Nutrition & Metabolism最新文献

Background: Cardiovascular disease (CVD) is a chronic disease with a serious prognosis, and obesity is a risk factor for CVD. Lipid accumulation product index (LAP) is a new indicator of obesity, waist circumference, and triglycerides were included in the formula, but its association with CVD is inconsistent. Therefore, this study researched the effect of LAP levels on CVD.

Methods: This prospective cohort study was based on the Kailuan cohort. A total of 95,981 participants who completed the first physical examination in 2006 and had no history of CVD or LAP absence were included. The participants were divided into four groups according to the LAP quartile (Q1 - Q4). Up until December 31, 2022, incidence density was calculated for each group. The hazard ratio (HR) and 95% confidence interval (CI) of CVD in each group were calculated by the Cox proportional hazards model.

Results: During a median follow-up period of 15.95 years, 9925 incident CVD events occurred (2123 myocardial infarction and 8096 stroke). There were differences in potential confounders among the four groups (P < 0.001). The incidence density and 95% CI of CVD in Q1-Q4 groups were 4.76(4.54, 5.00), 6 0.50(6.24, 6.77), 8.13(7.84, 8.44) and 9.34(9.02, 9.67), respectively. There were significant differences in the survival curves among the four groups by log-rank test (P < 0.001). After adjusting for potential confounders, Cox proportional hazards model results showed that compared with the Q1 group, the HR and 95% CI of CVD in the Q2, Q3, and Q4 groups were1.15(1.08, 1.23), 1.29(1.21, 1.38) and 1.39(1.30, 1.49), respectively. The HR and 95%CI of myocardial infarction were 1.28(1.10, 1.49), 1.71(1.47, 1.98) and 1.92(1.64, 2.23), respectively. The HR and 95%CI of stroke were 1.11 (1.03, 1.19), 1.20 (1.12, 1.29) and 1.28 (1.19, 1.38), respectively. After subgroup analysis by gender, there was no significant interaction (P = 0.169), and the relationship between LAP and CVD in different genders was consistent with the main results. After subgroup analysis by age, there was a significant interaction (P = 0.007), and the association between LAP and CVD in different age groups was consistent with the main results. After subgroup analysis by BMI, there was no significant interaction (P = 0.506), and the association between LAP and CVD in different BMI groups was consistent with the main results. The results remained robust after sensitivity analyses. For each unit increase in ln(LAP), the HR and 95%CI of CVD were 4.07 (3.92, 4.23).

Conclusion: This study demonstrated that the risk of CVD increased with the increase of LAP level. The risk of CVD in group Q2 - Q4 was 1.15, 1.29, and 1.39 times higher than that in group Q1, respectively.

Clinical trial registration number: ChiCTR2000029767.

Background: Cardiovascular disease (CVD) affects millions worldwide and is the leading cause of death among non-communicable diseases. Western diets typically comprise of meat and dairy products, both of which are rich in cholesterol (Cho) and methionine (Met), two well-known compounds with atherogenic capabilities. Despite their individual effects, literature on a dietary combination of the two in the context of CVD are limited. Therefore, studies on the combined effects of Cho and Met were carried out using male Sprague Dawley rats. An additional interest was to investigate the cardioprotective potential of sitagliptin, an anti-type 2 diabetic drug. We hypothesized that feeding a dietary combination of Cho and Met would result in adverse cardiac effects and would be attenuated upon administration of sitagliptin.

Methods: Adult male Sprague-Dawley rats were fed either a control (Con), high Met (1.5%), high Cho (2.0%), or high Met (1.5%) + high Cho (2.0%) diet for 35 days. They were orally gavaged with an aqueous preparation of sitagliptin (100 mg/kg/d) or vehicle (water) from day 10 through 35. On day 36, rats were euthanized, and tissues were collected for analysis.

Results: Histopathological evaluation revealed a reduction in myocardial striations and increased collagen deposition in hypercholesterolemia (HChol), responses that became exacerbated upon sitagliptin administration. Cardiac pro-inflammatory and pro-fibrotic responses were adversely impacted in similar fashion. The addition of Met to Cho (MC) attenuated all adverse structural and biochemical responses, with or without sitagliptin.

Conclusions: Adverse cardiac outcomes in HChol were enhanced by the administration of sitagliptin, and such effects were alleviated by Met. Our findings could be significant for understanding or revisiting the risk-benefit evaluation of sitagliptin in type 2 diabetics, and especially those who are known to consume atherogenic diets.

Background: Apoprotein A-I (ApoA-I) and Apoprotein B (ApoB) have emerged as novel cardiovascular risk biomarkers influenced by feeding behavior. Hypothalamic appetite peptides regulate feeding behavior and impact lipoprotein levels, which effects vary in different weight states. This study explores the intricate relationship between body mass index (BMI), hypothalamic appetite peptides, and apolipoproteins with emphasis on the moderating role of body weight in the association between neuropeptide Y (NPY), ghrelin, orexin A (OXA), oxytocin in cerebrospinal fluid (CSF) and peripheral ApoA-I and ApoB.

Methods: In this cross-sectional study, we included participants with a mean age of 31.77 ± 10.25 years, categorized into a normal weight (NW) (n = 73) and an overweight/obese (OW/OB) (n = 117) group based on BMI. NPY, ghrelin, OXA, and oxytocin levels in CSF were measured.

Results: In the NW group, peripheral ApoA-I levels were higher, while ApoB levels were lower than in the OW/OB group (all p < 0.05). CSF NPY exhibited a positive correlation with peripheral ApoA-I in the NW group (r = 0.39, p = 0.001). Notably, participants with higher CSF NPY levels had higher peripheral ApoA-I levels in the NW group and lower peripheral ApoA-I levels in the OW/OB group, showing the significant moderating effect of BMI on this association (R² = 0.144, β=-0.54, p < 0.001). The correlation between ghrelin, OXA and oxytocin in CSF and peripheral ApoB in both groups exhibited opposing trends (Ghrelin: r = -0.03 and r = 0.04; OXA: r = 0.23 and r=-0.01; Oxytocin: r=-0.09 and r = 0.04).

Conclusion: This study provides hitherto undocumented evidence that BMI moderates the relationship between CSF NPY and peripheral ApoA-I levels. It also reveals the protective role of NPY in the NW population, contrasting with its risk factor role in the OW/OB population, which was associated with the at-risk for cardiovascular disease.

Objective: This study was designed to evaluate the impact of VLCKD on cardiovascular risk factors in patients with T2DM.

Methods: Until March 2024, extensive searches were conducted on PubMed, Scopus, Web of Science, Embase, and other relevant databases. The purpose was to identify clinical trials examining the impact of VLCKD on glycemic control, lipid profile, and blood pressure. The GRADE (Grading of Recommendations Assessment, Development, and Evaluation) method was used to assess the evidence's degree of certainty.

Results: Our initial search found a total of 2568 records and finally 29 trials were included in final analysis. Our results showed that adherence from VLCKD led to significant reduction in fasting blood sugar (WMD= -11.68 mg/dl; 95% CI: -18.79, -4.56; P = 0.001), HbA1c (WMD= -0.29; 95% CI: -0.44, -0.14; P < 0.001), HOMA-IR(WMD= -0.71; 95% CI: -1.14, -0.29; P = 0.001), insulin (WMD= -1.45; 95% CI: -2.54, -0.36; P = 0.009), triglyceride (WMD= -17.95; 95% CI: -26.82, -9.07; P < 0.001), systolic blood pressure (WMD= -2.85, 95% CI: -4.99, -0.71; P = 0.009) and diastolic blood pressure (WMD= -1.40; 95% CI: -2.66, -0.13; P = 0.03). We also found a significant increase in high-density lipoprotein (HDL) level after adherence from VLCKD diet (WMD = 3.93, 95% CI: 2.03, 5.84; P = 0.000). We couldn't find any significant differences between groups in term of LDL and total cholesterol levels.

Conclusion: People following a VLCKD experience a more significant improvement in cardiovascular risk factors when compared to individuals on control diets.

Background: Natural compounds can positively impact health, and various studies suggest that they regulate glucose‒lipid metabolism by influencing short-chain fatty acids (SCFAs). This metabolism is key to maintaining energy balance and normal physiological functions in the body. This review explores how SCFAs regulate glucose and lipid metabolism and the natural compounds that can modulate these processes through SCFAs. This provides a healthier approach to treating glucose and lipid metabolism disorders in the future.

Methods: This article reviews relevant literature on SCFAs and glycolipid metabolism from PubMed and the Web of Science Core Collection (WoSCC). It also highlights a range of natural compounds, including polysaccharides, anthocyanins, quercetins, resveratrols, carotenoids, and betaines, that can regulate glycolipid metabolism through modulation of the SCFA pathway.

Results: Natural compounds enrich SCFA-producing bacteria, inhibit harmful bacteria, and regulate operational taxonomic unit (OTU) abundance and the intestinal transport rate in the gut microbiota to affect SCFA content in the intestine. However, most studies have been conducted in animals, lack clinical trials, and involve fewer natural compounds that target SCFAs. More research is needed to support the conclusions and to develop healthier interventions.

Conclusions: SCFAs are crucial for human health and are produced mainly by the gut microbiota via dietary fiber fermentation. Eating foods rich in natural compounds, including fruits, vegetables, tea, and coarse fiber foods, can hinder harmful intestinal bacterial growth and promote beneficial bacterial proliferation, thus increasing SCFA levels and regulating glucose and lipid metabolism. By investigating how these compounds impact glycolipid metabolism via the SCFA pathway, novel insights and directions for treating glucolipid metabolism disorders can be provided.

Background: Previous studies have reported a close association between the Geriatric Nutritional Risk Index (GNRI) and various conditions. However, the association between the GNRI and mortality remains unclear. To examine the correlation between the GNRI and all-cause, cancer-specific, and cardiovascular mortality, this study was performed.

Methods: We analyzed elderly participants in the National Health and Nutrition Examination Survey from 2005 to 2016. The GNRI was calculated using body mass index and serum albumin. Kaplan-Meier survival curves were drawn to compare the survival probability between the normal and decreased GNRI groups. Weighted multivariate Cox regression and restricted cubic spline (RCS) models were employed to determine the linear and non-linear associations of the GNRI with all-cause, cancer-specific, and cardiovascular mortality.

Results: A total of 3,276 participants were included in the analysis. The Kaplan-Meier survival curve showed that the decreased GNRI group had a lower survival probability for all-cause mortality and cancer-specific mortality (P < 0.001) but not for cardiovascular mortality (P > 0.05). In the full regression models, the decreased group had a higher risk of all-cause mortality (HR = 1.67, 95% CI = 1.21-2.30, P = 0.002), and cancer-specific mortality (HR = 2.20, 95% CI = 1.32-3.67, P = 0.003) than the normal group. For cardiovascular mortality, no significant association with GNRI (HR = 1.39, 95% CI = 0.60-3.22, P = 0.436) was detected. Notably, the RCS analysis identified a linear downward trend between the GNRI and all-cause, alongside cancer-specific mortalities (all P for overall < 0.05). The time-dependent Receiver Operating Characteristic (ROC) analysis unveiled the predictive power of the GNRI for 5-year all-cause mortality, cancer mortality, and cardiovascular mortality was 0.754, 0.757, and 0.836, respectively, after adjusting for covariates.

Conclusions: Individuals with a decreased GNRI had increased risks of all-cause, and cancer-specific mortality. There were linear associations of the GNRI with all-cause, and cancer-specific mortality. Nutritional status should be carefully monitored, which may improve the overall prognosis for the general population.

Background: Obesity is associated with alterations in the hypothalamic-pituitary-adrenal (HPA) axis. Effects of glucocorticoids on adipose tissues appear to depend on the specific adipose depot, in which they take place. In this study, we aimed to investigate the role of MRI-based adrenal gland volume as an imaging marker in association with different adipose tissue compartments.

Methods: The study cohort derives from the population-based research platform KORA (Cooperative Health Research in the Augsburg Region, Germany) MRI sub-study, a cross-sectional sub-study investigating the interactions between subclinical metabolic changes and cardiovascular disease in a study sample of 400 participants. Originally, eligible subjects underwent a whole-body MRI. MRI-based segmentations were performed manually and semi-automatically for adrenal gland volume, visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), epi- and pericardial fat and renal sinus fat. Hepatic and pancreatic lipid content were measured as pancreatic proton density fraction (PDFF) and MR-spectroscopic hepatic fat fraction (HFF). Multivariable linear regression analyses were performed.

Results: A number of 307 participants (56.2 ± 9.1 years, 60.3% male, 14.3% with type 2 diabetes (T2DM), 30.6% with obesity, 34.2% with hypertension) were included. In multivariable analyses, strong positive associations between adrenal gland volume and VAT, total adipose tissue (TAT) as well as HFF persisted after extensive step-wise adjustment for possible metabolic confounders (VAT: beta = 0.31, 95%-CI [0.71, 0.81], p < 0.001; TAT: beta = 0.14, 95%-CI [0.06, 0.23], p < 0.001; HFF: beta = 1.17, 95%-CI [1.04, 1.31], p = 0.009). In contrast, associations between adrenal gland volume and SAT were attenuated in multivariate analysis after adjusting for BMI. Associations between pancreatic PDFF, epi- and pericardial fat and renal sinus fat were mediated to a great extent by VAT (pancreatic PDFF: 72%, epicardial adipose tissue: 100%, pericardial adipose tissue: 100%, renal sinus fat: 81.5%).

Conclusion: Our results found MRI-based adrenal gland volume as a possible imaging biomarker of unfavorable adipose tissue distribution, irrespective of metabolic risk factors. Thus, adrenal gland volume may serve as a potential MRI-based biomarker of metabolic changes and contributes to an individual characterization of metabolic states and individual risk stratification. Future studies should elucidate in a longitudinal study design, if and how HPA axis activation may trigger unfavorable adipose tissue distribution and whether and to which extent this is involved in the pathogenesis of manifest metabolic syndrome.