Urinary C-peptide/creatinine ratio: A useful biomarker of insulin resistance and refined classification of type 2 diabetes mellitus

U-shaped association between plasma C-peptide and sarcopenia: A cross-sectional study of elderly Chinese patients with diabetes mellitus

Limited research exists regarding the relationship between fasting plasma C-peptide levels and sarcopenia. As a result, our study aimed to examine this association in elderly Chinese diabetic patients. This cross-sectional study included 288 elderly patients with diabetes mellitus from the Fourth People's Hospital in Guiyang who were enrolled prospectively between March 2020 and February 2023. The independent variable of interest was fasting plasma C-peptide, while the dependent variable was sarcopenia. Data on several covariates, including demographic factors, lifestyle habits, co-morbidities, anthropometric indicators, and laboratory indicators, were also collected. Of the 288 participants, 27.43% (79/288) had sarcopenia. After adjusting for potential confounding variables, we found a U-shaped association between fasting plasma C-peptide levels and sarcopenia, with inflection points identified at approximately 774 pmol/L and 939 mmol/L. Within the range of 50-744 pmol/L, each 100 pmol/L increase in CysC was associated with a 37% decrease in the odds of sarcopenia (odds ratio [OR], 0.63; 95% confidence interval [CI], 0.49 to 0.83; P < 0.001). Additionally, within the range of 939-1694 pmol/L, each 100 pmol/L increase in fasting plasma C-peptide was associated with a 76% increase in the odds of sarcopenia (odds ratio [OR], 1.76; 95% confidence interval [CI], 1.11 to 2.81; P = 0.017). Our study revealed a U-shaped association between fasting plasma C-peptide levels and the likelihood of sarcopenia, with lower risk in the range of 774-939 pmol/L. These findings may assist in the development of more effective prevention and treatment strategies for sarcopenia in elderly diabetic patients.

Precision subclassification of type 2 diabetes: a systematic review

BACKGROUND

Heterogeneity in type 2 diabetes presentation and progression suggests that precision medicine interventions could improve clinical outcomes. We undertook a systematic review to determine whether strategies to subclassify type 2 diabetes were associated with high quality evidence, reproducible results and improved outcomes for patients.

METHODS

We searched PubMed and Embase for publications that used 'simple subclassification' approaches using simple categorisation of clinical characteristics, or 'complex subclassification' approaches which used machine learning or 'omics approaches in people with established type 2 diabetes. We excluded other diabetes subtypes and those predicting incident type 2 diabetes. We assessed quality, reproducibility and clinical relevance of extracted full-text articles and qualitatively synthesised a summary of subclassification approaches.

RESULTS

Here we show data from 51 studies that demonstrate many simple stratification approaches, but none have been replicated and many are not associated with meaningful clinical outcomes. Complex stratification was reviewed in 62 studies and produced reproducible subtypes of type 2 diabetes that are associated with outcomes. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into clinically meaningful subtypes.

CONCLUSION

Critical next steps toward clinical implementation are to test whether subtypes exist in more diverse ancestries and whether tailoring interventions to subtypes will improve outcomes.

Urinary C-Peptide to Creatinine Ratio (UCPCR) as Indicator for Metabolic Risk in Apparently Healthy Adults-A BioPersMed Cohort Study

Background: C-peptide is produced in equimolar amounts with insulin from pancreatic beta cells, and thus is a fundamental biomarker for beta cell function. A non-invasive urinary C-peptide-to-creatinine ratio (UCPCR) has attracted attention as a biomarker for metabolic conditions. However, the UCPCR as an indicative risk predictor for prediabetes is still being investigated. Methods: We aimed to characterize UCPCRs in healthy people using American Diabetes Association (ADA) criteria and to evaluate their metabolic outcomes over time. A total of 1022 participants of the Biomarkers in Personalized Medicine cohort (BioPersMed) were screened for this study. Totals of 317 healthy with normal glucose metabolism, 87 prediabetic, and 43 diabetic subjects were included. Results: Prediabetic participants had a significantly higher UCPCR median value than healthy participants (p < 0.05). Dysglycaemia of healthy baseline participants was measured twice over 4.5 ± 0.9 years; 25% and 30% were detected with prediabetes during follow-ups, predicted by UCPCR both for the first (p < 0.05) and the second visit (p < 0.05), respectively. This is in good agreement with the negative predictive UCPCR value of 60.2% based on logistic regression. UCPCR levels were equal in both sexes. Conclusion: UCPCR measurements provide an indicative approach for metabolic risk, representing a potential use for prevention and monitoring of impaired glucose metabolism.

Systematic review of precision subclassification of type 2 diabetes

Heterogeneity in type 2 diabetes presentation, progression and treatment has the potential for precision medicine interventions that can enhance care and outcomes for affected individuals. We undertook a systematic review to ascertain whether strategies to subclassify type 2 diabetes are associated with improved clinical outcomes, show reproducibility and have high quality evidence. We reviewed publications that deployed 'simple subclassification' using clinical features, biomarkers, imaging or other routinely available parameters or 'complex subclassification' approaches that used machine learning and/or genomic data. We found that simple stratification approaches, for example, stratification based on age, body mass index or lipid profiles, had been widely used, but no strategy had been replicated and many lacked association with meaningful outcomes. Complex stratification using clustering of simple clinical data with and without genetic data did show reproducible subtypes of diabetes that had been associated with outcomes such as cardiovascular disease and/or mortality. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into meaningful groups. More studies are needed to test these subclassifications in more diverse ancestries and prove that they are amenable to interventions.

Urinary c-peptide creatinine ratio (UCPCR) as a predictor of coronary artery disease in type 1 diabetes mellitus

BACKGROUND

Elevated C-peptide has been suggested as a risk factor for coronary artery disease (CAD). Elevated urinary C-peptide to creatinine ratio (UCPCR) as an alternative measurement is shown to be related to insulin secretion dysfunction; however, data regarding UCPCR predictive value for CAD in diabetes mellitus (DM) are scarce. Therefore, we aimed to assess the UCPCR association with CAD in type 1 DM (T1DM) patients.

METHODS

279 patients previously diagnosed with T1DM included and categorized into two groups of CAD (n = 84) and without-CAD (n = 195). Furthermore, each group was divided into obese (body mass index (BMI) ≥ 30) and non-obese (BMI < 30) groups. Four models utilizing the binary logistic regression were designed to evaluate the role of UCPCR in CAD adjusted for well-known risk factors and mediators.

RESULTS

Median level of UCPCR was higher in CAD group compared to non-CAD group (0.07 vs. 0.04, respectively). Also, the well-acknowledged risk factors including being active smoker, hypertension, duration of diabetes, and body mass index (BMI) as well as higher levels of haemoglobin A1C (HbA1C), total cholesterol (TC), low-density lipoprotein (LDL) and estimated glomeruli filtration rate (e-GFR) had more significant pervasiveness in CAD patients. Based on multiple adjustments by logistic regression, UCPCR was a strong risk factor of CAD among T1DM patients independent of hypertension, demographic variables (gender, age, smoking, alcohol consumption), diabetes-related factors (diabetes duration, FBS, HbA1C), lipid profile (TC, LDL, HDL, TG) and renal-related indicators (creatinine, e-GFR, albuminuria, uric acid) in both patients with BMI≥30 and BMI < 30.

CONCLUSION

UCPCR is associated with clinical CAD, independent of CAD classic risk factors, glycaemic control, insulin resistance and BMI in type 1 DM patients.

Application of urine C-peptide creatinine ratio in type 2 diabetic patients with different levels of renal function

OBJECTIVE

This study aims to investigate the effect of single urine C peptide/creatinine (UCPCR) in assessing the islet β Cell function of type 2 diabetes mellitus (T2DM) patients with different renal function.

METHODS

A total of 85 T2DM patients were recruited in this study, all the patients were assigned to one group with estimated glomerular filtration rate (eGFR)≤60 ml·min^-1·1.73 m^-2 and another group complicated with eGFR>60 ml·min^-1·1.73 m^-2. Serum creatinine, urine creatinine, serum fasting C-peptide (FCP), fasting blood glucose (FBG), glycosylated hemoglobin (HbA1C) and 24-hour urinary C-peptide (24hUCP) were measured. The modified homeostasis model assessment-islet β cell function [HOMA-islet (CP-DM)], the modified homeostasis model assessment-insulin resistance [HOMA-IR(CP)] and UCPCR were calculated.

RESULTS

When compared with group eGFR ≤60 ml·min^-1·1.73 m^-2, the levels of UCPCR, FCP, the modified HOMA-IR(CP) and HOMA-islet (CP-DM) were promoted and the concentrations of HbA1C, FPG, creatinine were decreased in the patients of eGFR>60 ml·min^-1·1.73 m^-2 (P<0.05); FCP was uncorrelated with 24hUCP while associated with UCPCR in the patients of eGFR ≤ 60 ml·min^-1·1.73 m^-2; UCPCR was positively correlated with FCP and HOMA-IR(CP) in the T2DM patients with different levels of renal function; the cut-off (UCPCR ≤ 1.13 nmol/g) had 88.37% sensitivity and 95.24% specificity [95% confidence interval (CI):0.919-0.997] for identifying severe insulin deficiency in T2DM patients[area under the curve (AUC) 0.978].

CONCLUSION

UCPCR can be used to evaluate islets β Cell function in T2DM patients with different renal function status.

A Pilot Proteomic Study of Normal Human Tears: Leptin as a Potential Biomarker of Metabolic Disorders

The concentrations of insulin, leptin, active ghrelin, C-peptide and gastric inhibitory polypeptide (GIP) and their inter-day variations were examined in normal human tears. In addition, correlations between the concentrations of these metabolic proteins and ocular surface parameters were determined. Subjects with healthy ocular surfaces attended three visits, with 7-day intervals. Tear evaporation rate (TER) and non-invasive tear break-up time (NITBUT) were assessed, and a total of 2 µL tears were collected from all subjects. Tear fluid concentrations of insulin, leptin, active ghrelin, C-peptide and GIP were measured by multiplex bead analysis. Insulin was the most highly expressed metabolic protein, followed by leptin, C-peptide, active ghrelin and GIP. Of these, only active ghrelin had a significant inter-day variation (p < 0.05). There was no inter-day variation in the mean concentrations of the other metabolic proteins. Leptin had a strong intra-class reproducibility. No correlation was detected between tear metabolic protein concentrations and ocular surface parameters. This pilot study shows, for the first time, that active ghrelin and GIP are detectable in healthy tears. The strong intra-class reproducibility for leptin shows that it could be used as a potential tear fluid biomarker and, possibly, in determining the effects of metabolic disorders on the ocular surface.