The Journal of Pediatrics
Volume 153, Issue 1 , Pages 7-9, July 2008

Discordant HbA1c Results: The Hoofbeats Increase

  • Robert M. Cohen, MD

      Affiliations

    • Division of Endocrinology, Diabetes & Metabolism, Department of Medicine, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio
    • Corresponding Author InformationReprint requests: Robert M. Cohen, MD, Division of Endocrinology, Diabetes & Metabolism, PO Box 670547, Vontz Center for Molecular Studies, 3125 Eden Avenue, University of Cincinnati Medical Center, Cincinnati, OH 45267-0547.
    • ,
  • Clinton H. Joiner, MD, PhD

      Affiliations

    • Sickle Cell Center, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio
    • ,
  • Robert S. Franco, PhD

      Affiliations

    • Division of Hematology-Oncology, Department of Medicine, Sickle Cell Center, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio

Article Outline

Abbreviations: Hb, Hemoglobin, HbA1c, Glycated hemoglobin, HPLC, High-performance liquid chromatography

 

In this issue of The Journal, Felner and McGrath report 2 boys in whom assessment of glycemic control by hemoglobin A1c (HbA1c) in diabetes was confounded by the persistence of HbF.1 In the terminology taught to medical students concerning the proverbial “hoofbeats in the night,” taken in the narrow sense (ie, the specific hemoglobinopathy), these cases are “zebras.” But the report of these cases comes at a time when we have gained some new insight into the frequency and sources of discordance between HbA1c and other measures of glycemic control. We have historically considered 3 broad categories that affect the interpretation of HbA1c: hemoglobinopathies, diseases involving short red cell survival, and assay methodology.2, 3 Indeed, hemoglobinopathies collectively are not that uncommon, depending on the practice setting. However, by looking more systematically for discordances, we are finding new support for additional physiological mechanisms that influence HbA1c. It is not yet clear whether these mechanisms simply alter laboratory test results (for which some simple correction will eventually emerge) or instead affect the likelihood of complications and thus provide additional information that we need to learn how to use in risk assessment. Taken together, the “hoofbeats” represent not only zebras and some known breeds of horse, but also a few new breeds of horse as well.

See related article, p 137

Clinicians who see many patients with diabetes agree almost universally that HbA1c values do not always line up with blood glucose results. Such discordance is not uncommon. With the increasingly reliable downloadable blood glucose meters and increased access to continuous glucose sensors, it is becoming less likely that dishonesty or equipment malfunction is to blame. It is necessary to have a strategy for making comparisons and to bring a skeptical eye to the data. Several groups have noted that 2 different markers of glycemic control measured simultaneously should be randomly distributed around the population regression between the 2 markers on repeated occasions. If no confounder or systematic bias is present, then the distribution should be symmetric and random. If the relationship between the 2 different measures for 1 individual deviates from the population regression line in the same manner on repeated occasions, this indicates a reproducible perturbation and suggests that some factor is affecting the physiological relationship between the 2 tests.

We have applied this concept using 2 different measures of integrated glycemic control: HbA1c and glycated serum proteins (fructosamine). When comparing these 2 tests, most textbooks focus on the fact that the measured proteins have different survival times in the circulation and thus reflect glycemic control over different time periods; however, in reality, most of our patients with diabetes spend most of their life at some steady-state level of glycemic control, and thus those time differences cancel out when repeated pairs of samples are examined. We have characterized the relationship between HbA1c and fructosamine in our clinical laboratory, and can use these results to calculate a predicted HbA1c from the fructosamine result.4, 5 We then can calculate a “glycation gap” as the difference between measured HbA1c and predicted HbA1c. A consistently positive glycation gap indicates a higher than predicted HbA1c; similar reasoning would apply to a consistently negative result. A gap consistently near zero indicates that the HbA1c and fructosamine are concordant.

We chose this pair of tests because they are both integrated measures of glycemic control not subject to the moment-to-moment variation of blood glucose. Other investigators have applied the same principle comparing HbA1c with large numbers of self-monitored glucose levels measured over long periods and called this the “Hb glycation index.”6, 7, 8, 9 In statistical terms, these are 2 different names for the residual, that is, the deviation of an individual data point from a population regression line. This residual can potentially contain both systematic and random (ie, measurement-related) sources of variation.

Applying this paradigm to Felner and McGrath's case reports, we can confirm their impression about the sugars with fructosamine determinations. Assuming that the latter, like the sugars, were elevated when the HbA1c fell to normal, the calculated glycation gap would be substantially below zero. This likely would have resulted from underdetection of the glycated HbF in the numerator determination (glycated Hb immunoassay) while the total Hb used for the denominator was appropriately quantitated, lowering the reported percent of HbA1c. This finding on repeated occasions would indicate a systematic rather than a random variation. Routine hematology testing and Hb electrophoresis and/or high-performance liquid chromatography (HPLC) would be performed to identify the Hb variant. Had an HPLC ion-exchange–based HbA1c assay been used initially rather than the immunoassay relied on in the authors' clinical laboratory, some Hb variants may have been identified more promptly, and the discordance would have been apparent much earlier after the diagnosis of diabetes. But immunoassays are increasingly being used in clinical laboratories and form the basis for point-of-care HbA1c determinations; thus, it is simply a fact of life that the clues available from the older methodology often will not be available. In this situation, the threshold for performing Hb electrophoresis should be lowered. In Felner and McGrath's 2 patients with Hb variants, serum fructosamine may be a much more readily interpretable measure of glycemic control for their future care.

We applied this same strategy to the patients that 1 of us had followed for many years and found that nearly 30% of them had mismatches between measured HbA1c and fructosamine-predicted HbA1c of at least 1 HbA1c percentage point in one direction or the other.4 We evaluated the stability of the glycation gap and found that for the most part, positive values remained positive and negative values remained negative. Clearly, all of these patients do not have a hemoglobinopathy or a red cell survival disorder, prompting us to look for other possible mechanisms. For example, a 20% variation in red cell survival in hematologically normal patients could cause a 20% difference in HbA1c with identical blood glucose control. In practice, that would be the difference between an HbA1c of 7% versus 8.4% or an HbA1c of 7% versus 5.6%, which most would agree would lead to different clinical decisions. We have developed a new methodology to assess such differences and have presented preliminary data demonstrating that differences in red cell survival can be found in hematologically normal persons.5, 10, 11 We also have found, in a retrospective study, an association between a positive glycation gap and an increased frequency of nephropathy and, in a prospective study, an association between a positive glycation gap and an increased frequency of retinopathy.4, 12 Similar results have been obtained for the Hb glycation index.7, 9 These findings provide evidence that discordances between HbA1c and other measures of glycemic control (ie, fructosamine, blood glucose) can be linked to the risk of complications. Thus, the risk of diabetic complications is associated not only with determinants that affect both HbA1c and the alternative measure equally, but also with determinants that have an unequal effect. It seems unlikely that a wider-than-expected normal variation in red cell survival can be the only such determinant.

It is not surprising that interpreting these findings is tricky. There is a controversy in the literature as to whether the Hb glycation index is a predictor of complications independent of HbA1c.13, 14, 15 We do not believe that either the glycation gap or the Hb glycation index is independent of HbA1c in predicting complications; rather, we argue that HbA1c is itself determined by both glycemic control (which should act equally on HbA1c and fructosamine) and other mechanisms, some identified and some not, which cause the systematic variation in the glycation gap. We anticipate that these mechanisms will be identified within the next several years. Interindividual variation in the gradient of glucose across the red cell membrane is a possible candidate that conceivably could apply to other tissues.16 Evidence from twin studies suggests that genetic factors contribute to HbA1c and may represent additional risk factors for diabetic complications.17 Indeed, the genetic variation has been linked to the glycation gap fraction of HbA1c variability; in contrast, no evidence of genetic variation in glycated serum proteins has been reported.18 A recent study has found statistically different HbA1c results by race at equivalent blood glucose levels, suggesting that this phenomenon may be more widespread than once thought, whether due to genetic or environmental mechanisms.19

In closing, the hoofbeats in the HbA1c realm may occasionally be zebras, but increasingly, new breeds of horses are being found as well. This does not mean that HbA1c is a poor tool; one just needs to listen closely to add something new to the story.

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References 

  1. Felner EI, McGrath M. Inaccurate HbA1c levels in patients with type 1 diabetes and hereditary persistence of hemoglobin F. J Pediatr. 2008;153:137–139
  2. Cohen MP. Diabetes and Protein Glycosylation: Measurement and Biological Relevance. New York: Springer-Verlag; 1986;
  3. Jeha GS, Haymond M. Understanding and interpreting laboratory test results in the clinical management of diabetes mellitus. Pediatr Endocrinol Rev. 2007;5(Suppl 1):608–628
  4. Cohen RM, Holmes YR, Chenier TC, Joiner CH. Discordance between hemoglobin A1c and fructosamine: evidence for a glycosylation gap and its relation to nephropathy in long-standing type 1 diabetes. Diabetes Care. 2003;26:163–167
  5. Cohen RM. A1C: does one size fit all?. Diabetes Care. 2007;30:2756–2758
  6. Gould BJ, Davie SJ, Yudkin JS. Investigation of the mechanism underlying the variability of glycated haemoglobin in non-diabetic subjects not related to glycaemia. Clin Chim Acta. 1997;260:49–64
  7. McCarter RJ, Hempe JM, Gomez R, Chalew SA. Biological variation in HbA1c predicts risk of retinopathy and nephropathy in type 1 diabetes. Diabetes Care. 2004;27:1259–1264
  8. Wilson D, Fiallo-Scharer R, Xing D, Wysocki T, Block J, Weinzimer S, et al. Diabetes Research in Children Network (Reliability of two indices of the biologic variabiity in glycosylation among children and adolescents with T1DM). [abstract] Diabetes. 2005;54(Suppl 1):A454
  9. Kim J-I, Stevens RJ, Holman RR. The haemoglobin glycation index is an independent risk factor for microvascular complications in UKPDS patients with newly diagnosed type 2 diabetes. [abstract] Diabetes. 2005;54(Suppl 1):A244
  10. Lindsell CJ, Franco RS, Smith EP, Joiner CH, Cohen RM. A method for the continuous calculation of the age of labeled red blood cells. Am J Hematol. 2008;in press
  11. Cohen RM, Ciraolo P, Palascak MB, Lindsell CJ, Khera PK, Smith EP, et al. Red blood cell (RBC) survival differences among hematologically normal people with diabetes (DM) make a clinically important difference in HbA1c. [abstract] Diabetes. 2007;56(Suppl 1):A116
  12. Cohen RM, Lecaire TJ, Lindsell CJ, Smith EP, D'Alessio DJ. Relationship of prospective GHb to glycated serum proteins in incident diabetic retinopathy: implications of the glycation gap for mechanism of risk prediction. Diabetes Care. 2008;31:151–153
  13. Genuth S, Lachin JM, Nathan DM. Biological variation in HbA1c predicts risk of retinopathy and nephropathy in type 1 diabetes: response to McCarter et al. Diabetes Care. 2005;28:233–235
  14. Chalew SA, Hempe JM, McCarter RJ. Biological variation in HbA1c predicts risk of retinopathy and nephropathy in type 1 diabetes: response to Genuth, Lachin, and Nathan. Diabetes Care. 2005;28:234–235
  15. Lachin JM, Genuth S, Nathan DM, Rutledge BN. The hemoglobin glycation index is not an independent predictor of the risk of microvascular complications in the Diabetes Control and Complications Trial. Diabetes. 2007;56:1913–1921
  16. Khera PK, Joiner CH, Holmes YR, Cohen RM. Evidence for a steady-state glucose gradient across the erythrocyte membrane at 37°C: a potential source of variation in hemoglobin A1c. [abstract] Diabetes. 2001;50(Suppl 2):A176
  17. Snieder H, Sawtell PA, Ross L, Walker J, Spector TD, Leslie RD. HbA(1c) levels are genetically determined even in type 1 diabetes: evidence from healthy and diabetic twins. Diabetes. 2001;50:2858–2863
  18. Cohen RM, Snieder H, Lindsell CJ, Beyan H, Hawa M, Blincko S, et al. Evidence for independent heritability of the glycation gap (glycosylation gap) fraction of HbA1c in non-diabetic twins. Diabetes Care. 2006;29:1739–1743
  19. Herman WH, Ma Y, Uwaifo G, Haffner S, Kahn SE, Horton ES, et al. Differences in A1C by race and ethnicity among patients with impaired glucose tolerance in the Diabetes Prevention Program. Diabetes Care. 2007;30:2453–2457

PII: S0022-3476(08)00219-9

doi:10.1016/j.jpeds.2008.03.026

Refers to article:

  • Inaccurate Hemoglobin A1C Levels in Patients with Type 1 Diabetes and Hereditary Persistence of Hemoglobin F

    Eric I. Felner, Maureen McGrath
    The Journal of Pediatrics July 2008 (Vol. 153, Issue 1, Pages 137-139)

The Journal of Pediatrics
Volume 153, Issue 1 , Pages 7-9, July 2008

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