Exercise and diet are treatments for nonalcoholic fatty liver disease (NAFLD) and prediabetes, however, how exercise and diet interventions impact gut microbiota in patients is incompletely understood. We previously reported a 8.6-month, four-arm (Aerobic exercise, n = 29; Diet, n = 28; Aerobic exercise + Diet, n = 29; No intervention, n = 29) randomized, singe blinded (for researchers), and controlled intervention in patients with NAFLD and prediabetes to assess the effect of interventions on the primary outcomes of liver fat content and glucose metabolism. Here we report the third primary outcome of the trial—gut microbiota composition—in participants who completed the trial (22 in Aerobic exercise, 22 in Diet, 23 in Aerobic exercise + Diet, 18 in No Intervention). We show that combined aerobic exercise and diet intervention are associated with diversified and stabilized keystone taxa, while exercise and diet interventions alone increase network connectivity and robustness between taxa. No adverse effects were observed with the interventions. In addition, in exploratory ad-hoc analyses we find that not all subjects responded to the intervention in a similar manner, when using differentially altered gut microbe amplicon sequence variants abundance to classify the responders and low/non-responders. A personalized gut microbial network at baseline could predict the individual responses in liver fat to exercise intervention. Our findings suggest an avenue for developing personalized intervention strategies for treatment of NAFLD based on host-gut microbiome ecosystem interactions, however, future studies with large sample size are needed to validate these discoveries. The Trial Registration Number is ISRCTN 42622771.
Background: Cardiovascular diseases may originate in childhood. Biomarkers identifying individuals with increased risk for disease are needed to support early detection and to optimise prevention strategies. Methods: In this prospective study, by applying a machine learning to high throughput NMR-based metabolomics data, we identified circulating childhood metabolic predictors of adult cardiovascular disease risk (MetS score) in a cohort of 396 females, followed from childhood (mean age 11¢2 years) to early adulthood (mean age 18¢1 years). The results obtained from the discovery cohort were validated in a large longitudinal birth cohort of females and males followed from puberty to adulthood (n = 2664) and in four cross-sectional data sets (n = 6341). Findings: The identified childhood metabolic signature included three circulating biomarkers, glycoprotein acetyls (GlycA), large high-density lipoprotein phospholipids (L-HDL-PL), and the ratio of apolipoprotein B to apolipoprotein A-1 (ApoB/ApoA) that were associated with increased cardio-metabolic risk in early adulthood (AUC = 0¢641-0¢802, all p<0¢01). These associations were confirmed in all validation cohorts with similar effect estimates both in females (AUC = 0¢667-0¢905, all p<0¢01) and males (AUC = 0¢734-0¢889, all p<0¢01) as well as in elderly patients with and without type 2 diabetes (AUC = 0¢517-0¢700, all p<0¢01). We subsequently applied random intercept cross-lagged panel model analysis, which suggested bidirectional causal relationship between metabolic biomarkers and cardio-metabolic risk score from childhood to early adulthood. Interpretation: These results provide evidence for the utility of a circulating metabolomics panel to identify children and adolescents at risk for future cardiovascular disease, to whom preventive measures and followup could be indicated.
Colorectal cancer (CRC) has complex pathological features that defy the linear-additive reasoning prevailing in current biomedicine studies. In pursuing a mechanistic understanding behind such complexity, we constructed a core molecular–cellular interaction network underlying CRC and investigated its nonlinear dynamical properties. The hypothesis and modelling method has been developed previously and tested in various cancer studies. The network dynamics reveal a landscape of several attractive basins corresponding to both normal intestinal phenotype and robust tumour subtypes, identified by their different molecular signatures. Comparison between the modelling results and gene expression profiles from patients collected at the second affiliated hospital of Zhejiang University is presented as validation. The numerical ‘driving’ experiment suggests that CRC pathogenesis may depend on pathways involved in gastrointestinal track development and molecules associated with mesenchymal lineage differentiation, such as Stat5, BMP, retinoic acid signalling pathways, Runx and Hox transcription families. We show that the multi-faceted response to immune stimulation and therapies, as well as different carcinogenesis and metastasis routes, can be straightforwardly understood and analysed under such a framework.
The production of secondary metabolites, while important for bioengineering purposes, presents a paradox in itself. Though widely existing in plants and bacteria, they have no definite physiological roles. Yet in both native habitats and laboratories, their production appears robust and follows apparent metabolic switches. We show in this work that the enzyme-catalysed process may improve the metabolic stability of the cells. The latter can be responsible for the overall metabolic behaviours such as dynamic metabolic landscape, metabolic switches and robustness, which can in turn affect the genetic formation of the organism in question. Mangrove-derived Streptomyces xiamenensis 318, with a relatively compact genome for secondary metabolism, is used as a model organism in our investigation. Integrated studies via kinetic metabolic modelling, transcriptase measurements and metabolic profiling were performed on this strain. Our results demonstrate that the secondary metabolites increase the metabolic fitness of the organism via stabilizing the underlying metabolic network. And the fluxes directing to NADH, NADPH, acetyl-CoA and glutamate provide the key switches for the overall and secondary metabolism. The information may be helpful for improving the xiamenmycin production on the strain.
Background: Cardiovascular diseases may originate in childhood. Biomarkers identifying individuals with increased risk for disease are needed to support early detection and to optimise prevention strategies. Methods: In this prospective study, by applying a machine learning to high throughput NMR-based metabolomics data, we identified circulating childhood metabolic predictors of adult cardiovascular disease risk (MetS score) in a cohort of 396 females, followed from childhood (mean age 11¢2 years) to early adulthood (mean age 18¢1 years). The results obtained from the discovery cohort were validated in a large longitudinal birth cohort of females and males followed from puberty to adulthood (n = 2664) and in four cross-sectional data sets (n = 6341). Findings: The identified childhood metabolic signature included three circulating biomarkers, glycoprotein acetyls (GlycA), large high-density lipoprotein phospholipids (L-HDL-PL), and the ratio of apolipoprotein B to apolipoprotein A-1 (ApoB/ApoA) that were associated with increased cardio-metabolic risk in early adulthood (AUC = 0¢641-0¢802, all p<0¢01). These associations were confirmed in all validation cohorts with similar effect estimates both in females (AUC = 0¢667-0¢905, all p<0¢01) and males (AUC = 0¢734-0¢889, all p<0¢01) as well as in elderly patients with and without type 2 diabetes (AUC = 0¢517-0¢700, all p<0¢01). We subsequently applied random intercept cross-lagged panel model analysis, which suggested bidirectional causal relationship between metabolic biomarkers and cardio-metabolic risk score from childhood to early adulthood. Interpretation: These results provide evidence for the utility of a circulating metabolomics panel to identify children and adolescents at risk for future cardiovascular disease, to whom preventive measures and followup could be indicated.
ABSTRACT. Phosphatidylinositol-3-OH kinase and RAS-activated signaling pathways play an important role in tumor formation. Abnormalities in relevant genes play essential roles in the occurrence and development of many human cancers. Studies of breast cancer have mainly focused on the women in western countries, but few studies have examined the frequency of mutations in PIK3CA, BRAF, and KRAS in Chinese breast cancer patients. In this study, we conducted sequence analysis of PIK3CA, BRAF, and KRAS and determined relationships with the occurrence of breast cancer in women from Qinghai. DNA was extracted from 25 cases of human breast cancer tissue samples. PIK3CA, BRAF, and KRAS mutation analysis was performed by polymerase chain reaction and DNA sequencing. No mutations were found in PIK3CA, BRAF, and KRAS of adjacent tissues. However, PIK3CA mutations were observed in 32% (8) of the 25 breast cancer tissues examined, in which exon 9 accounted for 4% (1), exon 20 accounted for 28% (7), and no mutations were found in exon 1 of PIK3CA. Sequencing of exon 2 of KRAS suggested that 20% (5) of the 25 samples harbored a mutation and 16% (4) 14840-14846 (2015) harbored a mutation. Any mutation in these 3 oncogenes may induce the occurrence and development of breast cancer.
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