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Characterization and Heritability of Obesity and Associated Risk Factors in Vervet Monkeys
Article first published online: 6 SEP 2012
2007 North American Association for the Study of Obesity (NAASO)
Volume 15, Issue 7, pages 1666–1674, July 2007
How to Cite
Kavanagh, K., Fairbanks, L. A., Bailey, J. N., Jorgensen, M. J., Wilson, M., Zhang, L., Rudel, L. L. and Wagner, J. D. (2007), Characterization and Heritability of Obesity and Associated Risk Factors in Vervet Monkeys. Obesity, 15: 1666–1674. doi: 10.1038/oby.2007.199
- Issue published online: 6 SEP 2012
- Article first published online: 6 SEP 2012
- Received for review July 12, 2006, Accepted in final from December 16, 2006
- animal models;
- insulin resistance;
- metabolic syndrome
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- Research Methods and Procedures
Objective: The objective was to determine the prevalence and heritability of obesity and risk factors associated with metabolic syndrome (MS) in a pedigreed colony of vervet monkeys.
Design: A cross-sectional study of plasma lipid and lipoprotein concentrations, glycemic indices, and morphometric measures with heritability calculated from pedigree analysis. A selected population of females was additionally assessed for insulin sensitivity and glucose tolerance.
Subjects: All mature male (n = 98), pregnant (n = 40) and non-pregnant female (n = 157) vervet monkeys were included in the study. Seven non-pregnant females were selected on the basis of high or average glycated hemoglobin (GHb) for further characterization of carbohydrate metabolism.
Measurements: Morphometric measurements included body weight, length, waist circumference, and calculated BMI. Plasma lipids [total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C)] and glycemic measures (fasting blood glucose, insulin, and GHb) were measured. A homeostasis model assessment index was further reported. Glucose tolerance testing and hyperinsulinemic-euglycemic clamps were performed on 7 selected females.
Conclusion: Vervet monkeys demonstrate obesity, insulin resistance, and associated changes in plasma lipids even while consuming a low-fat (chow) diet. Furthermore, these parameters are heritable. Females are at particular risk for central obesity and an unfavorable lipid profile (higher TG, TC, and no estrogen-related increase in HDL-C). Selection of females by elevated GHb indicated impaired glucose tolerance and was associated with central obesity. This colony provides a unique opportunity to study the development of obesity-related disorders, including both genetic and environmental influences, across all life stages.
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- Research Methods and Procedures
The prevalence of obesity is currently estimated at >20% of the adult population. Overweight individuals add another 40%, such that two thirds of the adult population are at risk of developing obesity-related disorders such as metabolic syndrome (MS)1 (1). MS, defined as a cluster of cardiovascular disease (CVD) risk factors and insulin resistance (IR), has been estimated to affect over 20% of the adult population in the United States (2, 3). MS comprises the combination of abdominal obesity, dyslipidemia, hypertension, and impaired glucose tolerance (IGT), 3 of which must be present to confirm the diagnosis (4). There is considerable interest from both the public health sector and medical economists as to the best predictors for MS stemming from the fact that CVD is the number one cause of death and hospitalization in the United States (5, 6). There is abundant evidence that IR and IGT precede diabetes mellitus (DM) (7, 8), and both IR and hyperglycemia are risk factors for CVD in humans.
Obesity prevalence increases with age (9, 10), which is presumed to reflect combinations of aging, consumption of a westernized diet, and sedentary lifestyle. Genetic differences among individuals make some people more likely to store excess fat in times of food abundance. Genetic susceptibilities for DM and obesity have been identified (11), with a number of candidate genes characterized. However as both the overweight and IGT phenotypes are multifactorial, their associations and interactions with each other and the environment become difficult etiologies to assess. Non-human primates mirror these same changes in body composition and metabolic disturbances as they age or become pregnant (9, 12) and are prone to develop atherosclerosis (13, 14), which is augmented by DM (15). The purpose of this study was to evaluate a closed population of vervet monkeys (Chlorocebus aethiops) for the prevalence and heritability of obesity and other parameters associated with MS under relatively controlled circumstances that include a uniform diet and equal opportunities for exercise. By assessing heritability, we further validate this primate species for investigations of MS pathophysiology, with the ability to identify familial subsets at risk for obesity and investigate genetic differences and effects of intervention across these subsets and across their life stages.
Research Methods and Procedures
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- Research Methods and Procedures
The study population was a multigenerational pedigreed colony (University of California-Los Angeles Vervet Research Colony), of which all mature monkeys (age >4 to 22 years; n = 295), including 98 males, 157 non-pregnant, and 40 pregnant female vervet monkeys were evaluated. Pregnancy was confirmed by parturition, and stage of pregnancy at examination calculated back from actual parturition dates. In captivity, vervet females reach puberty at 2.5 years of age and achieve full adult size by the age of 4. Male vervets reach puberty at 3 years of age and complete growth by 5 years. The age range of the study population extends from young adulthood (4 to 5 years) to old age (>18 years). Most females are kept in the colony for life, while the majority of the males are culled by the age of 10 years. Aged females demonstrate reproductive senescence; however, a true menopause has yet to be documented. All subjects were descendants of 57 original founders imported from St. Kitts, West Indies.
Animals were housed in outdoor corrals varying from 380 to 1482 square feet with elevated perches, platforms, and climbing structures, and were fed commercial primate laboratory chow (Laboratory Diet 5038; Purina, St. Louis, MO) supplemented with fresh fruits and vegetables. All animals had ad libitum access to food and opportunities to exercise. Study procedures had been approved by University of California-Los Angeles, Veteran's Administration, and Wake Forest University Institutional Animal Care and Use committees.
Monkeys were fasted overnight, before sedation with intramuscular ketamine (8 to 10 mg/kg) to facilitate the collection of blood samples and morphometric measurements. Each monkey was weighed. A flexible tape measure was placed around the monkey's abdomen at the level of the umbilicus to measure waist circumference. The distance from the crown to the bottom of the pubic bone was recorded as length, which is the equivalent to sitting height. An index of BMI was calculated from the weight (in kg) divided by length (in meters) squared.
Glucose was measured on capillary blood sourced from a finger stick (One Touch Ultra Glucometer; Lifescan, Inc., Milpitas, CA). Blood samples were collected from the femoral vein and placed on ice until samples were processed. Plasma and whole blood were stored at −80° C before shipping to Wake Forest University.
Percent glycation of hemoglobin in whole blood (GHb) was measured by high-performance liquid chromatography borate affinity column (Primus PDQ, Kansas City, MO) to assess long-term glycemic control. Fasting plasma insulin concentrations were measured by enzyme-linked immunosorbent assay (Mercodia, Uppsala, Sweden) (12). Homeostasis model assessment (HOMA) was calculated from the product of glucose (mM) and insulin (UI/L)/22.5, and used as an indicator of IR (16). Plasma total cholesterol (TC), triglycerides (TG), and cholesterol associated with high-density lipoprotein (HDL-C) fractions were measured enzymatically (15).
A small group of older females (15 to 18 years) were characterized as IGT based on their elevated GHb (n = 3) or characterized as normal (n = 4) based on normal GHb and normal fasting glucose concentrations, as compared with the study population (n = 295). They were further evaluated by intravenous glucose tolerance testing (17) and insulin sensitivity assessment by hyperinsulinemic-euglycemic clamp methodology (18). Briefly, glucose tolerance testing involved the measurement of insulin and glucose concentrations over an hour before and after a standard glucose challenge (750 mg/kg). The rate of glucose disappearance was calculated from the slope of the log transformed glucose concentrations between minutes 5 to 20. Areas under the curve for insulin and glucose were calculated between times 0 to 60 minutes (17). A hyperinsulinemic-euglycemic clamp was performed by peripheral infusion of regular insulin (40 units/m2 per min) and variable administration of 20% dextrose solution to maintain glucose levels at fasting value for 3 hours under sedation with ketamine. The M value is calculated from the required dextrose infusion rate required over the final hour of the clamp (18).
Obesity was defined as a waist circumference >40.5 cm (corresponding to the colony population upper 20th percentile). This percentile cutoff was modeled on where the Adult Treatment Panel III MS risk waist definition falls for males and females in normal human populations (4, 19, 20) and was rounded to 40.5 cm in both sexes. An elevated GHb was defined as glycosylation of hemoglobin chain A1c being >5.7%, as has been described as predictive for MS in related individuals (21) and a HOMA value >6 was used as predictive for an insulin-resistant state (16).
The data are presented as the mean ± standard error for each group. Quartiles of insulin ranges and waist circumferences were based on even distribution of population numbers. Data were analyzed for normality and logarithmically transformed where necessary (glucose, HOMA, TG) before comparisons. Associations were evaluated by Pearson's correlation coefficient excluding the pregnant females. Differences between groups were analyzed by analysis of covariance with age as a covariate and post hoc testing for group and sex differences was performed with Tukey's honestly significant difference for multiple comparisons on detection of significant group and group by sex interactions. The non-parametric Mann-Whitney U test was utilized in comparing the parameters from the small subset of females selected for further assessment of insulin sensitivity. Statistical analysis was performed using Statistica 6 (StatSoft, Inc., Tulsa, OK), with significance set at α < 0.05.
Quantitative genetic analyses were performed to determine genetic contributions to variation in obesity and associated traits using Sequential Oligogenic Linkage Analysis Routines (SOLAR) (22). Variance component methods were used to model the individual trait values as a function of the mean trait value, covariates, genetic relatedness, and unmeasured environmental effects. This is a pedigree-based approach that accounts for the residual correlations among relatives estimated through the kinship matrix. Additive genetic effects are estimated from the covariance among relatives. Estimation of the mean, variance, covariate, and genetic effects are obtained simultaneously, using maximum likelihood methods. Heritability is a measure of the total proportion of the variance explained by genetic similarity among relatives. Components are tested using likelihood testing, where the likelihood of the data is estimated with and without the component to determine if the component is significant. Traits were adjusted for sex, age, and pregnancy before analysis. One female discovered to be diabetic (fasting blood glucose = 343) during the screening was excluded from the genetic analysis.
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- Research Methods and Procedures
The baseline characteristics of the entire population are presented in Table 1. As the population is a breeding colony, there were more females and those females were older than the males (Figure 1A). Age was significantly different between males and females and was significantly correlated to all lipid parameters, waist size, BMI, glucose, and GHb across the population. The uncorrected means for each of these measures are shown in Table 1, but the statistical analyses were performed with age as a covariate in the ANOVA model. Despite their smaller size [length and weight (Figure 1B), and the calculated BMI], waist circumference in non-pregnant or pregnant (only first and second trimester pregnancies were identified at screening) females did not differ from males. Relatively high insulin concentrations were detected across the entire population as compared with values reported in other primate species and these values were further increased by pregnancy. The non-pregnant females had elevated TG and TC, and tended toward lower HDL-C concentrations, as compared with the males, and these factors were not a function of age (Figure 2). In fact, when only the young adult population were evaluated (age range 5 to 10 yrs, p = 0.61 for age comparison between sexes), females still had elevated TG concentrations by more than 50% (22.2 vs. 34.1 mg/dL, respectively, p < 0.001).
|Parameter||Population (n = 295)||Males (n = 98)||Non-pregnant females (n = 157)||Pregnant females (n = 40)||p|
|Age (yrs)||9.67 (0.26)||7.05 (0.26)a||11.12 (0.38)b||10.63 (0.62)b||<0.001|
|GHb (%)||5.48 (0.09)||5.53 (0.13)||5.48 (0.15)||5.36 (0.15)||0.25|
|Insulin (uIU/mL)||30.1 (1.35)||29.3 (2.01)a||27.7 (1.72)a||41.27 (5.18)b||0.003|
|Weight (kg)||5.96 (0.075)||7.22 (0.10)a||5.33 (0.07)b||5.33 (0.11)b||<0.001|
|Length (cm)||45.94 (0.19)||49.76 (0.18)a||43.95 (0.12)b||43.62 (0.21)b||<0.001|
|Waist (cm)||37.59 (0.26)||37.14 (0.37)||37.8 (0.39)||38.16 (0.69)||0.09|
|Glucose (mg/dL)||61.047 (1.44)||62.16 (1.65)||60.31 (2.36)||61.23 (3.38)||0.05|
|BMI (kg/m)||27.99 (0.21)||29.07 (0.29)a||27.54 (0.31)b||27.93 (0.49)b||<0.001|
|HOMA-IR||4.92 (0.36)||4.71 (0.41)||4.48 (0.55)||7.17 (1.23)||0.07|
|Triglycerides (mg/dL)||33.5 (1.19)||22.15 (1)a||38.83 (1.81)b||40.4 (3.07)b||<0.001|
|Total cholesterol (mg/dL)||141.24 (1.90)||133.03 (2.2)a||153.21 (2.62)b||114.32 (5.15)c||0.002|
|HDL cholesterol (mg/dL)||65.89 (0.95)||71.27 (1.21)a||67.87 (1.13)a||44.92 (2.77)b||<0.001|
Heritability estimates for population characteristics ranged between ∼20% to 45% (Table 2). Among the most highly heritable phenotypes was waist circumference. Plasma lipids and lipoprotein cholesterol were robustly heritable. Measures of carbohydrate parameters had much weaker contributions of familial associations.
|Waist circumference||0.37 (0.16)||0.02|
|HDL cholesterol||0.29 (0.13)||0.002|
|HOMA value||0.02 (0.10)||0.36|
Twenty-five percent of the females and 16% of the males were classified as abdominally obese, as determined by an enlarged waist circumference (>80th percentile). These centrally obese animals were significantly hyperinsulinemic (p = 0.0003) and are classified as at-risk for type 2 diabetes by HOMA scores (p = 0.015; Figure 3) (16). Females that were centrally obese had HOMA scores of nearly double that of their lean counterparts (7.14 vs. 3.61, respectively), as compared with the more modest increases seen in the obese males (5.91 vs. 4.48, respectively). Consistent with the MS classification in people, the monkeys with high waist circumferences had 33% higher TG concentrations (30 mg/dL vs. 40 mg/dL, p = 0.03). Overall, triglyceride concentrations were significantly associated with increasing intra-abdominal fat as measured by waist circumference (r = 0.31, p < 0.001). Further, when waist circumference was examined by quartiles, the more obese quartiles had higher TG concentrations. Females had significantly higher TG concentrations within every waist group (Figure 4).
Waist circumference was significantly and positively correlated with insulin concentrations (r = 0.34, p < 0.01) with the obese animals having, on average, >40% higher insulin concentrations (Figure 3A). Waist circumference was also significantly and positively correlated with IR (HOMA; r = 0.34, p < 0.001) where the obese animals score for IR was nearly double that of the normal population (Figure 3B). Knowing waist size and insulin concentrations increase together, insulin was then divided into quartiles and evaluated for its relationship with glucose. Animals classified as diabetic (n = 5; fasting glucose ≥126 mg/dL) or with impaired fasting glucose (IFG; n = 4; fasting glucose >100 mg/dL) based on human criteria were present in all but the lowest quartile of insulin (Figure 5). However, a significant increase in mean glucose concentration was only seen in the highest quartile of insulin (ANOVA post hoc testing p = 0.01) and correlation between glucose and waist circumference was modest but significant (r = 0.17, p = 0.004). Diabetic animals all had enlarged waist circumferences (diabetic monkey average was 44 cm as compared with the population average of 37.6 cm) and >40% higher TG concentrations (mean of 47.3 mg/dL vs. 33.5 mg/dL for the entire population). Together, these data demonstrate that increasing abdominal obesity is associated with IR, hyperinsulinemia, and glucose.
This proposed pathogenesis was born out when older females selected for hyperglycemia (high GHb) were compared with age-matched normal controls (Table 3). Despite slightly higher fasting insulin concentrations, lack of insulin response after the intravenous glucose challenge confirmed abnormal pancreatic function (Figure 6). These animals had high fasting glucose concentrations and were glucose intolerant based on delayed glucose clearance and lower calculated Kg (Table 3; Figure 6). Associated with IFG status were significant increases in waist circumference and trends toward hypertriglyceridemia, which suggest these females are at high risk for developing MS (Table 3). These animals had HOMA scores indicative of IR, but unexpectedly had normal insulin sensitivity based on M-values obtained from hyperinsulinemic-euglycemic clamp.
|Unit||Control||Impaired glucose tolerant|
|Glycated hemoglobin||%||5.27 (0.19)||8.3 (0.40)|
|Glucose||mg/dL||60.5 (4.73)||104.7 (7.42)*|
|Insulin||uIU/mL||20.81 (5.19)||26.52 (2.82)|
|HOMA||3.04 (0.61)||6.76 (0.41)*|
|Kg||hr||3.58 (0.33)||1.92 (0.30)*|
|M-value||mg/kg per min||9.53 (1.06)||9.23 (0.45)|
|Waist circumference||cm||38.37 (0.36)||43.33 (2.17)*|
|Triglycerides||mg/dL||49.25 (10.5)||118 (40.15)|
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- Research Methods and Procedures
This colony of vervet monkeys demonstrates that without the dietary and lifestyle influences seen in present-day human populations, obesity, IR, and associated changes in plasma lipids are still observed and are heritable. In human populations, abdominal obesity is considered the central defining feature of MS because it is the best predictor of incident MS in non-diabetic populations (20, 23). Only a few non-human primate species are well characterized for developing obesity without dietary intervention (12, 24, 25). The vervet monkey has also been evaluated for atherosclerosis development (14), making it an attractive model for the study of interactions between MS and CVD.
In this colony, waist circumference and BMI were strongly heritable, but estimates were lower than those made from human populations (26). The heritability (h2) of BMI in this sample of vervet monkeys (h2 = 0.44) was surprisingly close to that measured in a comparable sample of pedigreed baboons (h2 = 0.46) (27). As waist circumference has been described as the best predictor for incident MS (20), subpopulations of vervets predicted at high risk for obesity based on pedigree could be selected and evaluated across all life stages. The abdominal location of adipose tissue is specifically associated with development of the MS, leading to the inclusion of waist circumference rather than BMI or waist-hip ratio in the Adult Treatment Panel III guidelines (28). Indeed, one study without a specific abdominal measure found no relationship between generalized adiposity and coronary artery disease (29).
A high waist circumference, indicating abdominal fat accumulation, is linked to development of IR (30). In this colony, higher insulin concentrations were associated with greater waist size. Abdominal fat deposition often occurs with aging, but it is the effect of an increase in waist size independent of age that largely determines insulin sensitivity as lean aged people have been shown to be comparable to lean youths (31). HOMA has been validated as a reliable estimate of insulin sensitivity when compared with the hyperinsulinemic-euglycemic clamp methodology, and is correlated with visceral fat area (16, 32). HOMA scores were increased in animals with central adiposity and the increase was most pronounced in females. The actual values, however, should be interpreted cautiously as glucose concentrations were lower than in people, and insulin concentrations considerably higher than those in people (20, 33, 34). Insulin concentrations in prior reports of vervet monkeys (35) and other non-human primate species, including the baboon and the rhesus macaque, are also reported to be higher than in people when typically measured by radioimmunoassay (9, 12, 27). The reasons for differences may include species sensitivity to abundant food availability or species differences in antibody reactivity and antibody source where human assays are typically applied to measure monkey samples (36, 37). Lower fasting glucose concentrations are also seen in other non-human primate species (9, 12) and may be a result of these generally higher insulin concentrations. The reasons for the differences are not clear.
The MS criterion uses IFG (glucose >100 mg/dL) to define pre-diabetes, which is less prevalent than IGT in most populations (5, 8) but is an easily measured parameter for screening purposes. In the vervet colony, even females selected for elevated GHb were not classified as IFG as their fasting blood glucose averaged >20 mg/dL lower than people (34). Thus, the prevalence of IGT or IFG is likely to be underestimated by using human definitions in the vervet population, as seen in other non-human primates (12). Incident diabetes risk increases with increasing fasting glucose concentrations even within the normal range (34), so establishment of species-specific reference values as described here will allow detection of individuals with marginally elevated glucose values, along with other risk factors for MS.
IR was prominent during pregnancy, demonstrated by significant hyperinsulinemia, and is similar to the profile of pregnant women. Insulin resistance and gestational DM are seen in non-human primates (38, 39) and are proposed to be in response to sex steroids and prolactin, resulting in a combination of β cell hyperplasia and enhanced insulin secretion to combat IR in peripheral tissues (40). The same group of pregnant females also had significantly lower HDL-C than both male and non-pregnant female monkeys. The reductions have been seen in other non-human primates (39, 41), and are in contrast to women who tend to develop hypercholesterolemia and hypertriglyceridemia, and demonstrate less of an effect on HDL-C (42). The reasons for the differences are not clear.
Insulin, lipids, and lipoproteins were also heritable. Triglyceride concentrations in the vervets had comparable heritability to triglyceride concentrations measured from adipose tissue of baboons (h2 = 0.33 vs. 0.2) (27). Our estimates of heritability of insulin differed from baboons, although both were significant (h2 = 0.21 vs. 0.46, respectively) (27). Further, whereas HOMA values and glucose were significantly heritable in the baboon sample (h2 = 0.47 and 0.19, respectively) (27), neither achieved significance in the vervet sample (h2 = 0.02 and 0.07, respectively). Differences between these values may reflect the greater population heterogeneity or the more advanced average age of the baboon colony (∼19 and 23 years in males and females, respectively, compared with 7 and 11 years in males and females in this report in vervets), which may have allowed detection of a greater range of glucose abnormalities. The failure to find significant genetic effects on fasting blood glucose was related to the cross-sectional nature of the sample and the colony management practices. Individuals with hyperglycemia or other clinical signs of DM are removed from the colony shortly after detection. If monkeys were allowed to remain in the colony, the lifetime incidence of hyperglycemia in this population would likely be heritable.
Independent of age, females had a less favorable lipid profile with triglyceride concentrations >70% higher than their male counterparts and a greater fraction of their cholesterol was carried on apolipoprotein-B-containing lipoproteins (the difference between the higher total cholesterol and lower HDL-C seen in females). This fraction is known to deliver cholesterol to the arterial wall in atherogenesis. Although values seem low for TG and cholesterol fractions, the diet is very low in cholesterol content and fat (13% of energy supplied as fat as compared with the 40% consumed in a typical western diet), and it would be expected that dietary manipulation would exaggerate the sex differences in lipid profile and further identify individuals prone to weight gain and associated dyslipidemias.
In summary, we report that a significant proportion of vervet monkeys have obesity and associated lipid changes, of which all are heritable. The development of obesity was associated with increasing insulin concentrations and lipid changes analogous to the IR and dyslipidemia associated with MS in people and was particularly apparent in females. These monkeys may present a useful model of MS in a species that is known to develop progression of atherosclerosis with dietary intervention. Additionally, the aging female population within the colony appears to be at particular risk and may be a suitable species for evaluation of the increased risk of CVD associated with menopause.
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This study was supported by NIH Grants 1 P40 RR19963-01A1 and TR 5 T32 HL07115-28. The authors thank Mary Jo Busa for editorial assistance.
Nonstandard abbreviations: MS, metabolic syndrome; CVD, cardiovascular disease; IR, insulin resistance; IGT, impaired glucose tolerance; DM, diabetes mellitus; GHb, glycated hemoglobin; HOMA, homeostasis model assessment; TC, total cholesterol; TG, triglyceride; HDL-C, high-density lipoprotein cholesterol; IFG, impaired fasting glucose; h2, heritability.
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- 4National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) (2002) Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation 106: 3143–3421.
- 8American Diabetes Association (2006) Diagnosis and classification of diabetes mellitus. Diabetes Care 29 (suppl): 43–48.
- 361983) Diabetes and carbohydrate impairment in nonhuman primates Dukelow, WR eds.. Nonhuman Primate Models for Human Diseases 1–36. CRC Press Boca Raton, FL.(
- 371999) Carbohydrate metabolism Loeb, WF Quimby, FW eds.. The Clinical Chemistry of Laboratory Animals 165–179. Taylor and Francis Philadelphia, PA.(