Non-linear associations of atherogenic index of plasma with prediabetes and type 2 diabetes mellitus among Chinese adults aged 45 years and above: a cross-sectional study from CHARLS

Background

Dyslipidemia is strongly associated with the development of prediabetes and type 2 diabetes mellitus (T2DM). The atherogenic index of plasma (AIP), as a comprehensive index for assessing lipid metabolism, has received extensive attention from researchers in recent years. However, there are relatively few studies exploring the relationships between AIP and the risk of prediabetes and T2DM in the Chinese population. This study focuses on exploring the relationships of AIP with the risk of prediabetes and T2DM in the Chinese population.

Methods

We conducted an analysis of the public data from the China Health and Retirement Longitudinal Study (CHARLS), involving a total of 12,060 participants aged 45 years and above in China. The study explored the relationships of AIP with prediabetes and T2DM risk through multivariate logistic regression, subgroup analysis, smooth curve fitting, and threshold effect analysis.

Results

After adjusting for potential confounding factors, we observed positive associations between AIP and the risk of prediabetes [odds ratio (OR) = 1.75, 95% confidence interval (CI): 1.49-2.06] and T2DM (OR = 2.91, 95% CI: 2.38-3.57). Participants with higher AIP levels demonstrated a significantly elevated risk of prediabetes (OR = 1.52, 95% CI: 1.33-1.74) and T2DM (OR = 2.28, 95% CI: 1.92-2.71) compared to those with lower AIP levels. AIP showed consistent correlations with prediabetes and T2DM risk in different subgroups. The results showed the non-linear relationships between AIP and risk of prediabetes and T2DM, with inflection points at 0.29 and -0.04, respectively. When AIP > 0.29, there was a positive association between AIP and the risk of prediabetes (OR = 2.24, 95% CI: 1.67-3.00, p < 0.0001). Similarly, when AIP > -0.04, AIP was positively associated with the risk of T2DM (OR = 3.33, 95% CI: 2.67-4.16, p < 0.0001).

Conclusions

This study demonstrated non-linear positive associations of AIP with the risk of prediabetes and T2DM among participants ≥ 45 years of age in China.

Apparent Insulin Deficiency in an Adult African Population With New-Onset Type 2 Diabetes

Identifying patients with new-onset type 2 diabetes who have insulin deficiency can aid in timely insulin replacement therapy. In this study, we measured fasting C-peptide concentration to assess endogenous insulin secretion and determine the prevalence and characteristics of patients with insulin deficiency in adult Ugandan patients with confirmed type 2 diabetes at presentation.

Methods

Adult patients with new-onset diabetes were recruited from seven tertiary hospitals in Uganda. Participants who were positive for the three islet autoantibodies were excluded. Fasting C-peptide concentrations were measured in 494 adult patients, and insulin deficiency was defined as a fasting C-peptide concentration <0.76 ng/ml. The socio-demographic, clinical, and metabolic characteristics of participants with and without insulin deficiency were compared. Multivariate analysis was performed to identify independent predictors of insulin deficiency.

Results

The median (IQR) age, glycated haemoglobin (HbA1c), and fasting C-peptide of the participants was 48 (39-58) years,10.4 (7.7-12.5) % or 90 (61-113) mmol/mol, and 1.4 (0.8-2.1) ng/ml, respectively. Insulin deficiency was present in 108 (21.9%) participants. Participants with confirmed insulin deficiency were more likely to be male (53.7% vs 40.4%, p=0.01), and had a lower body mass index or BMI [p<0.001], were less likely to be hypertensive [p=0.03], had reduced levels of triglycerides, uric acid, and leptin concentrations [p<0.001]), but higher HbA1c concentration (p=0.004). On multivariate analysis, BMI (AOR 0.89, 95% CI 0.85-0.94, p<0.001), non-HDLC (AOR 0.77, 95% CI 0.61-0.97, p=0.026), and HbA1c concentrations (AOR 1.08, 95% CI 1.00-1.17, p=0.049) were independent predictors of insulin deficiency.

Conclusion

Insulin deficiency was prevalent in this population, occurring in about 1 in every 5 patients. Participants with insulin deficiency were more likely to have high HbA1c and fewer markers of adiposity and metabolic syndrome. These features should increase suspicion of insulin deficiency and guide targeted testing and insulin replacement therapy.

A Multivariate Analysis of “Metabolic Phenotype” Patterns in Children and Adolescents with Obesity for the Early Stratification of Patients at Risk of Metabolic Syndrome

Background: Metabolic syndrome (MS) is closely linked to obesity; however, not all individuals with obesity will develop obesity-related complications and a metabolically healthy obesity (MHO) group is also described. Objective: To perform a multivariate analysis (MVA) of the anthropometric and biochemical data in pediatric patients with obesity to reveal a “phenotype” predictive for MS. Methods: We analyzed 528 children with obesity (OB) and 119 normal-weight pediatric patients (NW). Adiposity indices were recorded, and MS was detected. MVA was performed. Results: Analysis of the structure of correlation of the variables showed that the variables of waist circumference (WC), body mass index (BMI), and estimated fat mass (eFM) were positively correlated with each other as a whole. In addition, the variables of the triglycerides (TG), triglyceride–glucose (TyG) index, and visceral adiposity index were positively correlated with each other as a whole, although none were correlated with the variables of BMI z-score, waist-to-height ratio, WC, eFM, or weight. The variables that related to insulin resistance (IR) and dyslipidemia were crucial for the early stratification of patients at risk of MS. Conclusions: Independently of body weight, IR, dyslipidemia, hypertriglyceridemia, and fat distribution seem to be the strongest MS risk factors. The early detection of and intervention in these modifiable risk factors are useful to protect children’s health.

The Association Between the Triglyceride-to-High-Density Lipoprotein Cholesterol Ratio and the Risk of Progression to Diabetes From Prediabetes: A 5-year Cohort Study in Chinese Adults

OBJECTIVE

Evidence regarding the relationship between the triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-c) ratio and the risk of progression from prediabetes to diabetes remains limited. The purpose of our study was to investigate the relationship between the TG/HDL-C ratio and incident diabetes in prediabetic patients.

METHODS

This retrospective cohort study covered 32 regions and 11 cities in China and consecutively and non-selectively collected data from 15,017 patients with prediabetes who had received a health check from 2010 to 2016. Data were obtained from the DATADRYAD database (www.datadryad.org). The Cox proportional-hazards regression model with cubic spline functions and smooth curve fitting (cubic spline smoothing) was used to explore the non-linear relationship between the baseline TG/HDL-c ratio and the risk of diabetes in patients with prediabetes. In addition, we performed a series of sensitivity and subgroup analyses.

RESULTS

The mean age of the included individuals was 50.95 ± 13.48 years, and 9,745 (64.51%) were men. The median (interquartile range) TG/HDL-c ratio was 1.09 (0.69-1.72). During a median follow-up time of 3.05 years, 1,731 (11.46%) patients had a final diagnosis of diabetes. The analysis after adjusting for covariates showed that the TG/HDL-c ratio was positively related to incident diabetes in patients with prediabetes (HR = 1.111, 95% CI 1.061-1.164). Participants with the highest TG/HDL-c ratio (Q4) had higher diabetes incidence rates than those with the lowest TG/HDL-c ratio (Q1) (P < 0.001 for the trend). There was a non-linear relationship between the TG/HDL-c ratio and the risk of diabetes, and the inflection point of the TG/HDL-c ratio was 1.415. The effect sizes (HR) on the left and right sides of the inflection point were 1.336 (95% CI: 1.134-1.573) and 1.055 (95% CI: 0.988-1.126), respectively. The sensitivity analysis demonstrated the robustness of these results.

CONCLUSION

This study demonstrates a positive, non-linear relationship between the TG/HDL-c ratio and the risk of diabetes in Chinese patients with prediabetes. Aggressive intervention from a treatment perspective is required to lower the TG/HDL-c ratio below the inflection point (1.415) by lowering TG or increasing HDL-c levels.

Metabolic Dysfunction Biomarkers as Predictors of Early Diabetes

During the pathophysiological course of type 2 diabetes (T2D), several metabolic imbalances occur. There is increasing evidence that metabolic dysfunction far precedes clinical manifestations. Thus, knowing and understanding metabolic imbalances is crucial to unraveling new strategies and molecules (biomarkers) for the early-stage prediction of the disease's non-clinical phase. Lifestyle interventions must be made with considerable involvement of clinicians, and it should be considered that not all patients will respond in the same manner. Individuals with a high risk of diabetic progression will present compensatory metabolic mechanisms, translated into metabolic biomarkers that will therefore show potential predictive value to differentiate between progressors/non-progressors in T2D. Specific novel biomarkers are being proposed to entrap prediabetes and target progressors to achieve better outcomes. This study provides a review of the latest relevant biomarkers in prediabetes. A search for articles published between 2011 and 2021 was conducted; duplicates were removed, and inclusion criteria were applied. From the 29 studies considered, a survey of the most cited (relevant) biomarkers was conducted and further discussed in the two main identified fields: metabolomics, and miRNA studies.

Emerging Diabetic Novel Biomarkers of the 21st Century

Diabetes is a growing epidemic with estimated prevalence of infected to reach ~592 million by the year 2035. An effective way to approach is to detect the disease at a very early stage to reduce the complications and improve lifestyle management. Although several traditional biomarkers including glucated hemoglobin, glucated albumin, fructosamine, and 1,5-anhydroglucitol have helped in ease of diagnosis, there is lack of sensitivity and specificity and are inaccurate in certain clinical settings. Thus, search for new and effective biomarkers is a continuous process with an aim of accurate and timely diagnosis. Several novel biomarkers have surged in the present century that are helpful in timely detection of the disease condition. Although it is accepted that a single biomarker will have its inherent limitations, combining several markers will help to identify individuals at high risk of developing prediabetes and eventually its progression to frank diabetes. This review describes the novel biomarkers of the 21st century, both in type 1 and type 2 diabetes mellitus, and their present potential for assessing risk stratification due to insulin resistance that will pave the way for improved clinical outcome.

Triglyceride to HDL-cholesterol ratio and the incidence risk of type 2 diabetes in community dwelling adults: A longitudinal 12-year analysis of the Korean Genome and Epidemiology Study

AIMS

Serum triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio is known to be associated with cardiometabolic diseases. This study is aimed to evaluate the association between the TG/HDL-C ratio and incident type 2 diabetes with a large-sample, community-based Korean cohort over 12 years.

METHODS

Among 10,038 participants, a total of 8655 participants aged 40 to 69 years without diabetes were selected from the Korean Genome and Epidemiology Study (KoGES). The baseline TG/HDL-C ratio was divided into quartiles. Newly developed type 2 diabetes was defined by any of the following: a fasting plasma glucose level ≥ 126 mg/dL; a glucose level ≥ 200 mg/dL 2-hours after a 75 g oral glucose tolerance test; an HbA1c ≥ 6.5%; or treatment with anti-diabetic therapy. The hazard ratios (HRs) with 95% confidence intervals (CIs) for incident type 2 diabetes were calculated using multivariate Cox proportional hazards regression models after adjusting for potentially confounding variables.

RESULTS

During the 12-year follow-up period, type 2 diabetes developed in 1437 subjects (16.6%, 1437/8655), with incidence rate of 2.8-5.0 (over 2 years). Compared to the reference first quartile, the HRs (95% CIs) of incident type 2 diabetes in the second, third, and fourth quartiles increased in a dose-response manner after adjusting for potentially confounding variables.

CONCLUSIONS

High TG/HDL-C ratio at baseline may be a useful surrogate indicator of future incident type 2 diabetes.

Novel biomarkers for prediabetes, diabetes, and associated complications

The number of individuals with prediabetes is expected to grow substantially and estimated to globally affect 482 million people by 2040. Therefore, effective methods for diagnosing prediabetes will be required to reduce the risk of progressing to diabetes and its complications. The current biomarkers, glycated hemoglobin (HbA1c), fructosamine, and glycated albumin have limitations including moderate sensitivity and specificity and are inaccurate in certain clinical conditions. Therefore, identification of additional biomarkers is being explored recognizing that any single biomarker will also likely have inherent limitations. Therefore, combining several biomarkers may more precisely identify those at high risk for developing prediabetes and subsequent progression to diabetes. This review describes recently identified biomarkers and their potential utility for addressing the burgeoning epidemic of dysglycemic disorders.

Triglyceride-glucose index (TyG index) in comparison with fasting plasma glucose improved diabetes prediction in patients with normal fasting glucose: The Vascular-Metabolic CUN cohort

AIMS

We evaluated the potential role of the triglyceride-glucose index (TyG index) as a predictor of diabetes in a White European cohort, and compared it to fasting plasma glucose (FPG) and triglycerides.

METHODS

4820 patients of the Vascular-Metabolic CUN cohort (VMCUN cohort) were examined and followed up for 8.84years (±4.39). We performed a Cox proportional hazard ratio with repeated-measures analyses to assess the risk of developing type 2 diabetes across quartiles of FPG, triglycerides and the TyG index (ln[fasting triglycerides (mg/dl)×fasting plasma glucose (mg/dl)/2]), and plotted a receiver operating characteristics (ROC) curve for discrimination.

RESULTS

There were 332 incident cases of type 2 diabetes involving 43,197.32person-years of follow-up. We observed a progressively increased risk of diabetes in subjects with TyG index levels of 8.31 or more. Among those with normal fasting glucose at baseline, <100mg/dl, subjects with the TyG index in the fourth quartile were 6.87 times more likely to develop diabetes (95% CI, 2.76-16.85; P for trend<0.001), as compared with the bottom quartile. The areas under the ROC curves (95% CI) were 0.75 (0.70-0.81) for TyG index, 0.66 (0.60-0.72) for FPG and 0.71 (0.65-0.77) for TG, in subjects with normal fasting glucose (p=0.017).

CONCLUSIONS

Our data suggest that the TyG index is useful for the early identification of individuals at risk of type 2 diabetes. The TyG index seems to be a better predictor than FPG or triglycerides of the potential development of type 2 diabetes in normoglycemic patients.