Metabolic-related markers and inflammatory factors as predictors of dyslipidemia among urban Han Chinese adults

Effect of metabolic syndrome on testosterone levels in patients with metastatic prostate cancer: a real-world retrospective study

Background

Metabolic syndrome (MetS) has been shown to have a negative impact on prostate cancer (PCa). However, there is limited research on the effects of MetS on testosterone levels in metastatic prostate cancer (mPCa).

Objective

This study aims to investigate the influence of MetS, its individual components, and composite metabolic score on the prognosis of mPCa patients, as well as the impact on testosterone levels. Additionally, it seeks to identify MetS-related risk factors that could impact the time of decline in testosterone levels among mPCa patients.

Methods

A total of 212 patients with mPCa were included in the study. The study included 94 patients in the Non-MetS group and 118 patients in the combined MetS group. To analyze the relationship between MetS and testosterone levels in patients with mPCa. Additionally, the study aimed to identify independent risk factors that affect the time for testosterone levels decline through multifactor logistic regression analysis. Survival curves were plotted by the Kaplan-Meier method.

Results

Compared to the Non-MetS group, the combined MetS group had a higher proportion of patients with high tumor burden, T stage ≥ 4, and Gleason score ≥ 8 points (P < 0.05). Patients in the combined MetS group also had higher lowest testosterone values and it took longer for their testosterone to reach the lowest level (P < 0.05). The median progression-free survival (PFS) time for patients in the Non-MetS group was 21 months, while for those in the combined MetS group it was 18 months (P = 0.001). Additionally, the median overall survival (OS) time for the Non-MetS group was 62 months, whereas for the combined MetS group it was 38 months (P < 0.001). The median PFS for patients with a composite metabolic score of 0-2 points was 21 months, 3 points was 18 months, and 4-5 points was 15 months (P = 0.002). The median OS was 62 months, 42 months, and 29 months respectively (P < 0.001). MetS was found to be an independent risk factor for testosterone levels falling to the lowest value for more than 6 months. The risk of testosterone levels falling to the lowest value for more than 6 months in patients with MetS was 2.157 times higher than that of patients with Non-MetS group (P = 0.031). Patients with hyperglycemia had a significantly higher lowest values of testosterone (P = 0.015). Additionally, patients with a BMI ≥ 25 kg/m2 exhibited lower initial testosterone levels (P = 0.007). Furthermore, patients with TG ≥ 1.7 mmol/L experienced a longer time for testosterone levels to drop to the nadir (P = 0.023). The lowest value of testosterone in the group with a composite metabolic score of 3 or 4-5 was higher than that in the 0-2 group, and the time required for testosterone levels to decrease to the lowest value was also longer (P < 0.05).

Conclusion

When monitoring testosterone levels in mPCa patients, it is important to consider the impact of MetS and its components, and make timely adjustments to individualized treatment strategies.

Application of deep neural survival networks to the development of risk prediction models for diabetes mellitus, hypertension, and dyslipidemia

OBJECTIVES

: Although numerous risk prediction models have been proposed, few such models have been developed using neural network-based survival analysis. We developed risk prediction models for three cardiovascular disease risk factors (diabetes mellitus, hypertension, and dyslipidemia) among a working-age population in Japan using DeepSurv, a deep feed-forward neural network.

METHODS

: Data were obtained from the Japan Epidemiology Collaboration on Occupational Health Study. A total of 51 258, 44 197, and 31 452 individuals were included in the development of risk models for diabetes mellitus, hypertension, and dyslipidemia, respectively; two-thirds of whom were used to develop prediction models, and the rest were used to validate the models. We compared the performances of DeepSurv-based models with those of prediction models based on the Cox proportional hazards model.

RESULTS

: The area under the receiver-operating characteristic curve was 0.878 [95% confidence interval (CI) = 0.864-0.892] for diabetes mellitus, 0.835 (95% CI = 0.826-0.845) for hypertension, and 0.826 (95% CI = 0.817-0.835) for dyslipidemia. Compared with the Cox proportional hazards-based models, the DeepSurv-based models had better reclassification performance [diabetes mellitus: net reclassification improvement (NRI) = 0.474, P  ≤ 0.001; hypertension: NRI = 0.194, P  ≤ 0.001; dyslipidemia: NRI = 0.397, P  ≤ 0.001] and discrimination performance [diabetes mellitus: integrated discrimination improvement (IDI) = 0.013, P  ≤ 0.001; hypertension: IDI = 0.007, P  ≤ 0.001; and dyslipidemia: IDI = 0.043, P  ≤ 0.001].

CONCLUSION

: This study suggests that DeepSurv has the potential to improve the performance of risk prediction models for cardiovascular disease risk factors.

Beneficial effects of 1,3-1,6 β-glucans produced by Aureobasidium pullulans on non-esterified fatty acid levels in diabetic KKAy mice and their potential implications in metabolic dysregulation

Objectives

In this study, we used an obese and diabetic mouse model to compare two strains of Aureobasidium pullulans (AFO-202 and N-163) produced beta-glucans (β-glucans), which alleviate lipotoxicity.

Methods

Four groups of KK-Ay mice were used, with six subjects in each group. Group 1: sacrificed on day 0 for baseline values; Group 2: control (drinking water); Group 3: AFO-202 beta glucan-200 mg/kg/day; Group 4: N-163 beta glucan-300 mg/kg/day for 28 consecutive days.

Results

Group 4 (N-163) had the lowest non-esterified fatty acids (NEFA) levels and marginally decreased triglyceride levels compared to the other groups. There were no significant differences in blood glucose, hemoglobin A1c (HbA1c), triglycerides, low-density lipoprotein (LDL), and high-density lipoprotein (HDL) cholesterol levels. N-163 β-glucans decreased NEFA levels after 28 days.

Conclusion

These results, although modest, warrant further in-depth research into lipotoxicity and associated inflammatory cascades in both healthy and diseased subjects for the prevention and management of metabolic dysregulation and associated diseases such as non-alcoholic fatty liver disease (NAFLD).

Association of Advanced Lipoprotein Subpopulation Profiles with Insulin Resistance and Inflammation in Patients with Type 2 Diabetes Mellitus

Plasma lipoproteins exist as several subpopulations with distinct particle number and size that are not fully reflected in the conventional lipid panel. In this study, we sought to quantify lipoprotein subpopulations in patients with type 2 diabetes mellitus (T2DM) to determine whether specific lipoprotein subpopulations are associated with insulin resistance and inflammation markers. The study included 57 patients with T2DM (age, 61.14 ± 9.99 years; HbA1c, 8.66 ± 1.60%; mean body mass index, 35.15 ± 6.65 kg/m²). Plasma lipoprotein particles number and size were determined by nuclear magnetic resonance spectroscopy. Associations of different lipoprotein subpopulations with lipoprotein insulin resistance (LPIR) score and glycoprotein acetylation (GlycA) were assessed using multi-regression analysis. In stepwise regression analysis, VLDL and HDL large particle number and size showed the strongest associations with LPIR (R² = 0.960; p = 0.0001), whereas the concentrations of the small VLDL and HDL particles were associated with GlycA (R² = 0.190; p = 0.008 and p = 0.049, respectively). In adjusted multi-regression analysis, small and large VLDL particles and all sizes of lipoproteins independently predicted LPIR, whereas only the number of small LDL particles predicted GlycA. Conventional markers HbA1c and Hs-CRP did not exhibit any significant association with lipoprotein subpopulations. Our data suggest that monitoring insulin resistance-induced changes in lipoprotein subpopulations in T2DM might help to identify novel biomarkers that can be useful for effective clinical intervention.

A Retrospective Assessment of Laboratory Findings and Cytokine Markers in Severe SARS-CoV-2 Infection among Patients of Roma Population

Growing research data suggests that the severity of COVID-19 is linked with higher levels of inflammatory mediators, such as cytokines, chemokines, tumor necrosis factor, C-reactive protein, ferritin, and D-dimers. In addition, it was evident from the existing research data that the severity of SARS-CoV-2 infection differs according to independent risk factors such as race and ethnicity. Some scarce evidence shows that the European Roma community is likely to be at an elevated risk of illness and death during the pandemic due to their lifestyle, social factors, and economics. Assuming that precautions must be taken to protect this population from coronavirus infections and from widening existing disparities in comparison with the Romanian ethnic population, the current study aimed to observe the clinical evolution of the Roma patients with severe SARS-CoV-2 infection in correlation with the laboratory findings and inflammatory markers involved. After calculating the sample size requirements, we included 83 Roma patients admitted to the hospital with severe COVID-19 and 236 patients of Romanian ethnicity with the same inclusion criteria. Patients were selected from the period stretching from March 2020 to December 2021, before COVID-19 vaccines were introduced. Compared with the general population, the Roma patients with severe SARS-CoV-2 infection had a higher unemployment rate (39.8%), and most of them were residing in rural regions (65.4%). There were significantly more overweight patients in the Roma group than in the control group (57.8% vs. 40.7%), and it was also observed that high blood pressure and diabetes mellitus were significantly more prevalent in the Roma patients. They had significantly longer mean duration of hospitalization was significantly longer in the group of Roma patients (18.1 days vs. 16.3 days). IL-6 and CRP levels were significantly more elevated during admission in the group of Roma patients (43.4% vs. 28.4%); however, IL-6 levels normalized at discharge, but ESR remained high. Although ICU admissions were significantly more frequent in this group, the mortality rate was not significantly higher than in the general population. It is necessary to plan different healthcare strategies aimed at special populations, such as the Roma ethnicity to prevent disparities in negative outcomes reflected in this study. The results imply that community-health collaborations between organizations of minority groups and healthcare professionals can mitigate the disproportionate consequences of the pandemic on Roma.

Macronutrient intake modulates impact of EcoRI polymorphism of ApoB gene on lipid profile and inflammatory markers in patients with type 2 diabetes

We sought to examine whether dietary intakes may affect the relationship between ApoB EcoRI and lipid profile, as well as serum inflammatory markers, in patients with type 2 diabetes (T2DM). This current study consisted of 648 diabetic patients. Dietary intake was calculated by a food frequency questionnaire. Biochemical markers (high-density lipoprotein (HDL), total cholesterol (TC), LDL, TG, CRP, IL-18, PGF2α) were measured based on standard protocols. Genotyping of the Apo-B polymorphisms (rs1042031) was conducted by the PCR–RFLP method. The gene-diet interactions were evaluated using GLMs. In comparison to GG homozygotes, A-allele carriers with above the median -CHO intake (≥ 54 percent of total energy) had considerably greater TC and PGF2a concentrations. Furthermore, as compared to GG homozygotes, A-allele carriers with above the median protein intake (≥ 14 percent of total energy) had higher serum levels of TG (P = 0.001), CRP (P = 0.02), TG/HDL (P = 0.005), and LDL/HDL (P = 0.04) ratios. Moreover, A-allele carriers with above the median total fat intake (≥ 35 percent of total calories) had significantly higher TC level (P = 0.04) and LDL/HDL (P = 0.04) ratios compared to GG homozygotes. Furthermore, when compared to GG homozygotes, A-allele carriers who consumed above the median cholesterol (> 196 mg) had greater TG (P = 0.04), TG/HDL (P = 0.01) ratio, and IL-18 (P = 0.02). Furthermore, diabetic patients with the GA, AA genotype who consume above the median cholesterol had lower ghrelin levels (P = 0.01). In terms of LDL/HDL ratio, ApoB EcoRI and dietary intakes of specific fatty acids (≥ 9 percent for SFA and ≥ 12 percent for MUFA) had significant interaction. LDL/HDL ratio is greater in A-allele carriers with above the median SFA intake (P = 0.04), also when they consumed above the median MUFA this association was inverse (P = 0.04). Our study showed that plasma lipid levels in participants carrying the (AA or AG) genotype were found to be more responsive to increasing the percentage of energy derived from dietary fat, CHO, protein, SFA, and cholesterol consumption. Therefore, patients with a higher genetic susceptibility (AA or AG) seemed to have greater metabolic markers with a higher percentage of macronutrient consumption. Also, ApoB EcoRI correlations with metabolic markers might be attenuated with above the median MUFA consumption.

A cohort study on risk factors of high-density lipoprotein cholesterol hypolipidemia among urban Chinese adults

Background

High-density lipoprotein cholesterol (HDL-C) hypolipidemia, a major type of dyslipidemia, has been associated with many kinds of diseases, such as stroke, coronary heart disease, obesity and diabetes, and has displayed an increasing prevalence in China. This study explores the risk factors of HDL-C hypolipidemia and makes recommendations for controlling and preventing HDL-C hypolipidemia and the diseases caused by it.

Methods

Using a retrospective cohort study design, 26,863 urban adults without dyslipidemia, diabetes, cardiovascular and cerebrovascular diseases, hepatosis, renal insufficiency and thyroid diseases were enrolled in the study between 2010 and 2015. Data on each individual were collected at the 2010 baseline year and at a follow-up medical check. A Cox regression model was constructed to evaluate the influence of potential risk factors on the outcome event- HDL-C hypolipidemia.

Results

The incidence of HDL-C hypolipidemia was 5.7% (1531/26863). Sex, age, body mass index (BMI), HDL-C, triglyceride (TG) and urea nitrogen (UN) were significant risk factors of HDL-C hypolipidemia. Men were more likely to develop HDL-C hypolipidemia than women during follow-up medical checks (HR = 1.258, P = 0.014). The incidence of HDL-C hypolipidemia in the over 65 years old group was higher than that of the ≤65 age group (HR = 1.276, P = 0.009). The incidence of HDL-C hypolipidemia increased with increasing BMI (HR = 1.030, P = 0.002), TG (HR = 1.321, P = 0.001) and UN (HR = 1.054, P = 0.019), while falling with increasing HDL-C in the baseline year (HR = 0.002, P < 0.001).

Conclusions

Men, aged over 65, with high BMI were at the highest risk of developing HDL-C hypolipidemia. Measures should be taken to prevent HDL-C hypolipidemia even for healthy urban adults whose blood biochemical indicators were in the normal range when their level of TG, UN and HDL-C are closed to the border of the normal value range.

Role of resistin, IL-6 and NH2-terminal portion proBNP in the pathogenesis of cardiac disease in type 2 diabetes mellitus

INTRODUCTION

Epidemiological and genetic studies have recorded the association between proinflammatory cytokines and the development of insulin resistance, diabetes, and cardiovascular disease. The role of interleukin 6 (IL-6), NH2-terminal portion pro-brain natriuretic peptide (NT-proBNP) and resistin in the pathogenesis of heart disease in type 2 diabetes mellitus (T2DM) is still a matter of controversy. The current study aimed to evaluate the role of these biomarkers in the development of left ventricular systolic dysfunction and the ability to use them as non-invasive test in the prediction of left ventricular hypertrophy and systolic dysfunction in T2DM.

RESEARCH DESIGN AND METHODS

150 participants were included in this case-control study. Patients were divided into two subgroups according to echocardiographic findings: group 1a included 46 patients with type 2 diabetes mellitus and echocardiographic evidence of abnormal systolic function; group 1b included 54 patients with type 2 diabetes mellitus and with normal echocardiogenic study; and group 2 included 50 apparently healthy controls. Routine laboratory investigations such as complete blood count, liver and renal function tests, and lipid profile, serum IL-6, NT-proBNP, and resistin were measured in all participants. Conventional echocardiography was done with special concern on the assessment of left ventricular systolic function (ejection fraction).

RESULTS

There was a significant increase in the level of resistin, NT-proBNP and IL-6 in group 1a patients compared with group 1b and in healthy controls. Echocardiographic parameters showed a significant increase in left ventricular mass index, left ventricle posterior wall thickness, interventricular septum thickness, and left ventricle mass in group 1a compared with group 1b and the control group. The increased left ventricular mass index was associated with higher levels of IL-6, NT-proBNP and resistin.

CONCLUSIONS

Proinflammatory cytokines had a clear relation with left ventricular systolic dysfunction and hypertrophy and can be used as early non-invasive markers for detection of left ventricular remodeling and systolic dysfunction in patients with T2DM.