HbA(1c) levels are genetically determined even in type 1 diabetes: evidence from healthy and diabetic twins

Association between the haemoglobin glycation index (HGI) and clinical outcomes in patients with acute decompensated heart failure

BACKGROUND

A growing number of studies show that people with similar blood glucose levels have different levels of glycosylated haemoglobin (HbA1c), and relying only on HbA1c may lead to clinical decision-making errors. The haemoglobin glycation index (HGI) quantifies the difference in HbA1c among individuals and is strongly linked to the risk of cardiovascular disease. However, the connection between this phenomenon and the poor outcomes of patients with acute decompensated heart failure (ADHF) is currently unknown.

PATIENTS AND METHODS

This retrospective, single-centre-based cohort study included 1531 hospitalized patients with ADHF from September 2010 to January 2020. The HGI is calculated from the difference between the observed and predicted HbA1c values [predicted HbA1c = 0.024 × fasting plasma glucose (FPG) (mg/dL)+3.1]. The endpoints examined in the study included all-cause death, cardiovascular (CV) death, and major adverse cardiac events (MACE). We fitted multivariable-adjusted Cox proportional hazard models to investigate the association between the HGI and clinical outcomes.

RESULTS

During the five-year follow-up, 427 (27.9%) patients died from all causes, 232 (15.6%) from CV death, and 848 (55.4%) from MACE. The restricted cubic spline analysis also showed that the cumulative risk of all-cause and CV deaths decreased linearly with increasing HGI. According to multivariate Cox proportional hazard models, the highest tertile of the HGI was associated with a lower incidence of all-cause and cardiovascular deaths [all-cause death, adjusted hazard ratio (HR): 0.720, 95% confidence interval (CI): 0.563-0.921, p = 0.009; CV death, adjusted HR: 0.619, 95% CI: 0.445-0.861, p = 0.004]. A 1% increase in the HGI was associated with a 12.5% reduction in the risk of all-cause death and a 20.8% reduction in the risk of CV death.

CONCLUSIONS

A high HGI was directly associated with a reduction in all-cause and CV deaths but was not associated with MACE. These findings may be helpful in the management of patients with ADHF.

Association of haemoglobin glycation index with all-cause and cardiovascular disease mortality in diabetic kidney disease: a cohort study

BACKGROUND

While the high haemoglobin glycation index (HGI) has been extensively investigated in diabetic populations, its impact on patients with diabetic kidney disease (DKD) remains unclear.

METHODS

We examined data from the National Health and Nutrition Examination Surveys (NHANES) conducted between 1999 and 2018. HGI was determined using the formula recommended by Hempe et al., which calculates the difference between measured and predicted HbA1c. Predicted HbA1c was derived from the equation: 0.024 FPG + 3.1. National death index records up to December 31, 2019, were utilized to assess mortality outcomes. To estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for both all-cause and cardiovascular disease (CVD) mortality, we utilized Cox proportional hazard models. A restricted cubic spline analysis was performed to explore the potential nonlinear relationship between HGI levels and mortality.

RESULTS

Our cohort study comprised data from 1,057 participants with DKD (mean [SE] age, 61.61 [0.57] years; 48.24% female). The mean HGI level was 0.44 (SE 0.04). Over a median follow-up period of 6.67 years, we observed 381 deaths, including 140 due to CVD. Compared with participants in the second tertile of HGI levels (0.03-0.74), those in the lowest tertile of HGI (-5.29-0.02) exhibited an all-cause mortality hazard ratio of 1.39 (95% CI, 1.02-1.88) and a CVD mortality hazard ratio of 1.10 (95% CI, 0.67-1.81). Conversely, participants in the highest tertile (0.75-9.60) demonstrated an all-cause mortality hazard ratio of 1.48 (95% CI, 1.05-2.08) and a CVD mortality hazard ratio of 2.06 (95% CI, 1.13-3.77) after further adjusting for HbA1c and other important variables. Additionally, a restricted cubic spline analysis revealed a U-shaped relationship between HGI and all-cause mortality (P < 0.001 for nonlinearity) and a J-shaped relationship between HGI and CVD mortality (P = 0.044 for nonlinearity).

CONCLUSIONS

Our cohort study suggests that HGI in DKD populations exhibits a U-shaped association with all-cause mortality and a J-shaped association with CVD mortality, independent of HbA1c levels.

The Association of High and Low Glycation With Incident Diabetic Retinopathy in Adults With Type 1 Diabetes

BACKGROUND

We investigated the risk of incident diabetic retinopathy (DR) among high glycator compared to low glycator patients based on the hemoglobin glycation index (HGI). Visit-to-visit variations in HGI also were assessed.

METHODS

Glycated hemoglobin (HbA1c) and continuous glucose monitoring data were collected up to 7 years prior to the date of eye examination defining incident DR or no retinopathy (control). Hemoglobin glycation index was calculated as difference in measured HbA1c and an estimated A1c from sensor glucose (eA1c) to define high (HbA1c - eA1c >0%) or low (HbA1c - eA1c <0%) glycator. Stable glycators were defined as ≥75% of visits with same HGI category. Logistic regression was used to assess the association between glycation category and incident DR.

RESULTS

Of 119 adults with type 1 diabetes (T1D), 49 (41%) were stable low glycator (HbA1c - eA1c <0%), 36 (30%) were stable high glycator (HbA1c - eA1c >0%), and 34 (29%) were unstable glycator. Using alternate criteria to define high vs low glycator (consistent difference in HbA1c - eA1c of > 0.4% or <0.4%, respectively), 53% of the adults were characterized as unstable glycator. Compared to low glycators, high glycators did not have a significantly higher risk for incident DR over time when adjusted for age, T1D duration and continuous glucose monitoring (CGM) sensor type (odds ratio [OR] = 1.31, 95% confidence interval [CI] = 0.48-3.62, P = .15).

CONCLUSIONS

The risk of diabetic retinopathy was not found to differ significantly comparing high glycators to low glycators in adults with T1D. Moreover, HbA1c - eA1c relationship was not stable in nearly 30% to 50% adults with T1D, suggesting that discordance in HbA1c and eA1c are mostly related either HbA1c measurements or estimation of A1c from sensor glucose rather than physiological reasons.

Lower-than-normal glycemic levels to achieve optimal reduction of diabetes risk among individuals with prediabetes: A prospective cohort study

AIMS/HYPOTHESIS

To determine whether lower than currently accepted glycemic levels could lead to optimal risk reduction of incident diabetes among individuals with prediabetes.

METHODS

We enrolled 9903 individuals with prediabetes and 16,902 individuals with normoglycemia from a prospective cohort participating health check-ups between 2006 and 2017. While classifying fasting glucose into <5.0, 5.0-5.5, and 5.6-6.9 mmol/L and postprandial glucose into <6.7, 6.7-7.7, and 7.8-11.0 mmol/L, we grouped fasting/postprandial glucose into five categories (<5.0/<6.7, <5.0/6.7-7.7, 5.0-5.5/<6.7, 5.0-5.5/6.7-7.7 mmol/L, 5.6-6.9/7.8-11.0 mmol/L). The primary outcome was incident diabetes.

RESULTS

In individuals with prediabetes, the presence of a baseline fasting glucose <5.0 mmol/L or a postprandial glucose <6.7 mmol/L led to a greater risk reduction of incident diabetes with hazard ratios of 0.34 (95% confidence interval, 0.27-0.42) and 0.47 (0.41-0.54), respectively, relative to a fasting glucose 5.6-6.9 mmol/L and a postprandial glucose 7.8-11.0 mmol/L. For individuals with prediabetes having fasting/postprandial glucose <5.0/<6.7 mmol/L, the incidence of 6.4 (4.7-8.8) per 1000 person-years corresponded to that of 5.8 (4.2-8.0) per 1000 person-years for individuals with normoglycemia having 5.0-5.5/6.7-7.7 mmol/L.

CONCLUSIONS/INTERPRETATION

Given that lower-than-normal glycemic levels were plausible for optimal risk reduction of diabetes, stringent glycemic management could be beneficial for diabetes prevention among individuals with prediabetes.

Variation in the hemoglobin glycation index

A high hemoglobin glycation index (HGI) has been repeatedly associated with greater risk for hypoglycemia in people with diabetes and greater risk for chronic vascular disease in people with or without diabetes. This review explores how different sources of analytical and biological variation in HbA1c and blood glucose individually and collectively affect the clinical information value of HGI. We conclude that HGI is a complex quantitative trait that is a clinically practical biomarker of risk for both hypoglycemia and chronic vascular disease.

Advanced Glycation End-Products (AGEs) of Lysine and Effects of Anti-TCR/Anti-TNF-α Antibody-Based Therapy in the LEW.1AR1-iddm Rat, an Animal Model of Human Type 1 Diabetes

The LEW.1AR1-iddm rat is an animal model of human type 1 diabetes (T1D). Previously, we have shown that combination with anti-TCR/anti-TNF-α antibody-based therapy re-established normoglycemia and increased proteinic arginine-dimethylation in the spleen, yet not in the pancreas. High blood glucose is often associated with elevated formation of advanced glycation end-products (AGEs) which act via their receptor (RAGE). Both anti-TCR and anti-TNF-α are inhibitors of RAGE. The aim of the present work was to investigate potential biochemical changes of anti-TCR/anti-TNF-α therapy in the LEW.1AR1-iddm rat. We determined by stable-isotope dilution gas chromatography-mass spectrometry (GC-MS) the content of free and proteinic AGEs and the N^ε-monomethylation of lysine (Lys) residues in proteins of pancreas, kidney, liver, spleen and lymph nodes of normoglycemic control (ngCo, n = 6), acute diabetic (acT1D, n = 6), chronic diabetic (chT1D, n = 4), and cured (cuT1D, n = 4) rats after anti-TCR/anti-TNF-α therapy. Analyzed biomarkers included Lys and its metabolites N^ε-carboxymethyl lysine (CML), furosine and N^ε-monomethyl lysine (MML). Other amino acids were also determined. Statistical methods including ANOVA, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to evaluate the effects. Most statistical differences between the study groups were observed for spleen, pancreas and kidney, with liver and lymph nodes showing no such differences. In the pancreas, the groups differed with respect to proteinic furosine (p = 0.0289) and free CML (p = 0.0023). In the kidneys, the groups differed with respect to proteinic furosine (p = 0.0076) and CML (p = 0.0270). In the spleen, group differences were found for proteinic furosine (p = 0.0114) and free furosine (p = 0.0368), as well as for proteinic CML (p = 0.0502) and proteinic MML (p = 0.0191). The acT1D rats had lower furosine, CML and MML levels in the spleen than the rats in all other groups. This observation corresponds to the lower citrullination levels previously measured in these rats. PCA revealed diametric associations between PC1 and PC2 for spleen (r = −0.8271, p < 0.0001) compared to pancreas (r = 0.5805, p = 0.0073) and kidney (r = 0.8692, p < 0.0001). These findings underscore the importance of the spleen in this animal model of human T1D. OPLS-DA showed that in total sixteen amino acids differed in the experimental groups.

Hemoglobin glycation index, calculated from a single fasting glucose value, as a prediction tool for severe hypoglycemia and major adverse cardiovascular events in DEVOTE

INTRODUCTION

Hemoglobin glycation index (HGI) is the difference between observed and predicted glycated hemoglobin A1c (HbA1c), derived from mean or fasting plasma glucose (FPG). In this secondary, exploratory analysis of data from DEVOTE, we examined: whether insulin initiation/titration affected the HGI; the relationship between baseline HGI tertile and cardiovascular and hypoglycemia risk; and the relative strengths of HGI and HbA1c in predicting these risks.

RESEARCH DESIGN AND METHODS

In DEVOTE, a randomized, double-blind, cardiovascular outcomes trial, people with type 2 diabetes received once per day insulin degludec or insulin glargine 100 units/mL. The primary outcome was time to first occurrence of a major adverse cardiovascular event (MACE), comprising cardiovascular death, myocardial infarction or stroke; severe hypoglycemia was a secondary outcome. In these analyses, predicted HbA1c was calculated using a linear regression equation based on DEVOTE data (HbA1c=0.01313 FPG (mg/dL) (single value)+6.17514), and the population data were grouped into HGI tertiles based on the calculated HGI values. The distributions of time to first event were compared using Kaplan-Meier curves; HRs and 95% CIs were determined by Cox regression models comparing risk of MACE and severe hypoglycemia between tertiles.

RESULTS

Changes in HGI were observed at 12 months after insulin initiation and stabilized by 24 months for the whole cohort and insulin-naive patients. There were significant differences in MACE risk between baseline HGI tertiles; participants with high HGI were at highest risk (low vs high, HR: 0.73 (0.61 to 0.87)95% CI; moderate vs high, HR: 0.67 (0.56 to 0.81)95% CI; p<0.0001). No significant differences between HGI tertiles were observed in the risk of severe hypoglycemia (p=0.0911). With HbA1c included within the model, HGI no longer significantly predicted MACE.

CONCLUSIONS

High HGI was associated with a higher risk of MACE; this finding is of uncertain significance given the association of HGI with insulin initiation and HbA1c.

TRIAL REGISTRATION NUMBER

NCT01959529.

Protein glycation - biomarkers of metabolic dysfunction and early-stage decline in health in the era of precision medicine

Protein glycation provides a biomarker in widespread clinical use, glycated hemoglobin HbA1c (A1C). It is a biomarker for diagnosis of diabetes and prediabetes and of medium-term glycemic control in patients with established diabetes. A1C is an early-stage glycation adduct of hemoglobin with glucose; a fructosamine derivative. Glucose is an amino group-directed glycating agent, modifying N-terminal and lysine sidechain amino groups. A similar fructosamine derivative of serum albumin, glycated albumin (GA), finds use as a biomarker of glycemic control, particularly where there is interference in use of A1C. Later stage adducts, advanced glycation endproducts (AGEs), are formed by the degradation of fructosamines and by the reaction of reactive dicarbonyl metabolites, such as methylglyoxal. Dicarbonyls are arginine-directed glycating agents forming mainly hydroimidazolone AGEs. Glucosepane and pentosidine, an intense fluorophore, are AGE covalent crosslinks. Cellular proteolysis of glycated proteins forms glycated amino acids, which are released into plasma and excreted in urine. Development of diagnostic algorithms by artificial intelligence machine learning is enhancing the applications of glycation biomarkers. Investigational glycation biomarkers are in development for: (i) healthy aging; (ii) risk prediction of vascular complications of diabetes; (iii) diagnosis of autism; and (iv) diagnosis and classification of early-stage arthritis. Protein glycation biomarkers are influenced by heritability, aging, decline in metabolic, vascular, renal and skeletal health, and other factors. They are applicable to populations of differing ethnicities, bridging the gap between genotype and phenotype. They are thereby likely to find continued and expanding clinical use, including in the current era of developing precision medicine, reporting on multiple pathogenic processes and supporting a precision medicine approach.

The trials and tribulations of determining HbA1c targets for diabetes mellitus

Glycated haemoglobin (HbA_1c) is considered the gold standard for predicting glycaemia-associated risks for the microvascular and macrovascular complications of diabetes mellitus over 5-10 years. The value of HbA_1c in the care of patients with type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) is unassailable, yet HbA_1c targets remain contentious. Guidelines from diabetes care organizations recommend conflicting HbA_1c targets - generally between 6.5% and 8%. However, all such organizations advocate for individualization of HbA_1c targets, leaving both health-care providers and their patients confused about what HbA_1c target is appropriate in an individual patient. In this Review, we outline the landmark T1DM and T2DM trials that informed the current guidelines, we discuss the evidence that drives individualized HbA_1c targets, we examine the limitations of HbA_1c, and we consider alternatives for monitoring glycaemic control. Ultimately, in synthesizing this literature, we argue for an HbA_1c target of <7% for most individuals, but emphasize the importance of helping patients determine their own personal goals and determinants of quality of life that are independent of a particular glycaemic target. We also recognize that as newer technologies and anti-hyperglycaemic therapies emerge, glycaemic targets will continue to evolve.

The Sickle Effect: The Silent Titan Affecting Glycated Hemoglobin Reliability

Hemoglobin A1c (HbA1c) is a popular invaluable tool in the diagnosis of Type 2 diabetes for red blood cells (RBCs) with a lifespan of 120 days; however, many factors, including hemoglobinopathies, affect its accuracy. Sickle cell trait, primarily a benign medical condition, is a point mutation in only one of two beta-globin genes on chromosome 11. We performed a traditional review to identify how the sickle cell trait (SCT) affects the interpretation of HbA1c and the further implications it may have on the diagnosis and management of Type 2 diabetes. A literature search was performed using PubMed®/MEDLINE® and Google Scholar with formulated keywords (sickle cell trait, HbAS, HbA1c, glycosylated hemoglobin, diabetes, RBC lifespan, race, and genetics), with the majority of results being mainly observational studies. The National Glycohemoglobin Standardization Program (NGSP) is responsible for standardizing HbA1c results and also highlights factors that can interfere with HbA1c, including hemoglobin variants. Studies that utilize only an NGSP-certified method with no clinically significant interference by HbS in patients with and without SCT showed contrasting results. Additional studies showed that persons of African ancestry, the group to which the majority of SCT patients belong, have a higher HbA1c than non-Hispanic whites (NHWs), just based on race, and a greater probability of having glucose-6-phosphate dehydrogenase (G6PD) deficiency, which lowers HbA1c. The most extensive study investigating the RBC lifespan in SCT patients showed a reduction in the cell lifespan compared to normal patients; however, other smaller studies were contradictory. Our study highlights the need for hemoglobinopathy detection before or during HbA1c measurement in populations with a high degree of African ancestry and the importance of patient notification. It also shows that SCT affects the accuracy of HbA1c, through its likely reduction of RBC lifespan and its increased association with African ancestry and G6PD deficiency. This review recommends that for SCT patients with potential Type 2 diabetes, HbA1c should be used in combination with another diagnostic tool such as fasting blood glucose, fructosamine, or glycated albumin to decrease the chances of a missed diagnosis.

Heritability and genome-wide association analyses of fasting plasma glucose in Chinese adult twins

Background

Currently, diabetes has become one of the leading causes of death worldwide. Fasting plasma glucose (FPG) levels that are higher than optimal, even if below the diagnostic threshold of diabetes, can also lead to increased morbidity and mortality. Here we intend to study the magnitude of the genetic influence on FPG variation by conducting structural equation modelling analysis and to further identify specific genetic variants potentially related to FPG levels by performing a genome-wide association study (GWAS) in Chinese twins.

Results

The final sample included 382 twin pairs: 139 dizygotic (DZ) pairs and 243 monozygotic (MZ) pairs. The DZ twin correlation for the FPG level (r_DZ = 0.20, 95% CI: 0.04–0.36) was much lower than half that of the MZ twin correlation (r_MZ = 0.68, 95% CI: 0.62–0.74). For the variation in FPG level, the AE model was the better fitting model, with additive genetic parameters (A) accounting for 67.66% (95% CI: 60.50–73.62%) and unique environmental or residual parameters (E) accounting for 32.34% (95% CI: 26.38–39.55%), respectively. In the GWAS, although no genetic variants reached the genome-wide significance level (P < 5 × 10^− 8), 28 SNPs exceeded the level of a suggestive association (P < 1 × 10^− 5). One promising genetic region (2q33.1) around rs10931893 (P = 1.53 × 10^− 7) was found. After imputing untyped SNPs, we found that rs60106404 (P = 2.38 × 10^− 8) located at SPATS2L reached the genome-wide significance level, and 216 SNPs exceeded the level of a suggestive association. We found 1007 genes nominally associated with the FPG level (P < 0.05), including SPATS2L, KCNK5, ADCY5, PCSK1, PTPRA, and SLC26A11. Moreover, C1orf74 (P = 0.014) and SLC26A11 (P = 0.021) were differentially expressed between patients with impaired fasting glucose and healthy controls. Some important enriched biological pathways, such as β-alanine metabolism, regulation of insulin secretion, glucagon signaling in metabolic regulation, IL-1 receptor pathway, signaling by platelet derived growth factor, cysteine and methionine metabolism pathway, were identified.

Conclusions

The FPG level is highly heritable in the Chinese population, and genetic variants are significantly involved in regulatory domains, functional genes and biological pathways that mediate FPG levels. This study provides important clues for further elucidating the molecular mechanism of glucose homeostasis and discovering new diagnostic biomarkers and therapeutic targets for diabetes.

Limited Agreement between Classifications of Diabetes and Prediabetes Resulting from the OGTT, Hemoglobin A1c, and Fasting Glucose Tests in 7412 U.S. Adults

This investigation was designed to determine the degree of concordance resulting from tests of fasting plasma glucose (FPG) and hemoglobin A1c (A1c) compared to the oral glucose tolerance test (OGTT) for detecting prediabetes and diabetes in undiagnosed adults. Another objective was to measure concordance within subsamples of women and men, and within three age groups. Lastly, the value of combining the FPG and A1c for detecting diabetes was compared to the OGTT. A total of 7412 randomly selected adults from the National Health and Nutrition Examination Survey (NHANES) were included. With outcomes classified as normal, prediabetes, or diabetes, according to standard guidelines, overall test agreements were low. With an OGTT diagnosis of diabetes, concordance was only 34% for the A1c assessment and 44% for the FPG assay. Delimited to older adults, agreement between the OGTT and A1c was only 25%, and between the OGTT and FPG, concordance was only 33.5%. Given the large percentage of discordant results associated with the FPG and A1c, clinicians should be cautious about employing these tests as lone assessments. Using both the FPG and A1c helped with accurately diagnosing diabetes and normal glycemia, but not prediabetes. The OGTT is a good choice to reduce misdiagnosis.

Limited Agreement between Classifications of Diabetes and Prediabetes Resulting from the OGTT, Hemoglobin A1c, and Fasting Glucose Tests in 7412 U.S. Adults

This investigation was designed to determine the degree of concordance resulting from tests of fasting plasma glucose (FPG) and hemoglobin A1c (A1c) compared to the oral glucose tolerance test (OGTT) for detecting prediabetes and diabetes in undiagnosed adults. Another objective was to measure concordance within subsamples of women and men, and within three age groups. Lastly, the value of combining the FPG and A1c for detecting diabetes was compared to the OGTT. A total of 7412 randomly selected adults from the National Health and Nutrition Examination Survey (NHANES) were included. With outcomes classified as normal, prediabetes, or diabetes, according to standard guidelines, overall test agreements were low. With an OGTT diagnosis of diabetes, concordance was only 34% for the A1c assessment and 44% for the FPG assay. Delimited to older adults, agreement between the OGTT and A1c was only 25%, and between the OGTT and FPG, concordance was only 33.5%. Given the large percentage of discordant results associated with the FPG and A1c, clinicians should be cautious about employing these tests as lone assessments. Using both the FPG and A1c helped with accurately diagnosing diabetes and normal glycemia, but not prediabetes. The OGTT is a good choice to reduce misdiagnosis.

Limited Agreement between Classifications of Diabetes and Prediabetes Resulting from the OGTT, Hemoglobin A1c, and Fasting Glucose Tests in 7412 U.S. Adults

This investigation was designed to determine the degree of concordance resulting from tests of fasting plasma glucose (FPG) and hemoglobin A1c (A1c) compared to the oral glucose tolerance test (OGTT) for detecting prediabetes and diabetes in undiagnosed adults. Another objective was to measure concordance within subsamples of women and men, and within three age groups. Lastly, the value of combining the FPG and A1c for detecting diabetes was compared to the OGTT. A total of 7412 randomly selected adults from the National Health and Nutrition Examination Survey (NHANES) were included. With outcomes classified as normal, prediabetes, or diabetes, according to standard guidelines, overall test agreements were low. With an OGTT diagnosis of diabetes, concordance was only 34% for the A1c assessment and 44% for the FPG assay. Delimited to older adults, agreement between the OGTT and A1c was only 25%, and between the OGTT and FPG, concordance was only 33.5%. Given the large percentage of discordant results associated with the FPG and A1c, clinicians should be cautious about employing these tests as lone assessments. Using both the FPG and A1c helped with accurately diagnosing diabetes and normal glycemia, but not prediabetes. The OGTT is a good choice to reduce misdiagnosis.

"Mind the gap please…": estimated vs. measured A1c from continuous measurement of interstitial glucose over a 3-month period in patients with type 1 diabetes

Introduction: Glycated hemoglobin (A_1c) is the measurement of choice to estimate the glycemic exposure over the last 3 months prior to sampling. The Free Style Libre® is a continuous glucose monitoring device which provides an estimated A_1c (eA1c) from average interstitial glucose using Nathan's ADAG equation. The objective of this study was to compare eA1c and A_1c in type 1 diabetes patients (T1D) over a period of 3 months.Materials and methods: Data were collected from patient charts between July 2016 and October 2017. 3-months recordings with >70% of data available were analyzed. eA1c was recorded at each visit and the corresponding A_1c value measured by high performance liquid chromatography in a single reference lab.Results: A total of 344 reports from 170 T1D were studied, 3 categories were identified: eA1c = A_1c: 13% of reports. eA1c > A_1c: 57% of reports, positive difference (eA1c - A_1c) of +0.74 ± 0.5% (P < 0.0001). eA1c < A_1c: 30% of reports, negative difference (eA1c - A_1c) of -0.5 ± 0.3% (P < 0.0001).Conclusion: eA1c value was generally overestimated compared to measured A_1c in this T1D cohort. This lesser concordance may result from differences in measured glucose source and/or frequency to calculate eA1c compared to ADAG, but also from using the reverse equation which is a source of potential bias. Another explanation could be a different rate of hypoglycemia between groups, or an asymmetric distribution of A1c patients' phenotypes with differential hyper- or hypoglycation intrinsic propensity.

Heritability analysis of nontraditional glycemic biomarkers in the Atherosclerosis Risk in Communities Study

Nontraditional glycemic biomarkers, including fructosamine, glycated albumin, and 1,5-anhydroglucitol (1,5-AG) are potential alternatives or complement to traditional measures of hyperglycemia. Genetic variants are associated with these biomarkers, but the heritability, or extent to which genetics control their variation, is not known. We estimated pedigree-based, SNP-based, and bivariate heritabilities for traditional glycemic biomarkers (fasting glucose, HbA1c), and nontraditional biomarkers (fructosamine, glycated albumin, 1,5-AG) among white participants in the Atherosclerosis Risk in Communities (ARIC) Study (N = 400 first-degree relatives from sibships, N = 5,575 unrelated individuals). Pedigree-based heritabilities (representing heritability from the entire genome) for nontraditional biomarkers were substantial (0.44-0.55) and comparable to HbA1c (0.34); the fasting glucose estimate was nonsignificant. SNP-based heritabilities (representing heritability from common variants) were lower than pedigree-based heritabilities for all biomarkers. Bivariate heritabilities showed shared genetics between fructosamine and glycated albumin (0.46 pedigree-based, 1.00 SNP-based) and glycated albumin and 1,5-AG (0.50 pedigree-based, 0.47 SNP-based). Genetic factors contribute to a considerable proportion of the variance of fructosamine, glycated albumin, and 1,5-AG and a portion of this heritability likely comes from common variants.

Using the Novel Approach of an Artificial Pancreas to Manage Type 1 Diabetes Mellitus in Pregnancy

Recent National Institute for Health and Care Excellence (NICE) guidelines suggest that insulin pump therapy should be used in pregnant women with Type 1 diabetes mellitus (T1DM) who do not achieve optimal glycaemic control with multiple daily injection (MDI) therapy. Furthermore, a landmark trial has confirmed that prospective continuous glucose monitoring (CGM) may be beneficial for women using both MDI and insulin pumps during pregnancy, with positive effects on neonatal outcomes. More recently, overnight use of an artificial pancreas (AP) with a model-predictive control algorithm has been shown to improve the amount of time women spend within the overnight glucose target range (3.5–7.8 mmol/L) during pregnancy. However, preliminary studies where the AP is used day and night have shown a high degree of interindividual variability in response to the intervention, and further randomised trials are needed to understand which women are suitable candidates for CGM, insulin pump, and AP technology. It is understood that improvements in maternal glycaemic control can minimise the risk of adverse neonatal outcomes. Given the substantial improvements in glycaemic control with AP use outside of pregnancy, the recent advances in AP technology provide hope that AP systems will improve the effectiveness of continuous subcutaneous insulin infusion and CGM during pregnancy. Further research is needed to evaluate whether AP can optimise glucose control and neonatal outcomes in T1DM pregnancy. This paper will discuss emerging technologies available for the management of T1DM in pregnancy.

Diagnostic Accuracy of Glycated Haemoglobin and Average Glucose Values in Type 2 Diabetes Mellitus Treated with Premixed Insulin

INTRODUCTION

Studies assessing the relationship between glycated haemoglobin (HbA1c) and average blood glucose (ABG) were conducted in small groups of patients on different treatments and may be biased for these reasons. The aim of the study was to assess the relationship between HbA1c and ABG in a large group of type 2 diabetes patients treated with premix insulin.

METHODS

In 4257 patients treated with premixed insulin, the parallel point-of-care assessment of HbA1c and ABG from the preceding 90 days (ABG90), calculated automatically from all values measured by the glucometer, was performed twice. The regression formulas and respective values of HbA1c and ABG90 were calculated.

RESULTS

The mean number of recorded glucose values/patient was 2.37 estimations per day. The regression formula calculated using data from the first assessment was HbA1c = 5.28 + 0.01487 × ABG90 and that using data from the second one was HbA1c = 4.78 + 0.01683 × ABG90. The slopes of the regression lines are lower than that in a similar analysis from the A1c-Derived Average Glucose (ADAG) study. The comparison of ADAG formula and the formula derived from the present study shows that both formulas give similar results at low HbA1c values, but differ at higher HbA1c values. Additionally, the 95% confidence interval is broader in the PROGENS study e.g. a 95% probability of certainty that the actual HbA1c value was greater than 7.0% (53 mmol/mol) was achieved only at an ABG90 value of 220 mg/dL.

CONCLUSION

The relationship between HbA1c and ABG estimations may be different in various patients; therefore, it seems that the use of one equation in all populations may not be reliable. Broad assessment of ABG as a tool that may replace HbA1c measurements should be recommended only with caution, providing the possible limitations and confidence intervals.

FUNDING

Bioton S.A.

Genetic Determinants of Glycated Hemoglobin in Type 1 Diabetes

Glycated hemoglobin (HbA_1c) is an important measure of glycemia in diabetes. HbA_1c is influenced by environmental and genetic factors both in people with and in people without diabetes. We performed a genome-wide association study (GWAS) for HbA_1c in a Finnish type 1 diabetes (T1D) cohort, FinnDiane. Top results were examined for replication in T1D cohorts DCCT/EDIC, WESDR, CACTI, EDC, and RASS, and a meta-analysis was performed. Three SNPs in high linkage disequilibrium on chromosome 13 near relaxin family peptide receptor 2 (RXFP2) were associated with HbA_1c in FinnDiane at genome-wide significance (P < 5 × 10^-8). The minor alleles of rs2085277 and rs1360072 were associated with higher HbA_1c also in the meta-analysis with RASS (P < 5 × 10^-8), where these variants had minor allele frequencies ≥1%. Furthermore, these SNPs were associated with HbA_1c in an East Asian population without diabetes (P ≤ 0.013). A weighted genetic risk score created from 55 HbA_1c-associated variants from the literature was associated with HbA_1c in FinnDiane but explained only a small amount of variation. Understanding the genetic basis of glycemic control and HbA_1c may lead to better prevention of diabetes complications.

Association of characteristics of people with type 2 diabetes mellitus with discordant values of fasting glucose and HbA1c

BACKGROUND

Primary care physicians frequently encounter people with type 2 diabetes mellitus (T2DM) with discordant values for fasting glucose and HbA1c. The aim of this study was to identify the prevalence and characteristics of people in whom blood glucose and HbA1c did not match.

METHODS

Overall, 64 553 people with T2DM from 939 general or internal medicine practices (Disease Analyzer database, Germany; January 2013-December 2015) were analyzed. Multivariable logistic regression models were used to identify associations between baseline clinical characteristics, comorbidity, and glucose-lowering treatment and discordance of fasting glucose and HbA1c values measured at the same visit.

RESULTS

Overall, 8582 (13%) patients had fasting glucose ≥140 mg/dL and HbA1c <7% (<53 mmol/mol), and 6508 (10%) had HbA1c ≥7% (≥53 mmol/mol) and fasting glucose <140 mg/dL. Using patients with both fasting glucose <140 mg/dL and HbA1c <7% as the reference (n = 31 834; 49%), solitary high fasting glucose values (and HbA1c <7%) were positively associated with higher age, male sex, longer diabetes duration, obesity, liver disease, low estimated glomerular filtration rate (eGFR), and glucose-lowering treatment. High HbA1c (and fasting glucose <140 mg/dL) was positively related to longer diabetes duration, obesity, neuropathy, retinopathy, low eGFR, and insulin treatment. There were lower odds of having solitary increased HbA1c ≥7% (fasting glucose <140 mg/dL) with higher age, hypertension, depression, and the number of diabetes patients (>200) per practice.

CONCLUSIONS

A considerable number of people with T2DM in primary care practices have discordant fasting blood glucose and HbA1c values. People who have discordant glycemic values have different characteristics.

Relative contributions of preprandial and postprandial glucose exposures, glycemic variability, and non-glycemic factors to HbA 1c in individuals with and without diabetes

BACKGROUND/OBJECTIVE

There is substantial interest in dietary approaches to reducing postprandial glucose (PPG) responses, but the quantitative contribution of PPG to longer-term glycemic control (reflected in glycated hemoglobin, HbA_1c) in the general population is not known. This study quantified the associations of preprandial glucose exposure, PPG exposure, and glycemic variability with HbA_1c and estimated the explained variance in HbA_1c in individuals with and without type 2 diabetes (T2D).

SUBJECTS/METHODS

Participants in the A1c-Derived Average Glucose (ADAG) study without T2D (n = 77) or with non-insulin-treated T2D and HbA_1c<6.5% (T2D_{HbA1c < 6.5%}, n = 63) or HbA_1c ≥ 6.5% (T2D_{HbA1c ≥ 6.5%}, n = 34) were included in this analysis. Indices of preprandial glucose, PPG, and glycemic variability were calculated from continuous glucose monitoring during four periods over 12 weeks prior to HbA_1c measurement. In linear regression models, we estimated the associations of the glycemic exposures with HbA_1c and calculated the proportion of variance in HbA_1c explained by glycemic and non-glycemic factors (age, sex, body mass index, and ethnicity).

RESULTS

The factors in the analysis explained 35% of the variance in HbA_1c in non-diabetic individuals, 49% in T2D_{HbA1c < 6.5%}, and 78% in T2D_{HbA1c ≥ 6.5%}. In non-diabetic individuals PPG exposure was associated with HbA_1c in confounder-adjusted analyses (P < 0.05). In the T2D_{HbA1c < 6.5%} group, all glycemic measures were associated with HbA_1c (P < 0.05); preprandial glucose and PPG accounted for 14 and 18%, respectively, of the explained variation. In T2D_{HbA1c ≥ 6.5%}, these glycemic exposures accounted for more than 50% of the variation in HbA_1c and with equal relative contributions.

CONCLUSIONS

Among the glycemic exposures, PPG exposure was most strongly predictive of HbA_1c in non-diabetic individuals, suggesting that interventions targeting lowering of the PPG response may be beneficial for long-term glycemic maintenance. In T2D, preprandial glucose and PPG exposure contributed equally to HbA_1c.

Translating the HbA1c assay into estimated average glucose values in children and adolescents with type 1 diabetes mellitus

OBJECTIVE

The A1c assay, expressed as the percent of hemoglobin that is glycated, measures chronic glycemia and is widely used to judge the adequacy of diabetes treatment and adjust therapy. Day-to-day management is guided by self-monitoring of capillary glucose concentrations (milligrams per decilitre or millimoles per litter) as well as by using continuous glucose monitoring systems (CGMS). We found a mathematical relationship between A1c and average glucose (AG) levels measured by CGMS over 5 days and determined the correlation between the variable CGMS parameters and HbA1c in 50 children with type 1 diabetes mellitus (DM-1) on MDI therapy.

RESEARCH DESIGN AND METHODS

A total of 50 diabetic children randomly selected from a cohort of children with DM-1 were included in the analyses. A1c levels obtained at the end of 3 months and measured in a central laboratory were compared with the AG levels during the previous 5 days recorded by CGMS. AG was calculated by combining weighted results from 5 days of continuous glucose monitoring performed before measuring HbA1c, with 3-5 point daily self-monitoring of capillary (fingerstick) glucose.

RESULTS

Linear regression analysis between the A1c and AG values provided the tightest correlations HbA1c=0.0494 MG- 2E-14, R2=0.90, P<0.0001), allowing calculation of an estimated average glucose (eAG) for A1c values.

CONCLUSIONS

Our study showed a linear relationship between HbA1C and AG values measured by CGMS for 5 days before HbA1c measurement. The AG can be easily calculated using a formula derived from linear regression analysis of HbA1c data obtained in our diabetic children.

Limited benefit of haemoglobin glycation index as risk factor for cardiovascular disease in type 2 diabetes patients

BACKGROUND

The haemoglobin glycation index (HGI) has been proposed as a marker of interindividual differences in haemoglobin glycosylation. Previous studies have shown a relationship between high HGI and risk of cardiovascular disease (CVD) in patients with diabetes. However, no studies have investigated the role of previous CVD in this association.

METHODS

The study cohort comprised patients with type 2 diabetes mellitus (T2DM; n=1910) included in the Second Manifestations of Arterial Disease (SMART) study. The relationship between either HGI or HbA_1c and a composite of cardiovascular events as the primary outcome, and mortality, cardiovascular mortality, myocardial infarction and stroke as secondary outcomes, was investigated using Cox proportional-hazards models. Similar analyses were performed after stratification according to previous CVD.

RESULTS

A 1-unit higher HGI was associated with a 29% greater risk of a composite of cardiovascular events (HR: 1.29, 95% CI: 1.06-1.57) in patients without previous CVD, whereas no such relationship was seen in patients with previous CVD (HR: 0.96, 95% CI: 0.86-1.08). The direction and magnitude of the hazard ratios (HRs) of HGI and HbA_1c in relation to outcomes were similar. Additional adjustment for HbA_1c in the association between HGI and outcomes lowered the HRs.

CONCLUSION

Similar to HbA_1c, higher HGI is related to higher risk of cardiovascular events in patients with T2DM without CVD. As HbA_1c has proved to be a comparable risk factor, and obtaining and interpreting the HGI is complicated, any additional benefit of applying the HGI in clinical settings is likely to be limited.

Genetics of HbA1c: a case study in clinical translation

Glycated hemoglobin (HbA1c) measures the amount of glucose in the blood in the previous 2-3 months and is used to test whether an individual has diabetes (HbA1c≥6.5%), or how well they are managing their diabetes. Genome-wide association studies have successfully identified multiple genomic loci influencing HbA1c, through both glycemic (factors that affect the amount blood glucose levels) and erythrocytic (factors that affect the red blood cell) pathways. Inaccuracies in HbA1c, due to non-glycemic variants, could lead to suboptimal care or adverse health consequences. A recently published example is the erythrocytic variant (rs1050828) in G6PD, which leads to the artificial lowering of HbA1c and missed diagnosis of diabetes using current thresholds. In this review we will discuss recent insights into the genetic etiology of HbA1c, and how these can translate to the clinic.

Distribution of glycated haemoglobin and its determinants in Korean youth and young adults: a nationwide population-based study

The present study aimed to describe the distribution of and to investigate the factors associated with glycated haemoglobin (HbA1c) values in Korean youth (10–19 years old) and young adults (20–29 years old). Data from the Korea Health and Nutrition Examination Survey (2011–2015) were used. A total of 6,418 participants (male 3,140 [53.2%]) aged 10–29 years were included in the analysis. Percentiles of HbA1c were calculated and HbA1c values were compared according to age, sex, and associated factors. The mean HbA1c values (% [mmol/mol]) were 5.42 ± 0.01 (35.7 ± 0.1) for youths and 5.32 ± 0.01 (34.7 ± 0.1) for young adults (P < 0.001). Male participants showed significantly higher HbA1c level than females (P < 0.001). When age was grouped into 5-year intervals, HbA1c was the highest in those aged 10–14 years and the lowest in those aged 20–24 years. After controlling for confounding variables, the HbA1c values of youths and male participants were significantly higher than those of young adults and female participants. The present study provides nationally representative data on the distribution of HbA1c values in Korean youth and young adults. There were significant differences in the level of HbA1c according to age and sex.

Genome-wide meta-analysis in Japanese populations identifies novel variants at the TMC6-TMC8 and SIX3-SIX2 loci associated with HbA1c

Glycated haemoglobin (HbA1c) is widely used as a biomarker for the diagnosis of diabetes, for population-level screening, and for monitoring the glycaemic status during medical treatment. Although the heritability of HbA1c has been estimated at ~55-75%, a much smaller proportion of phenotypic variance is explained by the HbA1c-associated variants identified so far. To search for novel loci influencing the HbA1c levels, we conducted a genome-wide meta-analysis of 2 non-diabetic Japanese populations (n = 7,704 subjects in total). We identified 2 novel loci that achieved genome-wide significance: TMC6-TMC8 (P = 5.3 × 10-20) and SIX3-SIX2 (P = 8.6 × 10-9). Data from the largest-scale European GWAS conducted for HbA1c supported an association between the novel TMC6-TMC8 locus and HbA1c (P = 2.7 × 10-3). The association analysis with glycated albumin and glycation gap conducted using our Japanese population indicated that the TMC6-TMC8 and SIX3-SIX2 loci may influence the HbA1c level through non-glycaemic and glycaemic pathways, respectively. In addition, the pathway-based analysis suggested that the linoleic acid metabolic and 14-3-3-mediated signalling pathways were associated with HbA1c. These findings provide novel insights into the molecular mechanisms that modulate the HbA1c level in non-diabetic subjects.

DNA Advanced Glycation End Products (DNA-AGEs) Are Elevated in Urine and Tissue in an Animal Model of Type 2 Diabetes

More precise identification and treatment monitoring of prediabetic/diabetic individuals will require additional biomarkers to complement existing diagnostic tests. Candidates include hyperglycemia-induced adducts such as advanced glycation end products (AGEs) of proteins, lipids, and DNA. The potential for DNA-AGEs as diabetic biomarkers was examined in a longitudinal study using the Lepr^db/db animal model of metabolic syndrome. The DNA-AGE, N²-(1-carboxyethyl)-2'-deoxyguanosine (CEdG) was quantified by mass spectrometry using isotope dilution from the urine and tissue of hyperglycemic and normoglycemic mice. Hyperglycemic mice (fasting plasma glucose, FPG, ≥ 200 mg/dL) displayed a higher median urinary CEdG value (238.4 ± 112.8 pmol/24 h) than normoglycemic mice (16.1 ± 11.8 pmol/24 h). Logistic regression analysis revealed urinary CEdG to be an independent predictor of hyperglycemia. Urinary CEdG was positively correlated with FPG in hyperglycemic animals and with HbA1c for all mice. Average tissue-derived CEdG was also higher in hyperglycemic mice (18.4 CEdG/10⁶ dG) than normoglycemic mice (4.4 CEdG/10⁶ dG). Urinary CEdG was significantly elevated in Lepr^db/db mice relative to Lepr^wt/wt, and tissue CEdG values increased in the order Lepr^wt/wt < Lepr^wt/db < Lepr^db/db. These data suggest that urinary CEdG measurement may provide a noninvasive quantitative index of glycemic status and augment existing biomarkers for the diagnosis and monitoring of diabetes.

Differences in Hemoglobin A1c Between Hispanics/Latinos and Non-Hispanic Whites: An Analysis of the Hispanic Community Health Study/Study of Latinos and the 2007-2012 National Health and Nutrition Examination Survey

OBJECTIVE

To determine whether, after adjustment for glycemia and other selected covariates, hemoglobin A1c (HbA1c) differed among adults from six Hispanic/Latino heritage groups (Central American, Cuban, Dominican, Mexican, Puerto Rican, and South American) and between Hispanic/Latino and non-Hispanic white adults without self-reported diabetes.

RESEARCH DESIGN AND METHODS

We performed a cross-sectional analysis of data from 13,083 individuals without self-reported diabetes from six Hispanic/Latino heritage groups, enrolled from 2008 to 2011 in the Hispanic Community Health Study/Study of Latinos, and 2,242 non-Hispanic white adults enrolled during the 2007-2012 cycles of the National Health and Nutrition Examination Survey. We compared HbA1c levels among Hispanics/Latinos and between Hispanics/Latinos and non-Hispanic whites before and after adjustment for age, sex, fasting (FPG) and 2-h post-oral glucose tolerance test (2hPG) glucose, anthropometric measurements, and selected biochemical and hematologic variables and after stratification by diabetes status: unrecognized diabetes (FPG ≥7.1 mmol/L or 2hPG ≥11.2 mmol/L), prediabetes (FPG 5.6-7.0 mmol/L or 2hPG 7.8-11.1 mmol/L), and normal glucose tolerance (FPG <5.6 mmol/L and 2hPG <7.8 mmol/L).

RESULTS

Adjusted mean HbA1c differed significantly across all seven groups (P < 0.001). Non-Hispanic whites had significantly lower HbA1c (P < 0.05) than each individual Hispanic/Latino heritage group. Upon stratification by diabetes status, statistically significant differences (P < 0.001) in adjusted mean HbA1c persisted across all seven groups.

CONCLUSIONS

HbA1c differs among Hispanics/Latinos of diverse heritage groups and between non-Hispanic whites and Hispanics/Latinos after adjustment for glycemia and other covariates. The clinical significance of these differences is unknown.

Standardising HbA1c-based diabetes diagnosis: opportunities and challenges

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.

The Glucose Measurement Industry and Hemoglobin A1c: An Opportunity for Creative Destruction

The MyStar Extra self-monitoring blood glucose (SMBG) system provides moving estimates of the patient's hemoglobin A1c (HbA1c). There is a treasure trove of highly accurate glucose data available from highly accurate SMBG, CGM and FGM along with highly accurate HPLC HbA1c. If Nathan's criteria are used to select subjects whose glucoses can be correlated to the HbA1c, then algorithms can be developed for robustly transforming glucose into HbA1c. These algorithms can then be implemented in any SMBG or with the CGM and FGM software. This calculated HbA1c would even be accurate with Nathan's excluded population thus reducing the use of fructosamine and glycated protein. Finally, the developer of these new algorithms is advised to use a specific approach for testing her algorithm.

Modeling predictors of changes in glycemic control and diabetes-specific quality of life amongst adults with type 1 diabetes 1 year after structured education in flexible, intensive insulin therapy

Few studies have identified determinants of glycemic control (HbA1c) and diabetes-specific quality of life (DSQoL) in adults with type 1 diabetes. To identify factors predicting outcomes following structured diabetes education. 262 participants completed biomedical and questionnaire assessments before, and throughout 1 year of follow-up. The proportion of variance explained ranged from 28 to 62 % (DSQoLS) and 14-20 % (HbA1c). When change in psychosocial variables were examined, reduced hypoglycemia fear, lower 'perceived diabetes seriousness', greater self-efficacy and well-being predicted QoL improvements from baseline to 3-months. Increased frequency of blood glucose testing predicted improvements in HbA1c from baseline to 6-months. Greater benefits may be achieved if programs focus explicitly on psychosocial factors. Self-care behaviours did not predict HbA1c suggesting existing assessment tools need refinement. Evaluation of treatment mechanisms in self-management programs is recommended.

The hemoglobin glycation index identifies subpopulations with harms or benefits from intensive treatment in the ACCORD trial

OBJECTIVE

This study tested the hypothesis that intensive treatment in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial disproportionately produced adverse outcomes in patients with diabetes with a high hemoglobin glycation index (HGI = observed HbA1c - predicted HbA1c).

RESEARCH DESIGN AND METHODS

ACCORD was a randomized controlled trial of 10,251 patients with type 2 diabetes assigned to standard or intensive treatment with HbA1c goals of 7.0% to 7.9% (53 to 63 mmol/mol) and less than 6% (42 mmol/mol), respectively. In this ancillary study, a linear regression equation (HbA1c = 0.009 × fasting plasma glucose [FPG] [mg/dL] + 6.8) was derived from 1,000 randomly extracted participants at baseline. Baseline FPG values were used to calculate predicted HbA1c and HGI for the remaining 9,125 participants. Kaplan-Meier and Cox regression were used to assess the effects of intensive treatment on outcomes in patients with a low, moderate, or high HGI.

RESULTS

Intensive treatment was associated with improved primary outcomes (composite of cardiovascular events) in the low (hazard ratio [HR] 0.75 [95% CI 0.59-0.95]) and moderate (HR 0.77 [95% CI 0.61-0.97]) HGI subgroups but not in the high HGI subgroup (HR 1.14 [95% CI 0.93-1.40]). Higher total mortality in intensively treated patients was confined to the high HGI subgroup (HR 1.41 [95% CI 1.10-1.80]). A high HGI was associated with a greater risk for hypoglycemia in the standard and intensive treatment groups.

CONCLUSIONS

HGI calculated at baseline identified subpopulations in ACCORD with harms or benefits from intensive glycemic control. HbA1c is not a one-size-fits-all indicator of blood glucose control, and taking this into account when making management decisions could improve diabetes care.

Recent advances in glucose-lowering treatment to reduce diabetic kidney disease

INTRODUCTION

The epidemic of diabetes has now taken on epic proportions and therefore reducing the impact of diabetic complications represents one of the major global challenges in improving health and well-being worldwide. Preventing the development of diabetic kidney disease (DKD) is particularly important, as diabetes is one of the main risk factors for the development of chronic kidney disease, which in turn is strongly linked to development of cardiovascular disease, end-stage renal failure, hospitalization and premature death. Intensive glucose-lowering treatment has been shown to prevent and slow progression of DKD, yet to date, only certain populations have benefited from this intervention.

AREAS COVERED

We review the evidence for existing glucose-lowering treatments in the prevention of DKD, and research into techniques to better target individuals who will benefit from these therapies.

EXPERT OPINION

Diabetic patients with established kidney disease may benefit from glucose-lowering treatment, particularly if a safer side-effect profile of these treatments is achieved. Better understanding of glucose homeostasis and evaluation of compounds inhibiting its downstream effects are required in order to improve the outlook for individuals with DKD. An additional approach to improve the success rate of glucose-lowering treatment is to improve the selection of individuals who may benefit from treatment. A potential means to identify such subjects could involve the use of biomarkers.

Diet and glycaemia: the markers and their meaning. A report of the Unilever Nutrition Workshop

Consumption of carbohydrate-containing foods leads to transient postprandial rises in blood glucose concentrations that vary between food types. Higher postprandial glycaemic exposures have particularly been implicated in the development of chronic cardiometabolic diseases. Reducing such diet-related exposures may be beneficial not only for diabetic patients but also for the general population. A variety of markers have been used to track different aspects of glycaemic exposures, with most of the relevant knowledge derived from diabetic patients. The assessment of glycaemic exposures among the non-diabetic population may require other, more sensitive markers. The present report summarises key messages of presentations and related discussions from a workshop organised by Unilever intended to consider currently applied markers of glycaemic exposure. The particular focus of the meeting was to identify the potential applicability of glycaemic exposure markers for studying dietary effects in the non-diabetic population. Workshop participants concluded that markers of glycaemic exposures are sparsely used in intervention studies among non-diabetic populations. Continuous glucose monitoring remains the optimal approach to directly assess glycaemic exposure. Markers of glycaemic exposure such as glycated Hb, fructosamine, glycated albumin, 1,5-anhydroglucitol and advanced glycation end products can be preferred dependent on the aspect of interest (period of exposure and glucose variability). For all the markers of glycaemia, the responsiveness to interventions will probably be smaller among the non-diabetic than among the diabetic population. Further validation and acceptance of existing glycaemic exposure markers applied among the non-diabetic population would aid food innovation and better design of dietary interventions targeting glycaemic exposure.

Ethnic variation in the correlation between fasting glucose concentration and glycated hemoglobin (HbA1c)

OBJECTIVE

We aimed to determine the relationship between fasting serum glucose (FSG) concentration and glycated hemoglobin-A1c (HbA1c) in the 3 ethnicities in Singapore after adjustment for demographic and therapeutic variables.

METHODS

Fasting serum glucose (FSG), HbA1c, and serum creatinine levels were simultaneously sampled from 575 patients with diabetes (389 Chinese, 97 Indians, 89 Malays) in this cross-sectional study between January and May 2008, and the results were subjected to multivariate linear regression analysis.

RESULTS

We found a significant interaction between FSG and ethnicity on HbA1c. The correlation between FSG and HbA1c among Chinese subjects was 0.25 (95% confidence interval [CI]:0.2-0.3) relative to the Malays (0.38, 95% CI: 0.30-0.45) after adjustment for age; gender; serum creatinine concentrations; body mass index (BMI); duration of diabetes; use of sulfonylureas, metformin, and insulin; and hemoglobin (Hb) and red cell indices (P = .005). Hence, for a given FSG, the predicted HbA1c will be higher in Malays compared to Chinese subjects. We did not observe a statistically significant difference between Indians and Malays with respect to the correlation between FSG and HbA1c.

CONCLUSION

We showed a higher correlation between HbA1c and FSG in Malay subjects relative to the Chinese in this cohort. The ethnic variation in the HbA1c-FSG relationship may be related to differences in percentage contribution by the FSG to overall HbA1c among ethnic groups. Future studies using continuous glucose monitoring (CGM) to elucidate the relative contributions by FSG and postprandial glucose (PPG) to the daily blood glucose profile and the overall HbA1c by ethnicity are required.

Glucoregulatory function among African Americans and European Americans with normal or pre-diabetic hemoglobin A1c levels

OBJECTIVE

A hemoglobin (Hb) A1c range of 5.7%-6.4% has been recommended for the diagnosis of prediabetes. To determine the significance of such "prediabetic" HbA1c levels, we compared glucoregulatory function in persons with HbA1c levels of 5.7%-6.4% and those with HbA1c<5.7%.

METHODS

We studied 280 nondiabetic adults (142 black, 138 white; mean (±SD) age 44.2±10.6 years). Each subject underwent clinical assessment, blood sampling for HbA1c measurement, and a 75-g oral glucose tolerance test at baseline. Additional assessments during subsequent outpatient visits included insulin sensitivity, using homeostasis model assessment (HOMA)-IR and the hyperinsulinemic euglycemic clamp; insulin secretion, using HOMA-B and frequently samples intravenous glucose tolerance test (FSIVGTT) and disposition index (DI); and measurement of fat mass, using DXA.

RESULTS

Compared to subjects with HbA1c<5.7%, persons with HbA1c levels of 5.7%-6.4% were older, and had higher body mass index (BMI) and insulin secretion but similar insulin sensitivity. When the two groups were matched in age and BMI, persons with HbA1c 5.7%-6.4% were indistinguishable from those with HbA1c <5.7% with regard to all measures of glycemia and glucoregulatory function.

CONCLUSIONS

Unlike glucose-defined prediabetes status, an HbA1c range of 5.7%-6.4% does not reliably identify individuals with impaired insulin action or secretion, the classical defects underlying the pathophysiology of prediabetes. Thus, HbA1c cannot validly replace blood glucose measurement in the diagnosis of prediabetes. If utilized as a screening test due to convenience, aberrant HbA1c values should be corroborated with blood glucose measurement before therapeutic intervention.

CDKAL1 and HHEX are associated with type 2 diabetes-related traits among Yup'ik people

BACKGROUND

Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with type 2 diabetes (T2D), mainly among individuals of European ancestry. In the present study, we examined the frequency of these SNPs and their association with T2D-related traits in an Alaska Native study population with a historically low prevalence of T2D. We also investigated whether dietary characteristics that may protect against T2D, such as n-3 polyunsaturated fatty acid (PUFA) intake, modify these associations.

METHODS

In 1144 Yup'ik people, we examined 17 SNPs repeatedly identified in GWAS for individual and cumulative associations with T2D-related traits. Cumulative associations were evaluated using a genetic risk score (GRS) calculated by summing risk alleles. Associations were tested for interactions with sex, body mass index (BMI), and n-3 PUFA intake.

RESULTS

The rs7754840 SNP in CDKAL1 is significantly associated with HbA1c (P = 0.00091). The rs5015480 SNP near HHEX is significantly associated (in opposite direction to that in Europeans) with a combined fasting glucose (FG) and HbA1c measure (P = 0.00046) and with homeostatic model assessment of β-cell function (HOMA-B; P = 0.0014). The GRS is significantly associated with FG and combined FG and HbA1c only when the HHEX SNP is dropped from the GRS. Associations are not modified by BMI or n-3 PUFA intake.

CONCLUSION

Our results highlight the potential importance of CDKAL1 and HHEX in glucose homeostasis in this Alaska Native population with a low prevalence of T2D, and suggest that these loci should be examined in greater detail in this population.

Epidemiology and risk factors for diabetic kidney disease

Prevalence rates of diabetic kidney disease (DKD) are increasing in parallel with the incidence rates of diabetes mellitus. DKD has already become a significant health problem worldwide. Without radical improvements in prevention and treatment, DKD prevalence will continue to climb. The pathogenesis of DKD is complex and multifactorial, with genetic and environmental factors involved. Several nonmodifiable risk factors contribute to DKD, including genetics, sex, age, age at onset, and duration of diabetes. However, there are also several modifiable risk factors that have a strong effect on the risk of DKD. Traditional modifiable factors include glycemic control, blood pressure, lipids, and smoking. Other recently discovered modifiable risk factors include chronic low-grade inflammation, advanced glycation end products, and lack of physical activity. Efficient management of these modifiable risk factors may improve the prognosis of diabetic patients at risk of DKD.

Vitamin status as a determinant of serum homocysteine concentration in type 2 diabetic retinopathy

We investigated the association of serum homocysteine levels and vitamin status with type 2 diabetic retinopathy. This study included 65 patients with and 75 patients without diabetic retinopathy. Patients with diabetic retinopathy had significantly higher serum homocysteine levels (P < 0.001), higher prevalence of hyperhomocysteinemia (P < 0.001), lower serum folic acid (P < 0.001), and vitamin B12 (P = 0.014) levels than those without diabetic retinopathy. Regression analysis revealed that homocysteine was an independent risk factor for diabetic retinopathy and there was a threshold in its serum level (13.7  μ mol/L), above which the risk of diabetic retinopathy greatly increases (OR = 1.66, P = 0.001). Folic acid was associated with decreased odds for diabetic retinopathy (OR = 0.73, P < 0.001). There was a threshold in serum vitamin B12 level (248.4 pg/mL), below which serum homocysteine concentration significantly increases with decreasing serum vitamin B12 (P = 0.003). Our findings suggest that hyperhomocysteinemia is an independent risk factor for the development and progression of diabetic retinopathy. Decreased serum levels of folic acid and vitamin B12, through raising serum homocysteine concentrations, may also affect the diabetic retinopathy risk.

Relationship between HbA1c and continuous glucose monitoring in Chinese population: a multicenter study

Objective

Since there is a paucity of reference data in the literature to indicate the relationship between HbA1c, and 24 h mean blood glucose (MBG) from continuous glucose monitoring (CGM) in Chinese populations, we described the above relationship in adult Chinese subjects with different glucose tolerance status.

Methods

Seven-hundred-and-forty-two individuals without history of diabetes were included to the study at 11 hospitals in urban areas across China from 2007–2009 and data of 673 subjects were included into the final analysis. Oral glucose tolerance test (OGTT) classified the participants as nondiabetic subjects, including those with normal glucose regulation (NGR; n = 121) and impaired glucose regulation (IGR; n = 209), or newly diagnosed type 2 diabetes (n = 343). All participants completed testing for HbA1c levels and wore a CGM system for three consecutive days. The 24 h MBG levels were calculated. Spearman correlations and linear regression analyses were applied to quantify the relationship between glucose markers.

Results

The levels of HbA1c and 24 h MBG significantly increased with presence of glucose intolerance (NGR<IGR<type 2 diabetes; both, P<0.001). Analysis of the total population indicated that HbA1c was strongly correlated with 24 h MBG (r = 0.735). The correlation was also found to be significant for the subgroup of participants with newly diagnosed type 2 diabetes (r = 0.694, P<0.001). Linear regression analysis of the total study population yielded the following equation: 24 h MBG _mmol/L = 1.198×HbA1c–0.582 (24 h MBG _mg/dL = 21.564×HbA1c–10.476) (R² = 0.670, P<0.001). The model fit was not improved by application of exponential or quadratic modeling. When HbA1c was 6.5%, the calculated 24 h MBG was 7.2 (6.4–8.1) mmol/L (130 (115–146) mg/dL); and when HbA1c was 7.0%, the 24 h MBG was 7.8 (6.9–8.7) mmol/L (140 (124–157) mg/dL).

Conclusions

Our study provided the reference data of the relationship between HbA1c and CGM in Chinese subjects.

HbA1c for diagnosis of type 2 diabetes. Is there an optimal cut point to assess high risk of diabetes complications, and how well does the 6.5% cutoff perform?

Glycated hemoglobin (HbA1c) has recently been recommended for the diagnosis of type 2 diabetes mellitus (T2DM) by leading diabetes organizations and by the World Health Organization. The most important reason to define T2DM is to identify subjects with high risk of diabetes complications who may benefit from treatment. This review addresses two questions: 1) to assess from existing studies whether there is an optimal HbA1c threshold to predict diabetes complications and 2) to assess how well the recommended 6.5% cutoff of HbA1c predicts diabetes complications. HbA1c cutoffs derived from predominantly cross-sectional studies on retinopathy differ widely from 5.2%-7.8%, and among other reasons, this is due to the heterogeneity of statistical methods and differences in the definition of retinopathy. From the few studies on other microvascular complications, HbA1c thresholds could not be identified. HbA1c cutoffs make less sense for the prediction of cardiovascular events (CVEs) because CVE risks depend on various strong risk factors (eg, hypertension, smoking); subjects with low HbA1c levels but high values of CVE risk factors were shown to be at higher CVE risk than subjects with high HbA1c levels and low values of CVE risk factors. However, the recommended 6.5% threshold distinguishes well between subjects with and subjects without retinopathy, and this distinction is particularly strong in severe retinopathy. Thus, in existing studies, the prevalence of any retinopathy was 2.5 to 4.5 times as high in persons with HbA1c-defined T2DM as in subjects with HbA1c <6.5%. To conclude, from existing studies, a consistent optimal HbA1c threshold for diabetes complications cannot be derived, and the recommended 6.5% threshold has mainly been brought about by convention rather than by having a consistent empirical basis. Nevertheless, the 6.5% threshold is suitable to detect subjects with prevalent retinopathy, which is the most diabetes specific complication. However, most of the studies on associations between HbA1c and microvascular diabetes complications are cross-sectional, and there is a need for longitudinal studies.

Hemoglobin A1c, fasting plasma glucose, and 2-hour plasma glucose distributions in U.S. population subgroups: NHANES 2005-2010

PURPOSE

Although mean concentrations of hemoglobin A1c (A1C), fasting plasma glucose, and 2-hour plasma glucose differ by demographics, it is unclear what other characteristics of the distributions may differ, such as the amount of asymmetry of the distribution (skewness) and shift left or right compared with another distribution (shift).

METHODS

Using kernel density estimation, we created smoothed plots of the distributions of fasting plasma glucose (N = 7250), 2-hour plasma glucose (N = 5851), and A1C (N = 16,209) by age, race-ethnicity, and sex in the 2005-2010 National Health and Nutrition Examination Survey, a nationally representative sample of U.S. adults including people with and without diabetes. We tested differences in distributions using cumulative logistic regression.

RESULTS

The distributions were generally unimodal and right-skewed. All distributions were shifted higher and more right-skewed for older age groups (P < .001 for each marker). Compared with non-Hispanic whites, the distribution of fasting plasma glucose was shifted higher for Mexican-Americans (P = .01), whereas the distribution of A1C was shifted higher for non-Hispanic blacks (P < .001). The distribution of fasting plasma glucose was shifted higher for men (P < .001) and the distribution of 2-hour plasma glucose was shifted higher for women (P = .01).

CONCLUSIONS

We provide a graphic reference for comparing these distributions and diabetes cut-points by demographic factors.

Race/ethnicity disparities in dysglycemia among U.S. women of childbearing age found mainly in the nonoverweight/nonobese

OBJECTIVE

To describe the burden of dysglycemia-abnormal glucose metabolism indicative of diabetes or high risk for diabetes-among U.S. women of childbearing age, focusing on differences by race/ethnicity.

RESEARCH DESIGN AND METHODS

Using U.S. National Health and Nutrition Examination Survey data (1999-2008), we calculated the burden of dysglycemia (i.e., prediabetes or diabetes from measures of fasting glucose, A1C, and self-report) in nonpregnant women of childbearing age (15-49 years) by race/ethnicity status. We estimated prevalence risk ratios (PRRs) for dysglycemia in subpopulations stratified by BMI (measured as kilograms divided by the square of height in meters), using predicted marginal estimates and adjusting for age, waist circumference, C-reactive protein, and socioeconomic factors.

RESULTS

Based on data from 7,162 nonpregnant women, representing>59,000,000 women nationwide, 19% (95% CI 17.2-20.9) had some level of dysglycemia, with higher crude prevalence among non-Hispanic blacks and Mexican Americans vs. non-Hispanic whites (26.3% [95% CI 22.3-30.8] and 23.8% [19.5-28.7] vs. 16.8% [14.4-19.6], respectively). In women with BMI<25 kg/m2, dysglycemia prevalence was roughly twice as high in both non-Hispanic blacks and Mexican Americans vs. non-Hispanic whites. This relative increase persisted in adjusted models (PRRadj 1.86 [1.16-2.98] and 2.23 [1.38-3.60] for non-Hispanic blacks and Mexican Americans, respectively). For women with BMI 25-29.99 kg/m2, only non-Hispanic blacks showed increased prevalence vs. non-Hispanic whites (PRRadj 1.55 [1.03-2.34] and 1.28 [0.73-2.26] for non-Hispanic blacks and Mexican Americans, respectively). In women with BMI>30 kg/m2, there was no significant increase in prevalence of dysglycemia by race/ethnicity category.

CONCLUSIONS

Our findings show that dysglycemia affects a significant portion of U.S. women of childbearing age and that disparities by race/ethnicity are most prominent in the nonoverweight/nonobese.