The prevalence of obesity in the US is increasing exponentially across gender, age and ethnic groups. Obesity and a long-term hypercaloric diet result in what appears to be accelerated aging, often leading to a multi-systemic deterioration known as the metabolic syndrome. Due to their physiological similarity to humans as well as comparable rates of spontaneous obesity and diabetes mellitus, nonhuman primates provide a useful translational model for the human condition. They allow for an in vivo study of disease progression, interaction of comorbidities, and novel interventions. However, defining obesity in aged humans and nonhuman primates is difficult as the physiological changes that occur with aging are not accounted for using our current systems (BMI - body mass index and BCS - body condition score). Nonetheless, nonhuman primate studies have greatly contributed to our understanding of obesity and metabolic dysfunction and should continue to play a large role in translational research. Here, methods for defining obesity and metabolic syndrome in humans and nonhuman primates are described along with the prevalence and effects of these conditions.

Obesity is quickly replacing smoking as the leading cause of death for adults in developed countries, contributing to nearly 20% of all deaths in the US [1]. Moreover, obesity is associated with many comorbidities, including cardiovascular disease (CVD), type II diabetes mellitus (T2DM), and cancer, thereby presenting a higher risk of all-cause mortality [2,3]. As such, the economic and healthcare burden of obesity is immense and growing exponentially.

In an attempt to describe the extent of the obesity problem in our country, Ladabaum et al. [4] carried out several cross-sectional surveys. Through their work they determined that, since 1990, the prevalence of abdominal obesity has increased across age groups, with annual increases being more pronounced in the youngest group and abdominal obesity prevalence increasing with age [4]. Similar results were found with regard to average increases in waist circumference [4]. Since 1990, average body mass index (BMI) and waist circumference have increased by 0.37% per year among men and women of all ages and ethnic groups across the country [4]. In both obese persons and persons of normal weight, waist circumference is an independent predictor of morbidity and mortality [5,6].

The health consequences of increased visceral adiposity caused by a long-term, chronic, hypercaloric diet is a multi-systemic deterioration resulting in an increased risk for developing metabolic syndrome (MetS) [7]. MetS is diagnosed when 3 or more of the following characteristics are identified: (1) enlarged waist circumference, (2) elevated triglycerides, (3) decreased high-density lipoprotein cholesterol, (4) elevated blood pressure, and (5) increased fasting glucose [8]. In addition, each 11-cm increase in waste circumference is associated with an 80% increase in the risk of developing MetS over the following 5 years [7]. Likewise, as we age, the chance of developing metabolic disorders rises [4]. This statistic, along with the increasing obesity rates seen in the aging population, creates the potential for exponentially higher rates of visceral adiposity, insulin resistance, impaired glucose tolerance, overt T2DM, hypertension, dyslipidemia, and/or cardiovascular complications among the elderly population. In fact, recently published analyses of the NHANES cross-sectional study data, conducted between 2011 and 2012, revealed that the prevalence of T2DM among a nationally representative sample of US adults was highest in citizens aged 65 and over (33%) compared to younger cohorts (aged 45-64 years, 17.5%; aged <45 years, 5.0%) [9]. For this reason, it is progressively becoming more important to find adequate research models of obesity and aging in order to (1) better define how these conditions interact, (2) examine long-term consequences, and (3) study possible interventions.

Nonhuman primates (NHPs) and companion animals have obesity rates comparable to humans, ranging from 22 to 40% of the US population [10]. Though obesity can be induced in animal models when exposed to hypercaloric diets, reports of spontaneous obesity are common among NHPs, specifically rhesus and cynomolgus macaques, vervet monkeys, and squirrel monkeys [10,11,12]. Along with their close genetic relatedness, NHPs have obesity-related physiologic changes that are very similar to those of humans, making NHPs a valuable research model for obesity and aging [13]. These animals also carry similar rates of metabolic diseases and spontaneously develop T2DM at rates which increase with age [14,15].

In contrast, caloric restriction (CR) is associated with a decreased risk of age-associated pathologies in humans and NHPs [16,17,18]. CR is studied with regard to its potential benefits, increasing health span and extending life span, while obesity has been linked to diminished health and accelerated aging. NHP studies have shown that CR lowers insulin levels and results in decreased incidence of T2DM compared to controls [19,20]. Human studies have shown similar beneficial metabolic effects in overweight individuals after 6 months of CR, improving cardiovascular health along with other biomarkers of aging [21,22,23]. These results suggest that CR may provide protection against the development of T2DM and insulin resistance and, therefore, provides a useful tool for investigating mechanisms of aging and age-associated diseases. In fact, there are currently parallel longitudinal studies, at the National Institute on Aging (NIA) and the Wisconsin National Primate Research Center (WNPRC), using NHPs to investigate this phenomenon [17,24]. Preliminary findings from these studies have mixed results with regards to CR and extension of life span, but both have found an association between CR and extended health span [17,24]. In practice, CR is a difficult intervention to implement among the human population. As such, obesity and diabetes remain a prevalent health concern in the aging population.

In this review, the contributions made by NHP models of obesity and metabolic dysfunction are summarized.


In humans, obesity is defined as a BMI of ≥30 kg/m2, yet a BMI of 25.0-29.9 kg/m2 has been associated with an increased risk of death [3]. Defining obesity in monkeys is a similar process, though two measures are commonly used: (1) measures of abdominal fat folds, BMI, and abdominal circumference, or (2) waist/hip ratio and the circumference of the thigh (waist/thigh ratio) [25]. When compared to radioisotope methods in a cross-sectional analysis, both methods for defining obesity in rhesus monkeys were found to be highly correlated with body fat [25]. However, this analysis did not take weight across the life span into account [25].

Though fairly straightforward in young and healthy humans and NHPs, age-related changes in body composition make defining obesity in the aged population quite challenging [26]. For example, aging is associated with decreases in fat-free mass (termed sarcopenia), increases in fat mass, kyphosis, and compression of vertebrae leading to loss of height [26]. These variances, along with gender differences, are not taken into account when using BMI and body weight to determine obesity. Similarly, comparable difficulties are faced when assigning body condition scores [27] (a subjective measure of body fat) in an aged rhesus monkey colony.

Another factor complicating the story of obesity and aging is the obesity paradox. Here, obesity is thought to serve as a protectant of sorts after a certain age because elderly obese individuals seem to live longer and have fewer and shorter hospital stays compared to age-matched people of normal weight [26,28]. However, more recent studies have shown a much stronger association between obesity and morbidity in the elderly when various confounding factors are controlled (e.g. cohort factors and duration of life spent obese) [1,29]. The existence of an obesity paradox is a controversial topic with mixed findings to date [30]. Further human and NHP studies in this area are warranted.

Metabolic Syndrome

MetS occurs as a consequence of complex genetic and environmental factors [7]. McNeill et al. [31] found that, within the elderly population, individuals with MetS had increased incidence of coronary heart disease and CVD, with high blood pressure being the most strongly associated factor. Results indicate that MetS was associated with a 2-fold increase in risk of experiencing CVD, CVD mortality, and stroke [32]. However, beyond the age of 75 years, the relationship between MetS components and CVD is lost, similar to the obesity paradox. It has been proposed that this decrease in predictability with age may be due to an increase in the existence of competing risk factors (e.g. unhealthy diet, lack of exercise, insulin resistance, diabetes, etc.) once an individual reaches 75 years of age [31]. These are indications of the relative difficulty of describing obesity and MetS in individuals of advanced age.

Zhang et al. [33] used a population-screening approach to identify a model of spontaneous MetS in rhesus monkeys in order to investigate early pathogenesis and the relation of the syndrome to vascular difficulties. Screening parameters for MetS were based on those used in human medicine [8] and included waist and hip circumference, body weight, blood pressure, fasting plasma glucose, insulin, triglycerides, high- and low-density lipoprotein cholesterol, and total cholesterol. Animals scoring the highest on these measures were deemed to be predisposed to MetS and followed for 18 months. Similar to humans, predisposed NHPs in this study were overtly obese and had a higher body weight and waist circumference compared to similarly aged control animals and had significantly higher insulin levels, showing evidence of insulin resistance [33].

Type II Diabetes Mellitus

As is common in human medicine, diabetes is evaluated in monkeys with measures of fasting blood glucose and insulin levels, glycated hemoglobin (HbA1c) values, arginine stimulation test, intravenous glucose tolerance test (IVGTT), and oral glucose tolerance test (OGTT). Fasting glucose concentrations are generally lower in macaque monkeys compared to humans (50-80 and 70.2-100.0 mg/dl, respectively) [34,35]. A glucose concentration >106 mg/dl suggests overt diabetes in NHPs, whereas humans require >126 mg/dl for overt diabetes diagnosis (table 1) [34,35].

Table 1

Fasting blood glucose and insulin, and HbA1c values in normal and diabetic rhesus macaques and humans

Fasting blood glucose and insulin, and HbA1c values in normal and diabetic rhesus macaques and humans
Fasting blood glucose and insulin, and HbA1c values in normal and diabetic rhesus macaques and humans

Metabolic and Endocrine Factors

Diabetes and obesity are recognized causes of accelerated aging [36,37]. For example, obesity (high BMI) is associated with an accelerated rate of epigenetic changes associated with the age of the human liver, which may play a role in insulin resistance or liver cancer [38]. Obesity affects the adipose tissue and influences hormones, inflammation, and glucose homeostasis, which can lead to the development of diabetes and subsequent characteristics of accelerated aging. In obese states, macrophages infiltrate the adipose tissue, elevating cytokine levels (e.g. TNF-α and IL-6) and may result in insulin resistance and T2DM [39].

Serum lipids, cholesterol, and triglycerides are positively related to body fat distribution in obese and non-obese humans and NHPs [40]. Lipoprotein changes are observed in association with the development of diabetes in rhesus monkeys [40]. Specifically, these changes include increases in plasma triglycerides, total cholesterol, and very low-density lipoprotein, and decreases in high-density lipoprotein cholesterol [41].

Spontaneous T2DM in NHPs presents with similar clinical and pathological features as in humans, and the same risk factors have been identified [42,43]. Similar to humans, NHPs exhibit a pre-diabetic period of obesity-associated insulin resistance [44]. This period leads to compensatory insulin secretion, along with subsequent detrimental changes in plasma lipid and lipoprotein concentrations, composition, and glycation. Fasting glucose concentrations increase following a deficiency in pancreatic insulin production [45].

In addition, inflammation plays a crucial role in the development of insulin resistance, diabetes, and CVD associated with obesity [46]. Adiponectin, a hormone secreted by adipose tissue, is an anti-inflammatory molecule responsible for regulating lipid and glucose metabolism, increasing insulin sensitivity, regulating food intake and body weight, and protecting from chronic inflammation. Levels of adiponectin are inversely proportional to fat content; therefore, decreases in plasma levels of adiponectin are seen in obese diabetic NHPs and humans, contributing to the development of insulin resistance [47]. It is negatively associated with CVD risk factors (blood pressure, low-density lipoprotein cholesterol, and triglycerides) in humans [48] and with body weight and BMI in humans and NHPs [47,49].

Spontaneous Models

NHPs develop T2DM in an age-dependent manner, which is influenced by obesity and characterized by insulin resistance, hyperinsulinemia, and progressive hyperglycemia similar to humans [50]. This makes them a valuable resource for intervention studies, novel therapies, disease pathogenesis studies, studies of nuclear and cellular mechanisms, as well as the mechanisms of diabetic complications, such as CVD [51]. In addition, NHP's disease progression occurs in a much shorter timeframe compared to humans but in a longer timeframe compared to rodent models, allowing for study of disease pathogenesis. However, studies using spontaneous NHP models are limited due to the unpredictability of disease onset and the ability to conduct large-scale studies.

When given food ad libitum, captive-born animals may develop obesity-associated diseases in an age-dependent manner [41]. Elevated serum glucose and triglycerides have also been described in free-ranging primate colonies [52]. Tattersall et al. [52] describe a high-carbohydrate diet with excesses of sugar cane and molasses as likely contributing to these instances of diabetes in a cynomolgus macaque colony. The development of obesity and diabetes has also been described in the free-ranging rhesus monkeys on the island of Cayo Santiago [25].

Importantly, female Old World primates have menstrual cycles that closely approximate those of humans. For this reason, female monkeys provide useful models for the study of reproductive aging, menopause, and hormonal dysregulation along with its association with increased risk for developing MetS. Also, pregnancy, menopause, and/or sex hormone treatments can affect the development of insulin resistance and T2DM [53] in female monkeys. Endogenous gestational diabetes occurs in some species of NHPs along with complications similar to those observed in human females with the same disease [54]. Though rare, a NHP model of gestational diabetes provides a unique opportunity to study this disease and potential treatments, as ethical considerations constrain study in a human model.

Secondary Models

Obesity can be induced in a NHP model after administration of a Western diet (high fat/high cholesterol) [55]. T2DM and its associated metabolic perturbations can also be successfully induced in rhesus monkeys. For example, Bremer et al. [56] proposed that increases in dietary fructose consumption may have attributed, in part, to increased incidence of insulin resistance seen in the human population. To test this theory, a fructose-sweetened solution was administered daily to male monkeys for 6-12 months. In this short amount of time, a high-fructose dietary additive was able to produce many features of MetS including central obesity and T2DM in their animals [56]. Trans-fatty acids in foods have been regulated by the Food and Drug Administration due to their association with the development of abdominal obesity, CVD, and T2DM. To assess this phenomenon, Kavanagh et al. [57] administered a long-term diet high in trans-fatty acids to healthy African green monkeys. They found that this diet lead to significant weight gain and was associated with insulin resistance in this NHP model [57].

Contrary to human studies, which often rely on self-reporting of eating habits, NHP studies offer precise dietary control and valid measures of food consumption. With this model, the metabolic effects of specific dietary parameters can be assessed. Using this method, Astuti et al. [58] assessed the metabolic effects of 4 different diets over a 12-month period in cynomolgus monkeys and developed a reliable method for inducing atherosclerosis, a comorbidity of T2DM, in a NHP model. These important empirical advantages provided by NHP studies aid future exploration into biological mechanisms, disease progression, and novel interventions.

Streptozocin (STZ), a specific β-cell toxin, has been used to create a reproducible model of diabetes in monkeys and other animals [59,60]. This method specifically targets β cells resulting in hyperglycemia but produces pancreatic islet pathology that more closely resembles type 1 diabetes [45]. Here, monkeys are not insulin resistant, just insulin deficient, unless aged or obese, and the induction protocols can be modified to accommodate for this. In doing so, overweight animals can be made to convert to overt diabetes through a high-carbohydrate and high-fat diet, along with STZ treatment. Partial pancreatectomy with low-dose STZ is reportedly the safest and most reproducible method for inducing diabetes in a NHP model [61].

Models that target diabetic complications have also been developed. A dose and administration study determined that diabetic retinopathy could be induced in NHPs by subretinal injection with an adeno-associated virus vector to deliver human vascular endothelial growth factor (VEGF) protein to the retina [62]. This leads the way for future studies into the pathological mechanisms, developmental progression, and novel therapeutic treatment of diabetic blindness.

There are several disadvantages to a primate model: they are a long-lived species and expensive to study. Longitudinal studies in particular are costly due to specialized housing needs, trained and knowledgeable husbandry staff and veterinary care along with trained technical research staff. Induced diabetes models may show the early stages of diabetes, but do not necessarily develop all of the complications seen in overt diabetes [63].

Diabetic and pre-diabetic NHPs are clinically treated in much the same manner as humans. Diet and exercise are the first line of treatment for human patients. While dietary adjustments are easily implemented for NHPs, attempts to apply an exercise program can be much more problematic due to a variety of limitations (e.g. facility, space, staff, and individual temperaments). However, this is not an impossible task even with very limited space. In fact, treadmill exercise programs have been successfully implemented in young and old rhesus and cynomolgus monkeys [64,65].

Likewise, pharmacological treatment for spontaneous T2DM is quite similar for humans and NHPs. Exogenous insulin therapy is often administered to improve glycemic control. Other treatments include insulin-sensitizing agents, like thiazolidinedione and metformin, which are used to improve insulin resistance and glucose uptake. Sulfonylureas, glucagon-like peptide-1 (GLP-1) agonists and dipeptidyl peptidase-IV (DPP-IV) inhibitors are also used in both humans and NHPs to stimulate insulin secretion from the pancreas [63]. During such treatments, disease progression is typically followed by periodic monitoring of blood glucose levels and HbA1c.

NHPs have provided an invaluable translational model in the study of human pathology [66]. Due to their phylogenic similarities to humans, this model has been used to describe the aging process, to investigate the nature and causes of age-related illnesses, and to evaluate potential interventions [67,68]. Attributable to their biological similarities to humans and a comparable aging process, NHPs provide an extraordinarily unique resource for scientific inquiry. Moreover, unlike clinical trials, NHP studies allow for long-term control of diet and environment, something that is almost impossible with human subjects. Normal variations seen in clinical trials (lifestyle, diet, exercise, illness, medication, etc.) are effectively removed in NHP studies.

This research was supported entirely by the Intramural Research Program of the NIH, National Institute on Aging.

Masters RK, Reither EN, Powers DA, Yang YC, Burger AE, Link BG: The impact of obesity on US mortality levels: the importance of age and cohort factors in population estimates. Am J Public Health 2013;103:1895-1901.
Glickman D, Parker L, Sim LJ, Del Valle Cook H, Miller EA: Accelerating Progress in Obesity Prevention: Solving the Weight of the Nation. Washington, National Academy of Sciences, 2012.
Flegal KM, Kit BK, Orpana H, Graubard BI: Association of all-cause mortality with overweight and obesity using standard body mass index categories: a systematic review and meta- analysis. JAMA 2013;309:71-82.
Ladabaum U, Mannalithara A, Myer PA, Singh G: Obesity, abdominal obesity, physical activity, and caloric intake in US adults: 1988 to 2010. Am J Med 2014;127:717-727.e12.
Jacobs EJ, Newton CC, Wang Y, Patel AV, McCullough ML, Campbell PT, Thun MJ, Gapstur SM: Waist circumference and all-cause mortality in a large US cohort. Arch Intern Med 2010;170:1293-1301.
Koster A, Leitzmann MF, Schatzkin A, Mouw T, Adams KF, van Eijk JTM, Hollenbeck AR, Harris TB: Waist circumference and mortality. Am J Epidemiol 2008;167:1465-1475.
Kaur J: A comprehensive review on metabolic syndrome. Cardiol Res Pract 2014;2014:1-21.
Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, Fruchart JC, James WP, Loria CM, Smith SC Jr; International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; International Association for the Study of Obesity: Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 2009;120:1640-1645.
Menke A, Casagrande S, Geiss L, Cowie CC: Prevalence of and trends in diabetes among adults in the United States, 1988-2012. JAMA 2015;314:1021-1029.
Bauer SA, Arndt TP, Leslie KE, Pearl DL, Turner PV: Obesity in rhesus and cynomolgus macaques: a comparative review of the condition and its implications for research. Comp Med 2011;61:514-526.
Kavanagh K, Fairbanks LA, Bailey JN, Jorgensen MJ, Wilson ME, Zhang L, Rudel LL, Wagner JD: Characterization and heritability of obesity and associated risk factors in vervet monkeys. Obesity (Silver Spring) 2007;15:1666-1674.
Takahashi T, Higashino A, Takagi K, Kamanaka Y, Abe M, Morimoto M, Kang KH, Goto S, Suzuki J, Hamada Y, Kageyama T: Characterization of obesity in Japanese monkeys (Macaca fuscata) in a pedigreed colony. J Med Primatol 2006;35:30-37.
Pound LD, Kievit P, Grove KL: The nonhuman primate as a model for type 2 diabetes. Curr Opin Endocrinol Diabetes Obes 2014;21:89-94.
Anderson RM, Colman RJ: Prospects and perspectives in primate aging research. Antiox Redox Signal 2011;14:203-205.
Kemnitz JW, Roecker EB, Weindruch R, Elson DF, Baum ST, Bergman RN: Dietary restriction increases insulin sensitivity and lowers blood glucose in rhesus monkeys. Am J Physiol 1994;266(4 Pt 1):E540-E547.
Cava E, Fontana L: Will calorie restriction work in humans? Aging (Albany NY) 2013;5:507-514.
Mattison JA, Roth GS, Beasley TM, Tilmont EM, Handy AM, Herbert RL, Longo DL, Allison DB, Young JE, Bryant M, Barnard D, Ward WF, Qi W, Ingram DK, de Cabo R: Impact of caloric restriction on health and survival in rhesus monkeys from the NIA study. Nature 2012;489:318-321.
Ravussin E, Redman LM, Rochon J, Das SK, Fontana L, Kraus WE, Romashkan S, Williamson DA, Meydani SN, Villareal DT, Smith SR, Stein RI, Scott TM, Stewart TM, Saltzman E, Klein S, Bhapkar M, Martin CK, Gilhooly CH, Holloszy JO, Hadley EC, Roberts SB; CALERIE Study Group: A 2-year randomized controlled trial of human caloric restriction: feasibility and effects on predictors of health span and longevity. J Gerontol A Biol Sci Med Sci 2015;70:1097-1104.
Lane MA, Ball SS, Ingram DK, Cutler RG, Engel J, Read V, Roth GS: Diet restriction in rhesus monkeys lowers fasting and glucose-stimulated glucoregulatory end points. Am J Physiol 1995;268(5 Pt 1):E941-E948.
Lane MA, Ingram DK, Roth GS: Calorie restriction in nonhuman primates: effects on diabetes and cardiovascular disease risk. Toxicol Sci 1999;52(2 suppl):41-48.
Heilbronn LK, de Jonge L, Frisard MI, DeLany JP, Larson-Meyer DE, Rood J, Nguyen T, Martin CK, Volaufova J, Most MM, Greenway FL, Smith SR, Deutsch WA, Williamson DA, Ravussin E; Pennington CALERIE Team: Effect of 6-month calorie restriction on biomarkers of longevity, metabolic adaptation, and oxidative stress in overweight individuals: a randomized controlled trial. JAMA 2006;295:1539-1548.
Weiss EP, Racette SB, Villareal DT, Fontana L, Steger-May K, Schechtman KB, Klein S, Holloszy JO: Improvements in glucose tolerance and insulin action induced by increasing energy expenditure or decreasing energy intake: a randomized controlled trial. Am J Clin Nutr 2006;84:1033-1042.
Fontana L, Klein S, Holloszy JO: Effects of long-term calorie restriction and endurance exercise on glucose tolerance, insulin action, and adipokine production. Age (Dordr) 2010;32:97-108.
Colman RJ, Anderson RM, Johnson SC, Kastman EK, Kosmatka KJ, Beasley TM, Allison DB, Cruzen C, Simmons HA, Kemnitz JW, Weindruch R: Caloric restriction delays disease onset and mortality in rhesus monkeys. Science 2009;325:201-204.
Schwartz SM, Kemnitz JW: Age- and gender-related changes in body size, adiposity, and endocrine and metabolic parameters in free-ranging rhesus macaques. Am J Phys Anthropol 1992;89:109-121.
Fleischmann E, Teal N, Dudley J, May W, Bower JD, Salahudeen AK: Influence of excess weight on mortality and hospital stay in 1346 hemodialysis patients. Kidney Int 1999;55:1560-1567.
Summers L, Clingerman KJ, Yang X: Validation of a body condition scoring system in rhesus monkeys (Macaca mulatta): assessment of body composition by using dual-energy x-ray absorptiometry. J Am Assoc Lab Anim Sci 2012;51:88-93.
Dorner TE, Rieder A: Obesity paradox in elderly patients with cardiovascular diseases. Int J Cardiol 2012;155:56-65.
Abdullah A, Wolfe R, Stoelwinder JU, de Courten M, Stevenson C, Walls HL, Peeters A: The number of years lived with obesity and the risk of all-cause and cause-specific mortality. Int J Epidemiol 2011;40:985-996.
Fontana L, Hu FB: Optimal body weight for health and longevity: bridging basic, clinical, and population research. Aging Cell 2014;13:391-400.
McNeill AM, Katz R, Girman CJ, Rosamond WD, Wagenknecht LE, Barzilay JI, Tracy RP, Savage PJ, Jackson SA: Metabolic syndrome and cardiovascular disease in older people: the cardiovascular health study. J Am Geriatr Soc 2006;54:1317-1324.
Mottillo S, Filion KB, Genest J, Joseph L, Pilote L, Poirier P, Rinfret S, Schiffrin EL, Eisenberg MJ: The metabolic syndrome and cardiovascular risk: a systematic review and meta-analysis. J Am Coll Cardiol 2010;56:1113-1132.
Zhang X, Zhang R, Raab S, Zheng W, Wang J, Liu N, Zhu T, Xue L, Song Z, Mao J, Li K, Zhang H, Zhang Y, Han C, Ding Y, Wang H, Hou N, Liu Y, Shang S, Li C, Sebokova E, Cheng H, Huang PL: Rhesus macaques develop metabolic syndrome with reversible vascular dysfunction responsive to pioglitazone. Circulation 2011;124:77-86.
Bodkin NL: The rhesus monkey (Macaca mulatta): a unique and valuable model for the study of spontaneous diabetes mellitus and associated condition; in Sima AF, Shafir E (eds): Animal Models in Diabetes: A Primer. Singapore, Taylor & Francis, 2000, pp 309-325.
American Diabetes Association: Standards of medical care in diabetes - 2015. Diabetes Care 2015;38(suppl 1):S1-S93.
Tzanetakou IP, Katsilambros NL, Benetos A, Mikhailidis DP, Perrea DN: ‘Is obesity linked to aging?': adipose tissue and the role of telomeres. Ageing Res Rev 2012;11:220-229.
Monickaraj F, Aravind S, Gokulakrishnan K, Sathishkumar C, Prabu P, Prabu D, Mohan V, Balasubramanyam M: Accelerated aging as evidenced by increased telomere shortening and mitochondrial DNA depletion in patients with type 2 diabetes. Mol Cell Biochem 2012;365:343-350.
Horvath S, Erhart W, Brosch M, Ammerpohl O, von Schönfels W, Ahrens M, Heits N, Bell JT, Tsai PC, Spector TD, Deloukas P, Siebert R, Sipos B, Becker T, Röcken C, Schafmayer C, Hampe J: Obesity accelerates epigenetic aging of human liver. Proc Natl Acad Sci USA 2014;111:15538-15543.
Xu H: Chronic inflammation in fat plays a crucial role in the development of obesity-related insulin resistance. J Clin Invest 2003;112:1821-1830.
Winegar DA, Brown PJ, Wilkison WO, Lewis MC, Ott RJ, Tong WQ, Brown HR, Lehmann JM, Kliewer SA, Plunket KD, Way JM, Bodkin NL, Hansen BC: Effects of fenofibrate on lipid parameters in obese rhesus monkeys. J Lipid Res 2001;42:1543-1551.
Hannah JS, Verdery RB, Bodkin NL, Hansen BC, Le NA, Howard BV: Changes in lipoprotein concentrations during the development of noninsulin-dependent diabetes mellitus in obese rhesus monkeys (Macaca mulatta). J Clin Endocrinol Metab 1991;72:1067-1072.
Wagner JD, Kavanagh K, Ward GM, Auerbach BJ, Harwood HJ, Kaplan JR: Old world nonhuman primate models of type 2 diabetes mellitus. ILAR J 2006;47:259-271.
Yasuda M, Takaoka M, Fujiwara T, Mori M: Occurrence of spontaneous diabetes mellitus in a cynomolgus monkey (Macaca fascicularis) and impaired glucose tolerance in its descendants. J Med Primatol 1988;17:319-332.
Hansen BC, Bodkin NL: Heterogeneity of insulin responses: phases leading to type 2 (non-insulin-dependent) diabetes mellitus in the rhesus monkey. Diabetologia 1986;29:713-719.
Harwood HJ Jr, Listrani P, Wagner JD: Nonhuman primates and other animal models in diabetes research. J Diabetes Sci Technol 2012;6:503-514.
Hotamisligil GS: Inflammation and metabolic disorders. Nature 2006;444:860-867.
Hotta K, Funahashi T, Bodkin NL, Ortmeyer HK, Arita Y, Hansen BC, Matsuzawa Y: Circulating concentrations of the adipocyte protein adiponectin are decreased in parallel with reduced insulin sensitivity during the progression to type 2 diabetes in rhesus monkeys. Diabetes 2001;50:1126-1133.
Kazumi T, Kawaguchi A, Sakai K, Hirano T, Yoshino G: Young men with high-normal blood pressure have lower serum adiponectin, smaller LDL size, and higher elevated heart rate than those with optimal blood pressure. Diabetes Care 2002;25:971-976.
Xydakis AM, Case CC, Jones PH, Hoogeveen RC, Liu MY, Smith EO, Nelson KW, Ballantyne CM: Adiponectin, inflammation, and the expression of the metabolic syndrome in obese individuals: the impact of rapid weight loss through caloric restriction. J Clin Endocrinol Metab 2004;89:2697-2703.
Cefalu W: Animal models of type 2 diabetes: clinical presentation and pathophysiological relevance to the human condition. ILAR J 2006;47:186-198.
Chatzigeorgiou A, Halapas A, Kalafatakis K, Kamper E: The use of animal models in the study of diabetes mellitus. In Vivo 2009;23:245-258.
Tattersall I, Dunaif A, Sussman RW, Jamieson R: Hematological and serum biochemical values in free-ranging Macaca fascicularis of Mauritius: possible diabetes mellitus and correlation with nutrition. Am J Primatol 1981;1:413-419.
Franconi F, Seghieri G, Canu S, Straface E, Campesi I, Malorni W: Are the available experimental models of type 2 diabetes appropriate for a gender perspective? Pharmacol Res 2008;57:6-18.
Krugner-Higby L, Luck M, Hartley D, Crispen HM, Lubach GR, Coe CL: High-risk pregnancy in rhesus monkeys (Macaca mulatta): a case of ectopic, abdominal pregnancy with birth of a live, term infant, and a case of gestational diabetes complicated by pre-eclampsia. J Med Primatol 2009;38:252-256.
Mubiru JN, Garcia-Forey M, Higgins PB, Hemmat P, Cavazos NE, Dick EJ Jr, Owston MA, Bauer CA, Shade RE, Comuzzie AG, Rogers J: A preliminary report on the feeding of cynomolgus monkeys (Macaca fascicularis) with a high-sugar high-fat diet for 33 weeks. J Med Primatol 2011;40:335-341.
Bremer AA, Stanhope KL, Graham JL, Cummings BP, Wang W, Saville BR, Havel PJ: Fructose-fed rhesus monkeys: a nonhuman primate model of insulin resistance, metabolic syndrome, and type 2 diabetes. Clin Transl Sci 2011;4:243-252.
Kavanagh K, Jones KL, Sawyer J, Kelley K, Carr JJ, Wagner JD, Rudel LL: Trans fat diet induces abdominal obesity and changes in insulin sensitivity in monkeys. Obesity 2007;15:1675-1684.
Astuti DA, Sajuthi D, Suparto IH, Kaplan J, Appt S, Clarkson TB: The development of diets to induce atherogenic lipid profiles for cynomolgus monkeys in their country of origin. World J Agric Res 2014;2:247-251.
Sakata N, Yoshimatsu G, Tsuchiya H, Egawa S, Unno M: Animal models of diabetes mellitus for islet transplantation. Exp Diabetes Res 2012;2012:1-11.
Graham ML, Mutch LA, Rieke EF, Kittredge JA, Faig AW, DuFour TA, Munson JW, Zolondek EK, Hering BJ, Schuurman HJ: Refining the high-dose streptozotocin-induced diabetic non-human primate model: an evaluation of risk factors and outcomes. Exp Biol Med 2011;236:1218-1230.
Jin X, Zeng L, He S, Chen Y, Tian B, Mai G, Yang G, Wei L, Zhang Y, Li H, Wang L, Qiao C, Cheng J, Lu Y: Comparison of single high-dose streptozotocin with partial pancreatectomy combined with low-dose streptozotocin for diabetes induction in rhesus monkeys. Exp Biol Med 2010;235:877-885.
Lebherz C, Maguire AM, Auricchio A, Tang W, Aleman TS, Wei Z, Grant R, Cideciyan AV, Jacobson SG, Wilson JM, Bennett J: Nonhuman primate models for diabetic ocular neovascularization using AAV2-mediated overexpression of vascular endothelial growth factor. Diabetes 2005;54:1141-1149.
Forbes JM, Cooper ME: Mechanisms of diabetic complications. Physiol Rev 2013;93:137- 188.
Rhyu IJ, Bytheway JA, Kohler SJ, Lange H, Lee KJ, Boklewski J, McCormick K, Williams NI, Stanton GB, Greenough WT, Cameron JL: Effects of aerobic exercise training on cognitive function and cortical vascularity in monkeys. Neuroscience 2010;167:1239-1248.
McGee WK, Bishop CV, Pohl CR, Chang RJ, Marshall JC, Pau FK, Stouffer RL, Cameron JL: Effects of hyperandrogenemia and increased adiposity on reproductive and metabolic parameters in young adult female monkeys. Am J Physiol Endocrinol Metab 2014;306:E1292-E1304.
Shively CA, Clarkson TB: The unique value of primate models in translational research. Am J Primatol 2009;71:715-721.
Roth GS, Mattison JA, Ottinger MA, Chachich ME, Lane MA, Ingram DK: Aging in rhesus monkeys: relevance to human health interventions. Science 2004;305:1423-1426.
Ingram DK, Young J, Mattison JA: Calorie restriction in nonhuman primates: assessing effects on brain and behavioral aging. Neuroscience 2007;145:1359-1364.
Bodkin NL, Alexander TM, Ortmeyer HK, Johnson E, Hansen BC: Mortality and morbidity in laboratory-maintained rhesus monkeys and effects of long-term dietary restriction. J Gerontol A Biol Sci Med Sci 2003;58:212-219.
Melmed S, Polonsky KS, Larsen PR, HM K: Williams Textbook of Endocrinology, ed 12. Philadelphia, Elsevier Saunders, 2011.
Johnson JL, Duick DS, Chui MA, Aldasouqi SA: Identifying prediabetes using fasting insulin levels. Endocr Pract 2010;16:47-52.
Marigliano M, Casu A, Bertera S, Trucco M, Bottino R: Hemoglobin A1C percentage in nonhuman primates: a useful tool to monitor diabetes before and after porcine pancreatic islet xenotransplantation. J Transplant 2011;2011:1-8.
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