[go: up one dir, main page]

WO2025093461A1 - Procédé pour déterminer l'état de santé d'un chien - Google Patents

Procédé pour déterminer l'état de santé d'un chien Download PDF

Info

Publication number
WO2025093461A1
WO2025093461A1 PCT/EP2024/080371 EP2024080371W WO2025093461A1 WO 2025093461 A1 WO2025093461 A1 WO 2025093461A1 EP 2024080371 W EP2024080371 W EP 2024080371W WO 2025093461 A1 WO2025093461 A1 WO 2025093461A1
Authority
WO
WIPO (PCT)
Prior art keywords
dog
serum
probability
mortality risk
age
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/EP2024/080371
Other languages
English (en)
Inventor
Lorane TEXARI
Alix ZOLLINGER
Sébastien HERZIG
Philipp GUT
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Societe des Produits Nestle SA
Nestle SA
Original Assignee
Societe des Produits Nestle SA
Nestle SA
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Societe des Produits Nestle SA, Nestle SA filed Critical Societe des Produits Nestle SA
Publication of WO2025093461A1 publication Critical patent/WO2025093461A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/60—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/124—Animal traits, i.e. production traits, including athletic performance or the like
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/154—Methylation markers
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H15/00—ICT specially adapted for medical reports, e.g. generation or transmission thereof
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients

Definitions

  • the present invention relates to a method for determining the health status of a dog using a combination of biomarkers and a DNA methylation profile.
  • the invention relates to determining a biological age, mortality risk and/or probability of a healthy lifespan of a dog using a combination of biomarkers and a DNA methylation profile.
  • the ability to determine information regarding the health of a dog is desirable to inform about the dog’s general health and well-being.
  • Chronological age is known to be a major indicator of general health status, with increasing chronological age associated with reduced health. However, depending on genetics, nutrition, and lifestyles, individuals may age slower or faster than their chronological age. Chronological age may therefore not always reflect an individual’s rate of aging or risk of reduced health.
  • the biological age of an individual (based on e.g. clinical biochemistry and cell biology measures) can vary compared to others of the same chronological age. Methods for determining biological age, or phenotypic age, may be helpful for identifying individuals at risk of age-related disorders earlier than would be expected based on their chronological age (see e.g. WO2019/046725).
  • the present invention relates to a method for quantifying the health status of a dog by combining information based on biomarkers, in particular blood biomarkers, and a DNA methylation profile.
  • the method enables a determination of a biological age, mortality risk and/or probability of a healthy lifespan for the dog through an assessment of both biomarkers (i.e. blood biomarkers) and a DNA methylation profile from the dog.
  • Calculating the biological age of an animal may comprise determining a biomarker profile (i.e. blood biomarker profile) or a DNA methylation profile compared to an expected biomarker or DNA methylation profile at a given chronological age. Such methods are therefore based on the use of chronological age as the primary indicator of overall health.
  • the present invention may also take into account the direct predictive value of the described biomarkers and/or a DNA methylation profile on mortality risk and/or probability of a healthy lifespan.
  • a given biomarker and/or DNA methylation marker may not directly correlate with chronological age, but may be indicative of a particular pathological condition and thus an increased mortality risk and/or a probability of a reduced healthy lifespan.
  • the present methods may thus be described as identifying the mortality risk and/or a probability of a healthy lifespan of a dog.
  • the described biomarkers, DNA methylation markers and DNA methylation profiles of the present invention may not necessarily correlate with chronological age, but may relate to the difference between phenotypic and chronological age of the dog.
  • the present invention provides a method for determining a biological age, mortality risk and/or probability of a healthy lifespan of a dog; said method comprising using
  • the method may comprise: a) determining a biological age, mortality risk and/or probability of a healthy lifespan of the dog using the level of one or more biomarker(s) in one or more samples obtained from the dog, wherein the one or more biomarker(s) is selected from white blood cell count, serum albumin, serum alkaline phosphatase, serum creatine kinase, haemoglobin, haematocrit, mean corpuscular haemoglobin, serum glucose, mean red cell volume, serum globulin, serum calcium, platelet count, and/or red blood cell count; and b) determining a biological age, mortality risk and/or probability of a healthy lifespan for the dog using a DNA methylation profile from the dog.
  • the present invention relates to combining a biological age, mortality risk and/or probability of a healthy lifespan determined using one or more biomarker(s) described herein with a biological age, mortality risk and/or probability of a healthy lifespan determined using a DNA methylation profile.
  • the combination of these aspects i.e. a determination using one or more biomarker(s) and a determination using a DNA methylation profile - each as described herein
  • the present combined method may provide an improved determination of biological age, mortality risk and/or probability of a healthy lifespan e.g. by enabling the biological age, mortality risk and/or probability of a healthy lifespan to be calculated more accurately.
  • the biological age, mortality risk and/or probability of a healthy lifespan of the dog determined in step a) and the biological age, mortality risk and/or probability of a healthy lifespan for the dog determined in step b) may be combined to provide a composite biological age, mortality risk and/or probability of a healthy lifespan for the dog.
  • the biological age, mortality risk and/or probability of a healthy lifespan may be provided as a combined score derived from the biological age, mortality risk and/or probability of a healthy lifespan of the dog determined in step a) and the biological age, mortality risk and/or probability of a healthy lifespan for the dog determined in step b).
  • the score may be provided as a biological age, a delta or a score derived from biological age (e.g. Delta_diff: difference between biological age and chronological age; or Delta_res:the residuals of a linear model explaining biological age by chronological age); mortality risk or probability of a healthy lifespan.
  • a biological age e.g. Delta_diff: difference between biological age and chronological age; or Delta_res:the residuals of a linear model explaining biological age by chronological age
  • mortality risk or probability of a healthy lifespan e.g. Delta_diff: difference between biological age and chronological age; or Delta_res:the residuals of a linear model explaining biological age by chronological age
  • the biological age of the dog may be expressed in terms of years, months, days, etc.
  • Determining a mortality risk may refer to determining a likelihood that a dog will live for a longer or shorter period of time compared to an equivalent dog of - for example - the same chronological age, sex and breed. Accordingly, the present methods may determine the probability of a lifespan, health span and/or longevity for a dog compared to an equivalent dog of - for example - the same chronological age, sex and breed. In addition, methods for improving the biological age, mortality risk and/or probability of a healthy lifespan for the dog may improve the probable lifespan, health span and/or longevity of the dog.
  • ‘lifespan’ may refer to the length of time (e.g. years) for which a subject lives.
  • Health span may refer to length of time (e.g. years) of life without disease.
  • ‘Longevity’ may refer to length of time (e.g. years) that a subject lives beyond its expected lifespan.
  • mortality risk may be equated to the probability of a healthy lifespan for the dog; wherein a decreased mortality risk is equated to an increased probably of longer healthy lifespan for the dog or an increased mortality risk is equated to a decreased probability of longer healthy lifespan for the dog.
  • the mortality risk may be represented as the difference between determined age (i.e. biological age) and chronological age of the dog. For example, an increase in the difference between the biological age determined by the present method compared to chronological age may be indicative of an increased mortality risk for the dog. A decrease in the difference between the biological age determined by the present method compared to chronological age may be indicative of a decreased mortality risk for the dog.
  • the mortality risk and/or a probability of a healthy lifespan may be described as the biological age of the dog.
  • the mortality risk and/or a probability of a healthy lifespan determined using the present biomarkers may be described as the phenotypic age (phenoage) of the dog.
  • the biological age, mortality risk and/or a probability of a healthy lifespan determined using a DNA methylation profile may be described as the epigenetic age of the dog.
  • a present biological clock determined using a DNA methylation profile may be referred to as an epigenetic clock.
  • determining that the biological age of the dog is greater than its chronological age is indicative of a higher mortality risk.
  • determining that the biological age of the dog is less than its chronological age is indicative of a reduced mortality risk.
  • determining that the biological age of the dog is greater than its chronological age is indicative of a reduced probability of a longer healthy lifespan.
  • determining that the biological age of the dog is less than its chronological age is indicative of an increased probability of a longer healthy lifespan.
  • the present methods may be used to determine a biological age for a dog based on its biological age, mortality risk and/or probability of a healthy lifespan.
  • the present invention further provides a method for selecting a lifestyle regime, dietary regime or therapeutic intervention for a dog, the method comprising: i) determining a biological age, mortality risk and/or probability of a healthy lifespan for the dog according to the method of the invention; and ii) selecting a suitable lifestyle regime, dietary regime or therapeutic intervention for the dog based on the biological age, mortality risk and/or probability of a healthy lifespan determined in step i).
  • ‘selecting a suitable lifestyle regime, dietary regime or therapeutic intervention for a dog’ may also encompass ‘recommending a lifestyle regime, dietary regime or therapeutic intervention for the dog’ or ‘providing a recommended lifestyle regime, dietary regime or therapeutic intervention for the dog’.
  • improving the biological age, mortality risk and/or probability of a healthy lifespan of a dog may refer to a reduction in the difference between the biological age and chronological age of the dog, where the biological age of the dog is greater than its chronological age. Further, improving the biological age, mortality risk and/or probability of a healthy lifespan of a dog may refer to maintaining or further increasing the difference between the biological age and chronological age of the dog, where the biological age of the dog is less than its chronological age. Alternatively, a worsening in the biological age, mortality risk and/or probability of a healthy lifespan of a dog may refer to an increase in the difference between the biological age and chronological age of the dog, where the biological age of the dog is greater than its chronological age. A worsening in the biological age, mortality risk and/or probability of a healthy lifespan of a dog may also refer to a decrease in the difference between the biological age and chronological age of the dog, where the biological age of the dog is less than its chronological age.
  • the invention further provides a method for determining the efficacy of a lifestyle regime, dietary regime or therapeutic intervention for improving the biological age, mortality risk and/or probability of a healthy lifespan of a dog, said method comprising: applying a lifestyle regime, dietary regime or therapeutic intervention to the dog; ii) after a time period of applying the lifestyle regime, dietary regime or therapeutic intervention to the dog; determining a biological age, mortality risk and/or probability of a healthy lifespan of the dog according to the method of the invention; iii) determining if there has been a change in the biological age, mortality risk and/or probability of a healthy lifespan of the dog after the time period of following the lifestyle regime, dietary regime or therapeutic intervention.
  • improving the biological age, mortality risk and/or probability of a healthy lifespan of a dog may refer to a reduction in the rate of change between the biological age and chronological age of the dog, where the biological age of the dog is greater than its chronological age.
  • a dog’s biological age may have been increasing by 1 .5 years per 1 year increase in chronological age.
  • a reduction in the rate of change such that the dog’s biological age subsequently increases by 1.25 years per 1 year increase in chronological age may provide an improvement in the dog’s biological age, mortality risk and/or probability of a healthy lifespan.
  • Improving the biological age, mortality risk and/or probability of a healthy lifespan may also refer to maintaining or increasing in the rate of change between the biological age and chronological age of the dog, where the biological age of the dog is less than its chronological age.
  • a dog’s biological age may have been increasing by less than 1 year (e.g 0.9 years) per 1 year increase in chronological age.
  • the rate of change may alter such that the dog’s biological age subsequently increases by, for example, 0.8 years or fewer per 1 year increase in chronological age may provide an improvement in the dog’s biological age.
  • the present method enables a suitable lifestyle regime, dietary regime or therapeutic intervention to be selected for the dog, based on its biological age, mortality risk and/or probability of a healthy lifespan as determined from the DNA methylation profile.
  • highly digestible and high-quality protein diets are generally recommended based upon the chronological age of a dog.
  • the determination of an increased mortality risk and/or reduced probability of a healthy lifespan (i.e. an increased biological age) for a dog compared to its chronological age may allow a determination to switch the dog to a senior diet at an earlier age.
  • a dog with a reduced mortality risk and/or increased probability of a healthy lifespan i.e. reduced biological age
  • compared to its chronological age may be able to stay on an adult diet for longer.
  • the present methods may comprise selecting and/or applying a lifestyle regime, dietary regime or therapeutic intervention to a dog following a determination that the dog has an increased mortality risk and/or decreased probability of a healthy lifespan compared to its chronological age.
  • the disease is an age-related disease.
  • the age-related disease osteoarthritis, dementia, cognitive dysfunction, pre-diabetic condition, diabetes, cancer, heart disease, obesity, gastrointestinal disorders, incontinence, kidney disease, sarcopenia, vision loss, hearing loss, osteoporosis, cataracts, cerebrovascular disease, and/or liver disease.
  • the method may optionally further comprise administering the lifestyle regime, dietary regime or therapeutic intervention to the dog.
  • the lifestyle regime may be a dietary intervention or a therapeutic modality.
  • an anti-aging lifestyle regime, dietary regime or therapeutic intervention may be effective for dogs based on chronological age, it may be particularly effective when applied to a dog with an increased mortality risk and/or decreased probability of a healthy lifespan compared to its chronological age.
  • the present method may advantageously enable the selection of a dog that has an increased likelihood to respond, or improved magnitude of response, to the anti-aging lifestyle regime, dietary regime or therapeutic intervention.
  • the lifestyle regime, dietary regime or therapeutic intervention may be selected based on a determination that the dog has an increased mortality risk and/or reduced probability of a healthy lifespan (i.e. increased biological age) compared to its chronological age.
  • the lifestyle regime, dietary regime or therapeutic intervention may be a dietary intervention.
  • the dietary intervention may be a calorie-restricted diet, a senior diet or a low protein diet.
  • the DNA methylation profile may be associated with increased biological age of (i) a tissue; (ii) an organ; or (iii) a physiological system, such as the immune, gastrointestinal, urinary, muscular, cardiovascular, and/or neurological system.
  • the present invention may allow a biological age, mortality risk and/or probability of a healthy lifespan to be determined based on markers of multiple organ systems and functions. Accordingly, the present methods may advantageously encompass a range of potential organ dysfunctions.
  • Evaluating the biological age, mortality risk and/or probability of a healthy lifespan of a dog allows one to test several aspects of the animal’s wellbeing. First, it can predict whether this animal is more likely to need a dietary or supplement-based intervention. It can also be used to test the efficacy of a dietary or supplement-based intervention on aging.
  • Figure 1 Identification of blood biomarkers predictive of mortality risk.
  • a cox proportional hazard model was fit for each of the 28 biomarkers assessed, including sex and breed class (small or medium). Values are adjusted for the p. value of each parameter to account for multiple comparison (by false discovery rate (fdr)). Parameters show are those with an adjusted fdr below 0.05.
  • Figure 2 Demonstration of biomarkers that contribute to the predictive ability of the multiparameter model for determining phenoage.
  • Figure 5 Phenoage advance (delta with chronological age) changes mid-life with a calorie- restricted diet. This changes earlier in females than males.
  • Figure 6 Validation of an illustrative epigenetic clock trained on a dataset including mortality (second generation epigenetic clock) of the present invention in a calorie restriction study. Delta corresponds to the residuals of the regression model of Chronological Age vs predicted phenoDNAmAge. Dogs on a calorie restriction have a significantly lower biological Age (lower delta) compared to dogs on a control diet.
  • Figure 7 Validation of an illustrative epigenetic clock trained on a dataset including mortality (second generation epigenetic clock) of the present invention in a calorie restriction study at 6 years old. Delta corresponds to the residuals of the regression model of Chronological Age vs predicted phenoDNAmAge. Dogs on a calorie restriction have a lower biological Age (lower delta) compared to dogs on a control diet.
  • Figure 8 Adjusting linear mixed effects model (DogID as random effect). Dogs on a calorie restriction have significantly lower biological Age compared to dogs on a control diet.
  • Figure 10 A Cox proportional Hazard model fitted using sex and delta phenoDNAmAge (residuals from chronologicalAge vs predicted phenoDNAmAge), stratified on breed class (Small or Medium) on the training set. An increase in delta is associated with a higher mortality risk
  • FIG 11 An illustrative epigenetic clock comprising the A) top 3, B) top 5, C) top 10, E) top 20 methylation sites from the full epigenetic clock correlates with chronological age
  • Figure 12 - Biological age predicted using an illustrative epigenetic clock trained on chronological age (first generation biological clock) of the present invention is highly correlated with chronological age
  • Figure 13 Validation of an illustrative first generation epigenetic clock of the present invention in a calorie restriction study.
  • Delta corresponds to the residuals of the regression model of Chronological Age vs predicted biological age using the first gen clock. Dogs on a calorie restriction have a significantly lower biological age (lower delta) compared to dogs on a control diet.
  • Figure 14 An illustrative first generation epigenetic clock comprising the A) top 3, B) top 5, C) top 10, D) top 20, E) top 50 methylation sites from a first generation epigenetic clock correlates with chronological age
  • the methods and systems disclosed herein can be used by veterinarians, health-care professionals, lab technicians, pet care providers and so on.
  • the present invention provides a method for determining a biological age, mortality risk and/or probability of a healthy lifespan of a dog; said method comprising: a) determining a biological age, mortality risk and/or probability of a healthy lifespan of the dog using the level of one or more biomarker(s) in one or more samples obtained from the dog, wherein the one or more biomarker(s) is selected from white blood cell count, serum albumin, serum alkaline phosphatase, serum creatine kinase, haemoglobin, haematocrit, mean corpuscular haemoglobin, serum glucose, mean red cell volume, serum globulin, serum calcium, platelet count, and/or red blood cell count; and b) determining a biological age, mortality risk and/or probability of a healthy lifespan for the dog using a DNA methylation profile from the dog.
  • the biological age, mortality risk and/or probability of a healthy lifespan of the dog determined in step a) and the biological age, mortality risk and/or probability of a healthy lifespan for the dog determined in step b) may be combined to provide a composite biological age, mortality risk and/or probability of a healthy lifespan for the dog.
  • a ‘composite mortality risk and/or probability of a healthy lifespan’ may refer to providing a single biological age, mortality risk and/or probability of a healthy lifespan for the dog based on the determinations made in step a) and step b) of the present method.
  • the present methods may comprise combining (i) a biological age, mortality risk and/or probability of a healthy lifespan of the dog determined using the level of one or more biomarker(s) as described herein; and (ii) a biological age, mortality risk and/or probability of a healthy lifespan for the dog using a DNA methylation profile from the dog to provide a combined determination of biological age, mortality risk and/or probability of a healthy lifespan for the dog.
  • the biological age, mortality risk and/or probability of a healthy lifespan is provided as a combined score.
  • the method may be performed - and optionally the combined score provided - using a computer system or a computer program product according to the present invention.
  • the biological age, mortality risk and/or probability of a healthy lifespan of the dog determined in step a) and the biological age, mortality risk and/or probability of a healthy lifespan for the dog determined in step b) may be combined using any suitable method.
  • the biological age, mortality risk and/or probability of a healthy lifespan of the dog determined in step a) and the biological age, mortality risk and/or probability of a healthy lifespan for the dog determined in step b) may be combined by calculating a linear weighted combination, average, geometric mean (square root of the product), harmonic mean (reciprocal of the mean of the reciprocals), maximum difference value, minimum difference value, or a combination of delta (for example the difference compared to chronological age or residuals of a linear model with chronological age).
  • the weights for a linear weighted combination may not be equal between the determination made for step a) and step b).
  • the weights can be optimized by practice that is routine in the art.
  • a combination may be calculated by calculating a delta (e.g. in years) which is the residuals from a linear model explaining chronological age, for one or more biomarkers (step a)) and a DNA methylation profile (step b)), separately and combining the delta using the methods described above.
  • a delta e.g. in years
  • a DNA methylation profile step b
  • delta values for step a) and step b) may be combined using: the average, geometric mean (square root of the product), harmonic mean (reciprocal of the mean of the reciprocals), maximum difference value, or minimum difference value.
  • delta values calculated as above may be transformed into categories such as - infinity, -2[, [-2; -1[, [-1 ;0[, [0;+1 [, [+1 ;+2[, [+2 + infinity. From these categories, each category can be attributed a score from e.g. 1 to 6 and the sum of the scores from both part a) and part b) is considered.
  • the average score, or weighted average score may be considered.
  • the number and size of categories may be further modified, such as having categories by 0.5 years of increment, or to have cut point at 0.5 and 1.5 for example
  • the categories can be binary, i.e. either lower or higher than 0, or lower/higher than 1 or 1 .5. The categories may then be combined to get a final category
  • the present invention may comprise combining one or more biomarkers and DNA methylation sites (suitably a DNA methylation profile) as described herein as inputs in a linear model to explain biological age, mortality risk and/or probability of a healthy lifespan of a dog.
  • Suitable linear models may be calculating using a machine learning framework.
  • the machine learning framework may comprise fitting a penalised regression to a training dataset of dogs with a known chronological age (and optionally breed and/or sex); for example using glmnet R package.
  • the machine learning framework may comprise fitting an elastic net regression to a training dataset of dogs with a known chronological age (and optionally breed and/or sex); for example using glmnet R package.
  • the machine learning framework may comprise fitting a penalised regression, such as an elastic net regression, of chronological age explained by one or more biomarkers and a DNA methylation profile, (and optionally breed, age and/or sex).
  • a penalised regression such as an elastic net regression
  • the machine learning framework may comprise fitting a penalised regression, such as an elastic net regression, of chronological age explained by one or more biomarkers and a DNA methylation profile, breed, age and sex.
  • a penalised regression such as an elastic net regression
  • the present methods are directed to canine subjects. Accordingly, the subject of the present invention is a dog.
  • the subject may be a feline subject. Accordingly, in the alternative aspects of the invention, the subject is a cat. All disclosures herein are equally applicable to a cat, unless stated otherwise. Breed
  • the present methods may utilise information regarding the breed of the dog.
  • the dog may be categorised as a toy, small, medium, large or giant breed - for example.
  • the dog breed may be categorised based on the weight of the dog.
  • the dog breed may be categorised based on the average weight of a dog for a given breed.
  • the dog may be categorised as a small or medium breed.
  • the categorisation is determined by the average weight of adult dogs of this breed.
  • a breed with an average weight below 10kg is categorised as a small breed and/or a breed with an average weight above 10kg is categorised as a medium breed.
  • the cat may be a domestic cat.
  • the cat may be a Domestic Shorthair cat.
  • the sex of the dog may be classified as male or female.
  • Chronological age may be defined as the amount of time that has passed from the subject’s birth to the given date. Chronological age may be expressed in terms of years, months, days, etc.
  • the present method may be applied to a dog of any chronological age.
  • the dog may be at least about 2 years old.
  • the dog may be at least about 2, at least about 3, at least about 4, at least about 5, at least about 6, at least about 7, at least about 8, at least about 9 or at least about 10 years old.
  • the dog may be at least about 7 years old.
  • the present invention comprises a step of providing or determining a DNA methylation profile from one or more samples obtained from a subject.
  • the sample for providing or determining a DNA methylation profile is a blood, hair follicle, buccal swab, faecal, saliva or tissue sample.
  • the sample for providing or determining a DNA methylation profile is a hair follicle, buccal swab or saliva sample.
  • sample types are particularly applicable if the sample is to be provided, for example, outside of a veterinarian environment - for example using a kit according to the present invention.
  • the sample for determining the level of one or more biomarkers as described herein is a blood sample.
  • the sample is derived from blood.
  • the sample may contain a blood fraction or may be whole blood.
  • the sample preferably comprises whole blood.
  • the sample may comprise a peripheral blood mononuclear cell (PBMC) or lymphocyte sample.
  • PBMC peripheral blood mononuclear cell
  • Techniques for collecting samples from a subject and extracting DNA (e.g. genomic DNA) from the sample are well known in the art.
  • part (a) and part (b) of the present methods are performed on the same sample type.
  • part (a) and part (b) of the present methods are performed using a blood sample.
  • part (a) and part (b) of the present methods are performed using the same blood sample.
  • At least part (a) of the present method is performed on a blood sample.
  • the present methods may be performed on one or more samples obtained from the subject.
  • the method may be performed using a first sample obtained at a given time point and a second sample obtained following a time interval after the first sample was obtained.
  • the method may be performed more than once, on samples obtained from the same dog over a time period.
  • samples may be obtained repeatedly once per month, once a year, or once every two years.
  • the samples may be obtained around once per year (e.g. during an annual veterinary health check). This may be useful in determining the effects of a particular treatment or change in lifestyle - such as a dietary intervention or a change in exercise regime.
  • the method may be applied to a sample obtained from a subject prior to a change in lifestyle (e.g. a dietary product intervention or a change in exercise regime).
  • the method may be applied to a sample obtained from a subject prior to, and after the e.g. dietary product intervention or change in exercise regime.
  • the method may also be applied to samples obtained at predetermined times throughout the e.g. dietary product intervention or change in exercise regime. These predetermined times may be periodic throughout the e.g. dietary product intervention or change in exercise regime, e.g. every day or three days, or may depend on the subject being tested.
  • biomarkers used in the present invention can be determined using standard methods in the art and are typically measured as part of standard blood tests to determine the disease status of an animal.
  • the biomarkers are commonly determined as part of a standard clinical complete blood count (cbc) and standard clinical blood chemistry analysis.
  • a complete blood count provides information about blood cells and their properties; for example red blood cells, white blood cells, and platelets.
  • An example complete blood count can comprise an automated process using flow cytometry or Coulter counter to determine cell number in the blood.
  • flow cytometry or Coulter counter to determine cell number in the blood.
  • such automated systems may also be capable of determining other blood biomarker readings depending on their complexity. Such systems are able to simultaneously measure blood cell counts as well as red blood cell volume, hemoglobin level, mean corpuscular hemoglobin level and hematocrit.
  • IDEXX Laboratories provide a hematology analyzer capable of determining white blood cell count (WBC), red blood cell count (RBC), platelet count (PLT), hemoglobin (HGB), hematocrit (HCT), mean red cell volume (MCV) and mean corpuscular hemoglobin (MCH) (IDEXX Laboratories Inc., ProCyte Dx Hematology Analyzer).
  • the levels of other biomarkers unrelated to blood cells can be measured using chemical tests, in particular using automated chemistry analyser systems. These methods may utilize colorimetry-based approaches for quantification.
  • IDEXX Laboratories provide an automated chemistry analyzer able to quantify serum Albumin, serum Alkaline Phosphatase, serum Creatine Kinase, serum glucose, serum globulin, and serum Calcium (IDEXX Laboratories Inc., Catalyst One Chemistry Analyzer).
  • methods for determining the level of a biomarker used in the present invention may comprise assays that result in spectrophotometric changes (for example, chemical or antibody-linked changes that result in detectable signals at certain wavelengths). Such tests can be highly automated and efficient, and form the basis of many normal veterinary health check.
  • the biomarker level may be determined after overnight fasting and measured using standard veterinary clinical practice.
  • the level of the individual biomarker species in the sample may be measured or determined by any suitable method known in the art.
  • mass spectrometry MS
  • antibody detection methods e.g. enzyme-linked immunoabsorbent assay (ELISA)
  • ELISA enzyme-linked immunoabsorbent assay
  • non-antibody protein scaffolds e.g. fibronectin scaffolds
  • radioimmuno-assay RIA
  • aptamers e.g. RNA detection methods
  • Other spectroscopic methods, chromatographic methods, labelling techniques, or quantitative chemical methods may also be used.
  • Suitable antibodies for use in methods described above are known in the art and/or may be generated using known techniques.
  • Suitable test methods for detecting antibody levels include, but are not limited to, an immunoassay such as an enzyme-linked immunosorbent assay, radioimmunoassay, Western blotting and immunoprecipitation.
  • White blood cells also termed leukocytes, are a type of cell that are found in the blood. They have various immune-related functions, dependent on their sub-type: monocytes, lymphocytes, neutrophils, basophils and eosinophils. White blood cells contain a nucleus, and have a variable cell-shape that is also dependent on sub-type. White blood cell count is the number of this type of cell per volume of blood.
  • White blood cell count measurements can be done manually on a blood smear using staining and microscopy techniques, but can also be carried out as part of an automated complete blood count (CBC).
  • IDEXX Laboratories provide an automated hematology analyzer capable of white blood cell count measurements.
  • increased white blood cell count may be associated with a negative effect on reducing mortality risk. Accordingly, increased white blood cell count may be associated an increased mortality risk.
  • Serum Albumin is a globular protein found in the blood. It is a 65 kDa protein comprised of three homologous domains. Albumin regulates oncotic pressure, preventing loss of fluid from the blood to the tissues, and acting as a transport protein for fatty acids, bilirubin, heme, heavy metals, hormones and certain drugs. Albumin is highly abundant in the blood, accounting for 25-50% of total plasma protein by weight, and is produced by the liver. Abnormally high or low levels of albumin in the blood can be indicative of liver or kidney disease.
  • increased serum albumin levels may be associated with a positive effect on reducing mortality risk. Accordingly, increased serum albumin levels may be associated a reduced mortality risk.
  • Alkaline Phosphatase is an enzyme that has an important role in liver metabolism and in skeletal development. It is a 86 kDa homodimeric protein. High levels of this protein in the blood can be indicative of liver damage or bone disease.
  • increased serum alkaline phosphatase levels may be associated with a negative effect on reducing mortality risk. Accordingly, increased serum alkaline phosphatase levels may be associated an increased mortality risk.
  • Creatine Kinase is an enzyme that is predominantly found in muscles. This enzyme converts creatine and ATP into phosphocreatine for use in rapid energy generation during muscular contraction. The presence of high levels of this enzyme in the blood can be indicative of muscle damage.
  • Hemoglobin is a transport protein in red blood cells. It consists of a tetramer of two alpha chains and two beta chains. Each peptide chain binds a heme group, which consists of a porphyrin ring with an iron ion bound. This group can reversibly bind oxygen which allows hemoglobin to function as an oxygen-transport carrier protein.
  • increased haemoglobin levels may be associated with a positive effect on reducing mortality risk. Accordingly, increased haemoglobin may be associated a reduced mortality risk.
  • Hematocrit is the percentage by volume of red blood cells in the blood. Hematocrit levels that fall outside normal values can be indicative of diseases or conditions that result in a greater or lesser proportion of red blood cells in the blood than normal. A high hematocrit can be indicative of conditions such as dehydration, for example; whilst a low hematocrit can be indicative of anemia, hemolysis or decreased production of red blood cells.
  • haematocrit typically expressed as a percentage of blood volume (%)
  • Measurement can be carried out manually using packed cell volume by centrifuging blood in a microhematocrit tube.
  • haematocrit can be calculated from mean red cell volume and the red blood cell count, both of which can be measured directly by modern hematology analyzers in a standard complete blood count (CBC).
  • CBC complete blood count
  • increased haematocrit levels may be associated with a positive effect on reducing mortality risk. Accordingly, increased haematocrit may be associated a reduced mortality risk.
  • Mean corpuscular haemoglobin is the average mass of haemoglobin per red blood cell. MCH values that are outside normal ranges can be indicative of certain diseases such as macrocytic or hypochromic anemias.
  • Methods of measuring MCH are well known in the art, and commonly comprise calculation from observed values of hemoglobin level and red blood cell count that can be measured during a complete blood count (CBC) carried out using a hematology analyzer as described above.
  • CBC complete blood count
  • increased MCH may be associated with a positive effect on reducing mortality risk. Accordingly, increased MCH may be associated a reduced mortality risk.
  • Serum glucose is a measure of the amount of glucose present in the blood.
  • the level of glucose in the blood is controlled by hormones such as insulin to keep glucose levels within normal ranges.
  • hormones such as insulin to keep glucose levels within normal ranges.
  • glucose levels in the blood are outside normal levels it can be indicative of disease such as diabetes mellitus.
  • increased serum glucose levels may be associated with a negative effect on reducing mortality risk. Accordingly, increased serum glucose levels may be associated an increased mortality risk.
  • Mean red cell volume is a measure of the average volume of a red blood cell in the blood.
  • MCV is a diagnostic criteria that can categorize a possible anemia into micro-, normo-, or macrocytic anemia and may help to identify an underlying disease or disorder. High MCV can be indicative of disorders such as vitamin B12 deficiency, whereas low MCV can be indicative of disorders such as iron deficiency.
  • mean red cell volume typically expressed in femtoliters (fL)
  • fL femtoliters
  • hematology analyzers e.g. IDEXX Laboratories Inc., ProCyte Dx Hematology Analyzer
  • CBC complete blood count
  • increased MCV may be associated with a positive effect on reducing mortality risk. Accordingly, increased MCV may be associated a reduced mortality risk.
  • Serum globulin is a measure of the concentration of globular protein in the blood. Globular proteins are secreted mainly by the liver and a smaller proportion are secreted by immune cells. Albumin is the most abundant of the serum globulins. The remaining serum globulins can be separated into fractions based on their behaviour in electrophoresis separation methods. Immunoglobulins are an important part of the immune system and are secreted by immune cells. Examples of other serum globulins are immune system proteins such as complement, hormones and carrier proteins such as ferritin. Changes in the total level of serum globulin proteins can be indicative of certain conditions or diseases. An overall rise in serum globulins can indicate infection and an inflammatory immune response, whereas a fall in levels can be indicative of bleeding, gastrointestinal disease or severe malnutrition.
  • increased serum globulin levels may be associated with a negative effect on reducing mortality risk. Accordingly, increased serum globulin levels may be associated an increased mortality risk.
  • Serum Calcium is a measure of the total concentration of calcium in the blood. Calcium in the blood can be ionized, complexed, or protein-bound. Calcium is required in the body for a wide range of intracellular and extracellular functions, including muscular contractions and blood clotting, and is a major component of bone. Calcium levels that are too high can be as a result of certain cancers or bone disorders, and calcium levels that are too low can be as a result of kidney disease, pancreatitis or decreased serum albumin.
  • increased serum calcium levels may be associated with a positive effect on reducing mortality risk. Accordingly, increased serum calcium levels may be associated a reduced mortality risk.
  • Platelets also known as thrombocytes, are small cells that are components of the blood. They are small cells that lack a nucleus, and are produced from the cytoplasm of bone marrow cells known as megakaryocytes. Platelets help the clotting process to stop bleeding at the sites of damaged blood vessels. Platelet count levels that are above or below the normal range can indicate disorders or diseases. In particular, decreased platelet count can occur as a result of certain infections, cancer, immune system disorders or pancreatitis.
  • Platelet count typically expressed in thousands of cells per microliter (10 A 3/uL)
  • Platelet count can be done manually on a blood smear using staining and microscopy methods, but are commonly carried out as part of an automated complete blood count (CBC).
  • CBC complete blood count
  • increased platelet count may be associated with a negative effect on reducing mortality risk. Accordingly, increased platelet count may be associated an increased mortality risk.
  • Red blood cells also known as red blood corpuscles, are the most abundant cells present in the blood. These cells do not contain a nucleus, and instead consist mainly of hemoglobin contained within the cell membrane to maximise their oxygen-carrying potential. Red blood cell counts that are above or below normal levels are indicative of disorders or disease. Low red blood count can indicate hemolysis, blood loss, or reduced production of red blood cells that can result from multiple causes. High red blood cell count can indicate a relative increase of red blood cells per volume of blood compared to normal, due to dehydration or increased red blood cell production.
  • Red blood cell count measurements typically expressed in thousands of cells per microliter (10 A 3/uL), are well known in the art. Red blood cell count measurements can be done manually on a blood smear using microscopy, but are commonly carried out as part of an automated complete blood count (CBC).
  • CBC complete blood count
  • increased red blood cell count may be associated with a positive effect on reducing mortality risk. Accordingly, increased red blood cell count may be associated a reduced mortality risk.
  • biomarkers may have predictive value in the methods of the present invention
  • the quality and/or the predictive power of the methods may be improved by combining values from multiple biomarkers.
  • the present method may involve determining the level of at least two biomarkers from those described herein.
  • the method may comprise determining the level of two or more biomarkers selected from white blood cell count, serum albumin, serum alkaline phosphatase, serum creatine kinase, haemoglobin, haematocrit, mean corpuscular haemoglobin, serum glucose, mean red cell volume, serum globulin, serum calcium, platelet count, and/or red blood cell count in one or more samples.
  • biomarkers may include at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, at least eleven, at least twelve or at least thirteen biomarkers.
  • biomarkers may include one, two, three, four, five, six, seven, eight, nine, ten, eleven, twelve or thirteen biomarkers.
  • the present method may comprise determining the level of white blood cell count, serum albumin and serum alkaline phosphatase in one or more samples.
  • this combination of three biomarkers has been determined to provide a notable prediction of biological age, mortality risk and/or probability of a healthy lifespan.
  • the predictive ability may be further increased by incorporating one or more of the additional biomarkers selected from serum creatine kinase, haemoglobin, haematocrit, mean corpuscular haemoglobin, serum glucose, mean red cell volume, serum globulin, serum calcium, platelet count, and red blood cell count.
  • the present method may comprising determining the level of each of white blood cell count, serum albumin, serum alkaline phosphatase, serum creatine kinase, haemoglobin, haematocrit, mean corpuscular haemoglobin, serum glucose, mean red cell volume, serum globulin, serum calcium, platelet count, and red blood cell count in one or more samples. Combining the biomarker levels with further measures and/or characteristics
  • step (a) of the present method further comprises combining the level of the one or more biomarkers with one or more of the chronological age, breed and/or sex of the dog.
  • an improved model may be provided for the biological age, mortality risk and/or probability of a healthy lifespan of the dog.
  • levels of one or biomarkers as defined herein are determined for a sample from the dog and these levels are combined with the chronological age, breed and sex of the dog in order to determine a biological age, mortality risk and/or probability of a healthy lifespan for the dog.
  • the coefficient value for each parameter typically depends on the measurement units of all the variables in the model. As would be understood by the skilled person, the exact value for each coefficient value will therefore depend on, for example, the number and nature of the different parameters used in the model and the nature of the training data provided. Accordingly, routine statistical methods may be applied to a training data set in order to arrive at coefficient values for use in above formula. Such methods include, for example, computation of two gompertz functions on a training set (e.g. where the status of the dog (alive or dead) is known), one that models survival as a function of the selected biomarkers, chronological age, breed class (small or medium dog) and sex (model 1) and a second function that only considers chronological age, breed class and sex (model 2). These models may be fit using the flexsurv package (v 2.1) in the R software environment.
  • a negative coefficient for a given biomarker means that a higher level of the biomarker has a positive effect on reducing mortality risk and/or a lower level of the biomarker has a negative effect on reducing mortality risk.
  • a positive coefficient for a given biomarker means that a higher level of the biomarker has a negative effect on reducing mortality risk and/or a lower level of the biomarker has a positive effect on reducing mortality risk.
  • the phenotypic age may be defined as the time variable (“chronological age”) at which the survival probability of the animal given by model 2 is equal to the survival probability at their chronological age given by the model 1.
  • the phenotypic age (i.e. phenoage) of the dog may be expressed in terms of years, months, days, etc.
  • the biological age, mortality risk and/or probability of a healthy lifespan is represented as the difference between phenoage and chronological age of the dog. This difference may be referred to as the phenoage advance of the dog.
  • an increase in phenoage compared to chronological age may be indicative of an increased mortality risk for the dog.
  • a decrease in phenoage compared to chronological age may be indicative of a decreased mortality risk for the dog.
  • the present inventors determined that the difference between phenoage and chronological age (phenoage advance) was associated with a significant increase in mortality risk, and the magnitude of the effect was calculated to be a hazard ratio of 1.75 for a 1 year increase in phenoage compared to chronological age (see Example 3). In other words, the inventors determined that a 1 year increase in phenoage vs chronological age was associated with a risk of mortality 75% higher at any given point in life.
  • the method may comprise determining the white blood cell count in one or more samples obtained from the cat.
  • the method may further comprise determining the level of one or more biomarkers selected from hemoglobin, serum urea nitrogen, serum AST, serum chloride, serum total bilirubin, serum globulin, serum sodium, serum cholesterol, serum potassium, serum alkaline phosphatase, serum GGT, and/or red blood cell count in one or more samples.
  • the method may comprise determining the level of hemoglobin in one or more samples obtained from the cat.
  • the method may further comprise determining the level of one or more biomarkers selected from white blood cell count, serum urea nitrogen, serum AST, serum chloride, serum total bilirubin, serum globulin, serum sodium, serum cholesterol, serum potassium, serum alkaline phosphatase, serum GGT, and/or red blood cell count in one or more samples.
  • the method may comprise determining the level of serum urea nitrogen in one or more samples obtained from the cat.
  • the method may further comprise determining the level of one or more biomarkers selected from white blood cell count, hemoglobin, serum AST, serum chloride, serum total bilirubin, serum globulin, serum sodium, serum cholesterol, serum potassium, serum alkaline phosphatase, serum GGT, and/or red blood cell count in one or more samples.
  • the method may comprise determining the level of serum AST in one or more samples obtained from the cat.
  • the method may further comprise determining the level of one or more biomarkers selected from white blood cell count, hemoglobin, serum urea nitrogen, serum chloride, serum total bilirubin, serum globulin, serum sodium, serum cholesterol, serum potassium, serum alkaline phosphatase, serum GGT, and/or red blood cell count in one or more samples.
  • the method may comprise determining the level of serum chloride in one or more samples obtained from the cat.
  • the method may further comprise determining the level of one or more biomarkers selected from white blood cell count, hemoglobin, serum urea nitrogen, serum AST, serum total bilirubin, serum globulin, serum sodium, serum cholesterol, serum potassium, serum alkaline phosphatase, serum GGT, and/or red blood cell count in one or more samples.
  • the method may comprise determining the level of serum total bilirubin in one or more samples obtained from the cat.
  • the method may further comprise determining the level of one or more biomarkers selected from white blood cell count, hemoglobin, serum urea nitrogen, serum AST, serum chloride, serum globulin, serum sodium, serum cholesterol, serum potassium, serum alkaline phosphatase, serum GGT, and/or red blood cell count in one or more samples.
  • the method may comprise determining the level of serum globulin in one or more samples obtained from the cat.
  • the method may comprise determining the serum sodium level in one or more samples obtained from the cat.
  • the method may further comprise determining the level of one or more biomarkers selected from white blood cell count, hemoglobin, serum urea nitrogen, serum AST, serum chloride, serum total bilirubin, serum globulin, serum cholesterol, serum potassium, serum alkaline phosphatase, serum GGT, and/or red blood cell count in one or more samples.
  • the method may comprise determining the serum cholesterol in one or more samples obtained from the cat.
  • the method may further comprise determining the level of one or more biomarkers selected from white blood cell count, hemoglobin, serum urea nitrogen, serum AST, serum chloride, serum total bilirubin, serum globulin, serum cholesterol, serum potassium, serum alkaline phosphatase, serum GGT, and/or red blood cell count in one or more samples.
  • the method may comprise determining the level of serum potassium in one or more samples obtained from the cat.
  • the method may further comprise determining the level of one or more biomarkers selected from white blood cell count, hemoglobin, serum urea nitrogen, serum AST, serum chloride, serum total bilirubin, serum globulin, serum cholesterol, serum alkaline phosphatase, serum GGT, and/or red blood cell count in one or more samples.
  • the method may comprise determining the level of serum alkaline phosphatase in one or more samples obtained from the cat.
  • the method may further comprise determining the level of one or more biomarkers selected from white blood cell count, hemoglobin, serum urea nitrogen, serum AST, serum chloride, serum total bilirubin, serum globulin, serum cholesterol, serum potassium, serum GGT, and/or red blood cell count in one or more samples.
  • the method may comprise determining the level of serum GGT in one or more samples obtained from the cat.
  • the method may further comprise determining the level of one or more biomarkers selected from white blood cell count, hemoglobin, serum urea nitrogen, serum AST, serum chloride, serum total bilirubin, serum globulin, serum cholesterol, serum potassium, serum alkaline phosphatase, and/or red blood cell count in one or more samples.
  • the method may comprise determining the red blood cell count in one or more samples obtained from the cat.
  • the method may further comprise determining the level of one or more biomarkers selected from white blood cell count, hemoglobin, serum urea nitrogen, serum AST, serum chloride, serum total bilirubin, serum globulin, serum cholesterol, serum potassium, serum alkaline phosphatase, and/or serum GGT in one or more samples.
  • the method may comprise determining the level of each of white blood cell count, serum haemoglobin, serum urea nitrogen and serum AST.
  • the method may comprise determining the level of one or more further biomarkers selected from haematocrit, red blood cells count, serum albumin and/or mean corpuscular hemoglobin concentration in the one or more samples obtained from the cat.
  • the method comprises determining the level of each of white blood cell count, haemoglobin, serum urea nitrogen, serum AST, serum chloride, serum total bilirubin, serum globulin, haematocrit, red blood cells count, serum albumin and mean corpuscular hemoglobin concentration.
  • the method may comprise: a. determining the level of the following biomarkers; white blood cell count, haemoglobin, serum urea nitrogen, serum AST, serum chloride, serum total bilirubin, serum globulin, red blood cell count, serum sodium, serum cholesterol, serum potassium, serum alkaline phosphatase, and serum GGT in one or more samples obtained from the cat; and b. determining a phenotypic age (Phenoage) of the cat using formula (1): where xb is the sum of the value of each biomarker(s), multiplied by their respective coefficients according to formula (2): p
  • DNA methylation is the process by which a methyl group (CH3) is added covalently to a cytosine base that is part of a DNA molecule. In vivo, this process is catalysed by a family of DNA methyltransferases (Dnmts), that generate the modified cytosine by transfer of a methyl group from S-adenyl methionine (SAM). The cytosine is modified on the 5 th carbon atom, and the modified residue is known as 5-methylcytosine (5mC). The DNA methylation may also comprise 5-hydroxymethylcytosine (5hmc).
  • Dnmts DNA methyltransferases
  • SAM S-adenyl methionine
  • the cytosine is modified on the 5 th carbon atom, and the modified residue is known as 5-methylcytosine (5mC).
  • the DNA methylation may also comprise 5-hydroxymethylcytosine (5hmc).
  • DNA methylation is an example of an epigenetic mechanism, i.e. it is capable of modifying gene expression without modification of the underlying DNA sequence.
  • DNA methylation can, for example, inhibit the expression of genes by acting as a recruitment signal for repressive factors, or by directly blocking transcription factor recruitment.
  • DNA methylation predominantly occurs in the genome of somatic mammalian cells at sites of adjacent cytosine and guanine that form a dinucleotide (CpG). While non-CpG methylation is observed in embryonic development, in the adult these modifications are much reduced in most cell types.
  • CpG islands are stretches of DNA that have a high CpG density, but are generally unmethylated. These regions are associated with promoter regions, particularly promoter regions of housekeeping genes, and are thought to be maintained in a permissive state to allow gene expression.
  • DNA methylation has been found to vary with age in humans and other animals. Aged mammalian tissues show overall DNA hypomethylation, which is considered to be due to a gradual loss or mis-targeting of DMNT1 methyltransferase activity, but local hypermethylation of CpG islands. Local hypermethylation can result in repression of certain genes and this can contribute towards age-related disease.
  • the link between epigenetic changes in DNA methylation with age allows the estimation of a “biological age” using “DNA methylation clocks”. Generally, these clocks have been trained against chronological age using supervised machine learning approaches, and deviations of the “clock age” from the actual chronological age for an individual is considered an indicator of “biological” age. This correlates with the chronological age of the individual, but deviations from correlation can indicate potential risk of age-related disease or illness in individuals.
  • the detection of specific methylated DNA can be accomplished by multiple methods (see e.g. Zuo et al., 2009; Epigenomics. 1(2):331-345) and Rauluseviciute et al.’, Clinical Epigenetics; 2019; 11(193)).
  • a number of methods are available for detection of differentially methylated DNA at specific loci in samples such as blood, urine, stool or saliva. These methods are able to distinguish 5-methyl cytosine or methylated DNA from unmethylated DNA, and subsequently quantify the proportion of methylated and unmethylated DNA for a particular genomic site.
  • the present methods may comprise determining a DNA methylation profile for dog using any suitable method. Suitable methods include, but are not limited to, those described below.
  • enzymatic approaches are used to detect 5mC and 5hmC.
  • Enzymatic Methyl-seq EM-seq
  • EM-seq Enzymatic Methyl-seq
  • 5mC is oxidized to 5hmC, then 5fC and finally 5caC by the activity of Tet methylcytosine dioxygenase 2 (TET2).
  • TET2 Tet methylcytosine dioxygenase 2
  • apolipoprotein B mRNA editing enzyme catalytic polypeptide-like 3A (APOBEC3A) is used to deaminate cytosines, but is unable to deaminate the oxidised or glycosylated forms of 5mC and 5hmC. Only unmethylated cytosines are deaminated to form uracil bases.
  • the DNA fragments may be generated from mechanical shearing and end- repaired, A-tailed, and ligated to sequencing adaptors, which can be carried out using the NEBNext® DNA Ultra II reagents (NEB), for example.
  • NEB NEBNext® DNA Ultra II reagents
  • the deaminated single-stranded DNA may be amplified by PCR reactions, using polymerase such as NEBNext® Q5U TM which can amplify uracil containing templates, and the resulting library can be sequenced or analysed in an identical manner to the DNA sample generated by bisulfite sequencing.
  • the output of EM-seq is generally the same as whole genome bisulfite sequencing, but with the use of less DNA-damaging reagents, which consequently reduces sample loss, and can outperform bisulfite-conversion prepared samples in coverage, sensitivity and accuracy of cytosine methylation calling.
  • An illustrative EM-seq method is described by Vaisvila et al. (Genome Research; 2021 ; 31 :1-10).
  • Bisulfite conversion utilizes the selective conversion of unmethylated cytosines to uracil when treated with sodium bisulfite.
  • Denatured DNA is treated with sodium bisulfite, which converts all unmodified cytosines to uracil, and subsequent PCR amplification converts these residues to thymines.
  • Analysing the produced DNA sequences can be done via many different methods, examples of which include but are not limited to: denaturing gel electrophoresis, single-strand conformation polymorphism, melting curves, fluorescent real-time PCR (MethyLight), MALDI mass spectrometry, array hybridization, and sequencing (e.g. Whole Genome Bisulfite Sequencing WGBS).
  • restriction enzymes include, for example, restriction landmark genomic scanning (RLGS) (Costello et al., 2000; Nat Genet.;24(2):132-8), methylation-sensitive representational difference analysis (MS-RDA) (Ushijima et al., Proc Natl Acad Sci U S A. 1997 Mar 18;94(6):2284-9), and differential methylation hybridization (DMH) (Huang et al., Cancer Res. 1997 Mar 15;57(6): 1030-4). Restriction endonucleases can be methylation dependent in their digestion activity. This specificity can be used to differentiate methylated and unmethylated sequences. Certain restriction enzymes, for example BstUI, HpaW and Not ⁇ are sensitive to methylated recognition sequences. Others, such as /Wc/BC, are specific for methylated sequences.
  • differential methylation hybridisation (Huang et al., as above]) requires an initial fragmentation of the genome with a bulk genome restriction enzyme, such as Mse ⁇ , which fragments the genome into lengths of less than 200 bp. Following this step, the genome fragments are digested using a methylation-sensitive restriction endonuclease (MREs), or in some versions of the technique, a cocktail of MREs to improve coverage. Depending on the specificity of enzyme or enzymes used, either the methylated or the unmethylated sequences will be degraded. Digested sequences will not be amplified in a subsequent PCR step. The resultant PCR products are suitable for further processing and analysis by sequencing or microarray hybridisation in combination with fluorescent dyes.
  • MREs methylation-sensitive restriction endonuclease
  • the present methods utilise a DNA methylation profile generating by a method comprising the use of one or more MREs.
  • Suitable comparators can be used to investigate methylation state between conditions. DNA from healthy subjects can be compared with aged or diseased subjects to detect changes in methylation state (Huang et al., Hum Mol Genet. 1999 Mar;8(3):459-70). Alternatively, a methylation-insensitive version of the secondary digest enzyme, such as the HpaW isoschizomer Msp ⁇ , can be used to generate a control sample, so that intra- or inter- genomic DNA methylation comparisons can be made (Khulan et al., Genome Res. 2006 Aug; 16(8): 1046-55).
  • methods for detecting methylation include randomly shearing or randomly fragmenting the genomic DNA, cutting the DNA with a methylation-dependent or methylation-sensitive restriction enzyme and subsequently selectively identifying and/or analyzing the cut or uncut DNA.
  • Selective identification can include, for example, separating cut and uncut DNA (e.g., by size) and quantifying a sequence of interest that was cut or, alternatively, that was not cut.
  • the method can encompass amplifying intact DNA after restriction enzyme digestion, thereby only amplifying DNA that was not cleaved by the restriction enzyme in the area amplified.
  • amplification can be performed using primers that are gene specific.
  • adaptors can be added to the ends of the randomly fragmented DNA, the DNA can be digested with a methylationdependent or methylation-sensitive restriction enzyme, intact DNA can be amplified using primers that hybridize to the adaptor sequences.
  • a second step can be performed to determine the presence, absence or quantity of a particular gene in an amplified pool of DNA.
  • the DNA is amplified using real-time, quantitative PCR.
  • the digestion of nucleic acid is detected by selective hybridization of a probe or primer to the undigested nucleic acid.
  • the probe selectively hybridizes to both digested and undigested nucleic acid but facilitates differentiation between both forms, e.g., by electrophoresis.
  • Suitable detection methods for achieving selective hybridization to a hybridization probe include, for example, Southern or other nucleic acid hybridization.
  • Suitable hybridization conditions may be determined based on the melting temperature (Tm) of a nucleic acid duplex comprising the probe.
  • Tm melting temperature
  • optimum hybridization reaction conditions should be determined empirically for each probe, although some generalities can be applied.
  • hybridizations employing short oligonucleotide probes are performed at low to medium stringency.
  • a high stringency is defined herein as being a hybridization and/or wash carried out in about 0.1 x SSC buffer and/or about 0.1% (w/v) SDS, or lower salt concentration, and/or at a temperature of at least 65°C., or equivalent conditions.
  • Reference herein to a particular level of stringency encompasses equivalent conditions using wash/hybridization solutions other than SSC known to those skilled in the art.
  • RRBS Reduced representation bisulfite sequencing
  • the method involves digestion of DNA using the methylation-insensitive Mspl prior the bisulfite conversion and sequencing.
  • Mspl to digest genomic DNA results in fragments that always start with a C (if the cytosine is methylated) or a T (if a cytosine was not methylated and was converted to a uracil in the bisulfite conversion reaction).
  • the base composition is skewed due to the biased frequencies of C and T within the samples.
  • Various software for alignment and analysis is available, such as Maq, BS Seeker, Bismark or BSMAP. Alignment to a reference genome allows the programs to identify base pairs within the genome that are methylated. Affinity Enrichment Based Methods
  • Distinction of methylated from unmethylated DNA can be accomplished by the use of antibodies, such as anti-5mC, and/or methylated-CpG binding proteins, that contain a methyl- CpG-binding domain (MBD).
  • MBD-domain proteins are able to specifically isolate methylated DNA over unmethylated DNA. Methods that utilize antibodies are commonly referred to as MeDIP, whilst methods utilizing methylated-CpG binding proteins are often known as MBD or MIRA approaches.
  • affinity enrichment-based methods such as MethylCap-Seq or MBD-Seq. These methods reduce sample complexity by using a salt gradient to elute methylated DNA fragments in a methy-CpG-abundance dependent manner, segregating CpG islands and other highly methylated loci from less CpG dense loci. The fractions can then be sequenced separately improving sequence coverage.
  • Singlemolecule real-time (SMRT) DNA sequencing is available, for example the Sequel systems from Pacific Biosciences and has been shown to be able to identify modified bases such as methylated cytosine based on the polymerase kinetics.
  • Nanopore sequencing devices such as the MinlON nanopore sequencer from Oxford Nanopore Technologies, which are able to individually sequence long strands of DNA, are also able to detect de novo base modifications, including methylation.
  • a DNA methylation site may refer to the presence or absence of a 5mC at a single cytosine, suitably a single CpG dinucleotide.
  • a DNA methylation site may refer to the presence or absence of methylation (i.e. the number of 5mC or percentage of 5mC) across a plurality of CpG sites within a DNA region.
  • a DNA site methylation site may refer to the level of methylation (i.e. the number of 5mC or percentage of 5mC) across a plurality of CpG sites within a DNA region.
  • a “DNA region” may refer to a specific section of genomic DNA. These DNA regions may be specified either by reference to a gene name or a set of chromosomal coordinates. Both the gene names and the chromosomal coordinates would be well known to, and understood by, the person of skill in the art.
  • gene names and/or coordinates may be based on the “Tasha” dog reference genome (https://www.ncbi.nlm.nih.gOv/assembly/GCF_000002285.5; Jagannathan et a! , Genes (Bsael); 2021 ; 12(6); 847).
  • the DNA region may define a section of DNA in proximity to the promoter of a gene, for example.
  • Promoter regions are known to be rich in CpG.
  • the DNA region may refer to about 3kb upstream to about 3kb downstream; about 2kb upstream to about 2kb downstream; about 2kb upstream to about 1 kb downstream; about 2kb upstream to about 0.5kb downstream; about 1kb upstream to about 0.5kb downstream; about 0.5kb upstream to about 0.5kb downstream of a promoter.
  • the DNA region may refer to about 1 kb upstream to about 0.5kb downstream of a promoter.
  • the DNA region may comprise or consist of CpG sites that are less than about 5000, less than about 4000, less than about 3000, less than about 2000, less than about 1000, less than about 500, or less than about 200 bases apart.
  • the DNA region may comprise or consist of CpG sites that are between about 200 to about 5000, about 200 to about 4000, about 200 to about 3000, about 200 to about 2000, or about 200 to about 1000 bases apart.
  • the DNA region may comprise one or more CpG islands.
  • the DNA region may consist of a CpG island.
  • a “CpG island” may refer to a DNA region comprising at least 200 bp, a GC percentage greater than 50%, and an observed-to-expected CpG ratio greater than 60%.
  • the DNA methylation sites do not comprise X and/or Y chromosome CpGs.
  • the DNA methylation sites do not comprise CpGs known to comprise a SNP at the CpG.
  • each of the genes/DNA regions detailed above should be understood as a reference to all forms of these molecules and to fragments or variants thereof.
  • some genes are known to exhibit allelic variation between individuals or single nucleotide polymorphisms.
  • Variants include nucleic acid sequences from the same region sharing at least 90%, 95%, 98%, 99% sequence identity i.e. having one or more deletions, additions, substitutions, inverted sequences etc. relative to the DNA regions described herein. Accordingly, the present invention should be understood to extend to such variants which, in terms of the present applications, achieve the same outcome despite the fact that minor genetic variations between the actual nucleic acid sequences may exist between individuals.
  • the present invention should therefore be understood to extend to all forms of DNA which arise from any other mutation, polymorphic or allelic variation.
  • the assays can be designed to screen for specific DNA. It is well within the skill of the person in the art to choose which strand to analyse and to target that strand based on the chromosomal coordinates. In some circumstances, assays may be established to screen both strands.
  • “Methylation status” may be understood as a reference to the presence, absence and/or quantity of methylation at a particular nucleotide, or nucleotides, within a DNA region.
  • the methylation status of a particular DNA sequence e.g. DNA region as described herein
  • the methylation status can optionally be represented or indicated by a “methylation value.”
  • DNA methylation may be determined using an EM-Seq strategy.
  • a methylation level can be determined as the fraction of 'C bases out of 'C'+'ll' total bases at a target CpG site "i" following an enzyme and APOBEC3A conversion treatment.
  • the methylation level can be determined as the fraction of 'C bases out of 'C'+'T' total bases at site "i" following enzyme and APOBEC3A conversion treatment and subsequent nucleic acid amplification.
  • the mean methylation level at each site may then be evaluated to determine if one or more threshold is met.
  • a methylation level in particular when bisulfite conversion and sequencing methods are used, can be determined as the fraction of 'C bases out of 'C'+'ll' total bases at a target CpG site "i" following a bisulfite treatment. In other embodiments, the methylation level can be determined as the fraction of 'C bases out of 'C'+T total bases at site "i" following a bisulfite treatment and subsequent nucleic acid amplification. The mean methylation level at each site may then be evaluated to determine if one or more threshold is met.
  • a methylation value can be generated, for example, by quantifying the amount of intact DNA present following restriction digestion with a methylation dependent restriction enzyme.
  • a value i.e. , a methylation value, for example from the above described example, represents the methylation status and can thus be used as a quantitative indicator of the methylation status. This is of particular use when it is desirable to compare the methylation status of a sequence in a sample to a threshold value.
  • the present invention is not to be limited by a precise number of methylated residues that are considered to indicative of biological age, because some variation between samples will occur.
  • the present invention is also not necessarily limited by positioning of the methylated residue (e.g. a specific methylation site).
  • a screening method can be employed which is specifically directed to assessing the methylation status of one or more specific cytosine residues or the corresponding cytosine at position n+1 on the opposite DNA strand.
  • Determining a DNA methylation profile may comprise a step of enriching a DNA sample for selected DNA regions.
  • the methods may comprise a step of enriching a DNA sample for DNA regions comprising the DNA methylation sites which comprise the DNA methylation profile.
  • Suitable enrichment methods are known in the art and include, for example, amplification or hybridisation based methods.
  • Amplification enrichment typically refers to e.g. PCR based enrichment using primers against the DNA regions to be enriched.
  • Any suitable amplification format may be used, such as, for example, polymerase chain reaction (PCR), rolling circle amplification (RCA), inverse polymerase chain reaction (iPCR), in situ PCR, strand displacement amplification, or cycling probe technology.
  • Hybridisation enrichment or capture-based enrichment typically refers to the use of hybridisation probes (or capture probes) that hybridise to DNA regions to be enriched.
  • the hybridisation probe(s) may be attached directly to a solid support, or may comprise a moiety, e.g. biotin, to allow binding to a solid support suitable for capturing biotin moieties (e.g. beads coated with streptavidin).
  • DNA comprising sequence which is complementary to the probe may captured thus allowing to separate DNA comprising DNA regions of interest from not comprising the DNA regions of interest.
  • the DNA regions may be DNA regions in proximity to gene promoters.
  • an array used herein can vary depending on the probe composition and desired use of the array.
  • the nucleic acids (or CpG sites) detected in an array can be at least 10, 100, 1 ,000, 10,000, 0.1 million, 1 million, 10 million, 100 million or more.
  • the nucleic acids (or CpG sites) detected can be selected to be no more than 100 million, 10 million, 1 million, 0.1 million, 10,000, 1 , 000, 100 or less. Similar ranges can be achieved using nucleic acid sequencing approaches such as those known in the art; e.g. Next Generation or massively parallel sequencing.
  • an enrichment step may be performed before or after the step of separating or differentially treating methylated and unmethylated DNA.
  • enriching or “enrichment” for “DNA” or “DNA regions” means a process by which the (absolute) amount and/or proportion of the DNA comprising the desired sequence(s) is increased compared to the amount and/or proportion of DNA comprising the desired sequence(s) in the starting material.
  • enrichment by amplification increases the amount and proportion of the desired sequence(s).
  • enrichment by capturebased enrichment increases the proportion of DNA comprising the desired sequence(s).
  • the present methods may further comprise the step of identifying the sites which were methylated or unmethylated (i.e. in the original sample).
  • the identification step may comprise any suitable method known in the art, for example array detection or sequencing (e.g. next generation sequencing).
  • a sequencing identification step preferably comprises next generation sequencing (massively parallel or high throughput sequencing).
  • Next generation sequencing methods are well known in the art, and in principle, any method may be contemplated to be used in the invention.
  • Next generation sequencing technologies may be performed according to the manufacturer's instructions (as e.g. provided by Roche, Illumina, Applied Biosystems, PacBio, Oxford Nanopore or MGI).
  • the sample is treated by converting DNA methylation using enzymatic reactions, performing whole genome library preparation and measuring the methylation profile by sequencing (EM-Seq).
  • the sample is treated by converting DNA methylation using enzymatic reactions, performing whole genome library preparation, hybridizing the whole-genome-converted library preparation to capture probes (preferably capture probes capable of capturing DNA regions in proximity to gene promoters); and measuring the methylation profile by sequencing (EM-Seq).
  • a “DNA methylation profile” or “methylation profile” may refer to the presence, absence, quantity or level of 5mC at one or more DNA methylation sites.
  • “methylation profile” refers to the presence, absence, quantity or level of 5mC at a plurality of DNA methylation sites.
  • the presence, absence, quantity or level of 5mC at each individual DNA methylation site within the plurality of sites may be assessed and contribute to the determination of the biological age, mortality risk and/or probability of a healthy lifespan of the dog. The quality and/or the power of the methods may thus be improved by combining values from multiple DNA methylation markers.
  • the present biological clock comprises the methylation profile from a plurality of methylation sites.
  • presence or absence of 5mC from at least 3, at least 5, at least 10, at least 20, at least 50, at least 100, at least 200, at least 500, at least 1000, at least 2000, at least 5000, at least 10000, at least 50000, at least 10000, at least 250000, or at least 500000 DNA methylation sites may be used to determine biological age, mortality risk and/or probability of a healthy lifespan of the dog.
  • the methylation profile may refer to the presence or absence of 5mC from at least 100, at least 200, at least 500, at least 1000 or at least 2000 DNA methylation sites.
  • the methylation profile may refer to the presence or absence of 5mC from about 100, about 200, about 500, about 1000 or about 2000 DNA methylation sites.
  • an initial methylation profile may be processed or streamlined to produce a restricted methylation profile which is then used to generate the biological clock.
  • an initial methylation profile may be processed or streamlined by - for example - using DNA regions rather than individual cytosines, by selecting a subset of methylation sites that are associated with a particular physiological or biochemical pathway, performing a correlation analysis and retaining one or more representative DNA methylation sites per cluster, or performing differential analysis to pre-select DNA methylation sites or retain DNA methylation sites that vary more between young and old dogs,
  • the DNA region(s) may be any DNA region(s) as defined herein.
  • the methylation profile may refer to DNA methylation sites of genes that are associated with a particular physiological or biochemical pathway.
  • the methylation profile may enable a biological age of a particular tissue, organ, or physiological system to be determined. Determining a biological age for a particular tissue, organ or physiological system may advantageously allow the method to be utilised in a way which focuses on pathologies and diseases of that tissue, organ or physiological system. For example, if a particular breed of dog is known to be associated with muscular or cardiovascular disease, it may be advantageous to determine a biological age for that physiological system.
  • the physiological system may be the inflammatory, muscular, cardiovascular, and/or neurological system.
  • a biological age for a particular tissue, organ, or physiological system may be determined using a DNA methylation profile comprising, or consisting of, methylation sites from genes that are preferentially or specifically expressed by that tissue, organ, or physiological system.
  • Classifications of genes by a particular tissue, organ, or physiological system are publicly available at, for example, Gene Ontology (http://geneontology.org/), the KEGG pathway database (https://www.genome.jp/kegg/), or MSIgDB (https://www.gsea- msigdb.org/gsea/msigdb/index.jsp).
  • a threshold selects those sites having the highest-ranked mean methylation values for epigenetic age predictors.
  • the threshold can be those sites having a mean methylation level that is the top 50%, the top 40%, the top 30%, the top 20%, the top 10%, the top 5%, the top 4%, the top 3%, the top 2%, or the top 1 % of mean methylation levels across all sites “i” tested for a predictor, e.g., a biological clock.
  • the threshold can be those sites having a mean methylation level that is at a percentile rank greater than or equivalent to 50, 60, 70, 80, 90, 95, 96, 97, 98, or 99.
  • a threshold can be based on the absolute value of the mean methylation level.
  • the threshold can be those sites having a mean methylation level that is greater than 99%, greater than 98%, greater than 97%, greater than 96%, greater than 95%, greater than 90%, greater than 80%, greater than 70%, greater than 60%, greater than 50%, greater than 40%, greater than 30%, greater than 20%, greater than 10%, greater than 9%, greater than 8%, greater than 7%, greater than 6%, greater than 5%, greater than 4%, greater than 3%, or greater than 2%.
  • the relative and absolute thresholds can be applied to the mean methylation level at each site "i" individually or in combination.
  • a subset of sites that are in the top 3% of all sites tested by mean methylation level and also have an absolute mean methylation level of greater than 6%.
  • the result of this selection process is a DNA methylation profile, of specific hypermethylated sites (e.g., CpG sites) that are considered the most informative for biological age, mortality risk and/or probability of a healthy lifespan determination.
  • the DNA methylation profile may comprise at least one methylation site as listed in Table 3.
  • Table 3 provides an illustrative epigenetic clock for determining a biological age, mortality risk and/or probability of a healthy lifespan of a dog. This may be referred to as a ‘second generation epigenetic clock’.
  • the DNA methylation profile may comprise at least one methylation site as listed in Table 8.
  • Table 8 provides an illustrative epigenetic clock for determining a biological age of a dog. This may be referred to as a ‘first generation epigenetic clock’.
  • the methylation site(s) may be defined as the methylation markers present in any one or more of SEQ ID NO: 1-517.
  • SEQ ID NO: 1-517 show the sequence either side of the methylation marker in the “Tasha” dog reference genome (https://www.ncbi.nlm.nih.gOv/assembly/GCF_000002285.5; Jagannathan et al.; Genes (Bsael); 2021 ; 12(6); 847).
  • the “CG” methylation marker is the 26 th and 27 th nucleotides in the sequence (i.e. there are 25 nucleotides preceding the methylation marker and 25 nucleotides following the methylation marker).
  • the methylation sites may be defined as the intervening position in the column labelled “Site” in Table 3.
  • the methylation marker is chr1 : 3844419.
  • the DNA methylation profile may comprise at least 3, at least 5, at least 10, at least 20, at least 50, at least 100, at least 150, at least 200 or preferably each of the methylation sites as listed in Table 3.
  • the DNA methylation profile may comprise the methylation sites chr2.32494387.32494389; chr22.46374563.46374565; and chr6.45773846.45773848. These sites are shown in Table 4.
  • the DNA methylation profile may comprise the methylation sites chr2.32494387.32494389; chr22.46374563.46374565; chr6.45773846.45773848; chr5.61645225.61645227; and chr3.70831746.70831748. These sites are shown in Table 5.
  • the DNA methylation profile may comprise the methylation sites chr2.32494387.32494389; chr22.46374563.46374565; chr6.45773846.45773848; chr5.61645225.61645227; chr3.70831746.70831748; chr15.10856498.10856500; chr16.8886545.8886547; chr3.46843750.46843752; chr20.44942213.44942215; and chr20.57347921.57347923. These sites are shown in Table 6.
  • the DNA methylation profile may comprise the methylation sites chr2.32494387.32494389; chr22.46374563.46374565; chr6.45773846.45773848; chr5.61645225.61645227; chr3.70831746.70831748; chr15.10856498.10856500; chr16.8886545.8886547; chr3.46843750.46843752; chr20.44942213.44942215; chr20.57347921.57347923; chr24.21051024.21051026; chr33.26512711.26512713; chr23.37987526.37987528; chr5.32347978.32347980; chr6.60675998.60676000; chr19.44679975.44679977; chr10.7411293.7411295; chr33.26512692.2
  • the DNA methylation profile may comprise the methylation sites chr2.32494387.32494389; chr22.46374563.46374565; chr6.45773846.45773848; chr5.61645225.61645227; chr3.70831746.70831748; chr15.10856498.10856500; chr16.8886545.8886547; chr3.46843750.46843752; chr20.44942213.44942215; chr20.57347921.57347923; chr24.21051024.21051026; chr33.26512711.26512713; chr23.37987526.37987528; chr5.32347978.32347980; chr6.60675998.60676000; chr19.44679975.44679977; chr10.7411293.7411295; chr33.26512692.2
  • the methylation marker is chr1 : 32205239.
  • the DNA methylation profile may comprise at least 3, at least 5, at least 10, at least 20, at least 50, at least 100, at least 150, at least 200 or preferably each of the methylation sites as listed in Table 8.
  • the DNA methylation profile may comprise the methylation sites chr2.32494387.32494389; chr6.45773846.45773848; and chr16.8886545.8886547. These sites are shown in Table 9.
  • the DNA methylation profile may comprise the methylation sites chr2.32494387.32494389; chr6.45773846.45773848; chr16.8886545.8886547 chr5.61645225.61645227; and chr15.10856498.10856500. These sites are shown in Table 10.
  • the DNA methylation profile may comprise the methylation sites chr2.32494387.32494389; chr6.45773846.45773848; chr16.8886545.8886547 chr5.61645225.61645227; chr15.10856498.10856500; chr33.26512711.26512713; chr20.57347921.57347923; chr12.12684190.12684192; chr24.30860619.30860621 ; and chr33.26512692.26512694. These sites are shown in Table 11.
  • the DNA methylation profile may comprise the methylation sites chr2.32494387.32494389; chr6.45773846.45773848; chr16.8886545.8886547 chr5.61645225.61645227; chr15.10856498.10856500; chr33.26512711.26512713; chr20.57347921 .57347923; chr12.12684190.12684192; chr24.30860619.30860621 ; chr33.26512692.26512694; chr10.7411293.7411295; chr1.22213697.22213699; chr5.32711703.32711705; chr24.21051024.21051026; chr5.21480151.21480153; chr17.33851462.33851464; chr3.46843750.46843752; chr13.37474592.37474594; chr13.
  • the DNA methylation profile may comprise the methylation sites chr2.32494387.32494389; chr6.45773846.45773848; chr16.8886545.8886547 chr5.61645225.61645227; chr15.10856498.10856500; chr33.26512711.26512713; chr20.57347921.57347923; chr12.12684190.12684192; chr24.30860619.30860621 ; chr33.26512692.26512694; chr10.7411293.7411295; chr1.22213697.22213699; chr5.32711703.32711705; chr24.21051024.21051026; chr5.21480151.21480153; chr17.33851462.33851464; chr3.46843750.46843752; chr13.37474592.37474594; chr
  • the present invention comprises utilising a DNA methylation profile to determine a biological age, mortality risk and/or probability of a healthy lifespan of a dog.
  • the present invention comprises utilising a DNA methylation profile to generate a biological clock which is associated with biological age, mortality risk and/or probability of a healthy lifespan.
  • the present biological clock may also be referred to as an ‘epigenetic clock’.
  • DNA methylation sites or a DNA methylation profile that is indicative of biological age, mortality risk and/or probability of a healthy lifespan may be achieved through training datasets and machine learning approaches, for example.
  • the machine learning approaches may be supervised machine learning approaches.
  • DNA methylation sites or a DNA methylation profile may be trained against a dataset comprising dogs of a known chronological age or mortality outcome (alive or dead) and chronological age.
  • the DNA methylation sites or a DNA methylation profile may be trained against a dataset comprising dogs of a known (i) chronological age or (ii) mortality outcome and chronological age in combination with known breed and/or sex.
  • models for DNA methylation sites or a DNA methylation profile indicative of mortality risk and/or probability of a healthy lifespan may be provided by training a dataset of methylation status at a plurality of DNA methylation sites against a training dataset of dogs with a known mortality outcome (alive or dead) and chronological age using a machine learning framework, and testing against a with-held cohort to validate the veracity of the model.
  • This type of epigenetic clock may be referred to as a ‘second generation epigenetic clock’.
  • the machine learning framework may comprise fitting a penalised model to a training dataset of dogs with a known mortality outcome (alive or dead) and chronological age (and optionally breed and/or sex); for example using glmnet R package.
  • the penalised model may be a penalized Cox regression, a Least Angle Regression path of solution (LARS) Cox regression or a penalized survival model; for example.
  • Least Angle Regression path of solution (LARS) Cox regression or a penalized survival model; for example.
  • the machine learning framework may comprise fitting a penalized Cox regression to a training dataset of dogs with a known mortality outcome (alive or dead) and chronological age (and optionally breed and/or sex); for example using glmnet R package.
  • the machine learning framework may comprise fitting a penalised model, preferably a penalized Cox regression, of known mortality outcome (alive or dead)/survival explained by a DNA methylation profile and chronological age, (and optionally breed and/or sex).
  • a penalised model preferably a penalized Cox regression, of known mortality outcome (alive or dead)/survival explained by a DNA methylation profile and chronological age, (and optionally breed and/or sex).
  • the machine learning framework may comprise fitting a penalised model, preferably a penalized Cox regression, of known mortality outcome (alive or dead)/survival explained by a DNA methylation profile, chronological age, breed and sex.
  • a penalised model preferably a penalized Cox regression, of known mortality outcome (alive or dead)/survival explained by a DNA methylation profile, chronological age, breed and sex.
  • the machine learning framework may be used to determine a model comprising a set of DNA methylation sites or a DNA methylation profile that is indicative of biological age, mortality risk and/or probability of a healthy lifespan.
  • the model may comprise the methylation status at a plurality of DNA methylation sites; wherein the methylation status at each site is considered in the model by multiplying by a coefficient value.
  • sex may be coded as a numerical value with 0 for female and 1 for male.
  • breed may be coded as a numerical value with 0 for small breeds and 1 for medium breeds.
  • the biological age of the dog may be expressed in terms of years, months, days, etc.
  • the coefficient value for each parameter typically depends on the measurement units of all the variables in the model. As would be understood by the skilled person, the value for each coefficient value will therefore depend on, for example, the number and nature of the different parameters used in the model and the nature of the training data provided. Accordingly, routine statistical methods may be applied to a training data set in order to arrive at coefficient values. Such methods include, for example, computation of two gompertz or weibull functions on a training set (e.g. where the status of the dog (alive or dead) is known), one that models survival as a function of the methylation profile, chronological age, breed class (small or medium dog) and sex (model 1) and a second function that only considers chronological age, breed class and sex (model 2). These models may be fit using the flexsurv package (v 2.1) in the R software environment.
  • the biological age may be defined as the time variable (“chronological age”) at which the survival probability of the animal given by model 2 is equal to the survival probability at their chronological age given by the model 1.
  • Models for DNA methylation sites or a DNA methylation profile indicative of biological age, mortality risk and/or probability of a healthy lifespan may be provided by training a dataset of methylation status at a plurality of DNA methylation sites against a PhenoAge predicted at the age of DNA sample collection, and testing against a withheld cohort to validate the veracity of the model.
  • PhenoAge is calculated in step (a) of the present methods.
  • Methods for determining the PhenoAge of a cat are described in PCT/EP2023/061059. Calculation of PhenoAge takes into account the direct predictive value of blood biomarkers on mortality risk and/or probability of a healthy lifespan.
  • a given biomarker may not directly correlate with chronological age, but may be indicative of a particular pathological condition and thus an increased mortality risk and/or a probability of a reduced healthy lifespan.
  • a model for DNA methylation sites or a DNA methylation profile indicative of mortality risk and/or probability of a healthy lifespan trained against a PhenoAge may be provided in a two-step process.
  • a machine learning framework may comprise fitting a penalised model of a phenotypic age (PhenoAge) explained by one or more blood biomarkers as described herein and chronological age (and optionally sex and/or breed); for example using glmnet R package.
  • the machine learning framework may comprise fitting a penalised model of a phenotypic age (PhenoAge) explained by one or more blood biomarkers as described herein, chronological age, sex and breed.
  • the penalised model may be a penalized Cox regression, a Least Angle Regression path of solution (LARS) Cox regression or a penalized survival model; for example.
  • the machine learning framework may comprise fitting a penalised Cox regression of a phenotypic age (PhenoAge) explained by one or more blood biomarkers as described herein, chronological age, sex and breed.
  • the machine learning framework may comprise fitting a penalised regression of PhenoAge explained by a DNA methylation.
  • the machine learning framework may comprise fitting a penalised regression of PhenoAge explained by a DNA methylation profile.
  • the penalised regression may be an elastic net regression.
  • biomarkers may include at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, at least eleven, at least twelve or at least thirteen biomarkers.
  • biomarkers may include one, two, three, four, five, six, seven, eight, nine, ten, eleven, twelve or thirteen biomarkers.
  • DNA methylation sites or a DNA methylation profile may be combined with the level of one or more blood biomarkers described herein in order to generate a model indicative of mortality risk and/or probability of a healthy lifespan.
  • a model comprising a combination of a DNA methylation profile and the level of one or more blood biomarkers described herein may be provided by training a dataset of methylation status at a plurality of DNA methylation sites and the level of one or more blood biomarkers against a training dataset of dogs with a known mortality outcome (alive or dead) and chronological age, and testing against a with-held cohort to validate the veracity of the model.
  • the machine learning framework may comprise fitting a penalised regression to a training dataset of dogs with a known mortality outcome (alive or dead) and chronological age (and optionally breed and/or sex); for example using glmnet R package.
  • the machine learning framework may comprise fitting a penalized Cox regression to a training dataset of dogs with a known mortality outcome (alive or dead) and chronological age (and optionally breed and/or sex); for example using glmnet R package.
  • Models for DNA methylation sites or a DNA methylation profile indicative of biological age may be provided by training a dataset of methylation status at a plurality of DNA methylation sites against a training dataset of dogs with a known chronological age using a machine learning framework, and testing against a with-held cohort to validate the veracity of the model.
  • This type of epigenetic clock may be referred to as a ‘first generation epigenetic clock’.
  • the machine learning framework may comprise fitting a penalised regression to a training dataset of dogs with a known chronological age (and optionally breed and/or sex); for example using glmnet R package.
  • the machine learning framework may comprise fitting an elastic net regression to a training dataset of dogs with a known chronological age (and optionally breed and/or sex); for example using glmnet R package.
  • the machine learning framework may comprise fitting a penalised regression, such as an elastic net regression, of chronological age explained by a DNA methylation profile, (and optionally breed, age and/or sex).
  • a penalised regression such as an elastic net regression
  • the machine learning framework may comprise fitting a penalised regression, such as an elastic net regression, of chronological age explained by a DNA methylation profile, breed, age and sex.
  • a penalised regression such as an elastic net regression
  • the machine learning framework may be used to determine a model comprising a set of DNA methylation sites or a DNA methylation profile that is indicative of biological age.
  • the model may comprise the methylation status at a plurality of DNA methylation sites; wherein the methylation status at each site is considered in the model by multiplying by a coefficient value.
  • the coefficient value for each parameter typically depends on the measurement units of all the variables in the model. As would be understood by the skilled person, the value for each coefficient value will therefore depend on, for example, the number and nature of the different parameters used in the model and the nature of the training data provided. Accordingly, routine statistical methods may be applied to a training data set in order to arrive at coefficient values.
  • sex may be coded as a numerical value with 0 for female and 1 for male.
  • breed may be coded as a numerical value with 0 for small breeds and 1 for medium breeds.
  • the machine learning platform may comprise one or more deep neural networks.
  • Neural Networks are collections of neurons (also called units) connected in an acyclic graph. Neural Network models are often organized into distinct layers of neurons. For most neural networks, the most common layer type is the fully-connected layer in which neurons between two adjacent layers are fully pairwise connected, but neurons within a single layer share no connections.
  • One of the main features of deep neural networks is that neurons are controlled by non-linear activation functions. This non-linearity combined with the deep architecture make possible more complex combinations of the input features leading ultimately to a wider understanding of the relationships between them and as a result to a more reliable final output. Deep neural networks have been applied for many types of data ranging from structural data to chemical descriptors or transcriptomics data.
  • the machine learning platform comprises one or generative adversarial networks.
  • the machine learning platform comprises an adversarial autoencoder architecture.
  • the machine learning platform comprises a feature importance analysis for ranking DNA methylation site by their importance in biological age determination.
  • the biological age of the dog may be expressed in terms of years, months, days, etc.
  • the biological age, mortality risk and/or probability of a healthy lifespan is represented as the difference between biological age and chronological age of the dog.
  • the present methods may further comprise a step of comparing the difference in biomarkers and/or DNA methylation at one or more sites in the test sample to one or more reference or controls.
  • the level of a biomarker and/or the presence or absence of DNA methylation at one or more sites in the reference or control may be associated with a biological age or a predefined mortality risk and/or probability of a healthy lifespan.
  • the reference value is a value obtained previously for a subject or group of subjects with a known biological age or a mortality risk and/or probability of a healthy lifespan.
  • the reference value may be based on a known level of a biomarker associated with a given biological age or mortality status, or a DNA methylation status at one or more sites, e.g. a mean or median level, from a group of subjects with known biological age or mortality status (alive or dead), chronological age, breed, and/or sex.
  • the present method further comprises combining the DNA methylation profile with one or more of the chronological age, breed and/or sex of the dog.
  • the biological age determined by the method of the present invention may also be compared to one or more pre-determined thresholds (e.g. difference to chronological age). Using such thresholds, subjects may be stratified into categories which are indicative of determined risk, e.g. low, medium or high determined risk. The extent of the divergence from the thresholds is useful to determine which subjects would benefit most from certain interventions. In this way, dietary intervention and modification of lifestyle can be optimised.
  • pre-determined thresholds e.g. difference to chronological age.
  • the present invention provides a method for selecting a lifestyle regime, dietary regime or therapeutic intervention for a subject.
  • the modification in lifestyle may be any change as described herein, e.g. a dietary intervention and/or a change in exercise regime.
  • the modification in lifestyle may be administration of a therapeutic modality.
  • the lifestyle regime, dietary regime or therapeutic intervention may be applied to the dog for any suitable period of time. After said period of time, the dog’s biological age, mortality risk and/or probability of a healthy lifespan may be determined again using the present method in order to determine the efficacy of the lifestyle regime, dietary regime or therapeutic intervention for reducing the mortality risk and/or increasing probability of a healthy lifespan of the dog.
  • the lifestyle regime, dietary regime or therapeutic intervention may be applied for at least 2, at least 4, at least 8, at least 16, at least 32, or at least 64 weeks.
  • the lifestyle regime, dietary regime or therapeutic intervention may be applied for at least 3, at least 6, at least 12, at least 24, at least 36, at least 48 or at least 60 months.
  • the lifestyle regime, dietary regime or therapeutic intervention may be referred to as an antiaging lifestyle regime, dietary regime or therapeutic intervention.
  • the modification is a dietary intervention as described herein.
  • dietary intervention it is meant an external factor applied to a subject which causes a change in the subject’s diet. More preferably the dietary intervention includes the administration of at least dietary product or dietary regimen or a nutritional supplement.
  • the dietary intervention may be a meal, a regime of meals, a supplement or a regime of supplements or combinations of a meal and a supplement, or combinations of a meal and multiple supplements.
  • the dietary intervention or dietary product described herein may be any suitable dietary regime, for example, a calorie-restricted diet, a senior diet, a low protein diet, a phosphorous diet, low protein diet, potassium supplement diet, polyunsaturated fatty acids (PLIFA) supplement diet, anti-oxidant supplement diet, a vitamin B supplement diet, liquid diet, selenium supplement diet, omega 3-6 ratio diet, or diets supplemented with carnitine, branched chain amino acids or derivatives, nucleotides, nicotinamide precursors such as nicotinamide mononucleotide (MNM) or nicotinamide riboside (NR) or any combination of the above.
  • PKIFA polyunsaturated fatty acids
  • the dietary intervention or dietary product may be a calorie-restricted diet, a senior diet, or a low protein diet.
  • the dietary intervention or dietary product may be a calorie- restricted diet.
  • the dietary intervention or dietary product may be a low protein diet.
  • a dietary intervention may be determined based on the baseline maintenance energy requirement (MER) of the dog.
  • MER may be the amount of food that stabilizes the dog’s body weight (less than 5% change over three weeks).
  • a calorie-restricted diet may comprise about 50%, about 55%, about 60%, about 65%, about 75%, about 80%, about 85%, or about 90% of the dog’s MER.
  • a calorie- restricted diet may comprise about 60% or about 75% of the dog’s MER.
  • a low-protein diet may comprise less than 20% protein (% dry matter).
  • a low-protein diet may comprise less than 19% protein (% dry matter).
  • the dietary intervention may comprise a food, supplement and/or drink that comprises a nutrient and/or bioactive that mimics the benefits of caloric restriction (CR) without limiting daily caloric intake.
  • the food, supplement and/or drink may comprise a functional ingredient(s) having CR-like benefits.
  • the food, supplement and/or drink may comprise an autophagy inducer.
  • the food, supplement and/or drink may comprise fruit and/or nuts (or extracts thereof). Suitable examples include, but are not limited to, pomegranate, strawberries, blackberries, camu-camu, walnuts, chestnuts, pistachios, pecans.
  • the food, supplement and/or drink may comprise probiotics with or without fruit extracts or nut extracts.
  • Modifying a lifestyle of the subject also includes indicating a need for the subject to change lifestyle, e.g. prescribing more exercise. Similar to a dietary intervention, the determination of an increased mortality risk for a dog compared to what would be expected given its chronological age may allow a determination a switch the dog to an appropriate exercise regime.
  • Modifying a lifestyle of the subject also includes selecting or recommending a therapeutic modality or regimen.
  • the therapeutic modality or regimen may be a modality useful in treating and/or preventing - for example - arthritis, dental diseases, endocrine disorders, heart disease, diabetes, liver disease, kidney disease, prostate disorders, cancer and behavioural or cognitive disorders.
  • prophylactic therapies may be administered to a dog identified as being at risk of such disorders due to increased mortality risk and/or on the basis of particular biomarkers which are known to be associated with disease-relevant pathways.
  • dogs determined to be at risk of certain conditions (due to increased mortality risk) and/or on the basis of particular biomarkers which are known to be associated with disease-relevant pathways) may be monitored more regularly so that diagnosis and treatment can begin as early as possible.
  • the present invention is also directed to monitoring and/or determining the efficacy of an antiageing therapy or developing an anti-ageing therapy.
  • the anti-aging therapy may comprise, for example, a “rejuvenation” intervention.
  • a rejuvenation intervention aims to cause a reduction in the epigenetic or biological age of the subject.
  • the rejuvenation intervention may reprogram epigenetic age to that of a young dog or a very young dog.
  • Examples of such rejuvenation interventions include, but are not limited to, a gene therapy that reprograms epigenetic age, suitably to that of a young dog or a very young dog.
  • the present methods to monitor and/or determine the efficacy of a lifestyle regime, dietary regime or therapeutic intervention or develop a lifestyle regime, dietary regime or therapeutic intervention to reduce biological age are particularly applicable to this aspect.
  • the present invention may thus advantageously enable the identification of dogs that are expected to respond particularly well to a given intervention (e.g. lifestyle regime, dietary regime or therapeutic intervention).
  • a given intervention e.g. lifestyle regime, dietary regime or therapeutic intervention.
  • the intervention can thus be applied in a more targeted manner to dogs that are expected to respond.
  • the present invention provides a method for determining the efficacy of a lifestyle regime, dietary regime or therapeutic intervention for improving the biological age, mortality risk and/or probability of a healthy lifespan of a dog, said method comprising: i) applying a lifestyle regime, dietary regime or therapeutic intervention to the dog, optionally wherein the lifestyle regime, dietary regime or therapeutic intervention has been selecting according to the present invention; ii) after a time period of applying the lifestyle regime, dietary regime or therapeutic intervention to the dog; determining a biological age, mortality risk and/or probability of a healthy lifespan of the dog according to the method of the present invention; iii) determining if there has been a change in the biological age, mortality risk and/or probability of a healthy lifespan of the dog after the time period of following the lifestyle regime, dietary regime or therapeutic intervention.
  • the invention further provides a method for determining the efficacy of a lifestyle regime, dietary regime or therapeutic intervention for improving the biological age, mortality risk and/or probability of a healthy lifespan of a dog, said method comprising: i) determining a biological age, mortality risk and/or probability of a healthy lifespan for the dog according to the method of the present invention; ii) applying a lifestyle regime, dietary regime or therapeutic intervention selected based on the biological age, mortality risk and/or probability of a healthy lifespan determined in step i) to the dog; iii) after a time period of applying a lifestyle regime, dietary regime or therapeutic intervention to the dog; determining a biological age, mortality risk and/or probability of a healthy lifespan of the dog according to the method of the present invention; iv) determining if there has been a change in the biological age, mortality risk and/or probability of a healthy lifespan of the dog between step i) and step iii).
  • the lifestyle regime, dietary regime or therapeutic intervention may have been applied to the dog for a period before the first biological age, mortality risk and/or probability of a healthy lifespan is determined; however, the effectiveness of the lifestyle regime, dietary regime or therapeutic intervention for improving the biological age, mortality risk and/or probability of a healthy lifespan of the dog (i.e. reducing the mortality risk and/or increasing the probability of a healthy lifespan) may still be monitored by determining a biological age, mortality risk and/or probability of a healthy lifespan at two or more times during the application of the lifestyle regime, dietary regime or therapeutic intervention.
  • the present methods may comprise an ‘ecosystem’; in particular a digital ecosystem.
  • the present methods may comprise providing a sample obtained from the dog, optionally using a kit according to present invention; and providing the sample (e.g. by mailing) for subsequent biomarker and DNA extraction for the measurement of biomarkers as described herein and DNA methylation in extracted DNA from the sample to obtain a DNA methylation profile.
  • the biomarker and DNA methylation profile may then be used according to any of the present methods; preferably using a computer system or a computer program product according to the present invention.
  • the computer system or computer program may then prepare and share a report detailing the outcome of analysis/method in the form of e.g. selecting or recommending a suitable lifestyle regime, dietary regime or therapeutic intervention for a dog or any other outcome of the present methods.
  • the sample used to determine a DNA methylation profile from the dog may be a sample that can be obtained at home by a dog owner (e.g. not requiring a veterinarian or health-care professionals).
  • the sample may be a hair follicle, buccal swab or saliva sample.
  • the present invention provides a dietary intervention for use in reducing the mortality risk and/or increasing the probability of a healthy lifespan of a dog, wherein the dietary intervention is administered to a dog with a biological age, mortality risk and/or probability of a healthy lifespan determined by the present method.
  • the present invention provides the use of a dietary intervention to reduce the mortality risk and/or increase the probability of a healthy lifespan of a dog, wherein the dietary intervention is administered to a dog with a biological age, mortality risk and/or probability of a healthy lifespan determined by the present method.
  • the dietary intervention may be a dietary product or dietary regimen or a nutritional supplement.
  • the present methods may be performed using a computer. Accordingly, the present methods may be performed in silico.
  • the computer may prepare and share a report detailing the outcome of the present methods.
  • the methods described herein may be implemented as a computer program running on general purpose hardware, such as one or more computer processors.
  • the functionality described herein may be implemented by a device such as a smartphone, a tablet terminal or a personal computer.
  • the present invention provides a computer program product comprising computer implementable instructions for causing a programmable computer to determine the biological age, mortality risk and/or probability of a healthy lifespan of a dog as described herein.
  • the user inputs into the device levels of one or more of the biomarkers and DNA methylation markers as defined herein, optionally along with chronological age, breed and sex.
  • the device then processes this information and provides a determination of a biological age, mortality risk and/or probability of a healthy lifespan for the dog.
  • the device then processes this information and provides a determination of a suitable lifestyle regime, dietary regime or therapeutic intervention for the dog based on the biological age, mortality risk and/or probability of a healthy lifespan .
  • the device may generally be a server on a network. However, any device may be used as long as it can process biomarker data and/or additional parameters or characteristic data using a processor, a central processing unit (CPU) or the like.
  • the device may, for example, be a smartphone, a tablet terminal or a personal computer and output information indicating the determined biological age for the dog or a determination of a suitable lifestyle regime, dietary regime or therapeutic intervention for the dog based on the biological age.
  • the present invention provides the following aspects, defined by numbered paragraphs:
  • a method for determining a biological age, mortality risk and/or probability of a healthy lifespan of a dog comprising using (i) the level of one or more biomarker(s) in one or more samples obtained from the dog, and (ii) a DNA methylation profile from the dog to determine a biological age, mortality risk and/or probability of a healthy lifespan of the dog; wherein the one or more biomarkers are selected from white blood cell count, serum albumin, serum alkaline phosphatase, serum creatine kinase, haemoglobin, haematocrit, mean corpuscular haemoglobin, serum glucose, mean red cell volume, serum globulin, serum calcium, platelet count, and/or red blood cell count.
  • said method comprises: a) determining a biological age, mortality risk and/or probability of a healthy lifespan of the dog using the level of one or more biomarker(s) in one or more samples obtained from the dog, wherein the one or more biomarker(s) is selected from white blood cell count, serum albumin, serum alkaline phosphatase, serum creatine kinase, haemoglobin, haematocrit, mean corpuscular haemoglobin, serum glucose, mean red cell volume, serum globulin, serum calcium, platelet count, and/or red blood cell count; and b) determining a biological age, mortality risk and/or probability of a healthy lifespan for the dog using a DNA methylation profile from the dog.
  • step (a) is white blood cell count.
  • step (a) is serum albumin.
  • step (a) is serum alkaline phosphatase.
  • biomarkers in step (a) comprise white blood cell count, serum albumin and serum alkaline phosphatase.
  • biomarkers in step (a) comprise white blood cell count, serum albumin, serum alkaline phosphatase, serum creatine kinase, haemoglobin, haematocrit, mean corpuscular haemoglobin, serum glucose, mean red cell volume, and serum globulin.
  • step (a) further comprises combining the level of the one or more biomarker(s) with one or more of the chronological age, breed and/or sex of the dog.
  • step (a) comprises: a. determining the level of the following biomarkers; white blood cell count, serum albumin, serum alkaline phosphatase, serum creatine kinase, haemoglobin, haematocrit, mean corpuscular haemoglobin, serum glucose, mean red cell volume, and serum globulin in one or more samples obtained from the dog; and b. determining a phenotypic age (Phenoage) of the dog using formula (1): where xb is the sum of the value of each biomarker(s), sex and breed multiplied by their respective coefficients according to formula (2): p xb ' x u f> u + f>o
  • step (b) comprises providing a DNA methylation profile from a sample obtained from the dog.
  • step (b) further comprises determining a DNA methylation profile from a sample obtained from the dog.
  • DNA methylation is determined using a method which comprises one or more of the following steps: (a) treating the sample DNA with APOBEC to deaminate cytosines; (b) a capture-based enrichment; and/or (c) high throughput sequencing.
  • DNA methylation profile is determined from a blood, hair follicle, buccal swab, faecal, saliva or tissue sample; optionally wherein a blood sample is used for both step (a) and step (b).
  • step (b) comprises determining a biological age for the dog; optionally wherein the DNA methylation profile comprises at least one methylation site as listed in Table 3 or 8; or (ii) step b comprises determining a mortality risk and/or probability of a healthy lifespan; optionally wherein the DNA methylation profile comprises at least one methylation site as listed in Table 3 or 8.
  • DNA methylation profile comprises at least 3, at least 5, at least 10, at least 20, at least 50, at least 100, at least 150, at least 200 or each of the methylation sites as listed in Table 3 or Table 8.
  • step (b) further comprises combining the DNA methylation profile with one or more of the chronological age, breed and/or sex of the dog.
  • a method for selecting a lifestyle regime, dietary regime or therapeutic intervention for a dog comprising: i) determining a biological age, mortality risk and/or probability of a healthy lifespan for the dog according to the method of any preceding paragraph; and ii) selecting a suitable lifestyle regime, dietary regime or therapeutic intervention for the dog based on the biological age, mortality risk and/or probability of a healthy lifespan determined in step i).
  • a method for determining the efficacy of a lifestyle regime, dietary regime or therapeutic intervention for improving the biological age, mortality risk and/or probability of a healthy lifespan of a dog comprising: i) applying a lifestyle regime, dietary regime or therapeutic intervention to the dog, optionally wherein the lifestyle regime, dietary regime or therapeutic intervention has been selecting according to the method of paragraph 27; ii) after a time period of applying the lifestyle regime, dietary regime or therapeutic intervention to the dog; determining a biological age, mortality risk and/or probability of a healthy lifespan of the dog according to the method of any of paragraphs 1 to 26; iii) determining if there has been a change in the biological age, mortality risk and/or probability of a healthy lifespan of the dog after the time period of following the lifestyle regime, dietary regime or therapeutic intervention.
  • a method for determining the efficacy of a lifestyle regime, dietary regime or therapeutic intervention for improving the biological age, mortality risk and/or probability of a healthy lifespan of a dog comprising: i) determining a biological age, mortality risk and/or probability of a healthy lifespan for the dog according to the method of any of paragraphs 1 to 26; ii) applying a lifestyle regime, dietary regime or therapeutic intervention selected based on the biological age, mortality risk and/or probability of a healthy lifespan determined in step i) to the dog; iii) after a time period of applying a lifestyle regime, dietary regime or therapeutic intervention to the dog; determining a biological age, mortality risk and/or probability of a healthy lifespan of the dog according to the method of any of paragraphs 1 to 26; iv) determining if there has been a change in the biological age, mortality risk and/or probability of a healthy lifespan of the dog between step i) and step iii).
  • a method for developing an anti-aging lifestyle regime, dietary regime or therapeutic intervention comprising; i) determining a first biological age, mortality risk and/or probability of a healthy lifespan of a dog according to the method of any of paragraphs 1 to 26; ii) applying a lifestyle regime, dietary regime or therapeutic intervention to the dog; iii) after a time period of applying the lifestyle regime, dietary regime or therapeutic intervention to the dog; determining a second biological age, mortality risk and/or probability of a healthy lifespan of the dog according to the method of any of paragraphs 1 to 26; iv) determining if there has been a change in the first and second mortality risk and/or probability of a healthy lifespan of the dog after the time period of following the lifestyle regime, dietary regime or therapeutic intervention; wherein the lifestyle regime, dietary regime or therapeutic intervention is determined to be anti-ageing if it decreases the biological age, mortality risk and/or increases the probability of a healthy lifespan; and/or reduces the rate of increase of mortality risk and/or increases rate
  • a method for preventing or reducing the risk of a dog developing a disease comprising: i) determining a mortality risk and/or probability of a healthy lifespan of the dog according to the method of any of paragraphs 1 to 26; wherein the mortality risk and/or probability of a healthy lifespan determined for the dog is associated with an increased likelihood to develop the disease; and ii) selecting a lifestyle regime, dietary regime or therapeutic intervention for the dog based on the biological age, mortality risk and/or probability of a healthy lifespan determined in step i); wherein the lifestyle regime, dietary regime or therapeutic intervention prevents or reduces the risk of the dog developing the disease; preferably wherein the disease is an age-related disease.
  • a method for selecting a dog as being suitable for receiving an anti-aging lifestyle regime, dietary regime or therapeutic intervention comprising: i) determining a biological age, mortality risk and/or probability of a healthy lifespan of the dog according to the method of any of paragraphs 1 to 26; ii) selecting a dog as being suitable for receiving an anti-aging lifestyle regime, dietary regime or therapeutic intervention if it has an increased biological age, mortality risk and/or reduced probability of a healthy lifespan compared to its chronological age.
  • a method according to paragraph 34 wherein the dietary intervention is a calorie- restricted diet, a senior diet or a low protein diet.
  • a dietary intervention or therapeutic modality for use in reducing the biological age, mortality risk and/or increasing the probability of a healthy lifespan of a dog wherein the dietary intervention is administered to a dog with a biological age, mortality risk and/or probability of a healthy lifespan determined by the method of any of paragraphs 1 to 26.
  • a computer-readable medium comprising instructions that when executed cause one or more processors to perform the method of any of paragraphs 1 to 18 or 21 to 26.
  • a computer system for determining a biological age, mortality risk and/or probability of a healthy lifespan of a dog the computer system programmed to determine a mortality risk for the dog using:
  • biomarker(s) in one or more samples obtained from the dog, wherein the one or more biomarker(s) is selected from white blood cell count, serum albumin, serum alkaline phosphatase, serum creatine kinase, haemoglobin, haematocrit, mean corpuscular haemoglobin, serum glucose, mean red cell volume, serum globulin, serum calcium, platelet count, and/or red blood cell count; and
  • a computer system for selecting a suitable lifestyle regime, dietary regime or therapeutic intervention for a dog the computer system programmed to perform one or more of the steps of: i) determining a biological age, mortality risk and/or probability of a healthy lifespan for the dog according to the method of any of paragraphs 1-18 or 21-26; and ii) selecting a suitable lifestyle regime, dietary regime or therapeutic intervention for the dog based on the mortality risk and/or probability of a healthy lifespan determined in step i).
  • a computer system for determining the efficacy of a lifestyle regime, dietary regime or therapeutic intervention for improving the biological age, mortality risk and/or probability of a healthy lifespan for a dog the computer system programmed to perform one or more of the steps of: i) determining a biological age, mortality risk and/or probability of a healthy lifespan of the dog according to the method of any of paragraphs 1-18 or 21-26 from a sample obtained from the dog before the lifestyle regime, dietary regime or therapeutic intervention and a sample obtained from the dog after the lifestyle regime, dietary regime or therapeutic intervention; and ii) determining if there has been a change in the biological age, mortality risk and/or probability of a healthy lifespan of the dog between the sample obtained from the dog before and after the lifestyle regime, dietary regime or therapeutic intervention has been applied.
  • a computer system for determining a likelihood that a dog will benefit from an antiaging lifestyle regime, dietary regime or therapeutic intervention programmed to perform one or more of the steps of: a) determining a biological age, mortality risk and/or probability of a healthy lifespan for the dog according to the method of any of paragraphs 1-18 or 21-26; b) identifying a dog as likely to respond to an anti-aging lifestyle regime, dietary regime or therapeutic intervention if it has an increased biological age, mortality risk and/or reduced probability of a healthy lifespan compared to its chronological age.
  • a computer program product comprising computer implementable instructions for causing a programmable computer to determine a biological age, mortality risk and/or probability of a healthy lifespan for a dog according to the method of any of paragraphs 1-18 or 21-26.
  • a computer program product comprising computer implementable instructions for causing a programmable computer to determine a biological age, mortality risk and/or probability of a healthy lifespan for a dog according to the method of any of paragraphs 1-18 or 21-26; and select a suitable lifestyle regime, dietary regime or therapeutic intervention for the dog based on the biological age, mortality risk and/or probability of a healthy lifespan determined.
  • a computer program product comprising computer implementable instructions for causing a programmable computer to a) determine a biological age, mortality risk and/or probability of a healthy lifespan of a dog according to the method of any of paragraphs 1-18 or 21-26 from a sample obtained from the dog before a lifestyle regime, dietary regime or therapeutic intervention and a sample obtained from the dog after the lifestyle regime, dietary regime or therapeutic intervention; and b) determine if there has been a change in the biological age, mortality risk and/or probability of a healthy lifespan of the dog between the sample obtained from the dog before and after the lifestyle regime, dietary regime or therapeutic intervention has been applied.
  • a computer program product comprising computer implementable instructions for causing a programmable computer to a) determine a biological age, mortality risk and/or probability of a healthy lifespan for a dog according to the method of any of paragraphs 1-18 or 21-26; and b) identify a dog as likely to respond to an anti-aging lifestyle regime, dietary regime or therapeutic intervention if it has an increased biological age or mortality risk and/or reduced probability of a healthy lifespan compared to its chronological age.
  • a kit for determining a biological age, mortality risk and/or probability of healthy lifespan of a dog comprising means and reagents for collection and, optionally, stabilizing of a sample from the subject; and instructions for collection and, optionally, stabilizing of the sample, and wherein the sample is for mailing for subsequent biomarker and DNA extraction for the measurement of one or more biomarker(s) and DNA methylation from the sample to obtain the level of one or more biomarker(s) and a DNA methylation profile.
  • a method for determining a biological age, mortality risk and/or probability of a healthy lifespan for a dog using one or more biomarkers and a DNA methylation profile of the dog comprising (i) providing a sample from the dog, optionally using a kit according to paragraph 48; (ii) providing the sample for subsequent biomarker extraction and DNA extraction for the measurement of one or more biomarkers and DNA methylation in the extracted DNA from the sample to obtain a level of the one or more biomarkers and a DNA methylation profile; (iii) determining a biological age, mortality risk and/or probability of a healthy lifespan for the dog using a computer system according to paragraph 39 or a computer program product according to paragraph 43; wherein the computer system prepares and shares a report detailing the outcome of step (c).
  • a method for determining the efficacy of a lifestyle regime, dietary regime or therapeutic intervention for improving the biological age, mortality risk and/or probability of a healthy lifespan of a dog using one or more biomarkers and a DNA methylation profile comprising: (i) providing a sample obtained from the dog before the lifestyle regime, dietary regime or therapeutic intervention and a sample obtained from the dog after the lifestyle regime, dietary regime or therapeutic intervention, optionally using a kit according to paragraph 48; (ii) providing the samples for subsequent biomarker extraction and DNA extraction for the measurement of one or more biomarkers and DNA methylation in the extracted DNA from the sample to obtain a level of the one or more biomarkers and a DNA methylation profile; (iii) determining if there has been a change in the biological age, mortality risk and/or probability of a healthy lifespan of the dog between the sample obtained from the dog before and after the lifestyle regime, dietary regime or therapeutic intervention has been applied using a computer system according to paragraph 41 or a computer program product according to paragraph 45;
  • a method for identifying a dog as likely to respond to an anti-aging lifestyle regime, dietary regime or therapeutic intervention using one or more biomarkers and a DNA methylation profile comprising: (i) providing a sample obtained from the dog; optionally using a kit according to paragraph 48; (ii) providing the sample for subsequent biomarker extraction and DNA extraction for the measurement of one or more biomarkers and DNA methylation in the extracted DNA from the sample to obtain a level of the one or more biomarkers and a DNA methylation profile; (iii) identifying a dog as likely to respond to an anti-aging lifestyle or dietary if it has an increased biological age or mortality risk and/or reduced probability of a healthy lifespan compared to its chronological age using a computer system according to paragraph 42 or a computer program product according to paragraph 46; wherein the computer system prepares and shares a report detailing the outcome of step (iii).
  • Example 1 Determination of blood biomarkers associated with mortality risk in dogs
  • Predictive blood biomarkers were determined from a biomarker panel consisting of a standard clinical complete blood count (cbc) and standard clinical blood chemistry analysis. Serum samples were taken after overnight fasting and measured using standard veterinary clinical practice.
  • Serum Alkaline phosphatase U/L, In-transformed
  • Serum creatine Kinase I U/L, In-transformed
  • Hemoglobin g/dL
  • Hematocrit % Mean Corpuscular Hemoglobin (pg) Serum Sodium (mmol/L) Mean Red Cell Volume (fL) Serum Globulin (g/dL) Serum Calcium (mg/dL) Serum Platelet Count (10 A 3/uL)
  • Example 2 Multi-parameter model for predicting mortality risk
  • the phenotypic age of the animal was defined as the time variable (“age”) at which the survival probability of the animal given by model 2 is equal to the survival probability at their chronological age given by the model 1 .
  • Table 2 Coefficients and y and values have been measured from training set Further, by reducing the set of 10 biomarkers by systematically removing one biomarker, starting for the top of the list, we observed a reduction in the strength of the survival prediction (p value). The drop was most pronounced with the first parameters, confirming their biggest contribution, but we observed a change in quality of prediction by each reduction of the set, showing that each parameter contributes to the overall prediction ( Figure 2).
  • Example 3 Application of phenoage for predicting mortality risk
  • Phenoage advance (delta with chronological age) changes mid-life with a calorie-restricted diet (75% baseline maintenance energy requirement (MER)). This changes earlier in females than males ( Figure 5).
  • Example 4 Reduced protein diet reduces PhenoAge Advance
  • the two diets had comparable metabolizable energy (ME), but differed in protein, carbohydrate, fat and fiber. Feeding instruction
  • Dogs in both groups were fed 75% of their baseline MERs during the first 4 months of the study and 60% of their baseline MERs during the last 2 months of the study.
  • Serum samples were collected at baseline, 2, 4 and 6 months of the study. Complete blood count (CBC) and blood chemistry panel analyses were performed on those serum samples at the end of the study.
  • CBC Complete blood count
  • chemistry panel analyses were performed on those serum samples at the end of the study.
  • phenoage advance defined as the difference between a dog’s phenoage and their chronological age following a 6 month period of the weight loss diet.
  • the ages of dogs in the study ranged from 3 to 11 years.
  • the_two diets had quite different protein levels, the effects on PhenoAge were comparable between the two diets, suggesting that reduction in caloric intake led to younger PhenoAge regardless of the macronutrient ratios in dogs.
  • Example 5 Illustrative method for generating a second generation epigenetic clock
  • Whole blood samples from a canine cohort were analysed by performing DNA extraction, converting DNA methylation by using enzymatic reactions, performing whole genome library preparation, hybridizing the whole-genome-converted library preparation to capture probes directed against gene promoters and measuring the methylation profile by sequencing (EM- Seq).
  • the capture probes were directed against approximately 40,000 targets (promotor regions - approximately 1 kb upstream and 0.5 downstream of the transcriptional start site). These target regions comprise potential methylation sites of interest (individual cytosine residues that may be methylated).
  • the initial methylation profile may be filtered/processed in order to generate a restricted methylation profile comprising fewer discrete methylation sites.
  • the goal of this filtering is to provide a restricted methylation profile comprising e.g. between 50000 and 500000 methylation sites that can be used to train the biological clock.
  • Methods for filtering the initial methylation profile include:
  • WGCNA Weighted correlation network analysis
  • a dataset including information on the mortality status (alive or dead), chronological age, breed and sex of a cohort of dogs was split into training and testing sets (e.g. 2/3 data for training and 1/3 for testing, ensuring a good split with regards to metadata; for example similar proportion of each breed/each sex in the training and in the testing set).
  • a penalized Cox model was fitted to survival using methylation sites, breed/breed class, sex and chronological age as predictors. Parameters of the model as well as the penalty parameter is estimated using the glmnet package in R.
  • the mortality risk and/or probability of healthy lifespan age may be defined as the time variable (“chronological age”) at which the survival probability of the animal given by model 2 is equal to the survival probability at their chronological age given by the model 1.
  • the penalization parameter was selected to provide a reasonable number of DNA methylation sites (e.g. max 1000) with a good model fit for mortality risk and/or probability of healthy lifespan.
  • the model for biological age based on DNA methylation sites was then assessed on the testing set.
  • Figure 6 shows a validation of the clock in calorie restriction where dogs on a calorie restriction have a lower biological Age (lower delta) compared to dogs on a control diet. Delta in Figure 6 corresponds to the residuals of the regression model of Chronological Age vs predicted phenoDNAmAge.
  • Figure 8 shows there is a significant difference between the two diets when adjusting a linear mixed effects model (DogID as random effect).
  • Figure 9 shows a significant difference in survival between biologically younger and biologically older dogs.
  • Figure 10 shows an increase in delta phenoDNAmAge is significantly associated with an increase in the risk of mortality when a Cox proportional Hazard model was fitted using sex and delta phenoDNAmAge (residuals from chronologicalAge vs predicted phenoDNAmAge), stratified on breed class (Small or Medium) on the training set.
  • Methylation sites were identified and filtered using techniques described in Example 5.
  • the dataset including information on the chronological age, breed and sex of a cohort of dogs is split into training and testing sets (e.g. 2/3 data for training and 1/3 for testing, ensuring a good split with regards to metadata; for example similar proportion of each breed/each sex in the training and in the testing set).
  • a penalized regression was fit between chronological age and the restricted DNA methylation profile, sex and breed in order to identify DNA methylation sites that are relevant for biological age (i.e. to generate a DNA methylation biological clock).
  • the penalization parameter was selected to provide a reasonable number of DNA methylation sites (e.g. max 1000) with a good model fit for biological age.
  • the model for biological age based on DNA methylation sites is then assessed on the testing set.
  • Biological age predicted from using the first generation epigenetic clock is highly correlated with chronological age (see Figure 12).
  • the first generation epigenetic clock was also validated using a calorie restriction study (see Figure 13). Delta corresponds to the residuals of the regression model of Chronological Age vs predicted biological Age using the biological clock. Dogs on a calorie restriction were determined to have a significantly lower biological age (lower delta) compared to dogs on a control diet ( Figure 13).

Landscapes

  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Public Health (AREA)
  • Organic Chemistry (AREA)
  • Biomedical Technology (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Primary Health Care (AREA)
  • Pathology (AREA)
  • Immunology (AREA)
  • Analytical Chemistry (AREA)
  • Epidemiology (AREA)
  • Molecular Biology (AREA)
  • Genetics & Genomics (AREA)
  • Biochemistry (AREA)
  • Hematology (AREA)
  • Urology & Nephrology (AREA)
  • Zoology (AREA)
  • Microbiology (AREA)
  • Wood Science & Technology (AREA)
  • Physics & Mathematics (AREA)
  • Biotechnology (AREA)
  • Food Science & Technology (AREA)
  • General Physics & Mathematics (AREA)
  • Databases & Information Systems (AREA)
  • Data Mining & Analysis (AREA)
  • Biophysics (AREA)
  • Nutrition Science (AREA)
  • Medicinal Chemistry (AREA)
  • Cell Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • General Engineering & Computer Science (AREA)
  • Investigating Or Analysing Biological Materials (AREA)

Abstract

La présente invention concerne un procédé pour déterminer un âge biologique, un risque de mortalité et/ou une probabilité d'espérance de vie en bonne santé d'un chien. Ledit procédé consiste à : a) déterminer un âge biologique, un risque de mortalité et/ou une probabilité d'espérance de vie en bonne santé du chien en utilisant le niveau d'un ou plusieurs biomarqueurs dans un ou plusieurs échantillons prélevés chez le chien, le ou les biomarqueurs étant choisis parmi la numération des globules blancs, l'albumine sérique, la phosphatase alcaline sérique, la créatine kinase sérique, l'hémoglobine, l'hématocrite, l'hémoglobine corpusculaire moyenne, le glucose sérique, le volume érythrocytaire moyen, la globuline sérique, le calcium sérique, la numération plaquettaire et/ou la numération érythrocytaire ; et b) déterminer un âge biologique, un risque de mortalité et/ou une probabilité d'espérance de vie en bonne santé pour le chien par l'utilisation d'un profil de méthylation de l'ADN du chien.
PCT/EP2024/080371 2023-11-02 2024-10-28 Procédé pour déterminer l'état de santé d'un chien Pending WO2025093461A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
EP23207478.1 2023-11-02
EP23207478 2023-11-02

Publications (1)

Publication Number Publication Date
WO2025093461A1 true WO2025093461A1 (fr) 2025-05-08

Family

ID=88689870

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/EP2024/080371 Pending WO2025093461A1 (fr) 2023-11-02 2024-10-28 Procédé pour déterminer l'état de santé d'un chien

Country Status (1)

Country Link
WO (1) WO2025093461A1 (fr)

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2019046725A1 (fr) 2017-08-31 2019-03-07 The Regent Of The University Of California Profilage de méthylome chez des animaux et utilisations de celui-ci
WO2019143845A1 (fr) * 2018-01-17 2019-07-25 The Regents Of The University Of California Biomarqueurs basés sur la méthylation de l'adn et l'âge phénotypique pour l'espérance de vie et la morbidité
WO2019165064A1 (fr) * 2018-02-21 2019-08-29 Mars, Incorporated Marqueurs pour la détermination de l'âge biologique d'un chien
WO2022272120A1 (fr) * 2021-06-25 2022-12-29 The Regents Of The University Of California Horloges épigénétiques
WO2023232811A1 (fr) * 2022-05-31 2023-12-07 Société des Produits Nestlé S.A. Méthode pour améliorer la durée de vie saine d'un chien
WO2024015628A2 (fr) * 2022-07-15 2024-01-18 The Board Of Trustees Of The Leland Stanford Junior University Biomarqueurs de vieillissement d'organe dérivés du protéome plasmatique

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2019046725A1 (fr) 2017-08-31 2019-03-07 The Regent Of The University Of California Profilage de méthylome chez des animaux et utilisations de celui-ci
WO2019143845A1 (fr) * 2018-01-17 2019-07-25 The Regents Of The University Of California Biomarqueurs basés sur la méthylation de l'adn et l'âge phénotypique pour l'espérance de vie et la morbidité
WO2019165064A1 (fr) * 2018-02-21 2019-08-29 Mars, Incorporated Marqueurs pour la détermination de l'âge biologique d'un chien
WO2022272120A1 (fr) * 2021-06-25 2022-12-29 The Regents Of The University Of California Horloges épigénétiques
WO2023232811A1 (fr) * 2022-05-31 2023-12-07 Société des Produits Nestlé S.A. Méthode pour améliorer la durée de vie saine d'un chien
WO2024015628A2 (fr) * 2022-07-15 2024-01-18 The Board Of Trustees Of The Leland Stanford Junior University Biomarqueurs de vieillissement d'organe dérivés du protéome plasmatique

Non-Patent Citations (25)

* Cited by examiner, † Cited by third party
Title
ACTA PHYSIOLOGICA SCANDINAVICA, vol. 49, 1960, pages 192 - 197
ARNESON ET AL., NATURE COMMUNICATIONS, vol. 13, 2022, pages 783
BR J HAEMATOL., vol. 13, April 1967 (1967-04-01), pages 71 - 5
CARRADINI ET AL.: "describe the use of continuous glucose monitoring devices in dogs", ABBOTT LABORATORIES, FREESTYLE LIBRE
COSTELLO ET AL., NAT GENET., vol. 24, no. 2, 2000, pages 132 - 8
HORVATH STEVE ET AL: "DNA methylation clocks for dogs and humans", vol. 119, no. 21, 17 May 2022 (2022-05-17), XP093075636, ISSN: 0027-8424, Retrieved from the Internet <URL:https://www.pnas.org/doi/pdf/10.1073/pnas.2120887119> *
HUANG ET AL., CANCER RES., vol. 57, no. 6, 15 March 1997 (1997-03-15), pages 1030 - 4
HUANG ET AL., HUM MOL GENET., vol. 8, no. 3, March 1999 (1999-03-01), pages 459 - 70
JAGANNATHAN ET AL., GENES (BSAEL, vol. 12, no. 6, 2021, pages 847
KHULAN ET AL., GENOME RES., vol. 16, no. 8, August 2006 (2006-08-01), pages 1 046 - 55
LANGFELDERHORVATH, BMC BIOINFORMATICS, vol. 9, no. 559, 2008
MORGANE LEVINE ET AL: "An epigenetic biomarker of aging for lifespan and health span", AGING2018, 17 April 2018 (2018-04-17), XP055766768, Retrieved from the Internet <URL:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5940111/pdf/aging-10-101414.pdf> [retrieved on 20210119] *
OPII ET AL: "Proteomic identification of brain proteins in the canine model of human aging following a long-term treatment with antioxidants and a program of behavioral enrichment: Relevance to Alzheimer's disease", NEUROBIOLOGY OF AGING, TARRYTOWN, NY, US, vol. 29, no. 1, 17 November 2007 (2007-11-17), pages 51 - 70, XP022349351, ISSN: 0197-4580, DOI: 10.1016/J.NEUROBIOLAGING.2006.09.012 *
RAULUSEVICIUTE ET AL., CLINICAL EPIGENETICS, vol. 11, no. 193, 2019
SAGAR RAYALA S ET AL: "Creatine Kinase-MB as a Cardiac Biomarker in Canine Cardiac Disorders", IND J VET SCI AND BIOTECH (2021): 10.21887/IJVSBT.17.3.6, vol. 17, no. 3, 16 August 2021 (2021-08-16), pages 27 - 30, XP093078697, DOI: 10.21887/ijvsbt.17.3.6 *
STOKOL ET AL.: "describe the use of automated systems using a BCG-binding assay in determining serum Albumin levels in dogs in a clinical setting", VET CLIN PATHOL., vol. 30, no. 4, 2001, pages 170 - 176
THOMPSON MICHAEL J. ET AL: "An epigenetic aging clock for dogs and wolves", AGING, vol. 9, no. 3, 28 March 2017 (2017-03-28), pages 1055 - 1068, XP093076090, Retrieved from the Internet <URL:https://www.aging-us.com/article/101211/pdf> DOI: 10.18632/aging.101211 *
TINA WANG: "Quantitative translation of dog-to-human aging by conserved remodeling of epigenetic networks", BIORXIV, 19 November 2019 (2019-11-19), XP093154470, Retrieved from the Internet <URL:https://www.biorxiv.org/content/10.1101/829192v2> DOI: 10.1101/829192 *
TOTHOVA ET AL., VETERINARNI MEDICINA, vol. 61, 2016, pages 475 - 496
USHIJIMA ET AL., PROC NATL ACAD SCI U S A., vol. 94, no. 6, 18 March 1997 (1997-03-18), pages 2284 - 9
VAISVILA ET AL., GENOME RESEARCH, vol. 31, 2021, pages 1 - 10
XIA LI: "Longitudinal trajectories, correlations and mortality associations of nine biological ages across 20-years follow-up", ELIFE, 11 February 2020 (2020-02-11), XP093154561, Retrieved from the Internet <URL:https://cdn.elifesciences.org/articles/51507/elife-51507-v1.xml> DOI: 10.7554/eLife.51507 *
ZOLLINGER ET AL., BIOSTATISTICS, vol. 19, no. 2, 2018, pages 153 - 168
ZOU ET AL., BMC GENOMICS, vol. 19, 2018, pages 390
ZUO ET AL., EPIGENOMICS., vol. 1, no. 2, 2009, pages 331 - 345

Similar Documents

Publication Publication Date Title
Seifuddin et al. Systematic review of genome-wide gene expression studies of bipolar disorder
Iwamoto et al. Neurons show distinctive DNA methylation profile and higher interindividual variations compared with non-neurons
McManus et al. Regulatory divergence in Drosophila revealed by mRNA-seq
Wickramasinghe et al. RNA-sequencing: a tool to explore new frontiers in animal genetics
CN115161390B (zh) 使用血液中的无细胞dna检测血液病症
EP4532763A1 (fr) Méthode pour améliorer la durée de vie saine d&#39;un chien
Raymond et al. Genome-wide association study for bone strength in laying hens
Mozhui et al. Conserved effect of aging on DNA methylation and association with EZH2 polycomb protein in mice and humans
WO2014075083A1 (fr) Procédés de pronostic de l&#39;âge et agents d&#39;identification qui induisent ou inhibent le vieillissement prématuré
Soriano-Tarraga et al. DNA isolation method is a source of global DNA methylation variability measured with LUMA. Experimental analysis and a systematic review
de Jong et al. Whole genome sequencing of nearly isogenic WMI and WLI inbred rats identifies genes potentially involved in depression and stress reactivity
Yang et al. Genetic background of hematological parameters in Holstein cattle based on genome-wide association and RNA sequencing analyses
US20240153585A1 (en) Method
US20250346954A1 (en) Method to improve health outcomes of a dog using biological age
WO2025093461A1 (fr) Procédé pour déterminer l&#39;état de santé d&#39;un chien
US20250283874A1 (en) Methods of determining a health status of a dog based on one or more biomarkers, and methods of treating a mortality risk identified by the health status
US20250182847A1 (en) Method
US20250182905A1 (en) Method
CN113621696A (zh) 一种用于检测高原适应性的snp标志物及试剂盒
WO2025180998A1 (fr) Procédés utilisant la méthylation de l&#39;adn chez les canidés
WO2025114799A2 (fr) Procédés utilisant un profil de méthylation de l&#39;adn d&#39;un canin
HK40081560A (en) Detecting hematological disorders using cell-free dna in blood
HK1261820A1 (en) Detecting hematological disorders using cell-free dna in blood
HK1261820B (en) Detecting hematological disorders using cell-free dna in blood

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 24795207

Country of ref document: EP

Kind code of ref document: A1