Characterization of the hypertriglyceridemic waist phenotype in patients with type2 diabetes mellitus in Spain: An epidemiological study

CD36 polymorphism, sugary drinks, and sedentarism are associated with hypertriglyceridemic waist phenotype

Background: The hypertriglyceridemic waist (HTGW) phenotype is characterized by concomitant increases in waist circumference (WC) and blood triglyceride levels (TG), which have been identified as a predictor of metabolic disorders. This study aimed to analyze associations between food consumption, exercise, and the CD36 gene rs1761667 G>A polymorphism with the HTGW phenotype in adult Mexicans. Methods: This cross-sectional study included a total of 255 participants (both genders, between 18-64 years of age). The HTGW phenotype was defined as WC >88 cm in women, WC >102 cm in men, and TG >150 mg/dL. Body composition was analyzed by electrical bioimpedance. Dietary intakes (macro and micronutrients) were evaluated through a validated 64-item food frequency questionnaire and a 24-h recall. Physical exercise was subjectively recorded asking the participants if they regularly performed some systematic exercise or sport of moderate intensity at least 150-300 minutes a week. Biochemical tests were determined by an automated system. A Taqman real-time assay was used to detect the rs1761667 (G>A) polymorphism of the CD36 gene. A multivariate logistic regression model was performed to analyze the variables potentially associated with the HTGW phenotype (adjusted for age, energy intake, and total fat mass). Results: Overall, 21.6% of the population presented the HTGW phenotype; compared to the HTGW-, also, they were older, had more body fat, higher glucose, cholesterol and insulin levels, and high blood pressure. Female sex (OR=2.92, 95% CI: 1.12-7.60, p=0.028), body mass index (OR=1.19, 95% CI: 1.07-1.32, p=0.001), total cholesterol (OR=1.01, 95% CI:1.00-1.02, p=0.039), daily consumption of sugary drinks (OR=6.94, 95% CI: 1.80-26.8, p=0.005), and the CD36 AG genotype (OR=3.81, 95% CI: 1.08-13.4, p=0.037) were positively associated with the HTGW phenotype, while performing exercise played a protective role (OR=0.23, 95% CI: 0.08-0.62, p=0.004). Overall, the model predicted the HTGW phenotype in 47% (R2=0.47, p≤0.001). Conclusion: The CD36 AG genotype, daily consumption of sugary drinks and sedentarism are risk factors for the HTGW phenotype in Mexicans.

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.

Identification of Key LncRNAs and Pathways in Prediabetes and Type 2 Diabetes Mellitus for Hypertriglyceridemia Patients Based on Weighted Gene Co-Expression Network Analysis

Aims

Prevalence of prediabetes and type 2 diabetes mellitus(T2DM) are increasing worldwide. Key lncRNAs were detected to provide a reference for searching potential biomarkers of prediabetes and T2DM in hypertriglyceridemia patients.

Methods

The study included 18 hypertriglyceridemia patients: 6 newly diagnosed type 2 diabetes patients, 6 samples with prediabetes and 6 samples with normal blood glucose. Weighted gene co-expression network analysis (WGCNA) was conducted to construct co-expression network and obtain modules related to blood glucose, thus detecting key lncRNAs.

Results

The green, yellow and yellow module was significantly related to blood glucose in T2DM versus normal controls, T2DM versus prediabetes, prediabetes versus normal controls, respectively. ENST00000503273, ENST00000462720, ENST00000480633 and ENST00000485392 were detected as key lncRNAs for the above three groups, respectively.

Conclusions

For hypertriglyceridemia patients with different blood glucose levels, ENST00000503273, ENST00000462720 and ENST00000480633 could be potential biomarkers of T2DM.