Gut microbiota has been implicated as a pivotal contributing factor in diet-related obesity; however, its role in development of disease phenotypes in human genetic obesity such as Prader–Willi syndrome (PWS) remains elusive. In this hospitalized intervention trial with PWS (n = 17) and simple obesity (n = 21) children, a diet rich in non-digestible carbohydrates induced significant weight loss and concomitant structural changes of the gut microbiota together with reduction of serum antigen load and alleviation of inflammation. Co-abundance network analysis of 161 prevalent bacterial draft genomes assembled directly from metagenomic datasets showed relative increase of functional genome groups for acetate production from carbohydrates fermentation. NMR-based metabolomic profiling of urine showed diet-induced overall changes of host metabotypes and identified significantly reduced trimethylamine N-oxide and indoxyl sulfate, host-bacteria co-metabolites known to induce metabolic deteriorations. Specific bacterial genomes that were correlated with urine levels of these detrimental co-metabolites were found to encode enzyme genes for production of their precursors by fermentation of choline or tryptophan in the gut. When transplanted into germ-free mice, the pre-intervention gut microbiota induced higher inflammation and larger adipocytes compared with the post-intervention microbiota from the same volunteer. Our multi-omics-based systems analysis indicates a significant etiological contribution of dysbiotic gut microbiota to both genetic and simple obesity in children, implicating a potentially effective target for alleviation.Research in contextPoorly managed diet and genetic mutations are the two primary driving forces behind the devastating epidemic of obesity-related diseases. Lack of understanding of the molecular chain of causation between the driving forces and the disease endpoints retards progress in prevention and treatment of the diseases. We found that children genetically obese with Prader–Willi syndrome shared a similar dysbiosis in their gut microbiota with those having diet-related obesity. A diet rich in non-digestible but fermentable carbohydrates significantly promoted beneficial groups of bacteria and reduced toxin-producers, which contributes to the alleviation of metabolic deteriorations in obesity regardless of the primary driving forces.
R package, source code, and simulation study are available at https://github.com/YinanZheng/HIMA CONTACT: lei.liu@northwestern.edu.
Biological measures of aging are important for understanding the health of an aging population, with epigenetics particularly promising. Previous studies found that tumor tissue is epigenetically older than its donors are chronologically. We examined whether blood Δage (the discrepancy between epigenetic and chronological ages) can predict cancer incidence or mortality, thus assessing its potential as a cancer biomarker. In a prospective cohort, Δage and its rate of change over time were calculated in 834 blood leukocyte samples collected from 442 participants free of cancer at blood draw. About 3–5 years before cancer onset or death, Δage was associated with cancer risks in a dose-responsive manner (P = 0.02) and a one-year increase in Δage was associated with cancer incidence (HR: 1.06, 95% CI: 1.02–1.10) and mortality (HR: 1.17, 95% CI: 1.07–1.28). Participants with smaller Δage and decelerated epigenetic aging over time had the lowest risks of cancer incidence (P = 0.003) and mortality (P = 0.02). Δage was associated with cancer incidence in a ‘J-shaped’ manner for subjects examined pre-2003, and with cancer mortality in a time-varying manner. We conclude that blood epigenetic age may mirror epigenetic abnormalities related to cancer development, potentially serving as a minimally invasive biomarker for cancer early detection.
Objective To investigate the gut microbiota differences of obese children compared with the control healthy cohort to result in further understanding of the mechanism of obesity development. Methods We evaluated the 16S rRNA gene, the enterotypes, and quantity of the gut microbiota among obese children and the control cohort and learned the differences of the gut microbiota during the process of weight reduction in obese children. Results In the present study, we learned that the gut microbiota composition was significantly different between obese children and the healthy cohort. Next we found that functional changes, including the phosphotransferase system, ATP-binding cassette transporters, flagellar assembly, and bacterial chemotaxis were overrepresented, while glycan biosynthesis and metabolism were underrepresented in case samples. Moreover, we learned that the amount of Bifidobacterium and Lactobacillus increased among the obese children during the process of weight reduction. Conclusion Our results might enrich the research between gut microbiota and obesity and further provide a clinical basis for therapy for obesity. We recommend that Bifidobacterium and Lactobacillus might be used as indicators of healthy conditions among obese children, as well as a kind of prebiotic and probiotic supplement in the diet to be an auxiliary treatment for obesity.
Background Ambient particular matter (PM) exposure has been associated with short- and long-term effects on cardiovascular disease (CVD). Telomere length (TL) is a biomarker of CVD risk that is modified by inflammation and oxidative stress, two key pathways for PM effects. Whether PM exposure modifies TL is largely unexplored. Objectives To investigate effects of PM on blood TL in a highly-exposed population. Methods We measured blood TL in 120 blood samples from truck drivers and 120 blood samples from office workers in Beijing, China. We measured personal PM2.5 and Elemental Carbon (EC, a tracer of traffic particles) using light-weight monitors. Ambient PM10 was obtained from local monitoring stations. We used covariate-adjusted regression models to estimate percent changes in TL per an interquartile-range increase in exposure. Results Covariate-adjusted TL was higher in drivers (mean=0.87, 95%CI: 0.74; 1.03) than in office workers (mean=0.79, 95%CI: 0.67; 0.93; p=0.001). In all participants combined, TL increased in association with personal PM2.5 (+5.2%, 95%CI: 1.5; 9.1; p=0.007), personal EC (+4.9%, 95%CI: 1.2; 8.8; p=0.01), and ambient PM10 (+7.7%, 95%CI: 3.7; 11.9; p<0.001) on examination days. In contrast, average ambient PM10 over the 14 days before the examinations was significantly associated with shorter TL (−9.9%, 95%CI: −17.6; −1.5; p=0.02). Conclusions Short-term exposure to ambient PM is associated with increased blood TL, consistent with TL roles during acute inflammatory responses. Longer exposures may shorten TL as expected after prolonged pro-oxidant exposures. The observed TL alterations may participate in the biological pathways of short- and long-term PM effects.
DNA methylation in repetitive elements (RE) suppresses their mobility and maintains genomic stability, and decreases in it are frequently observed in tumor and/or surrogate tissues. Averaging methylation across RE in genome is widely used to quantify global methylation. However, methylation may vary in specific RE and play diverse roles in disease development, thus averaging methylation across RE may lose significant biological information. The ambiguous mapping of short reads by and high cost of current bisulfite sequencing platforms make them impractical for quantifying locus-specific RE methylation. Although microarray-based approaches (particularly Illumina's Infinium methylation arrays) provide cost-effective and robust genome-wide methylation quantification, the number of interrogated CpGs in RE remains limited. We report a random forest-based algorithm (and corresponding R package, REMP) that can accurately predict genome-wide locus-specific RE methylation based on Infinium array profiling data. We validated its prediction performance using alternative sequencing and microarray data. Testing its clinical utility with The Cancer Genome Atlas data demonstrated that our algorithm offers more comprehensively extended locus-specific RE methylation information that can be readily applied to large human studies in a cost-effective manner. Our work has the potential to improve our understanding of the role of global methylation in human diseases, especially cancer.
BackgroundMitochondria are both a sensitive target and a primary source of oxidative stress, a key pathway of air particulate matter (PM)-associated diseases. Mitochondrial DNA copy number (MtDNAcn) is a marker of mitochondrial damage and malfunctioning. We evaluated whether ambient PM exposure affects MtDNAcn in a highly-exposed population in Beijing, China.MethodsThe Beijing Truck Driver Air Pollution Study was conducted shortly before the 2008 Beijing Olympic Games (June 15-July 27, 2008) and included 60 truck drivers and 60 office workers. Personal PM2.5 and elemental carbon (EC, a tracer of traffic particles) were measured during work hours using portable monitors. Post-work blood samples were obtained on two different days. Ambient PM10 was averaged from 27 monitoring stations in Beijing. Blood MtDNAcn was determined by real-time PCR and examined in association with particle levels using mixed-effect models.ResultsIn all participants combined, MtDNAcn was negatively associated with personal EC level measured during work hours (β=−0.059, 95% CI: -0.011; -0.0006, p=0.03); and 5-day (β=−0.017, 95% CI: -0.029;-0.005, p=0.01) and 8-day average ambient PM10 (β=−0.008, 95% CI: -0.043; -0.008, p=0.004) after adjusting for possible confounding factors, including study groups. MtDNAcn was also negatively associated among office workers with EC (β=−0.012, 95% CI: -0.022;-0.002, p=0.02) and 8-day average ambient PM10 (β=−0.030, 95% CI: -0.051;-0.008, p=0.007).ConclusionsWe observed decreased blood MtDNAcn in association with increased exposure to EC during work hours and recent ambient PM10 exposure. Our results suggest that MtDNAcn may be influenced by particle exposures. Further studies are required to determine the roles of MtDNAcn in the etiology of particle-related diseases.
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