Is HDL cholesterol protective in patients with type 2 diabetes? A retrospective population-based cohort study

Association of serum uric acid to high-density lipoprotein cholesterol ratio with all-cause and cardiovascular mortality in patients with diabetes or prediabetes: a prospective cohort study

Background and aims

The serum uric acid (UA) to high-density lipoprotein cholesterol (HDL-C) ratio (UHR) is a novel biomarker that indicates inflammation and metabolic disorders. Also, it has been shown that UHR correlates with the risk of cardiovascular disease. Despite this, limited research exists on its prognostic significance. This study aimed to explore the association of UHR with all-cause and cardiovascular mortality in patients with diabetes or prediabetes.

Methods

This cohort study included 18,804 participants from the National Health and Nutrition Examination Survey (NHANES) 2005-2018 with diabetes or prediabetes aged 20 years or older, followed until December 31, 2019. Patients with diabetes or prediabetes were grouped according to quartiles of UHR, which was calculated as serum UA (mg/dL)/HDL-C (mg/dL). Kaplan-Meier survival analysis, multivariable Cox proportional hazards regression models, restricted cubic spline analysis, and threshold effects were performed to assess the association between baseline UHR and all-cause and cardiovascular mortality. Subgroup analysis and sensitivity analysis were also conducted.

Results

During a median follow-up of 80 months, a total of 2,748 (14.61%) deaths occurred, including 869 (4.63%) cardiovascular deaths. Kaplan-Meier survival analysis revealed that the highest quartile of UHR had the highest mortality rates. Multivariable Cox regression analysis indicated that individuals in the highest quartile of UHR had a significantly higher risk of all-cause mortality (HR: 1.24, 95% CI: 1.07-1.45) and cardiovascular mortality (HR: 1.56, 95% CI: 1.19-2.04) compared to those in the second quartile. A J-shaped association between UHR and both all-cause and cardiovascular mortality was observed, with threshold points of 13.73% and 9.39%, respectively. Specifically, when UHR was above the respective thresholds, the HRs of a 10% increment of UHR for all-cause mortality and cardiovascular mortality were 1.45 (95% CI: 1.31-1.61) and 1.38 (95% CI: 1.20-1.60). However, UHR below the threshold did not significantly correlate with mortality. Furthermore, subgroup analyses showed that the correlation of UHR with all-cause mortality was significantly modified by sex and age, with a persistent positive correlation observed in women and those aged < 60.

Conclusion

Higher UHR was correlated with increased all-cause and cardiovascular mortality in patients with diabetes or prediabetes.

Genomic network analysis characterizes genetic architecture and identifies trait-specific biology

Pervasive genetic overlap across human complex traits necessitates developing multivariate methods that can parse pleiotropic and trait-specific genetic signals. Here, we introduce Genomic Network Analysis (GNA), an analytic framework that applies the principles of network modelling to estimates of genetic overlap derived from genome-wide association study (GWAS) summary statistics. The result is a genomic network that describes the conditionally independent genetic associations between traits that remain when controlling for shared signal with the broader network of traits. Graph theory metrics provide added insight by formally quantifying the most important traits in the genomic network. GNA can discover additional trait-specific pathways by incorporating gene expression or genetic variants into the network to estimate their conditional associations with each trait. Extensive simulations establish GNA is well-powered for most GWAS. Application to a diverse set of traits demonstrate that GNA yields critical insight into the genetic architecture that demarcate genetically overlapping traits at varying levels of biological granularity.

Increasing the complexity of lipoprotein characterization for cardiovascular risk in type 2 diabetes

The burden of cardiovascular disease is particularly high among individuals with diabetes, even when LDL cholesterol is normal or within the therapeutic target. Despite this, cholesterol accumulates in their arteries, in part, due to persistent atherogenic dyslipidaemia characterized by elevated triglycerides, remnant cholesterol, smaller LDL particles and reduced HDL cholesterol. The causal link between dyslipidaemia and atherosclerosis in T2DM is complex, and our contention is that a deeper understanding of lipoprotein composition and functionality, the vehicle that delivers cholesterol to the artery, will provide insight for improving our understanding of the hidden cardiovascular risk of diabetes. This narrative review covers three levels of complexity in lipoprotein characterization: 1-the information provided by routine clinical biochemistry, 2-advanced nuclear magnetic resonance (NMR)-based lipoprotein profiling and 3-the identification of minor components or physical properties of lipoproteins that can help explain arterial accumulation in individuals with normal LDLc levels, which is typically the case in individuals with T2DM. This document highlights the importance of incorporating these three layers of lipoprotein-related information into population-based studies on ASCVD in T2DM. Such an attempt should inevitably run in parallel with biotechnological solutions that allow large-scale determination of these sets of methodologically diverse parameters.

HDL levels modulate the impact of type 2 diabetes susceptibility alleles in older adults

BACKGROUND

Type 2 Diabetes (T2D) is influenced by genetic, environmental, and ageing factors. Ageing pathways exacerbate metabolic diseases. This study aimed to examine both clinical and genetic factors of T2D in older adults.

METHODS

A total of 2,909 genotyped patients were enrolled in this study. Genome Wide Association Study was conducted, comparing T2D patients to non-diabetic older adults aged ≥ 60, ≥ 65, or ≥ 70 years, respectively. Binomial logistic regressions were applied to examine the association between T2D and various risk factors. Stepwise logistic regression was conducted to explore the impact of low HDL (HDL < 40 mg/dl) on the relationship between the genetic variants and T2D. A further validation step using data from the UK Biobank with 53,779 subjects was performed.

RESULTS

The association of T2D with both low HDL and family history of T2D increased with the age of control groups. T2D susceptibility variants (rs7756992, rs4712523 and rs10946403) were associated with T2D, more significantly with increased age of the control group. These variants had stronger effects on T2D risk when combined with low HDL cholesterol levels, especially in older control groups.

CONCLUSIONS

The findings highlight a critical role of age, genetic predisposition, and HDL levels in T2D risk. The findings suggest that individuals over 70 years who have high HDL levels without the T2D susceptibility alleles may be at the lowest risk of developing T2D. These insights can inform tailored preventive strategies for older adults, enhancing personalized T2D risk assessments and interventions.

The value of HDL subfractions in predicting cardiovascular outcomes in untreated, diabetic patients with stable coronary artery disease: An age- and gender-matched case-control study

OBJECTIVE

The aim of the present study was to examine the value of high-density lipoprotein (HDL) subfractions for predicting cardiovascular events (CVEs) in untreated type 2 diabetes mellitus (T2DM) patients with stable coronary artery disease (SCAD) using an age- and gender-matched case-control study.

METHODS

In total, 185 SCAD patients and 185 T2DM patients with SCAD were enrolled and subjected to a clinical follow-up of CVEs. HDL subfractions were analyzed using the Quantimetrix Lipoprint System. The relationship between HDL subfractions and CVEs in T2DM patients with SCAD was evaluated by Kaplan-Meier analysis and Cox proportional hazard models.

RESULTS

During a median 37.7-month follow-up, T2DM patients with SCAD had a higher percentage of CVEs compared to SCAD patients (p=0.039). The concentration of the combined intermediate and small HDL-C subfraction (defined as the mixed HDL subfraction) was related to the event incidence in T2DM patients with SCAD (p=0.004), and it was positively associated with increased CVEs even after adjustment in three models. Kaplan-Meier curve analysis indicated that T2DM patients with SCAD in the high mixed HDL subfraction group (>28 mg/dL) had lower event-free survival rates (p=0.008).

CONCLUSIONS

Elevated concentration of the mixed HDL subfraction concentration predicts events in T2DM patients with SCAD.

Associations of visit-to-visit variabilities and trajectories of serum lipids with the future probability of type 2 diabetes mellitus

Background

Serum lipid abnormalities are generally considered as a major risk factor for type 2 diabetes mellitus (T2DM). However, evidence for the effect of long-term serum lipid fluctuations on future T2DM probability remains limited.

Methods

A total of 4475 nondiabetic participants who underwent annual health examinations between 2010 and 2013 were followed for the subsequent 5-year risk of T2DM. The Cox proportional hazards model was performed to evaluate the associations of visit-to-visit variabilities and trajectories of triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-c) and low-density lipoprotein cholesterol (LDL-c) with T2DM probability.

Results

During the five-year follow-up, 223 newly developed T2DM cases were identified. Compared with the “Low” TG trajectory, “Moderate” and “Moderate-High” TG trajectories were significantly associated with T2DM incidence, with adjusted hazard ratios (HRs) and 95 % confidence intervals (CIs) of 1.51 (1.12-2.03) and 2.55 (1.62-4.03), respectively. Additionally, participants in the third and fourth quartiles of TG/standard deviation (SD) were associated with increased T2DM probability when compared with those in the lowest quartile. After excluding individuals with prediabetes, participants with “Moderate-High” TG trajectory still had a 2.43-fold greater risk of T2DM compared with those with “Low” TG trajectory (95 % CI: 1.28-4.63). In addition, compared with participants in “Low” HDL-c trajectory, the future T2DM probability was significantly reduced in those with “Moderate” and “High” HDL-c trajectories, with HR (95 % CI) of 0.52 (0.37-0.72) and 0.38 (0.18-0.80), respectively. After excluding individuals with prediabetes, the “Moderate” HDL-c trajectory remained associated with decreased T2DM probability when compared with “Low” HDL-c trajectory (HR: 0.55, 95 % CI: 0.35-0.88). However, the incidence of T2DM was not associated with the long-term fluctuations of TC and LDL-c.

Conclusions

Long-term visit-to-visit variability of TG, and the change trajectories of TG and HDL-c were significantly associated with future T2DM probability. Moreover, these associations were not affected after excluding individuals with prediabetes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12944-021-01592-9.

Predictive scores for identifying patients with type 2 diabetes mellitus at risk of acute myocardial infarction and sudden cardiac death

INTRODUCTION

The present study evaluated the application of incorporating non-linear J/U-shaped relationships between mean HbA1c and cholesterol levels into risk scores for predicting acute myocardial infarction (AMI) and non-AMI-related sudden cardiac death (SCD) respectively, amongst patients with type 2 diabetes mellitus.

METHODS

This was a territory-wide cohort study of patients with type 2 diabetes mellitus above the age 40 and free from prior AMI and SCD, with or without prescriptions of anti-diabetic agents between January 1st, 2009 to December 31st, 2009 at government-funded hospitals and clinics in Hong Kong. Patients recruited were followed up until 31 December 2019 or their date of death. Risk scores were developed for predicting incident AMI and non-AMI-related SCD. The performance of conditional inference survival forest (CISF) model compared to that of random survival forests (RSF) model and multivariate Cox model.

RESULTS

This study included 261 308 patients (age = 66.0 ± 11.8 years old, male = 47.6%, follow-up duration = 3552 ± 1201 days, diabetes duration = 4.77 ± 2.29 years). Mean HbA1c and low high-density lipoprotein-cholesterol (HDL-C) were significant predictors of AMI on multivariate Cox regression. Mean HbA1c was linearly associated with AMI, whilst HDL-C was inversely associated with AMI. Mean HbA1c and total cholesterol were significant multivariate predictors with a J-shaped relationship with non-AMI-related SCD. The AMI and SCD risk scores had an area under the curve (AUC) of 0.666 (95% confidence interval (CI) = [0.662, 0.669]) and 0.677 (95% CI = [0.673, 0.682]), respectively. CISF significantly improves prediction performance of both outcomes compared to RSF and multivariate Cox models.

CONCLUSION

A holistic combination of demographic, clinical and laboratory indices can be used for the risk stratification of patients with type 2 diabetes mellitus for AMI and SCD.

Independent association of atherogenic dyslipidaemia with all-cause mortality in individuals with type 2 diabetes and modifying effect of gender: a prospective cohort study

Background

Atherogenic dyslipidaemia has been implicated in the residual risk for cardiovascular morbidity and mortality, which remains despite attainment of LDL cholesterol goals especially in individuals with type 2 diabetes. However, its relationship with all-cause death has not been sufficiently explored. This analysis evaluated the independent association of increased triglycerides and triglyceride:HDL cholesterol ratio (TG:HDL) and decreased HDL cholesterol with total mortality and the possible modifying effect of gender in a large cohort of patients with type 2 diabetes.

Methods

This observational, prospective study enrolled 15,773 patients in 19 Diabetes Clinics throughout Italy in the years 2006–2008. Triglycerides and total and HDL cholesterol were measured by colorimetric enzymatic methods. Vital status was retrieved on 31 October 2015 for 15,656 patients (99.3%). Participants were stratified by quartiles of triglycerides, HDL cholesterol, and TG:HDL.

Results

There were 3,602 deaths over a follow-up 7.42 ± 2.05 years (31.0 × 1000 person-years). In the unadjusted analyses, the highest TG:HDL (but not triglyceride) and the lowest HDL cholesterol quartile were associated with increased death rate and mortality risk. When sequentially adjusting for confounders, including total, LDL, or non-HDL cholesterol and lipid-lowering treatment, mortality risk was significantly higher in the highest triglyceride (hazard ratio 1.167 [95% confidence interval 1.055–1.291], p = 0.003) and TG:HDL (1.192 [1.082–1.314], p < 0.0001) and the lowest HDL cholesterol (1.232 [1.117–1.360], p < 0.0001) quartile, though the association of triglycerides and HDL cholesterol disappeared after further adjustment for each other. Interaction with gender was significant only for HDL cholesterol (p = 0.0009). The relationship with death was stronger for triglycerides in males and HDL cholesterol in females, with these associations remaining significant even after adjustment for HDL cholesterol (1.161 [1.019–1.324], p = 0.025, for the highest vs the lowest triglyceride quartile) and triglycerides (1.366 [1.176–1.587], p < 0.0001, for the lowest vs the highest HDL cholesterol quartile).

Conclusions

In patients with type 2 diabetes, higher triglycerides and TG:HDL and lower HDL cholesterol were independently associated with increased all-cause mortality, with a modifying effect of gender for triglycerides and HDL cholesterol. These data suggest that atherogenic dyslipidaemia, especially TG:HDL, may serve as predictor of all-cause death in these individuals.

Trial registration ClinicalTrials.gov, NCT00715481, 15 July, 2008

Interaction between high-density lipoproteins and inflammation: Function matters more than concentration!

High-density lipoprotein (HDL) plays an important role in lipid metabolism and especially contributes to the reverse cholesterol transport pathway. Over recent years it has become clear that the effect of HDL on immune-modulation is not only dependent on HDL concentration but also and perhaps even more so on HDL function. This review will provide a concise general introduction to HDL followed by an overview of post-translational modifications of HDL and a detailed overview of the role of HDL in inflammatory diseases. The clinical potential of HDL and its main apolipoprotein constituent, apoA-I, is also addressed in this context. Finally, some conclusions and remarks that are important for future HDL-based research and further development of HDL-focused therapies are discussed.