Changes in Lipids and Inflammatory Markers after Consuming Diets High in Red Meat or Dairy for Four Weeks

Joint analysis of the metabolomics and transcriptomics uncovers the dysregulated network and develops the diagnostic model of high-risk neuroblastoma

High-risk neuroblastoma (HR-NB) has a significantly lower survival rate compared to low- and intermediate-risk NB (LIR-NB) due to the lack of risk classification diagnostic models and effective therapeutic targets. The present study aims to characterize the differences between neuroblastomas with different risks through transcriptomic and metabolomic, and establish an early diagnostic model for risk classification of neuroblastoma.Plasma samples from 58 HR-NB and 38 LIR-NB patients were used for metabolomics analysis. Meanwhile, NB tissue samples from 32 HR-NB and 23 LIR-NB patients were used for transcriptomics analysis. In particular, integrative metabolomics and transcriptomic analysis was performed between HR-NB and LIR-NB. A total of 44 metabolites (P < 0.05 and fold change > 1.5) were altered, including 12 that increased and 32 that decreased in HR-NB. A total of 1,408 mRNAs (P < 0.05 and |log2(fold change)|> 1) showed significantly altered in HR-NB, of which 1,116 were upregulated and 292 were downregulated. Joint analysis of both omic data identified 4 aberrant pathways (P < 0.05 and impact ≥ 0.5) consisting of glycerolipid metabolism, retinol metabolism, arginine biosynthesis and linoleic acid metabolism. Importantly, a HR-NB risk classification diagnostic model was developed using plasma circulating-free S100A9, CDK2, and UNC5D, with an area under receiver operating characteristic curve of 0.837 where the sensitivity and specificity in the validation set were both 80.0%. This study presents a novel pioneering study demonstrating the metabolomics and transcriptomics profiles of HR-NB. The glycerolipid metabolism, retinol metabolism, arginine biosynthesis and linoleic acid metabolism were altered in HR-NB. The risk classification diagnostic model based on S100A9, CDK2, and UNC5D can be clinically used for HR-NB risk classification.

Exosome Release Delays Senescence by Disposing of Obsolete Biomolecules

Accumulation of obsolete biomolecules can accelerate cell senescence and organism aging. The two efficient intracellular systems, namely the ubiquitin-proteasome system and the autophagy-lysosome system, play important roles in dealing with cellular wastes. However, how multicellular organisms orchestrate the processing of obsolete molecules and delay aging remains unclear. Herein, it is shown that prevention of exosome release by GW4869 or Rab27a^-/- accelerated senescence in various cells and mice, while stimulating exosome release by nutrient restriction delays aging. Interestingly, exosomes isolate from serum-deprived cells or diet-restricted human plasma, enriched with garbage biomolecules, including misfolded proteins, oxidized lipids, and proteins. These cellular wastes can be englobed by macrophages, eventually, for disintegration in vivo. Inhibition of nutrient-sensing mTORC1 signaling increases exosome release and delays senescence, while constitutive activation of mTORC1 reduces exosome secretion and exacerbates senescence in vitro and in mice. Notably, inhibition of exosome release attenuates nutrient restriction- or rapamycin-delayed senescence, supporting a key role for exosome secretion in this process. This study reveals a potential mechanism by which stimulated exosome release delays aging in multicellular organisms, by orchestrating the harmful biomolecules disposal via exosomes and macrophages.

Red meat consumption and risk for dyslipidaemia and inflammation: A systematic review and meta-analysis

Aim

The study (PROSPERO: CRD42021240905) aims to reveal the relationships among red meat, serum lipids and inflammatory biomarkers.

Methods and results

PubMed, EMBASE and the Cochrane databases were explored through December 2021 to identify 574 studies about red meat and serum lipids markers including total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), C-reactive protein (CRP) or hypersensitive-CRP (hs-CRP). Finally, 20 randomized controlled trials (RCTs) involving 1001 people were included, red meat and serum lipid markers and their relevant information was extracted. The pooled standard mean difference (SMD) was obtained by applying a random-effects model, and subgroup analyses and meta-regression were employed to explain the heterogeneity. Compared with white meat or grain diets, the gross results showed that the consumption of red meat increased serum lipid concentrations like TG (0.29 mmol/L, 95% CI 0.14, 0.44,P<0.001), but did not significantly influence the TC (0.13 mmol/L, 95% CI −0.07, 0.33, P = 0.21), LDL-C (0.11 mmol/L, 95% CI −0.23, 0.45, P = 0.53), HDL-C (−0.07 mmol/L, 95% CI −0.31, 0.17, P = 0.57),CRP or hs-CRP (0.13 mmol/L, 95% CI −0.10, 0.37,P = 0.273).

Conclusion

Our study provided evidence to the fact that red meat consumption affected serum lipids levels like TG, but almost had no effect on TC, LDL-C, HDL-C and CRP or hs-CRP. Such diets with red meat should be taken seriously to avoid the problem of high lipid profiles.

Systematic review registration

[https://www.crd.york.ac.uk/PROSPERO], identifier [CRD42021240905].

Diet quality in association to lipidaemic profile in adults of families at high-risk for type 2 diabetes in Europe: The Feel4Diabetes study

BACKGROUND AND AIMS

The role of diet in blood lipids is scarcely investigated in adults at risk of Type 2 Diabetes Mellitus (T2DM) and even less studied regarding their socioeconomic status (SES). This study aimed to investigate the associations of diet quality with blood lipids in adults from families at high-risk for developing T2DM from six European countries, considering their SES.

METHODS AND RESULTS

In total 2049 adults (67% women) from relatively low-SES regions and high T2DM risk families were enrolled. Dietary habits, sedentary behaviour and sociodemographic characteristics were assessed using standardised questionnaires. The associations of tertiles of healthy diet score (HDS) with blood lipids were tested by univariate analysis of variance (UNIANOVA). HDL-Cholesterol (HDL-C) was positively (B 1.54 95%CI 0.08 to 2.99) and LDL-Cholesterol (LDL-C) (B -4.15 95%CI -7.82 to -0.48), ratio of total cholesterol to HDL-C (B -0.24 95%CI -0.37 to -0.10), ratio of LDL-C to HDL-C (B -0.18 95%CI -0.28 to -0.08) and Atherogenic Index of Plasma (B -0.03 95%CI -0.06 to 0.00) inversely associated with the highest tertile of diet score compared to the lowest tertile independently of age, sex, Body Mass Index, total screen time and smoking. In sub-analysis of education (<14 and ≥ 14 years of education), these findings were only significant in the high-SES group.

CONCLUSION

While diet quality was poorer in the low-SES group, an association between diet quality and lipidemic profile was not found, as increased central obesity and smoking prevalence might have confounded this association. These findings indicate the need for tailor-made interventions, guided by the specific risk factors identified per population sub groups.

Changes in phospholipid metabolism in exosomes of hormone-sensitive and hormone-resistant prostate cancer cells

Background: To explore the changes in lipids in exosomes of hormone-sensitive and hormone-resistant prostate cancer cells and develop an inexpensive and rapid technique for screening lipid-based biomarkers of prostate cancer.

Methods: Exosomes were extracted from LnCap, PC₃ and DU-145 cells, and their lipid composition was analyzed quantitatively using high-throughput mass spectrometry. Exosomes released by LnCap prostate cancer cells were also purified using a modified procedure based on polyethylene glycol (PEG) precipitation.

Results: Exosomes extracted from LnCap cells contained higher proportions of phosphatidyl choline, phosphatidyl ethanolamine and phosphatidyl inositol lipids than whole LnCap cells. Lysophosphatidylcholine, a harmful intermediate product of phosphatidylcholine metabolism in vivo, was not found in LnCap cells but in exosomes. Phospholipids were different in exosomes from LnCap, PC3 and DU-145 prostate cancer cells. The main lipid pathways involved, i.e., glycerophospholipid metabolism, autophagy, and ferroptosis pathways, were also different in these cells. Exosomes isolated by this modified PEG precipitation technique were similar in purity to those obtained using a commercial kit.

Conclusions: This study demonstrates that phosphatidylcholine and its harmful product lysophosphatidylcholine may play important roles in hormone-sensitive prostate cancer. Phospholipid exosome metabolism was changed in hormone-sensitive and hormone-resistant prostate cancer cells. The LPC, lipid pathway of autophagy and ferroptosis may act as therapeutic targets. The possibility of purifying prostate cancer cell exosomes using modified PEG precipitation is suitable for cancer screening.

Long-term association of red meat consumption and lipid profile: A 13-year prospective population-based cohort study

OBJECTIVES

The long-term associations between red meat consumption and lipid profile are not completely known. This longitudinal study assessed the association of red meat consumption with lipid profile in healthy Iranian adults using repeated measurements of red meat intake.

METHODS

The population-based longitudinal study was conducted within the framework of the Isfahan Cohort Study on a subsample of 1376 healthy adults, aged ≥35 y, for whom complete information was available in all three phases of the study. A simplified qualitative 48-item food frequency questionnaire, blood pressure, anthropometric measurements, and fasting serum lipids and blood sugar were evaluated in three phases. Mixed-effects linear regression was applied to examine the longitudinal associations between red meat consumption and lipid profile.

RESULTS

After adjustment for potential confounders, each single-serving increase in red meat and organ meat consumption was significantly associated with an increment in triacylglycerol (β = 6.30; 95% confidence interval [CI], 3.97-8.63), total cholesterol (β = 3.03; 95% CI, 2.02-4.04), low-density lipoprotein (β = 3.40; 95% CI, 2.64-4.17), high-density lipoprotein (β = 0.60; 95% CI, 0.28-0.93), ratio of low-density to high-density lipoprotein (β = 0.03; 95% CI, 0.01-0.05), and non-high-density lipoprotein (β = 2.42; 95% CI, 1.41-3.43). However, processed meat consumption had no significant association with lipid profile.

CONCLUSIONS

Total red meat intake had a significant, direct association with lipid profile after a 13-year follow-up period in a cohort of the healthy Iranian population.

Effects of Total Red Meat Intake on Glycemic Control and Inflammatory Biomarkers: A Meta-Analysis of Randomized Controlled Trials

Our objective was to conduct a systematic review and meta-analysis to assess the effects of total red meat (TRM) intake on glycemic control and inflammatory biomarkers using randomized controlled trials of individuals free from cardiometabolic disease. We hypothesized that higher TRM intake would negatively influence glycemic control and inflammation based on positive correlations between TRM and diabetes. We found 24 eligible articles (median duration, 8 weeks) from 1172 articles searched in PubMed, Cochrane, and CINAHL up to August 2019 that included 1) diet periods differing in TRM; 2) participants aged ≥19 years; 3) included either men or women who were not pregnant/lactating; 4) no diagnosed cardiometabolic disease; and 5) data on fasting glucose, insulin, HOMA-IR, glycated hemoglobin (HbA1c), C-reactive protein (CRP), or cytokines. We used 1) a repeated-measures ANOVA to assess pre to post diet period changes; 2) random-effects meta-analyses to compare pre to post changes between diet periods with ≥ vs. <0.5 servings (35g)/day of TRM; and 3) meta-regressions for dose-response relationships. We grouped diet periods to explore heterogeneity sources, including risk of bias, using the National Heart, Lung, and Blood Institute's Quality Assessment of Controlled Interventions Studies. Glucose, insulin, and HOMA-IR values decreased, while HbA1c and CRP values did not change during TRM or alternative diet periods. There was no difference in change values between diet periods with ≥ vs. <0.5 servings/day of TRM [weighted mean differences (95% CIs): glucose, 0.040 mmol/L (-0.049, 0.129); insulin, -0.710 pmol/L (-6.582, 5.162); HOMA-IR, 0.110 (-0.072, 0.293); CRP, 2.424 nmol/L (-1.460, 6.309)] and no dose response relationships (P > 0.2). Risk of bias (85% of studies were fair to good) did not influence results. Total red meat consumption, for up to 16 weeks, does not affect changes in biomarkers of glycemic control or inflammation for adults free of, but at risk for, cardiometabolic disease. This trial was registered at PROSPERO as 2018 CRD42018096031.

Effects of dairy products consumption on inflammatory biomarkers among adults: A systematic review and meta-analysis of randomized controlled trials

AIMS

This study aimed to summarize earlier studies on the effects of dairy consumption on inflammatory biomarkers in adults and to quantify these effects through meta-analysis.

DATA SYNTHESIS

A comprehensive search of all relevant articles, published up to December 2019 indexed in PubMed, ISI (Institute for Scientific Information), EmBase, Scopus, and Google Scholar was done using relevant keywords. Randomized controlled trials (RCTs) that examined the effect of dairy products consumption, compared with low or no dairy intake, on inflammatory biomarkers in adults were included. Overall, 11 RCTs with 663 participants were included in this meta-analysis. We found that high consumption of dairy products, compared with low or no dairy intake, might significantly reduce CRP [weighed mean difference (WMD): -0.24 mg/L; 95% CI, -0.35, -0.14], TNF-α (WMD:- 0.66 pg/mL; 95% CI, -1.23, -0.09), IL-6 (WMD: -0.74 pg/mL; 95% CI, -1.36, -0.12), and MCP concentrations (WMD: -25.58 pg/mL; 95% CI, -50.31, -0.86). However, when the analyses were confined to cross-over trials, no such beneficial effects of dairy intake on inflammation were observed. In addition, high dairy intake might result in increased adiponectin levels (WMD: 2.42 μg/mL; 95% CI, 0.17, 4.66). No significant effect of dairy consumption on serum leptin (WMD: -0.32 ng/mL; 95% CI, -3.30, 2.65), ICAM-1 (WMD: -3.38 ng/ml; 95% CI, -15.57, 8.96) and VCAM-1 (WMD: 3.1 ng/mL; 95% CI, -21.38, 27.58) levels was observed.

CONCLUSIONS

In summary, the current meta-analysis indicated that dairy intake might improve several inflammatory biomarkers in adults. In most subgroups without heterogeneity, effects tended to be null. Study design and participants' age were the main sources of heterogeneity. More research, with a particular focus on fat content of dairy foods, is recommended.

Dairy Foods and Dairy Fats: New Perspectives on Pathways Implicated in Cardiometabolic Health

Low-fat and nonfat dairy products have been promoted as part of a healthy dietary pattern by both US dietary guidelines and professional organizations for several decades. The basis for this recommendation stems in part from the putative negative cardiometabolic effects associated with saturated fat consumption. However, as nutrition research has shifted from a single nutrient to a whole-food/dietary pattern approach, the role of dairy foods and dairy fat in the diet-disease relationship is being reexamined. Most observational and experimental evidence does not support a detrimental relationship between full-fat dairy intake and cardiometabolic health, including risks of cardiovascular disease and type 2 diabetes. Indeed, an expanded understanding of the dairy food matrix and the bioactive properties of dairy fats and other constituents suggests a neutral or potentially beneficial role in cardiometabolic health. To consider how consuming dairy foods, including full-fat dairy, is associated with cardiometabolic health, this review provides an innovative perspective on mechanisms that link dairy consumption to 3 main biological systems at the core of metabolic health, the gastrointestinal, hepatic, and vascular systems.

The Role of Meat Protein in Generation of Oxidative Stress and Pathophysiology of Metabolic Syndromes

Various processing methods have a great impact on the physiochemical and nutritional properties of meat that are of health concern. Hence, the postmortem processing of meat by different methods is likely to intensify the potential effects on protein oxidation. The influence of meat protein oxidation on the modulation of the systemic redox status and underlying mechanism is well known. However, the effects of processed meat proteins isolated from different sources on gut microbiota, oxidative stress biomarkers, and metabolomic markers associated with metabolic syndromes are of growing interest. The application of advanced methodological approaches based on OMICS, and mass spectrometric technologies has enabled to better understand the molecular basis of the effect of processed meat oxidation on human health and the aging process. Animal studies indicate the involvement of dietary proteins isolated from different sources on health disorders, which emphasizes the impact of processed meat protein on the richness of bacterial taxa such as (Mucispirillum, Oscillibacter), accompanied by increased expression of lipogenic genes. This review explores the most recent evidences on meat processing techniques, meat protein oxidation, underlying mechanisms, and their potential effects on nutritional value, gut microbiota composition and possible implications on human health.

Evaluation of the appropriate predictive contributor and diagnostic threshold for the cardio-metabolic syndrome in Chinese Uyghur adults

Background

Several epidemiological studies have suggested that optimal obesity and visceral adiposity indicators and their cut-off values to predict cardio-metabolic risks varied among different ethnic groups. However, few studies have investigated the associations of anthropometric indices with cardio-metabolic risks in Chinese Uyghur adults, and the results were inconsistent.

Methods

Between May and September 2016, a total of 4664 subjects aged ≥18 years old were recruited from Northwest China. Anthropometric indices and cardio-metabolic risk factors were measured by trained personnel. Partial correlation analyses and logistic regression analyses were used to evaluate the associations of anthropometric indices with cardio-metabolic risk factors. Receiver operating characteristic analysis was used to compare the abilities of different anthropometric indices to predict cardio-metabolic risk factors, and to determine the optimal cut-off values.

Results

The prevalence of metabolic syndrome was 39.41% in Uyghur adults from Xinjiang Uyghur Autonomous Region. Waist circumference (WC) performed better than other obesity indices in predicting the cardio-metabolic risk factors, and the optimal cut-off value of WC to diagnose metabolic syndrome risk factors was 86.50 cm for women and 90.50 cm for men.

Conclusions

Our study suggests that WC had the strongest predictive power for identifying cardio-metabolic risks in Xinjiang Uyghur adults. Further well-designed longitudinal studies are needed to confirm our findings.

Electronic supplementary material

The online version of this article (10.1186/s12889-019-6803-4) contains supplementary material, which is available to authorized users.

Both low- and regular-fat cheeses mediate improved insulin sensitivity and modulate serum phospholipid profiles in insulin-resistant rats

Dietary recommendations for cheese usually promote low (LOW)- over regular (REG)-fat versions due to the saturated fat. Conversely, epidemiological evidence shows that cheese consumption associates with reduced risk of type 2 diabetes. To investigate how cheese influences diabetes-related outcomes, a feeding trial comparing LOW and REG cheese was conducted in high-fat, lard-based diet (HFD)-fed insulin-resistant rats followed by evaluation of potential mechanisms. After 4 weeks of HFD, LOW or REG was added at 7 and 10 g/100 g diet, respectively, for another 8 weeks. Following either an oral glucose or insulin tolerance test to assess glucoregulation, rats were euthanized and serum was collected for metabolomic and lipid analyses. Hepatic tissue was used to measure glucoregulatory enzymes and lipid content. Both LOW and REG improved insulin sensitivity without effect on oral glucose tolerance, insulin secretion or body weight. Serum metabolomics identified 33 metabolites of interest, with 21 being phosphatidylcholines (PCs) or lysophosphatidylcholines (LPCs). HFD rats had significantly reduced LPC C16:1, C17:0, C18:1, C20:3 and C24:0, and these effects were normalized by LOW or REG cheese. Fourteen PC species were lowest in the HFD group and normalized by cheese feeding. Serum choline was elevated sevenfold in HFD- but not cheese-fed rats compared with rats fed low-fat diet. Liver triglyceride was elevated by LOW feeding. In conclusion, inclusion of both LOW and REG cheeses in the diet of insulin-resistant rats improves in vivo glucoregulation. This is associated with altered phospholipid metabolism, including cheese-mediated normalization of species that are decreased by high-fat feeding.

Food groups and intermediate disease markers: a systematic review and network meta-analysis of randomized trials

Background

In previous meta-analyses of prospective observational studies, we investigated the association between food groups and risk of chronic disease.

Objective

The aim of the present network meta-analysis (NMA) was to assess the effects of these food groups on intermediate-disease markers across randomized intervention trials.

Design

Literature searches were performed until January 2018. The following inclusion criteria were defined a priori: 1) randomized trial (≥4 wk duration) comparing ≥2 of the following food groups: refined grains, whole grains, nuts, legumes, fruits and vegetables, eggs, dairy, fish, red meat, and sugar-sweetened beverages (SSBs); 2) LDL cholesterol and triacylglycerol (TG) were defined as primary outcomes; total cholesterol, HDL cholesterol, fasting glucose, glycated hemoglobin, homeostasis model assessment insulin resistance, systolic and diastolic blood pressure, and C-reactive protein were defined as secondary outcomes. For each outcome, a random NMA was performed, and for the ranking, the surface under the cumulative ranking curves (SUCRA) was determined.

Results

A total of 66 randomized trials (86 reports) comparing 10 food groups and enrolling 3595 participants was identified. Nuts were ranked as the best food group at reducing LDL cholesterol (SUCRA: 93%), followed by legumes (85%) and whole grains (70%). For reducing TG, fish (97%) was ranked best, followed by nuts (78%) and red meat (72%). However, these findings are limited by the low quality of the evidence. When combining all 10 outcomes, the highest SUCRA values were found for nuts (66%), legumes (62%), and whole grains (62%), whereas SSBs performed worst (29%).

Conclusion

The present NMA provides evidence that increased intake of nuts, legumes, and whole grains is more effective at improving metabolic health than other food groups. For the credibility of diet-disease relations, high-quality randomized trials focusing on well-established intermediate-disease markers could play an important role. This systematic review was registered at PROSPERO (www.crd.york.ac.uk/PROSPERO) as CRD42018086753.

Metabolomic responses to lumacaftor/ivacaftor in cystic fibrosis

BACKGROUND

Cystic fibrosis (CF) is a life-limiting disease caused by a defect in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. Lumacaftor/Ivacaftor is a novel CFTR modulator approved for patients that are homozygous for Phe508del CFTR, but its clinical effectiveness varies amongst patients, making it difficult to determine clinical responders. Therefore, identifying biochemical biomarkers associated with drug response are clinically important for follow-up studies.

METHODS

Serum metabolomics was performed on twenty patients with CF pre- and 6-month post-Lumacaftor/Ivacaftor response via Ultrahigh Performance Liquid Chromatography-Tandem Mass Spectroscopy (UPLC-MS/MS). Correlation with clinical variables was performed.

RESULTS

Metabolomics analysis demonstrated 188 differentially regulated metabolites between patients pre- and post-Lumacaftor/Ivacaftor initiation, with a predominance of lipid and amino acid alterations. The top 30 metabolites were able to differentiate pre- and post-Lumacaftor/Ivacaftor status in greater than 90% of patients via a random-forest confusion matrix. Alterations in bile acids, phospholipids, and bacteria-associated metabolites were the predominant changes associated with drug response. Importantly, changes in metabolic patterns were associated with clinical responders.

CONCLUSIONS

Selected key lipid and amino acid metabolic pathways were significantly affected by Lumacaftor/Ivacaftor initiation and similar pathways were affected in clinical responders. Targeted metabolomics may provide useful and relevant biomarkers of CFTR modulator responses.