Effects of protein restriction on insulin-like growth factor (IGF)-1 in men with prostate cancer: results from a randomized clinical trial.

BACKGROUND: Insulin-like growth factor (IGF)-1 and its binding proteins are important in cancer growth, especially in prostate cancer. Observational studies suggest that protein restriction can lower IGF-1 levels. However, it is unclear whether an isocaloric protein-restricted diet affects IGF-1 and IGFBPs in men with prostate cancer. METHODS: In this academic, single-center, parallel-group, prospective, randomized, open-label, blinded end-point trial, 38 consenting overweight (BMI 30.5 ± 5.5 kg/m2) men with localized prostate cancer, aged 43-72 years, were randomized (1:1) with permuted blocks to 4-6 weeks of customized isocaloric PR diets (0.8 g protein/kg lean body mass) or their usual diet. Biomarkers influencing cancer biology, including serum IGF-1 and its binding proteins were measured longitudinally. RESULTS: Contrary to our hypothesis, feeding individuals an isocaloric protein-restricted diet did not result in a significant reduction in serum IGF-1. Moreover, there was no observed increase in serum IGFBP-1 or IGFBP-3 concentration. CONCLUSION: These findings demonstrate that protein restriction without calorie restriction does not reduce serum IGF-1 concentration or increase IGFBP-1 and IGFBP-3 in men with localized prostate cancer. Further research is needed to identify dietary interventions for safely and effectively reducing IGF-1 in this patient group.

Metaproteomic portrait of the healthy human gut microbiota.

Gut metaproteomics can provide direct evidence of microbial functions actively expressed in the colonic environments, contributing to clarify the role of the gut microbiota in human physiology. In this study, we re-analyzed 10 fecal metaproteomics datasets of healthy individuals from different continents and countries, with the aim of identifying stable and variable gut microbial functions and defining the contribution of specific bacterial taxa to the main metabolic pathways. The "core" metaproteome included 182 microbial functions and 83 pathways that were identified in all individuals analyzed. Several enzymes involved in glucose and pyruvate metabolism, along with glutamate dehydrogenase, acetate kinase, elongation factors G and Tu and DnaK, were the proteins with the lowest abundance variability in the cohorts under study. On the contrary, proteins involved in chemotaxis, response to stress and cell adhesion were among the most variable functions. Random-effect meta-analysis of correlation trends between taxa, functions and pathways revealed key ecological and molecular associations within the gut microbiota. The contribution of specific bacterial taxa to the main biological processes was also investigated, finding that Faecalibacterium is the most stable genus and the top contributor to anti-inflammatory butyrate production in the healthy gut microbiota. Active production of other mucosal immunomodulators facilitating host tolerance was observed, including Roseburia flagellin and lipopolysaccharide biosynthetic enzymes expressed by members of Bacteroidota. Our study provides a detailed picture of the healthy human gut microbiota, contributing to unveil its functional mechanisms and its relationship with nutrition, immunity, and environmental stressors.

DNA methylation-based biomarkers for cardiometabolic-related traits and their importance for risk stratification.

Recent findings: The prevalence of cardiometabolic syndrome in adults is increasing worldwide, highlighting the importance of biomarkers for individuals' classification based on their health status. Although cardiometabolic risk scores and diagnostic criteria have been developed aggregating adverse health effects of individual conditions on the overall syndrome, none of them has gained unanimous acceptance. Therefore, novel molecular biomarkers have been developed to better understand the risk, onset and progression of both individual conditions and the overall cardiometabolic syndrome. Summary: Consistent associations between whole blood DNA methylation (DNAm) levels at several single genomic (i.e. CpG) sites and both individual and aggregated cardiometabolic conditions supported the creation of second-generation DNAm-based cardiometabolic-related biomarkers. These biomarkers linearly combine individual DNAm levels from key CpG sites, selected by a two-step machine learning procedures. They can be used, even retrospectively, in populations with extant whole blood DNAm levels and without observed cardiometabolic phenotypes. Purpose of review: Here we offer an overview of the second-generation DNAm-based cardiometabolic biomarkers, discussing methodological advancements and implications on the interpretation and generalizability of the findings. We finally emphasize the contribution of DNAm-based biomarkers for risk stratification beyond traditional factors and discuss limitations and future directions of the field.