Biological diagnosis of diabetes mellitus

Zendjabil, Mustapha

doi:10.1016/j.patbio.2015.10.002

Cited by 10 publications

(4 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Recently, plasma levels of glycated hemoglobin (HbA1c) are also used for diagnosis of Type 2 diabetes. All existing diagnostic methods have their advantages and disadvantages [94]. There is an absolute need to discover new biomarkers that can be used for early diagnosis and disease monitoring.…”

Section: Proteome Profiling Of Diabetic Skeletal Musclementioning

confidence: 99%

Proteomics of Skeletal Muscle: Focus on Insulin Resistance and Exercise Biology

Deshmukh

2016

Proteomes

View full text Add to dashboard Cite

Skeletal muscle is the largest tissue in the human body and plays an important role in locomotion and whole body metabolism. It accounts for ~80% of insulin stimulated glucose disposal. Skeletal muscle insulin resistance, a primary feature of Type 2 diabetes, is caused by a decreased ability of muscle to respond to circulating insulin. Physical exercise improves insulin sensitivity and whole body metabolism and remains one of the most promising interventions for the prevention of Type 2 diabetes. Insulin resistance and exercise adaptations in skeletal muscle might be a cause, or consequence, of altered protein expressions profiles and/or their posttranslational modifications (PTMs). Mass spectrometry (MS)-based proteomics offer enormous promise for investigating the molecular mechanisms underlying skeletal muscle insulin resistance and exercise-induced adaptation; however, skeletal muscle proteomics are challenging. This review describes the technical limitations of skeletal muscle proteomics as well as emerging developments in proteomics workflow with respect to samples preparation, liquid chromatography (LC), MS and computational analysis. These technologies have not yet been fully exploited in the field of skeletal muscle proteomics. Future studies that involve state-of-the-art proteomics technology will broaden our understanding of exercise-induced adaptations as well as molecular pathogenesis of insulin resistance. This could lead to the identification of new therapeutic targets.

show abstract

Section: Proteome Profiling Of Diabetic Skeletal Musclementioning

confidence: 99%

Proteomics of Skeletal Muscle: Focus on Insulin Resistance and Exercise Biology

Deshmukh

2016

Proteomes

View full text Add to dashboard Cite

show abstract

“…2,3 However, HbA1c only reflects glycaemic control for 2-3 months and conditions, such as haemoglobinopathies, recent transfusion, pregnancy, blood loss or chronic kidney disease, can affect the validity of the HbA1c test. 4 Glycated albumin (GA), the product of a non-enzymatic reaction where blood glucose binds to the N-terminal residue of albumin, has been proposed as a haemoglobin-independent alternative to HbA1c 5,6 for evaluating short-term (2-3 weeks) glycaemic level. In 1979, a study initially reported that serum GA levels increased in people with diabetes.…”

Section: Introductionmentioning

confidence: 99%

“…Glycated haemoglobin (HbA1c) is one of the most commonly used glycaemic biomarkers, and it has been recommended for the diagnosis of diabetes and prediabetes 2 ,. 3 However, HbA1c only reflects glycaemic control for 2–3 months and conditions, such as haemoglobinopathies, recent transfusion, pregnancy, blood loss or chronic kidney disease, can affect the validity of the HbA1c test 4 . Glycated albumin (GA), the product of a non‐enzymatic reaction where blood glucose binds to the N‐terminal residue of albumin, has been proposed as a haemoglobin‐independent alternative to HbA1c 5,6 for evaluating short‐term (2–3 weeks) glycaemic level.…”

Section: Introductionmentioning

confidence: 99%

Serum glycated albumin as good biomarker for predicting type 2 diabetes: A retrospective cohort study of China National Diabetes and Metabolic Disorders Survey

Bai

Fang

Ming

et al. 2021

Diabetes Metabolism Res

View full text Add to dashboard Cite

Aims: Glycated albumin (GA) is a biomarker for short-term (2-3 weeks) glycaemic control. However, the predictive utility of GA for diabetes and prediabetes is largely uncharacterised. We aimed to investigate the relationships of baseline serum GA levels with incident diabetes and prediabetes. Methods:This was a longitudinal cohort study involving 516 subjects without diabetes or prediabetes at baseline. Blood glucose levels were observed during followup. Hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated using COX proportional hazard models. Receiver operating characteristic curves and areas under the curves (AUCs) were used to evaluate the discriminating abilities of glycaemic biomarkers and prediction models.Results: During a 9-year follow-up, 51 individuals (9.88%) developed diabetes and 92 (17.83%) prediabetes. Unadjusted HRs (95% CI) for both diabetes and prediabetes increased proportionally with increasing GA levels in a dose-response manner. Multivariable-adjusted HRs (95% CI) for diabetes were significantly elevated from 1.0 (reference) to 5.58 (1.86-16.74). However, the trend was no longer significant for prediabetes after multivariable adjustment. AUCs for GA, fasting blood glucose (FBG) and 2-h postprandial blood glucose (2h-PBG) for predicting diabetes were 0.698, 0.655 and 0.725, respectively. The AUCs for GA had no significant differences compared with those for FBG (p = 0.376) and 2h-PBG (p = 0.552). Replacing FBG or 2h-PBG or both with GA in diabetes prediction models made no significant changes to the AUCs of the models.Conclusions: GA is of good prognostic utility in predicting diabetes. However, GA may not be a useful biomarker for predicting prediabetes. K E Y W O R D S biomarker, cohort study, glycated albumin, type 2 diabetes Yuanyuan Bai and Yujie Fang are co-first authors.

show abstract

“…An HbA1c level of ≥6.5% on two separate occasions indicates the presence of diabetes. [ 2 ] Diabetes can lead to cardiovascular complications and end-organ damage.…”

Section: Introductionmentioning

confidence: 99%