Determinants of HbA1c in nondiabetic Dutch adults: genetic loci and clinical and lifestyle parameters, and their interactions in the Lifelines Cohort Study

Dairy consumption and incident prediabetes: prospective associations and network models in the large population-based Lifelines Study

BACKGROUND

Evidence on associations between dairy consumption and incident prediabetes is inconsistent. One potential explanation for heterogeneity is that health behavior and food intake covary with the consumption of various high-fat and low-fat dairy types.

OBJECTIVE

The objective was to investigate the associations of total dairy and dairy types with incident prediabetes and to assess how dairy intake is linked with metabolic risk factors, lifestyle behaviors, and foods, as potential explanations for these associations.

METHODS

Overall, 74,132 participants from the prospective population-based Lifelines study were included (mean age, 45.5 ± 12.3 y; 59.7% female). Baseline dairy intake was measured using a validated food frequency questionnaire. Prediabetes at follow-up was defined based on the World Health Organization/International Expert Committee criteria as fasting plasma glucose of 110-125 mg/dL or glycated hemoglobin concentrations of 6.0%-6.5%. Associations were analyzed using Poisson regression models adjusted for social demographics, lifestyle behaviors, family history of diabetes, and food group intake. Interconnections were assessed with mixed graphical model networks.

RESULTS

At a mean follow-up of 4.1 ± 1.1 y, 2746 participants developed prediabetes (3.7%). In regression analyses, neutral associations were found for most dairy types. Intake of plain milk and low-fat milk were associated with a higher risk of prediabetes in the top compared with bottom quartiles (relative risk [RR]: 1.17; 95% confidence interval [CI]: 1.05, 1.30; P-trend = 0.04 and RR: 1.18; 95% CI: 1.06, 1.31; P-trend =0.01). Strong but nonsignificant effect estimates for high-fat yogurt in relation to prediabetes were found (RRservings/day: 0.80; 95% CI: 0.64, 1.01). The network analysis showed that low-fat milk clustered with energy-dense foods, including bread, meat, and high-fat cheese, whereas high-fat yogurt had no clear link with lifestyle risk factors and food intake.

CONCLUSIONS

In this large cohort of Dutch adults, low-fat milk intake was associated with higher prediabetes risk. Heterogeneous associations by dairy type and fat content might partly be attributed to confounding caused by behaviors and food intake related to dairy intake.

Prediabetes and the risk of type 2 diabetes: Investigating the roles of depressive and anxiety symptoms in the Lifelines cohort study

AIMS

Depression and anxiety may increase the risk of progressing from prediabetes to type 2 diabetes. The present study examined the interactions between prediabetes status and elevated depressive and anxiety symptoms with the risk of type 2 diabetes.

METHODS

Participants (N = 72,428) were adults aged 40 years and above without diabetes at baseline from the Lifelines Cohort Study (58% female; mean age = 51.4 years). The Mini-International Neuropsychiatric Interview screened for elevated symptoms of major depressive disorder and generalized anxiety disorder. Glycated haemoglobin A1c (HbA_1c ) levels determined prediabetes status at baseline (2007-2013), and HbA_1c and self-reported diabetes diagnoses determined diabetes status at follow-up (2014-2017). Groups were formed for elevated depressive and anxiety symptoms, respectively, and prediabetes status at baseline (elevated depressive/anxiety symptoms with prediabetes, elevated depressive/anxiety symptoms alone, and prediabetes alone), and compared to a reference group (no prediabetes or anxiety/depression) on the likelihood of developing diabetes during the follow-up period.

RESULTS

N = 1300 (1.8%) participants developed diabetes. While prediabetes alone was associated with incident diabetes (OR = 5.94; 95% CI = 5.10-6.90, p < 0.001), the group with combined prediabetes and depressive symptoms had the highest likelihood of developing diabetes over follow-up (OR = 8.29; 95% CI = 5.58-12.32, p < 0.001). Similar results were found for prediabetes and anxiety symptoms (OR = 6.57; 95% CI = 4.62-9.33, p < 0.001), compared to prediabetes alone (OR = 6.09; 95% CI = 5.23-7.11, p < 0.001), though with a smaller effect. The interaction between depressive symptoms and prediabetes was synergistic in age-and-sex adjusted analyses.

CONCLUSIONS

Individuals with elevated depressive, and to some extent anxiety, symptoms in combination with prediabetes may represent a high-risk subgroup for type 2 diabetes.

Investigating the association between fasting insulin, erythrocytosis and HbA1c through Mendelian randomization and observational analyses

BACKGROUND

Insulin resistance (IR) with associated compensatory hyperinsulinemia (HI) are early abnormalities in the etiology of prediabetes (preT2D) and type 2 diabetes (T2D). IR and HI also associate with increased erythrocytosis. Hemoglobin A1c (HbA1c) is commonly used to diagnose and monitor preT2D and T2D, but can be influenced by erythrocytosis independent of glycemia.

METHODS

We undertook bidirectional Mendelian randomization (MR) in individuals of European ancestry to investigate potential causal associations between increased fasting insulin adjusted for BMI (FI), erythrocytosis and its non-glycemic impact on HbA1c. We investigated the association between the triglyceride-glucose index (TGI), a surrogate measure of IR and HI, and glycation gap (difference between measured HbA1c and predicted HbA1c derived from linear regression of fasting glucose) in people with normoglycemia and preT2D.

RESULTS

Inverse variance weighted MR (IVWMR) suggested that increased FI increases hemoglobin (Hb, b=0.54 ± 0.09, p=2.7 x 10^-10), red cell count (RCC, b=0.54 ± 0.12, p=5.38x10^-6) and reticulocyte (RETIC, b=0.70 ± 0.15, p=2.18x10^-6). Multivariable MR indicated that increased FI did not impact HbA1c (b=0.23 ± 0.16, p=0.162) but reduced HbA1c after adjustment for T2D (b=0.31 ± 0.13, p=0.016). Increased Hb (b=0.03 ± 0.01, p=0.02), RCC (b=0.02 ± 0.01, p=0.04) and RETIC (b=0.03 ± 0.01, p=0.002) might modestly increase FI. In the observational cohort, increased TGI associated with decreased glycation gap, (i.e., measured HbA1c was lower than expected based on fasting glucose, (b=-0.09 ± 0.009, p<0.0001)) in people with preT2D but not in those with normoglycemia (b=0.02 ± 0.007, p<0.0001).

CONCLUSIONS

MR suggests increased FI increases erythrocytosis and might potentially decrease HbA1c by non-glycemic effects. Increased TGI, a surrogate measure of increased FI, associates with lower-than-expected HbA1c in people with preT2D. These findings merit confirmatory studies to evaluate their clinical significance.

Validating the doubly weighted genetic risk score for the prediction of type 2 diabetes in the Lifelines and Estonian Biobank cohorts

As many cases of type 2 diabetes (T2D) are likely to remain undiagnosed, better tools for early detection of high‐risk individuals are needed to prevent or postpone the disease. We investigated the value of the doubly weighted genetic risk score (dwGRS) for the prediction of incident T2D in the Lifelines and Estonian Biobank (EstBB) cohorts. The dwGRS uses an additional weight for each single nucleotide polymorphism in the risk score, to correct for “Winner's curse” bias in the effect size estimates. The traditional (single‐weighted genetic risk score; swGRS) and dwGRS were calculated for participants in Lifelines (n = 12,018) and EstBB (n = 34,129). The dwGRS was found to have stronger association with incident T2D (hazard ratio [HR] = 1.26 [95% confidence interval: 1.10–1.43] and HR = 1.35 [1.28–1.42]) compared to the swGRS (HR = 1.21 [1.07–1.38] and HR = 1.25 [1.19–1.32]) in Lifelines and EstBB, respectively. Comparing the 5‐year predicted risks from the models with and without the dwGRS, the continuous net reclassification index was 0.140 (0.034–0.243; p = .009 Lifelines), and 0.257 (0.194–0.319; p < 2 × 10⁻¹⁶ EstBB). The dwGRS provided incremental value to the T2D prediction model with established phenotypic predictors. It clearly distinguished the risk groups for incident T2D in both biobanks thereby showing its clinical relevance.

Phenotypic and lifestyle determinants of HbA1c in the general population-The Hoorn Study

Aim

To investigate the relative contribution of phenotypic and lifestyle factors to HbA_1c, independent of fasting plasma glucose (FPG) and 2h post-load glucose (2hPG), in the general population.

Methods

The study populations included 2309 participants without known diabetes from the first wave of the Hoorn Study (1989) and 2619 from the second wave (2006). Multivariate linear regression models were used to analyze the relationship between potential determinants and HbA_1c in addition to FPG and 2hPG. The multivariate model was derived in the first wave of the Hoorn Study, and replicated in the second wave.

Results

In both cohorts, independent of FPG and 2hPG, higher age, female sex, larger waist circumference, and smoking were associated with a higher HbA_1c level. Larger hip circumference, higher BMI, higher alcohol consumption and vitamin C intake were associated with a lower HbA_1c level. FPG and 2hPG together explained 41.0% (first wave) and 53.0% (second wave) of the total variance in HbA_1c. The combination of phenotypic and lifestyle determinants additionally explained 5.7% (first wave) and 3.9% (second wave).

Conclusions

This study suggests that, independent of glucose, phenotypic and lifestyle factors are associated with HbA_1c, but the contribution is relatively small. These findings contribute to a better understanding of the low correlation between glucose levels and HbA_1c in the general population.

Associations of anemia and hemoglobin with hemoglobin A1c among non-diabetic workers in Japan

AIMS/INTRODUCTION

We examined the association between hemoglobin A1c (HbA1c) and anemia, which was categorized into three groups according to mean corpuscular volume (MCV), as well as the association between hemoglobin in the non-anemic range and HbA1c.

MATERIALS AND METHODS

We used the 2016 health checkup data from 36,422 workers without diabetes. Anemic people were divided into three groups based on MCV: <80, 80-90 and >90 fL. Non-anemic people were divided into four groups based on their hemoglobin levels. We carried out multiple linear regression models to estimate the means and 95% confidence intervals (CIs) of HbA1c.

RESULTS

For men, 0.2% had anemia with MCV <80 fL, 0.5% had anemia with MCV 80-90 fL, 0.9% had anemia with MCV >90 fL and 98.4% had no anemia. For women, the corresponding values were 6.1, 6.4, 2.8 and 84.7%, respectively. The adjusted mean HbA1c (%) values for men with anemia with MCV <80, 80-90 and >90 fL were 5.67 (95% CI 5.60-5.74), 5.58 (95% CI 5.54-5.62) and 5.41 (95% CI 5.37-5.44), respectively. Among men without anemia, HbA1c (%) increased from 5.36 (95% CI 5.34-5.39) in those with hemoglobin ≥17.5 mg/dL to 5.45 (95% CI 5.45-5.46) in those with hemoglobin 13.0 to <14.5 mg/dL (P for trend <0.001). The HbA1c values were higher in men with anemia with MCV <80 fL or MCV 80-90 fL, but lower in men with MCV >90 fL, compared with non-anemic men with hemoglobin 13.0 to <14.5 mg/dL (All P < 0.001). Similar findings were observed in women.

CONCLUSIONS

We observed elevated HbA1c among anemic people with MCV <80 fL or MCV 80-90 fL, and decreased HbA1c among anemic people with MCV >90 fL, suggesting that different types of anemia might influence HbA1c differently. In addition, non-anemic people with lower hemoglobin levels had higher HbA1c levels, suggesting that hemoglobin levels are in need of consideration when interpreting HbA1c values among non-anemic people.

Infant cholesterol and glycated haemoglobin concentrations vary widely-Associations with breastfeeding, infant diet and maternal biomarkers

AIM

Elevated total cholesterol (TC) and glycated haemoglobin (HbA1c) are risk factors for cardiovascular disease; however, little is known about their determinants in infants. We aimed to describe TC and HbA1c concentrations in infants aged 8-14 months and explore the relation between infant TC, HbA1c, breastfeeding, infant diet, and maternal TC and HbA1c.

METHODS

In this cross-sectional pilot study, mothers of infants aged 6 and 12 months were invited to complete a food frequency questionnaire and to take home-based dried blood spot samples from themselves and their infants.

RESULTS

Among the 143 included infants, the mean (SD, range) concentration was 4.1 (0.8, 2.3-6.6) mmol/L for TC and 4.9 (0.4, 3.7-6.0)% for HbA1c. There was no significant difference between age groups and sexes. There was a positive relation between TC concentrations of all infants and mothers (B = 0.30 unadjusted, B = 0.32 adjusted, P < .001 for both) and a negative relation between infant TC and intake of unsaturated fatty acids in the oldest age group (B = -0.09, P = .03 unadjusted, B = -0.08, P = .06 adjusted). Infant HbA1c was not significantly related to diet or maternal HbA1c.

CONCLUSION

TC and HbA1c concentrations varied widely among infants aged 8-14 months. Infant TC was associated with macronutrient intake and maternal TC.

Determinants of diagnostic discordance for non-diabetic hyperglycaemia and Type 2 diabetes using paired glycated haemoglobin measurements in a large English primary care population: cross-sectional study

AIM

To investigate factors influencing diagnostic discordance for non-diabetic hyperglycaemia and Type 2 diabetes.

METHODS

Some 10 000 adults at increased risk of diabetes were screened with HbA_1c and fasting plasma glucose (FPG). The 2208 participants with initial HbA_1c ≥ 42 mmol/mol (≥ 6.0%) or FPG ≥ 6.1 mmol/l were retested after a median 40 days. We compared the first and second HbA_1c results, and consequent diagnoses of non-diabetic hyperglycaemia and Type 2 diabetes, and investigated predictors of discordant diagnoses.

RESULTS

Of 1463 participants with non-diabetic hyperglycaemia and 394 with Type 2 diabetes on first testing, 28.4% and 21.1% respectively had discordant diagnoses on repeated testing. Initial diagnosis of non-diabetic hyperglycaemia and/or impaired fasting glucose according to both HbA_1c and FPG criteria, or to FPG only, made reclassification as Type 2 diabetes more likely than initial classification according to HbA_1c alone. Initial diagnosis of Type 2 diabetes according to both HbA_1c and FPG criteria made reclassification much less likely than initial classification according to HbA_1c alone. Age, and anthropometric and biological measurements independently but inconsistently predicted discordant diagnoses and changes in HbA_1c .

CONCLUSIONS

Diagnosis of non-diabetic hyperglycaemia or Type 2 diabetes with a single measurement of HbA_1c in a screening programme for entry to diabetes prevention trials is unreliable. Diagnosis of non-diabetic hyperglycaemia and Type 2 diabetes should be confirmed by repeat testing. FPG results could help prioritise retesting. These findings do not apply to people classified as normal on a single test, who were not retested.

Association between gain in adiposity and diabetic kidney disease worsening in type 2 diabetes is mediated by deteriorating glycaemic control: A 3-year follow-up analysis

AIMS

Increased adiposity confers elevated risk for diabetic kidney disease (DKD) progression in type 2 diabetes mellitus (T2DM). This 3-year prospective study examined whether worsening of metabolic control e.g. development of uncontrolled diabetes mediated the relationship between increased adiposity and DKD deterioration.

METHODS

T2DM subjects who had adequately controlled diabetes (HbA1c < 8%) at initial recruitment were analysed (N = 853). HbA1c ≥ 8% at follow-up was classified as development of uncontrolled T2DM. Absolute changes in body weight (ΔWeight), body mass index (ΔBMI), and body fat mass (ΔBFM) were calculated by subtracting baseline from follow-up values. DKD deterioration (outcome) was defined as an increase in the composite ranking of relative risk by glomerular filtration rate and albuminuria levels (Kidney Disease: Improving Global Outcomes 2009).

RESULTS

Subjects with deteriorated DKD displayed lower reduction in body composition at follow-up than those who remained stable or/improved (all P < 0.05). In separate regression models, ΔWeight (risk ratio (RR):1.04, 95% CI:1.01-1.06), ΔBMI (RR:1.07, 95% CI:1.01-1.13), and ΔBFM (RR:1.03, 95% CI:1.01-1.06) were independently associated with worsened DKD. The associations were attenuated after accounting for the loss of glycaemic control. Binary mediation analysis revealed that the development of uncontrolled diabetes explained 41.7%, 45.4% and 39.7%, respectively, of the effects of ΔWeight, ΔBMI and ΔBFM on the outcome.

CONCLUSIONS

Among T2DM individuals who had adequately-controlled T2DM at initial recruitment, the relationship between gain in adiposity and DKD deterioration is mediated by the development of poor glycaemic control over time. Therefore, preventing worsening adiposity and hyperglycaemia is pivotal to impede DKD progression.

The Relationship Between Alcohol and Glycohemoglobin: A Biopsychosocial Perspective

With the rising prevalence of type 2 diabetes mellitus (T2DM), there is debate regarding biological and psychosocial risk factors. While it is well established that alcohol lowers glycohemoglobin (HbA1c) levels, it is less clear whether alcohol consumption is protective of T2DM. It is also unclear how gender and ethnicity influence the utility of HbA1c screening as a tool for T2DM diagnosis, particularly in the context of alcohol use. This cross-sectional study utilized the National Health and Nutrition Examination Survey 2013–2014 dataset and was restricted to adults 20 years and older, nonpregnant, and not on antihypertensive medication (n = 4299) to evaluate the relationship between alcohol use and HbA1c. A multilinear regression model controlled for gender, ethnicity, education level, body mass index, and age. After controlling for covariates, both moderate (β = −0.073; p = 0.033) and heavy drinking (β = −0.167; p < 0.001) are associated with reduced HbA1c levels. Additionally, female gender is a significant negative predictor of HbA1c (β = −0.052; p = 0.024) and all ethnic groups have higher levels of HbA1c compared with non-Hispanic whites. Plausible biological mechanisms are discussed. The clinical utility of HbA1c as a screening tool for T2DM without considering alcohol use, gender, and ethnicity may lead to diagnostic errors. Individualized approaches and focused efforts toward health equity are needed to address rising rates of T2DM.

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.

Dairy product consumption is associated with pre-diabetes and newly diagnosed type 2 diabetes in the Lifelines Cohort Study

Previous studies show associations between dairy product consumption and type 2 diabetes, but only a few studies conducted detailed analyses for a variety of dairy subgroups. Therefore, we examined cross-sectional associations of a broad variety of dairy subgroups with pre-diabetes and newly diagnosed type 2 diabetes (ND-T2DM) among Dutch adults. In total, 112 086 adults without diabetes completed a semi-quantitative FFQ and donated blood. Pre-diabetes was defined as fasting plasma glucose (FPG) between 5·6 and 6·9 mmol/l or HbA1c% of 5·7-6·4 %. ND-T2DM was defined as FPG ≥7·0 mmol/l or HbA1c ≥6·5 %. Logistic regression analyses were conducted by 100 g or serving increase and dairy tertiles (T1ref), while adjusting for demographic, lifestyle and dietary covariates. Median dairy product intake was 324 (interquartile range 227) g/d; 25 549 (23 %) participants had pre-diabetes; and 1305 (1 %) had ND-T2DM. After full adjustment, inverse associations were observed of skimmed dairy (OR100 g 0·98; 95 % CI 0·97, 1·00), fermented dairy (OR100 g 0·98; 95 % CI 0·97, 0·99) and buttermilk (OR150 g 0·97; 95 % CI 0·94, 1·00) with pre-diabetes. Positive associations were observed for full-fat dairy (OR100 g 1·003; 95 % CI 1·01, 1·06), non-fermented dairy products (OR100 g 1·01; 95 % CI 1·00, 1·02) and custard (ORserving/150 g 1·13; 95 % CI 1·03, 1·24) with pre-diabetes. Moreover, full-fat dairy products (ORT3 1·16; 95 % CI 0·99, 1·35), non-fermented dairy products (OR100 g 1·05; 95 % CI 1·01, 1·09) and milk (ORserving/150 g 1·08; 95 % CI 1·02, 1·15) were positively associated with ND-T2DM. In conclusion, our data showed inverse associations of skimmed and fermented dairy products with pre-diabetes. Positive associations were observed for full-fat and non-fermented dairy products with pre-diabetes and ND-T2DM.

Association between Smoking Behavior Patterns and Glycated Hemoglobin Levels in a General Population

This study investigated the association of smoking behaviors, including dual smoking (smoking both cigarettes and e-cigarettes), cigarettes smoking, and previous smoking, with glycated hemoglobin (HbA1c) levels. National Health and Nutrition Examination Survey (KNHANES) data from 2014–2016 was used. Associations between smoking behavior patterns and HbA1c levels were analyzed via multiple regression. Among 8809 participants, individuals who were dual smokers and cigarettes smokers had significantly higher HbA1c levels than non-smokers (dual: β = 0.1116, p = 0.0012, single: β = 0.0752, p = 0.0022). This relationship strengthened in subgroups of men (dual: β = 0.1290, p = 0.0013, single: β = 0.1020, p = 0.0014, ex: β = 0.0654, p = 0.0308), physically inactive subjects (dual: β = 0.1527, p = 0.0053, single: β = 0.0876, p = 0.0197), and overweight (dual: β = 0.1425, p = 0.0133) and obese individuals (dual: β = 0.1694, p = 0.0061, single: β = 0.1035, p = 0.0217). This study suggests that smoking behaviors are likely to increase the risk of HbA1c level in a general population. The health effects of dual smoking remain uncertain and should be addressed in the future.

Discordance in glycemic categories and regression to normality at baseline in 10,000 people in a Type 2 diabetes prevention trial

The world diabetes population quadrupled between 1980 and 2014 to 422 million and the enormous impact of Type 2 diabetes is recognised by the recent creation of national Type 2 diabetes prevention programmes. There is uncertainty about how to correctly risk stratify people for entry into prevention programmes, how combinations of multiple 'at high risk' glycemic categories predict outcome, and how the large recently defined 'at risk' population based on an elevated glycosylated haemoglobin (HbA1c) should be managed. We identified all 141,973 people at highest risk of diabetes in our population, and screened 10,000 of these with paired fasting plasma glucose and HbA1c for randomisation into a very large Type 2 diabetes prevention trial. Baseline discordance rate between highest risk categories was 45.6%, and 21.3-37.0% of highest risk glycaemic categories regressed to normality between paired baseline measurements (median 40 days apart). Accurate risk stratification using both fasting plasma glucose and HbA1c data, the use of paired baseline data, and awareness of diagnostic imprecision at diagnostic thresholds would avoid substantial overestimation of the true risk of Type 2 diabetes and the potential benefits (or otherwise) of intervention, in high risk subjects entering prevention trials and programmes.

Cigarette Smoking and Hyperglycaemia in Diabetic Patients

BACKGROUND:

The incidence rate of diabetes mellitus has increased throughout the year. Various studies indicate that smoking may affect glucose metabolism and cause hyperglycemia in diabetes mellitus. This study aimed to compare the blood glucose and HbA1c level in diabetic smoking patients and non-smoking diabetic patients.

METHODS:

This study used the cross-sectional approach. The study population consisted of 30 diabetic smoking patients and 30 non-smoking diabetic patients. The diabetes history and the smoking status of the study population obtained by questionnaire-based interview, the blood glucose and HbA1c level were measured by hexokinase and immunoturbidimetry method using cobas 6000 analyser module c501 (Roche Diagnostics, Switzerland).

RESULTS:

The result in this study showed the fasting blood glucose, postprandial blood glucose, and HbA1c were higher by 23.64 mg/dl (p = 0.325), 58.00 mg/dl (p = 0.016), 0.39% (p = 0.412) in smoking diabetic patients compared to non-smoking diabetic patients. After statistical analysis, there was a significant difference (p < 0.05) of postprandial glucose level between smokers group and non-smokers group, but the non-significant difference of fasting blood glucose and HbA1c

CONCLUSIONS:

This study concluded that there was a significant difference in postprandial glucose level between smokers group and non-smokers group but the non-significant difference of fasting blood glucose and HbA1c.

The Interaction of Genetic Predisposition and Socioeconomic Position With Type 2 Diabetes Mellitus: Cross-Sectional and Longitudinal Analyses From the Lifelines Cohort and Biobank Study

OBJECTIVE

A strong genetic predisposition for type 2 diabetes mellitus (T2DM) may aggravate the negative effects of low socioeconomic position (SEP) in the etiology of the disorder. This study aimed to examine cross-sectional and longitudinal associations and interactions of a genetic risk score (GRS) and SEP with T2DM and to investigate whether clinical and behavioral risk factors can explain these associations and interactions.

METHODS

We used data from 13,027 genotyped participants from the Lifelines study. The GRS was based on single-nucleotide polymorphisms genome-wide associated with T2DM and was categorized into tertiles. SEP was measured as educational level. T2DM was based on biological markers, recorded medication use, and self-reports. Cross-sectional and longitudinal associations and interactions between the GRS and SEP on T2DM were examined.

RESULTS

The combination of a high GRS and low SEP had the strongest association with T2DM in cross-sectional (odds ratio = 3.84, 95% confidence interval = 2.28-6.46) and longitudinal analyses (hazard ratio = 2.71, 1.39-5.27), compared with a low GRS and high SEP. Interaction between a high GRS and a low SEP was observed in cross-sectional (relative excess risk due to interaction = 1.85, 0.65-3.05) but not in longitudinal analyses. Clinical and behavioral risk factors mostly explained the observed associations and interactions.

CONCLUSIONS

A high GRS combined with a low SEP provides the highest risk for T2DM. These factors also exacerbated each other's impact cross-sectionally but not longitudinally. Preventive measures should target individual and contextual factors of this high-risk group to reduce the risk of T2DM.

Red cell distribution width is associated with hemoglobin A1C elevation, but not glucose elevation

AIMS

To investigate the association between red cell distribution width (RDW) and elevation of glucose/glycated hemoglobin (HbA1c).

METHODS

An analysis was conducted using data from a prospective cohort study of adults. People without prediabetes or diabetes (n=7,795) were followed for a mean of 2.90years (range: 1-7years, 95% confidence interval: 2.86-2.94years). Glucose elevation is defined as fasting glucose levels exceeding 5.6mmol/l, or 2-hour glucose values in the oral glucose tolerance test exceeding 7.8mmol/l. HbA1c elevation is defined as a HbA1c value exceeding a normal limit of 39mmol/mol (5.7%). Adjusted Cox proportional hazards regression models were used to assess the association between RDW quartiles and elevation of HbA1c/glucose.

RESULTS

The multiple-adjusted hazard ratios (95% confidence interval) of HbA1c elevation for increased quartiles of RDW were 1.00 (reference), 1.08 (0.89, 1.30), 1.28 (1.07, 1.54), and 1.54 (1.29, 1.85) (P for trend<0.0001). However, no significant association was observed between RDW and blood glucose (fasting and postprandial).

CONCLUSIONS

Elevated RDW is independently related to future HbA1c elevation, but not to glucose elevation. This suggests that RDW may associate with HbA1c through a non-glycemic way, which should be taken into consideration when using HbA1c as a diagnostic criterion of prediabetes or diabetes.

Impact of demographics and disease progression on the relationship between glucose and HbA1c

CONTEXT

Several studies have shown that the relationship between mean plasma glucose (MPG) and glycated haemoglobin (HbA1c) may vary across populations. Especially race has previously been referred to shift the regression line that links MPG to HbA1c at steady-state (Herman & Cohen, 2012).

OBJECTIVE

To assess the influence of demographic and disease progression-related covariates on the intercept of the estimated linear MPG-HbA1c relationship in a longitudinal model.

DATA

Longitudinal patient-level data from 16 late-phase trials in type 2 diabetes with a total of 8927 subjects was used to study covariates for the relationship between MPG and HbA1c. The analysed covariates included age group, BMI, gender, race, diabetes duration, and pre-trial treatment. Differences between trials were taken into account by estimating a trial-to-trial variability component.

PARTICIPANTS

Participants included 47% females and 20% above 65years. 77% were Caucasian, 9% were Asian, 5% were Black and the remaining 9% were analysed together as other races.

ANALYSIS

Estimates of the change in the intercept of the MPG-HbA1c relationship due to the mentioned covariates were determined using a longitudinal model.

RESULTS

The analysis showed that pre-trial treatment with insulin had the most pronounced impact associated with a 0.34% higher HbA1c at a given MPG. However, race, diabetes duration and age group also had an impact on the MPG-HbA1c relationship.

CONCLUSION

Our analysis shows that the relationship between MPG and HbA1c is relatively insensitive to covariates, but shows small variations across populations, which may be relevant to take into account when predicting HbA1c response based on MPG measurements in clinical trials.

Higher body mass index and lower intake of dairy products predict poor glycaemic control among Type 2 Diabetes patients in Malaysia

This cross-sectional study was designed to determine factors contributing to glyceamic control in order to provide better understanding of diabetes management among Type 2 Diabetes patients. A pre-tested structured questionnaire was used to obtain information on socio-demographic and medical history. As a proxy measure for glycaemic control, glycosylated haemoglobin (HbA1c) was obtained as secondary data from the medical reports. Perceived self-care barrier on diabetes management, diet knowledge and skills, and diet quality were assessed using pretested instruments. With a response rate of 80.3%, 155 subjects were recruited for the study. Mean HbA1c level of the subjects was 9.02 ± 2.25% with more than 70% not able to achieve acceptable level in accordance to WHO recommendation. Diet quality of the subjects was unsatisfactory especially for vegetables, fruits, fish and legumes as well as from the milk and dairy products group. Higher body mass index (BMI), poorer medication compliance, lower diet knowledge and skill scores and lower intake of milk and dairy products contributed significantly on poor glycaemic control. In conclusion, while perceived self-care barriers and diet quality failed to predict HbA1c, good knowledge and skill ability, together with appropriate BMI and adequate intake of dairy products should be emphasized to optimize glycaemic control among type 2 diabetes patients.

Determinants of Glycated Hemoglobin in Subjects With Impaired Glucose Tolerance: Subanalysis of the Japan Diabetes Prevention Program

Background

Limited evidence is available about the relationship of lifestyle factors with glycated hemoglobin (HbA1c) in subjects with impaired glucose tolerance. The aim of study was to identify such determinant factors of HbA1c in subjects with impaired glucose tolerance.

Methods

This cross-sectional study included 121 men and 124 women with impaired glucose tolerance, who were diagnosed based on a 75-g oral glucose tolerance test. Demographic and biochemical parameters, including the body mass index (BMI), fasting plasma glucose (FPG), 2-h post-load glucose (2-h PG), and HbA1c, were measured. The pancreatic β-cell function and insulin resistance were assessed using homeostasis model assessment (HOMA-β). Dietary intake was assessed by a food frequency questionnaire.

Results

The levels of FPG, 2-h PG, and carbohydrate intake were correlated with the HbA1c level in men, while the FPG and 2-h PG levels were correlated with the HbA1c level in women. In multiple regression analyses, BMI, FPG, 2-h PG, and white rice intake were associated with HbA1c levels in men, while BMI, FPG, HOMA-β, and bread intake were associated with HbA1c levels in women.

Conclusions

The present findings suggest that a substantial portion of HbA1c may be composed of not only glycemic but also several lifestyle factors in men with impaired glucose tolerance. These factors can be taken into consideration as modifiable determinants in assessing the HbA1c level for the diagnosis and therapeutic monitoring of the disease course.

No Effect of the Thr92Ala Polymorphism of Deiodinase-2 on Thyroid Hormone Parameters, Health-Related Quality of Life, and Cognitive Functioning in a Large Population-Based Cohort Study

INTRODUCTION

The presence of the Thr92Ala polymorphism of deiodinase-2 (D2) has been thought to have several effects. It may influence its enzymatic function, is associated with increased expression of genes involved in oxidative stress in brain tissue, and may predict favorable response to combination levothyroxine (LT4) plus triiodothyronine (T3) therapy. It was hypothesized that homozygous carriers of the D2-92Ala allele have different thyroid hormone parameters, and reduced health-related quality of life (HRQoL) and cognitive functioning.

METHODS

In 12,625 participants from the LifeLines cohort study with genome-wide genetic data available, the effects of the Thr92Ala polymorphism (rs225014) were evaluated in the general population and in 364 people treated with thyroid hormone replacement therapy, the latter mainly because of primary hypothyroidism. In addition to evaluating anthropometric data, medication use, and existence of metabolic syndrome, HRQoL was assessed with the RAND 36-Item Health Survey, and the Ruff Figural Fluency Test was used as a sensitive test for executive functioning. Data on thyrotropin, free thyroxine (fT4), and free T3 (fT3) levels were available in a subset of 4479 participants.

RESULTS

The mean age (±standard deviation) was 53 ± 12 years and the body mass index was 27.0 ± 4.5 kg/m2 in the LT4 users compared with 48 ± 11 years and 26.2 ± 4.1 kg/m2 in participants from the general population. The Ala/Ala genotype of the D2-Thr92Ala polymorphism was present in 11.3% of LT4 users and in 10.7% of the general population. In total, 3742/4479 subjects with thyroid hormone data available had normal TSH (0.4-4.0 mIU/L), and 88% of LT4 users were females. LT4 users had higher fT4, lower fT3, and a lower fT3/fT4 ratio, and female patients had lower scores on the HRQoL domains of physical functioning, vitality, mental health, social functioning, bodily pain, and general health compared with those not using LT4 (p < 0.005). Executive functioning scores, as part of cognitive functioning, were comparable between female LT4 users and the general population. In both groups, the D2-Thr92Ala polymorphism was not associated with differences in TSH, fT4, fT3, the fT3/fT4 ratio, presence of metabolic syndrome or other comorbidities, use of medication, HRQoL, and cognitive functioning.

CONCLUSION

The Thr92Ala polymorphism of D2 was not associated with thyroid parameters, HRQoL, and cognitive functioning in the general population and in participants on thyroid hormone replacement therapy.

Eosinophil Count Is a Common Factor for Complex Metabolic and Pulmonary Traits and Diseases: The LifeLines Cohort Study

There is ongoing debate on the association between eosinophil count and diseases, as previous studies were inconsistent. We studied the relationship of eosinophil count with 22 complex metabolic, cardiac, and pulmonary traits and diseases. From the population-based LifeLines Cohort Study (N = 167,729), 13,301 individuals were included. We focused on relationship of eosinophil count with three classes of metabolic (7 traits, 2 diseases), cardiac (6 traits, 2 diseases), and pulmonary (2 traits, 2 diseases) outcomes. Regression analyses were applied in overall, women and men, while adjusted for age, sex, BMI and smoking. A p-value of <0.00076 was considered statistically significant. 58.2% of population were women (mean±SD 51.3±11.1 years old). In overall, one-SD higher of ln-eosinophil count was associated with a 0.04 (±SE ±0.002;p = 6.0×10⁻⁶) SD higher levels in ln-BMI, 0.06 (±0.007;p = 3.1×10⁻¹²) SD in ln-TG, 0.04 (±0.003;p = 7.0×10⁻⁶) SD in TC, 0.04 (±0.004;p = 6.3×10⁻⁷) SD in LDL, 0.04 (±0.006;p = 6.0×10⁻⁶) SD in HbA1c; and with a 0.05 (±0.004;p = 1.7×10⁻⁸) SD lower levels in HDL, 0.05 (±0.007;p = 3.4×10⁻²³) SD in FEV1, and 0.09 (±0.001;p = 6.6×10⁻²⁸) SD in FEV1/FVC. A higher ln-eosinophil count was associated with 1.18 (95%CI 1.09–1.28;p = 2.0×10⁻⁵) odds ratio of obesity, 1.29 (1.19–1.39;p = 1.1×10⁻¹⁰) of metabolic syndrome, 1.40 (1.25–1.56;p = 2.7×10⁻⁹) of COPD and 1.81 (1.61–2.03;p = 1.0×10⁻²³) of asthma. Similar results were found in women. We found no association between ln-eosinophil count either with blood pressure indices in overall, women and men; or with BMI, LDL, HbA1c and obesity in men. In a large population based cohort, we confirmed eosinophil count as a potential factor implicated in metabolic and pulmonary outcomes.

Association between Alcohol Intake and Hemoglobin A1c in the Korean Adults: The 2011-2013 Korea National Health and Nutrition Examination Survey

BACKGROUND

Although alcohol consumption is commonly encountered in clinical practice, few studies have investigated the clinical significance of alcohol intake on the use of the hemoglobin A1c (HbA1c) level.

OBJECTIVES

This study was performed to investigate the association between alcohol intake and HbA1c level in the general population.

METHODS

Among the 24,594 participants who participated in the 2011-2013 Korea National Health and Nutrition Examination Survey (KNHANES), 12,923 participants were analyzed in this study. We excluded diabetic patients currently taking antidiabetes medication. We compared the HbA1c level and proportions of patients with an HbA1c level of ≥5.7%, ≥6.1%, and ≥6.5% according to the fasting plasma glucose (FPG) concentration range and the amount of alcohol intake. The average amounts of daily alcohol intake were categorized into three groups: 0 g/day, <30 g/day, ≥30 g/day.

RESULTS

The mean HbA1c level was 5.65%, and the mean FPG concentration was 95.3 mg/dl. The percentages of patients with an HbA1c level of ≥5.7%, ≥6.1%, and ≥6.5% were 42.6%, 13.4%, and 4.5%, respectively. The average amount of alcohol intake was 12.3 g/day. The percentages of subjects with alcohol intake 0, <30, and ≥ 30 g/day were 16.5%, 69.7%, and 13.8%, respectively. There was a significant positive relationship between alcohol intake and FPG concentration (P < 0.001), the prevalence of impaired fasting glucose (P < 0.001), and the prevalence of diabetes (P < 0.001). However, there was no significant relationship between the alcohol intake and HbA1c level. Overall, the adjusted HbA1c levels decreased across alcohol intake (5.70% ± 0.01%, 5.66% ± 0.01%, and 5.55% ± 0.01%) after adjustment for confounding factors such as age, sex, FPG concentration, college graduation, smoking history, presence of hypertension, waist circumference, serum total cholesterol concentration, serum high-density lipoprotein cholesterol concentration, serum triglyceride concentration, presence of anemia, serum white blood cell count, and serum alanine aminotransferase concentration (P < 0.001). The adjusted proportions (%) of patients with an HbA1c level of ≥5.7% (P < 0.001), ≥6.1% (P < 0.001), and ≥6.5% (P < 0.001) showed significant negative trends across alcohol intake after adjustment for confounders. Logistic regression analyses showed that, when using the group that abstained as the control, the group that consumed ≥ 30g/day was negatively associated with the risk of an HbA1c level of ≥5.7% (P < 0.001), ≥6.1% (P < 0.001), and ≥6.5% (P < 0.001), using the above-mentioned variables as covariates.

CONCLUSIONS

Higher alcohol intake was associated with lower HbA1c levels, even after adjusting for confounding factors, including the FPG concentration, in this nationally representative sample of Korean adults. These results suggest that excessive drinking shifts the HbA1c level downward, which might complicate use of the HbA1c level for the diagnosis of diabetes or prediabetes.

Mechanistic modeling of hemoglobin glycation and red blood cell kinetics enables personalized diabetes monitoring

The amount of glycated hemoglobin (HbA1c) in diabetic patients' blood provides the best estimate of the average blood glucose concentration over the preceding 2 to 3 months. It is therefore essential for disease management and is the best predictor of disease complications. Nevertheless, substantial unexplained glucose-independent variation in HbA1c makes its reflection of average glucose inaccurate and limits the precision of medical care for diabetics. The true average glucose concentration of a nondiabetic and a poorly controlled diabetic may differ by less than 15 mg/dl, but patients with identical HbA1c values may have true average glucose concentrations that differ by more than 60 mg/dl. We combined a mechanistic mathematical model of hemoglobin glycation and red blood cell kinetics with large sets of within-patient glucose measurements to derive patient-specific estimates of nonglycemic determinants of HbA1c, including mean red blood cell age. We found that between-patient variation in derived mean red blood cell age explains all glucose-independent variation in HbA1c. We then used our model to personalize prospective estimates of average glucose and reduced errors by more than 50% in four independent groups of greater than 200 patients. The current standard of care provided average glucose estimates with errors >15 mg/dl for one in three patients. Our patient-specific method reduced this error rate to 1 in 10. Our personalized approach should improve medical care for diabetes using existing clinical measurements.

UVR protection influences fructosamine level after sun exposure of healthy adults

BACKGROUND

Seasonal variation in glycated hemoglobin levels has been observed, and sun exposure has been considered as one of the factors associated with this relationship. Fructosamine is a short-time marker of blood protein glycation.

AIM

We investigated the effect of seven days of sunbathing on blood fructosamine concentration in healthy volunteers using different ultraviolet radiation (UVR) protections.

MATERIALS AND METHODS

Participants were assigned to one of three groups: group A - used a UVA and UVB absorbing sunscreen (N = 15), group B - used a UVB absorbing sunscreen (N = 18), and group C - followed uncontrolled sun protection habits (N = 22).

RESULTS

Overall, the fructosamine concentration did not change after sun exposure (baseline 248.8 μmol/l, 25-75%: 238.5 to 258.8 μmol/l vs. after 247.3 μmol/l, 25-75%: 234.9 to 261.8 μmol/l, P = 0.6637). Median change of fructosamine differed significantly between groups (A: -1.90 μmol/l, 25-75%: -17.10 to 1.80 μmol/l vs. B: -3.80 μmol/l, 25-75%: -18.50 to 2.40 μmol/l vs. C: +4.05 μmol/l, 25-75%: -3.20 to 22.0 μmol/l; one-way ANOVAP = 0.0277). After age adjustment and combining groups A and B, the difference in change of fructosamine concentration was statistically significant between groups A + B (decrease) vs. group C (increase, P = 0.0193).

CONCLUSION

Appropriate sunscreen use during sunbathing resulted in decreased fructosamine concentrations, while inadequate UVR protection resulted in its increase.

Depressive symptoms and glycated hemoglobin A1c: a reciprocal relationship in a prospective cohort study

BACKGROUND

The aim of this study was to evaluate the dynamic association between depressive symptoms and glycated hemoglobin A1c (HbA1c) levels using data from the English Longitudinal Study of Ageing (ELSA).

METHOD

The sample was comprised of 2886 participants aged ⩾50 years who participated in three clinical assessments over an 8-year period (21% with prediabetes and 7% with diabetes at baseline). Structural equation models were used to address reciprocal associations between depressive symptoms and HbA1c levels and to evaluate the mediating effects of lifestyle-related behaviors and cardiometabolic factors.

RESULTS

We found a reciprocal association between depressive symptoms and HbA1c levels: depressive symptoms at one assessment point predicted HbA1c levels at the next assessment point (standardized β = 0.052) which in turn predicted depressive symptoms at the following assessment point (standardized β = 0.051). Mediation analysis suggested that both lifestyle-related behaviors and cardiometabolic factors might mediate the association between depressive symptoms and HbA1c levels: depressive symptoms at baseline predicted lifestyle-related behaviors and cardiometabolic factors at the next assessment, which in turn predicted HbA1c levels 4 years later. A similar association was observed for the other direction: HbA1c levels at baseline predicted lifestyle-related behaviors and cardiometabolic factors at the next assessment, which in turn predicted depressive symptoms 4 years later.

CONCLUSIONS

Our results suggest a dynamic relationship between depressive symptoms and HbA1c which might be mediated by both lifestyle and cardiometabolic factors. This has important implications for investigating the pathways which could link depressive symptoms and increased risk of diabetes.

Association between Self-Reported Smoking and Hemoglobin A1c in a Korean Population without Diabetes: The 2011-2012 Korean National Health and Nutrition Examination Survey

Background

Several Western studies have revealed that among non-diabetics, glycosylated hemoglobin A1c (HbA1c) levels are higher in smokers than non-smokers. While studies conducted in Western populations consistently support this association, a recent meta-analysis reported that studies carried out in non-Western populations, including studies of Chinese, Egyptian, and Japanese-Americans, did not detect any significant differences in HbA1c levels between smokers and non-smokers.

Objectives

We assessed the association between smoking habits and HbA1c levels in the general Korean adult population using data from the Korean National Health and Nutrition Examination Survey (KNHANES) performed in 2011–2012.

Methods

A total of 10,241 participants (weighted n=33,946,561 including 16,769,320 men and 17,177,241 women) without diabetes were divided into four categories according to their smoking habits: never smokers (unweighted n/ weighted n= 6,349/19,105,564), ex-smokers (unweighted n/ weighted n= 1,912/6,207,144), current light smokers (<15 cigarettes per day, unweighted n/ weighted n=1,205/5,130,073), and current heavy smokers (≥15 cigarettes per day, unweighted n/ weighted n=775/3,503,781).

Results

In age- and gender-adjusted comparisons, the HbA1c levels of each group were 5.52 ± 0.01% in non-smokers, 5.49 ± 0.01% in ex-smokers, 5.53 ± 0.01% in light smokers, and 5.61 ± 0.02% in heavy smokers. HbA1c levels were significantly higher in light smokers than in ex-smokers (p = 0.033), and in heavy smokers compared with light smokers (p < 0.001). The significant differences remained after adjusting for age, gender, fasting plasma glucose, heavy alcohol drinking, hematocrit, college graduation, and waist circumference. Linear regression analyses for HbA1c using the above-mentioned variables as covariates revealed that a significant association between current smoking and HbA1c (coefficient 0.021, 95% CI 0.003–0.039, p = 0.019).

Conclusions

Current smoking was independently associated with higher HbA1c levels in a cigarette exposure-dependent manner in a representative population of Korean non-diabetic adults. In this study, we have observed an association between smoking status and HbA1c levels in non-diabetics drawn from a non-Western population, consistent with previous findings in Western populations.

Modulation of red blood cell population dynamics is a fundamental homeostatic response to disease

Increased red blood cell (RBC) volume variation (RDW) has recently been shown to predict a wide range of mortality and morbidity: death due to cardiovascular disease, cancer, infection, renal disease, and more; complications in heart failure and coronary artery disease, advanced stage and worse prognosis in many cancers, poor outcomes in autoimmune disease, and many more. The mechanisms by which all of these diseases lead to increased RDW are unknown. Here we use a semi-mechanistic mathematical model of in vivo RBC population dynamics to dissect the factors controlling RDW and show that elevated RDW results largely from a slight reduction in the in vivo rate of RBC turnover. RBCs become smaller as they age, and a slight reduction in the rate of RBC turnover allows smaller cells to continue circulating, expanding the low-volume tail of the RBC population's volume distribution, and thereby increasing RDW. Our results show that mildly extended RBC lifespan is a previously unrecognized homeostatic adaptation common to a very wide range of pathologic states, likely compensating for subtle reductions in erythropoietic output. A mathematical model-based estimate of the clearance rate may provide a novel early-warning biomarker for a wide range of morbidity and mortality.

Glycated hemoglobin and long-term prognosis in patients with suspected stable angina pectoris without diabetes mellitus: a prospective cohort study

OBJECTIVE

Associations of glycated hemoglobin A1c (HbA1c) levels to incident coronary and cardiovascular events among non-diabetic patients with coronary artery disease are unclear. We investigated relations of HbA1c to long-term prognosis in such patients.

METHODS

A prospective cohort of 2519 patients undergoing elective coronary angiography for suspected stable angina pectoris (SAP) was divided into pre-defined categories according to HbA1c (%) levels (<5.0, 5.0-5.6 (reference), 5.7-6.4), and followed for median 4.9 years. The primary end-point was major coronary events (including non-fatal and fatal acute myocardial infarctions, and sudden cardiac death). Secondary end-points were death from cardiovascular disease (CVD) and all-cause mortality. Hazard ratios (HRs) (95% confidence intervals [CIs]) were obtained by Cox regression.

RESULTS

Median age at inclusion was 62 years, 73% were males, median HbA1c was 5.6% and random plasma-glucose 5.4 mmol/L. After multivariate adjustment, HbA1c levels within the pre-diabetic range were not associated with risk of major coronary events, HR (95% CI): 1.13 (0.79-1.62); P=0.49, death from CVD or all-cause mortality HR (95% CI): 0.95 (0.55-1.66) and 1.04 (0.70-1.53), respectively; P≥0.85. Similarly, there was no significant association between HbA1c values within the lowest category and risk of study outcomes, (P≥0.18).

CONCLUSION

In non-diabetic patients with suspected SAP, there was no overall association between HbA1c levels and prognosis, questioning an independent role of glycemia in the pathogenesis of atherosclerotic complications in these patients.

Associations of Plasma Kynurenines With Risk of Acute Myocardial Infarction in Patients With Stable Angina Pectoris

Objective—

Enhanced tryptophan degradation, induced by the proinflammatory cytokine interferon-γ, has been related to cardiovascular disease progression and insulin resistance. We assessed downstream tryptophan metabolites of the kynurenine pathway as predictors of acute myocardial infarction in patients with suspected stable angina pectoris. Furthermore, we evaluated potential effect modifications according to diagnoses of pre-diabetes mellitus or diabetes mellitus.

Approach and Results—

Blood samples were obtained from 4122 patients (median age, 62 years; 72% men) who underwent elective coronary angiography. During median follow-up of 56 months, 8.3% had acute myocardial infarction. Comparing the highest quartile to the lowest, for the total cohort, multivariable adjusted hazard ratios (95% confidence intervals) were 1.68 (1.21–2.34), 1.81 (1.33–2.48), 1.68 (1.21–2.32), and 1.48 (1.10–1.99) for kynurenic acid, hydroxykynurenine, anthranilic acid, and hydroxyanthranilic acid, respectively. The kynurenines correlated with phenotypes of the metabolic syndrome, and risk associations were generally stronger in subgroups classified with pre-diabetes mellitus or diabetes mellitus at inclusion ( P int ≤0.05). Evaluated in the total population, hydroxykynurenine and anthranilic acid provided statistically significant net reclassification improvements (0.21 [0.08–0.35] and 0.21 [0.07–0.35], respectively).

Conclusions—

In patients with suspected stable angina pectoris, elevated levels of plasma kynurenines predicted increased risk of acute myocardial infarction, and risk estimates were generally stronger in subgroups with evidence of impaired glucose homeostasis. Future studies should aim to clarify roles of the kynurenine pathway in atherosclerosis and glucose metabolism.

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.

Pleiotropic effects of lipid genes on plasma glucose, HbA1c, and HOMA-IR levels

Dyslipidemia is strongly associated with raised plasma glucose levels and insulin resistance (IR), and genome-wide association studies have identified 95 loci that explain a substantial proportion of the variance in blood lipids. However, the loci's effects on glucose-related traits are largely unknown. We have studied these lipid loci and tested their association collectively and individually with fasting plasma glucose (FPG), glycated hemoglobin (HbA1c), and IR in two independent cohorts: 10,995 subjects from LifeLines Cohort Study and 2,438 subjects from Prevention of Renal and Vascular Endstage Disease (PREVEND) study. In contrast to the positive relationship between dyslipidemia and glucose traits, the genetic predisposition to dyslipidemia showed a pleiotropic lowering effect on glucose traits. Specifically, the genetic risk score related to higher triglyceride level was correlated with lower levels of FPG (P = 9.6 × 10(-10) and P = 0.03 in LifeLines and PREVEND, respectively), HbA1c (P = 4.2 × 10(-7) in LifeLines), and HOMA of estimated IR (P = 6.2 × 10(-4) in PREVEND), after adjusting for blood lipid levels. At the single nucleotide polymorphism level, 15 lipid loci showed a pleiotropic association with glucose traits (P < 0.01), of which eight (CETP, MLXIPL, PLTP, GCKR, APOB, APOE-C1-C2, CYP7A1, and TIMD4) had opposite allelic directions of effect on dyslipidemia and glucose levels. Our findings suggest a complex genetic regulation and metabolic interplay between lipids and glucose.

Alpha- and beta-cell abnormalities in haemoglobin A1c-defined prediabetes and type 2 diabetes

New recommendations for the use of glycated haemoglobin A1c (HbA1c) to diagnose prediabetes and type 2 diabetes have changed the constitution of the two populations. We aimed to investigate the pathophysiological characteristics of individuals with HbA1c-defined prediabetes and type 2 diabetes, respectively. Ten subjects with HbA1c-defined prediabetes, i.e. HbA1c from 5.7 to 6.4 % (39-46 mmol/mol), eight newly diagnosed patients with HbA1c-defined type 2 diabetes [HbA1c ≥6.5 % (≥48 mmol/mol)], and ten controls with HbA1c lower than 5.7 % (<39 mmol/mol), were studied. Blood was sampled over 4 h on two separate days after a 75 g-oral glucose tolerance test and an isoglycaemic intravenous glucose infusion, respectively. Blood was analysed for glucose, insulin, C-peptide, glucagon, and incretin hormones. Insulinogenic index, disposition index, glucagon suppression, and incretin effect were evaluated. Subjects with HbA1c-defined prediabetes showed significantly lower insulinogenic index (P = 0.02), disposition index (P = 0.001), and glucagon suppression compared with controls; and similar (P = NS) insulinogenic index and glucagon suppression and higher disposition index (P = 0.02) compared to HbA1c-diagnosed type 2 diabetic patients. The patients with type 2 diabetes showed lower insulinogenic index (P = 0.0003), disposition index (P < 0.0001), and glucagon suppression compared with the controls. The incretin effect was significantly (P < 0.05) reduced in patients with HbA1c-defined type 2 diabetes compared to subjects with HbA1c-defined prediabetes and controls. Plasma levels of incretin hormones were similar across the three groups. HbA1c associated negatively with insulinogenic index, disposition index, and incretin effect. Our findings show clear alpha- and beta-cell dysfunction in HbA1c-defined type 2 diabetes compatible with the previously described pathophysiology of plasma glucose-defined type 2 diabetes. Furthermore, in HbA1c-defined prediabetes, we show defective insulin response in combination with inappropriate suppression of glucagon, which may constitute new targets for pharmacological interventions.

Bilirubin is an independent factor inversely associated with glycated hemoglobin level in pediatric patients with type 1 diabetes

OBJECTIVE

Bilirubin is a potent antioxidant, and serum total bilirubin (STB) concentrations correlate negatively with cardiovascular risk. In adult diabetic patients and in healthy adults, a negative correlation between STB and glycated hemoglobin (HbA1c) has been reported. We investigated whether there is such an association in children and adolescents with type 1 diabetes mellitus.

METHODS

The study group included 224 patients with type 1 diabetes duration of more than 12 months. Patients with suspected or confirmed hemolytic anemia or liver dysfunction were excluded.

RESULTS

A statistically significant negative correlation was found between STB and HbA1c (R = -0.15; p = 0.024), which retained its significance in multivariate analysis (β = -0.18, p = 0.005). Patients' age and daily insulin dose were positively correlated with HbA1c levels, whereas other variables included in the multivariate analysis [sex, diabetes duration, insulin regimen, C-peptide, hemoglobin, mean corpuscular hemoglobin concentration (MCHC), alanine transaminase (ALT), and aspartate transaminase (AST)] did not correlate with HbA1c. The mean HbA1c level in patients with STB >1.2 mg/dL (>21 µmol/L; the threshold for clinical diagnosis of Gilbert's syndrome) was lower than in patients with STB ≤1.2 mg/dL (≤21 µmol/L), and the mean difference was 0.63% (6.9 mmol/mol; 95% CI: 0.11-1.16%).

CONCLUSIONS

These results show that in young patients with type 1 diabetes, STB concentration is an independent factor inversely associated with HbA1c level. Further studies should investigate the background and long-term effects of this association.

Ethnic differences in glycemic markers in patients with type 2 diabetes

OBJECTIVE

Recent studies have reported hemoglobin A1c (HbA1c) differences across ethnic groups that could limit its use in clinical practice. The authors of the A1C-Derived Average Glucose study have advocated to report HbA1c in estimated average glucose (AG) equivalents. The aim of this study was to assess the relationships between HbA1c and the mean of three 7-point self-monitored blood glucose (BG) profiles, and to assess whether estimated AG is an accurate measure of glycemia in different ethnic groups.

RESEARCH DESIGN AND METHODS

We evaluated 1,879 participants with type 2 diabetes in the DURABLE trial who were 30 to 80 years of age, from 11 countries, and, according to self-reported ethnic origin, were Caucasian, of African descent (black), Asian, or Hispanic. We performed logistic regression of the relationship between the mean self-monitored BG and HbA1c, and estimated AG, according to ethnic background.

RESULTS

Baseline mean (SD) HbA1c was 9.0% (1.3) (75 [SD, 14] mmol/mol), and mean self-monitored BG was 12.1 mmol/L (3.1) (217 [SD, 55] mg/dL). In the clinically relevant HbA1c range of 7.0-9.0% (53-75 mmol/mol), non-Caucasian ethnic groups had 0.2-0.5% (2-6 mmol/mol) higher HbA1c compared with Caucasians for a given BG level. At the mean self-monitored BG levels≤11.6 mmol/L, estimated AG overestimated the actual average BG; at levels>11.6 mmol/L, estimated AG underestimated the actual BG levels.

CONCLUSIONS

For a given degree of glycemia, HbA1c levels vary among different ethnic groups. Ethnicity needs to be taken into account when using HbA1c to assess glycemic control or to set glycemic targets. Estimated AG is not a reliable marker for mean glycemia and therefore is of limited clinical value.