Background & AimsThe incidence of nonalcoholic steatohepatitis (NASH) is increasing. The pathophysiological mechanisms of NASH and the sequence of events leading to hepatic fibrosis are incompletely understood. The aim of this study was to gain insight into the dynamics of key molecular processes involved in NASH and to rank early markers for hepatic fibrosis.MethodsA time-course study in low-density lipoprotein–receptor knockout. Leiden mice on a high-fat diet was performed to identify the temporal dynamics of key processes contributing to NASH and fibrosis. An integrative systems biology approach was used to elucidate candidate markers linked to the active fibrosis process by combining transcriptomics, dynamic proteomics, and histopathology. The translational value of these findings were confirmed using human NASH data sets.ResultsHigh-fat-diet feeding resulted in obesity, hyperlipidemia, insulin resistance, and NASH with fibrosis in a time-dependent manner. Temporal dynamics of key molecular processes involved in the development of NASH were identified, including lipid metabolism, inflammation, oxidative stress, and fibrosis. A data-integrative approach enabled identification of the active fibrotic process preceding histopathologic detection using a novel molecular fibrosis signature. Human studies were used to identify overlap of genes and processes and to perform a network biology-based prioritization to rank top candidate markers representing the early manifestation of fibrosis.ConclusionsAn early predictive molecular signature was identified that marked the active profibrotic process before histopathologic fibrosis becomes manifest. Early detection of the onset of NASH and fibrosis enables identification of novel blood-based biomarkers to stratify patients at risk, development of new therapeutics, and help shorten (pre)clinical experimental time frames.

BackgroundA key feature of metabolic health is the ability to adapt upon dietary perturbations. A systemic review defined an optimal nutritional challenge test, the “PhenFlex test” (PFT). Recently, it has been shown that the PFT enables the quantification of all relevant metabolic processes involved in maintaining or regaining homeostasis of metabolic health. Furthermore, it was demonstrated that quantification of PFT response was more sensitive as compared to fasting markers in demonstrating reduced phenotypic flexibility in metabolically impaired type 2 diabetes subjects.MethodsThis study aims to demonstrate that quantification of PFT response can discriminate between different states of health within the healthy range of the population. Therefore, 100 healthy subjects were enrolled (50 males, 50 females) ranging in age (young, middle, old) and body fat percentage (low, medium, high), assuming variation in phenotypic flexibility. Biomarkers were selected to quantify main processes which characterize phenotypic flexibility in response to PFT: flexibility in glucose, lipid, amino acid and vitamin metabolism, and metabolic stress. Individual phenotypic flexibility was visualized using the “health space” by representing the four processes on the health space axes. By quantifying and presenting the study subjects in this space, individual phenotypic flexibility was visualized.ResultsUsing the “health space” visualization, differences between groups as well as within groups from the healthy range of the population can be easily and intuitively assessed. The health space showed a different adaptation to the metabolic PhenFlex test in the extremes of the recruited population; persons of young age with low to normal fat percentage had a markedly different position in the health space as compared to persons from old age with normal to high fat percentage.ConclusionThe results of the metabolic PhenFlex test in conjunction with the health space reliably assessed health on an individual basis. This quantification can be used in the future for personalized health quantification and advice.Electronic supplementary materialThe online version of this article (10.1186/s12263-017-0589-8) contains supplementary material, which is available to authorized users.

Bile acids (BA) are signaling molecules with a wide range of biological effects, also identified among the most responsive plasma metabolites in the postprandial state. We here describe this response to different dietary challenges and report on key determinants linked to its interindividual variability. Healthy men and women ( = 72, 62 ± 8 yr, mean ± SE) were enrolled into a 12-wk weight loss intervention. All subjects underwent an oral glucose tolerance test and a mixed-meal tolerance test before and after the intervention. BA were quantified in plasma by liquid chromatography-tandem mass spectrometry combined with whole genome exome sequencing and fecal microbiota profiling. Considering the average response of all 72 subjects, no effect of the successful weight loss intervention was found on plasma BA profiles. Fasting and postprandial BA profiles revealed high interindividual variability, and three main patterns in postprandial BA response were identified using multivariate analysis. Although the women enrolled were postmenopausal, effects of sex difference in BA response were evident. Exome data revealed the contribution of preselected genes to the observed interindividual variability. In particular, a variant in the gene, encoding the small intestinal BA transporter organic anion-transporting polypeptide-1A2 (OATP1A2), was associated with delayed postprandial BA increases. Fecal microbiota analysis did not reveal evidence for a significant influence of bacterial diversity and/or composition on plasma BA profiles. The analysis of plasma BA profiles in response to two different dietary challenges revealed a high interindividual variability, which was mainly determined by genetics and sex difference of host with minimal effects of the microbiota. Considering the average response of all 72 subjects, no effect of the successful weight loss intervention was found on plasma bile acid (BA) profiles. Despite high interindividual variability, three main patterns in postprandial BA response were identified using multivariate analysis. A variant in the gene, encoding the small intestinal BA transporter organic anion-transporting polypeptide-1A2 (OATP1A2), was associated with delayed postprandial BA increases in response to both the oral glucose tolerance test and the mixed-meal tolerance test.

Summary Background Alterations of the skin microbiome have been associated with atopic dermatitis (AD) and its severity. The nasal microbiome in relation to AD severity is less well studied. Objectives We aimed to characterize the nasal and skin microbiomes in children with AD in relation to disease severity. In addition, we explored the differences and correlations between the nasal and skin communities. Methods We characterized the microbial composition of 90 nasal and 108 lesional skin samples cross‐sectionally from patients with AD, using 16S‐rRNA sequencing. In addition, a quantitative polymerase chain reaction was performed for Staphylococcus aureus and Staphylococcus epidermidis on the skin samples, and AD severity was estimated using the self‐administered Eczema Area and Severity Index. Results We found an association between the microbial composition and AD severity in both the nose and skin samples (R2 = 2·6%; P = 0·017 and R2 = 7·0%; P = 0·004), strongly driven by staphylococci. However, other species also contributed, such as Moraxella in the nose. Skin lesions were positive for S. aureus in 50% of the children, and the presence and the load of S. aureus were not associated with AD severity. Although the nose and skin harbour distinct microbial communities (n = 48 paired samples; P < 0·001), we found that correlations exist between species in the nose and (other) species on the skin. Conclusions Our results indicate that both the nasal and the skin microbiomes are associated with AD severity in children and that, next to staphylococci, other species contribute to this association.

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