Visceral Adiposity Index, Triglyceride/High-Density Lipoprotein Ratio, and Lipid Accumulation Product Index to Discriminate Metabolic Syndrome Among Adult Type 1 Diabetes Patients

Double diabetes-when type 1 diabetes meets type 2 diabetes: definition, pathogenesis and recognition

Currently, the differentiation between type 1 diabetes (T1D) and type 2 diabetes (T2D) is not straightforward, and the features of both types of diabetes coexist in one subject. This situation triggered the need to discriminate so-called double diabetes (DD), hybrid diabetes or type 1.5 diabetes, which is generally described as the presence of the insulin resistance characteristic of metabolic syndrome in individuals diagnosed with T1D. DD not only raises the question of proper classification of diabetes but is also associated with a significantly greater risk of developing micro- and macroangiopathic complications, which was independent of glycaemic control. When considering the global obesity pandemic and increasing incidence of T1D, the prevalence of DD may also presumably increase. Therefore, it is of the highest priority to discover the mechanisms underlying the development of DD and to identify appropriate methods to prevent or treat DD. In this article, we describe how the definition of double diabetes has changed over the years and how it is currently defined. We discuss the accuracy of including metabolic syndrome in the DD definition. We also present possible hypotheses connecting insulin resistance with T1D and propose possible methods to identify individuals with double diabetes based on indirect insulin resistance markers, which are easily assessed in everyday clinical practice. Moreover, we discuss adjuvant therapy which may be considered in double diabetic patients.

A Blood-Based Lipid Profile Associated With Hippocampal Volume and Brain Resting-State Activation Within Obese Adults from the UK Biobank

Objectives: Obesity and dyslipidemia may be associated with hippocampal alterations and may increase the risk of neurodegeneration. This study studied hippocampal anatomical and functional association with a lipid profile based on high-density lipoprotein, low-density lipoprotein, and triglyceride related to dyslipidemia in obese and nonobese adults. A whole-brain analysis was also conducted to examine the effect of dyslipidemia on resting-state function across the brain. Participants and Methods: In total, 553 UK Biobank participants comprised three groups based on body mass index (BMI) rankings: obese adults with high BMI (OHigh, n = 184, 32.7 kg/m2 ≤ BMI ≤53.4 kg/m2), obese adults with a lower BMI (OLow, n = 182, 30.3 kg/m2 ≤ BMI ≤32.6 kg/m2), and nonobese controls (n = 187). Structural MRI and functional MRI data were accessed. The fractional amplitude of low-frequency fluctuations (fALFFs) maps was calculated to reflect resting-state brain activity. A lipid health factor was created using principal component analysis. Linear models tested for associations between the lipid health score and hippocampal MRI readouts. Results: With a higher lipid health factor corresponding to a lower dyslipidemia risk, we found a positive correlation between hippocampal volume with the lipid health factor exclusively in group OLow (p = 0.01). We also found a positive association between the lipid health factor and hippocampal fALFF in group OHigh (p = 0.02). Additional fALFF voxel-wise analysis to group OHigh also implicated that the premotor cortex, amygdala, thalamus, subcallosal cortex, temporal fusiform cortex, and middle temporal gyrus brain regions are related with lipid. Conclusion: The study finds novel associations among circulating lipid, hippocampal structure, and hippocampal function exclusively in the obese adults.

Lipid accumulation product is a better predictor of metabolic syndrome in Chinese adolescents: a cross-sectional study

Aim

Confirm and compare the degree of associations of non-traditional lipid profiles and metabolic syndrome (MetS) in Chinese adolescents, determine the lipid parameter with better predictive potential, and investigate their discriminatory power on MetS.

Methods

Medical measurements, including anthropometric measurements and biochemical blood tests, were undergone among a total sample of 1112 adolescents (564 boys and 548 girls) aged from 13 to 18 years. Univariate and multivariate logistic regression analyses were applied for assessing the relationships between the levels of traditional/non-traditional lipid profiles and MetS. We performed Receiver Operating Characteristic (ROC) analyses to mensurate the effectiveness of lipid accumulation product (LAP) on the diagnosis of MetS. Meanwhile, areas under the ROC curve and the cut-off values were calculated for MetS and its components.

Results

Univariate analysis showed that all our lipid profiles were closely associated with MetS (P< 0.05). LAP index showed the closest association with MetS than the other lipid profiles. Additionally, ROC analyses indicated that the LAP index showed sufficient capabilities to identify adolescents with MetS and its components.

Conclusion

The LAP index is a simple and efficient tool to identify individuals with MetS in Chinese adolescents.

Visceral adiposity index is a better predictor to discriminate metabolic syndrome than other classical adiposity indices among young adults

BACKGROUND

Visceral adiposity index (VAI) has been identified as a cardiometabolic risk marker in children and adolescents which reflects abdominal fat distribution. The aim of the present study was to evaluated the predictive capacity of VAI, a body shape index (ABSI), atherogenic index of plasma (AIP), and triglycerides and glucose index (TyG index) compared with classical anthropometric measurements to discriminate metabolic syndrome (MetS).

METHODS

This retrospective study included 1372 individuals. Anthropometric, clinical, and biochemical measurements were used to screen the prevalence of MetS components and to calculate VAI, ABSI, TyG index, and AIP.

RESULTS

The discriminatory capacity among the variables was assessed by the area under the receiver operating characteristic (ROC) curve (AUC). VAI was the variable with the highest AUC with 0.932 CI 95% (0.917-0.948), followed by AIP with 0.914 CI 95% (0.897-0.931), and TyG index with 0.889 CI 95% (0.871-0.908).

CONCLUSION

VAI is a promising tool to identify MetS in the late adolescence setting. Among the novel adiposity indexes VAI, AIP, TyG index are able to determine MetS presence, while ABSI is not capable.

Comparison between traditional and new obesity measurement index for screening metabolic associated fatty liver disease

Objectives

Obesity measurement indexes have certain screening value for metabolic diseases. To investigate associations between metabolic associated fatty liver disease (MAFLD) and obesity measurement indexes, including traditional indexes (BMI, WC, WHtR) and new indexes (ABSI, BRI, VAI, LAP), and assess their screening ability.

Methods

12,658 subjects aged 18-75 at the Health Center of a Class III Grade A Hospital were included, who were divided into MAFLD and non-MAFLD groups. Spearman's rank correlation was used to study the correlation between MAFLD and obesity measurement indexes. Receiver operating characteristic (ROC) curves were used to calculate the area under the curve (AUC) to evaluate their screening accuracy.

Results

MAFLD had strong correlation with traditional BMI and new index LAP. ROC analysis showed that BMI had the highest AUC (0.89), followed by LAP (0.87). Stratification by BMI, LAP had the highest AUC (0.90) for MAFLD in population without obesity (BMI< 23kg/m²), and its optimal cutoff value was 20.75, with a sensitivity and specificity of 85.9% and 79.0%, respectively.

Conclusions

We proposed a two-step screening strategy for MAFLD, combining BMI and LAP, and defined a high-risk population for MAFLD as follows: 1) BMI ≥ 23 kg/m²; and 2) BMI< 23 kg/m² and LAP ≥ 20.75.

Evaluation among trace elements, clinical parameters and type 1 diabetes according to sex: A new sight of auxiliary prediction in negative insulin auto-antibodies population

BACKGROUND

Type 1 diabetes (T1D) exhibited sex-specific metabolic status including oxidative stress with dynamic change of trace elements, which emphasized the importance of the evaluation of trace elements according to sex. Besides, the most significant characteristic, insulin auto-antibodies, could not be found in all T1D patients, which needed the auxiliary prediction of clinical parameters. And it would benefit the early detection and treatment if some high-risk groups of T1D could predict and prevent the occurrence of disease through common clinical parameters. Hence, there was an urgent need to construct more effective and scientific statistical prediction models to serve clinic better. This study aimed to evaluate the sex-specific levels of trace elements and the relationship between trace elements and clinical parameters in T1D, and construct sex-specific auxiliary prediction model combined with trace elements and clinical parameters.

METHODS

A total of 105 T1D patients with negative insulin auto-antibodies and 105 age/sex-matched healthy individuals were enrolled in First Hospital of Jilin University. Inductively Coupled Plasma Mass Spectrometry was performed for the measurement of calcium (Ca), magnesium (Mg), zinc (Zn), copper (Cu), iron (Fe), selenium (Se) in the serum, and the data of clinical parameters were received from medical record system. The lambda-mu-sigma method was used to evaluate the relationship between abnormal clinical parameters and trace elements. Training set and validation set were divided for the construction of predictable models in males and females: clinical parameters model, trace element model and the combined model (clinical parameters and trace elements). Goodness fit test, decision curve analysis and other related statistical methods were used to perform data analysis.

RESULTS

Lower levels of Mg, Ca, Fe in the serum were found in T1D population in females compared with healthy population, while levels of Fe, Zn and Cu of serum in T1D individuals were higher than those of healthy population in males. Levels of serum Mg, Fe and Cu in T1D group were found with significant sex difference for (P < 0.05), and the levels of Fe and Cu in serum of males were higher than those of females, level of serum Mg in males was lower than those of females. Levels of serum Mg and Zn showed fluctuation trend with increased numbers of abnormal clinical parameters (NACP) in males. Serum Zn in females showed consistent elevated trend with NACP; serum Se increased first and then decreased with NACP in males and females. The auxiliary prediction model (Triglyceride, Total protein, serum Mg) was found with the highest predicted efficiency in males (AUC=0.993), while the model in females (Apolipoprotein A, Creatinine, Fe, Se, Zn/Cu ratio) showed the best predicted efficiency (AUC=0.951). The models had passed the verification in validation set, and Chi-square goodness-of-fit test, DCA results both confirmed their satisfactory clinical applicability.

CONCLUSION

Sex-specific difference were found in serum Mg, Fe and Cu in T1D. The combination of triglyceride, total protein and serum Mg for males, and apolipoprotein A, creatinine, Fe, Se, Zn/Cu ratio for females could effectively predict T1D in patients with negative anti-bodies, which would provide alarm for the population with high-risk of T1D and serve the T1D prediction in patients with negative anti-bodies.

Sex-specific contribution of lipid accumulation product and cardiometabolic index in the identification of nonalcoholic fatty liver disease among Chinese adults

Background

Lipid accumulation product (LAP) and cardiometabolic index (CMI) are two novel obesity-related indexes associated with enhancing metabolic disease (MD) risk. Current evidences suggest that the differences in sex hormones and regional fat distribution in both sexes are directly correlated with MD and nonalcoholic fatty liver disease (NAFLD) risk. Hence, NAFLD incidences reflect sex differences. Herein, we examined the accuracy of LAP and CMI in diagnosing NAFLD in both sexes.

Methods

Overall, 14,407 subjects, who underwent health check-up in the northeastern China, were enrolled in this study, and their corresponding LAP and CMI were calculated. Abdominal ultrasonography was employed for NAFLD diagnosis. Multivariate analyses were analyzed potential correlations between LAP and/or CMI and NAFLD. Odds ratios (ORs) and 95% confidence intervals (CIs) were evaluated. Receiver operating characteristic curve analyses was executed for the exploration of the diagnostic accuracies. Areas under the curves (AUCs) with 95%CIs were calculated.

Results

NAFLD prevalence increased with elevated quartiles of LAP and CMI in both sexes. In multivariate logistic regression analyses, LAP and CM expressed as continuous variables or quartiles, significantly correlated with NAFLD. The ORs for the top versus bottom quartile of LAP and CMI for NAFLD were 13.183 (95%CI = 8.512–20.417) and 8.662 (95%CI = 6.371–11.778) in women and 7.544 (95%CI = 5.748–9.902) and 5.400 (95%CI = 4.297–6.786) in men. LAP and CMI exhibited larger AUCs, compared to other obesity-related indexes in terms of discriminating NAFLD. The AUCs of LAP and CMI were 0.860 (95%CI = 0.852–0.867) and 0.833 (95%CI = 0.825–0.842) in women and 0.816 (95%CI = 0.806–0.825) and 0.779 (95%CI = 0.769–0.789) in men.

Conclusions

LAP and CMI are convenient indexes for the screening and quantification of NAFLD within a Chinese adult population. Their associations with NAFLD are substantially greater in women than men.