Multiple biomarker prediction of type 2 diabetes

Bibliometric analysis of research on the utilization of nanotechnology in diabetes mellitus and its complications

Aim: To identify hotspots in this field and provide insights into future research directions. Methods: Publications were retrieved from the Web of Science Core Collection database. R Bibliometrix software, VOSviewer and CiteSpace were used to perform the bibliometric and visualization analyses. Results: The analysis comprised 468 publications from 58 countries, with the United States, China and India being the leading contributors. 'Gene therapy', 'nanoparticles' and 'insulin therapy' are the primary focuses. 'Green synthesis', 'cytotoxicity', 'bioavailability' and 'diabetic foot ulcers' have gained prominence, signifying high-intensity areas of interest expected to persist as favored research topics in the future. Conclusion: This study delves into recent frontiers and topical research directions and provides valuable references for further research in this field.

Nonlinear Relationship Between AST-to-ALT Ratio and the Incidence of Type 2 Diabetes Mellitus: A Follow-Up Study

Background

The aspartate aminotransferase (AST) to alanine aminotransferase (ALT) ratio has been demonstrated to be associated with insulin resistance and metabolic syndrome. However, few studies have directly explored the association between the AST/ALT ratio and the incidence of type 2 diabetes mellitus (T2DM). As such, the present study aimed to investigate the relationship between the AST/ALT ratio and incident T2DM during follow-up in a population-based cohort.

Methods

This retrospective cohort analysis included 15,464 Japanese males and females without DM at baseline between 2004 and 2015. The association between AST/ALT ratio and T2DM was retrospectively examined using the Cox proportional hazard model after adjusting for multiple potential confounders.

Results

After follow-up, 373 (2.41%) patients developed T2DM. A nonlinear relationship between the AST/ALT ratio and T2DM was observed after adjusting for potential confounders. The risk for developing T2DM decreased with AST/ALT ratio up to a threshold of 0.93 (adjusted hazard ratio [HR] 0.14 [95% confidence interval (CI) = 0.02-0.90; P = 0.0385]). An AST/ALT ratio >0.93 was not associated with the risk for developing T2DM (adjusted HR = 0.67, 95% CI = 0.17-2.65; P = 0.5718).

Conclusion

The AST/ALT ratio was associated with a lower incidence of T2DM in a nonlinear pattern. The threshold AST/ALT ratio for developing T2DM was 0.93. AST/ALT levels were inversely correlated with the occurrence of T2DM when AST/ALT ratio ≤0.93.

Salivary resistin level and its association with insulin resistance in obese individuals

The escalating global burden of type 2 diabetes mellitus necessitates the implementation of strategies that are both more reliable and faster in order to improve the early identification of insulin resistance (IR) in high-risk groups, including overweight and obese individuals. The use of salivary biomarkers offers a promising alternative to serum collection because it is safer, more comfortable, and less painful to obtain saliva samples. As obesity is the foremost contributory factor in IR development, the adipocytokines such as leptin, adiponectin, resistin, and visfatin secreted from the adipose tissue have been studied as potential reliable biomarkers for IR. Measurement of salivary adipokines as predictors for IR has attracted widespread attention because of the strong correlation between their blood and salivary concentrations. One of the adipokines that is closely related to IR is resistin. However, there are conflicting findings on resistin’s potential role as an etiological link between obesity and IR and the reliability of measuring salivary resistin as a biomarker for IR. Hence this study reviewed the available evidence on the potential use of salivary resistin as a biomarker for IR in order to attempt to gain a better understanding of the role of resistin in the development of IR in obese individuals.

Multiple Biomarkers Improved Prediction for the Risk of Type 2 Diabetes Mellitus in Singapore Chinese Men and Women

BACKGROUND

Multiple biomarkers have performed well in predicting type 2 diabetes mellitus (T2DM) risk in Western populations. However, evidence is scarce among Asian populations.

METHODS

Plasma triglyceride-to-high density lipoprotein (TG-to-HDL) ratio, alanine transaminase (ALT), high-sensitivity C-reactive protein (hs-CRP), ferritin, adiponectin, fetuin-A, and retinol-binding protein 4 were measured in 485 T2DM cases and 485 age-and-sex matched controls nested within the prospective Singapore Chinese Health Study cohort. Participants were free of T2DM at blood collection (1999 to 2004), and T2DM cases were identified at the subsequent follow-up interviews (2006 to 2010). A weighted biomarker score was created based on the strengths of associations between these biomarkers and T2DM risks. The predictive utility of the biomarker score was assessed by the area under receiver operating characteristics curve (AUC).

RESULTS

The biomarker score that comprised of four biomarkers (TG-to-HDL ratio, ALT, ferritin, and adiponectin) was positively associated with T2DM risk (P trend <0.001). Compared to the lowest quartile of the score, the odds ratio was 12.0 (95% confidence interval [CI], 5.43 to 26.6) for those in the highest quartile. Adding the biomarker score to a base model that included smoking, history of hypertension, body mass index, and levels of random glucose and insulin improved AUC significantly from 0.81 (95% CI, 0.78 to 0.83) to 0.83 (95% CI, 0.81 to 0.86; P=0.002). When substituting the random glucose levels with glycosylated hemoglobin in the base model, adding the biomarker score improved AUC from 0.85 (95% CI, 0.83 to 0.88) to 0.86 (95% CI, 0.84 to 0.89; P=0.032).

CONCLUSION

A composite score of blood biomarkers improved T2DM risk prediction among Chinese.

Application of a novel sex independent anthropometric index, termed angle index, in relation to type 2 diabetes: a Trinidadian case-control study

OBJECTIVE

To develop a novel sex independent anthropometric index, termed as angle index, related to type 2 diabetes.

DESIGN

Case-control.

PARTICIPANTS

The study comprised 121 participants and were divided into two groups. One group had no form of diabetes and served as controls (n=50). The other group had the condition of type 2 diabetes (n=71). 31% (n=37) of the subjects were male and 69% (n=84) were female. 62% (n=75) of the subjects were of East Indian ethnicity, 28% (n=34) were of African ethnicity and 10% (n=12) were of mixed ethnicity.

SETTING

Participants of the study were from the island of Trinidad, located in the Caribbean. Patients in the study were selected at random from hospital records.

PRIMARY OUTCOME MEASURE

It was hypothesised that the mean angle index of patients with type 2 diabetes would be higher than the mean angle index of patients without type 2 diabetes.

RESULTS

Patients with type 2 diabetes had a significantly higher angle index value as compared with controls (p<0.001). Angle index was the superior sex independent anthropometric index in relation to type 2 diabetes (area under the curve=0.72; p<0.001) as compared with other sex independent variables. Angle index correlated with glycated haemoglobin (r_s=0.28, p=0.003) and fasting blood glucose (r_s=0.31, p=0.001) levels. Patients with type 2 diabetes were four times more likely to have an angle index greater than 184° (OR 4.2, 95% CI 1.8 to 9.9) as compared with controls.

CONCLUSION

Angle index was a superior sex independent index for discriminating between patients with and without type 2 diabetes, as compared with waist circumference, abdominal volume index, conicity index, blood pressure readings, triglyceride levels and very low-density lipoprotein levels.

Precision medicine in type 2 diabetes

The Precision Medicine Initiative defines precision medicine as 'an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment and lifestyle for each person'. This approach will facilitate more accurate treatment and prevention strategies in contrast to a one-size-fits-all approach, in which disease treatment and prevention strategies are developed for generalized usage. Diabetes is clearly more heterogeneous than the conventional subclassification into type 1 and type 2 diabetes. Monogenic forms of diabetes like MODY and neonatal diabetes have paved the way for precision medicine in diabetes, as carriers of unique mutations require unique treatment. Diagnosis of diabetes in the past has been dependent upon measuring one metabolite, glucose. By instead including six variables in a clustering analysis, we could break down diabetes into five distinct subgroups, with better prediction of disease progression and outcome. The severe insulin-resistant diabetes (SIRD) cluster showed the highest risk of kidney disease and highest prevalence of nonalcoholic fatty liver disease, whereas patients in the insulin-deficient cluster 2 (SIDD) had the highest risk of retinopathy. In the future, this will certainly be improved and expanded by including genetic, epigenetic and other biomarker to allow better prediction of outcome and choice of more precise treatment.

Exposure to Environmental and Occupational Particulate Air Pollution as a Potential Contributor to Neurodegeneration and Diabetes: A Systematic Review of Epidemiological Research

It has been hypothesised that environmental air pollution, especially airborne particles, is a risk factor for type 2 diabetes mellitus (T2DM) and neurodegenerative conditions. However, epidemiological evidence is inconsistent and has not been previously evaluated as part of a systematic review. Our objectives were to carry out a systematic review of the epidemiological evidence on the association between long-term exposure to ambient air pollution and T2DM and neurodegenerative diseases in adults and to identify if workplace exposures to particles are associated with an increased risk of T2DM and neurodegenerative diseases. Assessment of the quality of the evidence was carried out using the GRADE system, which considers the quality of the studies, consistency, directness, effect size, and publication bias. Available evidence indicates a consistent positive association between ambient air pollution and both T2DM and neurodegeneration risk, such as dementia and a general decline in cognition. However, corresponding evidence for workplace exposures are lacking. Further research is required to identify the link and mechanisms associated with particulate exposure and disease pathogenesis and to investigate the risks in occupational populations. Additional steps are needed to reduce air pollution levels and possibly also in the workplace environment to decrease the incidence of T2DM and cognitive decline.

Diagnostic Accuracy of Protein Glycation Sites in Long-Term Controlled Patients with Type 2 Diabetes Mellitus and Their Prognostic Potential for Early Diagnosis

Current screening tests for type 2 diabetes mellitus (T2DM) identify less than 50% of undiagnosed T2DM patients and provide no information about how the disease will develop in prediabetic patients. Here, twenty-nine protein glycation sites were quantified after tryptic digestion of plasma samples at the peptide level using tandem mass spectrometry and isotope-labelled peptides as internal standard. The glycation degrees were determined in three groups, i.e., 48 patients with a duration of T2DM exceeding ten years, 48 non-diabetic individuals matched for gender, BMI, and age, and 20 prediabetic men. In long-term controlled diabetic patients, 27 glycated peptides were detected at significantly higher levels, providing moderate diagnostic accuracies (ACCs) from 61 to 79%, allowing a subgrouping of patients in three distinct clusters. Moreover, a feature set of one glycated peptides and six established clinical parameters provided an ACC of 95%. The same number of clusters was identified in prediabetic males (ACC of 95%) using a set of eight glycation sites (mostly from serum albumin). All patients present in one cluster showed progression of prediabetic state or advanced towards diabetes in the following five years. Overall, the studied glycation sites appear to be promising biomarkers for subgrouping prediabetic patients to estimate their risk for the development of T2DM.

Assessment of Salivary Adipokines Resistin, Visfatin, and Ghrelin as Type 2 Diabetes Mellitus Biomarkers

Type 2 diabetes mellitus (T2DM) is emerging as a metabolic epidemic worldwide. Pathologically, dysregulation of many biological pathways precedes hyperglycemia and the clinical diagnosis of T2DM. Changing trajectories along the process of T2DM development necessitates frequent measurement of biomarkers for early identification of at-risk individuals and successful prevention. Increase in circulating inflammatory adipokines has been suggested as predictive of T2DM. Human saliva is an easily accessible biospecimen amenable for painless frequent collection and possesses nearly 50% of serum proteome. In this study, we measured the adipokines resistin, visfatin, TNF-α, and ghrelin as markers for T2DM in unstimulated whole saliva (UWS) using specific assay kits. Resistin and visfatin concentrations were significantly higher in T2DM saliva. Although the concentration of acylated or unacylated ghrelin was lower in diabetic saliva, the decrease was not significant. Since resistin and visfatin are biomarkers integral to T2DM pathology, their salivary assessments may receive clinical acceptance.

Global aetiology and epidemiology of type 2 diabetes mellitus and its complications

Globally, the number of people with diabetes mellitus has quadrupled in the past three decades, and diabetes mellitus is the ninth major cause of death. About 1 in 11 adults worldwide now have diabetes mellitus, 90% of whom have type 2 diabetes mellitus (T2DM). Asia is a major area of the rapidly emerging T2DM global epidemic, with China and India the top two epicentres. Although genetic predisposition partly determines individual susceptibility to T2DM, an unhealthy diet and a sedentary lifestyle are important drivers of the current global epidemic; early developmental factors (such as intrauterine exposures) also have a role in susceptibility to T2DM later in life. Many cases of T2DM could be prevented with lifestyle changes, including maintaining a healthy body weight, consuming a healthy diet, staying physically active, not smoking and drinking alcohol in moderation. Most patients with T2DM have at least one complication, and cardiovascular complications are the leading cause of morbidity and mortality in these patients. This Review provides an updated view of the global epidemiology of T2DM, as well as dietary, lifestyle and other risk factors for T2DM and its complications.

Investigating Molecular Connections of Non-alcoholic Fatty Liver Disease with Associated Pathological Conditions in West Virginia for Biomarker Analysis

Non-alcoholic fatty liver disease (NAFLD) is a disease characterized by a steatosis of the liver that may progress to more serious pathological conditions including: nonalcoholic steatohepatitis (NASH), fibrosis, and cirrhosis. As the prevalence of NAFLD has increased worldwide in recent years, pathophysiology and risk factors associated with disease progression of NAFLD are at the focus of many studies. NAFLD is related to and shares common serum biomarkers with cardiovascular disease (CVD), type 2 diabetes mellitus (T2DM), obesity, and metabolic syndrome (MetS). West Virginia (WV) is a state with some of the highest rates of CVD, obesity and diabetes mellitus. As NAFLD is closely related to these diseases, it is of particular interest in WV. Currently there is no cost-effective, standardized method used clinically to detect NAFLD prior to the onset of reversible complications. At this time, the diagnosis of NAFLD is made with costly radiologic studies and invasive biopsy. These studies are only diagnostic once changes to hepatic tissue have occurred. The diagnosis of NAFLD by traditional methods may not allow for successful intervention and may not be readily available in areas with already sparse medical resources. In this literature review, we identify a list of biomarkers common among CVD, T2DM, obesity, MetS and NAFLD. From this research we propose the following biomarkers are good candidates for inclusion in a panel of biomarkers for the early detection of NAFLD: adiponectin, AST, ALT, apo-B, CK18, CPS1, CRP, FABP-1, ferritin, GGT, GRP78, HDL-C, IGF-1, IL-1β, 6, 8, 10, IRS-2PAI-1, leptin, lumican, MDA SREBP-1c and TNF-α. Creating and implementing a biomarker panel for the early detection and attenuation of NAFLD, prior to the onset of irreversible complication would provide maximum benefit and decrease the disease burden on the patients and healthcare system of WV.

Skin Deep: Enhanced Variable May Help Explain Racial Disparities in Type 2 Diabetes and Prediabetes

INTRODUCTION

The study refined definitions of type 2 diabetes and prediabetes (Pre-/T2D) via its four-category outcome variable. Respondents were identified as Pre-/T2D on the basis of (a) doctor's diagnosis only (i.e., managed Pre-/T2D); (b) biomarker only (i.e., undiagnosed Pre-/T2D); or (c) both diagnosis and biomarker (i.e., unmanaged Pre-/T2D). The reference was Pre-/T2D not indicated. We linked the outcome to social structural and social support factors, health care-related factors, mental disorder, and lifestyle variables, for each racial/ethnic group.

METHODS

We used the 2011-2012 and 2013-2014 National Health and Nutrition Examination Surveys to measure the four-category outcome and examine race/ethnicity's role in explaining the outcome.

RESULTS

We found Pre-/T2D to be associated with age, BMI, physical activity, income, education, receiving health services, and other factors. A moderating role for race/ethnicity was also confirmed.

CONCLUSION

The racial disparities observed in our three main categories generally resulted from high levels of undiagnosed Pre-/T2D and high levels of diagnosed but unmanaged Pre-T2D. Race/ethnicity's moderating role generally indicated that, through the factors BMI, age, and receiving health services, minority status (with its attendant disadvantages) could facilitate undiagnosed Pre-/T2D as well as Pre-/T2D indicated concurrently by diagnosis and biomarker.

Glycated lysine-141 in haptoglobin improves the diagnostic accuracy for type 2 diabetes mellitus in combination with glycated hemoglobin HbA1c and fasting plasma glucose

BACKGROUND

Recent epidemiological studies indicate that only 30-50% of undiagnosed type 2 diabetes mellitus (T2DM) patients are identified using glycated hemoglobin (HbA1c) and elevated fasting plasma glucose (FPG) levels. Thus, novel biomarkers for early diagnosis and prognosis are urgently needed for providing early and personalized treatment.

METHODS

Here, we studied the glycation degrees of 27 glycation sites representing nine plasma proteins in 48 newly diagnosed male T2DM patients and 48 non-diabetic men matched for age (range 35-65 years). Samples were digested with trypsin and enriched for glycated peptides using boronic acid affinity chromatography. Quantification relied on mass spectrometry (multiple reaction monitoring) using isotope-labelled peptides as internal standard.

RESULTS

The combination of glycated lysine-141 of haptoglobin (HP K141) and HbA1c provided a sensitivity of 94%, a specificity of 98%, and an accuracy of 96% to identify T2DM. A set of 15 features considering three glycation sites in human serum albumin, HP K141, and 11 routine laboratory measures of T2DM, metabolic syndrome, obesity, inflammation, and insulin resistance provided a sensitivity of 98%, a specificity of 100%, and an accuracy of 99% for newly diagnosed T2DM patients.

CONCLUSIONS

Our studies demonstrated the great potential of glycation sites in plasma proteins providing an additional diagnostic tool for T2DM and elucidating that the combination of these sites with HbA1c and FPG could improve the diagnosis of T2DM.

Use of Biomarkers in Predicting the Onset, Monitoring the Progression, and Risk Stratification for Patients with Type 2 Diabetes Mellitus

BACKGROUND

As the worldwide prevalence of type 2 diabetes mellitus (T2DM) increases, it is even more important to develop cost-effective methods to predict and diagnose the onset of diabetes, monitor progression, and risk stratify patients in terms of subsequent cardiovascular and diabetes complications.

CONTENT

Nonlaboratory clinical risk scores based on risk factors and anthropomorphic data can help identify patients at greatest risk of developing diabetes, but glycemic indices (hemoglobin A1c, fasting plasma glucose, and oral glucose tolerance tests) are the cornerstones for diagnosis, and the basis for monitoring therapy. Although family history is a strong predictor of T2DM, only small populations of patients carry clearly identifiable genetic mutations. Better modalities for detection of insulin resistance would improve earlier identification of dysglycemia and guide effective therapy based on therapeutic mechanisms of action, but improved standardization of insulin assays will be required. Although clinical risk models can stratify patients for subsequent cardiovascular risk, the addition of cardiac biomarkers, in particular, high-sensitivity troponin and natriuretic peptide provide, significantly improves model performance and risk stratification.

CONCLUSIONS

Much more research, prospectively planned and with clear treatment implications, is needed to define novel biomarkers that better identify the underlying pathogenic etiologies of dysglycemia. When compared with traditional risk features, biomarkers provide greater discrimination of future risk, and the integration of cardiac biomarkers should be considered part of standard risk stratification in patients with T2DM.

Fingerprinting of Peptides with a Large Channel of Bacteriophage Phi29 DNA Packaging Motor

Nanopore technology has become a highly sensitive and powerful tool for single molecule sensing of chemicals and biopolymers. Protein pores have the advantages of size amenability, channel homogeneity, and fabrication reproducibility. But most well-studied protein pores for sensing are too small for passage of peptide analytes that are typically a few nanometers in dimension. The funnel-shaped channel of bacteriophage phi29 DNA packaging motor has previously been inserted into a lipid membrane to serve as a larger pore with a narrowest N-terminal constriction of 3.6 nm and a wider C-terminal end of 6 nm. Here, the utility of phi29 motor channel for fingerprinting of various peptides using single molecule electrophysiological assays is reported. The translocation of peptides is proved unequivocally by single molecule fluorescence imaging. Current blockage percentage and distinctive current signatures are used to distinguish peptides with high confidence. Each peptide generated one or two distinct current blockage peaks, serving as typical fingerprint for each peptide. The oligomeric states of peptides can also be studied in real time at single molecule level. The results demonstrate the potential for further development of phi29 motor channel for detection of disease-associated peptide biomarkers.

Effects of diet and exercise interventions on diabetes risk factors in adults without diabetes: meta-analyses of controlled trials

BACKGROUND AND AIMS

Fasting insulin (FI), fasting glucose (FG), systolic blood pressure (SBP), high density lipoproteins (HDL), triacylglycerides (TAG), and body mass index (BMI) are well-known risk factors for type 2 diabetes. Reliable estimates of lifestyle intervention effects on these factors allow diabetes risk to be predicted accurately. The present meta-analyses were conducted to quantitatively summarize effects of diet and exercise intervention programs on FI, FG, SBP, HDL, TAG and BMI in adults without diabetes.

MATERIALS AND METHODS

MEDLINE and EMBASE were searched to find studies involving diet plus exercise interventions. Studies were required to use adults not diagnosed with type 2 diabetes, involve both dietary and exercise counseling, and include changes in diabetes risk factors as outcome measures. Data from 18, 24, 23, 30, 29 and 29 studies were used for the analyses of FI, FG, SBP, HDL, TAG and BMI, respectively. About 60% of the studies included exclusively overweight or obese adults. Mean age and BMI of participants at baseline were 48 years and 30.1 kg/m(2). Heterogeneity of intervention effects was first estimated using random-effect models and explained further with mixed-effects models.

RESULTS

Adults receiving diet and exercise education for approximately one year experienced significant (P <0.001) reductions in FI (-2.56 ± 0.58 mU/L), FG (-0.18 ± 0.04 mmol/L), SBP (-2.77 ± 0.56 mm Hg), TAG (-0.258 ± 0.037 mmol/L) and BMI (-1.61 ± 0.13 kg/m(2)). These risk factor changes were related to a mean calorie intake reduction of 273 kcal/d, a mean total fat intake reduction of 6.3%, and 40 minutes of moderate intensity aerobic exercise four times a week. Lifestyle intervention did not have an impact on HDL. More than 99% of total variability in the intervention effects was due to heterogeneity. Variability in calorie and fat intake restrictions, exercise type and duration, length of the intervention period, and the presence or absence of glucose, insulin, or lipid abnormalities explained 23-63% of the heterogeneity.

CONCLUSIONS

Calorie and total fat intake restrictions coupled with moderate intensity aerobic exercises significantly improved diabetes risk factors in healthy normoglycemic adults although normoglycemic adults with glucose, insulin, and lipid abnormalities appear to benefit more.

Opening Pandora’s box in the UK: a hypothetical pharmacogenetic test for clozapine

Clozapine is a uniquely efficacious antipsychotic drug in treatment-resistant schizophrenia. Its use is restricted due to adverse effects including a rare but dangerous reduction in neutrophils (agranulocytosis) and the mandatory hematological monitoring this entails in many countries. We review the statistical, ethical and legal issues arising from a hypothetical pharmacogenetic test for clozapine, using the UK as an exemplary case for consideration. Our key findings include: a consideration of the probabilistic results that a pharmacogenetic test may return; the impact on drug licensing; and the potential for pharmacogenetic tests for clozapine being used without consent under the UK’s legal framework. We make recommendations regarding regulatory changes applicable to the special case of pharmacogenetic testing in clozapine treatment.

Sperm parameters: paradigmatic index of good health and longevity

Since the discovery of spermatozoon by Anton van Leeuwenhoek in 1677, there has been an ever increasing understanding of its role in reproduction. Many factors adversely affect sperm quality, including varicocele, accessory gland infection, immunological factors, congenital abnormalities, and iatrogenic systemic and endocrine causes, such as diabetes mellitus, obesity, metabolic syndrome, and smoking. The mechanisms responsible for the association between poor sperm parameters and ill health may include oxidative stress, low-grade inflammation, low testosterone, and low sex-hormone-binding globulin. Oxidative stress in the testicular microenvironment may result in decreased spermatogenesis and sperm DNA damage, loss of sperm motility, and abnormal sperm morphology. Low testosterone caused by advanced age, visceral obesity, and inflammation is associated with the development of cardiovascular disease. Hence, semen analysis has an important role in the routine evaluation of idiopathic male infertility, usually manifested as low sperm counts, impaired sperm motility, or absence of sperm, and remains the most common single diagnostic tool. Several studies have shown an inverse relationship between semen quality and medical disorders. This review elucidates the effect of medical disorders and social habits on sperm quality, the mechanisms that are involved in the impairment of sperm quality, and whether or not sperm quality can be used as an index of good health and longevity in a man.

Multiplexed volumetric bar-chart chip for point-of-care diagnostics

Microfluidics have become an enabling technology for point-of-care and personalized diagnostics. Desirable capabilities of microfluidics-based diagnostic devices include simplicity, portability, low cost and the performance of multiplexed and quantitative measurements, ideally in a high-throughput format. Here we present the multiplexed volumetric bar-chart chip (V-Chip), which integrates all these capabilities in one device. A key feature of the V-Chip is that quantitative results are displayed as bar charts directly on the device-without the need for optical instruments or any data processing or plotting steps. This is achieved by directly linking oxygen production by catalase, which is proportional to the concentration of the analyte, with the displacement of ink along channels on the device. We demonstrate the rapid quantification of protein biomarkers in diverse clinical samples with the V-Chip. The development of the V-Chip thus opens up the possibility of greatly simplified point-of-care and personalized diagnostics.

Label-free microcavity biosensors: steps towards personalized medicine

Personalized medicine has the potential to improve our ability to maintain health and treat disease, while ameliorating continuously rising healthcare costs. Translation of basic research findings to clinical applications within regulatory compliance is required for personalized medicine to become the new foundation for practice of medicine. Deploying even a few of the thousands of potential diagnostic biomarkers identified each year as part of personalized treatment workflows requires clinically efficient biosensor technologies to monitor multiple biomarkers in patients in real time. This paper discusses a critical component of a regulatory system, a microcavity optical biosensor for label-free monitoring of biomolecular interactions at physiologically-relevant concentrations. While most current biosensor research focuses on improving sensitivity, this paper emphasizes other characteristics a biosensor technology requires to be practical in a clinical setting, presenting robust microcavity biosensors which are easy to manufacture and integrate with microfluidics into flexible and redesignable platforms making the microcavity biosensors deployable for continuous monitoring of biomarkers in body fluids in the clinic, in dense 2D random arrays for high-throughput applications like drug-library screening in interactomics, and of the secretory behavior of single cells in the laboratory.

Non-linear contribution of glucose measures to cardiovascular diseases and mortality: reclassifying the Framingham's risk categories: a decade follow-up from the Tehran lipid and glucose study

BACKGROUND

We investigated non-linear contribution of fasting plasma glucose (FPG) and 2-hour post-challenge plasma glucose (2h-PCPG) to the risk of CVD and mortality. We hypothesized that glucose measures improve risk-stratification made by the Framingham's general CVD risk algorithm.

METHODS

Among participants aged ≥ 30 (n=8071), not taking glucose-lowering agents, 6169 (3477 women) remained eligible. Non-linear contribution of FPG and 2h-PCPG to incident CVD and mortality were assessed using Cox models incorporating restricted cubic splines functions. Risk reclassification improvement conferred by FPG and 2h-PCPG was examined using an extended version of net reclassification index (NRI) that takes into account the censoring nature of survival data.

RESULTS

We documented 465 incident CVD events (402 CHD), 212 deaths from any cause (94 CVD deaths). Excluding the contribution of the 2h-PCGP to mortality (that was linear) dose-response relationships between glucose measures and CVD and mortality were curvilinear with nadirs below which decreasing levels of glucose were unlikely to offer any benefit. These nadirs were assigned to FPG of 4.9-5.3 and 2h-PCPG of 6.0 mmol.l(-1). Glucose measures added to the predictive ability of the Framingham's general CVD risk algorithm with cutpoint-free NRIs ranging from 19 to 54%.

CONCLUSION

Glucose measures contributed to the risk of CVD and mortality in a curvilinear fashion, we observed increased risk below glucose thresholds currently used to define diabetes, supporting criteria for the diagnosis of impaired fasting glycemia and impaired glucose tolerance. Glucose measures were observed to add to predictive ability of the predictive model which included established cardiovascular risk factors.

Metabolic syndrome, impaired fasting glucose and obesity, as predictors of incident diabetes in 14 120 hypertensive patients of ASCOT-BPLA: comparison of their relative predictability using a novel approach

AIMS

To evaluate, in hypertensive patients, whether the metabolic syndrome is a better predictor of new-onset diabetes compared with impaired fasting glucose, obesity or its other individual components alone, or collectively.

METHODS

Cox models were developed to assess the risk of new-onset diabetes associated with the metabolic syndrome after adjusting for a priori confounders (age, sex, ethnicity and concomitant use of non-cardiovascular medications), its individual components and other determinants of new-onset diabetes. Area under receiver operator curves using the metabolic syndrome or models of impaired fasting glucose were compared, and the ability of these models to correctly identify those who (after 5-years of follow-up) would or would not develop diabetes was assessed.

RESULTS

The metabolic syndrome adjusted for a priori confounders and its individual components, and further adjusted for other determinants, was associated with significantly increased risk of new-onset diabetes [1.19 (1.00-1.40), P = 0.05 and 1.22 (1.03-1.44), P = 0.02, respectively]. The discriminative ability of the metabolic syndrome model [area under receiver operating curve: 0.764 (0.750-0.778)] was significantly better than the model of impaired fasting glucose [0.742 (0.727-0.757)] (P < 0.001). The metabolic syndrome correctly allocates the risk of new-onset diabetes in a significantly higher proportion of patients (62.3%) than impaired fasting glucose status (37.7%) (P < 0.001). The presence of both the metabolic syndrome and impaired fasting glucose were associated with an approximately 9-fold (7.47-10.45) increased risk of new-onset diabetes. Among normoglycaemic patients, the metabolic syndrome was also associated with significantly increased risk of new-onset diabetes, after adjusting for BMI and a priori confounders [1.66 (1.29-2.13)].

CONCLUSIONS

Both impaired fasting glucose and the metabolic syndrome predict the risk of new-onset diabetes; however, the metabolic syndrome is a better predictor than impaired fasting glucose in assigning the risk of new-onset diabetes in hypertensive patients, and among those with normoglycaemia.