Diabetes Care
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

Diabetes Care 30:2411-2413, 2007
DOI: 10.2337/dc07-1067
© 2007 by the American Diabetes Association
This Article
Right arrow Extract Freely available
Right arrow Full Text (PDF)
Right arrow Purchase Article
Right arrow View Shopping Cart
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow Request Permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by McAuley, K. A.
Right arrow Articles by Shaw, G. M.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by McAuley, K. A.
Right arrow Articles by Shaw, G. M.
Social Bookmarking
Add to CiteULike   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?

Editorials
Point-counterpoint

Point: HOMA—Satisfactory for the Time Being

HOMA: The best bet for the simple determination of insulin sensitivity, until something better comes along

Kirsten A. McAuley, MBCHB, PHD1, Jim I. Mann, FRACP1, J. Geoffrey Chase, PHD2, Thomas F. Lotz, DIP-ING2 and Geoffrey M. Shaw, FJFICM3

1 Edgar National Centre for Diabetes Research, University of Otago, Dunedin, New Zealand
2 Centre for Bioengineering, Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand
3 Department of Intensive Care, Christchurch Hospital and Christchurch School of Medicine and Health Sciences, University of Otago, Christchurch, New Zealand

Address correspondence and reprint requests to Professor Jim I. Mann, Edgar National Centre for Diabetes Research, Department of Medical and Surgical Sciences, P.O. Box 913, Dunedin 9054, New Zealand. E-mail: jim.mann{at}otago.ac.nz

There is no doubt that the cluster of clinical and metabolic features associated with insulin resistance predicts risk of developing type 2 diabetes and cardiovascular disease (CVD) (1); however, whether there is merit in defining a syndrome is less clear (2). There is also a lack of agreement regarding the value of measuring insulin sensitivity in clinical practice (3). The widely used criteria for defining the metabolic syndrome (those recommended by the World Health Organization [4] and the Adult Treatment Panel III [5]) includes a measure of insulin resistance in the definition of the syndrome. A very recent approach suggested by a group representing the International Diabetes Federation involves identifying individuals with central obesity and a range of clinical and metabolic parameters associated with insulin resistance; however, it does not include a direct measure of insulin sensitivity (6). It is argued that measures of insulin resistance do not predict CVD when other more easily measured components of the metabolic syndrome cluster are present, and these measures based on fasting insulin are unreliable (3). However, measurement of insulin sensitivity has greatly enhanced the understanding of the pathophysiology of diabetes and relationships to cardiovascular outcomes (7). Dismissing the assessment of insulin sensitivity because its measurement is too variable or difficult (3) is understandable, but hardly desirable, as one major dimension of altered metabolism will be omitted from research and clinical assessments. It may prove to be much the same as assessing cardiovascular risk without serum cholesterol. A truly reliable simple measure may prove to be more appropriate than an aggregation of surrogates in predicting subsequent development of diabetes and CVD and in further explaining disease progression and response to treatment.

Several reviews (8,9) describe some of the numerous methods for measuring or estimating insulin sensitivity. The different methods do not necessarily measure the same effect, even if they correlate well with accepted accurate methods. The euglycemic insulin clamp, which provides highly reproducibly (coefficient of variation [CV] 6–10%) (8) steady-state estimates of insulin-mediated glucose clearance in peripheral tissues, is generally regarded as the gold standard. The test uses very high-dose infusions of glucose and insulin to almost completely suppress hepatic glucose uptake and pancreatic insulin secretion. The euglycemic insulin clamp may be criticized on the grounds that it is an assessment in a nonphysiological state and that the test yields different results if performed at different infusion rates, suggesting saturable peripheral glucose uptake; hence, there is underestimation of actual insulin sensitivity. As a result, studies using very different insulin infusion rates cannot be compared (10). Non–insulin-dependent glucose uptake, such as the constant uptake by the brain and central nervous system, are not separately accounted for and included in the final measure of insulin sensitivity. In addition, the procedure is time consuming, expensive, reasonably difficult to perform, and not suited to population studies, large intervention trials, or clinical practice.

The intravenous glucose tolerance test, using Bergman's minimal model, has been extensively used in relatively small research studies and compares favorably with the euglycemic insulin clamp, although it is considerably less reproducible (CV 14–30%) and is just as arduous to undertake (8,11,12). Various modifications have been made in an attempt to improve its reliability. These modifications include the infusion of tolbutamide to trigger a pancreatic response, an injection of insulin 20 min after glucose administration, the addition of glucose tracers to separate the effects of glucose production and utilization, and several different methods to enhance the minimal model (13–15). Overall, its use is limited to small research studies as an alternative to the euglycemic insulin clamp (16,17).

The continuous infusion of glucose with model assessment involves relatively low-dose infusion of glucose over 60 min to mimic a postprandial state. It is physologically and relatively simple and safe, but the high CV (17–21%) and relatively poor correlation with the euglycemic insulin clamp (r = 0.66–0.87) (18,19) explain why continuous infusion of glucose with model assessment is no longer used. Measurements of insulin sensitivity based on the oral glucose tolerance test were developed to avoid the requirement of intravenous procedures. Whereas all the oral methods are less invasive, they are inherently less reproducible due to the variability of entry of oral glucose in circulation, which is determined by the rate of gastric emptying and splanchnic glucose uptake.

The remaining surrogate methods rely on fasting blood samples (9). The appreciable number of such tests suggests that none are ideal. Homeostasis model assessment (HOMA), based on fasting glucose and insulin, is the oldest (developed in 1985) (20) and most widely used and published test. For this reason alone, it offers some advantage over other methods in that it permits comparisons among studies that use this metric. HOMA has the additional advantage of providing an assessment of ß-cell function, in addition to insulin sensitivity. Its calculation is based on a simplified solution of a physiologically based structural model. It is based on the relationship of basal glucose and insulin levels, which reflect the balance between hepatic glucose output and insulin secretion and is maintained by a feedback loop between the liver and ß-cells (21). HOMA has been most extensively used in descriptive epidemiological studies, e.g., comparisons of insulin sensitivity in different racial groups (22–24), and in those with different genetic polymorphisms (25). The approach has also been used to examine changes in insulin sensitivity and ß-cell function as the disease state progresses in longitudinal studies and to determine effects of treatment (26). HOMA has been inappropriately used to assess ß-cell function in isolation or after relatively short interventions.

A recent review of the methods estimating insulin sensitivity on the basis of a simple fasting sample compared fasting insulin, glucose-to-insulin ratio, insulin-to-glucose ratio, HOMA of insulin resistance, quantitative insulin sensitivity check index, Belfiore glycemia, Belfiore free fatty acids, and the McAuley Index. Their performance was compared in normal-weight and overweight individuals, in those with type 2 diabetes, and in the group as a whole. It would appear from this review (9) that no one method outshines another. Whereas this review concluded that the methods were generally comparable, there may be situations when one of the surrogates has advantages over the others. For example, the McAuley Index, based on fasting insulin and triglyceride (27), was developed to determine insulin sensitivity in those with no detectable abnormalities of glucose metabolism with an aim of identifying and treating those at risk of the consequences of insulin resistance at the earliest detectable stage of the disease process. In this respect, the McAuley Index appeared to outperform HOMA of insulin resistance (27). However, HOMA may indeed remain the preferred method in large epidemiological studies.

More recently, we have attempted to develop an improved physiological simple measure that includes basal and dynamic components to provide a clear indication of glucose and insulin metabolism in individuals and groups. The test can be completed in 30–45 min, requires a simple intravenous cannula and small amounts of intravenous glucose (10 g) and insulin (1 unit), has no special techniques and tracers, and is performed by a registered nurse under medical supervision in an outpatient setting. Blood samples for glucose, insulin, and C-peptide enable a glucose and insulin profile and an estimate of endogenous insulin secretion to be generated for each individual. With significant advances in the modeling of glucose and insulin kinetics and in the model parameter identification methods used, this method has generated insulin sensitivity values that correlate very highly with euglycemic insulin clamp results (r = 0.97, n = 60) (28). In addition to providing a quantitative measure of insulin sensitivity, the test also provides a profile of glucose and insulin metabolism, including blood glucose concentration in response to a small glucose and insulin challenge, basal insulin levels, first-phase insulin response, and the endogenous insulin secretion peak and decay. This comprehensive profile adds considerably over and above the usual known risk factors for type 2 diabetes and would allow a more detailed classification of a heterogeneous group of individuals. Examples of individual glucose, insulin, and insulin secretion profiles generated by this method are shown in Fig. 1.


Figure 1
View larger version (60K):
[in this window]
[in a new window]

  		Figure 1— Examples of three profiles from the proposed new test in an individual with normal glucose tolerance (NGT), impaired glucose tolerance (IGT), and type 2 diabetes (type 2). The individual with NGT has an insulin sensitivity value of 16.9 x 10–5 l · pmol–1 · min–1. The first-phase ß-cell response to a bolus of glucose is very distinct and large, releasing 4,840 pmol insulin during the first 10 min after glucose administration. The first-phase release is 5–10 min, and the insulin secretion rate drops immediately back to its basal rate. The individual with IGT has an insulin sensitivity value of 4.6 x 10–5 l · pmol–1 · min–1 and fasting glucose and insulin levels are increased. After a glucose bolus, the first-phase insulin secretion is no longer distinct, and high amounts of insulin are secreted for the duration of the test. Blood glucose levels drop slowly. The individual with type 2 diabetes has an insulin sensitivity value of 9.7 x 10–5 l · pmol–1 · min–1 (higher than the individual with IGT). Basal insulin secretion is elevated, but not as high as the person with IGT, and it increases only slightly in response to the glucose bolus (1,576 pmol of insulin released during first-phase secretion), consistent with ß-cell exhaustion. Black circles indicate measured glucose and insulin, with the respective assay error bars, and the shaded area represents glucose and insulin profiles calculated using the proposed model equations.

 
This method now needs to be tested and validated in a new population, but it already shows promise for generating useful, reliable, and accurate data from a relatively easy to perform safe test. This would likely convince those who have previously given up assessing insulin sensitivity that there is a useful and practical method that provides a glucose and insulin profile rather than just a metric for insulin sensitivity.

Acknowledgments

We acknowledge funding from the University of Otago and the National Heart Foundation of New Zealand for enabling the investigation of this novel measure for insulin sensitivity.

We thank Victoria Farmer for research assistance in writing this manuscript.

References

  1. Eckel RH, Grundy SM, Zimmet PZ: The metabolic syndrome. Lancet 365:1415–1428, 2005[Medline]
  2. Gale EA: The myth of the metabolic syndrome. Diabetologia 48:1679–1683, 2005[Medline]
  3. Samaras K, McElduff A, Twigg SM, Proietto J, Prins JB, Welborn TA, Zimmet P, Chisholm DJ, Campbell LV: Insulin levels in insulin resistance: phantom of the metabolic opera? Med J Aust 185:159–161, 2006[Medline]
  4. World Health Organization: Definition, Diagnosis, and Classification of Diabetes Mellitus and Its Complications: Report of a WHO Consultation. Geneva, World Health Org., 1999
  5. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults: Executive summary of the 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). JAMA 285:2486–2497, 2001[Free Full Text]
  6. Alberti KG, Zimmet P, Shaw J: Metabolic syndrome–a new world-wide definition: a consensus statement from the International Diabetes Federation. Diabet Med 23:469–480, 2006[Medline]
  7. McLaughlin T, Abbasi F, Lamendola C, Reaven G: Heterogeneity in the prevalence of risk factors for cardiovascular disease and type 2 diabetes mellitus in obese individuals: effect of differences in insulin sensitivity. Arch Intern Med 167:642–648, 2007[Abstract/Free Full Text]
  8. Ferrannini E, Mari A: How to measure insulin sensitivity. J Hypertens 16:895–906, 1998[Medline]
  9. Ruige JB, Mertens IL, Bartholomeeusen E, Dirinck E, Ferrannini E, Van Gaal LF: Fasting-based estimates of insulin sensitivity in overweight and obesity: a critical appraisal. Obesity (Silver Spring ) 14:1250–1256, 2006[Medline]
  10. Natali A, Gastaldelli A, Camastra S, Sironi AM, Toschi E, Masoni A, Ferrannini E, Mari A: Dose-response characteristics of insulin action on glucose metabolism: a non-steady-state approach. Am J Physiol Endocrinol Metab 278:E794–E801, 2000[Abstract/Free Full Text]
  11. Monzillo LU, Hamdy O: Evaluation of insulin sensitivity in clinical practice and in research settings. Nutr Rev 61:397–412, 2003[Medline]
  12. Scheen AJ, Paquot N, Castillo MJ, Lefebvre PJ: How to measure insulin action in vivo. Diabetes Metab Rev 10:151–188, 1994[Medline]
  13. Cobelli C, Pacini G, Toffolo G, Sacca L: Estimation of insulin sensitivity and glucose clearance from minimal model: new insights from labeled IVGTT. Am J Physiol 250:E591–E598, 1986[Medline]
  14. Caumo A, Cobelli C: Hepatic glucose production during the labeled IVGTT: estimation by deconvolution with a new minimal model. Am J Physiol 264:E829–E841, 1993[Medline]
  15. Mari A: Assessment of insulin sensitivity and secretion with the labelled intravenous glucose tolerance test: improved modelling analysis. Diabetologia 41:1029–1039, 1998[Medline]
  16. Storgaard H, Jensen CB, Vaag AA, Volund A, Madsbad S: Insulin secretion after short- and long-term low-grade free fatty acid infusion in men with increased risk of developing type 2 diabetes. Metabolism 52:885–894, 2003[Medline]
  17. Pedrini MT, Niederwanger A, Kranebitter M, Tautermann C, Ciardi C, Tatarczyk T, Patsch JR: Postprandial lipaemia induces an acute decrease of insulin sensitivity in healthy men independently of plasma NEFA levels. Diabetologia 49:1612–1618, 2006[Medline]
  18. Hosker JP, Matthews DR, Rudenski AS, Burnett MA, Darling P, Bown EG, Turner RC: Continuous infusion of glucose with model assessment: measurement of insulin resistance and beta-cell function in man. Diabetologia 28:401–411, 1985[Medline]
  19. Nijpels G, van der Wal PS, Bouter LM, Heine RJ: Comparison of three methods for the quantification of beta-cell function and insulin sensitivity. Diabetes Res Clin Pract 26:189–195, 1994[Medline]
  20. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC: Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28:412–419, 1985[Medline]
  21. Wallace TM, Levy JC, Matthews DR: Use and abuse of HOMA modeling. Diabetes Care 27:1487–1495, 2004[Abstract/Free Full Text]
  22. Dabelea D, Pettitt DJ, Hanson RL, Imperatore G, Bennett PH, Knowler WC: Birth weight, type 2 diabetes, and insulin resistance in Pima Indian children and young adults. Diabetes Care 22:944–950, 1999[Abstract]
  23. Matsumoto K, Miyake S, Yano M, Ueki Y, Yamaguchi Y, Akazawa S, Tominaga Y: Glucose tolerance, insulin secretion, and insulin sensitivity in nonobese and obese Japanese subjects. Diabetes Care 20:1562–1568, 1997[Abstract]
  24. Haffner SM, Miettinen H, Stern MP: The homeostasis model in the San Antonio Heart Study. Diabetes Care 20:1087–1092,1997
  25. Strazzullo P, Iacone R, Siani A, Cappuccio FP, Russo O, Barba G, Barbato A, D'Elia L, Trevisan M, Farinaro E: Relationship of the Trp64Arg polymorphism of the beta3-adrenoceptor gene to central adiposity and high blood pressure: interaction with age: cross-sectional and longitudinal findings of the Olivetti Prospective Heart Study. J Hypertens 19:399–406, 2001[Medline]
  26. Hanefeld M, Marx N, Pfutzner A, Baurecht W, Lubben G, Karagiannis E, Stier U, Forst T: Anti-inflammatory effects of pioglitazone and/or simvastatin in high cardiovascular risk patients with elevated high sensitivity C-reactive protein: the PIOSTAT Study. J Am Coll Cardiol 49:290–297, 2007[Abstract/Free Full Text]
  27. McAuley KA, Williams SM, Mann JI, Walker RJ, Lewis-Barned NJ, Temple LA, Duncan AW: Diagnosing insulin resistance in the general population. Diabetes Care 24:460–464, 2001[Abstract/Free Full Text]
  28. Lotz T, Chase J, McAuley K, Lee D, Lin J, Hann C, Mann JI: Transient and steady-state euglycemic clamp validation of a model for glycemic control and insulin sensitivity testing. Diabetes Technol Ther 8:338–346, 2006[Medline]

Add to CiteULike CiteULike   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?


This article has been cited by other articles:


Home page
 DiabetesHome page
A. Festa, K. Williams, A. J.G. Hanley, and S. M. Haffner
{beta}-Cell Dysfunction in Subjects With Impaired Glucose Tolerance and Early Type 2 Diabetes: Comparison of Surrogate Markers With First-Phase Insulin Secretion From an Intravenous Glucose Tolerance Test
Diabetes, June 1, 2008; 57(6): 1638 - 1644.
[Abstract] [Full Text] [PDF]

Home page
 Diabetes CareHome page
E. J. Boyko and C. C. Jensen
Do We Know What Homeostasis Model Assessment Measures?: If not, does it matter?
Diabetes Care, October 1, 2007; 30(10): 2725 - 2728.
[Full Text] [PDF]

This Article
Right arrow Extract Freely available
Right arrow Full Text (PDF)
Right arrow Purchase Article
Right arrow View Shopping Cart
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow Request Permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by McAuley, K. A.
Right arrow Articles by Shaw, G. M.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by McAuley, K. A.
Right arrow Articles by Shaw, G. M.
Social Bookmarking
Add to CiteULike   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Diabetes Diabetes Care Clinical Diabetes Diabetes Spectrum