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Articles by R Muniyappa
Total Records ( 3 ) for R Muniyappa
  R Muniyappa , H Chen , R. H Muzumdar , F. H Einstein , X Yan , L. Q Yue , N Barzilai and M. J. Quon

Assessing insulin resistance in rodent models gives insight into mechanisms that cause type 2 diabetes and the metabolic syndrome. The hyperinsulinemic euglycemic glucose clamp, the reference standard for measuring insulin sensitivity in humans and animals, is labor intensive and technically demanding. A number of simple surrogate indexes of insulin sensitivity/resistance have been developed and validated primarily for use in large human studies. These same surrogates are also frequently used in rodent studies. However, in general, these indexes have not been rigorously evaluated in animals. In a recent validation study in mice, we demonstrated that surrogates have a weaker correlation with glucose clamp estimates of insulin sensitivity/resistance than in humans. This may be due to increased technical difficulties in mice and/or intrinsic differences between human and rodent physiology. To help distinguish among these possibilities, in the present study, using data from rats substantially larger than mice, we compared the clamp glucose infusion rate (GIR) with surrogate indexes, including QUICKI, HOMA, 1/HOMA, log (HOMA), and 1/fasting insulin. All surrogates were modestly correlated with GIR (r = 0.34–0.40). Calibration analyses of surrogates adjusted for body weight demonstrated similar predictive accuracy for GIR among all surrogates. We conclude that linear correlations of surrogate indexes with clamp estimates and predictive accuracy of surrogate indexes in rats are similar to those in mice (but not as substantial as in humans). This additional rat study (taken with the previous mouse study) suggests that application of surrogate insulin sensitivity indexes developed for humans may not be appropriate for determining primary outcomes in rodent studies due to intrinsic differences in metabolic physiology. However, use of surrogates may be appropriate in rodents, where feasibility of clamps is an obstacle and measurement of insulin sensitivity is a secondary outcome.

  P Singal , R Muniyappa , R Chisholm , G Hall , H Chen , M. J Quon and K. J. Mather

After a constant insulin infusion is initiated, determination of steady-state conditions for glucose infusion rates (GIR) typically requires ≥3 h. The glucose infusion follows a simple time-dependent rise, reaching a plateau at steady state. We hypothesized that nonlinear fitting of abbreviated data sets consisting of only the early portion of the clamp study can provide accurate estimates of steady-state GIR. Data sets from two independent laboratories were used to develop and validate this approach. Accuracy of the predicted steady-state GDR was assessed using regression analysis and Altman-Bland plots, and precision was compared by applying a calibration model. In the development data set (n = 88 glucose clamp studies), fitting the full data set with a simple monoexponential model predicted reference GDR values with good accuracy (difference between the 2 methods –0.37 mg·kg–1·min–1) and precision [root mean square error (RMSE) = 1.11], validating the modeling procedure. Fitting data from the first 180 or 120 min predicted final GDRs with comparable accuracy but with progressively reduced precision [fitGDR-180 RMSE = 1.27 (P = NS vs. fitGDR-full); fitGDR-120 RMSE = 1.56 (P < 0.001)]. Similar results were obtained with the validation data set (n = 183 glucose clamp studies), confirming the generalizability of this approach. The modeling approach also derives kinetic parameters that are not available from standard approaches to clamp data analysis. We conclude that fitting a monoexponential curve to abbreviated clamp data produces steady-state GDR values that accurately predict the GDR values obtained from the full data sets, albeit with reduced precision. This approach may help reduce the resources required for undertaking clamp studies.

  R Muniyappa , B. A Irving , U. S Unni , W. M Briggs , K. S Nair , M. J Quon and A. V. Kurpad

Insulin resistance is highly prevalent in Asian Indians and contributes to worldwide public health problems, including diabetes and related disorders. Surrogate measurements of insulin sensitivity/resistance are used frequently to study Asian Indians, but these are not formally validated in this population. In this study, we compared the ability of simple surrogate indices to accurately predict insulin sensitivity as determined by the reference glucose clamp method. In this cross-sectional study of Asian-Indian men (n = 70), we used a calibration model to assess the ability of simple surrogate indices for insulin sensitivity [quantitative insulin sensitivity check index (QUICKI), homeostasis model assessment (HOMA2-IR), fasting insulin-to-glucose ratio (FIGR), and fasting insulin (FI)] to predict an insulin sensitivity index derived from the reference glucose clamp method (SIClamp). Predictive accuracy was assessed by both root mean squared error (RMSE) of prediction as well as leave-one-out cross-validation-type RMSE of prediction (CVPE). QUICKI, FIGR, and FI, but not HOMA2-IR, had modest linear correlations with SIClamp (QUICKI: r = 0.36; FIGR: r = –0.36; FI: r = –0.27; P < 0.05). No significant differences were noted among CVPE or RMSE from any of the surrogate indices when compared with QUICKI. Surrogate measurements of insulin sensitivity/resistance such as QUICKI, FIGR, and FI are easily obtainable in large clinical studies, but these may only be useful as secondary outcome measurements in assessing insulin sensitivity/resistance in clinical studies of Asian Indians.

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