Biomarkers in diabetes:hemoglobin A1c, vascular and tissue markers

Biomarkers are conventionally defined as "biological molecules that represent health and disease states." They typically are measured in readily available body fluids (blood or urine), lie outside the causal pathway, are able to detect subclinical disease, and are used to monitor clinical and subclinical disease burden and response to treatments. Biomarkers can be "direct" endpoints of the disease itself, or "indirect" or surrogate endpoints. New technologies (such as metabolomics, proteomics, genomics) bring a wealth of opportunity to develop new biomarkers. Other new technologies enable the development of nonmolecular, functional, or biophysical tissue-based biomarkers. Diabetes mellitus is a complex disease affecting almost every tissue and organ system, with metabolic ramifications extending far beyond impaired glucose metabolism. Biomarkers may reflect the presence and severity of hyperglycemia (ie, diabetes itself) or the presence and severity of the vascular complications of diabetes. Illustrative examples are considered in this brief review. In blood, hemoglobin A1c (HbA1c) may be considered as a biomarker for the presence and severity of hyperglycemia, implying diabetes or prediabetes, or, over time, as a "biomarker for a risk factor," ie, hyperglycemia as a risk factor for diabetic retinopathy, nephropathy, and other vascular complications of diabetes. In tissues, glycation and oxidative stress resulting from hyperglycemia and dyslipidemia lead to widespread modification of biomolecules by advanced glycation end products (AGEs). Some of these altered species may serve as biomarkers, whereas others may lie in the causal pathway for vascular damage. New noninvasive technologies can detect tissue damage mediated by AGE formation: these include indirect measures such as pulse wave analysis (a marker of vascular dysfunction) and more direct markers such as skin autofluorescence (a marker of long-term accumulation of AGEs). In the future, we can be optimistic that new blood and tissue-based biomarkers will enable the detection, prevention, and treatment of diabetes and its complications long before overt disease develops.

Obesity during pregnancy on vagal tone, hemoglobin A1c, oxygenation, and perinatal outcomes

Purpose: To examine the effect of obesity and gestational weight gain on heart rate variability (HRV), oxygenation (HbO 2 and SpO2), hemoglobin A1c (HbA1c) and the frequency of pregnancy complications in obese (O) and non-obese (NO) women.^ Design: The study was an observational comparison study with a repeated measures design. ^ Setting: The setting was a low risk prenatal, university clinic located in a large southeastern metropolitan city. ^ Sample: The sample consisted of a volunteer group of 41 pregnant women who were observed at the three time points of 20, 28, and 36 weeks gestation. ^ Analysis: Analysis included general linear modeling with repeated measures to test for group differences with changes over time on vagal response, HbA1c, and oxygenation. Odds ratios were computed to compare the frequency of birth outcomes. ^ Findings: The interaction effect of time between O and NO women on HbO2 was significant. The mean HP, RSA, and HbO2 changed significantly over time within the NO women. The mean HbA 1c increased significantly over time within the O women. Women with excess gestational weight gain had significantly lower heart period than women with weight gain within the IOM recommendations. Obese women were more likely to have Group B streptococcal infections, gestational hypertension, give birth by cesarean or instrument assistance, and have at least one postnatal event. ^ Conclusions: Monitoring HRV, oxygenation, and HbA1c using minimally invasive measures may permit early identification of alterations in autonomic response. Implementation of interventions to promote vagal tone may help to reduce risks for adverse perinatal outcomes related to obesity. Future studies should examine the effect of obesity on the vagal response and perinatal outcomes. ^

Use of Hemoglobin A1C to Detect Haitian-Americans with Undiagnosed Type 2 Diabetes

OBJECTIVE: To evaluate the validity of hemoglobin A1C (A1C) as a diagnostic tool for type 2 diabetes and to determine the most appropriate A1C cutoff point for diagnosis in a sample of Haitian-Americans. SUBJECTS AND METHODS: Subjects (n = 128) were recruited from Miami-Dade and Broward counties, FL. Receiver operating characteristics (ROC) analysis was run in order to measure sensitivity and specificity of A1C for detecting diabetes at different cutoff points. RESULTS: The area under the ROC curve was 0.86 using fasting plasma glucose ≥ 7.0 mmol/L as the gold standard. An A1C cutoff point of 6.26% had sensitivity of 80% and specificity of 74%, whereas an A1C cutoff point of 6.50% (recommended by the American Diabetes Association – ADA) had sensitivity of 73% and specificity of 89%. CONCLUSIONS: A1C is a reliable alternative to fasting plasma glucose in detecting diabetes in this sample of Haitian-Americans. A cutoff point of 6.26% was the optimum value to detect type 2 diabetes.

Assessment of Two Diabetes Point-of-Care Analyzers Measuring Hemoglobin A1c in the Peruvian Amazon

Aims: Measurement of glycated hemoglobin (HbA1c) is an important indicator of glucose control over time. Point-of-care (POC) devices allow for rapid and convenient measurement of HbA1c, greatly facilitating diabetes care. We assessed two POC analyzers in the Peruvian Amazon where laboratory-based HbA1c testing is not available.

Methods: Venous blood samples were collected from 203 individuals from six different Amazonian communities with a wide range of HbA1c, 4.4-9.0% (25-75 mmol/mol). The results of the Afinion AS100 and the DCA Vantage POC analyzers were compared to a central laboratory using the Premier Hb9210 high-performance liquid chromatography (HPLC) method. Imprecision was assessed by performing 14 successive tests of a single blood sample.

Results: The correlation coefficient r for POC and HPLC results was 0.92 for the Afinion and 0.93 for the DCA Vantage. The Afinion generated higher HbA1c results than the HPLC (mean difference = +0.56% [+6 mmol/mol]; p < 0.001), as did the DCA Vantage (mean difference = +0.32% [4 mmol/mol]). The bias observed between POC and HPLC did not vary by HbA1c level for the DCA Vantage (p = 0.190), but it did for the Afinion (p < 0.001). Imprecision results were: CV = 1.75% for the Afinion, CV = 4.01% for the DCA Vantage. Sensitivity was 100% for both devices, specificity was 48.3% for the Afinion and 85.1% for the DCA Vantage, positive predictive value (PPV) was 14.4% for the Afinion and 34.9% for the DCA Vantage, and negative predictive value (NPV) for both devices was 100%. The area under the receiver operating characteristic (ROC) curve was 0.966 for the Afinion and 0.982 for the DCA Vantage. Agreement between HPLC and POC in classifying diabetes and prediabetes status was slight for the Afinion (Kappa = 0.12) and significantly different (McNemar’s statistic = 89; p < 0.001), and moderate for the DCA Vantage (Kappa = 0.45) and significantly different (McNemar’s statistic = 28; p < 0.001).

Conclusions: Despite significant variation of HbA1c results between the Afinion and DCA Vantage analyzers compared to HPLC, we conclude that both analyzers should be considered in health clinics in the Peruvian Amazon for therapeutic adjustments if healthcare workers are aware of the differences relative to testing in a clinical laboratory. However, imprecision and bias were not low enough to recommend either device for screening purposes, and the local prevalence of anemia and malaria may interfere with diagnostic determinations for a substantial portion of the population.

Seasonal variation of haemoglobin A1c in a Portuguese adult population

Haemoglobin A1c (Hb A1c) is routinely used for monitoring glycemic control in patients with diabetes. Hb A1c seasonal fluctuations can be directly related to different biological, geographical and cultural influences. Our purpose was to evaluate seasonal variation of Hb A1c in a hospital-based adult population over a period of 5 years.

Validation of the Chinese version of the Problem Areas in Diabetes (PAID-C) scale

OBJECTIVE To examine the psychometric properties of a Chinese version of the Problem Areas In Diabetes (PAID-C) scale. RESEARCH DESIGN AND METHODS The reliability and validity of the PAID-C were evaluated in a convenience sample of 205 outpatients with type 2 diabetes. Confirmatory factor analysis, Bland-Altman analysis, and Spearman's correlations facilitated the psychometric evaluation. RESULTS Confirmatory factor analysis confirmed a one-factor structure of the PAID-C (χ2/df ratio = 1.894, goodness-of-fit index = 0.901, comparative fit index = 0.905, root mean square error of approximation = 0.066). The PAID-C was associated with A1C (rs = 0.15; P < 0.05) and diabetes self-care behaviors in general diet (rs = −0.17; P < 0.05) and exercise (rs = −0.17; P < 0.05). The 4-week test-retest reliability demonstrated satisfactory stability (rs = 0.83; P < 0.01). CONCLUSIONS The PAID-C is a reliable and valid measure to determine diabetes-related emotional distress in Chinese people with type 2 diabetes.

Clinical outcomes, not clinical utility, should be the major consideration for saxagliptin with or without metformin

A recent review by Panagoulias and Doupis, published in Patient Preference and Adherence, concerned the saxagliptin/metformin fixed combination (SAXA/MET FDC), and was titled "Clinical utility in the treatment of type 2 diabetes with the saxagliptin/metformin fixed combination."1 This review concluded that "The SAXA/MET FDC is a patient-friendly, dosage-flexible, and hypoglycemia-safe regimen with very few adverse events and a neutral or even favorable effect on body weight. It achieves significant glycosylated hemoglobin A1c reduction helping the patient to achieve his/her individual glycemic goals."1

The OnTrack Diabetes web-based program for type 2 diabetes and dysphoria self-management: A randomized controlled trial protocol

Background: The prevalence of type 2 diabetes is rising with the majority of patients practicing inadequate disease self-management. Depression, anxiety, and diabetes-specific distress present motivational challenges to adequate self-care. Health systems globally struggle to deliver routine services that are accessible to the entire population, in particular in rural areas. Web-based diabetes self-management interventions can provide frequent, accessible support regardless of time and location Objective: This paper describes the protocol of an Australian national randomized controlled trial (RCT) of the OnTrack Diabetes program, an automated, interactive, self-guided Web program aimed to improve glycemic control, diabetes self-care, and dysphoria symptoms in type 2 diabetes patients. Methods: A small pilot trial is conducted that primarily tests program functionality, efficacy, and user acceptability and satisfaction. This is followed by the main RCT, which compares 3 treatments: (1) delayed program access: usual diabetes care for 3 months postbaseline followed by access to the full OnTrack Diabetes program; (2) immediate program: full access to the self-guided program from baseline onward; and (3) immediate program plus therapist support via Functional Imagery Training (FIT). Measures are administered at baseline and at 3, 6, and 12 months postbaseline. Primary outcomes are diabetes self-care behaviors (physical activity participation, diet, medication adherence, and blood glucose monitoring), glycated hemoglobin A1c (HbA1c) level, and diabetes-specific distress. Secondary outcomes are depression, anxiety, self-efficacy and adherence, and quality of life. Exposure data in terms of program uptake, use, time on each page, and program completion, as well as implementation feasibility will be conducted. Results: This trial is currently underway with funding support from the Wesley Research Institute in Brisbane, Australia. Conclusions: This is the first known trial of an automated, self-guided, Web-based support program that uses a holistic approach in targeting both type 2 diabetes self-management and dysphoria. Findings will inform the feasibility of implementing such a program on an ongoing basis, including in rural and regional locations.

Depression and Cognition in Type 2 Diabetes from a Life Course Perspective

Background: Type 2 diabetes is linked to several complications which add to both physical and mental distress. Depression is a common co-morbidity of diabetes which can occur both as a cause and a consequence of type 2 diabetes. Depression has been shown to correlate with glucose regulation and treating depression might prove beneficial for glucose regulation as well as for mental well being. Another complication which might affect diabetes management is cognitive decline. Several risk factors and complications of diabetes might modify the risk for developing cognitive impairment, which is increased 1.5 times among subjects with type 2 diabetes. Type 2 diabetes, depression and impaired cognitive performance have all been linked to low birth weight. This thesis aimed to explore the effects and interactions of birth weight, depression and cognitive ability in relation to type 2 diabetes from a life course perspective. Subjects and methods: Studies I, II and V were part of the Helsinki Birth Cohort Study. 2003 subjects participated in an extensive clinical examination at an average age of 61 years. A standard glucose tolerance test (OGTT) was performed and depressive symptoms were assessed using the Beck Depression Inventory (BDI). In addition data was obtained from child welfare clinics and national registers. A subset of the cohort (n=1247) also performed a test on cognitive performance (CogState ®) at the average age of 64. Studies III and IV were randomised clinical trials where mildly depressed diabetic subjects were treated with paroxetine or placebo and the effect on metabolic parameters and quality of life was assessed. The first trial included 14 women and lasted 10 weeks, while the second trial included 43 subjects, both men and women, and lasted 6 months. Results: Type 2 diabetes was positively associated with the occurrence of depressive symptoms. Among diabetic subjects 23.6% had depressive symptoms, compared to 16.7% of subjects with normal glucose tolerance (OR = 1.77, p<0.001). Formal mediation analysis revealed that cardiovascular disease (CVD) is likely to act as a mediator in the association. Furthermore, low birth weight was found to modify the association between type 2 diabetes, CVD and depression. The association between BDI score and having type 2 diabetes or CVD was twice as strong in the subgroup with low birth weight (≤ 2500g) compared with the group with birth weight > 2500g (p for interaction 0.058). In the six months long randomised clinical trial (study IV) paroxetine had a transient beneficial effect on glycosylated haemoglobin A1c (GHbA1c) and quality of life when compared to placebo after three months of treatment. In study V we found that subjects with known diabetes had a consistently poorer level of cognitive performance than subjects with normal glucose tolerance in most of the tested cognitive domains. This effect was further amplified among those born with a small birth weight (p for interaction 0.002). Conclusions: Type 2 diabetes is associated with a higher occurrence of depressive symptoms compared to subjects with normal glucose tolerance. This association is especially strong among subjects with CVD and those born with a low birth weight. Treating depressed diabetic subjects with paroxetine has no long term effect on glucose regulation. Physicians should be aware of depression as an important co-morbidity of type 2 diabetes. Both depression and the cognitive decline often seen among diabetic subjects are increased if the subject is born with a low birth weight. Physicians should recognise low birth weight as an additional risk factor and modifier of diabetic complications.

Molecular Epidemiology of HIV-1 Subtypes in India: Origin and Evolutionary History of the Predominant Subtype C

Background: India has the third largest HIV-1 epidemic with 2.4 million infected individuals. Molecular epidemiological analysis has identified the predominance of HIV-1 subtype C (HIV-1C). However, the previous reports have been limited by sample size, and uneven geographical distribution. The introduction of HIV-1C in India remains uncertain due to this lack of structured studies. To fill the gap, we characterised the distribution pattern of HIV-1 subtypes in India based on data collection from nationwide clinical cohorts between 2007 and 2011. We also reconstructed the time to the most recent common ancestor (tMRCA) of the predominant HIV-1C strains. Methodology/Principal Findings: Blood samples were collected from 168 HIV-1 seropositive subjects from 7 different states. HIV-1 subtypes were determined using two or three genes, gag, pol, and env using several methods. Bayesian coalescent-based approach was used to reconstruct the time of introduction and population growth patterns of the Indian HIV-1C. For the first time, a high prevalence (10%) of unique recombinant forms (BC and A1C) was observed when two or three genes were used instead of one gene (p<0.01; p = 0.02, respectively). The tMRCA of Indian HIV-1C was estimated using the three viral genes, ranged from 1967 (gag) to 1974 (env). Pol-gene analysis was considered to provide the most reliable estimate 1971, (95% CI: 1965-1976)]. The population growth pattern revealed an initial slow growth phase in the mid-1970s, an exponential phase through the 1980s, and a stationary phase since the early 1990s. Conclusions/Significance: The Indian HIV-1C epidemic originated around 40 years ago from a single or few genetically related African lineages, and since then largely evolved independently. The effective population size in the country has been broadly stable since the 1990s. The evolving viral epidemic, as indicated by the increase of recombinant strains, warrants a need for continued molecular surveillance to guide efficient disease intervention strategies.

STAR 3 randomized controlled trial to compare sensor-augmented insulin pump therapy with multiple daily injections in the treatment of type 1 diabetes: research design, methods, and baseline characteristics of enrolled subjects.

BACKGROUND: Sensor-augmented pump therapy (SAPT) integrates real-time continuous glucose monitoring (RT-CGM) with continuous subcutaneous insulin infusion (CSII) and offers an alternative to multiple daily injections (MDI). Previous studies provide evidence that SAPT may improve clinical outcomes among people with type 1 diabetes. Sensor-Augmented Pump Therapy for A1c Reduction (STAR) 3 is a multicenter randomized controlled trial comparing the efficacy of SAPT to that of MDI in subjects with type 1 diabetes. METHODS: Subjects were randomized to either continue with MDI or transition to SAPT for 1 year. Subjects in the MDI cohort were allowed to transition to SAPT for 6 months after completion of the study. SAPT subjects who completed the study were also allowed to continue for 6 months. The primary end point was the difference between treatment groups in change in hemoglobin A1c (HbA1c) percentage from baseline to 1 year of treatment. Secondary end points included percentage of subjects with HbA1c < or =7% and without severe hypoglycemia, as well as area under the curve of time spent in normal glycemic ranges. Tertiary end points include percentage of subjects with HbA1c < or =7%, key safety end points, user satisfaction, and responses on standardized assessments. RESULTS: A total of 495 subjects were enrolled, and the baseline characteristics similar between the SAPT and MDI groups. Study completion is anticipated in June 2010. CONCLUSIONS: Results of this randomized controlled trial should help establish whether an integrated RT-CGM and CSII system benefits patients with type 1 diabetes more than MDI.

Study protocol: the Adherence and Intensification of Medications (AIM) study--a cluster randomized controlled effectiveness study.

BACKGROUND: Many patients with diabetes have poor blood pressure (BP) control. Pharmacological therapy is the cornerstone of effective BP treatment, yet there are high rates both of poor medication adherence and failure to intensify medications. Successful medication management requires an effective partnership between providers who initiate and increase doses of effective medications and patients who adhere to the regimen. METHODS: In this cluster-randomized controlled effectiveness study, primary care teams within sites were randomized to a program led by a clinical pharmacist trained in motivational interviewing-based behavioral counseling approaches and authorized to make BP medication changes or to usual care. This study involved the collection of data during a 14-month intervention period in three Department of Veterans Affairs facilities and two Kaiser Permanente Northern California facilities. The clinical pharmacist was supported by clinical information systems that enabled proactive identification of, and outreach to, eligible patients identified on the basis of poor BP control and either medication refill gaps or lack of recent medication intensification. The primary outcome is the relative change in systolic blood pressure (SBP) measurements over time. Secondary outcomes are changes in Hemoglobin A1c, low-density lipoprotein cholesterol (LDL), medication adherence determined from pharmacy refill data, and medication intensification rates. DISCUSSION: Integration of the three intervention elements--proactive identification, adherence counseling and medication intensification--is essential to achieve optimal levels of control for high-risk patients. Testing the effectiveness of this intervention at the team level allows us to study the program as it would typically be implemented within a clinic setting, including how it integrates with other elements of care. TRIAL REGISTRATION: The ClinicalTrials.gov registration number is NCT00495794.