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Novel Insulin Sensitivity Index Derived from Oral Glucose Tolerance Test

Division of Endocrinology and Metabolism, Department of Medicine (S.S., W.S., A.T., C.R.); Department of Pathology (W.C.); and Epidemiology Unit (A.G.), Faculty of Medicine, Prince of Songkla University, Hat-Yai, Songkhla 90110, Thailand

Address all correspondence and requests for reprints to: Supamai Soonthornpun, M.D., Division of Endocrinology and Metabolism, Department of Medicine, Prince of Songkla University, Hat-Yai, Songkhla 90110, Thailand. E-mail: ssupamai{at}ratree.psu.ac.th.

	Abstract

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The euglycemic hyperglycemic clamp is generally regarded as a reference method for assessing insulin sensitivity. However, this method is laborious and expensive. The oral glucose tolerance test (OGTT), the most commonly used method for evaluating whole body glucose tolerance, has often been used to assess insulin sensitivity. In the previous studies the correlation between the insulin sensitivity index (ISI) obtained from the OGTT (ISI_OGTT) and those obtained from the glucose clamp (ISI_Clamp) may not be satisfactory. This is because the glucose clamp study is designed for measuring peripheral glucose utilization, whereas plasma glucose responses during the OGTT are the results of peripheral glucose utilization and hepatic glucose production. Based on this problem, we developed a new equation, ISI_OGTT, [1.9/6 x body weight (kg) x fasting plasma glucose (mmol/liter) + 520 - 1.9/18 x body weight x area under the glucose curve (mmol/h·liter) - urinary glucose (mmol)/1.8] ÷ [area under the insulin curve (pmol/h·liter) x body weight], which would represent peripheral glucose utilization only. We tested our equation with ISI_Clamp and also compared with others. Thirty-three healthy volunteers (16 males) with normal glucose tolerance underwent a 75-g, 3-h OGTT on the morning of d 1 and a glucose clamp on the morning of d 2. Their mean (±SD) age and body mass index were 30.8 ± 8.3 yr and 22.0 ± 3.9 kg/m², respectively. The mean (±SD) glucose disposal rate and ISI determined by glucose clamp were 27.46 ± 16.55 µmol/kg·min and 7.39 ± 2.72 µmol/kg·min/pmol·liter, respectively. Pearson’s correlation coefficient between our ISI_OGTT and ISI_Clamp was 0.869 (P < 0.0001) which was stronger than those corresponding values calculated from HOMA, QUICKI, Belfiore, Cederholm, Gutt, Matsuda, and Stumvoll, the respective values of which were 0.404, 0.434, 0.643, 0.533, 0.584, 0.734, and 0.508. In conclusion, the ISI_OGTT derived from our equation is more suitable than others in assessing insulin sensitivity in subjects with normal glucose tolerance. Further studies in subjects with impaired glucose tolerance and diabetes mellitus should be performed to confirm the validity of this equation.

	Introduction

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INSULIN RESISTANCE NOT only plays an important pathophysiological role in type 2 diabetes mellitus, but it also is a common feature of polycystic ovary disease and many metabolic disturbances associated with coronary artery disease, including obesity, dyslipidemia, and hypertension (1). The ability to easily assess insulin sensitivity would therefore be useful for investigating the role of insulin resistance in the pathophysiology of these diseases. Euglycemic hyperinsulinemic clamp or glucose clamp is generally regarded as a reference method for assessing insulin sensitivity, because it directly measures the effects of insulin to promote glucose utilization under steady state conditions, whereas hepatic glucose production is completely shut off by insulin infusion. However, this method is laborious, expensive, and not routinely available for every physician. As the oral glucose tolerance test (OGTT), the most commonly used method for evaluating whole body glucose tolerance, is simple and cheap, a number of formulas for insulin sensitivity index (ISI) obtained from OGTT (ISI_OGTT) have been developed to assess insulin sensitivity (Table 1). However, the correlation between ISI_OGTT and those obtained from glucose clamp (ISI_Clamp) in previous studies may not be satisfactory (2, 3, 4, 5). This is because the glucose clamp study is designed for measuring peripheral glucose utilization (6), whereas plasma glucose responses during the OGTT are the results of peripheral glucose utilization and hepatic glucose production (7). The area under the glucose curve during the OGTT represents glucose that comes from hepatic glucose production and unused glucose. Based on this problem, we developed an equation for ISI_OGTT that would represent only peripheral glucose utilization by using the area above the glucose curve instead.

	Subjects and Methods

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We enrolled 33 healthy volunteers, 16 males and 17 females [mean ± SD age, 30.8 ± 8.3 yr; range, 20–47; mean body mass index (BMI), 22.0 ± 3.9 kg/m²; range, 17.1–32.7]. All had normal glucose tolerance according to the WHO criteria. Each subject was studied for 2 consecutive d. They all underwent a 75-g OGTT in the morning of d 1 and a euglycemic hyperinsulinemic clamp on the morning of d 2. The study was approved by the ethics committee of Faculty of Medicine, Prince of Songkla University. Informed consent was obtained from each subject before participation.

75-g OGTT

The 75-g OGTT was carried out after a 10-h overnight fast. Subjects ingested 75 g glucose in 300 ml water over a period of less than 5 min. Blood samples were collected through an indwelling catheter before and at 30-min intervals after the glucose load over a 3-h period for determination of plasma glucose and serum insulin. The subjects voided just before the ingestion of glucose and were seated during the test. Urine was collected at the end of OGTT for the determination of urinary glucose.

Euglycemic hyperinsulinemic clamp

Glucose clamp was carried out as described originally by DeFronzo et al. (8). The subjects were studied in the recumbent or supine position at 0900 h after a 10-h overnight fast. An iv catheter was placed in an antecubital vein for infusion of insulin and glucose. Another catheter was placed in the contralateral hand for blood sampling. This hand was placed in a warming box thermostatically controlled at 60 C to arterialize the blood. An insulin solution (Actrapid, Novo Nordisk, Copenhagen, Denmark) was prepared with normal saline at a concentration of 0.3 U/ml. A 10-min priming insulin infusion was followed by a constant infusion of 50 mU/m² surface area·min for 110 min. The plasma glucose concentration was measured at the bedside every 5 min, and an infusion of 20% dextrose was adjusted to maintain the plasma glucose concentration at 5 mmol/liter according to a computerized algorithm with a coefficient of variation less than 5%. Blood samples were also collected at the beginning and every 10 min during the last hour of study for determination of serum insulin concentrations.

Assays

Glucose concentrations were analyzed by the glucose oxidase method using Synchron CX-3 (Beckman Coulter, Inc., Fullerton, CA). Serum insulin concentrations were determined by RIA (Diagnostic Products, Los Angeles, CA). Intraassay coefficients of variation were 5.8% and 4.2% at mean concentrations of 300 and 960 pmol/liter, and interassay coefficients of variation were 8.0% and 7.0% at mean concentrations of 280 and 1174 pmol/liter.

ISI_OGTT

Assuming that there was no insulin available in the body and 75 g glucose are ingested, the plasma glucose concentration would be very high, as shown in Fig. 1. Let’s call this level of plasma glucose concentration the postloading plasma glucose concentration without insulin (PPGC-without insulin). In reality, after glucose is ingested, the plasma glucose concentration responses during OGTT would be much lower than the PPGC-without insulin. The appearance of glucose or the area under the glucose curve (AUCglu) represents glucose that comes from hepatic glucose production and unused glucose. Therefore, the peripheral glucose utilization is the area above the glucose curve (AACglu) less urinary glucose during the OGTT. PPGC-without insulin originates from the fasting plasma glucose concentration (FPG) plus the estimated plasma glucose concentration when 75 g glucose are ingested in the absence of insulin, the level of which is calculated from the glucose load divided by the extracellular fluid volume or glucose space (Eq I). The glucose load is 0.75 multiplied by 75,000 mg, which is converted to millimoles by dividing by 180. The factor 0.75 is the proportion of ingested glucose absorbed by the intestine in 3 h, which is approximately 75% (7, 9, 10, 11). The glucose space is 0.19 liters of body weight (BW) in kilograms:

AACglu is calculated by subtracting AUCglu from the area under PPGC-without insulin in 3 h (3 x PPGC-without insulin) and is converted into millimoles by multiplying by glucose space:

Peripheral glucose utilization (millimoles) is calculated by subtracting glucose appearing in the urine (Uglu) from AACglu and is converted to micromoles by multiplying by 1000. The glucose disposal rate is calculated by dividing the peripheral glucose utilization by BW in kilograms and number of minutes (180) during the OGTT:

ISI_OGTT is calculated by dividing the glucose disposal rate by the area under the insulin curve during the OGTT (AUCins). For convenience, we express our data by multiplying ISI_OGTT by 100. When we combine all equations together, ISI_OGTT can be rewritten as follows.

The AUCglu and AUCins responses during OGTT were calculated by a trapezoidal method.

View larger version (17K): [in this window] [in a new window]   Figure 1. Model derived from oral glucose tolerance test for calculating insulin sensitivity index. PPGC-without insulin, post-loading plasma glucose concentration without insulin. AAUglu, area above the glucose curve. AUCglu, area under the glucose curve.

Glucose disposal rates (M) were calculated at 20-min intervals (Eq V) and averaged over the last 60 min of the glucose clamp study. The steady state serum insulin levels (I) were averaged over the same period. ISI_Clamp is the ratio of the mean glucose disposal rates and steady state serum insulin levels (M/I):

Space correction, a factor of considerable magnitude if plasma glucose levels are relatively unstable, is calculated according to Eq VI. G₂ and G₁ are the glucose concentrations at the end and the beginning of the time period, respectively:

Statistical analysis

Data were expressed as the mean ± SD. Pearson’s correlation coefficients were used for studying the strength of association. Comparisons between two correlation coefficients were tested by the use of Z = z₁ - z₂/ , as described in Zar et al. (12). P < 0.05 was considered statistically significant. Statistical analysis was performed using SPSS 9.0 for Windows (SPSS, Inc., Chicago, IL).

	Results

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Plasma glucose and serum insulin during OGTT and glucose clamp are presented in Figs. 2 and 3, respectively. The glucose disposal rate and ISI_Clamp were 27.46 ± 16.55 µmol/kg·min and 7.39 ± 2.72 µmol/kg·min/pmol·liter, respectively. Figure 4 displays the scatterplot of the relationship between our equation of ISI_OGTT and ISI_Clamp. There was a highly significant correlation between the two measurements (r = 0.869; P < 0.0001). Applying our data to other formulas developed by a number of researchers gave the correlation coefficients shown in Table 2. The correlation between our equation of ISI_OGTT and ISI_Clamp was significantly better than the correlation between other equations of ISI_OGTT and ISI_Clamp, except that of Matsuda and DeFronzo (2).

View larger version (19K): [in this window] [in a new window]   Figure 2. Plasma glucose (•) and serum insulin () concentrations during the OGTT.

View larger version (24K): [in this window] [in a new window]   Figure 3. Plasma glucose (•) and serum insulin () during the euglycemic hyperinsulinemic clamp study.

View larger version (10K): [in this window] [in a new window]   Figure 4. Scatterplot of our equation of ISIOGTT vs. ISIClamp in 33 subjects (r = 0.869; P < 0.0001).

	Discussion

Top Abstract Introduction Subjects and Methods Results Discussion References

Based on the facts that compensatory hyperinsulinemia is normally found in the insulin resistance state and that plasma glucose concentrations are similar in subjects with normal glucose tolerance, insulin levels, which represent the ability of pancreatic ß-cells to secrete insulin, are therefore associated with insulin resistance. Previous studies showed that fasting insulin, either alone or combined with fasting glucose, provided a reasonable ISI (13, 14, 15, 16). Likewise, several studies have demonstrated that HOMA and QUICKI had a good correlation with ISI_Clamp (2, 4, 5, 17). In contrast, this study demonstrated that both HOMA and QUICKI had a weak correlation with ISI_Clamp. The most likely explanation for this discrepancy is that the subjects in this study were lean and had low fasting insulin concentrations (mean fasting insulin, 53 pmol/liter), whereas the subjects in previous studies that reported good results by HOMA and QUICKI were obese and had high fasting insulin levels (mean fasting insulin, 76–122 pmol/liter). As the intraassay coefficient of variation of insulin determination at low concentrations was high, a high variability in determinations at low levels of insulin could possibly cause a weak correlation between HOMA or QUICKI and ISI_Clamp in this study. This finding was in agreement with several investigators. Katz et al. (5) found that the correlation between QUICKI and ISI_Clamp was lower in nonobese subjects (r = 0.49) compared with obese subjects (r = 0.89). Likewise, Burn et al. (15) demonstrated that the correlation between ISI that used fasting insulin with or without fasting glucose and ISI_Clamp was higher in an obese group than in a group consisting of both lean and obese subjects. Furthermore, the correlation also depends on the range of insulin sensitivity in the study population. If this is wide, the correlation is greater than if it is narrow (18).

In accordance with previous reports (2, 3), our data showed that the ISI_OGTT by which both fasting and postload glucose and insulin concentrations were included (i.e. Cederholm, Gutt, Belfiore, and Matsuda) had higher correlation with ISI_Clamp than those that included only fasting glucose and insulin concentrations (i.e. HOMA and QUICKI). This is because fasting glucose concentrations are largely determined by basal hepatic glucose production (11, 19), which is inversely correlated with hepatic insulin sensitivity. The product of fasting glucose and fasting insulin (for HOMA) or summation of log fasting glucose and log fasting insulin (for QUICKI) therefore provides a measure of hepatic insulin sensitivity rather than peripheral insulin sensitivity. Matsuda and DeFronzo (2) demonstrated that there were a significant number of individuals with normal or near normal hepatic insulin sensitivity, but with impaired peripheral insulin sensitivity and vice versa. Therefore, ISI_OGTT, which includes postload glucose and insulin concentrations, would provide a more reasonable estimate of peripheral insulin sensitivity than those including only fasting glucose and insulin concentrations.

Recently, Stumvoll et al. (4) developed an ISI_OGTT using the regression equation derived from multiple linear regression that was highly correlated with ISI_Clamp (r = 0.79). In contrast, our study demonstrated a poor correlation between the ISI_OGTT developed by Stumvoll et al. and the ISI_Clamp (r = 0.508). The plausible explanation for the discrepancy is that the equation derived by Stumvoll et al. (4) included BMI and was obtained from obese European (BMI, 19.7–45.8 kg/m²), whereas all subjects in our study were Asian, and most of them were lean. It is well known that the relationship between the percent body fat and BMI is different among different ethnic groups. For a given value of BMI, Asians have higher body fat than Caucasians (after correction for age and gender) (20, 21). Furthermore, body fat, especially visceral fat, is a major determinant of insulin resistance (22). Therefore, Asians should have higher degrees of insulin resistance than Caucasians at the same BMI. When the equation of ISI_OGTT developed by Stumvoll et al. (4) was applied to Asians, such as in our study population, a substantially lower correlation was found.

We concluded that our equation was valid and superior to other equations of ISI derived from fasting and OGTT measurements of glucose and insulin in assessing the insulin sensitivity in subjects with normal glucose tolerance. Further studies in subjects with impaired glucose tolerance and diabetes mellitus should be performed to confirm the validity of this equation.

	Footnotes

 
This work was supported by a Faculty of Medicine research grant from Prince of Songkla University and by Glaxo SmithKline (Thailand).

Abbreviations: AACglu, Area above the glucose curve; AUCglu, area under the glucose curve; AUCins, area under the insulin curve; BMI, body mass index; BW, body weight; FPG, fasting plasma glucose concentration; ISI, insulin sensitivity index; ISI_Clamp, insulin sensitivity index obtained from glucose clamp; ISI_OGTT, insulin sensitivity index obtained from oral glucose tolerance test; OGTT, oral glucose tolerance test; PPGC-without insulin, postloading plasma glucose concentration without insulin; Uglu, glucose appearing in the urine.

Received July 18, 2002.

Accepted November 20, 2002.

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This Article Abstract Full Text (PDF) Submit a related Letter to the Editor Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Copyright Permission Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Soonthornpun, S. Articles by Geater, A. Search for Related Content PubMed PubMed Citation Articles by Soonthornpun, S. Articles by Geater, A. Pubmed/NCBI databases Compound via MeSH Substance via MeSH