological and biomedical research - experimental and ethical concerns. An Acad Bras Ciênc. 2017;91(suppl 1): e20170238. [DOI] [PubMed] [Google Scholar]
  • 18.Hommes C, Ambrose A, Vega E, Martinez R. Four reasons for adopting a life course approach to health in the COVID-19 era and beyond. Rev Panam Salud Publica. 2022;46: e182. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Swenor BK, Lee MJ, Varadaraj V, Whitson HE, Ramulu PY. Aging with vision loss: a framework for assessing the impact of visual impairment on older adults. Gerontologist. 2020;60:989–95. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Zhang JH, Ramke J, Jan C, et al. Advancing the sustainable development goals through improving eye health: a scoping review. Lancet Planet Health. 2022;6:e270–80. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Marques AP, Ramke J, Cairns J, et al. The economics of vision impairment and its leading causes: A systematic review. EClinicalMedicine. 2022;46: 101354. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Assi L, Chamseddine F, Ibrahim P, et al. A global assessment of eye health and quality of life: a systematic review of systematic reviews. JAMA Ophthalmol. 2021;139(5):526–41. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Purola P, Koskinen S, Uusitalo H. Impact of vision on generic health-related quality of life - A systematic review. Acta Ophthalmol. 2023;101(7):717–28. [DOI] [PubMed] [Google Scholar]
  • 24.GBD 2019 Blindness and Vision Impairment Collaborators, Vision Loss Expert Group of the Global Burden of Disease Study. Trends in prevalence of blindness and distance and near vision impairment over 30 years: an analysis for the Global Burden of Disease Study. Lancet Glob Health. 2021;9:e130–43. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Prasad S, Galetta SL. Anatomy and physiology of the afferent visual system. Handb Clin Neurol. 2011;102:3–19. [DOI] [PubMed] [Google Scholar]
  • 26.Celesia GG, DeMarco PJ Jr. Anatomy and physiology of the visual system. J Clin Neurophysiol. 1994;11(5):482–92. [DOI] [PubMed] [Google Scholar]
  • 27.GBD 2017 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2018;392:1789–858. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.GBD 2019 Blindness and Vision Impairment Collaborators, Vision Loss Expert Group of the Global Burden of Disease Study. Causes of blindness and vision impairment in 2020 and trends over 30 years, and prevalence of avoidable blindness in relation to VISION 2020: the Right to Sight: an analysis for the Global Burden of Disease Study. Lancet Glob Health. 2021;9:e144–60. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Del Amo EM, Urtti A. Rabbit as an animal model for intravitreal pharmacokinetics: clinical predictability and quality of the published data. Exp Eye Res. 2015;137(111–485):24. [DOI] [PubMed] [Google Scholar]
  • 30.Pang IH, Clark AF. Inducible rodent models of glaucoma. Prog Retin Eye Res. 2020;75: 100799. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Wyman M, Ketring K. Congenital glaucoma in the basset hound: a biologic model. Trans Sect Ophthalmol Am Acad Ophthalmol Otolaryngol. 1976;81(4 Pt 1):OP645-52. [PubMed] [Google Scholar]
  • 32.Lai AK, Lo AC. Animal models of diabetic retinopathy: summary and comparison. J Diabetes Res. 2013;2013: 106594. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Olivares AM, Althoff K, Chen GF, et al. Animal models of diabetic retinopathy. Curr Diab Rep. 2017;17(10):93. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Kostic C, Arsenijevic Y. Animal modelling for inherited central vision loss. J Pathol. 2016;238(2):300–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Wisely CE, Sayed JA, Tamez H, et al. The chick eye in vision research: an excellent model for the study of ocular disease. Prog Retin Eye Res. 2017;61:72–97. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Picaud S, Dalkara D, Marazova K, Goureau O, Roska B, Sahel JA. The primate model for understanding and restoring vision. Proc Natl Acad Sci U S A. 2019;116(52):26280–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Burgoyne CF. The non-human primate experimental glaucoma model. Exp Eye Res. 2015;141:57–73. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Moshiri A, Chen R, Kim S, et al. A nonhuman primate model of inherited retinal disease. J Clin Invest. 2019;129(2):863–74. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Fernandes AG, Alexopoulos P, Burgos-Rodriguez A, et al. Age-related differences in ocular features of a naturalistic free-ranging population of Rhesus Macaques. Invest Ophthalmol Vis Sci. 2023;64(7):3. [DOI] [PMC free article] [PubMed]
  • 40.Lin KH, Tran T, Kim S, et al. Age-related changes in the rhesus macaque eye. Exp Eye Res. 2021;212: 108754. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Asbell PA, Dualan I, Mindel J, Brocks D, Ahmad M, Epstein S. Age-related cataract. Lancet. 2005;365(9459):599–609. [DOI] [PubMed] [Google Scholar]
  • 42.Schmitt C, Hockwin O. The mechanisms of cataract formation. J Inherit Metab Dis. 1990;13(4):501–8. [DOI] [PubMed] [Google Scholar]
  • 43.Zhang K, Zhu X, Lu Y. The proteome of cataract markers: focus on crystallins. Adv Clin Chem. 2018;86:179–210. [DOI] [PubMed] [Google Scholar]
  • 44.Rossi T, Romano MR, Iannetta D, Romano V, Gualdi L, D’Agostino I, Ripandelli G. Cataract surgery practice patterns worldwide: a survey. BMJ Open Ophthalmol. 2021;6(1): e000464. 10.1136/bmjophth-2020-000464. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Zhao L, Chen XJ, Zhu J, et al. Lanosterol reverses protein aggregation in cataracts. Nature. 2015;523(7562):607–11. [DOI] [PubMed] [Google Scholar]
  • 46.Maddirala Y, Tobwala S, Karacal H, Ercal N. Prevention and reversal of selenite-induced cataracts by N-acetylcysteine amide in Wistar rats. BMC Ophthalmol. 2017;17(1):54. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Lim V, Schneider E, Wu H, Pang IH. Cataract preventive role of isolated phytoconstituents: findings from a decade of research. Nutrients. 2018;10(11):1580. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Bodoki E, Vostinaru O, Samoila O, et al. Topical nanodelivery system of lutein for the prevention of selenite-induced cataract. Nanomedicine. 2019;15(1):188–97. [DOI] [PubMed] [Google Scholar]
  • 49.Weinreb RN, Aung T, Medeiros FA. The pathophysiology and treatment of glaucoma: a review. JAMA. 2014;311:1901–11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Weinreb RN, Leung CK, Crowston JG, et al. Primary open-angle glaucoma. Nat Rev Dis Primers. 2016;2:16067. [DOI] [PubMed] [Google Scholar]
  • 51.Wilsey L, Gowrisankaran S, Cull G, Hardin C, Burgoyne CF, Fortune B. Comparing three different modes of electroretinography in experimental glaucoma: diagnostic performance and correlation to structure. Doc Ophthalmol. 2017;134(2):111–28. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52.McAllister F, Harwerth R, Patel N. Assessing the true intraocular pressure in the non-human primate. Optom Vis Sci. 2018;95(2):113–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Yan ZC, Yang XJ, Chen HR, Deng SF, Zhu YT, Zhuo YH. Effects of chronic elevated intraocular pressure on parameters of optical coherence tomography in rhesus monkeys. Int J Ophthalmol. 2019;12(4):542–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Chan ASY, Tun TA, Allen JC, et al. Longitudinal assessment of optic nerve head changes using optical coherence tomography in a primate microbead model of ocular hypertension. Sci Rep. 2020;10(1):14709. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Antwi-Boasiako K, Carter-Dawson L, Harwerth R, Gondo M, Patel N. The relationship between macula retinal ganglion cell density and visual function in the nonhuman primate. Invest Ophthalmol Vis Sci. 2021;62(1):5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Kim J, Gardiner SK, Ramazzotti A, et al. Strain by virtual extensometers and video-imaging optical coherence tomography as a repeatable metric for IOP-Induced optic nerve head deformations. Exp Eye Res. 2021;211: 108724. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57.Zambrano R, Khreish M, Lee TF, et al. Can lamina cribrosa pressure challenge predict future structural glaucoma progression? Invest Ophthalmol Vis Sci. 2023;64(9):PB0023. [Google Scholar]
  • 58.Pennesi ME, Neuringer M, Courtney RJ. Animal models of age related macular degeneration. Mol Aspects Med. 2012;33(4):487–509. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59.Dawson WW, Dawson JC, Lake KP, Gonzalez-Martinez J. Maculas, monkeys, models, AMD and aging. Vision Res. 2008;48(3):360–5. [DOI] [PubMed] [Google Scholar]
  • 60.Zeiss CJ. Animals as models of age-related macular degeneration: an imperfect measure of the truth. Vet Pathol. 2010;47(3):396–413. [DOI] [PubMed] [Google Scholar]
  • 61.Bhutto IA, McLeod DS, Thomson BR, Lutty GA, Edwards MM. Visualization of choroidal vasculature in pigmented mouse eyes from experimental models of AMD. Exp Eye Res. 2024;238: 109741. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62.Teo ZL, Tham YC, Yu M, et al. Global prevalence of diabetic retinopathy and projection of burden through 2045: systematic review and meta-analysis. Ophthalmology. 2021;128(11):1580–91. [DOI] [PubMed] [Google Scholar]
  • 63.Fernandes AG, Ferraz AN, Brant R, Malerbi FK. Diabetic retinopathy screening and treatment through the Brazilian National Health Insurance. Sci Rep. 2022;12(1):13941. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64.Jo DH, Cho CS, Kim JH, Jun HO, Kim JH. Animal models of diabetic retinopathy: doors to investigate pathogenesis and potential therapeutics. J Biomed Sci. 2013;20(1):38. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65.Wada H. The ear: its structure and function, related to hearing. In: Crocker MJ, editor. Handbook of Noise and Vibration Control. John Wiley & Sons; 2007. pp. 277–85.
  • 66.Hayes SH, Ding D, Salvi RJ, Allman BL. Anatomy and physiology of the external, middle and inner ear. In: Celesia GG, editor. Handbook of clinical neurophysiology. Elsevier; 2013. pp. 3–23.
  • 67.Ugarteburu M, Withnell RH, Cardoso L, Carriero A, Richter CP. Mammalian middle ear mechanics: a review. Front Bioeng Biotechnol. 2022;10: 983510. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 68.Agrawal Y, Platz EA, Niparko JK. Prevalence of hearing loss and differences by demographic characteristics among US adults: data from the National Health and Nutrition Examination Survey, 1999–2004. Arch Intern Med. 2008;168(14):1522–30. [DOI] [PubMed] [Google Scholar]
  • 69.Davis A, McMahon CM, Pichora-Fuller KM, et al. Aging and hearing health: the life-course approach. Gerontologist. 2016;56(Suppl 2):S256-67. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 70.Lin FR, Niparko JK, Ferrucci L. Hearing loss prevalence in the United States. Arch Intern Med. 2011;171(20):1851–2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 71.Lin FR, Ferrucci L. Hearing loss and falls among older adults in the United States. Arch Intern Med. 2012;172(4):369–71. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 72.Lin FR, Yaffe K, Xia J, et al. Hearing loss and cognitive decline in older adults. JAMA Intern Med. 2013;173(4):293–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 73.Bowl MR, Dawson SJ. Age-related hearing loss. Cold Spring Harb Perspect Med. 2019;9(8):a033217. [DOI] [PMC free article] [PubMed]
  • 74.Ohlemiller KK. Age-related hearing loss: the status of Schuknecht’s typology. Curr Opin Otolaryngol Head Neck Surg. 2004;12:439–43. [DOI] [PubMed] [Google Scholar]
  • 75.Guerrieri M, Di Mauro R, Di Girolamo S, Di Stadio A. Hearing and ageing. Subcell Biochem. 2023;103:279–90. [DOI] [PubMed] [Google Scholar]
  • 76.Yang CH, Schrepfer T, Schacht J. Age-related hearing impairment and the triad of acquired hearing loss. Front Cell Neurosci. 2015;9:276. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 77.Bowl MR, Dawson SJ. The mouse as a model for age-related hearing loss—a mini-review. Gerontology. 2015;61:149–57. [DOI] [PubMed] [Google Scholar]
  • 78.Ohlemiller KK, Jones SM, Johnson KR. Application of mouse models to research in hearing and balance. J Assoc Res Otolaryngol. 2016;17:493–523. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 79.Tarnowski BI, Schmiedt RA, Hellstrom LI, Lee FS, Adams JC. Age-related changes in cochleas of mongolian gerbils. Hear Res. 1991;54:123–34. [DOI] [PubMed] [Google Scholar]
  • 80.Schmiedt RA, Lang H, Okamura HO, Schulte BA. Effects of furosemide applied chronically to the round window: a model of metabolic presbyacusis. J Neurosci. 2002;22(21):9643–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 81.Spicer SS, Schulte BA. Pathologic changes of presbycusis begin in secondary processes and spread to primary processes of strial marginal cells. Hear Res. 2005;205(1–2):225–40. [DOI] [PubMed] [Google Scholar]
  • 82.Heffner RS, Heffner HE. Behavioral hearing range of the chinchilla. Hear Res. 1991;52(1):13–6. [DOI] [PubMed] [Google Scholar]
  • 83.Salvi R, Boettcher FA. Animal models of noise-induced hearing loss. In: Conn PM, editor. Sourcebook of Models for Biomedical Research. Humana Press; 2008. pp. 289–301.
  • 84.Trevino M, Lobarinas E, Maulden AC, Heinz MG. The chinchilla animal model for hearing science and noise-induced hearing loss. J Acoust Soc Am. 2019;146(5):3710. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 85.McRackan TR, Bauschard M, Hatch JL, et al. Meta-analysis of quality-of-life improvement after cochlear implantation and associations with speech recognition abilities. Laryngoscope. 2018;128(4):982–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 86.Attias J, Hod R, Raveh E, et al. Hearing loss patterns after cochlear implantation via the round window in an animal model. Am J Otolaryngol. 2016;37(2):162–8. [DOI] [PubMed] [Google Scholar]
  • 87.Kopelovich JC, Robinson BK, Soken H, et al. Acoustic hearing after murine cochlear implantation: effects of trauma and implant type. Ann Otol Rhinol Laryngol. 2015;124(12):931–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 88.Yildiz E, Gerlitz M, Gadenstaetter AJ, et al. Single-incision cochlear implantation and hearing evaluation in piglets and minipigs. Hear Res. 2022;426: 108644. [DOI] [PubMed] [Google Scholar]
  • 89.Marx M, Girard P, Escudé B, Barone P, Fraysse B, Deguine O. Cochlear implantation feasibility in rhesus macaque monkey: anatomic and radiologic results. Otol Neurotol. 2013;34(7):e76-81. [DOI] [PubMed] [Google Scholar]
  • 90.Burton JA, Valero MD, Hackett TA, Ramachandran R. The use of nonhuman primates in studies of noise injury and treatment. J Acoust Soc Am. 2019;146(5):3770. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 91.Duan YY, Clark GM, Cowan RS. A study of intra-cochlear electrodes and tissue interface by electrochemical impedance methods in vivo. Biomaterials. 2004;25(17):3813–28. [DOI] [PubMed] [Google Scholar]
  • 92.Reiss LAJ, Kirk J, Claussen AD, Fallon JB. Animal models of hearing loss after cochlear implantation and electrical stimulation. Hear Res. 2022;426: 108624. [DOI] [PubMed] [Google Scholar]
  • 93.Kaufmann CR, Tejani VD, Fredericks DC, et al. Pilot evaluation of sheep as in vivo model for cochlear implantation. Otol Neurotol. 2020;41(5):596–604. [DOI] [PubMed] [Google Scholar]
  • 94.Trinh TT, Cohen C, Boullaud L, Cottier JP, Bakhos D. Sheep as a large animal model for cochlear implantation. Braz J Otorhinolaryngol. 2022;88(Suppl 1):S24–32. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 95.Yi H, Guo W, Chen W, Chen L, Ye J, Yang S. Miniature pigs: a large animal model of cochlear implantation. Am J Transl Res. 2016;8(12):5494–502. [PMC free article] [PubMed] [Google Scholar]
  • 96.Nevo O, Heymann EW. Led by the nose: olfaction in primate feeding ecology. Evol Anthropol. 2015;24(4):137–48. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 97.Lübke KT, Pause BM. Always follow your nose: the functional significance of social chemosignals in human reproduction and survival. Horm Behav. 2015;68:134–44. [DOI] [PubMed] [Google Scholar]
  • 98.Schaal B, Saxton TK, Loos H, Soussignan R, Durand K. Olfaction scaffolds the developing human from neonate to adolescent and beyond. Philos Trans R Soc Lond B Biol Sci. 1800;2020(375):20190261. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 99.Boesveldt S, Parma V. The importance of the olfactory system in human well-being, through nutrition and social behavior. Cell Tissue Res. 2021;383(1):559–67. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 100.Poirier AC, Melin AD. Smell throughout the life course. Evol Anthropol. 2024;33(4): e22030. [DOI] [PubMed] [Google Scholar]
  • 101.Buck L, Axel R. A novel multigene family may encode odorant receptors: a molecular basis for odor recognition. Cell. 1991;65(1):175–87. [DOI] [PubMed] [Google Scholar]
  • 102.Bushdid C, Magnasco MO, Vosshall LB, Keller A. Humans can discriminate more than 1 trillion olfactory stimuli. Science. 2014;343(6177):1370–2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 103.Veilleux CC, Dominy NJ, Melin AD. The sensory ecology of primate food perception, revisited. Evol Anthropol. 2022;31(6):281–301.  10.1002/evan.21967. [DOI] [PubMed] [Google Scholar]
  • 104.Smith TD, Rossie J, Doherty P. Primate olfaction: anatomy and evolution. In: Brewer WJ, Castle D, Pantelis C, editors. Olfaction and the Brain. Cambridge University Press: Cambridge; 2006. p. 135–66. [Google Scholar]
  • 105.D’Aniello B, Semin GR, Scandurra A, Pinelli C. The vomeronasal organ: a neglected organ. Front Neuroanat. 2017;11:70. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 106.Bruintjes TD, Bleys RLAW. The clinical significance of the human vomeronasal organ. Surg Radiol Anat. 2023;45:457–60. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 107.Doty RL, Shaman P, Applebaum SL, Giberson R, Siksorski L, Rosenberg L. Smell identification ability: changes with age. Science. 1984;226(4681):1441–3. [DOI] [PubMed] [Google Scholar]
  • 108.Lindroos R, Raj R, Pierzchajlo S, Hörberg T, Herman P, Challma S, Hummel T, Larsson M, Laukka EJ, Olofsson JK. Perceptual odor qualities predict successful odor identification in old age. Chem Senses. 2022;47:bjac025. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 109.Zhang C, Wang X. Initiation of the age-related decline of odor identification in humans: a meta-analysis. Ageing Res Rev. 2017;40:45–50. [DOI] [PubMed] [Google Scholar]
  • 110.Boesveldt S, Yee JR, McClintock MK, Lundström JN. Olfactory function and the social lives of older adults: a matter of sex. Sci Rep. 2017;7:45118. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 111.Attems J, Walker L, Jellinger KA. Olfaction and aging: a mini-review. Gerontology. 2015;61(6):485–90. [DOI] [PubMed] [Google Scholar]
  • 112.Mazzatenta A, Cellerino A, Origlia N, Barloscio D, Sartucci F, Di Giulio C, Domenici L. Olfactory phenotypic expression unveils human aging. Oncotarget. 2016;7(15):19193–200. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 113.Ekström I, Larsson M, Rizzuto D, Fastbom J, Bäckman L, Laukka EJ. Predictors of olfactory decline in aging: a longitudinal population-based study. J Gerontol A Biol Sci Med Sci. 2020;75(12):2441–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 114.Roberts SC, Havlíček J, Schaal B. Human olfactory communication: current challenges and future prospects. Philos Trans R Soc Lond B Biol Sci. 1800;2020(375):20190258. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 115.Brann JH, Firestein SJ. A lifetime of neurogenesis in the olfactory system. Front Neurosci. 2014;8:182. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 116.Mobley AS, Rodriguez-Gil DJ, Imamura F, Greer CA. Aging in the olfactory system. Trends Neurosci. 2014;37(2):77–84. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 117.Kondo K, Kikuta S, Ueha R, Suzukawa K, Yamasoba T. Age-related olfactory dysfunction: epidemiology, pathophysiology, and clinical management. Front Aging Neurosci. 2020;12:208. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 118.Murphy C, Solomon ES, Haase L, Wang M, Morgan CD. Olfaction in aging and Alzheimer’s disease: event-related potentials to a cross-modal odor-recognition memory task discriminate ApoE epsilon4+ and ApoE epsilon 4- individuals. Ann N Y Acad Sci. 2009;1170:647–57. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 119.Landis BN, Konnerth CG, Hummel T. A study on the frequency of olfactory dysfunction. Laryngoscope. 2004;114(10):1764–9. [DOI] [PubMed] [Google Scholar]
  • 120.Steinbach S, Hundt W, Zahnert T. Der Riechsinn im alltäglichen Leben. ZFA. 2008;84(08):348–62. [DOI] [PubMed] [Google Scholar]
  • 121.Feng Q, Liu H, Zhang H, et al. Objective assessment of hyposmia in Alzheimer’s disease from image and behavior by combining pleasant odor with unpleasant odor. Front Neurol. 2021;12: 697487. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 122.Cecchini MP, Federico A, Zanini A, et al. Olfaction and taste in Parkinson’s disease: the association with mild cognitive impairment and the single cognitive domain dysfunction. J Neural Transm (Vienna). 2019;126(5):585–95. [DOI] [PubMed] [Google Scholar]
  • 123.Dan X, Wechter N, Gray S, Mohanty JG, Croteau DL, Bohr VA. Olfactory dysfunction in aging and neurodegenerative diseases. Ageing Res Rev. 2021;70: 101416. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 124.Olofsson JK, Ekström I, Larsson M, Nordin S. Olfaction and aging: a review of the current state of research and future directions. Iperception. 2021;12(3):20416695211020332. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 125.Kraemer S, Apfelbach R. Olfactory sensitivity, learning and cognition in young adult and aged male Wistar rats. Physiol Behav. 2004;81(3):435–42. [DOI] [PubMed] [Google Scholar]
  • 126.Schoenbaum G, Nugent S, Saddoris MP, Gallagher M. Teaching old rats new tricks: age-related impairments in olfactory reversal learning. Neurobiol Aging. 2002;23(4):555–64. [DOI] [PubMed] [Google Scholar]
  • 127.LaSarge CL, Montgomery KS, Tucker C, et al. Deficits across multiple cognitive domains in a subset of aged Fischer 344 rats. Neurobiol Aging. 2007;28(6):928–36. [DOI] [PubMed] [Google Scholar]
  • 128.Prediger RD, Batista LC, Takahashi RN. Caffeine reverses age-related deficits in olfactory discrimination and social recognition memory in rats. Involvement of adenosine A1 and A2A receptors. Neurobiol Aging. 2005;26(6):957–64. [DOI] [PubMed] [Google Scholar]
  • 129.Roman FS, Alescio-Lautier B, Soumireu-Mourat B. Age-related learning and memory deficits in odor-reward association in rats. Neurobiol Aging. 1996;17(1):31–40. [DOI] [PubMed] [Google Scholar]
  • 130.Yoder WM, Gaynor LS, Burke SN, Setlow B, Smith DW, Bizon JL. Interaction between age and perceptual similarity in olfactory discrimination learning in F344 rats: relationships with spatial learning. Neurobiol Aging. 2017;53:122–37. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 131.Enwere E, Shingo T, Gregg C, Fujikawa H, Ohta S, Weiss S. Aging results in reduced epidermal growth factor receptor signaling, diminished olfactory neurogenesis, and deficits in fine olfactory discrimination. J Neurosci. 2004;24(38):8354–65. 10.1523/JNEUROSCI.2751-04.2004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 132.Ahnaou A, Rodriguez-Manrique D, Embrechts S, et al. Aging alters olfactory bulb network oscillations and connectivity: relevance for aging-related neurodegeneration studies. Neural Plast. 2020;2020:1703969. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 133.Bontempi P, Ricatti MJ, Sandri M, et al. Age-related in vivo structural changes in the male mouse olfactory bulb and their correlation with olfactory-driven behavior. Biology (Basel). 2023;12(3):381. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 134.Richard MB, Taylor SR, Greer CA. Age-induced disruption of selective olfactory bulb synaptic circuits. Proc Natl Acad Sci U S A. 2010;107(35):15613–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 135.Loo AT, Youngentob SL, Kent PF, Schwob JE. The aging olfactory epithelium: neurogenesis, response to damage, and odorant-induced activity. Int J Dev Neurosci. 1996;14(7–8):881–900. [DOI] [PubMed] [Google Scholar]
  • 136.Hwang IK, Kim DS, Lee HY, et al. Age-related changes of parvalbumin immunoreactive neurons in the rat main olfactory bulb. Mol Cells. 2003;16:302–6. [PubMed] [Google Scholar]
  • 137.Dan X, Yang B, McDevitt RA, et al. Loss of smelling is an early marker of aging and is associated with inflammation and DNA damage in C57BL/6J mice. Aging Cell. 2023;22: e13793. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 138.Tzeng W-Y, Figarella K, Garaschuk O. Olfactory impairment in men and mice related to aging and amyloid-induced pathology. Pflugers Arch - Eur J Physiol. 2021;473:805–21. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 139.Wesson DW, Borkowski AH, Landreth GE, Nixon RA, Levy E, Wilson DA. Sensory network dysfunction, behavioral impairments, and their reversibility in an Alzheimer’s β-amyloidosis mouse model. J Neurosci. 2011;31(44):15962–71. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 140.Mitrano DA, Houle SE, Pearce P, et al. Olfactory dysfunction in the 3xTg-AD model of Alzheimer’s disease. IBRO Neurosci Rep. 2021;10:51–61. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 141.Klæstrup IH, Just MK, Holm KL, et al. Impact of aging on animal models of Parkinson’s disease. Front Aging Neurosci. 2022;14: 909273. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 142.MacDougall G, Brown LY, Kantor B, Chiba-Falek O. The path to progress preclinical studies of age-related neurodegenerative diseases: a perspective on rodent and hiPSC-derived models. Mol Ther. 2021;29:949–72. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 143.Bathini P, Brai E, Auber LA. Olfactory dysfunction in the pathophysiological continuum of dementia. Ageing Res Rev. 2019;55: 100956. [DOI] [PubMed] [Google Scholar]
  • 144.Browne C, Stafford K, Fordham R. The use of scent-detection dogs. Ir Vet J. 2006;59:97–104. [Google Scholar]
  • 145.Kokocińska-Kusiak A, Woszczyło M, Zybala M, et al. Canine olfaction: physiology, behavior, and possibilities for practical applications. Animals (Basel). 2021;11(8):2463. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 146.Jenkins EK, DeChant MT, Perry EB. When the nose doesn’t know: canine olfactory function associated with health, management, and potential links to microbiota. Front Vet Sci. 2018;5:56. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 147.Lazarowski L, Krichbaum S, DeGreeff LE, et al. Methodological considerations in canine olfactory detection research. Front Vet Sci. 2020;7:408. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 148.Hirai T, Kojima S, Shimada A, et al. Age-related changes in the olfactory system of dogs. Neuropathol Appl Neurobiol. 1996;22(6):531–9. [DOI] [PubMed] [Google Scholar]
  • 149.Khan MZ, Mondino A, Russell K, Case B, Fefer G, Woods H, et al. A novel task of canine olfaction for use in adult and senior pet dogs. Sci Rep. 2023;13(1):2224. 10.1038/s41598-023-29361-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 150.Wei Q, Zhang H, Ma S, Guo D. Sex- and age-related differences in c-fos expression in dog olfactory bulbs. Acta Zoologica. 2017;98:370–6. [Google Scholar]
  • 151.Ozawa M, Inoue M, Uchida K, et al. Physical signs of canine cognitive dysfunction. J Vet Med Sci. 2019;81(12):1829–34. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 152.Alvites R, Caine A, Cherubini GB, et al. The olfactory bulb in companion animals-anatomy, physiology, and clinical importance. Brain Sci. 2023;13(5):713. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 153.Languille S, Blanc S, Blin O, et al. The grey mouse lemur: a non-human primate model for ageing studies. Ageing Res Rev. 2012;11(1):150–62. [DOI] [PubMed] [Google Scholar]
  • 154.Hozer C, Pifferi F, Aujard F, Perret M. The biological clock in gray mouse lemur: adaptive, evolutionary and aging considerations in an emerging non-human primate model. Front Physiol. 2019;10:1033. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 155.Aujard F, Némoz-Bertholet F. Response to urinary volatiles and chemosensory function decline with age in a prosimian primate. Physiol Behav. 2004;81(4):639–44. [DOI] [PubMed] [Google Scholar]
  • 156.Cayetanot F, Némoz-Bertholet F, Aujard F. Age effects on pheromone induced Fos expression in olfactory bulbs of a primate. NeuroReport. 2005;16:1091. [DOI] [PubMed] [Google Scholar]
  • 157.Joly M, Deputte B, Verdier JM. Age effect on olfactory discrimination in a non-human primate, Microcebus murinus. Neurobiol Aging. 2006;27(7):1045–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 158.Golub EM, Conner B, Edwards M, Gillis L, Lacreuse A. Potential trade-off between olfactory and visual discrimination learning in common marmosets (Callithrix jacchus): Implications for the assessment of age-related cognitive decline. Am J Primatol. 2022;84(9):e23427. [DOI] [PMC free article] [PubMed]
  • 159.Feng P, Huang L, Wang H. Taste bud homeostasis in health, disease, and aging. Chem Senses. 2014;39:3–16. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 160.Finger TE, Barlow LA. Cellular diversity and regeneration in taste buds. Curr Opin Physiol. 2021;20:146–53. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 161.Yoshida R, Horio N, Murata Y, et al. NaCl responsive taste cells in the mouse fungiform taste buds - ClinicalKey. Neuroscience. 2009;159:795–803. [DOI] [PubMed] [Google Scholar]
  • 162.Ohla K, Yoshida R, Roper SD, et al. Recognizing taste: coding patterns along the neural axis in mammals. Chem Senses. 2019;44:237–47. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 163.Nelson G, Chandrashekar J, Hoon MA, et al. An amino-acid taste receptor. Nature. 2002;416:199–202. [DOI] [PubMed] [Google Scholar]
  • 164.Nelson G, Hoon MA, Chandrashekar J, et al. Mammalian sweet taste receptors. Cell. 2001;106:381–90. [DOI] [PubMed] [Google Scholar]
  • 165.Tu Y-H, Cooper AJ, Teng B, et al. An evolutionarily conserved gene family encodes proton-selective ion channels. Science. 2018;359:1047–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 166.Zhang J, Jin H, Zhang W, et al. Sour sensing from the tongue to the brain. Cell. 2019;179:392-402.e15. [DOI] [PubMed] [Google Scholar]
  • 167.Teng B, Wilson CE, Tu Y-H, et al. Cellular and neural responses to sour stimuli require the proton channel Otop1. Curr Biol. 2019;29:3647-3656.e5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 168.Chandrashekar J, Kuhn C, Oka Y, et al. The cells and peripheral representation of sodium taste in mice. Nature. 2010;464:297–301. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 169.Oka Y, Butnaru M, von Buchholtz L, et al. High salt recruits aversive taste pathways. Nature. 2013;494:472–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 170.Liman ER, Zhang YV, Montell C. Peripheral coding of taste. Neuron. 2014;81:984–1000. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 171.Bigiani A. The origin of saltiness: oral detection of NaCl. Curr Opin Physiol. 2021;19:156–61. [Google Scholar]
  • 172.Mavi A, Ceyhan O. Bitter taste thresholds, numbers and diameters of circumvallate papillae and their relation with age in a Turkish population. Gerodontology. 1999;16:119–22. [DOI] [PubMed] [Google Scholar]
  • 173.Mela DJ, Mattes RD. The chemical senses and nutrition: part I. Nutr Today. 1988;23:4. [Google Scholar]
  • 174.Karikkineth AC, Tang EY, Kuo P, et al. Longitudinal trajectories and determinants of human fungiform papillae density. Aging. 2021;13:24989–5003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 175.Segovia C, Hutchinson I, Laing DG, Jinks AL. A quantitative study of fungiform papillae and taste pore density in adults and children. Dev Brain Res. 2002;138:135–46. [DOI] [PubMed] [Google Scholar]
  • 176.Pavlidis P, Gouveris H, Anogeianaki A, et al. Age-related changes in electrogustometry thresholds, tongue tip vascularization, density, and form of the fungiform papillae in humans. Chem Senses. 2013;38:35–43. [DOI] [PubMed] [Google Scholar]
  • 177.Fischer ME, Cruickshanks KJ, Schubert CR, et al. Factors related to Fungiform papillae density: the Beaver Dam Offspring Study. Chem Senses. 2013;38:669–77. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 178.Feeney EL, Hayes JE. Regional differences in suprathreshold intensity for bitter and umami stimuli. Chemosens Percept. 2014;7:147–57. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 179.Webb J, Bolhuis DP, Cicerale S, et al. The relationships between common measurements of taste function. Chemosens Percept. 2015;8:11–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 180.Saito T, Ito T, Ito Y, et al. Comparison of fungiform taste-bud distribution among age groups using confocal laser scanning microscopy in vivo in combination with gustatory function. Eur J Oral Sci. 2016;124:135–40. [DOI] [PubMed] [Google Scholar]
  • 181.Zuniga JR, Davis SH, Englehardt RA, et al. Taste performance on the anterior human tongue varles with fungiform taste bud density. Chem Senses. 1993;18:449–60. [Google Scholar]
  • 182.Doty RL, Bagla R, Morgenson M, Mirza N. NaCl thresholds: relationship to anterior tongue locus, area of stimulation, and number of fungiform papillae. Physiol Behav. 2001;72:373–8. [DOI] [PubMed] [Google Scholar]
  • 183.Proserpio C, Laureati M, Bertoli S, et al. Determinants of obesity in italian adults: the role of taste sensitivity, food liking, and food neophobia. Chem Senses. 2016;41:169–76. [DOI] [PubMed] [Google Scholar]
  • 184.Piochi M, Dinnella C, Prescott J, Monteleone E. Associations between human fungiform papillae and responsiveness to oral stimuli: effects of individual variability, population characteristics, and methods for papillae quantification. Chem Senses. 2018;43:313–27. [DOI] [PubMed] [Google Scholar]
  • 185.Wiriyawattana P, Suwonsichon S, Suwonsichon T. Effects of aging on taste thresholds: a case of Asian people. J Sens Stud. 2018;33: e12436. [Google Scholar]
  • 186.Schiffman SS. The aging gustatory system. In: Fritzsch B, editor. The senses: a comprehensive reference. 2nd ed. New York: Elsevier Academic Press; 2020. pp. 382–97.
  • 187.Hays N, Roberts S. The anorexia of aging in humans. Physiol Behav. 2006;88:257–66. [DOI] [PubMed] [Google Scholar]
  • 188.Chandrashekar J, Hoon MA, Ryba NJP, Zuker CS. The receptors and cells for mammalian taste. Nature. 2006;444:288–94. [DOI] [PubMed] [Google Scholar]
  • 189.Vennemann MM, Hummel T, Berger K. The association between smoking and smell and taste impairment in the general population. J Neurol. 2008;255:1121–6. [DOI] [PubMed] [Google Scholar]
  • 190.Correia C, Lopez KJ, Wroblewski KE, et al. Global sensory impairment in older adults in the United States. J Am Geriatr Soc. 2016;64:306–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 191.Liu G, Zong G, Doty RL, Sun Q. Prevalence and risk factors of taste and smell impairment in a nationwide representative sample of the US population: a cross-sectional study. BMJ Open. 2016;6: e013246. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 192.Chia CW, Yeager SM, Egan JM. Endocrinology of taste with aging. Endocrinol Metab Clin. 2023;52:295–315. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 193.Ship JA. The influence of aging on oral health and consequences for taste and smell. Physiol Behav. 1999;66:209–15. [DOI] [PubMed] [Google Scholar]
  • 194.Arvidson K. Location and variation in number of taste buds in human fungiform papillae. Eur J Oral Sci. 1979;87:435–42. [DOI] [PubMed] [Google Scholar]
  • 195.Miller IJ. Human taste bud density across adult age groups. J Gerontol. 1988;43:M26–30. [DOI] [PubMed] [Google Scholar]
  • 196.Arey LB, Tremaine MJ, Monzingo FL. The numerical and topographical relations of taste buds to human circumvallate papillae throughout the life span. Anat Rec. 1935;64:9–25.
  • 197.Mochizuki Y. An observation on the numerical and topographical relations of taste buds to circumvallate papillae of Japanese. Okajimas Folia Anat Jpn. 1937;15:595–608. [Google Scholar]
  • 198.Shimizu Y. A Histomorphometric study of the age-related changes of the human taste buds in circumvallate papillae. Oral Med Pathol. 1997;2:17–24. [Google Scholar]
  • 199.Fábián TK, Beck A, Fejérdy P, et al. Molecular mechanisms of taste recognition: considerations about the role of saliva. Int J Mol Sci. 2015;16:5945–74. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 200.Xu F, Laguna L, Sarkar A. Aging-related changes in quantity and quality of saliva: where do we stand in our understanding? J Texture Stud. 2019;50:27–35. [DOI] [PubMed] [Google Scholar]
  • 201.Bigiani A. Salt taste. In: Fritzsch B, editor. The senses: a comprehensive reference. 2nd ed. New York: Elsevier Academic Press: 2020. pp.247–63.
  • 202.Wang M, Septier C, Brignot H, et al. Astringency sensitivity to tannic acid: effect of ageing and saliva. Molecules. 2022;27:1617. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 203.Kazarina A, Kuzmicka J, Bortkevica S, et al. Oral microbiome variations related to ageing: possible implications beyond oral health. Arch Microbiol. 2023;205:116. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 204.Cattaneo C, Gargari G, Koirala R, et al. New insights into the relationship between taste perception and oral microbiota composition. Sci Rep. 2019;9:3549. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 205.Plewa B, Skieresz-Szewczyk K, Jackowiak H. Three-dimensional characteristic of fungiform papillae and its taste buds in European bison (Bison bonasus), cattle (Bos taurus), and Bison bonasus hybrid. BMC Vet Res. 2022;18:21. [DOI] [PMC free article] [PubMed]
  • 206.Frank HER, Amato K, Trautwein M, et al. The evolution of sour taste. Proc R Soc B Biol Sci. 2022;289:20211918. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 207.Iwasaki S. Evolution of the structure and function of the vertebrate tongue. J Anat. 2002;201:1–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 208.Hellekant G, Danilova V, Ninomiya Y. Primate sense of taste: behavioral and single chorda tympani and glossopharyngeal nerve fiber recordings in the rhesus monkey Macaca mulatta. J Neurophysiol. 1997;77:978–93. [DOI] [PubMed] [Google Scholar]
  • 209.Laugerette F, Passilly-Degrace P, Patris B, et al. CD36 involvement in orosensory detection of dietary lipids, spontaneous fat preference, and digestive secretions. J Clin Invest. 2005;115:3177–84. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 210.Hayakawa T, Suzuki-Hashido N, Matsui A, Go Y. Frequent expansions of the bitter taste receptor gene repertoire during evolution of mammals in the Euarchontoglires clade. Mol Biol Evol. 2014;31:2018–31. [DOI] [PubMed] [Google Scholar]
  • 211.Chéron J-B, Golebiowski J, Antonczak S, Fiorucci S. The anatomy of mammalian sweet taste receptors. Proteins Struct Funct Bioinforma. 2017;85:332–41. [DOI] [PubMed] [Google Scholar]
  • 212.Lim MY, Song E-J, Kang KS, Nam Y-D. Age-related compositional and functional changes in micro-pig gut microbiome. GeroScience. 2019;41:935–44. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 213.Lunney JK, Van Goor A, Walker KE, et al. Importance of the pig as a human biomedical model. Sci Transl Med. 2021;13:eabd5758. [DOI] [PubMed] [Google Scholar]
  • 214.Roura E, Koopmans S-J, Lallès J-P, et al. Critical review evaluating the pig as a model for human nutritional physiology. Nutr Res Rev. 2016;29:60–90. [DOI] [PubMed] [Google Scholar]
  • 215.Roura E, Fu M. Taste, nutrient sensing and feed intake in pigs (130 years of research: then, now and future). Anim Feed Sci Technol. 2017;233:3–12. [Google Scholar]
  • 216.Shin Y-K, Cong W, Cai H, et al. Age-related changes in mouse taste bud morphology, hormone expression, and taste responsivity. J Gerontol Ser A. 2012;67A:336–44. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 217.Inui-Yamamoto C, Yamamoto T, Ueda K, et al. Taste preference changes throughout different life stages in male rats. PLoS ONE. 2017;12: e0181650. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 218.Narukawa M, Kurokawa A, Kohta R, Misaka T. Participation of the peripheral taste system in aging-dependent changes in taste sensitivity. Neuroscience. 2017;358:249–60. [DOI] [PubMed] [Google Scholar]
  • 219.Whiddon ZD, Rynberg ST, Mast TG, Breza JM. Aging decreases chorda-tympani nerve responses to NaCl and alters morphology of fungiform taste pores in rats. Chem Senses. 2018;43:117–28. [DOI] [PubMed] [Google Scholar]
  • 220.Bernstein IL, Longley A, Taylor EM. Amiloride sensitivity of chorda tympani response to NaCl in Fischer 344 and Wistar rats. Am J Physiol-Regul Integr Comp Physiol. 1991;261:R329–33. [DOI] [PubMed] [Google Scholar]
  • 221.Blizard DA. Sweet and bitter taste of ethanol in C57BL/6J and DBA2/J mouse strains. Behav Genet. 2007;37:146–59. [DOI] [PubMed] [Google Scholar]
  • 222.Bachmanov AA, Bosak NP, Glendinning JI, et al. Genetics of amino acid taste and appetite. Adv Nutr. 2016;7:806S-S822. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 223.Mistretta CM, Baum BJ. Quantitative study of taste buds in fungiform and circumvallate papillae of young and aged rats. J Anat. 1984;138:323–32. [PMC free article] [PubMed] [Google Scholar]
  • 224.He L, Yadgarov A, Sharif S, McCluskey LP. Aging profoundly delays functional recovery from gustatory nerve injury. Neuroscience. 2012;209:208–18. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 225.McBride M, Mistretta CM. Taste responses from the chorda tympani nerve in young and old Fischer rats. J Gerontol. 1986;41:306–14. [DOI] [PubMed] [Google Scholar]
  • 226.Harada S, Kanemaru N, Kasahara Y. Change in distribution of taste buds in aging rats. Dent Jpn. 2003;39:37–9. [Google Scholar]
  • 227.Cai H, Daimon M, Cong W, et al. Longitudinal analysis of calorie restriction on rat taste bud morphology and expression of sweet taste modulators. J Gerontol Ser A. 2014;69:532–44. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 228.Takeuchi K, Yoshii K, Ohtubo Y. Age-related electrophysiological changes in mouse taste receptor cells. Exp Physiol. 2021;106:519–31. [DOI] [PubMed] [Google Scholar]
  • 229.Abdel-maksoud FM, Inui-Yamamoto C, Kawano A, et al. Histological and immunohistochemical studies of the fungiform and the circumvallate papillae through the life stages from 6- to 72-week-old Sprague-Dawley male rats. Anat Rec. 2024;307(2):414–25. [DOI] [PubMed] [Google Scholar]
  • 230.Bradley RM, Stedman HM, Mistretta CM. Age does not affect numbers of taste buds and papillae in adult rhesus macaques. Anat Rec. 1985;212:246–9. [DOI] [PubMed] [Google Scholar]
  • 231.Yamaguchi K, Harada S, Kanemaru N, Kasahara Y. Age-related alteration of taste bud distribution in the common marmoset. Chem Senses. 2001;26:1–6. [DOI] [PubMed] [Google Scholar]
  • 232.Zhao GQ, Zhang Y, Hoon MA, et al. The receptors for mammalian sweet and umami taste. Cell. 2003;115:255–66. [DOI] [PubMed] [Google Scholar]
  • 233.Toda Y, Hayakawa T, Itoigawa A, et al. Evolution of the primate glutamate taste sensor from a nucleotide sensor. Curr Biol. 2021;31:4641-4649.e5. [DOI] [PubMed] [Google Scholar]
  • 234.Guevara EE, Veilleux CC, Saltonstall K, et al. Potential arms race in the coevolution of primates and angiosperms: brazzein sweet proteins and gorilla taste receptors. Am J Phys Anthropol. 2016;161:181–5. [DOI] [PubMed] [Google Scholar]
  • 235.da Silva EC, de Jager N, Burgos-Paz W, et al. Characterization of the porcine nutrient and taste receptor gene repertoire in domestic and wild populations across the globe. BMC Genomics. 2014;15:1057. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 236.Leshem M. Salt need needs investigation. Br J Nutr. 2020;123:1312–20. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 237.ten Donkelaar HJ, Broman J, van Domburg P. The somatosensory system. In: ten Donkelaar HJ, editor. Clinical Neuroanatomy: Brain Circuitry and Its Disorders. Cham: Springer International Publishing; 2020. p. 171–255. [Google Scholar]
  • 238.Owens DM, Lumpkin EA. Diversification and specialization of touch receptors in skin. Cold Spring Harb Perspect Med. 2014;4:a013656. 10.1101/cshperspect.a013656. [DOI] [PMC free article] [PubMed]
  • 239.Zimmerman A, Bai L, Ginty DD. The gentle touch receptors of mammalian skin. Science. 2014;346:950–4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 240.Tuthill JC, Azim E. Proprioception. Curr Biol. 2018;28(5):R194–203. [DOI] [PubMed] [Google Scholar]
  • 241.Cobo R, García-Piqueras J, García-Mesa Y, et al. Peripheral mechanobiology of touch—studies on vertebrate cutaneous sensory corpuscles. Int J Mol Sci. 2020;21:6221. 10.3390/ijms21176221. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 242.Shaffer SW, Harrison AL. Aging of the somatosensory system: a translational perspective. Phys Ther. 2007;87:193–207. [DOI] [PubMed] [Google Scholar]
  • 243.Deshpande N, Simonsick E, Metter EJ, et al. Ankle proprioceptive acuity is associated with objective as well as self-report measures of balance, mobility, and physical function. Age. 2016;38:53. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 244.Peters RM, McKeown MD, Carpenter MG, Inglis JT. Losing touch: age-related changes in plantar skin sensitivity, lower limb cutaneous reflex strength, and postural stability in older adults. J Neurophysiol. 2016;116:1848–58. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 245.Anson E, Bigelow RT, Swenor B, et al. Loss of peripheral sensory function explains much of the increase in postural sway in healthy older adults. Front Aging Neurosci. 2017;9:202. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 246.Gibson SJ, Farrell M. A review of age differences in the neurophysiology of nociception and the perceptual experience of pain. Clin J Pain. 2004;20:227. [DOI] [PubMed] [Google Scholar]
  • 247.Lautenbacher S, Peters JH, Heesen M, et al. Age changes in pain perception: a systematic-review and meta-analysis of age effects on pain and tolerance thresholds. Neurosci Biobehav Rev. 2017;75:104–13. [DOI] [PubMed] [Google Scholar]
  • 248.Stevens JC, Choo KK. Spatial acuity of the body surface over the life span. Somatosens Mot Res. 1996;13:153–66. [DOI] [PubMed] [Google Scholar]
  • 249.Stevens JC, Choo KK. Temperature sensitivity of the body surface over the life span. Somatosens Mot Res. 1998;15(1):13–28. [DOI] [PubMed] [Google Scholar]
  • 250.Stevens JC, Alvarez-Reeves M, Dipietro L, et al. Decline of tactile acuity in aging: a study of body site, blood flow, and lifetime habits of smoking and physical activity. Somatosens Mot Res. 2003;20:271–9. [DOI] [PubMed] [Google Scholar]
  • 251.Adamo DE, Alexander NB, Brown SH. The influence of age and physical activity on upper limb proprioceptive ability. J Aging Phys Act. 2009;17:272–93. [DOI] [PubMed] [Google Scholar]
  • 252.Tremblay F, Master S. Touch in aging. In: Prescott TJ, Ahissar E, editors. Scholarpedia of touch. Atlantis Press; 2016. pp. 351–61.
  • 253.Skedung L, El Rawadi C, Arvidsson M, et al. Mechanisms of tactile sensory deterioration amongst the elderly. Sci Rep. 2018;8:5303. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 254.McIntyre S, Nagi SS, McGlone F, Olausson H. The effects of ageing on tactile function in humans. Neuroscience. 2021;464:53–8. [DOI] [PubMed] [Google Scholar]
  • 255.Legge GE, Madison C, Vaughn BN, et al. Retention of high tactile acuity throughout the life span in blindness. Percept Psychophys. 2008;70:1471–88. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 256.Joo Kim Y, Rogers JC, Kwok G, et al. Somatosensation differences in older adults with and without diabetes, and by age group. Occup Ther Health Care. 2016;30:231–44. [DOI] [PubMed] [Google Scholar]
  • 257.Legge GE, Granquist C, Lubet A, et al. Preserved tactile acuity in older pianists. Atten Percept Psychophys. 2019;81:2619–25. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 258.Perry SD. Evaluation of age-related plantar-surface insensitivity and onset age of advanced insensitivity in older adults using vibratory and touch sensation tests. Neurosci Lett. 2006;392:62–7. [DOI] [PubMed] [Google Scholar]
  • 259.Guergova S, Dufour A. Thermal sensitivity in the elderly: a review. Ageing Res Rev. 2011;10:80–92. [DOI] [PubMed] [Google Scholar]
  • 260.Decorps J, Saumet JL, Sommer P, et al. Effect of ageing on tactile transduction processes. Ageing Res Rev. 2014;13:90–9. [DOI] [PubMed] [Google Scholar]
  • 261.García-Piqueras J, García-Mesa Y, Cárcaba L, et al. Ageing of the somatosensory system at the periphery: age-related changes in cutaneous mechanoreceptors. J Anat. 2019;234:839–52. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 262.Delmas P, Hao J, Rodat-Despoix L. Molecular mechanisms of mechanotransduction in mammalian sensory neurons. Nat Rev Neurosci. 2011;12:139–53. [DOI] [PubMed] [Google Scholar]
  • 263.Ranade SS, Woo S-H, Dubin AE, et al. Piezo2 is the major transducer of mechanical forces for touch sensation in mice. Nature. 2014;516:121–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 264.Nakatani M, Maksimovic S, Baba Y, Lumpkin EA. Mechanotransduction in epidermal Merkel cells. Pflugers Arch. 2015;467:101–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 265.Desiderio S, Schwaller F, Tartour K, Padmanabhan K, Lewin GR, Carroll P, Marmigere F. Touch receptor end-organ innervation and function require sensory neuron expression of the transcription factor Meis2. Elife. 2024;12:RP89287. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 266.Ras VR, Nava PB. Age-related changes of neurites in Meissner corpuscles of diabetic mice. Exp Neurol. 1986;91:488–501. [DOI] [PubMed] [Google Scholar]
  • 267.Wai V, Roberts L, Michaud J, et al. The anatomical distribution of mechanoreceptors in mouse hind paw skin and the influence of integrin α1β1 on Meissner-like corpuscle density in the footpads. Front Neuroanat. 2021;15: 628711. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 268.Nava PB. The effects of age on murine pacinian corpuscles. In: Hnik P, Soukup T, Vejsada R, Zelena J, editors. Mechanoreceptors: development, structure, and function. Springer US; 1988. pp. 289–94.
  • 269.Nava PB, Mathewson RC. Effect of age on the structure of Meissner corpuscles in murine digital pads. Microsc Res Tech. 1996;34:376–89. [DOI] [PubMed] [Google Scholar]
  • 270.Canta A, Chiorazzi A, Carozzi VA, et al. Age-related changes in the function and structure of the peripheral sensory pathway in mice. Neurobiol Aging. 2016;45:136–48. [DOI] [PubMed] [Google Scholar]
  • 271.Vaughan SK, Stanley OL, Valdez G. Impact of aging on proprioceptive sensory neurons and intrafusal muscle fibers in mice. J Gerontol A Biol Sci Med Sci. 2017;72:771–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 272.Miwa T, Miwa Y, Kanda K. Dynamic and static sensitivities of muscle spindle primary endings in aged rats to ramp stretch. Neurosci Lett. 1995;201:179–82. [DOI] [PubMed] [Google Scholar]
  • 273.Coq JO, Xerri C. Sensorimotor experience modulates age-dependent alterations of the forepaw representation in the rat primary somatosensory cortex. Neuroscience. 2001;104:705–15. [DOI] [PubMed] [Google Scholar]
  • 274.Paré M, Albrecht PJ, Noto CJ, et al. Differential hypertrophy and atrophy among all types of cutaneous innervation in the glabrous skin of the monkey hand during aging and naturally occurring type 2 diabetes. J Comp Neurol. 2007;501:543–67. [DOI] [PubMed] [Google Scholar]
  • 275.Suazo I, Vega JA, García-Mesa Y, García-Piqueras J, García-Suárez O, Cobo T. The lamellar cells of vertebrate meissner and pacinian corpuscles: development, characterization, and functions. Front Neurosci. 2022;16: 790130. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 276.Bolanowski SJ, Pawson L. Organization of meissner corpuscles in the glabrous skin of monkey and cat. Somatosens Mot Res. 2003;20:223–31. 10.1080/08990220310001622915. [DOI] [PubMed] [Google Scholar]
  • 277.Harcourt-Smith WEH, Aiello LC. Fossils, feet and the evolution of human bipedal locomotion. J Anat. 2004;204:403–16. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 278.Hashimoto T, Ueno K, Ogawa A, et al. Hand before foot? Cortical somatotopy suggests manual dexterity is primitive and evolved independently of bipedalism. Philos Trans R Soc B Biol Sci. 2013;368:20120417. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 279.Cassidy A, Onal M, Pelletier S. Novel methods for the generation of genetically engineered animal models. Bone. 2023;167:116612. [DOI] [PMC free article] [PubMed]
  • 280.Ashby R, Ohlendorf A, Schaeffel F. The effect of ambient illuminance on the development of deprivation myopia in chicks. Invest Ophthalmol Vis Sci. 2009;50(11):5348–54. [DOI] [PubMed] [Google Scholar]
  • 281.He M, Xiang F, Zeng Y, et al. Effect of time spent outdoors at school on the development of myopia among children in China: a randomized clinical trial. JAMA. 2015;314(11):1142–8. [DOI] [PubMed] [Google Scholar]
  • 282.Klein BE, Howard KP, Iyengar SK, et al. Sunlight exposure, pigmentation, and incident age-related macular degeneration. Invest Ophthalmol Vis Sci. 2014;55(9):5855–61. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 283.Lee J, Kim UJ, Lee Y, et al. Sunlight exposure and eye disorders in an economically active population: data from the KNHANES 2008–2012. Ann Occup Environ Med. 2021;33: e24. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 284.Lee HJ, Kim CO, Lee DC. Association between daily sunlight exposure duration and diabetic retinopathy in Korean adults with diabetes: a nationwide population-based cross-sectional study. PLoS ONE. 2020;15(8): e0237149. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 285.Newman LE, Testard C, DeCasien AR, et al. The biology of aging in a social world: insights from free-ranging rhesus macaques. Neurosci Biobehav Rev. 2023;154: 105424. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 286.Alexopoulos P, Fernandes AG, Ghassabi Z, et al. Lamina cribrosa microstructure in non-human primates with naturally occurring peripapillary retinal nerve fiber layer thinning. Invest Ophthalmol Vis Sci. 2022;63(7):932-A0401. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 287.Festing S, Wilkinson R. The ethics of animal research. Talking Point on the use of animals in scientific research. EMBO Rep. 2007;8(6):526–30. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 288.Calvillo L. Editorial: 3Rs approach (replace, reduce and refine animal models) to improve preclinical research. Front Physiol. 2022;13:1040575. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.


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