Dataset Information

Evaluation of four hemoglobin separation analyzers for hemoglobinopathy diagnosis.

ABSTRACT:

Background

Four automated hemoglobin separation devices are compared in their ability to detect hemoglobinopathies, both in HbA1c and in hemoglobinopathy mode.

Methods

Quality control material and 58 samples, including one heterozygous ?-thalassemia sample, six heterozygote ?-thalassemia samples and 32 samples with a known hemoglobin variant, were used to assess imprecision of HbF and HbA2 measurements, correlation with the gold standard and sensitivity for detecting ?-thalassemia and Hb variants on D-100 (Bio-Rad Laboratories), HA 8180T (Menarini), HLC-723G8 (Tosoh Bioscience) and Capillarys 2 Flex Piercing (Sebia).

Results

Imprecision was <10% for both HbF and HbA2 in all modes of all analyzers. Correlation studies for HbF and HbA2 demonstrated statistically significant but small biases when compared to the gold standard. All six ?-thalassemia samples but one were detected on all analyzers using a HbA2 cut-off value of 3.5%. D-100, HA8180T and the Hb-pathy mode of the HLC-723G8 and the Capillarys are able to detect the most common important Hb variants (Hb C, D, E and S), but more seldom variants can be missed as they co-elute with HbA0. The HbA1c mode of the Capillarys correctly detected all measured hemoglobin variants and can therefore be used as a hemoglobinopathy screening device. This was also the case for the most common important Hb variants on the HbA1c mode of the HLC-723G8, but two rare variants were not detected.

Conclusion

This study stresses the importance for individual laboratories to know the advantages and drawbacks of their hemoglobin separation analyzer and its different modes in the diagnosis of hemoglobinopathies.

SUBMITTER: Degandt S

PROVIDER: S-EPMC6817248 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Publications

Evaluation of four hemoglobin separation analyzers for hemoglobinopathy diagnosis.

Degandt Simon S Coens Rémy R Cauwelier Barbara B Devos Helena H Langlois Michel M Emmerechts Jan J

Journal of clinical laboratory analysis 20170406 1

<h4>Background</h4>Four automated hemoglobin separation devices are compared in their ability to detect hemoglobinopathies, both in HbA1c and in hemoglobinopathy mode.<h4>Methods</h4>Quality control material and 58 samples, including one heterozygous α-thalassemia sample, six heterozygote β-thalassemia samples and 32 samples with a known hemoglobin variant, were used to assess imprecision of HbF and HbA2 measurements, correlation with the gold standard and sensitivity for detecting β-thalassemia ...[more]

PMID: 28383138

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Project description:BACKGROUND: Chronic hyperglycemia confers increased risk for long-term diabetes-associated complications and repeated hemoglobin A1c (HbA1c) measures are a widely used marker for glycemic control in diabetes treatment and follow-up. A recent genome-wide association study revealed four genetic loci, which were associated with HbA1c levels in adults with type 1 diabetes. We aimed to evaluate the effect of these loci on glycemic control in type 2 diabetes. METHODS: We genotyped 1,486 subjects with type 2 diabetes from a Norwegian population-based cohort (HUNT2) for single-nucleotide polymorphisms (SNPs) located near the BNC2, SORCS1, GSC and WDR72 loci. Through regression models, we examined their effects on HbA1c and non-fasting glucose levels individually and in a combined genetic score model. RESULTS: No significant associations with HbA1c or glucose levels were found for the SORCS1, BNC2, GSC or WDR72 variants (all P-values > 0.05). Although the observed effects were non-significant and of much smaller magnitude than previously reported in type 1 diabetes, the SORCS1 risk variant showed a direction consistent with increased HbA1c and glucose levels, with an observed effect of 0.11% (P = 0.13) and 0.13 mmol/l (P = 0.43) increase per risk allele for HbA1c and glucose, respectively. In contrast, the WDR72 risk variant showed a borderline association with reduced HbA1c levels (? = -0.21, P = 0.06), and direction consistent with decreased glucose levels (? = -0.29, P = 0.29). The allele count model gave no evidence for a relationship between increasing number of risk alleles and increasing HbA1c levels (? = 0.04, P = 0.38). CONCLUSIONS: The four recently reported SNPs affecting glycemic control in type 1 diabetes had no apparent effect on HbA1c in type 2 diabetes individually or by using a combined genetic score model. However, for the SORCS1 SNP, our findings do not rule out a possible relationship with HbA1c levels. Hence, further studies in other populations are needed to elucidate whether these novel sequence variants, especially rs1358030 near the SORCS1 locus, affect glycemic control in type 2 diabetes.

Dataset Information

Evaluation of four hemoglobin separation analyzers for hemoglobinopathy diagnosis.

Background

Methods

Results

Conclusion

Publications

Evaluation of four hemoglobin separation analyzers for hemoglobinopathy diagnosis.

Similar Datasets

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