Triglycerides: Emerging Targets in Diabetes Care? Review of Moderate Hypertriglyceridemia in Diabetes

Remnant cholesterol is more positively related to diabetes, prediabetes, and insulin resistance than conventional lipid parameters and lipid ratios: A multicenter, large sample survey

BACKGROUND

Not many large-sample investigations are available that compare the potency of the relationship of remnant cholesterol (RC) and other lipid parameters with diabetes and prediabetes. The goals of our study are to discover the relationship between RC and prediabetes, diabetes, and insulin resistance (IR) and to investigate RC, high-density lipoprotein cholesterol (HDL-C), non-HDL-C, triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), TC/HDL-C, LDL-C/HDL-C, and TG/HDL-C, which are the lipid parameters that are most positively related to diabetes, prediabetes, and IR.

METHODS

This research enrolled 36 684 subjects from China's eight provinces. We employed multiple logistic regression analysis for testing the relationship between lipid parameters and diabetes, prediabetes, and IR.

RESULTS

After adjusting for potential confounders, and comparing the results with other lipid parameters, the positive relationship between RC and diabetes (odds ratio [OR] 1.417, 95% confidence interval [CI]: 1.345-1.492), prediabetes (OR 1.555, 95% CI: 1.438-1.628), and IR (OR 1.488, 95% CI: 1.404-1.577) was highest. RC was still related to diabetes, prediabetes, and IR even when TG <2.3 mmol/L (diabetes: OR 1.256, 95% CI: 1.135-1.390; prediabetes: OR 1.503, 95% CI: 1.342-1.684; and IR: OR 1.278, 95% CI: 1.140-1.433), LDL-C <2.6 mmol/L (diabetes: OR 1.306, 95% CI: 1.203-1.418; prediabetes: OR 1.597, 95% CI: 1.418-1.798; and IR: OR 1.552, 95% CI: 1.416-1.701), or HDL-C ≥1 mmol/L (diabetes: OR 1.456, 95% CI: 1.366-1.550; prediabetes: OR 1.553, 95% CI: 1.421-1.697; and IR: OR 1.490, 95% CI: 1.389-1.598).

CONCLUSION

RC is more positively related to diabetes, prediabetes, and IR than conventional lipids and lipid ratios in the general population, the relationships between RC and diabetes, prediabetes, and IR are stable, even if HDL-C, LDL-C, or TG are at appropriate levels.

Sex differences in circulating metabolites across glycemic status and risk of coronary heart disease

Background

Women with type 2 diabetes (T2D) have a 50% excess risk of coronary heart disease (CHD) than men with T2D. We compared circulating metabolites and their associations with CHD in men and women across glycemic status.

Methods

We used metabolomic data (lipoproteins, fatty acids, amino acids, glycolysis, ketones, inflammation, and fluid balance) for 87,326 CHD-free UK Biobank participants. We used linear regressions to examine the association of sex and metabolites (log) in newly diagnosed T2D (diagnosis<2 yrs from baseline), prediabetes (A1c 5.7-6.5%), and euglycemia, accounting for age, race, Deprivation Index, income, smoking, alcohol drinking, obesity, physical activity, medications for hypertension, hyperlipidemia, and diabetes. We used Cox models to evaluate the association of metabolites and CHD risk by sex, adjusting the same covariates and menopausal status (women). All analyses were FDR-adjusted.

Findings

We included 1250 individuals with new T2D, 12,706 with prediabetes, and 83,315 with euglycemia. In adjusted linear regressions, women showed a progressive increase in atherogenic lipid and lipoprotein markers and inflammatory marker, glycoprotein acetyls, compared to men as their glycemic status advanced. However, women had lower levels of albumin during this transition. Menopausal status did not alter these sex differences. In a 10-year follow-up, an SD higher total TG, TG in VLDL, LDL, and HDL, saturated fatty acids (SFA) were positively associated with a higher risk of CHD in women with T2D but not in men (p-interactions 0.03-0.15).

Interpretation

With advancing glycemic status, women exhibited higher levels of atherogenic lipids and lipoproteins, as well as inflammatory markers, but lower circulating albumin. Women with T2D appear to be at a higher risk of CHD associated with TG, VLDL-TG, LDL-TG, and HDL-TG, and SFA than men with T2D.

A 3-year follow-up analysis of renal function in elderly patients with type 2 diabetes mellitus and an estimated glomerular filtration rate <90 mL/min/1.73m2: A retrospective cohort study

Type 2 diabetes mellitus (T2DM) is a risk factor for patients with impaired renal function. The onset of T2DM-induced diabetic kidney disease (DKD) is frequently sub-clinical, potentially culminating in end-stage renal disease. In the current study the factors influencing DKD in elderly patients diagnosed with T2DM were determined. A retrospective cohort study was conducted involving patients ≥60 years of age with T2DM from June 2019 to December 2022. The Cockcroft-Gault formula was used to estimate the glomerular filtration rate. The clinical information and biochemical indicators of patients with an estimated glomerular filtration rate (eGFR) < 90 mL/min/1.73m2 were collected. Patients were grouped based on a 3-year eGFR decline < 15% and ≥ 15%. The differences between the two groups were compared and the factors influencing the 3-year eGFR decline ≥ 15% were analyzed. A total of 242 patients were included, including 154 in the group with a 3-year eGFR decline < 15% and 88 in the group with a three-year eGFR decline ≥ 15%. Univariate logistic regression analysis showed that smoking cigarettes, and triglycerides (TG) and high-density lipoprotein levels were related to a 3-year eGFR decline ≥ 15% (P = .039, P < .001, and P = .011, respectively). Multivariate logistic regression analysis showed that the TG level was independently related to a 3-year eGFR decline ≥ 15% (P = .004; OR = 2.316). There was a significant linear relationship between the eGFR decline and TG level (P = .002). Patients with a TG concentration > 1.7 mmol/L had a more apparent decrease in the eGFR (P < .05). For elderly patients with T2DM and an eGFR < 90 mL/min/1.73m2, the TG level may be an important risk factor for deteriorating renal function that warrants actively intervention.

Comparison of Lipid Profiles Between Prediabetic and Non-prediabetic Young Adults

Introduction Insulin resistance is considered a key component in the pathophysiology of prediabetes. Derangement in lipid parameters can occur in prediabetics that predispose to cardiovascular complications. Material and methods We performed an observational cross-sectional analytical study in a tertiary level Acharya Vinoba Bhave hospital, Sawangi, Wardha to compare the lipid profile in prediabetics with non-prediabetic young individuals between 18 and 35 age group in terms of parameters such as total cholesterol, triglyceride (TG), low-density lipoproteins (LDL) cholesterol, very low-density lipoprotein (VLDL) cholesterol, and high-density lipoprotein (HDL) cholesterol. Results We observed that prediabetics have significantly elevated total cholesterol, LDL cholesterol, VLDL cholesterol, and TG; and significantly reduced HDL cholesterol compared with the controls (p<0.001 each). Conclusion We conclude that the lipid parameters are deranged in prediabetics and this might contribute to the risk associated with dyslipidemia in this population.

Effect of transgenerational diabetes via maternal lineage in female rats

Aim

To investigate the transgenerational effect of maternal hyperglycemia on oxidative stress markers, lipid profile, glycemia, pancreatic beta (β)-cells, and reproductive outcomes in the F2 adult generation. Additionally, to expand the knowledge on transgenerational diabetes the F3 generation at birth will be evaluated.

Methods

On day 5 of postnatal life female Sprague-Dawley rat newborns (F0 generation) were distributed into two groups: Diabetic (Streptozotocin-STZ, 70 mg/kg body weight, subcutaneous route) and Control rats. Adult female rats from the F0 generation and subsequently the F1 generation were mated to obtain the F2 generation, which was distributed into F2 generation (granddaughters) from control (F2_C) and diabetic (F2_D) rats. Oral Glucose Tolerance Test (OGTT), the area under the curve (AUC), blood biochemical analyses, and pancreatic morphology were analyzed before pregnancy. Reproductive outcomes were performed at the end of pregnancy. At birth, the glycemia and body weight of F3_C and F3_D rats were determined. p < 0.05 was considered significant.

Results

F2_D had higher body weight, triglyceride levels, and percentage of insulin-immunostained cells, contributing to glucose intolerance, and insulin resistance before pregnancy. At day 21 of pregnancy, the F2_D showed increased embryonic losses before and after implantation (84.33 and 83.74 %, respectively). At birth, F3_D presented hyperglycemia, and 16.3 % of newborns were large for pregnancy age (LGA).

Conclusion

Diabetes induction since the neonatal period in the first generation (F0) led to transgenerational (F2 and F3 generations) changes via the maternal lineage of female rats, confirming the relevance of control strictly the glycemia all the time.

Untargeted lipidomics analysis in women with morbid obesity and type 2 diabetes mellitus: A comprehensive study

There is a phenotype of obese individuals termed metabolically healthy obese that present a reduced cardiometabolic risk. This phenotype offers a valuable model for investigating the mechanisms connecting obesity and metabolic alterations such as Type 2 Diabetes Mellitus (T2DM). Previously, in an untargeted metabolomics analysis in a cohort of morbidly obese women, we observed a different lipid metabolite pattern between metabolically healthy morbid obese individuals and those with associated T2DM. To validate these findings, we have performed a complementary study of lipidomics. In this study, we assessed a liquid chromatography coupled to a mass spectrometer untargeted lipidomic analysis on serum samples from 209 women, 73 normal-weight women (control group) and 136 morbid obese women. From those, 65 metabolically healthy morbid obese and 71 with associated T2DM. In this work, we find elevated levels of ceramides, sphingomyelins, diacyl and triacylglycerols, fatty acids, and phosphoethanolamines in morbid obese vs normal weight. Conversely, decreased levels of acylcarnitines, bile acids, lyso-phosphatidylcholines, phosphatidylcholines (PC), phosphatidylinositols, and phosphoethanolamine PE (O-38:4) were noted. Furthermore, comparing morbid obese women with T2DM vs metabolically healthy MO, a distinct lipid profile emerged, featuring increased levels of metabolites: deoxycholic acid, diacylglycerol DG (36:2), triacylglycerols, phosphatidylcholines, phosphoethanolamines, phosphatidylinositols, and lyso-phosphatidylinositol LPI (16:0). To conclude, analysing both comparatives, we observed decreased levels of deoxycholic acid, PC (34:3), and PE (O-38:4) in morbid obese women vs normal-weight. Conversely, we found elevated levels of these lipids in morbid obese women with T2DM vs metabolically healthy MO. These profiles of metabolites could be explored for the research as potential markers of metabolic risk of T2DM in morbid obese women.

Nonlinear relationship between untraditional lipid parameters and the risk of prediabetes: a large retrospective study based on Chinese adults

BACKGROUND

Abnormal lipid metabolism poses a risk for prediabetes. However, research on lipid parameters used to predict the risk of prediabetes is scarce, and the significance of traditional and untraditional lipid parameters remains unexplored in prediabetes. This study aimed to comprehensively evaluate the association between 12 lipid parameters and prediabetes and their diagnostic value.

METHODS

This cross-sectional study included data from 100,309 Chinese adults with normal baseline blood glucose levels. New onset of prediabetes was the outcome of concern. Untraditional lipid parameters were derived from traditional lipid parameters. Multivariate logistic regression and smooth curve fitting were used to examine the nonlinear relationship between lipid parameters and prediabetes. A two-piecewise linear regression model was used to identify the critical points of lipid parameters influencing the risk of prediabetes. The areas under the receiver operating characteristic curve estimated the predictive value of the lipid parameters.

RESULTS

A total of 12,352 participants (12.31%) were newly diagnosed with prediabetes. Following adjustments for confounding covariables, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol were negatively correlated with prediabetes risk. Conversely, total cholesterol, triglyceride (TG), lipoprotein combine index (LCI), atherogenic index of plasma (AIP), non-HDL-C, atherogenic coefficient, Castelli's index-I, remnant cholesterol (RC), and RC/HDL-C ratio displayed positive correlations. In younger adults, females, individuals with a family history of diabetes, and non-obese individuals, LCI, TG, and AIP exhibited higher predictive values for the onset of prediabetes compared to other lipid profiles.

CONCLUSION

Nonlinear associations were observed between untraditional lipid parameters and the risk of prediabetes. The predictive value of untraditional lipid parameters for prediabetes surpassed that of traditional lipid parameters, with LCI emerging as the most effective predictor for prediabetes.

Metabolomic analysis indicated changes in triacylglycerols' levels as a result of training in Whippet dogs

Regular physical effort produces metabolic changes manifested as adaptation to exercise and increasing performance. In humans these changes have been characterized at metabolome level as depending on the discipline. However, all sports involve some level of changes in protein, carbohydrate and lipid metabolism. Recently, also performance horses have been subjected to metabolic analyses, but similar studies were lacking in sports dogs. In this study we performed the metabolomic analysis in plasma of Whippet dogs regularly trained and competing in coursing events, and untrained dogs of the same breed, fed with the same diet. We have also compared the hematological and blood biochemical results in these two groups of dogs. Basic blood tests indicated that enzymes related to lipid metabolism (lipase and gamma-glutamyltransferase) differed considerably between the groups. Metabolomic analysis of plasma confirmed the metabolic shift expressed as the differences in triacylglycerols levels between training and non-training dogs, aimed at improving the use of fatty acids as a source of energy during exertion. Surprisingly, other classes of metabolites were only hardly changed when comparing training and non-training Whippets.

High residual cardiovascular risk after lipid-lowering: prime time for Predictive, Preventive, Personalized, Participatory, and Psycho-cognitive medicine

As time has come to translate trial results into individualized medical diagnosis and therapy, we analyzed how to minimize residual risk of cardiovascular disease (CVD) by reviewing papers on "residual cardiovascular disease risk". During this review process we found 989 papers that started off with residual CVD risk after initiating statin therapy, continued with papers on residual CVD risk after initiating therapy to increase high-density lipoprotein-cholesterol (HDL-C), followed by papers on residual CVD risk after initiating therapy to decrease triglyceride (TG) levels. Later on, papers dealing with elevated levels of lipoprotein remnants and lipoprotein(a) [Lp(a)] reported new risk factors of residual CVD risk. And as new risk factors are being discovered and new therapies are being tested, residual CVD risk will be reduced further. As we move from CVD risk reduction to improvement of patient management, a paradigm shift from a reductionistic approach towards a holistic approach is required. To that purpose, a personalized treatment dependent on the individual's CVD risk factors including lipid profile abnormalities should be configured, along the line of P5 medicine for each individual patient, i.e., with Predictive, Preventive, Personalized, Participatory, and Psycho-cognitive approaches.

Body composition and risk factors for cardiovascular disease in global multi-ethnic populations

BACKGROUND

No large-scale studies have compared associations between body composition and cardiovascular risk factors across multi-ethnic populations.

METHODS

Population-based surveys included 30,721 Malay, 10,865 Indian and 25,296 Chinese adults from The Malaysian Cohort, and 413,737 White adults from UK Biobank. Sex-specific linear regression models estimated associations of anthropometry and body composition (body mass index [BMI], waist circumference [WC], fat mass, appendicular lean mass) with systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-C), triglycerides and HbA1c.

RESULTS

Compared to Malay and Indian participants, Chinese adults had lower BMI and fat mass while White participants were taller with more appendicular lean mass. For BMI and fat mass, positive associations with SBP and HbA1c were strongest among the Chinese and Malay and weaker in White participants. Associations with triglycerides were considerably weaker in those of Indian ethnicity (eg 0.09 [0.02] mmol/L per 5 kg/m2 BMI in men, vs 0.38 [0.02] in Chinese). For appendicular lean mass, there were weak associations among men; but stronger positive associations with SBP, triglycerides, and HbA1c, and inverse associations with LDL-C, among Malay and Indian women. Associations between WC and risk factors were generally strongest in Chinese and weakest in Indian ethnicities, although this pattern was reversed for HbA1c.

CONCLUSION

There were distinct patterns of adiposity and body composition and cardiovascular risk factors across ethnic groups. We need to better understand the mechanisms relating body composition with cardiovascular risk to attenuate the increasing global burden of obesity-related disease.

Algorithms for Treating Dyslipidemia in Youth

PURPOSE OF REVIEW

The goal of this article is to review algorithms for treating dyslipidemia in youth, discuss pitfalls, propose enhanced algorithms to address pitfalls, and consider future directions.

RECENT FINDINGS

The presence of modifiable and non-modifiable cardiovascular disease (CVD) risk factors during childhood is associated with CVD-related events in adulthood. Recent data has shown that childhood initiation of statin therapy in youth < 18 years of age with familial hypercholesterolemia reduces the risk of adult CVD. However, pediatric dyslipidemia remains undertreated in part due to a lack of primary health care providers with adequate understanding of screening guidelines and pediatric lipidologists with experience in treatment and follow-up of this unique population. Management algorithms have been published by the National Heart, Lung, and Blood Institute and American Heart Association as tools to empower clinicians to manage dyslipidemia. We propose enhanced algorithms, which incorporate recently approved pharmacotherapy to address the management gaps. Future algorithms based upon clinical risk scores may enhance treatment and improve outcomes. Algorithms for dyslipidemia management which target youth < 18 years of age are tools which empower clinicians to manage dyslipidemia in this unique population. Enhanced algorithms may help address pitfalls. We acknowledge the need for further risk assessment tools in pediatrics for tailored dyslipidemia management.

Association between time in range 70-180 mg/dl in early stage and severity with in patients acute pancreatitis

BACKGROUND

It is not well understood whether glucose control in the early stage of acute pancreatitis(AP) is related to outcome. This study aimed to investigate the association between blood glucose time in range (TIR) of 70-180 mg/dL in the first 72 h(h) on admission and the progression of AP.

METHODS

Individuals admitted with AP to the Gastroenterology Department of the Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University between January 2017 and December 2021 were included and retrospectively evaluated. The percentage of TIR between 70 and 180 mg/dL in the first 72 h was calculated. According to the progress of AP at discharge, patients were divided into mild pancreatitis(MAP), and moderately severe acute pancreatitis (MSAP), or severe acute pancreatitis (SAP) groups. We examined the association between TIR or TIR ≥ 70% and AP severity using logistic regression models stratified by a glycosylated hemoglobin (HbA1c) level of 6.5%. Receiver operating characteristic (ROC) curves were generated to assess the ability of the TIR to predict MSAP or SAP.

RESULTS

A total of 298 individuals were included, of whom 35 developed MSAP or SAP. Logistic regression analyses indicated that TIR was independently associated with the incidence of more serious AP (odds ratio [OR] = 0.962, 95% CI = 0.941-0.983, p = 0.001). This association remained significant in individuals with HbA1c levels ≤ 6.5% (OR = 0.928, 95% CI = 0.888-0.969, p = 0.001). A TIR ≥ 70% was independently associated with reduced severity only in people with well-antecedent controls (OR = 0.238; 95% CI = 0.071-0.802; p = 0.020). TIR was not powerful enough to predict the severity of AP in both patients with poor antecedent glucose control (AUC = 0.641) or with HbA1c < 6.5% (AUC = 0.668).

CONCLUSIONS

TIR was independently associated with severity in patients with AP, particularly those with good antecedent glucose control.

An Ethyl Acetate Extract of Eryngium carlinae Inflorescences Attenuates Oxidative Stress and Inflammation in the Liver of Streptozotocin-Induced Diabetic Rats

Secondary metabolites such as flavonoids are promising in the treatment of non-alcoholic fatty liver disease (NAFLD), which is one of the complications of diabetes due to oxidative stress and inflammation. Some plants, such as Eryngium carlinae, have been investigated regarding their medicinal properties in in vitro and in vivo assays, showing favorable results for the treatment of various diseases such as diabetes and obesity. The present study examined the antioxidant and anti-inflammatory effects of the phenolic compounds present in an ethyl acetate extract of the inflorescences of Eryngium carlinae on liver homogenates and mitochondria from streptozotocin (STZ)-induced diabetic rats. Phenolic compounds were identified and quantified by UHPLC-MS. In vitro assays were carried out to discover the antioxidant potential of the extract. Male Wistar rats were administered with a single intraperitoneal injection of STZ (45 mg/kg) and were given the ethyl acetate extract at a level of 30 mg/kg for 60 days. Phytochemical assays showed that the major constituents of the extract were flavonoids; in addition, the in vitro antioxidant activity was dose dependent with IC50 = 57.97 mg/mL and IC50 = 30.90 mg/mL in the DPPH and FRAP assays, respectively. Moreover, the oral administration of the ethyl acetate extract improved the effects of NAFLD, decreasing serum and liver triacylglycerides (TG) levels and oxidative stress markers and increasing the activity of the antioxidant enzymes. Likewise, it attenuated liver damage by decreasing the expression of NF-κB and iNOS, which lead to inflammation and liver damage. We hypothesize that solvent polarity and consequently chemical composition of the ethyl acetate extract of E. carlinae, exert the beneficial effects due to phenolic compounds. These results suggest that the phenolic compounds of the ethyl acetate extract of E. carlinae have antioxidant, anti-inflammatory, hypolipidemic, and hepatoprotective activity.

Metabolic drivers of dysglycemia in pregnancy: ethnic-specific GWAS of 146 metabolites and 1-sample Mendelian randomization analyses in a UK multi-ethnic birth cohort

Introduction

Gestational diabetes mellitus (GDM) is the most common pregnancy complication worldwide and is associated with short- and long-term health implications for both mother and child. Prevalence of GDM varies between ethnicities, with South Asians (SAs) experiencing up to three times the risk compared to white Europeans (WEs). Recent evidence suggests that underlying metabolic difference contribute to this disparity, but an investigation of causality is required.

Methods

To address this, we paired metabolite and genomic data to evaluate the causal effect of 146 distinct metabolic characteristics on gestational dysglycemia in SAs and WEs. First, we performed 292 GWASs to identify ethnic-specific genetic variants associated with each metabolite (P ≤ 1 x 10-5) in the Born and Bradford cohort (3688 SA and 3354 WE women). Following this, a one-sample Mendelian Randomisation (MR) approach was applied for each metabolite against fasting glucose and 2-hr post glucose at 26-28 weeks gestation. Additional GWAS and MR on 22 composite measures of metabolite classes were also conducted.

Results

This study identified 15 novel genome-wide significant (GWS) SNPs associated with tyrosine in the FOXN and SLC13A2 genes and 1 novel GWS SNP (currently in no known gene) associated with acetate in SAs. Using MR approach, 14 metabolites were found to be associated with postprandial glucose in WEs, while in SAs a distinct panel of 11 metabolites were identified. Interestingly, in WEs, cholesterols were the dominant metabolite class driving with dysglycemia, while in SAs saturated fatty acids and total fatty acids were most commonly associated with dysglycemia.

Discussion

In summary, we confirm and demonstrate the presence of ethnic-specific causal relationships between metabolites and dysglycemia in mid-pregnancy in a UK population of SA and WE pregnant women. Future work will aim to investigate their biological mechanisms on dysglycemia and translating this work towards ethnically tailored GDM prevention strategies.

Exploring the Complex Relationship between Diabetes and Cardiovascular Complications: Understanding Diabetic Cardiomyopathy and Promising Therapies

Diabetes mellitus (DM) and cardiovascular complications are two unmet medical emergencies that can occur together. The rising incidence of heart failure in diabetic populations, in addition to apparent coronary heart disease, ischemia, and hypertension-related complications, has created a more challenging situation. Diabetes, as a predominant cardio-renal metabolic syndrome, is related to severe vascular risk factors, and it underlies various complex pathophysiological pathways at the metabolic and molecular level that progress and converge toward the development of diabetic cardiomyopathy (DCM). DCM involves several downstream cascades that cause structural and functional alterations of the diabetic heart, such as diastolic dysfunction progressing into systolic dysfunction, cardiomyocyte hypertrophy, myocardial fibrosis, and subsequent heart failure over time. The effects of glucagon-like peptide-1 (GLP-1) analogues and sodium-glucose cotransporter-2 (SGLT-2) inhibitors on cardiovascular (CV) outcomes in diabetes have shown promising results, including improved contractile bioenergetics and significant cardiovascular benefits. The purpose of this article is to highlight the various pathophysiological, metabolic, and molecular pathways that contribute to the development of DCM and its significant effects on cardiac morphology and functioning. Additionally, this article will discuss the potential therapies that may be available in the future.

Effects of stopping criterion on the growth of trees in regression random forests

Random forests are a powerful machine learning tool that capture complex relationships between independent variables and an outcome of interest. Trees built in a random forest are dependent on several hyperparameters, one of the more critical being the node size. The original algorithm of Breiman, controls for node size by limiting the size of the parent node, so that a node cannot be split if it has less than a specified number of observations. We propose that this hyperparameter should instead be defined as the minimum number of observations in each terminal node. The two existing random forest approaches are compared in the regression context based on estimated generalization error, bias-squared, and variance of resulting predictions in a number of simulated datasets. Additionally the two approaches are applied to type 2 diabetes data obtained from the National Health and Nutrition Examination Survey. We have developed a straightforward method for incorporating weights into the random forest analysis of survey data. Our results demonstrate that generalization error under the proposed approach is competitive to that attained from the original random forest approach when data have large random error variability. The R code created from this work is available and includes an illustration.

Gender and urban-rural residency based differences in the prevalence of type-2 diabetes mellitus and its determinants among adults in Naghadeh: Results of IraPEN survey

BACKGROUND

Type 2 diabetes mellitus (T2DM) is one of the most important risk factors for cardiovascular diseases, with a high economic burden on health care systems. Since gender and residency can affect people's lifestyle and health behaviors, this study was conducted to investigate the prevalence of T2DM and its determinants by gender and residency.

METHODS

A secondary analysis study was conducted on the survey data of the IraPEN (Iran's Package of Essential Non-Communicable Disease) pilot program conducted in 2017 in Naghadeh County, Iran. Data of 3,691 participants aged 30-70 years from rural and urban areas of the County were included into data analysis process. Sociodemographic factors, anthropometric measurements, and cardiovascular risk factors related to T2DM were assessed.

RESULTS

The overall prevalence of T2DM within the population was 13.8%, which was significantly higher among women (15.5%) than men (11.8%), and non-significantly higher in urban (14.5%) areas than rural (12.3%) areas. In both genders, age (male: OR 1.01, 95% CI: 1.00-1.03; P = 0.012; female: OR 1.03, 95% CI: 1.02-1.04; P<0.001), blood pressure (male: OR 1.77, 95% CI: 1.13-2.79; P = 0.013; female: OR 2.86, 95% CI: 2.12-3.85; P<0.001), and blood triglycerides (male: OR 1.46, 95% CI: 1.01-2.11; P = 0.04; female: OR 1.34, 95% CI: 1.02-1.77; P = 0.035) had a significant relationship with the chance of developing T2DM. Among women, a significant relationship was found between abdominal obesity (OR 1.68, 95% CI: 1.17-2.40; P = 0.004) and the chance of developing T2DM. Age (rural: OR 1.03, 95% CI: 1.01-1.04; P<0.001; urban: OR 1.02, 95% CI: 1.01-1.04; P<0.001), blood pressure (rural: OR 3.14, 95% CI: 2.0-4.93; P<0.001; urban: OR 2.23, 95% CI: 1.66-3; P<0.001), and abdominal obesity (rural: OR 2.34, 95% CI: 1.41-3.87; P = 0.001; urban: OR 1.46, 95% CI: 1.06-2.01; P = 0.019), in both rural and urban areas, blood cholesterol (OR 1.59, 95% CI: 1.07-2.37; P = 0.02) in rural areas, and blood triglycerides (OR 1.51, 95% CI: 1.16-1.98; P = 0.002) in urban areas were significant predictors of T2DM.

CONCLUSION

Given the higher prevalence of T2DM among females, risk reduction strategies at the community level should be more targeted at women. The higher prevalence of T2DM risk factors among the urban population is a wake-up call for policymakers to pay more attention to the consequences of unhealthy and sedentary lifestyles within urban communities. Future actions should be focused on appropriate timely action plans for the prevention and control of T2DM from early years of life.

Paper-based colorimetric glucose sensor using Prussian blue nanoparticles as mimic peroxidase

A novel paper-based colorimetric glucose sensor was proposed employing Prussian blue nanoparticles (PB NPs) as mimic peroxidase. The sensor was manufactured by spraying solution containing PB NPs, glucose oxidase and chromogenic agents into a paper, then coating the filter layer and spreading layer on the top. The layer-by-layer structure enabled the sensor detect glucose in whole blood, as well as elimination of the coffee-ring effect which ensure the performance. As a powerful alternative to natural peroxidase, PB NPs showed the mimic enzymatic activity well preserved in dry environment. The manufacture process of the sensor is easy to be industrialized. Under optimal conditions, the sensor exhibited a linear range from 2.5 mM to 25 mM for glucose in blood with satisfactory reproducibility (the coefficient of variant <4%), great storage stability (1 month at 45 °C) and excellent linearity compared with those commercial kits (R > 0.99). Coupled with a handhold device, the PB NPs-based test strip realized the goal of personal operation, user-friendly control, automatic readouts, and data storage, and able to link the Cloud, showing unique potential in clinical application, especially in community-level medical scenarios.

Systematic metabolic characterization of mental disorders reveals age‐related metabolic disturbances as potential risk factors for depression in older adults

Mental disorders are associated with dysregulated metabolism, but comprehensive investigations of their metabolic similarities and differences and their clinical relevance are few. Here, based on the plasma metabolome and lipidome of subcohort1, comprising 100 healthy participants, 55 cases with anxiety, 52 persons with depression, and 41 individuals with comorbidity, which are from WCHAT, a perspective cohort study of community‐dwelling older adults aged over 50, multiple metabolites as potential risk factors of mental disorders were identified. Furthermore, participants with mental illnesses were classified into three subtypes (S1, S2, and S3) by unsupervised classification with lipidomic data. Among them, S1 showed higher triacylglycerol and lower sphingomyelin, while S2 displayed opposite features. The metabolic profile of S3 was like that of the normal group. Compared with S3, individuals in S1 and S2 had worse quality of life, and suffered more from sleep and cognitive disorders. Notably, an assessment of 6,467 individuals from the WCHAT showed an age‐related increase in the incidence of depression. Seventeen depression‐related metabolites were significantly correlated with age, which were validated in an independent subcohort2. Collectively, this work highlights the clinical relevance of metabolic perturbation in mental disorders, and age‐related metabolic disturbances may be a bridge‐linking aging and depressive.

1-2 Drinks Per Day Affect Lipoprotein Composition after 3 Weeks-Results from a Cross-Over Pilot Intervention Trial in Healthy Adults Using Nuclear Magnetic Resonance-Measured Lipoproteins and Apolipoproteins

Alcohol consumption ranging from 1−2 drinks/day associates with a lower risk of coronary heart disease in some studies. The underlying mechanisms are unclear. The Metabolic Imprints of Alcoholic Beverages (MetAl) trial aimed to explore the short-term effects of moderate alcohol consumption on cardiovascular biomarkers. A 2 × 3-week cross-over single-blinded intervention trial investigating the effect of 1−2 drinks/day (~12−24 g) compared with abstention on 1H Nuclear Magnetic Resonance-measured main lipoproteins and subfractions was performed in 26 healthy adults. Volunteers were classified as occasional or habitual drinkers based on their habitual alcohol intakes (<2 or ≥2 drinks/week). Compared with abstention, 1−2 drinks/day increased HDL2a-C (p = 0.004), HDL3-C (p = 0.008), and HDL non-significantly (p = 0.19). Total apoA1 and apoA1 in HDL and its subfractions increased (p < 0.05). Novel findings were a decreased apoB/apoA1 ratio (p = 0.02), and increased HDL2a phospholipid content (p = 0.04). In women alone, the results were similar but attenuated, and LDL-P decreased. Thus, changes in apoA1- and HDL-related biomarkers occur within weeks in moderate drinkers. Compared with abstention, 1−2 drinks/day increased total apoA1 more strongly than HDL-C and increased the cholesterol, apoA1, and phospholipid content of several HDL subfractions. Whether this provides a cardiovascular benefit requires further study. Clinicaltrials.gov: NCT03384147.

Evaluation of the value of conventional and unconventional lipid parameters for predicting the risk of diabetes in a non-diabetic population

BACKGROUND

Conventional and unconventional lipid parameters are associated with diabetes risk, the comparative studies on lipid parameters for predicting future diabetes risk, however, are still extremely limited, and the value of conventional and unconventional lipid parameters in predicting future diabetes has not been evaluated. This study was designed to determine the predictive value of conventional and unconventional lipid parameters for the future development of diabetes.

METHODS

The study was a longitudinal follow-up study of 15,464 participants with baseline normoglycemia. At baseline, conventional lipid parameters such as low-density lipoprotein cholesterol (LDL-C), triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) were measured/calculated, and unconventional lipid parameters such as non-HDL-C, remnant cholesterol (RC), LDL/HDL-C ratio, TG/HDL-C ratio, non-HDL/HDL-C ratio, TC/HDL-C ratio and RC/HDL-C ratio were calculated. Hazard ratio (HR) and 95% confidence interval (CI) were estimated by Cox proportional hazard regression adjusting for demographic and diabetes-related risk factors. The predictive value and threshold fluctuation intervals of baseline conventional and unconventional lipid parameters for future diabetes were evaluated by the time-dependent receiver operator characteristics (ROC) curve.

RESULTS

The incidence rate of diabetes was 3.93 per 1000 person-years during an average follow-up period of 6.13 years. In the baseline non-diabetic population, only TG and HDL-C among the conventional lipid parameters were associated with future diabetes risk, while all the unconventional lipid parameters except non-HDL-C were significantly associated with future diabetes risk. In contrast, unconventional lipid parameters reflected diabetes risk better than conventional lipid parameters, and RC/HDL-C ratio was the best lipid parameter to reflect the risk of diabetes (HR: 6.75, 95% CI 2.40-18.98). Sensitivity analysis further verified the robustness of this result. Also, time-dependent ROC curve analysis showed that RC, non-HDL/HDL-C ratio, and TC/HDL-C ratio were the best lipid parameters for predicting the risk of medium-and long-term diabetes.

CONCLUSIONS

Unconventional lipid parameters generally outperform conventional lipid parameters in assessing and predicting future diabetes risk. It is suggested that unconventional lipid parameters should also be routinely evaluated in clinical practice.

Lipid traits and type 2 diabetes risk in African ancestry individuals: A Mendelian Randomization study

BACKGROUND

Dyslipidaemia is highly prevalent in individuals with type 2 diabetes mellitus (T2DM). Numerous studies have sought to disentangle the causal relationship between dyslipidaemia and T2DM liability. However, conventional observational studies are vulnerable to confounding. Mendelian Randomization (MR) studies (which address this bias) on lipids and T2DM liability have focused on European ancestry individuals, with none to date having been performed in individuals of African ancestry. We therefore sought to use MR to investigate the causal effect of various lipid traits on T2DM liability in African ancestry individuals.

METHODS

Using univariable and multivariable two-sample MR, we leveraged summary-level data for lipid traits and T2DM liability from the African Partnership for Chronic Disease Research (APCDR) (N = 13,612, 36.9% men) and from African ancestry individuals in the Million Veteran Program (Ncases = 23,305 and Ncontrols = 30,140, 87.2% men), respectively. Genetic instruments were thus selected from the APCDR after which they were clumped to obtain independent instruments. We used a random-effects inverse variance weighted method in our primary analysis, complementing this with additional sensitivity analyses robust to the presence of pleiotropy.

FINDINGS

Increased genetically proxied low-density lipoprotein cholesterol (LDL-C) and total cholesterol (TC) levels were associated with increased T2DM liability in African ancestry individuals (odds ratio (OR) [95% confidence interval, P-value] per standard deviation (SD) increase in LDL-C = 1.052 [1.000 to 1.106, P = 0.046] and per SD increase in TC = 1.089 [1.014 to 1.170, P = 0.019]). Conversely, increased genetically proxied high-density lipoprotein cholesterol (HDL-C) was associated with reduced T2DM liability (OR per SD increase in HDL-C = 0.915 [0.843 to 0.993, P = 0.033]). The OR on T2DM per SD increase in genetically proxied triglyceride (TG) levels was 0.884 [0.773 to 1.011, P = 0.072] . With respect to lipid-lowering drug targets, we found that genetically proxied 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) inhibition was associated with increased T2DM liability (OR per SD decrease in genetically proxied LDL-C = 1.68 [1.03-2.72, P = 0.04]) but we did not find evidence of a relationship between genetically proxied proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibition and T2DM liability.

INTERPRETATION

Consistent with MR findings in Europeans, HDL-C exerts a protective effect on T2DM liability and HMGCR inhibition increases T2DM liability in African ancestry individuals. However, in contrast to European ancestry individuals, LDL-C may increase T2DM liability in African ancestry individuals. This raises the possibility of ethnic differences in the metabolic effects of dyslipidaemia in T2DM.

FUNDING

See the Acknowledgements section for more information.

Significance of Lipid Profile Parameters in Predicting Pre-Diabetes

In prediabetes, blood glucose levels are higher than normal; however, they remain below the diabetes threshold. Studies conducted on biomarkers for this disease result in controlling diabetes mellitus (DM) or reducing the risk of developing complications. Lipid profile parameters are considered important predictors of DM. Therefore, this study was conducted on three groups of normoglycemic (n=30), pre-diabetics (n=125), and diabetics (n=30) to recognize the predictive role of lipid parameters in the transition from pre-diabetes to diabetes. In this experiment, in addition to total cholesterol and triglycerides, very-low-density lipoprotein (VLDL), low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglyceride/HDL ratio, and fasting triglyceride-fasting blood glucose (FBG) index were measured. Based on the results, medians for total cholesterol, LDL, HDL, LDL/HDL ratio, cholesterol/HDL ratio, and LDL/HDL ratio did not differ significantly across the groups of normoglycemia, prediabetes, and diabetes. For triglyceride, the medians were significantly higher in pre-diabetes and also diabetes, compared to normoglycemia (i.e., 127.9 and 129.1 vs. 94.5 mg/dL, respectively [P<0.001]). Moreover, the same results were observed in the case of VLDL (i.e., 25.6 and 30.9 vs. 18.9 mg/dL, respectively). The triglyceride/HDL ratio significantly increased pre-diabetics and diabetics, compared to normoglycemic (2.72 and 2.67 vs. 2.18, respectively). Moreover, the median of the triglyceride-FBG index significantly had an increase in pre-diabetics and diabetics, compared to normoglycemic (8.89 and 9.38 vs. 8.22, respectively). The importance of triglyceride, VLDL, triglyceride/HDL ratio, and triglyceride-FBG index in distinguishing between pre-diabetes and normoglycemia was verified by a receiver operating characteristic curve analysis of the results. Logistic regression analysis confirmed the risk effects of the four parameters on pre-diabetes and diabetes. Therefore, triglyceride, VLDL, triglyceride-FBG index, and triglyceride/HDL ratio are considered promising biomarkers used to predict pre-diabetes and DM in the general population.

New metabolic health definition might not be a reliable predictor for diabetes in the nonobese Chinese population

AIM

To investigate the predictive values of the new metabolic health (MH) definition for future diabetes in a nonobese Chinese population, compared with the MH definition from metabolic syndrome (MetS).

METHODS

The data were collected in 1992 and then again in 2007 from the same group of 653 participants. The risk assessment of the new MH definition and the MH definition from MetS for future diabetes was performed by Cox regression analysis with overlap weighting as the primary analysis.

RESULTS

During the follow-up, 62 participants were diagnosed with diabetes. In the primary analysis with overlap weighting, there was no significant association between new MH and diabetes (HR: 1.12; 95% CI: 0.45-2.78, p = 0.803); conversely, based on the MH definition from MetS, the participants with MH were less likely to have had diabetes than the participants with MUHs (HR: 0.41; 95% CI: 0.22-0.78, p = 0.007). Furthermore, other analysis methods also confirmed the reproducibility of abovementioned results. In addition, sensitivity analysis excluding participants with prediabetes also demonstrated similar results with the primary analysis.

CONCLUSION

In contrast to the previous MH definition from MetS, the new MH definition was not a reliable predictor for future diabetes in the nonobese Chinese population.

Mechanisms and Treatment of Dyslipidemia in Diabetes

PURPOSE OF REVIEW

Type 2 diabetes mellitus is widespread throughout the world and is a powerful risk factor for the development of atherosclerotic cardiovascular disease (ASCVD). This manuscript explored the mechanisms underlying dyslipidemia in type 2 diabetes as well as currently available treatment options and guideline recommendations.

RECENT FINDINGS

Type 2 diabetes is associated with a characteristic pattern of dyslipidemia, often termed diabetic dyslipidemia. Patients with type 2 diabetes often present with low HDL levels, elevated levels of small dense LDL particles, and elevated triglyceride levels. LDL lowering is the cornerstone of managing diabetic dyslipidemia, and statins are the mainstay of therapy. The cholesterol absorption inhibitor ezetimibe and PCSK9 inhibitors have also been shown to lower risk in patients with diabetes. Recently, the eicosapentaenoic (EPA) only n-3 fatty acid, icosapent ethyl, has also shown benefit for cardiovascular risk reduction in patients with diabetes. To date, no agents targeting HDL increase have shown cardiovascular benefit in patients on background statin therapy. Diabetic dyslipidemia is significant cardiovascular disease risk factor, and LDL-lowering therapy with statins, PCSK9 inhibitors, and ezetimibe continues to be mainstay therapy to reduce cardiovascular risk. Future studies targeting low HDL and high triglycerides levels associated with type 2 diabetes could provide additional novel therapies to manage diabetic dyslipidemia.

The aberrant expression of CD69 on peripheral T-helper cells in diet-induced inflammation is ameliorated by low-dose aspirin and metformin treatment

Chronic inflammation in patients with type 2 diabetes (T2D) is associated with T-cell dysfunction. Using a rodent model, we evaluated changes in metabolic profiles, inflammation status and the expression of T-cell function markers following high-fat diet (HFD)-feeding. In addition, we assessed the modulatory effects of treatment with low-dose aspirin (LDA) and its combination with metformin (LDA + Met) on these parameters. Notably, HFD-feeding induced metabolic disorders and aggravated inflammation. Most importantly, it was associated with decreased expression of CD69 on T-helper cells but had no effect on the expression of programmed cell death 1 (PD-1). Treatment with LDA monotherapy had no effect on metabolic profiles. However, its combination with metformin ameliorated the levels of inflammation and up-regulated the expression of CD69 although it had no therapeutic effect on the levels of PD-1 expression. Therefore, alleviating inflammation and lowering glucose levels in T2D may be an effective strategy to improve T-cell function in these patients.

Development of Fatty Acid Reference Ranges and Relationship with Lipid Biomarkers in Middle-Aged Healthy Singaporean Men and Women

Dietary fatty acids (FA) are essential for overall human health, yet individual FA reference ranges have yet to be established. Developing individual FA reference ranges can provide context to reported concentrations and whether an individual displays deficient, or excess amounts of FA. Reference ranges of sixty-seven individual FA (μmol/L) were profiled and analyzed using gas chromatography with a flame ionization detector from serum samples collected from 476 middle-aged Singaporean males (BMI:23.3 ± 2.9) and females (BMI:21.8 ± 3.6). Measures of triglycerides (TG), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and total cholesterol (TC) (mmol/L) were also collected. The mean FA concentration seen in this cohort (11,458 ± 2478 was similar to that of overweight North American cohorts assessed in past studies. Ten biologically relevant FA were compared between sexes, with females exhibiting significantly higher concentrations in four FA (p < 0.05). A multiple regression model revealed the ten FA contributed significantly to nearly all lipid biomarkers (p < 0.05). A majority of participants who had FA concentrations in the ≥95th percentile also exhibited TG, HDL, LDL, and TC levels in the “high” risk classification of developing cardiovascular disease. Future studies profiling individual FA reference ranges in many unique, global cohorts are necessary to develop cut-off values of individual FA concentrations highly related to disease-risk.

Early detection of type 2 diabetes mellitus using machine learning-based prediction models

Most screening tests for T2DM in use today were developed using multivariate regression methods that are often further simplified to allow transformation into a scoring formula. The increasing volume of electronically collected data opened the opportunity to develop more complex, accurate prediction models that can be continuously updated using machine learning approaches. This study compares machine learning-based prediction models (i.e. Glmnet, RF, XGBoost, LightGBM) to commonly used regression models for prediction of undiagnosed T2DM. The performance in prediction of fasting plasma glucose level was measured using 100 bootstrap iterations in different subsets of data simulating new incoming data in 6-month batches. With 6 months of data available, simple regression model performed with the lowest average RMSE of 0.838, followed by RF (0.842), LightGBM (0.846), Glmnet (0.859) and XGBoost (0.881). When more data were added, Glmnet improved with the highest rate (+ 3.4%). The highest level of variable selection stability over time was observed with LightGBM models. Our results show no clinically relevant improvement when more sophisticated prediction models were used. Since higher stability of selected variables over time contributes to simpler interpretation of the models, interpretability and model calibration should also be considered in development of clinical prediction models.

Selective Peroxisome Proliferator-Activated Receptor Alpha Modulators (SPPARMα): New Opportunities to Reduce Residual Cardiovascular Risk in Chronic Kidney Disease?

PURPOSE OF REVIEW

Chronic kidney disease (CKD) poses a major global challenge, which is exacerbated by aging populations and the pandemic of type 2 diabetes mellitus. Much of the escalating burden of CKD is due to cardiovascular complications. Current treatment guidelines for dyslipidemia in CKD prioritize low-density lipoprotein cholesterol management, but still leave a high residual cardiovascular risk. Targeting elevated triglycerides and low plasma high-density lipoprotein cholesterol, a common feature of CKD, could offer additional benefit. There are, however, safety issues with current fibrates (peroxisome proliferator-activated receptor alpha [PPARα] agonists), notably the propensity for elevation in serum creatinine, indicating the need for new approaches.

RECENT FINDINGS

Interactions between the ligand and PPARα receptor influence the specificity and potency of receptor binding, and downstream gene and physiological effects. The peroxisome proliferator-activated receptor alpha modulator (SPPARMα) concept aims to modulate the ligand structure so as to enhance binding at the PPARα receptor, thereby improving the ligand's selectivity, potency, and safety profile. This concept has led to the development of pemafibrate, a novel SPPARMα agent. This review discusses evidence that differentiates pemafibrate from current fibrates, especially the lack of evidence for elevation in serum creatinine or worsening of renal function in high-risk patients, including those with CKD. Differentiation of pemafibrate from current fibrates aims to address unmet clinical needs in CKD. The ongoing PROMINENT study will provide critical information regarding the long-term efficacy and safety of pemafibrate in patients with type 2 diabetes mellitus, including those with CKD, and whether the favorable lipid-modifying profile translates to reduction in residual cardiovascular risk.

Legacy effect of fibrate add-on therapy in diabetic patients with dyslipidemia: a secondary analysis of the ACCORDION study

BACKGROUND

The Action to Control Cardiovascular Risk in Diabetes (ACCORD)-Lipid study found no evidence of a beneficial effect of statin-fibrate combined treatment, compared to statins alone, on cardiovascular outcomes and mortality in type 2 diabetes mellitus after 5 years of active treatment. However, a beneficial reduction in major CVD events was shown in a pre-specified sub-group of participants with dyslipidemia. The extended follow-up of this trial provides the opportunity to further investigate possible beneficial effects of fibrates in this group of patients. We aimed to evaluate possible "legacy effects" of fibrate add-on therapy on mortality and major cardiovascular outcomes in patients with dyslipidemia.

METHODS

The ACCORD-lipid study was a randomized controlled trial of 5518 participants assigned to receive simvastatin plus fenofibrate vs simvastatin plus placebo. After randomized treatment allocation had finished at the end of the trial, all surviving participants were invited to attend an extended follow-up study (ACCORDION) to continue prospective collection of clinical outcomes. We undertook a secondary analysis of trial and post-trial data in patients who had dyslipidemia. The primary outcome was all-cause and cardiovascular mortality, and secondary outcomes were nonfatal myocardial infarction, stroke, congestive heart failure and major coronary heart disease. We used an intention-to-treat approach to analysis to make comparisons between the original randomized treatment groups.

RESULTS

853 participants with dyslipidemia had survived at the end of the trial. Most participants continued to use statins, but few used fibrates in either group during the post-trial period. The incidence rates in the fenofibrate group were lower with respect to all-cause mortality, CVD mortality, nonfatal myocardial infarction, congestive heart failure and major coronary heart disease than those in the placebo group over a post-trial follow-up. Allocation to the combined fibrate-statin treatment arm during the trial period had a beneficial legacy effect on all-cause mortality (adjusted HR = 0.65, 95% CI 0.45-0.94; P = 0.02).

CONCLUSIONS

Fibrate treatment during the initial trial period was associated with a legacy benefit of improved survival over a post-trial follow-up. These findings support re-evaluation of fibrates as an add-on strategy to statins in order to reduce cardiovascular risk in diabetic patients with dyslipidemia. Trial registration clinicaltrials.gov, Identifier: NCT00000620.

Residual Hypertriglyceridemia and Estimated Atherosclerotic Cardiovascular Disease Risk by Statin Use in U.S. Adults With Diabetes: National Health and Nutrition Examination Survey 2007-2014

OBJECTIVE

Hypertriglyceridemia (HTG) is common in patients with diabetes, and statins remain the first-line therapy. However, the proportion of patients with diabetes having elevated triglycerides (TGs) on statin treatment and their atherosclerotic cardiovascular disease (ASCVD) risk has not been described. We quantified the prevalence of HTG in U.S. adults with diabetes currently treated versus not treated with statins and the estimated 10-year ASCVD risk.

RESEARCH DESIGN AND METHODS

Among 1,448 U.S. adults aged 20 years and over with diabetes (projected to 24.4 million) in the 2007-2014 National Health and Nutrition Examination Survey (NHANES), we compared the prevalence of borderline HTG (TG 150-199 mg/dL) and HTG (TG ≥200 mg/dL) by statin use and LDL cholesterol (LDL-C) levels, and we used logistic regression to identify risk factors for HTG. We also estimated the 10-year ASCVD risk in those without prior ASCVD.

RESULTS

The prevalence of borderline HTG and HTG was 20.0% and 19.5%, respectively, in statin users and 20.1% and 25.3%, respectively, in nonstatin users (P < 0.0001). Even among statin users with LDL-C <70 mg/dL, borderline HTG prevalence was 16.8% and HTG prevalence was 16.7%. Approximately 77.5% of those with HTG had an estimated 10-year ASCVD risk of ≥7.5%, with almost 40% of statin users having ASCVD risk ≥20%.

CONCLUSIONS

Residual HTG occurs in over one-fifth (∼5.5 million) of U.S. adults with diabetes, including those on statin therapy and with well-controlled LDL-C. Over three-quarters of adults with diabetes with HTG are at moderate or high 10-year risk for ASCVD. Greater efforts are needed to promote lifestyle and pharmacologic means to address residual HTG.

Milk-induced hypertriglyceridaemia and acute pancreatitis after discontinuation of treatment for type 2 diabetes and hyperlipidaemia

A 39-year-old man with a background of type 2 diabetes mellitus presented with extreme hypertriglyceridaemia (114.4 mmol/L) and acute pancreatitis, attributed to excessive dairy intake. At his peak, he was drinking up to 6 pints of full fat milk a day. He was treated with an insulin regimen and was counselled on the danger his diet posed to his health. He recovered well, but this case highlights the impact that dietary and lifestyle factors can have on health, sometimes with life-threatening results.