Background HbA1c is a widely used biomarker for diabetes mellitus management. Here, we evaluated the accuracy of six methods for determining HbA1c values in Chinese patients with common α- and β-globin chains variants in China. Methods Blood samples from normal subjects and individuals exhibiting hemoglobin variants were analyzed for HbA1c, using Sebia Capillarys 2 Flex Piercing (C2FP), Bio-Rad Variant II Turbo 2.0, Tosoh HLC-723 G8 (ver. 5.24), Arkray ADAMS A1c HA-8180V fast mode, Cobas c501 and Trinity Ultra2 systems. Results DNA sequencing revealed five common β-globin chain variants and three common α-globin chain variants. The most common variant was Hb E, followed by Hb New York, Hb J-Bangkok, Hb G-Coushatta, Hb Q-Thailand, Hb G-Honolulu, Hb Ube-2 and Hb G-Taipei. Variant II Turbo 2.0, Ultra2 and Cobas c501 showed good agreement with C2FP for most samples with variants. HLC-723 G8 yielded no HbA1c values for Hb J-Bangkok, Hb Q-Thailand and Hb G-Honolulu. Samples with Hb E, Hb G-Coushatta, Hb G-Taipei and Hb Ube-2 produced significant negative biases for HLC-723 G8. HA-8180V showed statistically significant differences for Hb E, Hb G-Coushatta, Hb G-Taipei, Hb Q-Thailand and Hb G-Honolulu. HA-8180V yielded no HbA1c values for Hb J-Bangkok. All methods showed good agreement for samples with Hb New York. Conclusions Some common hemoglobin variants can interfere with HbA1c determination by the most popular methods in China.

Effects of common hemoglobin variants on HbA1c measurements in China: results for α- and β-globin variants measured by six methods

Globally, the incidence of diabetes mellitus is rising at an alarming rate and has become a health crisis that threatens the economies of all nations. Therefore, diagnosing diabetes has become an important issue in the management of diabetes. Glycated hemoglobin (HbA1c) is now recommended as a means to diagnose diabetes, but its use still has limitations. In this article, the biology, measurement, standardization, and opportunities and challenges of the use of HbA1c to diagnose diabetes are reviewed. More specifically, its use in China and the Asian region is discussed in detail.

Standardising HbA1c-based diabetes diagnosis: opportunities and challenges.

Background Quantification of glycated hemoglobin (HbA1c) is a challenge in patients with hemoglobin (Hb) variants. We evaluated the impact of various Hb variants on five routine HbA1c assays by comparing with the IFCC reference measurement procedure (RMP). Methods Whole blood samples showing warning flags or no results on routine HPLC HbA1c assays were confirmed for Hb variants and were submitted to HbA1c quantification using Sebia Capillarys 2 Flex Piercing, Roche Tina-quant HbA1c Gen. 2, Bio-Rad Variant II Turbo 2.0, ADAMS HA-8180, Tosoh G8 standard mode, and IFCC RMP using LC-MS. Results Among 114 samples, the most common variants were Hb G-Coushatta (n=47), Queens (n=41), Ube-4 (n=11), Chad (n=4), Yamagata (n=4), G-His-Tsou (n=2), G-Taipei (n=1), Fort de France (n=1), Hoshida (n=1), and two novel variants (Hb α-globin, HBA 52 Gly>Cys and Hb β-globin, HBB 146 His>Asn). In terms of control samples, all the result of HbA1c were "acceptable", within the criteria of ±7% compared to IFCC RMP target values. However, percentage of "unacceptable" results of samples with Hb variants were 16% for Capillarys 2, 7% for Tina-quant, 51% for Variant II Turbo 2.0, 95% for G8 standard mode, and 89% for HA-8180. The Capillarys 2 and HA-8180 assay did not provide the results in 5 and 40 samples with Hb variants, respectively. Conclusions HbA1c results from five routine assays in patients with relatively common Hb variants in Korea showed various degrees of bias compared to those of IFCC RMP. Therefore, laboratories should be aware of the limitation of their methods with respect to interference from Hb variants found commonly in their local population and suggest an alternative HbA1c quantification method.

Hb variants in Korea: Effect on HbA1c using five routine methods

Objectives Hemoglobin (Hb) variant is one of the most common monogenic inherited disorders. We aimed to explore the prevalence and hematological and molecular characteristics of Hb variants in southern China. Methods We collected blood samples from all patients with suspected variants found during HbA1c measurement via a cation-exchange high-performance liquid chromatography system (Bio-Rad Variant II Turbo 2.0) or a capillary electrophoresis method (Sebia Capillarys). Hematological analysis, Sanger sequencing, and gap-PCR were performed for these samples. Results Among the 311,024 patients tested, we found 1,074 Hb variant carriers, including 823 identified using Capillarys and 251 using Variant II Turbo 2.0, with a total carrier rate of 0.35%. We discovered 117 types of Hb variants (52 HBB, 47 HBA, and 18 HBD mutations) containing 18 new mutations. The most common variant found was Hb E, followed by Hb New York, Hb J-Bangkok, Hb Q-Thailand, Hb G-Coushatta, Hb G-Honolulu, Hb G-Taipei, and Hb Broomhill. Most heterozygotes for the Hb variant exhibited normal hematological parameters. However, most patients with compound heterozygotes for the Hb variant and thalassemia showed varied degrees of microcytic hypochromic anemia. Conclusions The prevalence of hemoglobin variants remains high and exhibits genetic diversity and widespread distribution in the population of southern China.

Hemoglobin variants in southern China: results obtained during the measurement of glycated hemoglobin in a large population

Patients with gestational diabetes mellitus (GDM) need strict blood glucose control to reduce the incidence of perinatal complications in the mother or infant. The purpose of this study was to investigate whether the glycated hemoglobin (HbA1c) values of GDM patients were affected by β-thalassemia minor and to subsequently discuss the limitations of HbA1c monitoring for blood glucose control. 41 GDM patients with β-thalassemia minor were enrolled to serve as the study group. 93 GDM patients without thalassemia were randomly selected as a control group. Clinical data on the 134 mothers as well as their newborns were retrospectively analyzed. The blood glucose values of the participants at various times during the gestation period were compared between the groups, as were their HbA1c and ferritin levels and iron deficiency rates in late pregnancy (36–38 weeks of gestation). Pearson’s coefficient was calculated to determine the correlations between HbA1c and ferritin in both the study and control groups. The study and control groups did not show any significant differences in newborn birth weight, maternal age, maternal pre-pregnancy body mass index (BMI), gestational age, newborn sex, gravidity, and parity. The blood glucose values of the participants at different times during the gestation period also did not differ significantly between the study group and the control group. However, the late-pregnancy HbA1c level (5.23 ± 0.49%) and iron deficiency rate (12.19%) in the study group were significantly lower than those in the control group (5.42 ± 0.43% and 58.06%, respectively); P  < 0.05. Also, the late-pregnancy ferritin level in the study group (46.59 ± 18.03 ng/mL) was significantly higher than that in the control group (25.58 ± 11.42 ng/mL); P  < 0.05. In addition, a significant negative correlation was observed between HbA1c and ferritin in both the study group (R = − 0.459, P = 0.003) and the control group (R = − 0.358, P = 0.010). The HbA1c level is affected by many factors. Using serum HbA1c values to monitor blood glucose in GDM patients with β-thalassemia minor may lead to a mistaken assumption of low blood glucose levels, so HbA1c may not be a suitable indicator for monitoring blood glucose in pregnant women, particularly GDM patients with β-thalassemia minor.

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Investigating the Reliability of HbA1c Monitoring for Blood Glucose Control During Late Pregnancy in Patients with Gestational Diabetes Mellitus (GDM) with and without β-Thalassemia Minor.

Background HbA1c is a widely used biomarker for the management of diabetes mellitus and can be quantified from blood samples by using various methods, including ion-exchange high-performance liquid chromatography (HPLC), boronate affinity HPLC, and capillary electrophoresis (CE). Here, we evaluated the accuracy of four separation methods for determination of HbA1c values in Chinese patients with different hemoglobin disorders. Methods Blood samples from normal patients, patients with β-thalassemia, patients exhibiting heterozygosity, and patients exhibiting homozygosity were analyzed using ion-exchange HPLC (Variant II Turbo, Bio-Rad and Adams A1c HA-8160, Arkray, run in diabetes mode), boronate affinity HPLC (Ultra2, Trinity Biotech), and CE (Capillarys 2 Flex Piercing, Sebia). Results Samples from patients with β-thalassemia produced significant positive biases on the Variant II Turbo system compared to the other three systems. For heterozygous βA/βE patients, a good agreement was observed between Capillarys 2 Flex Piercing and Ultra2 systems, while a significant negative bias was observed between HA-8160 and Capillarys 2 Flex Piercing systems and between Variant II Turbo and Capillarys 2 Flex Piercing systems. For homozygous (βE/βE) patients, a clear context without HbA, all systems except the Capillarys 2 Flex Piercing system yielded random HbA1c results. Only the Capillarys 2 Flex Piercing system could detect all hemoglobin variants tested. Conclusions β-Thalassemia can cause errors in HbA1c determination using the Variant II Turbo system. HbE heterozygosity or HbE homozygosity also complicated HbA1c measurements. The Capillarys 2 Flex Piercing system detected all Hb variants and HbA1c in patients with β-thalassemia and could provide measurements with high accuracy.

Erroneous HbA1c measurements in the presence of β-thalassemia and common Chinese hemoglobin variants.

Background

α-Thalassemia is a benign condition that is often present in patients with diabetes mellitus Here, we evaluated the effects of different genotypes α-thalassemia on HbA1c measurement



Methods

A total of 189 samples from nondiabetic patients were analyzed HbA1c analysis was performed by ion-exchange high-performance liquid chromatography, boronate affinity HPLC, immunoassay, and capillary electrophoresis Fasting glucose, fructosamin, and HbA2 were also performed All samples were confirmed by genotyping for thalassemia



Results

In patients with two or three functional α-genes, HbA1c values were not significantly different from those of controls (P > 005); however, in individuals with α-thalassemia with one functional α-gene (ie, HbH disease), HbA1c levels were significantly different from those of controls (P 005)



Conclusions

In this study, HbA1c values in samples from individuals with two or three functional α-genes basically reflected the normal mean blood glucose level, while those in samples from individuals with one functional α-gene did not

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Effects of α-Thalassemia on HbA1c Measurement.

Background Evidence-based evaluation of laboratory performances including pre-analytical, analytical and post-analytical stages of the total testing process (TTP) is crucial to ensure patients receiving safe, efficient and effective care. To conduct risk assessment, quality management tools such as Failure Mode and Effect Analysis (FMEA) and the Failure Reporting and Corrective Action System (FRACAS) were constantly used for proactive or reactive analysis, respectively. However, FMEA and FRACAS faced big challenges in determining the scoring scales and failure prioritization in the assessment of real-world cases. Here, we developed a novel strategy, by incorporating Sigma metrics into risk assessment based on quality indicators (QIs) data, to provide a more objective assessment of risks in TTP. Methods QI data was collected for 1 year and FRACAS was applied to produce the risk rating based on three variables: (1) Sigma metrics for the frequency of defects; (2) possible consequence; (3) detection method. The risk priority number (RPN) of each QI was calculated by a 5-point scale score, where a value of RPN > 50 was rated as high-risk. Results The RPNs of two QIs in post-analytical phase (TAT of Stat biochemistry analyte and Timely critical values notification) were above 50 which required rigorous monitoring and corrective actions to eliminate the high risks. Nine QIs (RPNs between 25 and 50) required further investigation and monitoring. After 3 months of corrective action the two identified high-risk processes were successfully reduced. Conclusions The strategy can be implemented to reduce identified risk and assuring patient safety.

Risk assessment of the total testing process based on quality indicators with the Sigma metrics.

We read with interest the article by Li et al. (1). The authors reported a case with an extremely abnormal HbA1c value due to interference of a hemoglobin (Hb) variant. We agree with the authors regarding the necessity of visual inspection of chromatograms of HbA1c prior to reporting the results, especially in the scenario of discordance between HbA1c and other clinical findings. However, we believe some comments and suggestions for future investigation are important for exploring this issue.

Li et al. (1) should double-check their gene sequencing data, which were not included in the case report. We note that they identified a heterozygous mutation (c.242T>A, Leu81His) in …

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Yong Xia

Papers

Erroneous HbA1c measurements in the presence of β-thalassemia and common Chinese hemoglobin variants.

Effects of common hemoglobin variants on HbA1c measurements in China: results for α- and β-globin variants measured by six methods

Effects of α-Thalassemia on HbA1c Measurement.

Risk assessment of the total testing process based on quality indicators with the Sigma metrics.

Comment on Li et al. Visual Inspection of Chromatograms Assists Interpretation of HbA1c: A Case Report. Diabetes Care 2018;41:1829-1830.