The Genetic Basis of Obesity and Related Metabolic Diseases in Humans and Companion Animals

Obesity is one of the most prevalent health conditions in humans and companion animals globally. It is associated with premature mortality, metabolic dysfunction, and multiple health conditions across species. Obesity is, therefore, of importance in the fields of medicine and veterinary medicine. The regulation of adiposity is a homeostatic process vulnerable to disruption by a multitude of genetic and environmental factors. It is well established that the heritability of obesity is high in humans and laboratory animals, with ample evidence that the same is true in companion animals. In this review, we provide an overview of how genes link to obesity in humans, drawing on a wealth of information from laboratory animal models, and summarise the mechanisms by which obesity causes related disease. Throughout, we focus on how large-scale human studies and niche investigations of rare mutations in severely affected patients have improved our understanding of obesity biology and can inform our ability to interpret results of animal studies. For dogs, cats, and horses, we compare the similarities in obesity pathophysiology to humans and review the genetic studies that have been previously reported in those species. Finally, we discuss how veterinary genetics may learn from humans about studying precise, nuanced phenotypes and implementing large-scale studies, but also how veterinary studies may be able to look past clinical findings to mechanistic ones and demonstrate translational benefits to human research

Development, factor structure and application of the Dog Obesity Risk and Appetite (DORA) questionnaire.

Background. Dogs are compelling models in which to study obesity since the condition shares many characteristics between humans and dogs. Differences in eating behaviour are recognised to contribute to obesity susceptibility in other species but this has not been systematically studied in dogs. Aim. To develop and validate an owner-reported measure of canine eating behaviour and owner or dog related factors which can alter the development of obesity. Further, to then test variation in food-motivation in dogs and its association with obesity and owner management. Methods. Owner interviews, a literature review and existing human appetite scales were used to identify relevant topics and generate items for the questionnaire. Following a pilot phase, a 75 item online questionnaire was distributed via social media. Responses from 302 dog/owner dyads were analysed and factor structure and descriptive statistics calculated. Results were compared with descriptions of dog behaviour and management from a subset of respondents during semi-structured interviews. The optimum questions were disseminated as a 34 item final questionnaire completed by 213 owners, with a subset of respondents repeating the questionnaire 3 weeks later to assess test-retest reliability. Results. Analysis of responses to the final questionnaire relating to 213 dog/owner dyads showed a coherent factor structure and good test-retest reliability. There were three dog factors (food responsiveness and satiety, lack of selectivity, Interest in food), four owner factors (owner motivation to control dog weight, owner intervention to control dog weight, restriction of human food, exercise taken) and two dog health factors (signs of gastrointestinal disease, current poor health). Eating behaviour differed between individuals and between breed groups. High scores on dog factors (high food-motivation) and low scores on owner factors (less rigorous control of diet/exercise) were associated with obesity. Owners of more highly food-motivated dogs exerted more control over their dogs' food intake than those of less food-motivated dogs. Conclusions. The DORA questionnaire is a reliable and informative owner-reported measure of canine eating behaviour and health and management factors which can be associated with obesity development. The tool will be applicable to study of the canine obesity model and to clinical veterinarians. Results revealed eating behaviour to be similarly associated with obesity as exercise and owners giving titbits

A Deletion in the Canine POMC Gene Is Associated with Weight and Appetite in Obesity-Prone Labrador Retriever Dogs.

Sequencing of candidate genes for obesity in Labrador retriever dogs identified a 14 bp deletion in pro-opiomelanocortin (POMC) with an allele frequency of 12%. The deletion disrupts the β-MSH and β-endorphin coding sequences and is associated with body weight (per allele effect of 0.33 SD), adiposity, and greater food motivation. Among other dog breeds, the deletion was only found in the closely related flat-coat retriever (FCR), where it is similarly associated with body weight and food motivation. The mutation is significantly more common in Labrador retrievers selected to become assistance dogs than pets. In conclusion, the deletion in POMC is a significant modifier of weight and appetite in Labrador retrievers and FCRs and may influence other behavioral traits.We are grateful to Rachel Moxon of Guide Dogs UK for collecting the assistance dog samples; Stephen J Sharp of the MRC Epidemiology Unit for his statistical advice; Jens Häggström, Karin Hultin Jäderlund and Berndt Klingeborn for the Swedish dog samples; Anne White for efforts to develop a canine beta MSH assay and adaptation of her original for figure 1b; and the Dogslife Consortium for samples from British Labrador retrievers (supported by an Institute Core Strategic Grant from the BBSRC to the Roslin Institute). A full list of the investigators who contributed to the Dogslife project is available from www.dogslife.ac.uk/who-runs-dogslife. AJG's academic post at the University of Liverpool is financially supported by Royal Canin. The work was primarily supported by the Wellcome Trust (Senior Investigator Award 095515/Z/11/Z and Strategic Award 100574/Z/12/Z), MRC (MRC Metabolic Diseases Unit, award 4050281695 and MRC_MC_UU_12012/5), and Dogs Trust. The authors would like to thank all the veterinary surgeons and nurses, owners and dogs who contributed samples.This is the final version of the article. It first appeared from Elsevier via https://doi.org/10.1016/j.cmet.2016.04.01

Retriever_POMC_phenotypes_2023

Data are results from experiments in which we measured phenotypes including weight, adiposity, food motivation, blood pressure, energy expenditure in Labrador and flatcoat retriever dogs with and without a mutation in the gene POMC which was previously described in Raffan 2016 (PMID: 27157046). Each worksheet in the excel file can be exported as plain text for analysis with accompanying code. In addition there is a README tab with experimenter contact information, and a Participation Summary sheet which shows which dogs took part in the different experiments. FCR_epi and RCR_epi_readme: Flatcoat retriever epidemiology information and data. EndocrineTests: Results of ACTH, TT4, TSH BP: Blood pressure data EnergyExp: indirect calorimetry data from FCR FoodPreference, AdLibitum, IncentiveSalience: data from different eating behaviour experiments.Wellcome Trust 205187/Z/16/Z and 095515/Z/11/Z BBSRC BB/M011194/1 BB/S017593/1 Dogs Trust. MRC (MRC_MC_UU_00014/1; MR/S026193/1)

Lessons from Labradors on the genetics and physiology of obesity - implications for management

INTRODUCTION As many as 65% of pet dogs are overweight or obese1,2. Dogs gain weight following chronic energy imbalance, during which energy intake from food exceeds energy expended at exercise. Being obese is associated with an increased incidence of metabolic, endocrine, respiratory, orthopaedic, dermatological, neoplastic and other disease that means clinicians should be concerned with its prevention and treatment3. At the most fundamental level, obesity shortens lives, with obese dogs dying on average 1-2 years earlier4. There is evidence that the quality of life of overweight dogs is lower compared to lean dogs and that quality of life improves after weight loss5-7

Obesity as an Endocrine Disease: Theory and Clinical Application

WHAT CAUSES OBESITY? At its most simplistic, this is easy to answer – an individual piles on the pounds because there is a mismatch between energy intake and expenditure. That balance is most commonly affected by alterations in food intake and energy expended during exercise, but may also be influenced by the efficiency of substrate utilisation, factors that alter metabolic rate, and/or nutrient partitioning (storage of excess calories). The veterinary literature has mainly focussed on how owners manage their dogs and has identified many predictable food and exercise related risk factors. But breed, age and gender also consistently identified as risk factors for obesity and remain there even when management factors are evened out in mathematical modelling, meaning their effect is physiological and independent of owners. So, while the physics of the energy balance equation between intake and expenditure is true, and owners should be able to control their dogs’ food an exercise to keep them lean, it is disingenuous to dismiss the role of physiology in obesity development

A Comprehensive Review of the Role of Genetics in Obesity in Dogs and Other Species

Obesity is a big problem. In recent years, the increasing incidence of obesity in companion animal species, particularly dogs, cats and horses, has attracted headlines. Near universally, poor owner management of diet and exercise are blamed for this increase in the press. However, there is a weight of evidence that obesity is perhaps best viewed as a complex homeostatic mechanism gone awry, influenced by genetics. In this lecture, I will review the role of genetics in influencing obesity susceptibility in dogs and other species and touch on what genetic studies have taught us about obesity biology

The Genetic Basis of Obesity and Related Metabolic Diseases in Humans and Companion Animals

Obesity is one of the most prevalent health conditions in humans and companion animals globally. It is associated with premature mortality, metabolic dysfunction, and multiple health conditions across species. Obesity is, therefore, of importance in the fields of medicine and veterinary medicine. The regulation of adiposity is a homeostatic process vulnerable to disruption by a multitude of genetic and environmental factors. It is well established that the heritability of obesity is high in humans and laboratory animals, with ample evidence that the same is true in companion animals. In this review, we provide an overview of how genes link to obesity in humans, drawing on a wealth of information from laboratory animal models, and summarise the mechanisms by which obesity causes related disease. Throughout, we focus on how large-scale human studies and niche investigations of rare mutations in severely affected patients have improved our understanding of obesity biology and can inform our ability to interpret results of animal studies. For dogs, cats, and horses, we compare the similarities in obesity pathophysiology to humans and review the genetic studies that have been previously reported in those species. Finally, we discuss how veterinary genetics may learn from humans about studying precise, nuanced phenotypes and implementing large-scale studies, but also how veterinary studies may be able to look past clinical findings to mechanistic ones and demonstrate translational benefits to human research

The Genetic Basis of Obesity and Related Metabolic Diseases in Humans and Companion Animals

Obesity is one of the most prevalent health conditions in humans and companion animals globally. It is associated with premature mortality, metabolic dysfunction, and multiple health conditions across species. Obesity is, therefore, of importance in the fields of medicine and veterinary medicine. The regulation of adiposity is a homeostatic process vulnerable to disruption by a multitude of genetic and environmental factors. It is well established that the heritability of obesity is high in humans and laboratory animals, with ample evidence that the same is true in companion animals. In this review, we provide an overview of how genes link to obesity in humans, drawing on a wealth of information from laboratory animal models, and summarise the mechanisms by which obesity causes related disease. Throughout, we focus on how large-scale human studies and niche investigations of rare mutations in severely affected patients have improved our understanding of obesity biology and can inform our ability to interpret results of animal studies. For dogs, cats, and horses, we compare the similarities in obesity pathophysiology to humans and review the genetic studies that have been previously reported in those species. Finally, we discuss how veterinary genetics may learn from humans about studying precise, nuanced phenotypes and implementing large-scale studies, but also how veterinary studies may be able to look past clinical findings to mechanistic ones and demonstrate translational benefits to human research

Dataset and code corresponding to the journal article 'Increased food motivation and adiposity based on caregiver survey in dogs receiving anti-seizure drugs'

The R code contains everything necessary to replicate the study. The dataset provided is the final sample population used for the study which contains a control group that has already been matched by sex, neuter status, and breed as closely as possible to the epileptic study group. The columns correspond to the following: - ID: randomly allocated to preserve the anonymity of participating. dogs. - Group: Control (healthy dogs), IE (idiopathic epilepsy). - Group_binomial: 0 = control/healthy, 1 = Idiopathic epilepsy. - SEX, NEUTER, Breed and Dog_Age are self-explanatory. Age is provided in years. - Sex_binomial: 0=female, 1=male. - Neuter_binomial: 0=entire, 1=neutered. - Dog_shape: owner-reported BCS (1-9). - F_CombinedGreedFactors: DORA's dog Food Motivation Score (0-1). - F1_ResponsivenessAndSatiety: Food Motivation Score subfactor 'Responsiveness and Satiety Score' (0-1). - F2_LackOfFussiness: Food Motivation Score subfactor 'Lack of Fussiness Score' (0-1). - F3_InterestInFood: Food Motivation Score subfactor 'Interest in Food Score' (0-1). - F_Owner_Intervention: DORA's owner management factor 'Owner Intervention Score' (0-1). - F_Restriction_Human_Food: DORA's owner management factor 'Restriction of Human Food Score' (0-1). - F_Exercise_Taken: DORA's owner management factor 'Exercise Score' (0-1). - F_Owner_Control: DORA's owner management factor 'Owner Control Score' (0-1). For the epileptic group only, the following variables are included: - Seizure_age_diagnosis: age at which idiopathic epilepsy was diagnosed (years). - AED_Which: which anti-seizure drug is the dog currently taking? multiple choices were available. - Appetite_WhichDrug: corresponds to the question 'Which drug is affecting your dog's appetite the most?' provided to respondents who selected more than one anti-seizure drug. - Therapy_num: number of anti-seizure drugs being administered to their dog. The following questions were answered as 'Not at all true', 'Somewhat true', 'Mainly true' or 'Definitely true' in relation to the mentioned side effect of the current anti-seizure treatment received - CurrentTreatment_Energy: reduced energy - CurrentTreatment_Coordination: decreased coordination. - CurrentTreatmetn_Hunger: increased hunger - CurrentTreatemnt_FoodIntake: increased food intake. In relation to the administration of anti-seizure drugs, the following questions were responded to as 'Never', 'Rare;y, 'Sometimes', 'Often', or 'Always': - treats.to.administer.treatment: corresponds to the question 'Do you use treats to administer the treatment?' - AfterSeizure_food: corresponds to the question 'Do you give your dog treats because he/she had a seizure?'. - BeforeSeizure_Treat: corresponds to the question 'Do you give your dog treats because they are going to have a seizure?' - Epilepsy_Treats: corresponds to the question 'Do you give your dog extra treats or food because they have epilepsy?' - Treats_FoodCompensation: corresponds to the question 'Do you alter meals to compensate for treats?'. The following questions classify the study population through different groups of interest: - Control_IEwithASD: Control = healthy dogs, IE = Epileptic dogs taking anti-seizure drugs. - Control_IE_PolyMonoNaive: Control = healthy dogs, IE Polytherapy = epileptic dogs receiving polytherapy of anti-seizure drugs, IE Monotherapy = Epileptic dogs receiving one anti-seizure drug, IE Drug Naive = Epileptic dogs not receiving anti-seizure drugs. - Control_IE_PolyMono: Control = healthy dogs, IE Polytherapy = epileptic dogs receiving polytherapy of anti-seizure drugs, IE Monotherapy = Epileptic dogs receiving one anti-seizure drug