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Abstract Background Colorectal cancer (CRC) risk is strongly affected by dietary habits with red and processed meat increasing risk, and foods rich in dietary fibres considered protective. Dietary habits also shape gut microbiota, but the role of the combination between diet, the gut microbiota, and the metabolite profile on CRC risk is still missing an unequivocal characterisation. Methods To investigate how gut microbiota affects diet-associated CRC risk, we fed Apc-mutated PIRC rats and azoxymethane (AOM)-induced rats the following diets: a high-risk red/processed meat-based diet (MBD), a normalised risk diet (MBD with α-tocopherol, MBDT), a low-risk pesco-vegetarian diet (PVD), and control diet. We then conducted faecal microbiota transplantation (FMT) from PIRC rats to germ-free rats treated with AOM and fed a standard diet for 3 months. We analysed multiple tumour markers and assessed the variations in the faecal microbiota using 16S rRNA gene sequencing together with targeted- and untargeted-metabolomics analyses. Results In both animal models, the PVD group exhibited significantly lower colon tumorigenesis than the MBD ones, consistent with various CRC biomarkers. Faecal microbiota and its metabolites also revealed significant diet-dependent profiles. Intriguingly, when faeces from PIRC rats fed these diets were transplanted into germ-free rats, those transplanted with MBD faeces developed a higher number of preneoplastic lesions together with distinctive diet-related bacterial and metabolic profiles. PVD determines a selection of nine taxonomic markers mainly belonging to Lachnospiraceae and Prevotellaceae families exclusively associated with at least two different animal models, and within these, four taxonomic markers were shared across all the three animal models. An inverse correlation between nonconjugated bile acids and bacterial genera mainly belonging to the Lachnospiraceae and Prevotellaceae families (representative of the PVD group) was present, suggesting a potential mechanism of action for the protective effect of these genera against CRC. Conclusions These results highlight the protective effects of PVD while reaffirming the carcinogenic properties of MBD diets. In germ-free rats, FMT induced changes reminiscent of dietary effects, including heightened preneoplastic lesions in MBD rats and the transmission of specific diet-related bacterial and metabolic profiles. Importantly, to the best of our knowledge, this is the first study showing that diet-associated cancer risk can be transferred with faeces, establishing gut microbiota as a determinant of diet-associated CRC risk. Therefore, this study marks the pioneering demonstration of faecal transfer as a means of conveying diet-related cancer risk, firmly establishing the gut microbiota as a pivotal factor in diet-associated CRC susceptibility. Video Abstract

Abstract Accurate non-invasive biomarkers to diagnose metabolic dysfunction-associated steatotic liver disease (MASLD)-related fibrosis are urgently needed. This study applies a translational approach to develop a blood-based biomarker panel for fibrosis detection in MASLD. A molecular gene expression signature identified from a diet-induced MASLD mouse model (LDLr−/−.Leiden) is translated into human blood-based biomarkers based on liver biopsy transcriptomic profiles and protein levels in MASLD patient serum samples. The resulting biomarker panel consists of IGFBP7, SSc5D and Sema4D. LightGBM modeling using this panel demonstrates high accuracy in predicting MASLD fibrosis stage (F0/F1: AUC = 0.82; F2: AUC = 0.89; F3/F4: AUC = 0.87), which is replicated in an independent validation cohort. The overall accuracy of the model outperforms predictions by the existing markers Fib-4, APRI and FibroScan. In conclusion, here we show a disease mechanism-related blood-based biomarker panel with three biomarkers which is able to identify MASLD patients with mild or advanced hepatic fibrosis with high accuracy.

With the purpose of identifying a sensitive, robust, and easy-to-measure set of biomarkers to assess stress reactivity, we here study a large set of relatively easy to obtain markers reflecting subjective, autonomic nervous system (ANS), endocrine, and inflammatory responses to acute social stress (n = 101). A subset of the participants was exposed to another social stressor the next day (n = 48) while being measured in the same way. Acute social stress was induced following standardized procedures. The markers investigated were self-reported positive and negative affect, heart rate, electrodermal activity, salivary cortisol, and ten inflammatory markers both in capillary plasma and salivary samples, including IL-22 which has not been studied in response to acute stress in humans before. Robust effects (significant effect in the same direction for both days) were found for self-reported negative affect, heart rate, electrodermal activity, plasma IL-5, plasma IL-22, salivary IL-8 and salivary IL-10. Of these seven markers, the participants’ IL-22 responses on the first day were positively correlated to those on the second day. We found no correlations between salivary and capillary plasma stress responses for any of the ten cytokines and somewhat unexpectedly, cytokine responses in saliva seemed more pronounced and more in line with previous literature than cytokines in capillary plasma. In sum, seven robust and easy to obtain biomarkers to measure acute stress response were identified and should be used in future stress research to detect and examine stress reactivity. This includes IL-22 in plasma as a promising novel marker.

The prevalence of non-alcoholic steatohepatitis (NASH) is rapidly increasing and associated with cardiovascular disease (CVD), the major cause of mortality in NASH patients. Although sharing common risk factors, the mechanisms by which NASH may directly contribute to the development to CVD remain poorly understood. The aim of this study is to gain insight into key molecular processes of NASH that drive atherosclerosis development. Thereto, a time-course study was performed in Ldlr−/−.Leiden mice fed a high-fat diet to induce NASH and atherosclerosis. The effects on NASH and atherosclerosis were assessed and transcriptome analysis was performed. Ldlr−/−.Leiden mice developed obesity, hyperlipidemia and insulin resistance, with steatosis and hepatic inflammation preceding atherosclerosis development. Transcriptome analysis revealed a time-dependent increase in pathways related to NASH and fibrosis followed by an increase in pro-atherogenic processes in the aorta. Gene regulatory network analysis identified specific liver regulators related to lipid metabolism (SC5D, LCAT and HMGCR), inflammation (IL1A) and fibrosis (PDGF, COL3A1), linked to a set of aorta target genes related to vascular inflammation (TNFA) and atherosclerosis signaling (CCL2 and FDFT1). The present study reveals pathogenic liver processes that precede atherosclerosis development and identifies hepatic key regulators driving the atherogenic pathways and regulators in the aorta.

The number of individuals suffering from type 2 diabetes is dramatically increasing worldwide, resulting in an increasing burden on society and rising healthcare costs. With increasing evidence supporting lifestyle intervention programs to reduce type 2 diabetes, and the use of scenario simulations for policy support, there is an opportunity to improve population interventions based upon cost–benefit analysis of especially complex lifestyle intervention programs through dynamic simulations. In this article, we used the System Dynamics (SD) modeling methodology aiming to develop a simulation model for policy makers and health professionals to gain a clear understanding of the patient journey of type 2 diabetes mellitus and to assess the impact of lifestyle intervention programs on total cost for society associated with prevention and lifestyle treatment of pre-diabetes and type 2 diabetes in The Netherlands. System dynamics describes underlying structure in the form of causal relationships, stocks, flows, and delays to explore behavior and simulate scenarios, in order to prescribe intervention programs. The methodology has the opportunity to estimate and simulate the consequences of unforeseen interactions in order to prescribe intervention programs based on scenarios tested through “what-if” experiments. First, the extensive knowledge of diabetes, current available data on the type 2 diabetes population, lifestyle intervention programs, and associated cost in The Netherlands were captured in one simulation model. Next, the relationships between leverage points on the growth of type 2 diabetes population were based upon available data. Subsequently, the cost and benefits of future lifestyle intervention programs on reducing diabetes were simulated, identifying the need for an integrated adaptive design of lifestyle programs while collecting the appropriate data over time. The strengths and limitations of scenario simulations of complex lifestyle intervention programs to improve the (cost)effectiveness of these programs to reduce diabetes in a more sustainable way compared to usual care are discussed.