Intestinal bacteria may be an important piece in the jigsaw puzzle of multiple sclerosis uni_copenhagen
] and individuals phenotyped at Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen . The CMBR cohort was recruited from urban areas in Denmark by advertisement in local newspapers, social media, and other online resources from November 2013 to November 2014.
Blood was drawn in the morning after an overnight fast from a cubital vein into an EDTA tube, centrifuged to separate plasma and cells, and immediately stored at −80°C until analysis. Collected plasma samples were further used for metabolic markers and cytokine measurement . Stools were collected according to International Human Microbiome Standards guidelines in kits by multiple sclerosis cases and HC at home and immediately stored at −20 °C until they were transported on dry ice and frozen 4–24 h later at −80°C in plastic tubes at the biobanks of Novo Nordisk Foundation Center for Metabolic Research or Glostrup Hospital. Stools were further subjected to shotgun sequencing , bacterial cell counting , and fecal water estimation .
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Statistical and machine learning methods for spatially resolved transcriptomics data analysis - Genome BiologyThe recent advancement in spatial transcriptomics technology has enabled multiplexed profiling of cellular transcriptomes and spatial locations. As the capacity and efficiency of the experimental technologies continue to improve, there is an emerging need for the development of analytical approaches. Furthermore, with the continuous evolution of sequencing protocols, the underlying assumptions of current analytical methods need to be re-evaluated and adjusted to harness the increasing data complexity. To motivate and aid future model development, we herein review the recent development of statistical and machine learning methods in spatial transcriptomics, summarize useful resources, and highlight the challenges and opportunities ahead.
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Pharmacies are running out of cold and flu medicine as winter bugs continue to spread🔴 Throat lozenges, cough mixtures and some pain killers are in short supply, according to the Association of Independent Multiple Pharmacies
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Selfless St Annes hospital entertainer pleads for new piano for elderly ward“The music gives patients a lot of pleasure and it is good medicine for them”
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Genetic regulation of serum IgA levels and susceptibility to common immune, infectious, kidney, and cardio-metabolic traits - Nature CommunicationsImmunoglobulin A protects against infectious disease and contributes to autoimmune and inflammatory disorders. Here, the authors perform a genome-wide association study for serum IgA levels, identifying 20 genome-wide significant loci, providing new insights into the genetic regulation of IgA levels.
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Genome-Wide Pleiotropy Study Identifies Association of PDGFB with Age-Related Macular Degeneration and COVID-19 Infection OutcomesAge-related macular degeneration (AMD) has been implicated as a risk factor for severe consequences from COVID-19. We evaluated the genetic architecture shared between AMD and COVID-19 (critical illness, hospitalization, and infections) using analyses of genetic correlations and pleiotropy (i.e., cross-phenotype meta-analysis) of AMD (n=33,976) and COVID-19 (n ≥ 1,388,342) and subsequent analyses including expression quantitative trait locus (eQTL), differential gene expression, and Mendelian randomization (MR). We observed a significant genetic correlation between AMD and COVID-19 infection (rG=0.10, p=0.02) and identified novel genome-wide significant associations near PDGFB (best SNP: rs130651; p=2.4 × 10−8) in the pleiotropy analysis of the two diseases. The disease-risk allele of rs130651 was significantly associated with increased gene expression levels of PDGFB in multiple tissues (best eQTL p=1.8 × 10−11 in whole blood) and immune cells (best eQTL p=7.1 × 10−20 in T-cells). PDGFB expression was observed to be higher in AMD cases than AMD controls {fold change (FC)=1.02; p=0.067}, as well as in the peak COVID-19 symptom stage (11–20 days after the symptom onset) compared to early/progressive stage (0–10 days) among COVID-19 patients over age 40 (FC=2.17; p=0.03) and age 50 (FC=2.15; p=0.04). Our MR analysis found that the liability of AMD risk derived from complement system dysfunction {OR (95% CI); hospitalization=1.02 (1.01–1.03), infection=1.02 (1.01–1.03) and increased levels of serum cytokine PDGF-BB {β (95% CI); critical illness=0.07 (0.02–0.11)} are significantly associated with COVID-19 outcomes. Our study demonstrated that the liability of AMD is associated with an increased risk of COVID-19, and PDGFB may be responsible for the severe COVID-19 outcomes among AMD patients.
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Adiposity and risk of prostate cancer death: a prospective analysis in UK Biobank and meta-analysis of published studies - BMC MedicineBackground The association of adiposity with prostate cancer specific mortality remains unclear. We examined how adiposity relates to fatal prostate cancer and described the cross-sectional associations of commonly used adiposity measurements with adiposity estimated by imaging in UK Biobank. We also conducted a dose-response meta-analysis to integrate the new data with existing prospective evidence. Methods 218,237 men from UK Biobank who were free from cancer at baseline were included. Body mass index (BMI), total body fat percentage (using bioimpedance), waist circumference (WC) and waist-to-hip ratio (WHR) were collected at recruitment. Risk of dying from prostate cancer (primary cause) by the different adiposity measurements was estimated using multivariable-adjusted Cox proportional hazards models. Results from this and other prospective cohort studies were combined in a dose-response meta-analysis. Results In UK Biobank, 661 men died from prostate cancer over a mean follow-up of 11.6 years. In the subsample of participants with magnetic resonance imaging and dual-energy X-ray absorptiometry, BMI, body fat percentage and WC were strongly associated with imaging estimates of total and central adiposity (e.g. visceral fat, trunk fat). The hazard ratios (HR) for prostate cancer death were 1.07 (95% confidence interval = 0.97–1.17) per 5 kg/m2 higher BMI, 1.00 (0.94–1.08) per 5% increase in total body fat percentage, 1.06 (0.99–1.14) per 10 cm increase in WC and 1.07 (1.01–1.14) per 0.05 increase in WHR. Our meta-analyses of prospective studies included 19,633 prostate cancer deaths for BMI, 670 for body fat percentage, 3181 for WC and 1639 for WHR, and the combined HRs for dying from prostate cancer for the increments above were 1.10 (1.07–1.12), 1.03 (0.96–1.11), 1.07 (1.03–1.11), and 1.06 (1.01–1.10), respectively. Conclusion Overall, we found that men with higher total and central adiposity had similarly higher risks of prostate cancer death, which may be biol
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