11 research outputs found

    Immunological and Cardiometabolic Risk Factors in the Prediction of Type 2 Diabetes and Coronary Events: MONICA/KORA Augsburg Case-Cohort Study

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    BACKGROUND: This study compares inflammation-related biomarkers with established cardiometabolic risk factors in the prediction of incident type 2 diabetes and incident coronary events in a prospective case-cohort study within the population-based MONICA/KORA Augsburg cohort. METHODS AND FINDINGS: Analyses for type 2 diabetes are based on 436 individuals with and 1410 individuals without incident diabetes. Analyses for coronary events are based on 314 individuals with and 1659 individuals without incident coronary events. Mean follow-up times were almost 11 years. Areas under the receiver-operating characteristic curve (AUC), changes in Akaike's information criterion (ΔAIC), integrated discrimination improvement (IDI) and net reclassification index (NRI) were calculated for different models. A basic model consisting of age, sex and survey predicted type 2 diabetes with an AUC of 0.690. Addition of 13 inflammation-related biomarkers (CRP, IL-6, IL-18, MIF, MCP-1/CCL2, IL-8/CXCL8, IP-10/CXCL10, adiponectin, leptin, RANTES/CCL5, TGF-β1, sE-selectin, sICAM-1; all measured in nonfasting serum) increased the AUC to 0.801, whereas addition of cardiometabolic risk factors (BMI, systolic blood pressure, ratio total/HDL-cholesterol, smoking, alcohol, physical activity, parental diabetes) increased the AUC to 0.803 (ΔAUC [95% CI] 0.111 [0.092-0.149] and 0.113 [0.093-0.149], respectively, compared to the basic model). The combination of all inflammation-related biomarkers and cardiometabolic risk factors yielded a further increase in AUC to 0.847 (ΔAUC [95% CI] 0.044 [0.028-0.066] compared to the cardiometabolic risk model). Corresponding AUCs for incident coronary events were 0.807, 0.825 (ΔAUC [95% CI] 0.018 [0.013-0.038] compared to the basic model), 0.845 (ΔAUC [95% CI] 0.038 [0.028-0.059] compared to the basic model) and 0.851 (ΔAUC [95% CI] 0.006 [0.003-0.021] compared to the cardiometabolic risk model), respectively. CONCLUSIONS: Inclusion of multiple inflammation-related biomarkers into a basic model and into a model including cardiometabolic risk factors significantly improved the prediction of type 2 diabetes and coronary events, although the improvement was less pronounced for the latter endpoint

    Metagenomic binning of a marine sponge microbiome reveals unity in defense but metabolic specialization

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    Marine sponges are ancient metazoans that are populated by distinct and highly diverse microbial communities. In order to obtain deeper insights into the functional gene repertoire of the Mediterranean sponge Aplysina aerophoba, we combined Illumina short-read and PacBio long-read sequencing followed by un-targeted metagenomic binning. We identified a total of 37 high-quality bins representing 11 bacterial phyla and two candidate phyla. Statistical comparison of symbiont genomes with selected reference genomes revealed a significant enrichment of genes related to bacterial defense (restriction-modification systems, toxin-antitoxin systems) as well as genes involved in host colonization and extracellular matrix utilization in sponge symbionts. A within-symbionts genome comparison revealed a nutritional specialization of at least two symbiont guilds, where one appears to metabolize carnitine and the other sulfated polysaccharides, both of which are abundant molecules in the sponge extracellular matrix. A third guild of symbionts may be viewed as nutritional generalists that perform largely the same metabolic pathways but lack such extraordinary numbers of the relevant genes. This study characterizes the genomic repertoire of sponge symbionts at an unprecedented resolution and it provides greater insights into the molecular mechanisms underlying microbial-sponge symbiosis

    Single-cell genomics reveals complex carbohydrate degradation patterns in poribacterial symbionts of marine sponges

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    Kamke J, Sczyrba A, Ivanova N, et al. Single-cell genomics reveals complex carbohydrate degradation patterns in poribacterial symbionts of marine sponges. The ISME journal. 2013;7(12):2287-2300.Many marine sponges are hosts to dense and phylogenetically diverse microbial communities that are located in the extracellular matrix of the animal. The candidate phylum Poribacteria is a predominant member of the sponge microbiome and its representatives are nearly exclusively found in sponges. Here we used single-cell genomics to obtain comprehensive insights into the metabolic potential of individual poribacterial cells representing three distinct phylogenetic groups within Poribacteria. Genome sizes were up to 5.4 Mbp and genome coverage was as high as 98.5%. Common features of the poribacterial genomes indicated that heterotrophy is likely to be of importance for this bacterial candidate phylum. Carbohydrate-active enzyme database screening and further detailed analysis of carbohydrate metabolism suggested the ability to degrade diverse carbohydrate sources likely originating from seawater and from the host itself. The presence of uronic acid degradation pathways as well as several specific sulfatases provides strong support that Poribacteria degrade glycosaminoglycan chains of proteoglycans, which are important components of the sponge host matrix. Dominant glycoside hydrolase families further suggest degradation of other glycoproteins in the host matrix. We therefore propose that Poribacteria are well adapted to an existence in the sponge extracellular matrix. Poribacteria may be viewed as efficient scavengers and recyclers of a particular suite of carbon compounds that are unique to sponges as microbial ecosystems

    Host microbiota can facilitate pathogen infection

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