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Author: KATHERINE R. BELSITO and KELLY S. SWANSON - University of Illinois, Urbana, Illinois, USA (Courtesy of Alltech Inc.)
The obesity epidemic that has been sweeping the human population is now highly prevalent in our dog and cat populations as well. In developed countries, approximately 22 to 44% of dogs are considered overweight or obese (Lewis, 1978; Norris and Beaver, 1993; Armstrong and Lund, 1996; McGreevy et al. 2005), while overweight and obese cats make up 20 to 40% of the cat population (Sloth, 1992; Scarlett et al., 1994; Lund et al., 2005; Burkholder and Toll, 2000).
Although numerous factors contribute to obesity, the importance of adipose tissue in energy homeostasis is becoming increasingly apparent. This brief review will highlight the importance of adipocyte metabolism and genomic biology, as researchers try to understand the etiology and devise prevention and treatment strategies.
A general definition of obesity is an accumulation of excessive amounts of adipose tissue in the body. A more meaningful definition states that overweight cats and dogs are defined as having a body weight (BW) greater than 15% of their ‘optimal BW’ and obese ones have a BW that exceeds 30% of optimal BW (Burkhold and Toll, 2000).
However, a lack of information regarding standard weights for cats and the wide variety in size and body frames of different cat and dog breeds limits the use of this definition.
More suitable definitions of adiposity involve evaluating body composition, more specifically, percent fat mass and lean body mass. However, techniques such as dual energy x-ray absorptiometry (DEXA) are expensive and often not economically feasible for owners. Body condition scoring and other methods for body composition analysis generally define overweight or obese dogs as having fat mass percentages greater than 30%. The multitude of methods available and varying definitions of obesity, while useful, may also pose a problem when it comes to replicating and sharing results in obesity research.
While defining obesity may be a challenge, there is a general agreement that the factors contributing to the development of obesity are many. Two of the most common factors, a shift to a more sedentary lifestyle and access to calorically dense, highly palatable foods, are the same factors that are often named as major contributors to human obesity. Gender is another factor, with female dogs and male cats having a greater risk than their counterparts. Age is also becoming a risk factor, as modern veterinary practices and better nutrition are allowing our dogs and cats to live longer lives.
Other factors include spaying and neutering and genetics. Recent studies have determined that weight gain associated with gonadectomy may be the result of a decreased metabolic rate, increased food intake, decreased physical activity level, increased efficiency of nutrient utilization, or a combination of these factors (Fettman et al., 1997; Jeusette et al., 2004; Jeusette et al., 2006). These alterations are thought to be the result of the elimination of gonadal steroids and the resulting disturbance of other key regulators of food intake and energy expenditure.
The Labrador Retriever, Cairn Terrier, Cavalier King Charles Spaniel, Scottish Terrier, and Cocker Spaniel are dog breeds associated with an increased incidence of obesity (Edney and Smith, 1986; Mason, 1970). Cats with a mixed breed ancestry may be at a higher risk of developing obesity, also (German, 2006). While numerous factors have been identified as likely causes for the onset of obesity, the amount of influence each factor has and the mechanisms involved remain complex and vaguely understood.
Adipose tissue and energy homeostasis
Until recently, adipose tissue was thought to function merely as a depot for storing the body’s most abundant fuel. Adipose tissue collects excess energy and stores it in the form of triglycerides (TG) to be used at a later time.
In 1994, leptin was discovered, which led to a radical change in the way we view and understand adipose tissue. Since leptin’s discovery, adipose tissue has emerged as a major endocrine tissue secreting proteins, commonly known as adipokines that are crucial in regulating energy metabolism. Table 1 presents an incomplete list of known adipokines and their actions (Ronti et al., 2006).
With the rising incidence of obesity in humans and animals alike, elucidating and understanding adipokines and their influence on adipose metabolism may prove vital to understanding obesity and its prevention.
Energy balance is regulated by the interaction between neural and hormonal signaling.
Adipose tissue is a key player in energy balance maintenance. Lipogenesis occurs when excess energy is present. Through the action of lipoprotein lipase, circulating chylomicrons and very low density lipoproteins are hydrolyzed to free fatty acids, which can be taken up and converted to triglycerides and stored in the adipocytes.
During periods of low energy availability, triglycerides are hydrolyzed by the enzyme hormone sensitive lipase and released as glycerol or free fatty acids to be used by other tissues for energy. Insulin is a major regulator of lipogenesis, stimulating lipoprotein lipase and other enzymes involved in the conversion of free fatty acids to triglycerides and mediating the uptake of glucose needed for triglyceride re-esterification.
There is overwhelming evidence that animals have evolved to conserve energy. Hormones involved with reduced food intake and increased energy expenditure act on short-term appetite control rather than the depletion of energy stores (Wilding, 2002).
As a result, the majority of animals are programmed to store energy more efficiently than to expend it. Given the western lifestyle and the abundance of high quality foods, the body is now relying on mechanisms to monitor and control body adiposity. The lipostatic theory states that body adiposity is communicated to the central nervous system via adipokines such as leptin, which influences energy intake and expenditure accordingly (Loftus, 1999; Schwartz et al., 1999; Woods and Seeley, 2000; Weigle et al., 1998).
When this complex signaling system is disrupted, however, abnormal metabolic regulation may result in pathologic conditions.
Table 1. Incomplete list of adipokines and their primary function(s).


Because adipose tissue is the main mediator of fatty acid metabolism, it is metabolically connected with other tissues, especially skeletal muscle. Dysregulation of adipose metabolism, therefore, does not remain an isolated problem. A prime example is the case of insulin resistance.
In recent years, an abundance of papers have been published linking insulin resistance with the rising incidence of obesity and type 2 diabetes. Insulin resistance of tissues such as skeletal muscle results in the reduced ability of insulin to stimulate glucose transport and utilization (Cahova et al., 2006). Controversy still exists as to the exact cause of insulin resistance and whether it originates in adipose or skeletal muscle tissue.
Growing evidence suggests that a net positive energy balance (obesity) and resulting dysregulation of fat metabolism are key factors in the pathogenesis of insulin resistance (Lewis et al., 2002). The dysregulation of fat metabolism includes the impaired ability of insulin to suppress hormone-sensitive lipase (Chen et al., 1987; Groop et al., 1989) and up-regulate lipoprotein lipase activities (Ong and Kern, 1989; Coppack et al., 1992).
The fact that adipose tissue also secretes several proteins having insulin-sensitizing or - desensitizing effects suggests that adipose tissue is the primary site of origin of insulin resistance.
The dysregulation of fat metabolism often manifests itself as dyslipidemia. It is thought that elevated levels of free fatty acids cause altered glucose metabolism due to substrate competition, changes in enzyme regulation, and changes in intracellular signaling and/ or gene transcription (Kraegen, 1997).
In free fatty acid-dependent tissues like skeletal muscle, these disturbances are thought to result in the accumulation of intracellular fatty acid metabolites that induce insulin resistance (Cahova et al., 2006). In healthy individuals, skeletal muscle is metabolically flexible and is capable of switching between fatty acid and carbohydrate metabolism depending on the substrates present (Andres et al., 1956; Kelley et al., 1990). Insulin-resistant skeletal muscle is unable to maintain its metabolic flexibility, further exacerbating the condition.
Obese cats and dogs have been shown to develop insulin resistance and abnormal lipoprotein metabolism (Jeusett et al., 2006; Hoenig et al., 2002; Wilkins et al., 2004). Thus, many of the mechanisms contributing to metabolic inflexibility in cats and dogs are thought to be similar to those that have been demonstrated in humans. To date, very little has been done to study gene expression profiles of adipose tissue and whole body metabolism in obese dogs and cats.
Using genomic biology to study adipocyte metabolism
The Human Genome Project and other technologic developments sparked the ‘omics’ era of research. Aided by genome sequencing, our knowledge in countless areas of research has expanded exponentially. The advances in genomic biology, computer science, and nanotechnology have resulted in many new research techniques and more sophisticated equipment. These advances have enabled the study of RNA, DNA, and protein expression more efficiently from both a time and cost standpoint.
For example, reverse transcriptasepolymerase chain reaction (RT-PCR) is currently one of the most sensitive techniques for measuring and detecting levels of mRNA. As our research tool kit and knowledge base has expanded, more branches of genomic biology such as proteomics, metabolomics, and functional genomics (including nutritional genomics) have developed.
From a health standpoint, research into the various genomic areas is proving to be an exciting venture. As a result, the ‘omics’ era could not have come at a better time as it has allowed researchers to make strides towards understanding, treating, and preventing diseases, including obesity and diabetes mellitus that have become epidemics in the United States. Humans are not the only ones under threat, as the numbers of obese and diabetic dogs and cats have increased at a disturbingly high rate over the past years.
While the mechanisms underlying obesity remain ambiguous, the tools are now available to study this exciting area of science that may identify strategies for treatment and prevention.
Canine adipose gene expression
Our lab recently employed the use of a canine microarray to explore the effects of diet on adipose gene expression profiles of young adult and geriatric dogs. Six geriatric (11 years old at baseline) and six young (eight weeks old at baseline) female Beagles were randomly assigned to one of two diets: 1) Animal-protein-based diet (APB) containing 28% protein, 23% fat, and 5% dietary fiber; or 2) Plant-protein-based diet (PPB) containing 26% protein, 11% fat, and 15% dietary fiber. Dogs remained on experiment for 12 months.
RNA was isolated from adipose tissue samples using Trizol (Invitrogen, Carlsbad, CA), followed by RNeasy clean up kits (Qiagen, Valencia, CA) and hybridized to Affymetrix GeneChip Canine Genome Arrays 2.0 (Affymetrix), as per the manufacturer’s instructions. After microarray normalization, data were analyzed using limma package cell means model (Bioconductor). Transcripts having a P<0.05 and >1.5-fold change were considered significantly different between groups.
Very few main effects of diet were observed in this experiment (five transcripts). The main effect of age had a greater impact, altering 52 transcripts. Numerous diet × age interactions were also observed. The majority of gene transcripts up-regulated in geriatric dogs versus young adult dogs appear to be linked to processes involved in increased immune response, cell adhesion and repair and decreased transcription and signal transduction.
The process of aging results in stress on mechanisms trying to cope with progressively inefficient systems in the body (Slawik and Vidal-Puig, 2006) and may explain why the incidence of many diseases, including obesity, and physiologic abnormalities increase with age. Gene interactions were identified using Ingenuity Pathway Analysis (Ingenuity Systems Inc., Redwood City, CA). These analyses have identified two gene networks (example in Figure 1) that have provided insight into the processes and pathways that are influenced by age in adipose tissue.


Figure 1. Gene network affected by age in adipose tissue of canines.
These preliminary data are a beginning towards understanding the process of normal aging. Similar strategies may be used to elucidate the etiology of obesity as well. Genomic biology enables researchers to elucidate complex interactions and pathways by breaking them down into step-by-step processes. The benefit of modern technology and the vast array of genomic tools allow these processes to then be reassembled to understand the entire system. Hopefully this concept can be applied to obesity and help us combat the rise of this disease and its co-morbidities in our dog and cat populations.
References
Andres, R., G. Cader and K. Zierler. 1956. The quantitatively minor role of carbohydrate in oxidative metabolism by skeletal muscle in intact man in the basal state. Measurement of oxygen and glucose uptake and carbon dioxide production in the forearm. J. Clin. Invest. 35:671-682.
Armstrong, P.J. and E.M. Lund. 1996. Changes in body composition and energy balance with aging. Vet. Clin. Nutr. 3:83-87.
Burkholder, W.J. and P.W. Toll. 2000. Obesity. In: Small Animal Clinical Nutrition (M.S Hand, C.D. Thatcher, R.L. Reimillard, P. Roudebush, M.L. Morris and B.J. Novotny, eds). 4th edition, Mark Morris Institute, Topeka, KS, USA, pp. 401-430.
Cahova, M., H. Vavrinkova and L. Kazdova. 2006. Glucose-fatty acid interaction in skeletal muscle and adipose tissue in insulin resistance. Physiol. Res. (in press).
Chen, Y.D., A. Golay, A. Swislocki and G.M. Reaven. 1987. Resistance to insulin suppression of plasma free fatty acid concentrations and insulin stimulation of glucose uptake in noninsulin dependent diabetes mellitus. J. Clin. Endocrinol. Metab. 64:17-21.
Coppack, S.W., R.D. Evans, R.M. Fischer, K.N. Frayn, G.G. Gibbons, S.M. Humphreys, M.L. Kirk, J.L. Potts and T.D. Hockaday. 1992. Adipose tissue metabolism in obesity: lipase action in vivo before and after a mixed meal. Metabolism 41:264-272.
Edney, A.T. and P.M. Smith. 1986. Study of obesity in dogs visiting veterinary practices in the United Kingdom. Vet. Rec. 118:391-396.
Fettman, M.J., C.A. Stanton, L.L. Banks, D.W. Hamar, D.E. Johnson, R.L. Hegstad and S. Johnston. 1997. Effects of neutering on body weight, metabolic rate and glucose tolerance of domestic cats. Res. Vet. Sci. 62:131-136.
German, A.J. 2006. The growing problem of obesity in dogs and cats. J. Nutr. 136:1940S- 1946S.
Groop, L.R. Bonadonna, S. Del Prato, K. Ratheiser, K. Zyck, E. Ferrannini and R.A. DeFronzo. 1989. Glucose and free fatty acid metabolism in non-insulin dependent diabetes mellitus. Evidence for multiple sites of insulin resistance. J. Clin. Invest. 82:205-213.
Hoenig, M., S. Alexander, J. Holson and D.C. Ferguson. 2002. Influence of glucose dosage on interpretation of intravenous glucose tolerance tests in lean and obese cats. J. Vet. Intern. Med. 16:529-532.
Jeusette, I., J. Detilleux, C. Cuvelier, L. Istasse and M. Diez. 2004. Ad libitum feeding following ovariectomy in female Beagle dogs: Effect on maintenance energy requirement and on blood metabolites. J. Anim. Phys. Anim. Nutr. 88:117-121.
Jeusette, I, S. Daminet, P. Nguyen, H. Shibata, M. Saito, T. Honjoh, L. Istasse and M. Diez. 2006. Effect of ovariectomy and ad libitum feeding on body composition, thyroid status, ghrelin and leptin plasma concentrations in female dogs. J. Anim. Phys. Anim. Nutr. 90:12-18.
Kelley, D.E., J. Reilly, T. Veneman and L.J. Mandarino. 1990. Effect of insulin on skeletal muscle glucose storage, oxidation and glycolysis in humans. Am. J. Physiol. 258:E923- E929.
Kraegen, E. 1997. Activation of protein kinase C-epsilon may contribute to muscle insulin resistance induced by lipid accumulation during chronic glucose infusion in rats. Diabetes 46:241A.
Lewis, L.D. 1978. Obesity in the dog. J. Am. Anim. Hosp. Assoc. 14:402-409.
Lewis, G.F., A. Carpenter, K. Adeli and A. Giacca. 2002. Disordered fat storage and mobilization in the pathogenesis of insulin resistance and type 2 diabetes. Endocr. Rev. 23:210-229.
Loftus, T.M. 1999. An adipocyte-central nervous system regulatory loop in the control of adipose homeostasis. Semin. Cell Dev. Biol. 10:11-18.
Lund, E.M., P.J. Armstrong, C.A. Kirk and J.S. Klausner. 2005. Prevalence and risk factor for obesity in adult cats from private US veterinary practices. Int. J. Appl. Res. Vet. Med. 3:88-96.
Mason, E. 1970. Obesity in pet dogs. Vet. Rec. 86:612-616.
McGreevy, P.D., P.C. Thomson, C. Pride, A. Fawcett, T. Grassi and B. Jones. 2005. Prevalence of obesity in dogs examined by Australian veterinary practices and the risk factors involved. Vet. Rec. 156:695-707.
Norris, M.P. and B.V. Beaver. 1993. Application of behavior therapy techniques to the treatment of obesity in companion animals. J. Am. Vet. Med. Assoc. 202:728-730.
Ong, J. and P. Kern. 1989. Effect of feeding and obesity on lipoprotein lipase activity, immunoreactive protein and messenger RNA levels in human adipose tissue. J. Clin. Invest. 84:305-311.
Ronti, T., G. Lupattelli and E. Mannarino. 2006. The endocrine function of adipose tissue: an update. Clin. Endocrin. 64:355-365.
Scarlett, J.M., S. Donoghue, J. Saidla and J. Wills. 1994. Overweight cats: Prevalence and risk factors. Int. J. Obes. Relat. Metab. Disord. 18:S22-S28.
Schwartz, M.W., D.G. Baskin, K. J. Kaiyala and S.C. Woods. 1999. Model for the regulation of energy balance and adiposity by the central nervous system. Am. J. Clin. Nutr. 69:584- 596.
Slawik, M. and A.J. Vidal-Puig. 2006. Lipotoxicity, overnutrition and energy metabolism in aging. Ageing Res. Rev. 5:144-164.
Sloth, C. 1992. Practical management of obesity in dogs and cats. J. Small Anim. Pract. 33:178-182.
Weigle, D.S., A.M. Hutson, J.M. Kramer, M.G. Fallon, J.M. Lehner, S. Lok and J.L. Kuijper. 1998. Leptin does not fully account for the satiety activity of adipose tissueconditioned medium. Am. J. Physiol. 275:R976-R985.
Wilding, J.P.H. 2002. Neuropeptides and appetite control. Diab. Med. 19:619-627.
Wilkins, C., Long, Jr., R.C., M. Waldron, D.C. Ferguson and M. Hoenig. 2004. Effects of obesity on lipid profiles in neutered male and female cats. Am. J. Vet. Res. 65:1090-1099.
Woods, S.C. and R.J. Seeley. 2000. Adiposity signals and the control of energy homeostasis. Nutrition 16:894-902.
Author: KATHERINE R. BELSITO and KELLY S. SWANSON - University of Illinois, Urbana, Illinois, USA (Courtesy of Alltech Inc.)
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