20 results on '"Forslund S"'
Search Results
2. P020 Characterisation of mucus in patients with Crohn’s disease
- Author
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Kramer, C, primary, Ziegler, J, additional, Alzain, N, additional, Schroeter, S, additional, Almalla, A, additional, Elomaa, L, additional, Addante, A, additional, Kuppe, A, additional, Fentker, K, additional, Nazat Martinez Medina, J, additional, Jarquin-Diaz, V H, additional, Rulff, H, additional, Gradzielski, M, additional, Forslund, S, additional, Mertins, P, additional, Mall, M, additional, Weinhart, M, additional, Glauben, R, additional, and Siegmund, B, additional
- Published
- 2023
- Full Text
- View/download PDF
3. AB0114 IMPROVEMENT OF GUT MICROBIOTA DYSBIOSIS IN PATIENTS WITH AXIAL SPONDYLOARTHRITIS AFTER ONE YEAR OF BIOLOGICAL TREATMENT
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Rios Rodriguez, V., primary, Essex, M., additional, Rademacher, J., additional, Torgutalp, M., additional, Proft, F., additional, Löber, U., additional, Marko, L., additional, Poddubnyy, D., additional, and Forslund, S. K., additional
- Published
- 2022
- Full Text
- View/download PDF
4. Shared and distinct gut microbiome signatures in patients with axial spondyloarthritis and its related immune-mediated diseases
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Rios Rodriguez, V, Essex, M, Rademacher, J, Proft, F, Löber, U, Marko, L, Pleyer, U, Siegmund, B, Poddubnyy, D, and Forslund, S
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ddc: 610 - Published
- 2021
5. OP0031 SHARED AND DISTINCT GUT MICROBIOME SIGNATURES IN PATIENTS WITH AXIAL SPONDYLOARTHRITIS AND ITS RELATED IMMUNE-MEDIATED DISEASES
- Author
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Rios Rodriguez, V., primary, Essex, M., additional, Rademacher, J., additional, Proft, F., additional, Löber, U., additional, Marko, L., additional, Pleyer, U., additional, Siegmund, B., additional, Poddubnyy, D., additional, and Forslund, S., additional
- Published
- 2021
- Full Text
- View/download PDF
6. Reporting guidelines for human microbiome research: the STORMS checklist
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Mirzayi, C, Renson, A, Furlanello, C, Sansone, SA, Zohra, F, Elsafoury, S, Geistlinger, L, Kasselman, LJ, Eckenrode, K, van de Wijgert, J, Loughman, Amy, Marques, FZ, MacIntyre, DA, Arumugam, M, Azhar, R, Beghini, F, Bergstrom, K, Bhatt, A, Bisanz, JE, Braun, J, Bravo, HC, Buck, GA, Bushman, F, Casero, D, Clarke, G, Collado, MC, Cotter, PD, Cryan, JF, Demmer, RT, Devkota, S, Elinav, E, Escobar, JS, Fettweis, J, Finn, RD, Fodor, AA, Forslund, S, Franke, A, Gilbert, J, Grice, E, Haibe-Kains, B, Handley, S, Herd, P, Holmes, S, Jacobs, JP, Karstens, L, Knight, R, Knights, D, Koren, O, Kwon, DS, Langille, M, Lindsay, B, McGovern, D, McHardy, AC, McWeeney, S, Mueller, NT, Nezi, L, Olm, M, Palm, N, Pasolli, E, Raes, J, Redinbo, MR, Rühlemann, M, Balfour Sartor, R, Schloss, PD, Schriml, L, Segal, E, Shardell, M, Sharpton, T, Smirnova, E, Sokol, H, Sonnenburg, JL, Srinivasan, S, Thingholm, LB, Turnbaugh, PJ, Upadhyay, V, Walls, RL, Wilmes, P, Yamada, T, Zeller, G, Zhang, M, Zhao, N, Zhao, L, Bao, W, Culhane, A, Devanarayan, V, Dopazo, J, Fan, X, Fischer, M, Jones, W, Kusko, R, Mason, CE, Mercer, TR, Scherer, A, Shi, L, Thakkar, S, Tong, W, Wolfinger, R, Hunter, C, Mirzayi, C, Renson, A, Furlanello, C, Sansone, SA, Zohra, F, Elsafoury, S, Geistlinger, L, Kasselman, LJ, Eckenrode, K, van de Wijgert, J, Loughman, Amy, Marques, FZ, MacIntyre, DA, Arumugam, M, Azhar, R, Beghini, F, Bergstrom, K, Bhatt, A, Bisanz, JE, Braun, J, Bravo, HC, Buck, GA, Bushman, F, Casero, D, Clarke, G, Collado, MC, Cotter, PD, Cryan, JF, Demmer, RT, Devkota, S, Elinav, E, Escobar, JS, Fettweis, J, Finn, RD, Fodor, AA, Forslund, S, Franke, A, Gilbert, J, Grice, E, Haibe-Kains, B, Handley, S, Herd, P, Holmes, S, Jacobs, JP, Karstens, L, Knight, R, Knights, D, Koren, O, Kwon, DS, Langille, M, Lindsay, B, McGovern, D, McHardy, AC, McWeeney, S, Mueller, NT, Nezi, L, Olm, M, Palm, N, Pasolli, E, Raes, J, Redinbo, MR, Rühlemann, M, Balfour Sartor, R, Schloss, PD, Schriml, L, Segal, E, Shardell, M, Sharpton, T, Smirnova, E, Sokol, H, Sonnenburg, JL, Srinivasan, S, Thingholm, LB, Turnbaugh, PJ, Upadhyay, V, Walls, RL, Wilmes, P, Yamada, T, Zeller, G, Zhang, M, Zhao, N, Zhao, L, Bao, W, Culhane, A, Devanarayan, V, Dopazo, J, Fan, X, Fischer, M, Jones, W, Kusko, R, Mason, CE, Mercer, TR, Scherer, A, Shi, L, Thakkar, S, Tong, W, Wolfinger, R, and Hunter, C
- Published
- 2021
7. Imidazole propionate is increased in diabetes and associated with dietary patterns and altered microbial ecology (vol 11, 5881, 2020)
- Author
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Molinaro, A, Lassen, PB, Henricsson, M, Wu, H, Adriouch, S, Belda, E, Chakaroun, R, Nielsen, T, Bergh, P-O, Rouault, C, Andre, S, Marquet, F, Andreelli, F, Salem, J-E, Assmann, K, Bastard, J-P, Forslund, S, Le Chatelier, E, Falony, G, Pons, N, Prifti, E, Quinquis, B, Roume, H, Vieira-Silva, S, Hansen, TH, Pedersen, HK, Lewinter, C, Sonderskov, NB, Kober, L, Vestergaard, H, Hansen, T, Zucker, J-D, Galan, P, Dumas, M-E, Raes, J, Oppert, J-M, Letunic, I, Nielsen, J, Bork, P, Ehrlich, SD, Stumvoll, M, Pedersen, O, Aron-Wisnewsky, J, Clement, K, Backhed, F, and Commission of the European Communities
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Multidisciplinary Sciences ,MetaCardis Consortium ,Science & Technology ,Science & Technology - Other Topics - Published
- 2020
8. The gut microbiome is associated with behavioural task in honey bees
- Author
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Jones, Julia, Fruciano, C., Marchant, J., Hildebrand, F., Forslund, S., Bork, P., Engel, P., Hughes, W. O. H., Jones, Julia, Fruciano, C., Marchant, J., Hildebrand, F., Forslund, S., Bork, P., Engel, P., and Hughes, W. O. H.
- Abstract
The gut microbiome is recognised as playing an integral role in the health and ecology of a wide variety of animal taxa. However, the relationship between social behavioural traits and the microbial community has received little attention. Honey bees are highly social and the workers perform different behavioural tasks in the colony that cause them to be exposed to different local environments. Here we examined whether the gut microbial community composition of worker honey bees is associated with the behavioural tasks they perform, and therefore also the local environment they are exposed to. We set up five observation hives, in which all workers were matched in age and observed the behaviour of marked bees in each colony over 4 days. The gut bacterial communities of bees seen performing predominantly foraging or predominantly in nest tasks were then characterised and compared based on amplicon sequencing of the 16S rRNA gene. Our results show that some core members of the unique honey bee gut bacterial community are represented in different relative abundances in bees performing different behavioural tasks. The differentially represented bacterial taxa include some thought to be important in carbohydrate metabolism and transport, and also linked to bee health. The results suggest an influence of task-related local environment exposure and diet on the honey bee gut microbial community and identify focal core taxa for further functional analyses.
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- 2018
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9. Identification and characterization of human observational studies in nutritional epidemiology on gut microbiomics for joint data analysis
- Author
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Pinart, Mariona, Nimptsch, Katharina, Forslund, Sofia, Schlicht, Kristina, Gueimonde, Miguel, Brigidi, Patrizia, Turroni, Silvia, Ahrens, Wolfgang, Hebestreit, Antje, Wolters, Maike, Dötsch, Andreas, Nöthlings, Ute, Oluwagbemigun, Kolade, Cuadrat, Rafael, Schulze, Matthias, Standl, Marie, Schloter, Michael, De Angelis, Maria, Iozzo, Patricia, Guzzardi, Maria Angela, Vlaemynck, Geertrui, Penders, John, Jonkers, Daisy, Stemmer, Maya, Chiesa, Giulia, Cavalieri, Duccio, De Filippo, Carlotta, Ercolini, Danilo, De Filippis, Francesca, Ribet, David, Achamrah, Najate, Tavolacci, Marie-Pierre, Déchelotte, Pierre, Bouwman, Jildau, Laudes, Matthias, Pischon, Tobias, Pinart M., Nimptsch K., Forslund S.K., Schlicht K., Gueimonde M., Brigidi P., Turroni S., Ahrens W., Hebestreit A., Wolters M., Dotsch A., Nothlings U., Oluwagbemigun K., Cuadrat R.R.C., Schulze M.B., Standl M., Schloter M., De Angelis M., Iozzo P., Guzzardi M.A., Vlaemynck G., Penders J., Jonkers D.M.A.E., Stemmer M., Chiesa G., Cavalieri D., De Filippo C., Ercolini D., De Filippis F., Ribet D., Achamrah N., Tavolacci M.-P., Dechelotte P., Bouwman J., Laudes M., Pischon T., Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), 13125 Berlin, Germany, Experimental and Clinical Research Center, A Cooperation of Charité-Universitätsmedizin Berlin and Max Delbrück Center for Molecular Medicine, Lindenberger Weg 80, 13125 Berlin, Germany, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, 10117 Berlin, Germany, Host-Microbiome Factors in Cardiovascular Disease Lab, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, 13125 Berlin, Germany, German Centre for Cardiovascular Research (DZHK), Partner Site Berlin, 10785 Berlin, Germany, Berlin Institute of Health (BIH), 10178 Berlin, Germany, Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany, Institute of Diabetes and Clinical Metabolic Research, University of Kiel, 24105 Kiel, Germany, Department of Microbiology and Biochemistry of Dairy Products, IPLA-CSIC, 33300 Villaviciosa, Spain, Diet, Microbiota and Health Group, Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), 33011 Oviedo, Spain, Department of Medical and Surgical Sciences, University of Bologna, Via Massarenti 9, 40138 Bologna, Italy, Department of Pharmacy and Biotechnology, University of Bologna, Via Belmeloro 6, 40126 Bologna, Italy, Leibniz Institute for Prevention Research and Epidemiology-BIPS, 28359 Bremen, Germany, Institute of Statistics, Bremen University, 28359 Bremen, Germany, Department of Physiology and Biochemistry of Nutrition, Max Rubner-Institut (MRI)-Federal Research Institute of Nutrition and Food, 76131 Karlsruhe, Germany, Nutritional Epidemiology Unit, Institute of Nutrition and Food Sciences, University of Bonn, 53115 Bonn, Germany, Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, 14558 Nuthetal, Germany, Institute of Nutritional Science, University of Potsdam, 14558 Potsdam, Germany, German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany, Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany, Research Unit for Comparative Microbiome Analysis, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany, Department of Soil, Plant and Food Sciences, University of Bari Aldo Moro, 70126 Bari, Italy, Institute of Clinical Physiology, National Research Council, Via Moruzzi 1, 56124 Pisa, Italy, Department Technology and Food, Flanders Research Institute for Agriculture, Fisheries and Food, 9090 Melle, Belgium, Department of Medical Microbiology, School of Nutrition and Translational Research in Metabolism (NUTRIM) and Care and Public Health Research Institute (CAPHRI), Maastricht University Medical Center, 6200 MD Maastricht, The Netherlands, Department of Internal Medicine, Division Gastroenterology-Hepatology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Center, 6200 MD Maastricht, The Netherlands, Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer-Sheva P.O. Box 653, Israel, Department of Pharmacological and Biomolecular Sciences, Università degli Studi di Milano, 20133 Milan, Italy, Department of Biology, University of Florence, Via Madonna del Piano 6, 50019 Florence, Italy, Institute of Agricultural Biology and Biotechnology National Research Council, Via Moruzzi 1, 56124 Pisa, Italy, Department of Agricultural Sciences, University of Naples Federico II, 80055 Portici, Italy, Task Force on Microbiome Studies, University of Naples Federico II, 80134 Naples, Italy, Nutrition, inflammation et dysfonctionnement de l'axe intestin-cerveau (ADEN), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institute for Research and Innovation in Biomedicine (IRIB), Normandie Université (NU)-Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), UNIROUEN - UFR Santé (UNIROUEN UFR Santé), Normandie Université (NU)-Normandie Université (NU), Service de nutrition [CHU Rouen], Normandie Université (NU)-Normandie Université (NU)-CHU Rouen, Normandie Université (NU), Centre d'Investigation Clinique [CHU Rouen] (CIC Rouen), Hôpital Charles Nicolle [Rouen]-CHU Rouen, Normandie Université (NU)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Microbiology and Systems Biology Group, TNO, Utrechtseweg 48, 3704 HE Zeist, The Netherlands, Biobank Technology Platform, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), 13125 Berlin, Germany, Biobank Core Facility, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, 10178 Berlin, Germany, European Commission, Fonds de la Recherche Scientifique (Fédération Wallonie-Bruxelles), Research Foundation - Flanders, Institut National de la Santé et de la Recherche Médicale (France), Federal Ministry of Education and Research (Germany), Federal Ministry of Food and Agriculture (Germany), Ministero dell'Istruzione, dell'Università e della Ricerca, Ministero delle Politiche Agricole Alimentari e Forestali, National Institutes of Health (US), Ministero della Salute, Instituto de Salud Carlos III, Netherlands Organisation for Health Research and Development, Austrian Research Promotion Agency, Federal Ministry of Education, Science and Research (Austria), Ministry of Science, Technology and Space (Israel), Swedish Research Council for Sustainable Development, German Research Foundation, RS: CAPHRI - R4 - Health Inequities and Societal Participation, Med Microbiol, Infect Dis & Infect Prev, RS: NUTRIM - R2 - Liver and digestive health, Interne Geneeskunde, Pinart, M., Nimptsch, K., Forslund, S. K., Schlicht, K., Gueimonde, M., Brigidi, P., Turroni, S., Ahrens, W., Hebestreit, A., Wolters, M., Dotsch, A., Nothlings, U., Oluwagbemigun, K., Cuadrat, R. R. C., Schulze, M. B., Standl, M., Schloter, M., De Angelis, M., Iozzo, P., Guzzardi, M. A., Vlaemynck, G., Penders, J., Jonkers, D. M. A. E., Stemmer, M., Chiesa, G., Cavalieri, D., De Filippo, C., Ercolini, D., De Filippis, F., Ribet, D., Achamrah, N., Tavolacci, M. -P., Dechelotte, P., Bouwman, J., Laudes, M., Pischon, T., Humboldt-Universität zu Berlin, and CHU Rouen
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Nutritional Sciences ,Metabolome ,Metadata ,Data sharing ,Observational studies ,Data integration ,Dietary intake ,Microbiome ,Diet Surveys ,Article ,Eating ,Nutritional Science ,AGE ,Humans ,TX341-641 ,observational studies ,Nutrition. Foods and food supply ,Information Dissemination ,Nutrition Survey ,Nutrition Surveys ,Observational studie ,Gastrointestinal Microbiome ,Diet Survey ,Europe ,Observational Studies as Topic ,Cardiovascular and Metabolic Diseases ,Data Integration ,Data Sharing ,Dietary Intake ,Observational Studies ,Technology Platforms ,[SDV.AEN]Life Sciences [q-bio]/Food and Nutrition ,Human - Abstract
In any research field, data access and data integration are major challenges that even large, well-established consortia face. Although data sharing initiatives are increasing, joint data analyses on nutrition and microbiomics in health and disease are still scarce. We aimed to identify observational studies with data on nutrition and gut microbiome composition from the Intestinal Microbiomics (INTIMIC) Knowledge Platform following the findable, accessible, interoperable, and reusable (FAIR) principles. An adapted template from the European Nutritional Phenotype Assessment and Data Sharing Initiative (ENPADASI) consortium was used to collect microbiome-specific information and other related factors. In total, 23 studies (17 longitudinal and 6 cross-sectional) were identified from Italy (7), Germany (6), Netherlands (3), Spain (2), Belgium (1), and France (1) or multiple countries (3). Of these, 21 studies collected information on both dietary intake (24 h dietary recall, food frequency questionnaire (FFQ), or Food Records) and gut microbiome. All studies collected stool samples. The most often used sequencing platform was Illumina MiSeq, and the preferred hypervariable regions of the 16S rRNA gene were V3–V4 or V4. The combination of datasets will allow for sufficiently powered investigations to increase the knowledge and understanding of the relationship between food and gut microbiome in health and disease., This research was supported by the Joint Action “European Joint Programming Initiative “A Healthy Diet for a Healthy Life” (JPI HDHL)”and the respective national/regional funding organisations: Fund for Scientific Research (FRS—FNRS, Belgium); Research Foundation—Flanders (FWO, Belgium); INSERM Institut National de la Santé et de la Recherche Médicale (France); Federal Ministry of Education and Research (BMBF, FKZ 01EA1906B, 01EA1906D); Federal Ministry of Food and Agriculture (BMEL) through the Federal Office for Agriculture and Food (BLE, Germany, grant number 2819ERA10F); Ministry of Education, University and Research (MIUR), Ministry of agricultural, food and forestry policies (MiPAAF), National Institute of Health (ISS) on behalf of Ministry of Health (Italy); National Institute of Health Carlos III (Spain); The Netherlands Organisation for Health Research and Development (ZonMw, The Netherlands), Austrian Research Promotion Agency (FFG) on behalf of the Austrian Federal Ministry for Education, Science and Research (BMBWF), Ministry of Science and Technology (Israel), Formas (Sweden). This research was also supported by the German Research Foundation (DFG, KFO339: “food@”).
- Published
- 2021
10. Tolerance induction through early feeding to prevent food allergy in infants and children with sensitization against food allergens (TIFFANI): rationale, study design, and methods of a randomized controlled trial.
- Author
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Kalb B, Meixner L, Heller S, Dölle-Bierke S, Roll S, Tissen-Diabaté T, Lau S, Forslund S, Marenholz I, Lee YA, Thiel A, Babina M, Scheffel J, Worm M, and Beyer K
- Subjects
- Child, Infant, Cattle, Humans, Female, Animals, Milk adverse effects, Allergens adverse effects, Immune Tolerance, Chickens, Food Hypersensitivity diagnosis, Food Hypersensitivity prevention & control
- Abstract
Background: Children with sensitization against foods have to be orally food-challenged before eating these foods for the first time. However, the waiting time for an oral food challenge (OFC) in Germany is about 3-6 months. In contrast, there are hints that an early introduction of allergenic foods might be protective regarding the development of food allergy. The aim of this clinical trial is therefore to investigate, whether an introduction and regular consumption of small amounts of food allergens is safe and will result in an increase of tolerance in children with sensitization against food allergens with unknown clinical relevance., Methods: In this randomized, placebo-controlled, double-blind, single-center trial, 138 children (8 months to 4 years of age) sensitized to the target allergen(s) hen's egg, cow's milk, peanuts, and/or hazelnuts with unknown clinical relevance will be randomized in a 1:1 ratio to either an active or a placebo group, daily receiving a rusk-like biscuit powder with or without the target allergen(s) for 3-6 months until an OFC will be performed in routine diagnostics. The primary endpoint is an IgE-mediated food allergy to the primary target allergen, after the interventional period., Discussion: Children with sensitization against food allergens with unknown clinical relevance often have to avoid the corresponding foods for several months until an OFC is performed. Therefore, the "window of opportunity" for an early preventive introduction of allergenic foods might be missed. This trial will assess whether an introduction of small allergen amounts will favor tolerance development in these children., Trial Registration: German Clinical Trials Register DRKS00032769. Registered on 02 October 2023., (© 2024. The Author(s).)
- Published
- 2024
- Full Text
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11. The effect of probiotic and synbiotic supplementation on lipid parameters among patients with cardiometabolic risk factors: a systematic review and meta-analysis of clinical trials.
- Author
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Ghorbani Z, Kazemi A, U P Bartolomaeus T, Martami F, Noormohammadi M, Salari A, Löber U, Balou HA, K Forslund S, and Mahdavi-Roshan M
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- Humans, Lipids, Triglycerides, Synbiotics adverse effects, Probiotics adverse effects, Cardiovascular Diseases diagnosis, Cardiovascular Diseases prevention & control
- Abstract
Although the available evidence emphasizes the beneficial effects of probiotics in normalizing various cardiometabolic markers, there is still substantial uncertainty in this regard. Thus, we set out to determine the effect sizes of probiotics on blood lipid parameters more coherently. A systematic literature search of the Medline (PubMed) and Scopus databases was conducted from inception to 12 February 2021, applying both MeSH terms and free text terms to find the relevant randomized controlled trials (RCTs). The meta-analysis was conducted based on a random-effect model to calculate the mean effect sizes demonstrated as weighted mean differences (WMDs) and the 95% confidence intervals (95% CIs). To explore the heterogeneity, the Cochrane χ2 test, and analysis of Galbraith plots were performed. Meta-analysis of data from 40 RCTs (n = 2795) indicated a significant decrease in serum/plasma triglyceride [WMD (95% CI) = -12.26 (-17.11 to -7.41) mg/dL; P-value <0.001; I2 (%) = 29.9; P heterogeneity = 0.034], total cholesterol (with high heterogeneity) (WMD (95% CI) = -8.43 (-11.90 to -4.95) mg/dL; P-value <0.001; I2 (%) = 56.8; P heterogeneity < 0.001), LDL-C [WMD (95% CI) = -5.08 (-7.61, -2.56) mg/dL; P-value <0.001; I2 (%) = 42.7; P heterogeneity = 0.002], and HDL-C (with high heterogeneity) (WMD (95% CI) = 1.14 (0.23, 2.05) mg/dL; P-value = 0.014; I2 (%) = 59.8; P heterogeneity < 0.001) following receiving probiotic/synbiotic supplements. Collectively, the current preliminary evidence supports the effectiveness of probiotics/synbiotics in improving dyslipidaemia and various lipid parameters more prominently among subjects with hyperlipidaemia, diabetes, and metabolic syndrome. However, large and well conducted RCTs are required to provide further convincing support for these results., Competing Interests: Conflict of interest:The authors declare that they have no conflict of interest., (© The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)
- Published
- 2023
- Full Text
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12. Impairment of gut microbial biotin metabolism and host biotin status in severe obesity: effect of biotin and prebiotic supplementation on improved metabolism.
- Author
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Belda E, Voland L, Tremaroli V, Falony G, Adriouch S, Assmann KE, Prifti E, Aron-Wisnewsky J, Debédat J, Le Roy T, Nielsen T, Amouyal C, André S, Andreelli F, Blüher M, Chakaroun R, Chilloux J, Coelho LP, Dao MC, Das P, Fellahi S, Forslund S, Galleron N, Hansen TH, Holmes B, Ji B, Krogh Pedersen H, Le P, Le Chatelier E, Lewinter C, Mannerås-Holm L, Marquet F, Myridakis A, Pelloux V, Pons N, Quinquis B, Rouault C, Roume H, Salem JE, Sokolovska N, Søndertoft NB, Touch S, Vieira-Silva S, Galan P, Holst J, Gøtze JP, Køber L, Vestergaard H, Hansen T, Hercberg S, Oppert JM, Nielsen J, Letunic I, Dumas ME, Stumvoll M, Pedersen OB, Bork P, Ehrlich SD, Zucker JD, Bäckhed F, Raes J, and Clément K
- Subjects
- Humans, Mice, Animals, Prebiotics, Biotin pharmacology, Mice, Inbred C57BL, Obesity metabolism, Inflammation, Gastrointestinal Microbiome, Obesity, Morbid surgery, Diabetes Mellitus, Type 2, Vitamin B Complex pharmacology
- Abstract
Objectives: Gut microbiota is a key component in obesity and type 2 diabetes, yet mechanisms and metabolites central to this interaction remain unclear. We examined the human gut microbiome's functional composition in healthy metabolic state and the most severe states of obesity and type 2 diabetes within the MetaCardis cohort. We focused on the role of B vitamins and B7/B8 biotin for regulation of host metabolic state, as these vitamins influence both microbial function and host metabolism and inflammation., Design: We performed metagenomic analyses in 1545 subjects from the MetaCardis cohorts and different murine experiments, including germ-free and antibiotic treated animals, faecal microbiota transfer, bariatric surgery and supplementation with biotin and prebiotics in mice., Results: Severe obesity is associated with an absolute deficiency in bacterial biotin producers and transporters, whose abundances correlate with host metabolic and inflammatory phenotypes. We found suboptimal circulating biotin levels in severe obesity and altered expression of biotin-associated genes in human adipose tissue. In mice, the absence or depletion of gut microbiota by antibiotics confirmed the microbial contribution to host biotin levels. Bariatric surgery, which improves metabolism and inflammation, associates with increased bacterial biotin producers and improved host systemic biotin in humans and mice. Finally, supplementing high-fat diet-fed mice with fructo-oligosaccharides and biotin improves not only the microbiome diversity, but also the potential of bacterial production of biotin and B vitamins, while limiting weight gain and glycaemic deterioration., Conclusion: Strategies combining biotin and prebiotic supplementation could help prevent the deterioration of metabolic states in severe obesity., Trial Registration Number: NCT02059538., Competing Interests: Competing interests: KC is a consultant for Danone Research, Ysopia and CONFO therapeutics for work not associated with this study. KC held a collaborative research contract with Danone Research in the context of MetaCardis project. FB is a shareholder of Implexion pharma AB. MB received lecture and/or consultancy fees from AstraZeneca, Boehringer-Ingelheim, Lilly, Novo Nordisk, Novartis and Sanofi., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
- Published
- 2022
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13. Author Correction: Elevated aldosterone and blood pressure in a mouse model of familial hyperaldosteronism with ClC-2 mutation.
- Author
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Schewe J, Seidel E, Forslund S, Marko L, Peters J, Muller DN, Fahlke C, Stölting G, and Scholl U
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- 2022
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14. Reporting guidelines for human microbiome research: the STORMS checklist.
- Author
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Mirzayi C, Renson A, Zohra F, Elsafoury S, Geistlinger L, Kasselman LJ, Eckenrode K, van de Wijgert J, Loughman A, Marques FZ, MacIntyre DA, Arumugam M, Azhar R, Beghini F, Bergstrom K, Bhatt A, Bisanz JE, Braun J, Bravo HC, Buck GA, Bushman F, Casero D, Clarke G, Collado MC, Cotter PD, Cryan JF, Demmer RT, Devkota S, Elinav E, Escobar JS, Fettweis J, Finn RD, Fodor AA, Forslund S, Franke A, Furlanello C, Gilbert J, Grice E, Haibe-Kains B, Handley S, Herd P, Holmes S, Jacobs JP, Karstens L, Knight R, Knights D, Koren O, Kwon DS, Langille M, Lindsay B, McGovern D, McHardy AC, McWeeney S, Mueller NT, Nezi L, Olm M, Palm N, Pasolli E, Raes J, Redinbo MR, Rühlemann M, Balfour Sartor R, Schloss PD, Schriml L, Segal E, Shardell M, Sharpton T, Smirnova E, Sokol H, Sonnenburg JL, Srinivasan S, Thingholm LB, Turnbaugh PJ, Upadhyay V, Walls RL, Wilmes P, Yamada T, Zeller G, Zhang M, Zhao N, Zhao L, Bao W, Culhane A, Devanarayan V, Dopazo J, Fan X, Fischer M, Jones W, Kusko R, Mason CE, Mercer TR, Sansone SA, Scherer A, Shi L, Thakkar S, Tong W, Wolfinger R, Hunter C, Segata N, Huttenhower C, Dowd JB, Jones HE, and Waldron L
- Subjects
- Humans, Translational Science, Biomedical, Computational Biology methods, Dysbiosis microbiology, Microbiota physiology, Observational Studies as Topic methods, Research Design
- Abstract
The particularly interdisciplinary nature of human microbiome research makes the organization and reporting of results spanning epidemiology, biology, bioinformatics, translational medicine and statistics a challenge. Commonly used reporting guidelines for observational or genetic epidemiology studies lack key features specific to microbiome studies. Therefore, a multidisciplinary group of microbiome epidemiology researchers adapted guidelines for observational and genetic studies to culture-independent human microbiome studies, and also developed new reporting elements for laboratory, bioinformatics and statistical analyses tailored to microbiome studies. The resulting tool, called 'Strengthening The Organization and Reporting of Microbiome Studies' (STORMS), is composed of a 17-item checklist organized into six sections that correspond to the typical sections of a scientific publication, presented as an editable table for inclusion in supplementary materials. The STORMS checklist provides guidance for concise and complete reporting of microbiome studies that will facilitate manuscript preparation, peer review, and reader comprehension of publications and comparative analysis of published results., (© 2021. The Author(s), under exclusive licence to Springer Nature America, Inc.)
- Published
- 2021
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15. Human and preclinical studies of the host-gut microbiome co-metabolite hippurate as a marker and mediator of metabolic health.
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Brial F, Chilloux J, Nielsen T, Vieira-Silva S, Falony G, Andrikopoulos P, Olanipekun M, Hoyles L, Djouadi F, Neves AL, Rodriguez-Martinez A, Mouawad GI, Pons N, Forslund S, Le-Chatelier E, Le Lay A, Nicholson J, Hansen T, Hyötyläinen T, Clément K, Oresic M, Bork P, Ehrlich SD, Raes J, Pedersen OB, Gauguier D, and Dumas ME
- Subjects
- Animals, Biodiversity, Denmark, Female, Humans, Magnetic Resonance Spectroscopy, Male, Metabolome, Metagenomics, Mice, Middle Aged, Phenotype, Biomarkers metabolism, Gastrointestinal Microbiome, Hippurates metabolism
- Abstract
Objective: Gut microbial products are involved in regulation of host metabolism. In human and experimental studies, we explored the potential role of hippurate, a hepatic phase 2 conjugation product of microbial benzoate, as a marker and mediator of metabolic health., Design: In 271 middle-aged non-diabetic Danish individuals, who were stratified on habitual dietary intake, we applied
1 H-nuclear magnetic resonance (NMR) spectroscopy of urine samples and shotgun-sequencing-based metagenomics of the gut microbiome to explore links between the urine level of hippurate, measures of the gut microbiome, dietary fat and markers of metabolic health. In mechanistic experiments with chronic subcutaneous infusion of hippurate to high-fat-diet-fed obese mice, we tested for causality between hippurate and metabolic phenotypes., Results: In the human study, we showed that urine hippurate positively associates with microbial gene richness and functional modules for microbial benzoate biosynthetic pathways, one of which is less prevalent in the Bacteroides 2 enterotype compared with Ruminococcaceae or Prevotella enterotypes. Through dietary stratification, we identify a subset of study participants consuming a diet rich in saturated fat in which urine hippurate concentration, independently of gene richness, accounts for links with metabolic health. In the high-fat-fed mice experiments, we demonstrate causality through chronic infusion of hippurate (20 nmol/day) resulting in improved glucose tolerance and enhanced insulin secretion., Conclusion: Our human and experimental studies show that a high urine hippurate concentration is a general marker of metabolic health, and in the context of obesity induced by high-fat diets, hippurate contributes to metabolic improvements, highlighting its potential as a mediator of metabolic health., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.)- Published
- 2021
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16. Protein Intake, Metabolic Status and the Gut Microbiota in Different Ethnicities: Results from Two Independent Cohorts.
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Bel Lassen P, Attaye I, Adriouch S, Nicolaou M, Aron-Wisnewsky J, Nielsen T, Chakaroun R, Le Chatelier E, Forslund S, Belda E, Bork P, Bäckhed F, Stumvoll M, Pedersen O, Herrema H, Groen AK, Pinto-Sietsma SJ, Zwinderman AH, Nieuwdorp M, Clement K, and On Behalf Of Metacardis Consortium
- Subjects
- Adult, Aged, DNA, Bacterial genetics, Diet, Ethnicity, Feces microbiology, Female, Humans, Male, Middle Aged, Dietary Proteins pharmacology, Energy Metabolism, Gastrointestinal Microbiome drug effects, Racial Groups
- Abstract
Background: Protein intake has been associated with the development of pre-diabetes (pre-T2D) and type 2 diabetes (T2D). The gut microbiota has the capacity to produce harmful metabolites derived from dietary protein. Furthermore, both the gut microbiota composition and metabolic status (e.g., insulin resistance) can be modulated by diet and ethnicity. However, to date most studies have predominantly focused on carbohydrate and fiber intake with regards to metabolic status and gut microbiota composition., Objectives: To determine the associations between dietary protein intake, gut microbiota composition, and metabolic status in different ethnicities., Methods: Separate cross-sectional analysis of two European cohorts (MetaCardis, n = 1759; HELIUS, n = 1528) including controls, patients with pre-T2D, and patients with T2D of Caucasian/non-Caucasian origin with nutritional data obtained from Food Frequency Questionnaires and gut microbiota composition., Results: In both cohorts, animal (but not plant) protein intake was associated with pre-T2D status and T2D status after adjustment for confounders. There was no significant association between protein intake (total, animal, or plant) with either gut microbiota alpha diversity or beta diversity, regardless of ethnicity. At the species level, we identified taxonomical signatures associated with animal protein intake that overlapped in both cohorts with different abundances according to metabolic status and ethnicity., Conclusions: Animal protein intake is associated with pre-T2D and T2D status but not with gut microbiota beta or alpha diversity, regardless of ethnicity. Gut microbial taxonomical signatures were identified, which could function as potential modulators in the association between dietary protein intake and metabolic status.
- Published
- 2021
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17. Author Correction: Imidazole propionate is increased in diabetes and associated with dietary patterns and altered microbial ecology.
- Author
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Molinaro A, Bel Lassen P, Henricsson M, Wu H, Adriouch S, Belda E, Chakaroun R, Nielsen T, Bergh PO, Rouault C, André S, Marquet F, Andreelli F, Salem JE, Assmann K, Bastard JP, Forslund S, Le Chatelier E, Falony G, Pons N, Prifti E, Quinquis B, Roume H, Vieira-Silva S, Hansen TH, Pedersen HK, Lewinter C, Sønderskov NB, Køber L, Vestergaard H, Hansen T, Zucker JD, Galan P, Dumas ME, Raes J, Oppert JM, Letunic I, Nielsen J, Bork P, Ehrlich SD, Stumvoll M, Pedersen O, Aron-Wisnewsky J, Clément K, and Bäckhed F
- Published
- 2020
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18. Imidazole propionate is increased in diabetes and associated with dietary patterns and altered microbial ecology.
- Author
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Molinaro A, Bel Lassen P, Henricsson M, Wu H, Adriouch S, Belda E, Chakaroun R, Nielsen T, Bergh PO, Rouault C, André S, Marquet F, Andreelli F, Salem JE, Assmann K, Bastard JP, Forslund S, Le Chatelier E, Falony G, Pons N, Prifti E, Quinquis B, Roume H, Vieira-Silva S, Hansen TH, Pedersen HK, Lewinter C, Sønderskov NB, Køber L, Vestergaard H, Hansen T, Zucker JD, Galan P, Dumas ME, Raes J, Oppert JM, Letunic I, Nielsen J, Bork P, Ehrlich SD, Stumvoll M, Pedersen O, Aron-Wisnewsky J, Clément K, and Bäckhed F
- Subjects
- Adult, Aged, Bacteria classification, Bacteria genetics, Bacteria isolation & purification, Bacteria metabolism, Cohort Studies, Diabetes Mellitus, Type 2 blood, Diabetes Mellitus, Type 2 metabolism, Female, Histidine metabolism, Humans, Male, Middle Aged, Diabetes Mellitus, Type 2 microbiology, Gastrointestinal Microbiome, Imidazoles blood
- Abstract
Microbiota-host-diet interactions contribute to the development of metabolic diseases. Imidazole propionate is a novel microbially produced metabolite from histidine, which impairs glucose metabolism. Here, we show that subjects with prediabetes and diabetes in the MetaCardis cohort from three European countries have elevated serum imidazole propionate levels. Furthermore, imidazole propionate levels were increased in subjects with low bacterial gene richness and Bacteroides 2 enterotype, which have previously been associated with obesity. The Bacteroides 2 enterotype was also associated with increased abundance of the genes involved in imidazole propionate biosynthesis from dietary histidine. Since patients and controls did not differ in their histidine dietary intake, the elevated levels of imidazole propionate in type 2 diabetes likely reflects altered microbial metabolism of histidine, rather than histidine intake per se. Thus the microbiota may contribute to type 2 diabetes by generating imidazole propionate that can modulate host inflammation and metabolism.
- Published
- 2020
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19. Commentary on a combined approach to the problem of developing biomarkers for the prediction of spontaneous preterm labor that leads to preterm birth.
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Lamont RF, Richardson LS, Boniface JJ, Cobo T, Exner MM, Christensen IB, Forslund SK, Gaba A, Helmer H, Jørgensen JS, Khan RN, McElrath TF, Petro K, Rasmussen M, Singh R, Tribe RM, Vink JS, Vinter CA, Zhong N, and Menon R
- Subjects
- Female, Humans, Pregnancy, Biomarkers blood, Obstetric Labor, Premature blood
- Abstract
Introduction: Globally, preterm birth has replaced congenital malformation as the major cause of perinatal mortality and morbidity. The reduced rate of congenital malformation was not achieved through a single biophysical or biochemical marker at a specific gestational age, but rather through a combination of clinical, biophysical and biochemical markers at different gestational ages. Since the aetiology of spontaneous preterm birth is also multifactorial, it is unlikely that a single biomarker test, at a specific gestational age will emerge as the definitive predictive test., Methods: The Biomarkers Group of PREBIC, comprising clinicians, basic scientists and other experts in the field, with a particular interest in preterm birth have produced this commentary with short, medium and long-term aims: i) to alert clinicians to the advances that are being made in the prediction of spontaneous preterm birth; ii) to encourage clinicians and scientists to continue their efforts in this field, and not to be disheartened or nihilistic because of a perceived lack of progress and iii) to enable development of novel interventions that can reduce the mortality and morbidity associated with preterm birth., Results: Using language that we hope is clear to practising clinicians, we have identified 11 Sections in which there exists the potential, feasibility and capability of technologies for candidate biomarkers in the prediction of spontaneous preterm birth and how current limitations to this research might be circumvented., Discussion: The combination of biophysical, biochemical, immunological, microbiological, fetal cell, exosomal, or cell free RNA at different gestational ages, integrated as part of a multivariable predictor model may be necessary to advance our attempts to predict sPTL and PTB. This will require systems biological data using "omics" data and artificial intelligence/machine learning to manage the data appropriately. The ultimate goal is to reduce the mortality and morbidity associated with preterm birth., (Copyright © 2020 Elsevier Ltd. All rights reserved.)
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- 2020
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20. Elevated aldosterone and blood pressure in a mouse model of familial hyperaldosteronism with ClC-2 mutation.
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Schewe J, Seidel E, Forslund S, Marko L, Peters J, Muller DN, Fahlke C, Stölting G, and Scholl U
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- Adrenal Glands pathology, Amino Acid Sequence, Animals, Base Sequence, CLC-2 Chloride Channels, Chloride Channels chemistry, Chlorides urine, Cytochrome P-450 CYP11B2 metabolism, Disease Models, Animal, Female, Heterozygote, Hyperaldosteronism urine, Male, Mice, Inbred C57BL, Phenotype, Renin blood, Sodium urine, Aldosterone blood, Blood Pressure, Chloride Channels genetics, Hyperaldosteronism blood, Hyperaldosteronism physiopathology, Mutation genetics
- Abstract
Gain-of-function mutations in the chloride channel ClC-2 were recently described as a cause of familial hyperaldosteronism type II (FH-II). Here, we report the generation of a mouse model carrying a missense mutation homologous to the most common FH-II-associated CLCN2 mutation. In these Clcn2
R180Q/+ mice, adrenal morphology is normal, but Cyp11b2 expression and plasma aldosterone levels are elevated. Male Clcn2R180Q/+ mice have increased aldosterone:renin ratios as well as elevated blood pressure levels. The counterpart knockout model (Clcn2-/- ), in contrast, requires elevated renin levels to maintain normal aldosterone levels. Adrenal slices of Clcn2R180Q/+ mice show increased calcium oscillatory activity. Together, our work provides a knockin mouse model with a mild form of primary aldosteronism, likely due to increased chloride efflux and depolarization. We demonstrate a role of ClC-2 in normal aldosterone production beyond the observed pathophysiology.- Published
- 2019
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