Canine genetics and obesity
Written by Anna Morros-Nuevo
Obesity in pet dogs is nothing new, but scientific understanding as to why some animals get fat – and what can be done about it – is progressing apace.
Article

Key points
Canine obesity is a complex disease with a strong genetic component, and is not simply a result of owner negligence or poor self-control.
Recent research has identified key genetic mutations that significantly increase a dog’s predisposition to adiposity and heightened food motivation, particularly in certain breeds.
High food motivation, often genetically influenced, is a major driver of canine obesity; tools, such as specifically designed questionnaires, can help assess this trait.
Effective weight management requires an individualized approach, and acknowledges both the dog’s genetic susceptibility and the owner’s capacity for behavioral change.
Introduction
Canine obesity is a widespread health concern – much like the current human obesity epidemic (1) – and it has been historically, and simplistically, viewed as a consequence of inadequate owner management of diet and exercise (2,3). However, mounting scientific evidence reveals a more nuanced picture: obesity is a complex disease of disordered energy homeostasis, profoundly influenced by the intricate interplay of genetic predispositions and environmental factors (4,5). For veterinary clinicians, understanding this complex interplay is crucial for effective prevention and management strategies.
The heritability of obesity
Obesity is highly heritable (6,7), with genetic factors significantly influencing an individual’s drive to eat and their susceptibility to an obesogenic environment. This concept, known as the behavioral susceptibility theory, posits that genetically influenced appetite variations determine how an individual responds to readily available, high-calorie food and limited exercise (8). Evidence for the strong genetic component of canine obesity comes from clear breed predispositions (4,9-12). A recent study using electronic health records from over 1 million dogs (4) showed wide variation in the probability of developing obesity across different breeds, strongly suggesting that obesity risk is largely mediated by genetically determined food motivation (Figure 1), and not solely due to lifestyle or owner perception of ideal body shape.

Figure 1. Breed-averaged Food Motivation Score (0-1), from the DORA questionnaire, varies widely across breeds and is highly correlated with breed obesity/overweight probability (0-1). From (4).
© Anna Morros-Nuevo/Redrawn by Sandrine Fontègne
Genetic discoveries: unpacking the mechanisms
Obesity is a disease of disordered energy homeostasis, whereby energy intake chronically exceeds energy output. The central leptin-melanocortin axis in the hypothalamus is a critical neuroendocrine signaling pathway that regulates this process (5). Leptin, secreted by adipocytes, signals the body’s energy status to the hypothalamus, activating pro-opiomelanocortin (POMC) neurons which, in turn, produce neuroactive peptides, alpha- and beta- melanocyte stimulating hormone (α-MSH and β-MSH) (5,13). These peptides activate melanocortin receptors, mainly MC4R, which leads to reduced food intake and increased energy expenditure (9,14). Significant breakthroughs in obesity genetics often relate to this pathway (Figure 2). A mutation in the POMC gene is common in Labrador and Flat-coated Retrievers (14), which disrupts the production of β-MSH and β-endorphin, leading to greater body weight (+2kg per allele), adiposity, and significantly higher food motivation. Dogs with this mutation have also been shown to have a lower resting metabolic rate and increased hunger in response to food cues, even though their satiety and hedonic response to food are not different (13). A mutation in the MC4R gene identified in Beagles was also found to be significantly associated with body weight (5), and a recent canine genome-wide association study in Labrador Retrievers found that each allele of a risk variant from the DENND1B gene conferred approximately 7.5% higher body fat (15). DENND1B is expressed with MC4R in the hypothalamus, and research shows it might facilitate MC4R endocytosis, leading to reduced MC4R signaling and, therefore, increased appetite and decreased energy expenditure.

Figure 2. The energy homeostasis pathway starts with leptin (from fat) signaling the hypothalamus to activate POMC neurons. These produce MSH peptides, which act on MC4R to reduce hunger. A POMC gene deletion in dogs disrupts MSH production, leading to increased hunger and adiposity and decreased energy expenditure. A DENND1B gene variant in dogs also affects MC4R function, leading to higher body fat.
© Anna Morros-Nuevo/Redrawn by Sandrine Fontègne
While monogenic forms of obesity, like the POMC mutation in Labradors, involve a single gene with a large effect, obesity is typically a complex, polygenic trait (5,15). This means many genomic loci contribute incrementally to an individual’s susceptibility to obesity, and the net effect of these many variants, combined with environmental influences, determine whether obesity develops. A “polygenic risk score” for obesity can be calculated; this has been shown to predict BCS (body condition score) and food motivation in Labradors, supporting the notion that food motivation is an important genetic driver for obesity, both within a breed and between breeds (4,15) (Figure 1). Importantly, research shows that dogs with lower genetic risk resist obesity even with lax owner management, while those with higher genetic risk are significantly impacted by their environment and owner care (15) (Figure 3).

Figure 3. Owners of highly food-motivated dogs apply greater effort to control their dog’s weight compared to owners of “fussy eaters”. The four graphs show how BCS (and BCS adjusted for sex, age and neuter status) is affected by different owner management factors and how these effects vary for dogs in different risk group, according to their food motivation score (FMS). FMS is split into tertiles for the study population: green for dogs in the lowest tertile, orange for medium, and mauve for the highest tertile). Owner management factors and FMS were assessed via the DORA questionnaire (Table 1). The graphs illustrate that for any given level of owner management effort, highly food-motivated dogs (highest tertile – mauve) show greater adiposity compared to “less foody dogs” reflecting the difficulties owners face to deal with “pester power” of highly food-motivated dogs. Importantly though, all dogs can be kept at an ideal body weight with increased weight management effort. Figure and data from (4).
© Anna Morros-Nuevo/Redrawn by Sandrine Fontègne
The gene-environment interplay
The relationship between genetics and the environment is key to why some dogs gain weight and others don’t. Food motivation (i.e., an individual’s drive to seek and consume food) is a major behavioral factor for obesity development. The Dog Obesity Risk Assessment (DORA) questionnaire (16), a validated tool for assessing canine eating behavior (Tables 1 and 2), consistently shows a strong link between high food motivation and increased adiposity (4,9,13,15). This inherent drive, often genetically predisposed, makes certain dogs highly vulnerable to an “obesogenic environment”.
While genetics establish susceptibility, the environment and owner management are crucial in determining if a dog gains weight. Owners often find it challenging to implement necessary behavioral changes for their pet’s weight loss (17,18). Factors such as precise food portioning and restricting human food or table scraps heavily influence a dog’s body condition. For instance, owners of highly food-motivated dogs often exert greater control on weight management, but also tend to be less restrictive with human food, suggesting owners compensate for their dog’s strong drive to eat by restricting the main meal but perhaps succumbing to “pester power” by giving additional treats to dogs which are motivated to beg for them (Figure 3).
Table 1. Dog Obesity Risk Assessment (DORA) questionnaire adapted to clinical use. Print and provide this table to owners to identify their dog’s “level of greediness” and their own current level of intervention to modify their dog’s weight. The calculations for each factor are shown in Table 2.
| Never | Rarely | Sometimes | Often | Always | Factor | |
|---|---|---|---|---|---|---|
| My dog will turn down food if s/he is not hungry (R) | 1 | 0.75 | 0.5 | 0.25 | 0 | FM |
| My dog gets excited when there is food around | 0 | 0.25 | 0.5 | 0.75 | 1 | FM |
| My dog finishes a meal straight away | 0 | 0.25 | 0.5 | 0.75 | 1 | FM |
| After a meal my dog is still interested in eating | 0 | 0.25 | 0.5 | 0.75 | 1 | FM |
| My dog takes his/her time to eat a meal (R) | 1 | 0.75 | 0.5 | 0.25 | 0 | FM |
| My dog is choosy about which titbits he eats (R) | 1 | 0.75 | 0.5 | 0.25 | 0 | FM |
| My dog inspects unfamiliar foods before deciding whether to eat them (R) | 1 | 0.75 | 0.5 | 0.25 | 0 | FM |
| My dog eats titbits straight away | 0 | 0.25 | 0.5 | 0.75 | 1 | FM |
| My dog hangs around for titbits even if there is not much chance of getting them | 0 | 0.25 | 0.5 | 0.75 | 1 | FM |
| My dog hangs around when I am preparing or eating human food | 0 | 0.25 | 0.5 | 0.75 | 1 | FM |
| My dog gets human leftovers in his/her food bowl (R) | 1 | 0.75 | 0.5 | 0.25 | 0 | RHF |
| My dog gets bits of human food when we are eating (R) | 1 | 0.75 | 0.5 | 0.25 | 0 | RHF |
| My dog spends most of his/her walks off the lead | 0 | 0.25 | 0.5 | 0.75 | 1 | EX |
| My dog runs around a lot | 0 | 0.25 | 0.5 | 0.75 | 1 | EX |
| Not at all true | Somewhat true | Mainly true | Definitely true | Factor | |
|---|---|---|---|---|---|
| My dog is very greedy | 0 | 0.33 | 0.66 | 1 | FM |
| My dog seems to be hungry all the time | 0 | 0.33 | 0.66 | 1 | FM |
| My dog would eat anything | 0 | 0.33 | 0.66 | 1 | FM |
| I am careful to regulate the exercise my dog gets in order to keep him/her slim |
0 | 0.33 | 0.66 | 1 | OI |
| I alter the food my dog gets in order to control his/her weight | 0 | 0.33 | 0.66 | 1 | OI |
| I am careful about my dog‘s weight | 0 | 0.33 | 0.66 | 1 | OI |
| I weigh or measure how much food I give my dog | 0 | 0.33 | 0.66 | 1 | OI |
| My dog gets no food at human mealtimes | 0 | 0.33 | 0.66 | 1 | RHF |
| My dog often gets human food (R) | 1 | 0.66 | 0.33 | 0 | RHF |
| My dog gets a lot of exercise | 0 | 0.33 | 0.66 | 1 | EX |
| My dog’s walks are mostly on the lead (R) | 1 | 0.66 | 0.33 | 0 | EX |
| My dog’s walks involve a lot of energetic play or chasing | 0 | 0.33 | 0.66 | 1 | EX |
| I am happy with my dog’s weight (R) | 1 | 0.66 | 0.33 | 0 | OP |
| My dog is very fit (R) | 1 | 0.66 | 0.33 | 0 | OP |
| I think my dog could do with losing some weight | 0 | 0.33 | 0.66 | 1 | OP |
| Abbreviations; FM = food motivation score; OI = owner intervention score; RHF = restriction of human food score; EX = exercise score; OP = owner perception; R = reverse scoring | |||||
Table 2. Calculating the scores. The various factors (FM, RHF, OI, OP and EX)) are calculated as the sum of scores obtained from the corresponding statements, divided by the number of statements. Each statement is scored as Never (0) – Always (1) or Not at all true (0) – Definitely true (1), except for some statements where the scoring values are reversed (R). Owner Control (OC) is obtained as the sum of RHF, OI and EX divided by three. Note that the original questionnaire (16) also contained statements referring to gastrointestinal status, which are not used here as it is assumed that the clinician holds this information.
| Calculation | Results | Interpretation | |
|---|---|---|---|
| Food motivation score (FM) | = Sum of results /13 | Represents how food-oriented a dog is. In a mixed breed population of ~15,000 dogs, the mean was 0.63 with dogs being classified as highly food-motivated above 0.78 and low food- motivated under 0.50 (4). However, it is worth considering Figure 1 for breed averages. | |
| Owner intervention score (OI) | = Sum of results /4 | Identifies the overall strategic effort owners apply to control weight. Notice that owners might apply effort to increase what they perceive as inappropriately low body condition. Mixed breed population average is 0.60 (4). | |
| Restriction of human food score (RHF) | = Sum of results /4 | Contemplates the efforts to restrict consumption of table scraps and human food. Mean average in multi-breed population is 0.63 (4). | |
| Exercise score (EX) | = Sum of results /5 | Identifies the level of exercise and activity perceived by the owner. Mean multi-breed average is 0.65 (4). For reference, breed averages identified (unpublished data) go from < 0.6 for breeds like Greyhound, Maltese, Lhasa Apso, Dachshund, English Bulldog, American Cocker Spaniel, Rottweiler, Cavalier King Charles Spaniel, French Bulldog and Pug; 0.6-0.7 includes Golden Retriever, Staffordshire Bull Terrier, Jack Russell Terrier, Boxer, Australian Cattle Dog, German Shepherd Dog, Whippet, Labradoodle, Australian Shepherd; > 0.7 includes English Cocker spaniels, Springer Spaniels, Labrador Retriever, Weimaraner, Cockapoo, Pointer breeds, Border Collies | |
| Owner perception (OP) | = Sum of results /3 | Quantifies the perception of body weight status that the owner holds of their dog. No reference value available. | |
| Owner control score (OC) | = Sum of [OI + RHF + EX]/3 | This contemplates all three previous factors (Owner intervention, Restriction of human food and Exercise) and in a multibreed population this falls on 0.63 (4). |
Clinical implications and practical strategies
Proactive counseling from the veterinarian and veterinary staff on nutrition, exercise, and body condition monitoring should begin early, especially for predisposed breeds (Figure 4). Prevention is easier than treatment.

Figure 4. Early intervention and proactive counseling on nutrition, exercise, and body condition monitoring should begin as soon as possible, especially for predisposed breeds.
© Shuttertock
1) Recognize and acknowledge genetic predisposition:
- Breed predisposition: Be aware of high-risk breeds (e.g., Retriever breeds, Pugs, Beagles) to facilitate early intervention and owner discussions.
- Beyond “lack of discipline”: Educate owners that obesity is a complex, genetically influenced disease, not solely a result of poor care. This reduces owner guilt and boosts engagement.
- Genetic testing: While genetic testing is not routinely available, understanding the polygenic nature of obesity and specific mutations (such as POMC in Retrievers) can inform advice.
2) Identify at-risk individuals:
- Food motivation assessment: Use owner questionnaires, such as DORA (Tables 1 and 2), during wellness exams, especially for predisposed breeds or those showing early weight gain.
- Medication-induced risk: Medications known to increase appetite, such as glucocorticoids or antiseizure drugs (19), must be taken into account during an obesity risk assessment.
- Other factors: Acknowledge sex-specific effects of neutering (e.g., increased risk of neutering in males), aging, and variables like chocolate coat color in Labradors (9).
3) Tailor weight management strategies:
- Individualized approach: Develop plans that consider the dog’s genetic predisposition, owner’s lifestyle, and ability to make behavioral changes.
- Dietary management: Recommend specialized weight loss diets (high in protein and fiber) to enhance satiety and preserve lean muscle.
- Portion control: Provide clear, measured portion instructions and emphasize avoidance of free feeding. Discuss managing treats and human food, acknowledging common challenges.
- Exercise: Do not over-rely on exercise, as diet is the key factor for weight loss, although of course exercising offers other health benefits.
- Environmental enrichment: For highly food-motivated dogs, use puzzle feeders and interactive toys to engage natural foraging and slow eating, reducing frustration from simple food restriction.
4) Enhance owner communication and compliance:
- Avoid weight stigma: Discuss obesity empathetically. Explain that genetic variations in food drive can overwhelm good intentions, helping owners understand their dog’s struggle as a biological predisposition.
- Empower owners: Provide evidence-based resources, such as the GOdogs project website (20), to help owners address both dog and human behavioral factors.
- Set realistic expectations: Explain that weight loss is often slow with plateaus; celebrate small wins and provide ongoing encouragement. Regular follow-ups are crucial.
- Embrace the “pester power” challenge: Acknowledge owner struggles with highly food-motivated dogs. Offer empathy and practical solutions, such as non-food bonding activities or redirecting begging.
Obesity is typically a complex, polygenic trait. This means many genomic loci contribute incrementally to an individual’s susceptibility to obesity, and the net effect of these many variants, combined with environmental influences, determine whether obesity develops.
Conclusion
Canine obesity is a complex disease driven by multiple factors, extending beyond simple owner negligence. Recent scientific progress has illuminated the critical role of genetics, particularly when it comes to influencing traits like food motivation, in predisposing dogs to obesity. By integrating knowledge of genetic predispositions and food motivation with an understanding of environmental factors and owner behavior, veterinary professionals can develop more effective, empathetic, and personalized weight management strategies. Recognizing obesity as a disease with a strong genetic component is crucial for fostering better communication, improving owner compliance, and enhancing the health of our canine patients.
| The author has no conflict of interest to declare. |
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Anna Morros-Nuevo
LVet, MSc, GPCert(AnBeh), FCert(ECC), MRCVS, University of Cambridge, UK
Dr. Morros-Nuevo graduated from Barcelona in 2013 and worked in small animal first opinion and primary emergency clinics – in both Spain and the United Kingdom – until 2023, when she moved into a referral position. Alongside this, she undertook three postgraduate certifications prior to starting a part-time PhD at the University of Cambridge, as part of the GOdogs Project, which she currently combines with her clinical work.
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