Lipoprotein Insulin Resistance Index: A Simple, Accurate Method for Assessing Insulin Resistance in South Asians

Author:

Fosam Andin1,Bansal Rashika1,Ramanathan Amrita1,Sarcone Camila1,Iyer Indiresha2,Murthy Meena3,Remaley Alan T4ORCID,Muniyappa Ranganath1ORCID

Affiliation:

1. Clinical Endocrine Section, Diabetes, Endocrinology, and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health , Bethesda, MD 20892 , USA

2. Department of Cardiovascular Medicine, Cleveland Clinic , Akron, OH 44302 , USA

3. Department of Endocrinology, Saint Peter's University Hospital , New Brunswick, NJ 08901 , USA

4. Lipoprotein Metabolism Section, Translational Vascular Medicine Branch, National Heart, Lung and Blood Institute (NHLBI), National Institutes of Health (NIH) , Bethesda, MD 20892 , USA

Abstract

Abstract Context Identification of insulin resistance (IR) in South Asians, who are at a higher risk for type 2 diabetes, is important. Lack of standardization of insulin assays limits the clinical use of insulin-based surrogate indices. The lipoprotein insulin resistance index (LP-IR), a metabolomic marker, reflects the lipoprotein abnormalities observed in IR. The reliability of the LP-IR index in South Asians is unknown. Objective We evaluated the predictive accuracy of LP-IR compared with other IR surrogate indices in South Asians. Methods In a cross-sectional study (n = 55), we used calibration model analysis to assess the ability of the LP-IR score and other simple surrogate indices (Homeostatic Model Assessment of Insulin Resistance, Quantitative insulin sensitivity check index, Adipose insulin resistance index, and Matsuda Index) to predict insulin sensitivity (SI) derived from the reference frequently sampled intravenous glucose tolerance test. LP-IR index was derived from lipoprotein particle concentrations and sizes measured by nuclear magnetic resonance spectroscopy. Predictive accuracy was determined by root mean squared error (RMSE) of prediction and leave-one-out cross-validation type RMSE of prediction (CVPE). The optimal cut-off of the LP-IR index was determined by the area under the receiver operating characteristic curve (AUROC) and the Youden index. Results The simple surrogate indices showed moderate correlations with SI (r = 0.53-0.69, P < .0001). CVPE and RMSE were not different in any of the surrogate indices when compared with LP-IR. The AUROC was 0.77 (95% CI 0.64-0.89). The optimal cut-off for IR in South Asians was LP-IR >48 (sensitivity: 75%, specificity: 70%). Conclusion The LP-IR index is a simple, accurate, and clinically useful test to assess IR in South Asians.

Publisher

The Endocrine Society

Subject

Endocrinology, Diabetes and Metabolism

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