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EP-4740220-A1 - MACHINE LEARNING-BASED PHENOTYPIC AGE AND PHENOTYPIC AGE ACCELERATION/DECELERATION PREDICTION TOOL FOR PETS

EP4740220A1EP 4740220 A1EP4740220 A1EP 4740220A1EP-4740220-A1

Abstract

The disclosure provides a system for generating a multi-component aging index for an individual companion animal comprising digital biomarkers, biological biomarkers and subjective assessment methods to predict phenotypic age and phenotypic age acceleration/deceleration (phenotypic age above or below chronological age) in dogs and cats. The disclosure also provides a method for decelerating phenotypic aging of a companion animal in need thereof. The method comprises determining an index according to the first aspect of the disclosure and providing personalized health, diet and nutrition measures to the companion animal according to the index for that companion animal. The method can also be considered to be a method of ameliorating accelerated aging in the animal. In some embodiments, the personalized health measure comprises a diet that decelerates phenotypic aging and/or ameliorates accelerated phenotypic aging.

Inventors

  • WERNIMONT, Susan
  • THOMPSON, ROBIN
  • HORSCHLER, DANIEL
  • GROSS, KATHY

Assignees

  • Hill's Pet Nutrition, Inc.

Dates

Publication Date
20260513
Application Date
20240812

Claims (20)

  1. CLAIMS What Is Claimed Is: 1. A system for generating a multi-component aging index for an individual companion animal based on measuring at least one of digital biomarkers, traditional biomarkers and subjective assessment methods to predict phenotypic age and phenotypic age acceleration/deceleration in dogs and cats, the system optionally further comprising determining at least one of sex, neuter status, and lifestage.
  2. 2. The system according to claim 1, the system further comprising at least one of wearable devices to measure physical activity comprising walking, running, resting, jumping, sleep time, sleep quality and sleep regularity, subjective assessment via at least one of pet parent questionnaires and veterinary questionnaires, clinical characteristics comprising chronological age, weight, BCS, BFI, temperature, respiration rate, and heart rate, environmental sensors comprising sensors detecting at least one of location and location- based behaviors and activities comprising proximity to pet parent, play, timing and frequency of feeding, location of eating, drinking, urination and defecation, body posture, pose estimation, tail position, body position, movement tracking over time, repeated measures of clinical, digital and biological data, eating, drinking, urinating, defecating patterns, signs of emotional health, cognitive health, fear, anxiety, stress, dementia and social interaction with humans and other animals, and veterinary assessment of at least one of gastrointestinal disease, genitourinary disease, kidney disease, dermatological disease, respiratory disease, neurological disease, muscular disease, ophthalmological disease, auditory disease, cardiovascular disease, cancer, oral health, endocrine disease, infectious disease, immune function, inflammation, orthopedic disease, mobility, and pain.
  3. 3. The system according to claim 1 or 2, wherein the biomarker panels comprise two or more traditional biomarkers selected from CBC/chemistry parameters, fecal microbiome, fecal metabolites, urinary microbiome, urinary metabolites, blood metabolites, and blood biomarkers comprising albumin, creatinine, glucose, lymphocyte percent, mean cell volume, red cell distribution width, alkaline phosphatase, white blood cell count, SDMA, circulating peptides comprising Aβ42, circulating postbiotics, immunoglobulins, immunoglobulin M, growth hormone (GH)/insulin growth factor-1 (IGF-1), and DNA biomarkers, SNPs, and genetic variants.
  4. 4. The system according to any foregoing claim, wherein the biomarker panels comprise three or more traditional biomarkers selected from CBC/chemistry parameters, fecal microbiome, fecal metabolites, urinary microbiome, urinary metabolites, blood metabolites, and blood biomarkers comprising albumin, creatinine, glucose, lymphocyte percent, mean cell volume, red cell distribution width, alkaline phosphatase, white blood cell count, SDMA, circulating peptides comprising Aβ42, circulating postbiotics, immunoglobulins, immunoglobulin M, growth hormone (GH)/insulin growth factor-1 (IGF-1), and DNA biomarkers, SNPs, and genetic variants.
  5. 5. The system according to any foregoing claim, wherein the biomarker panels comprise four or more traditional biomarkers selected from CBC/chemistry parameters, fecal microbiome, fecal metabolites, urinary microbiome, urinary metabolites, blood metabolites, and blood biomarkers comprising albumin, creatinine, glucose, lymphocyte percent, mean cell volume, red cell distribution width, alkaline phosphatase, white blood cell count, SDMA, circulating peptides comprising Aβ42, circulating postbiotics, immunoglobulins, immunoglobulin M, growth hormone (GH)/insulin growth factor-1 (IGF-1), and DNA biomarkers, SNPs, and genetic variants
  6. 6. The system according to any foregoing claim, wherein the biomarker panels comprise five or more traditional biomarkers selected from CBC/chemistry parameters, fecal microbiome, fecal metabolites, urinary microbiome, urinary metabolites, blood metabolites, and blood biomarkers comprising albumin, creatinine, glucose, lymphocyte percent, mean cell volume, red cell distribution width, alkaline phosphatase, white blood cell count, SDMA, circulating peptides comprising Aβ42, circulating postbiotics, immunoglobulins, immunoglobulin M, growth hormone (GH)/insulin growth factor-1 (IGF-1), and DNA biomarkers, SNPs, and genetic variants.
  7. 7. The system according to any foregoing claim, wherein the multi-component aging index for an individual companion animal is further based on measuring epigenetic modifications including the DNA methylome.
  8. 8. The system according to any one of claims 3 to 7, wherein the DNA biomarkers comprise one or a plurality of single nucleotide polymorphism (SNPs).
  9. 9. The system according to any one of claims 2 to 8, wherein the wearable device is a Collar Mounted Activity Sensor (CMAS).
  10. 10. The system according to any one of claims 2 to 9, further comprising one or more of a smart bed, a smart room and a smart toy and optionally one or more of a camera, computer vision, and audio units.
  11. 11. A method for decelerating phenotypic aging of a companion animal in need thereof comprising determining an index using the system of any foregoing claim, and based thereon providing customized health, dietary and/or nutrition measures to the companion animal.
  12. 12. The method according to claim 11, wherein the companion animal is an overweight animal.
  13. 13. The method according to claim 11, wherein the companion animal is an undernourished animal.
  14. 14. The method according to any one of claims 11 to 13, wherein the companion animal is an animal that has difficulty maintaining a healthy weight.
  15. 15. The method according to any one of claims 11 to 14, wherein the companion animal is an elderly animal or wherein the companion animal is an unknown age and determined to be experiencing advanced phenotypic age or aging acceleration via analysis of at least one traditional biomarker from the companion animal.
  16. 16. The method according to any one of claims 11 to 15 wherein the personalized health measure comprises a diet that ameliorates accelerating phenotypic aging.
  17. 17. A system comprising: (a) a biosensor comprising: (i) a solid support comprising an internal cavity and external surface; (i) a band operably linked to an external surface of the solid support; (ii) an electrical circuit positioned within the internal cavity comprising at least a first position sensor and at least a first motion sensor; (b) at least one computer storage memory; and (c) a controller; wherein each of the sensors is in electrical communication with the controller.
  18. 18. A method of determining acceleration or deceleration of age of a subject comprising: (a) measuring one or a combination of activity metrics of the subject over a period of time; (b) determining a mobility score of the subject relative to a control subject of the same age; (c) classifying the subject as active if the mobility score is at or over the control mobility score for the age of the subject; or classifying the subject as inactive if the mobility score is under the control mobility score for the age of the subject.
  19. 19. The method according to claim 18, wherein the subject is a companion animal.
  20. 20. The method according to claim 18 or claim 19, wherein the activity metric is proximity to pet parent, play, timing and frequency of feeding, location of eating, drinking, urination and defecation, body posture (e.g., via pose estimation), tail position, body position, movement tracking over time, and incorporation of repeated measures of selected clinical, digital and biological data, eating, drinking, urinating, defecating and signs of emotional/cognitive health, such as fear, anxiety, stress, dementia and social interaction with humans and other animals tail movement, barking, jumping, scratching, speed of the animal in a direction, or sleeping.

Description

MACHINE LEARNING-BASED PHENOTYPIC AGE AND PHENOTYPIC AGE ACCELERATION/DECELERATION PREDICTION TOOL FOR PETS CROSS-REFERENCE TO RELATED APPLICATION [0001] This application claims the benefit of U.S. provisional application No.63/532,360, which was filed August 12, 2023, is titled “Machine Learning-Based Phenotypic Age and Phenotypic Age Acceleration/deceleration Prediction Tool for Pets,” and is incorporated herein by reference as if fully set forth. BACKGROUND [0002] The disclosure relates to tools to determine phenotypic age of companion animals (a/k/a “pets”, “dogs” or “cats” and used interchangeably herein) and to identify whether such phenotypic age is accelerating or decelerating for an individual companion animal as well as to predict life span. The disclosure also relates to a method for decelerating phenotypic aging of companion animals in need thereof. [0003] Pets are important in the lives of humans. They provide companionship, entertainment and even can improve people’s health. However, one of the downsides of pet ownership is that pets do not live as long as people and people feel sadness and grief when they lose their pet. Not all pets, even those of the same initial age and breed, have the same predicted lifespan. In addition, not all pets age at the same rate, with some pets showing evidence that they are aging faster than would be expected based on their chronological age and other pets showing evidence that they are aging slower than would be expected based on their chronological age. Two pets of the same breed and same age may have very different aging trajectories, with one pet having poor health and developing age-related conditions relatively early and another pet having excellent health and developing age-related conditions relatively late or not at all. Poor health may result in a shorter lifespan, but a pet may also live for years with age-related conditions, which may limit the pet’s physical abilities, cognitive abilities, care requirements and quality of life while they are living. The impact of the pet’s aging trajectory also impacts the pet parent, for example, through increased veterinary and home care requirements, limited ability to perform activities of daily living, medication costs, and the inability to enjoy previously shared activities. Because of the potential impacts of their pet’s aging process, pet parents want to take the best care of their pet and ensure their pet remains as healthy as possible for as long as possible. One barrier to selecting the best care possible for their pet is the lack of understanding of the aging process in pets. Pets are quite diverse in their lifespan. This is especially true in dogs where some breeds may have a lifespan of only six years while others can live to twenty years or more. Lifespan of individuals within breeds is also quite variable and is influenced by genetics, healthcare practices, feeding and nutrition, exercise, environment and other factors. [0004] Guidelines for examinations, vaccinations, diagnostic and screening tests and aging- related accommodations are different for senior pets vs. those in earlier lifestages. However, the definition of the senior lifestage in dogs requires identifying dogs that are in the last 25% of their estimated lifespan, a threshold that may be difficult for both pet parents and veterinarians to identify. See Bartges, J. et al. “AAHA Canine Life Stage Guidelines” (2012) JAAHA 48:1. Further dogs are the most phenotypically diverse mammalian species with lifespans that vary widely by breed (Ruple, A et al. “Dog Models of Aging” (2022) Annu. Rev. Anim. Biosci. 10:419–439) in addition to genetic, nutritional and environmental factors. [0005] In cats, the definition of the senior lifestage is a bit more well-defined (cats over 10 years of age are considered senior) See Quimby, J. et al. “2021 AAHA/AAFP Feline Life Stage Guidelines” (2021) JAAHA 57:2. Nevertheless, cat lifespans too can vary widely, with a typical lifespan being reported to be between 13 and 17 years, some cats known to live over 20 years and the oldest cat on record reported to have lived over 38 years. Even in the context of a “typical” lifespan, a pet may spend between 25-40% of its life as a “senior” pet, suggesting that chronological age alone may not be sufficient to reflect the aging process. A better understanding of the aging process in a given pet would allow pet parents and veterinarians to provide more targeted and personalized care. [0006] Some aspects of the aging process may be easier to recognize, such as graying fur, but pets also do not always exhibit easily recognizable changes in appearance or behavior as they age to provide pet parents or veterinarians clues to the pet aging process. Furthermore, even when signs are present, pet parents and veterinarians may not recognize signs of aging in pets, including both dogs and cats, until aging is advanced. Other aspects of the aging process may be invisible without