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Disposition index

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Hyberbolic relationship between insulin sensitivity and beta cell function showing dynamical compensation in "healthy" insulin resistance (transition from A to B) and the evolution of type 2 diabetes mellitus (transition from A to C).
Hyberbolic relationship between insulin sensitivity and beta cell function showing dynamical compensation in "healthy" insulin resistance (transition from A to B) and the evolution of type 2 diabetes mellitus (transition from A to C). Disposition metrics integrate beta cell function and insulin sensitivity in a way so that the results remain constant across dynamical compensation. Changed from Cobelli et al. 2007 and Hannon et al. 2018[1][2]

The Disposition index (DI) is a measure for the loop gain of the insulin-glucose feedback control system. It is defined as the product of insulin sensitivity times the amount of insulin secreted in response to blood glucose levels.[3][4] "Metabolically healthy" Insulin resistant individuals can maintain normal responses to blood glucose due to the fact that higher levels of insulin are secreted as long as the beta cells of the pancreas are able to increase their output of insulin to compensate for the insulin resistance. But the ratio of the incremental increase in plasma insulin associated with an incremental increase in plasma glucose (disposition index) provides a better measure of beta cell function than the plasma insulin response to a glucose challenge.[5] Loss of function of the beta cells, reducing their capacity to compensate for insulin resistance, results in a lower disposition index.[3]

Methods of determination

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The disposition index can be obtained on the basis of data that provide information on insulin sensitivity and beta cell function. Suitable sources include:

If clamp investigations are used the disposition index is defined as the product of the area under the insulin response curve () and the insulin sensitivity index (ISIClamp, average glucose infusion rate divided by average insulin concentration) with

.[6]

Determining the disposition index on the basis of an FSIGT requires fitting the timeseries of insulin and glucose concentrations to the minimal model of insulin-glucose homeostasis.[10] The disposition index is then calculated as

from the first phase response of plasma insulin to the glucose injection () and the insulin sensitivity index (SI).[10]

Based on an oral glucose tolerance test a disposition index can be calculated with

from the insulinogenic index (IGI) and the insulin sensitivity index (ISIcomposite).[7][8]

The fasting-based disposition index (SPINA-DI) can be obtained from the product of the secretory capacity of pancreatic beta cells ( or SPINA-GBeta) times the insulin receptor gain ( or SPINA-GR):

.[9]

The four approaches deliver slightly different information. Although the results of clamp-, IVGTT-, OGTT- and SPINA-derived disposition indices significantly correlate with each other the correlations are only modest.[11][12] In direct comparison, the SPINA-based disposition index (SPINA-DI) had higher discriminatory power for the diagnosis of diabetes than the OGTT-based disposition index according to Matsuda and DeFronzo.[9]

Clinical implications

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Disposition index is used as a measure of beta cell function and the ability of the body to dispose of a glucose load. Thus a lowering of disposition index predicts the conversion of insulin resistance to diabetes mellitus type 2.[13] Disposition index, but not insulin resistance, can predict type 2 diabetes in persons with normal blood glucose levels, but who do not have a family history (genetic predisposition) to type 2 diabetes.[14]

Disposition index can be increased by aerobic exercise, but only to the extent that insulin sensitivity is improved.[15]

Predictive aspects

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In a longitudinal evaluation of the NHANES study, a large sample of the general US population, over 10 years, a reduced static disposition index (SPINA-DI) significantly predicted all-cause mortality.[16]

See also

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References

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  1. ^ a b Cobelli C, Toffolo GM, Dalla Man C, Campioni M, Denti P, Caumo A, Butler P, Rizza R (July 2007). "Assessment of beta-cell function in humans, simultaneously with insulin sensitivity and hepatic extraction, from intravenous and oral glucose tests". American Journal of Physiology. Endocrinology and Metabolism. 293 (1): E1–E15. doi:10.1152/ajpendo.00421.2006. PMID 17341552.
  2. ^ Hannon TS, Kahn SE, Utzschneider KM, Buchanan TA, Nadeau KJ, Zeitler PS, Ehrmann DA, Arslanian SA, Caprio S, Edelstein SL, Savage PJ, Mather KJ, RISE C (January 2018). "Review of methods for measuring β-cell function: Design considerations from the Restoring Insulin Secretion (RISE) Consortium". Diabetes, Obesity & Metabolism. 20 (1): 14–24. doi:10.1111/dom.13005. PMC 6095472. PMID 28493515.
  3. ^ a b Bergman RN, Ader M, Huecking K, Van Citters G (2002). "Accurate assessment of beta-cell function: the hyperbolic correction". Diabetes. 51 (Supp 1): S212–S220. doi:10.2337/diabetes.51.2007.s212. PMID 11815482.
  4. ^ Ferrannini E, Mari A (May 2004). "Beta cell function and its relation to insulin action in humans: a critical appraisal". Diabetologia. 47 (5): 943–56. doi:10.1007/s00125-004-1381-z. PMID 15105990.
  5. ^ Defronzo RA (2009). "Banting Lecture. From the triumvirate to the ominous octet: a new paradigm for the treatment of type 2 diabetes mellitus". Diabetes. 58 (4): 773–795. doi:10.2337/db09-9028. PMC 2661582. PMID 19336687.
  6. ^ a b Shah SS, Ramirez CE, Powers AC, Yu C, Shibao CA, Luther JM (June 2016). "Hyperglycemic clamp-derived disposition index is negatively associated with metabolic syndrome severity in obese subjects". Metabolism: Clinical and Experimental. 65 (6): 835–42. doi:10.1016/j.metabol.2016.02.011. PMC 4867079. PMID 27173462.
  7. ^ a b Matsuda M, DeFronzo RA (September 1999). "Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp". Diabetes Care. 22 (9): 1462–70. doi:10.2337/diacare.22.9.1462. PMID 10480510.
  8. ^ a b DeFronzo RA, Matsuda M (July 2010). "Reduced time points to calculate the composite index". Diabetes Care. 33 (7): e93. doi:10.2337/dc10-0646. PMID 20587713.
  9. ^ a b c Dietrich JW, Abood A, Dasgupta R, Anoop S, Jebasingh FK, Spurgeon R, Thomas N, Boehm BO (2 January 2024). "A novel simple disposition index (SPINA-DI) from fasting insulin and glucose concentration as a robust measure of carbohydrate homeostasis". Journal of Diabetes. 16 (9). doi:10.1111/1753-0407.13525. PMC 11418405. PMID 38169110.
  10. ^ a b Bergman RN (2020). "Origins and History of the Minimal Model of Glucose Regulation". Frontiers in Endocrinology. 11: 583016. doi:10.3389/fendo.2020.583016. PMC 7917251. PMID 33658981.
  11. ^ Retnakaran R, Qi Y, Goran MI, Hamilton JK (December 2009). "Evaluation of proposed oral disposition index measures in relation to the actual disposition index". Diabetic Medicine. 26 (12): 1198–203. doi:10.1111/j.1464-5491.2009.02841.x. PMID 20002470. S2CID 9477335.
  12. ^ Sjaarda LG, Bacha F, Lee S, Tfayli H, Andreatta E, Arslanian S (July 2012). "Oral disposition index in obese youth from normal to prediabetes to diabetes: relationship to clamp disposition index". The Journal of Pediatrics. 161 (1): 51–7. doi:10.1016/j.jpeds.2011.12.050. PMC 3366166. PMID 22325254.
  13. ^ Lorenzo C, Wagenknecht LE, Rewers MJ, Karter AJ, Bergman RN, Hanley AJ, Haffner SM (2011). "Disposition index, glucose effectiveness, and conversion to type 2 diabetes: the Insulin Resistance Atherosclerosis Study (IRAS)". Diabetes Care. 33 (9): 2098–2103. doi:10.2337/dc10-0165. PMC 2928371. PMID 20805282.
  14. ^ Goldfine AB, Bouche C, Parker RA, Kim C, Kerivan A, Soeldner JS, Martin BC, Warram JH, Kahn CR (2003). "Insulin resistance is a poor predictor of type 2 diabetes in individuals with no family history of disease". Proceedings of the National Academy of Sciences of the United States of America. 100 (5): 2724–2729. Bibcode:2003PNAS..100.2724G. doi:10.1073/pnas.0438009100. PMC 151408. PMID 12591951.
  15. ^ Solomon TP, Malin SK, Karstoft K, Kashyap SR, Haus JM, Kirwan JP (2013). "Pancreatic β-cell function is a stronger predictor of changes in glycemic control after an aerobic exercise intervention than insulin sensitivity". The Journal of Clinical Endocrinology and Metabolism. 98 (10): 4176–4186. doi:10.1210/jc.2013-2232. PMC 3790622. PMID 23966244.
  16. ^ Dietrich JW (2024). "P4-Endokrinologie – Kybernetische Perspektiven eines neuen Ansatzes" (PDF). Leibniz Online. 54. doi:10.53201/LEIBNIZONLINE54.
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