Sex and age affect agreement between fasting plasma glucose and glycosylated hemoglobin for diagnosis of dysglycemia

Multivariate reference and tolerance regions based on conditional transformation models: Application to glycemic markers

The reference interval is the most widely used medical decision-making, constituting a central tool in determining whether an individual is healthy or not. When the results of several continuous diagnostic tests are available for the same patient, their clinical interpretation is more reliable if a multivariate reference region (MVR) is available rather than multiple univariate reference intervals. MVRs, defined as regions containing 95% of the results of healthy subjects, extend the concept of the reference interval to the multivariate setting. However, they are rarely used in clinical practice owing to difficulties associated with their interpretability and the restrictions inherent to the assumption of a Gaussian distribution. Further statistical research is thus needed to make MVRs more applicable and easier for physicians to interpret. Since the joint distribution of diagnostic test results may well change with patient characteristics independent of disease status, MVRs adjusted for covariates are desirable. The present work introduces a novel formulation for MVRs based on multivariate conditional transformation models (MCTMs). Additionally, we take into account the estimation uncertainty of such MVRs by means of tolerance regions. These conditional MVRs imply no parametric restriction on the response, and potentially nonlinear continuous covariate effects can be estimated. MCTMs allow the estimation of the effects of covariates on the joint distribution of multivariate response variables and on these variables' marginal distributions, via the use of most likely transformation estimation. Our contributions proved reliable when tested with simulated data and for a real data application with two glycemic markers.

The Footprint of Type 1 Diabetes on Red Blood Cells: A Metabolomic and Lipidomic Study

The prevalence of diabetes type 1 (T1D) in the world populations is continuously growing. Although treatment methods are improving, the diagnostic is still symptom-based and sometimes far after onset of the disease. In this context, the aim of the study was the search of new biomarkers of the disease in red blood cells (RBCs), until now unexplored. The metabolomic and the lipidomic profile of RBCs from T1D patients and matched healthy controls was determined by NMR spectroscopy, and different multivariate discrimination models were built to select the metabolites and lipids that change most significantly. Relevant metabolites were further confirmed by univariate statistical analysis. Robust separation in the metabolomic and lipidomic profiles of RBCs from patients and controls was confirmed by orthogonal projection on latent structure discriminant analysis (OPLS-DA), random forest analysis, and significance analysis of metabolites (SAM). The main changes were detected in the levels of amino acids, organic acids, creatine and phosphocreatine, lipid change length, and choline derivatives, demonstrating changes in glycolysis, BCAA metabolism, and phospholipid metabolism. Our study proves that robust differences exist in the metabolic and lipidomic profile of RBCs from T1D patients, in comparison with matched healthy individuals. Some changes were similar to alterations found already in RBCs of T2D patients, but others seemed to be specific for type 1 diabetes. Thus, many of the metabolic differences found could be biomarker candidates for an earlier diagnosis or monitoring of patients with T1D.

Continuous Glucose Monitoring Time-in-Range and HbA1c Targets in Pregnant Women with Type 1 Diabetes

The CONCEPTT trial compared real-time Continuous Glucose Monitoring (RT-CGM) to capillary glucose monitoring in pregnant women with type 1 diabetes. We analyzed CGM and glycated hemoglobin (HbA_1c) measures in first (n = 221), second (n = 197), and third (n = 172) trimesters, aiming to examine target glucose attainment and associations with pregnancy outcomes. CGM targets were Time-in-range (TIR) > 70%, Time-above-range (TAR) <25%, and Time-below-range (TBR) < 4%, and HbA_1c targets < 6.5% (National Institute for Health and Care Excellence [NICE]) and HbA_1c < 6.0% in second and third trimesters (American Diabetes Association [ADA]). TIR/TAR/TBR targets were achieved by 7.7/14.5/30.3% participants in first, 10.2/14.2/52.8% in second, and 35.5/37.2/52.9% in third trimesters. CGM target attainment was low but increased during pregnancy and with RT-CGM use. In the adjusted analyses, achieving TBR target was associated with a higher risk of pre-eclampsia and neonatal hypoglycemia. ADA HbA_1c target attainment was low and unchanged during pregnancy (23.5/27.9/23.8%) but increased with RT-CGM use. In the adjusted analyses, HbA_1c target attainment was associated with a lower risk of preterm birth, large-for-gestational age and neonatal hypoglycemia. We conclude that CONCEPTT trial participants had a low rate of CGM and of HbA_1c target attainment. Attainment of CGM and NICE HbA_1c targets increased throughout gestation and all targets (both NICE/ADA HbA_1c and CGM) were more likely to be achieved by RT-CGM users, at 34 weeks' gestation. ADA HbA_1c target achievement was independently associated with better perinatal outcomes, while the independent association of TBR target achievement with increased risk warrants further study. ClinicalTrials.gov Registration Identifier NCT01788527.

Progression to diabetes by baseline glycemic status among middle-aged and older adults in the United States, 2006-2014

AIMS

Primary prevention studies have indicated that structured lifestyle change programs in adults with an annual diabetes risk of 4.7% are cost-effective. However, few population-based studies have quantified the risk of diabetes among adults with prediabetes.

METHODS

We used the nationally representative U.S. Health and Retirement Study to identify adults aged ≥ 52 years with prediabetes (A1c: 5.7% - 6.4%) in 2006 and followed them to 2014 to assess diabetes status defined by A1c ≥ 6.5% in 2010 or 2014 or by self-report of a diabetes diagnosis by various risk factors.

RESULTS

Among the 1,406 adults with prediabetes (average 4.7 years of follow-up), risk factors significantly associated with subsequent incident diabetes with adjusted annual risk of diabetes ≥ 4.7% were: male gender (4.8%); aged 52-64 years (5.0%); Black race (5.5%); obesity (body mass index (kg/m²) ≥ 30.0, 6.8%); large waist circumference (women: > 35 in.; men: > 40 in., 4.9%); C-reactive protein levels ≥ 3 ug/L (5.5%); treated for high cholesterol (4.7%); treated for hypertension (5.3%); and moderate mobility loss (4.8%).

CONCLUSIONS

Primary prevention interventions among adults with prediabetes who also have moderate mobility loss or well-known risk factors for diabetes are likely to be cost-effective.

A Translational In Vivo and In Vitro Metabolomic Study Reveals Altered Metabolic Pathways in Red Blood Cells of Type 2 Diabetes

Clinical parameters used in type 2 diabetes mellitus (T2D) diagnosis and monitoring such as glycosylated haemoglobin (HbA1c) are often unable to capture important information related to diabetic control and chronic complications. In order to search for additional biomarkers, we performed a pilot study comparing T2D patients with healthy controls matched by age, gender, and weight. By using ¹H-nuclear magnetic resonance (NMR) based metabolomics profiling of red blood cells (RBCs), we found that the metabolic signature of RBCs in T2D subjects differed significantly from non-diabetic controls. Affected metabolites included glutathione, 2,3-bisphophoglycerate, inosinic acid, lactate, 6-phosphogluconate, creatine and adenosine triphosphate (ATP) and several amino acids such as leucine, glycine, alanine, lysine, aspartate, phenylalanine and tyrosine. These results were validated by an independent cohort of T2D and control patients. An analysis of the pathways in which these metabolites were involved showed that energetic and redox metabolism in RBCs were altered in T2D, as well as metabolites transported by RBCs. Taken together, our results revealed that the metabolic profile of RBCs can discriminate healthy controls from T2D patients. Further research is needed to determine whether metabolic fingerprint in RBC could be useful to complement the information obtained from HbA1c and glycemic variability as well as its potential role in the diabetes management.