Anthropometric and blood parameters for the prediction of NAFLD among overweight and obese adults

Backround: Non-alcoholic fatty liver disease (NAFLD) comprises non-progressive steatosis and non-alcoholic steatohepatitis (NASH), the latter of which may cause cirrhosis and hepatocellular carcinoma (HCC). As NAFLD detection is imperative for the prevention of its complications, we evaluated whether a combination of blood-based biomarkers and anthropometric parameters can be used to predict NAFLD among overweight and obese adults. Methods: 143 overweight or obese non-smokers free of diabetes (50% women, age: 35–65 years) were recruited. Anthropometric indices and routine biomarkers of metabolism and liver function were measured to predict magnetic resonance (MR) - derived NAFLD by multivariable logistic regression models. In addition, we evaluated to which degree the use of more novel biomarkers (adiponectin, leptin, resistin, C-reactive protein, TNF-α, IL-6, IL-8 and interferon-γ) could improve prediction models. Results: NAFLD was best predicted by a combination of age, sex, waist circumference, ALT, HbA1c, and HOMA-IR at an area under the receiver operating characteristic curve (AUROC) of 0.87 (95% CI: 0.81, 0.93) before and 0.85 (95% CI: 0.78, 0.91) after internal bootstrap validation. The use of additional biomarkers of inflammation and metabolism did not improve NAFLD prediction. Previously published indices predicted NAFLD at AUROCs between 0.71 and 0.82. Conclusions: The AUROC of > 0.8 obtained by our regression model suggests the feasibility of a non-invasive detection of NAFLD by anthropometry and circulating biomarkers, even though further increments in the capacity of prediction models may be needed before NAFLD indices can be applied in routine clinical practice

Identification Of Urinary Polyphenol Metabolite Patterns Associated With Polyphenol-rich Food Intake In Adults From Four European Countries

We identified urinary polyphenol metabolite patterns by a novel algorithm that combines dimension reduction and variable selection methods to explain polyphenol-rich food intake, and compared their respective performance with that of single biomarkers in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. The study included 475 adults from four European countries (Germany, France, Italy, and Greece). Dietary intakes were assessed with 24-h dietary recalls (24-HDR) and dietary questionnaires (DQ). Thirty-four polyphenols were measured by ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI-MS-MS) in 24-h urine. Reduced rank regression-based variable importance in projection (RRR-VIP) and least absolute shrinkage and selection operator (LASSO) methods were used to select polyphenol metabolites. Reduced rank regression (RRR) was then used to identify patterns in these metabolites, maximizing the explained variability in intake of pre-selected polyphenol-rich foods. The performance of RRR models was evaluated using internal cross-validation to control for over-optimistic findings from over-fitting. High performance was observed for explaining recent intake (24-HDR) of red wine (r = 0.65; AUC = 89.1%), coffee (r = 0.51; AUC = 89.1%), and olives (r = 0.35; AUC = 82.2%). These metabolite patterns performed better or equally well compared to single polyphenol biomarkers. Neither metabolite patterns nor single biomarkers performed well in explaining habitual intake (as reported in the DQ) of polyphenol-rich foods. This proposed strategy of biomarker pattern identification has the potential of expanding the currently still limited list of available dietary intake biomarkers

Dietary essential α-linolenic acid and linoleic acid differentially modulate TNFα-induced NFκB activity in FADS2-deficient HEK-293 cells

<p>The pro- or anti-inflammatory bioactivity of dietary essential linoleic acid (LA) and alpha-linolenic acid (ALA) is mainly attributed to rate-limiting delta-6 desaturase (D6D) activity. The aim of this study was to analyze mechanisms of D6D-substrates ALA, LA and D6D-product gamma-linolenic acid (GLA) under D6D-deficient conditions. Fatty acid profiles (GC-MS), D6D gene expression (real-time RT-PCR) and NFκB activity (luciferase assay) were assessed in HEK293 cells. FADS2 gene expression was approved being marginal. Incubation with ALA or LA did not increase D6D products but their elongase products C20:3<i>n</i>-3 and C20:2<i>n</i>-6. Bypassing the D6D, GLA elevated C20:3<i>n</i>-6 and C20:4<i>n</i>-6. LA significantly increased (+18% at 60 μM; <i>p</i> < .001), ALA reduced (−32% at 100 μM; <i>p</i> < .001) and GLA did not specifically change NFκB activity. Our data indicate that D6D might not be essential for the distinct effects of LA and ALA on NFκB activity.</p

Dietary Factors in Relation to Liver Fat Content: A Cross-sectional Study

Non-alcoholic fatty liver disease (NAFLD) can lead to functional liver impairment and severe comorbidities. Beyond energy balance, several dietary factors may increase NAFLD risk, but human studies are lacking. The aim of this cross-sectional study was to investigate the associations between food consumption (47 food groups, derived Mediterranean and Dietary Approaches to Stop Hypertension (DASH) diet quality scores) and liver fat content (continuous scale and NAFLD, i.e., &gt;5% liver fat content). Liver fat content was measured by magnetic resonance imaging (MRI) in 136 individuals (BMI: 25&ndash;40 kg/m2, age: 35&ndash;65, 50.7% women) and food intake was recorded by food frequency questionnaires (FFQs). Associations between food items and liver fat were evaluated by multi-variable regression models. Intakes of cake and cookies as well legumes were inversely associated with liver fat content, while positive associations with intakes of high-fat dairy and cheese were observed. Only cake and cookie intake also showed an inverse association with NAFLD. This inverse association was unexpected, but not affected by adjustment for reporting bias. Both diet quality scores were inversely associated with liver fat content and NAFLD. Thus, as smaller previous intervention studies, our results suggest that higher diet quality is related to lower liver fat, but larger trials with iso-caloric interventions are needed to corroborate these findings

Key Genes of Lipid Metabolism and WNT-Signaling Are Downregulated in Subcutaneous Adipose Tissue with Moderate Weight Loss

Smaller cross-sectional studies and bariatric surgery trials suggest that weight loss may change the expression of genes in adipose tissue that have been implicated in the development of metabolic diseases, but well-powered intervention trials are lacking. In post hoc analyses of data from a 12-week dietary intervention trial initially designed to compare metabolic effects of intermittent vs. continuous calorie restriction, we analyzed the effects of overall weight loss on the subcutaneous adipose tissue (SAT) transcriptome. Changes in the transcriptome were measured by microarray using SAT samples of 138 overweight or obese individuals (age range: 35&ndash;65 years, BMI range: 25&ndash;40, non-smokers, non-diabetics). Participants were grouped post hoc according to the degree of their weight loss by quartiles (average weight loss in quartiles 1 to 4: 0%, &minus;3.2%, &minus;5.9%, and &minus;10.7%). Candidate genes showing differential expression with weight loss according to microarray analyses were validated by reverse transcription quantitative polymerase chain reaction (RT-qPCR), and fold changes (FCs) were calculated to quantify differences in gene expression. A comparison of individuals in the highest vs. the lowest weight loss quartile revealed 681 genes to be differentially expressed (corrected p &lt; 0.05), with 40 showing FCs of at least 0.4. Out of these, expression changes in secreted frizzled-related protein 2 (SFRP2, FC = 0.65, p = 0.006), stearoyl-CoA desaturase (SCD, FC = &minus;1.00, p &lt; 0.001), and hypoxia inducible lipid droplet-associated (HILPDA, FC = &minus;0.45, p = 0.001) with weight loss were confirmed by RT-qPCR. Dietary weight loss induces significant changes in the expression of genes implicated in lipid metabolism (SCD and HILPDA) and WNT-signaling (SFRP2) in SAT

Changes in Pancreatic Fat Content Following Diet-Induced Weight Loss

Background: Obesity can lead to ectopic pancreatic fat accumulation and increase the risk for type 2 diabetes. Smaller intervention trials have shown a decrease in pancreatic fat content (PFC) with weight loss, and we intended to investigate the effects of weight loss on PFC in a larger trial. Methods: Data from the HELENA-Trial, a randomized controlled trial (RCT) among 137 non-diabetic obese adults were used. The study cohort was classified into 4 quartiles based on weight change between baseline and 12 weeks post-intervention. Changes in PFC (baseline, 12 weeks and 50 weeks post-intervention) upon weight loss were analyzed by linear mixed models. Spearman&#8217;s coefficients were used to obtain correlations between anthropometric parameters, blood biochemical markers, and PFC. Results: At baseline, PFC only showed a significant correlation with visceral adipose tissue (VAT) (r = 0.41). Relative changes in PFC were significantly (p = 0.01) greater in Q4 (&#8722;30.8 &#177; 5.7%) than in Q1 (1.3 &#177; 6.7%). These differences remained similar after one year. However, when adjusting the statistical analyses for changes in VAT, the differences in PFC between Q1 and Q4 were no longer statistically significant. Conclusion: Weight loss is associated with a decrease in PFC. However, the reduction of PFC is not independent from reductions in VAT. Unlike VAT, PFC was not associated with metabolic biomarkers

Changes in Plasma Short-Chain Fatty Acid Levels after Dietary Weight Loss among Overweight and Obese Adults over 50 Weeks

Gut microbial-derived short-chain fatty acids (SCFAs) may regulate energy homeostasis and exert anti-carcinogenic, immunomodulatory and anti-inflammatory effects. Smaller trials indicate that dietary weight loss may lead to decreased SCFA production, but findings have been inconclusive. SCFA concentrations were measured by HPLC-MS/MS in plasma samples of 150 overweight or obese adults in a trial initially designed to evaluate the metabolic effects of intermittent (ICR) versus continuous (CCR) calorie restriction (NCT02449148). For the present post hoc analyses, participants were classified by quartiles of weight loss, irrespective of the dietary intervention. Linear mixed models were used to analyze weight-loss-induced changes in SCFA concentrations after 12, 24 and 50 weeks. There were no differential changes in SCFA levels across the initial study arms (ICR versus CCR versus control) after 12 weeks, but acetate concentrations significantly decreased with overall weight loss (mean log-relative change of −0.7 ± 1.8 in the lowest quartile versus. −7.6 ± 2 in the highest, p = 0.026). Concentrations of propionate, butyrate and other SCFAs did not change throughout the study. Our results show that weight-loss, achieved through calorie restriction, may lead to smaller initial decreases in plasma acetate, while plasma SCFAs generally remain remarkably stable over time

Adherence and Dietary Composition during Intermittent vs. Continuous Calorie Restriction: Follow-Up Data from a Randomized Controlled Trial in Adults with Overweight or Obesity

Although intermittent calorie restriction (ICR) has become popular as an alternative weight loss strategy to continuous calorie restriction (CCR), there is insufficient evidence on diet quality during ICR and on its feasibility over longer time periods. Thus, we compared dietary composition and adherence between ICR and CCR in a follow-up analysis of a randomized trial. A total of 98 participants with overweight or obesity [BMI (kg/m2) 25–39.9, 35–65 years, 49% females] were randomly assigned to ICR, operationalized as a “5:2 diet” (energy intake: ~100% on five non-restricted (NR) days, ~25% on two restricted (R) days), or CCR (daily energy intake: ~80%). The trial included a 12-week (wk) intervention phase, and follow-up assessments at wk24, wk50 and wk102. Apart from a higher proportion of energy intake from protein with ICR vs. CCR during the intervention (wk2: p &lt; 0.001; wk12: p = 0.002), there were no significant differences with respect to changes in dietary composition over time between the groups, while overall adherence to the interventions appeared to be good. No significant difference between ICR and CCR regarding weight change at wk102 was observed (p = 0.63). However, self-reported adherence was worse for ICR than CCR, with 71.1% vs. 32.5% of the participants reporting not to or only rarely have followed the regimen to which they were assigned between wk50 and wk102. These results indicate that within a weight management setting, ICR and CCR were equivalent in achieving modest weight loss over two years while affecting dietary composition in a comparable manner