The oxidative stress imposed by reactive oxygen species (ROS) plays an important role in many chronic and degenerative diseases. As an important category of phytochemicals, phenolic compounds universally exist in plants, and have been considered to have high antioxidant ability and free radical scavenging capacity, with the mechanism of inhibiting the enzymes responsible for ROS production and reducing highly oxidized ROS. Therefore, phenolic compounds have attracted increasing attention as potential agents for preventing and treating many oxidative stress-related diseases, such as cardiovascular diseases, cancer, ageing, diabetes mellitus and neurodegenerative diseases. This review summarizes current knowledge of natural polyphenols, including resource, bioactivities, bioavailability and potential toxicity.
There is much epidemiological evidence that a diet rich in fruits and vegetables could lower the risk of certain cancers. The effect has been attributed, in part, to natural polyphenols. Besides, numerous studies have demonstrated that natural polyphenols could be used for the prevention and treatment of cancer. Potential mechanisms included antioxidant, anti-inflammation as well as the modulation of multiple molecular events involved in carcinogenesis. The current review summarized the anticancer efficacy of major polyphenol classes (flavonoids, phenolic acids, lignans and stilbenes) and discussed the potential mechanisms of action, which were based on epidemiological, in vitro, in vivo and clinical studies within the past five years.
14 November 2022 in Translational Neurodegeneration
Background: Microbiome-gut-brain axis may be involved in the progression of age-related cognitive impairment and relevant brain structure changes, but evidence from large human cohorts is lacking. This study was aimed to investigate the associations of gut microbiome with cognitive impairment and brain structure based on multi-omics from three independent populations. Methods: We included 1430 participants from the Guangzhou Nutrition and Health Study (GNHS) with both gut microbiome and cognitive assessment data available as a discovery cohort, of whom 272 individuals provided fecal samples twice before cognitive assessment. We selected 208 individuals with baseline microbiome data for brain magnetic resonance imaging during the follow-up visit. Fecal 16S rRNA and shotgun metagenomic sequencing, targeted serum metabolomics, and cytokine measurements were performed in the GNHS. The validation analyses were conducted in an Alzheimer’s disease case–control study (replication study 1, n = 90) and another community-based cohort (replication study 2, n = 1300) with cross-sectional dataset. Results: We found protective associations of specific gut microbial genera (Odoribacter, Butyricimonas, and Bacteroides) with cognitive impairment in both the discovery cohort and the replication study 1. Result of Bacteroides was further validated in the replication study 2. Odoribacter was positively associated with hippocampal volume (β, 0.16; 95% CI 0.06–0.26, P = 0.002), which might be mediated by acetic acids. Increased intra-individual alterations in gut microbial composition were found in participants with cognitive impairment. We also identified several serum metabolites and inflammation-associated metagenomic species and pathways linked to impaired cognition. Conclusions: Our findings reveal that specific gut microbial features are closely associated with cognitive impairment and decreased hippocampal volume, which may play an important role in dementia development.
The relationship of triglycerides (TG) to the risk of death remains uncertain. The aim of this study was to determine the associations between blood triglyceride levels and cardiovascular diseases (CVDs) mortality and all-cause mortality. Four databases were searched without language restriction for relevant studies: PubMed, ScienceDirect, EMBASE, and Google Scholar. All prospective cohort studies reporting an association between TG and CVDs or all-cause mortality published before July 2013 were included. Risk ratios (RRs) with 95% confidence intervals (CIs) were extracted and pooled according to TG categories, unit TG, and logarithm of TG using a random-effects model with inverse-variance weighting. We identified 61 eligible studies, containing 17,018 CVDs deaths in 726,030 participants and 58,419 all-cause deaths in 330,566 participants. Twelve and fourteen studies, respectively, reported the effects estimates of CVDs and total mortality by TG categories. Compared to the referent (90–149 mg/dL), the pooled RRs (95% CI) of CVDs mortality for the lowest (< 90 mg/dL), borderline-high (150–199 mg/dL), and high TG (≥ 200 mg/dL) groups were 0.83 (0.75 to 0.93), 1.15 (1.03 to 1.29), and 1.25 (1.05 to 1.50); for total mortality they were 0.94 (0.85 to 1.03), 1.09 (1.02 to 1.17), and 1.20 (1.04 to 1.38), respectively. The risks of CVDs and all-cause deaths were increased by 13% and 12% (p < 0.001) per 1-mmol/L TG increment in twenty-two and twenty-two studies reported RRs per unit TG, respectively. In conclusion, elevated blood TG levels were dose-dependently associated with higher risks of CVDs and all-cause mortality.
OBJECTIVE To identify the core gut microbial features associated with type 2 diabetes risk and potential demographic, adiposity, and dietary factors associated with these features. RESEARCH DESIGN AND METHODS We used an interpretable machine learning framework to identify the type 2 diabetes–related gut microbiome features in the cross-sectional analyses of three Chinese cohorts: one discovery cohort (n = 1,832, 270 cases of type 2 diabetes) and two validation cohorts (cohort 1: n = 203, 48 cases; cohort 2: n = 7,009, 608 cases). We constructed a microbiome risk score (MRS) with the identified features. We examined the prospective association of the MRS with glucose increment in 249 participants without type 2 diabetes and assessed the correlation between the MRS and host blood metabolites (n = 1,016). We transferred human fecal samples with different MRS levels to germ-free mice to confirm the MRS–type 2 diabetes relationship. We then examined the prospective association of demographic, adiposity, and dietary factors with the MRS (n = 1,832). RESULTS The MRS (including 14 microbial features) consistently associated with type 2 diabetes, with risk ratio for per 1-unit change in MRS 1.28 (95% CI 1.23–1.33), 1.23 (1.13–1.34), and 1.12 (1.06–1.18) across three cohorts. The MRS was positively associated with future glucose increment (P < 0.05) and was correlated with a variety of gut microbiota–derived blood metabolites. Animal study further confirmed the MRS–type 2 diabetes relationship. Body fat distribution was found to be a key factor modulating the gut microbiome–type 2 diabetes relationship. CONCLUSIONS Our results reveal a core set of gut microbiome features associated with type 2 diabetes risk and future glucose increment.
Objective: The human gut fungal community, known as the mycobiome, plays a fundamental role in the gut ecosystem and health. Here we aimed to investigate the determinants and long-term stability of gut mycobiome among middle-aged and elderly adults. We further explored the interplay between gut fungi and bacteria on metabolic health. Design: The present study included 1244 participants from the Guangzhou Nutrition and Health Study. We characterised the long-term stability and determinants of the human gut mycobiome, especially long-term habitual dietary consumption. The comprehensive multiomics analyses were performed to investigate the ecological links between gut bacteria, fungi and faecal metabolome. Finally, we examined whether the interaction between gut bacteria and fungi could modulate the metabolic risk. Results: The gut fungal composition was temporally stable and mainly determined by age, long-term habitual diet and host physiological states. Specifically, compared with middle-aged individuals, Blastobotrys and Agaricomycetes spp were depleted, while Malassezia was enriched in the elderly. Dairy consumption was positively associated with Saccharomyces but inversely associated with Candida. Notably, Saccharomycetales spp interacted with gut bacterial diversity to influence insulin resistance. Bidirectional mediation analyses indicated that bacterial function or faecal histidine might causally mediate an impact of Pichia on blood cholesterol. Conclusion: We depict the sociodemographic and dietary determinants of human gut mycobiome in middle-aged and elderly individuals, and further reveal that the gut mycobiome may be closely associated with the host metabolic health through regulating gut bacterial functions and metabolites.