{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T14:31:46Z","timestamp":1783521106499,"version":"3.55.0"},"reference-count":54,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2024,9,21]],"date-time":"2024-09-21T00:00:00Z","timestamp":1726876800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,9,21]],"date-time":"2024-09-21T00:00:00Z","timestamp":1726876800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Universit\u00e4t Augsburg"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Metabolomics"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Introduction\/objectives<\/jats:title>\n                <jats:p>Changes in the stool metabolome have been poorly studied in the metabolic syndrome (MetS). Moreover, few studies have explored the relationship of stool metabolites with circulating metabolites. Here, we investigated the associations between stool and blood metabolites, the MetS and systemic inflammation.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>We analyzed data from 1,370 participants of the KORA FF4 study (Germany). Metabolites were measured by Metabolon, Inc. (untargeted) in stool, and using the AbsoluteIDQ<jats:sup>\u00ae<\/jats:sup> p180 kit (targeted) in blood. Multiple linear regression models, adjusted for dietary pattern, age, sex, physical activity, smoking status and alcohol intake, were used to estimate the associations of metabolites with the MetS, its components and high-sensitivity C-reactive protein (hsCRP) levels. Partial correlation and Multi-Omics Factor Analysis (MOFA) were used to investigate the relationship between stool and blood metabolites.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>The MetS was significantly associated with 170 stool and 82 blood metabolites. The MetS components with the highest number of associations were triglyceride levels (stool) and HDL levels (blood). Additionally, 107 and 27 MetS-associated metabolites (in stool and blood, respectively) showed significant associations with hsCRP levels. We found low partial correlation coefficients between stool and blood metabolites. MOFA did not detect shared variation across the two datasets.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>The MetS, particularly dyslipidemia, is associated with multiple stool and blood metabolites that are also associated with systemic inflammation. Further studies are necessary to validate our findings and to characterize metabolic alterations in the MetS. Although our analyses point to weak correlations between stool and blood metabolites, additional studies using integrative approaches are warranted.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1007\/s11306-024-02166-3","type":"journal-article","created":{"date-parts":[[2024,9,21]],"date-time":"2024-09-21T21:01:29Z","timestamp":1726952489000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Stool and blood metabolomics in the metabolic syndrome: a cross-sectional study"],"prefix":"10.1007","volume":"20","author":[{"given":"Mariana","family":"Ponce-de-Leon","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rui","family":"Wang-Sattler","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Annette","family":"Peters","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wolfgang","family":"Rathmann","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Harald","family":"Grallert","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anna","family":"Artati","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cornelia","family":"Prehn","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jerzy","family":"Adamski","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christa","family":"Meisinger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jakob","family":"Linseisen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,9,21]]},"reference":[{"issue":"6","key":"2166_CR1","doi-asserted-by":"publisher","first-page":"1174","DOI":"10.1136\/GUTJNL-2020-323071","volume":"70","author":"A Agus","year":"2021","unstructured":"Agus, A., Cl\u00e9ment, K., & Sokol, H. (2021). Gut microbiota-derived metabolites as central regulators in metabolic disorders. Gut, 70(6), 1174\u20131182. https:\/\/doi.org\/10.1136\/GUTJNL-2020-323071","journal-title":"Gut"},{"issue":"5","key":"2166_CR3","doi-asserted-by":"publisher","first-page":"469","DOI":"10.1111\/j.1464-5491.2006.01858.x","volume":"23","author":"KGMM Alberti","year":"2006","unstructured":"Alberti, K. G. M. M., Zimmet, P., & Shaw, J. (2006). Metabolic syndrome\u2014a new world-wide definition. A Consensus Statement from the International Diabetes Federation. Diabetic Medicine, 23(5), 469\u2013480. https:\/\/doi.org\/10.1111\/j.1464-5491.2006.01858.x","journal-title":"Diabetic Medicine"},{"issue":"16","key":"2166_CR2","doi-asserted-by":"publisher","first-page":"1640","DOI":"10.1161\/CIRCULATIONAHA.109.192644","volume":"120","author":"KGMM Alberti","year":"2009","unstructured":"Alberti, K. G. M. M., Eckel, R. H., Grundy, S. M., Zimmet, P. Z., Cleeman, J. I., Donato, K. A., Fruchart, J. C., James, W. P. T., Loria, C. M., & Smith, S. C. (2009). Harmonizing the metabolic syndrome. Circulation, 120(16), 1640\u20131645. https:\/\/doi.org\/10.1161\/CIRCULATIONAHA.109.192644","journal-title":"Circulation"},{"key":"2166_CR4","doi-asserted-by":"publisher","unstructured":"Ambroselli, D., Masciulli, F., Romano, E., Catanzaro, G., Besharat, Z. M., Massari, M. C., Ferretti, E., Migliaccio, S., Izzo, L., Ritieni, A., Grosso, M., Formichi, C., Dotta, F., Frigerio, F., Barbiera, E., Giusti, A. M., Ingallina, C., & Mannina, L. (2023). New advances in metabolic syndrome, from Prevention to Treatment: The role of Diet and Food. Nutrients, 15(3). https:\/\/doi.org\/10.3390\/nu15030640","DOI":"10.3390\/nu15030640"},{"issue":"6","key":"2166_CR5","doi-asserted-by":"publisher","first-page":"e8124","DOI":"10.15252\/MSB.20178124","volume":"14","author":"R Argelaguet","year":"2018","unstructured":"Argelaguet, R., Velten, B., Arnol, D., Dietrich, S., Zenz, T., Marioni, J. C., Buettner, F., Huber, W., & Stegle, O. (2018). Multi-omics factor Analysis\u2014a framework for unsupervised integration of multi-omics data sets. Molecular Systems Biology, 14(6), e8124. https:\/\/doi.org\/10.15252\/MSB.20178124","journal-title":"Molecular Systems Biology"},{"key":"2166_CR6","doi-asserted-by":"publisher","unstructured":"Breuninger, T. A., Wawro, N., Freuer, D., Reitmeier, S., Artati, A., Grallert, H., Adamski, J., Meisinger, C., Peters, A., Haller, D., & Linseisen, J. (2022). Fecal bile acids and neutral sterols are Associated with Latent Microbial subgroups in the human gut. Metabolites, 12(9). https:\/\/doi.org\/10.3390\/metabo12090846","DOI":"10.3390\/metabo12090846"},{"key":"2166_CR7","doi-asserted-by":"publisher","first-page":"108238","DOI":"10.1016\/j.pharmthera.2022.108238","volume":"237","author":"J Cai","year":"2022","unstructured":"Cai, J., Rimal, B., Jiang, C., Chiang, J. Y. L., & Patterson, A. D. (2022). Bile acid metabolism and signaling, the microbiota, and metabolic disease. Pharmacology & Therapeutics, 237, 108238. https:\/\/doi.org\/10.1016\/j.pharmthera.2022.108238","journal-title":"Pharmacology & Therapeutics"},{"key":"2166_CR8","doi-asserted-by":"crossref","unstructured":"Calzadilla, N., Comiskey, S. M., Dudeja, P. K., Saksena, S., Gill, R. K., & Alrefai, W. A. (2022). Bile acids as inflammatory mediators and modulators of intestinal permeability. Frontiers in Immunology, 13, 1021924. https:\/\/doi.org\/10.3389\/FIMMU.2022.1021924\/BIBTEX","DOI":"10.3389\/fimmu.2022.1021924"},{"issue":"null","key":"2166_CR9","doi-asserted-by":"publisher","first-page":"991","DOI":"10.2147\/DMSO.S294894","volume":"14","author":"D Cheng","year":"2021","unstructured":"Cheng, D., Zhao, X., Yang, S., Cui, H., & Wang, G. (2021). Metabolomic Signature between Metabolically Healthy Overweight\/Obese and metabolically unhealthy Overweight\/Obese: A systematic review. Diabetes Metabolic Syndrome and Obesity, 14(null), 991\u20131010. https:\/\/doi.org\/10.2147\/DMSO.S294894","journal-title":"Diabetes Metabolic Syndrome and Obesity"},{"issue":"2","key":"2166_CR10","doi-asserted-by":"publisher","first-page":"488","DOI":"10.1016\/J.CMET.2018.09.022","volume":"29","author":"ET Cirulli","year":"2019","unstructured":"Cirulli, E. T., Guo, L., Leon Swisher, C., Shah, N., Huang, L., Napier, L. A., Kirkness, E. F., Spector, T. D., Caskey, C. T., Thorens, B., Venter, J. C., & Telenti, A. (2019). Profound perturbation of the metabolome in obesity is Associated with Health Risk. Cell Metabolism, 29(2), 488\u2013500e2. https:\/\/doi.org\/10.1016\/J.CMET.2018.09.022","journal-title":"Cell Metabolism"},{"key":"2166_CR11","doi-asserted-by":"publisher","unstructured":"Coleman, M. J., Espino, L. M., Lebensohn, H., Zimkute, M. V., Yaghooti, N., Ling, C. L., Gross, J. M., Listwan, N., Cano, S., Garcia, V., Lovato, D. M., Tigert, S. L., Jones, D. R., Gullapalli, R. R., Rakov, N. E., Perez, T., E. G., & Castillo, E. F. (2022). Individuals with metabolic syndrome show altered fecal lipidomic profiles with no signs of intestinal inflammation or increased intestinal permeability. Metabolites, 12(5). https:\/\/doi.org\/10.3390\/metabo12050431","DOI":"10.3390\/metabo12050431"},{"key":"2166_CR12","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/j.aca.2020.02.046","volume":"1108","author":"M De Spiegeleer","year":"2020","unstructured":"De Spiegeleer, M., De Graeve, M., Huysman, S., Vanderbeke, A., Van Meulebroek, L., & Vanhaecke, L. (2020). Impact of storage conditions on the human stool metabolome and lipidome: Preserving the most accurate fingerprint. Analytica Chimica Acta, 1108, 79\u201388. https:\/\/doi.org\/10.1016\/j.aca.2020.02.046","journal-title":"Analytica Chimica Acta"},{"issue":"1","key":"2166_CR13","doi-asserted-by":"publisher","first-page":"571","DOI":"10.1038\/s41467-023-36256-y","volume":"14","author":"K Deng","year":"2023","unstructured":"Deng, K., Xu, J., Shen, L., Zhao, H., Gou, W., Xu, F., Fu, Y., Jiang, Z., Shuai, M., Li, B., Hu, W., Zheng, J. S., & Chen, Y. (2023). Comparison of fecal and blood metabolome reveals inconsistent associations of the gut microbiota with cardiometabolic diseases. Nature Communications, 14(1), 571. https:\/\/doi.org\/10.1038\/s41467-023-36256-y","journal-title":"Nature Communications"},{"key":"2166_CR14","doi-asserted-by":"publisher","first-page":"s3","DOI":"10.5604\/01.3001.0010.5493","volume":"16(Suppl","author":"A Di Ciaula","year":"2017","unstructured":"Di Ciaula, A., Garruti, G., Baccetto, R. L., Molina-Molina, E., Bonfrate, L., Wang, D. Q. H., & Portincasa, P. (2017). Bile Acid Physiology. Annals of Hepatology, 16(Suppl, 1: s3\u2013105. https:\/\/doi.org\/10.5604\/01.3001.0010.5493","journal-title":"Annals of Hepatology"},{"issue":"11","key":"2166_CR15","doi-asserted-by":"publisher","first-page":"1560","DOI":"10.1038\/s42255-022-00670-1","volume":"4","author":"C Diener","year":"2022","unstructured":"Diener, C., Dai, C. L., Wilmanski, T., Baloni, P., Smith, B., Rappaport, N., Hood, L., Magis, A. T., & Gibbons, S. M. (2022). Genome\u2013microbiome interplay provides insight into the determinants of the human blood metabolome. Nature Metabolism, 4(11), 1560\u20131572. https:\/\/doi.org\/10.1038\/s42255-022-00670-1","journal-title":"Nature Metabolism"},{"issue":"1","key":"2166_CR16","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1038\/s41579-020-0433-9","volume":"19:1","author":"Y Fan","year":"2020","unstructured":"Fan, Y., & Pedersen, O. (2020). Gut microbiota in human metabolic health and disease. Nature Reviews Microbiology 2020, 19:1(1), 55\u201371. https:\/\/doi.org\/10.1038\/s41579-020-0433-9. 19.","journal-title":"Nature Reviews Microbiology 2020"},{"key":"2166_CR17","doi-asserted-by":"publisher","unstructured":"Faquih, T., van Smeden, M., Luo, J., le Cessie, S., Kastenm\u00fcller, G., Krumsiek, J., Noordam, R., van Heemst, D., Rosendaal, F. R., van Hylckama Vlieg, A., van Dijk, W., K., & Mook-Kanamori, D. O. (2020). A workflow for missing values imputation of untargeted Metabolomics Data. Metabolites, 10(12). https:\/\/doi.org\/10.3390\/metabo10120486","DOI":"10.3390\/metabo10120486"},{"issue":"5","key":"2166_CR18","doi-asserted-by":"publisher","first-page":"599","DOI":"10.3945\/jn.113.186858","volume":"144","author":"A Fechner","year":"2014","unstructured":"Fechner, A., Kiehntopf, M., & Jahreis, G. (2014). The formation of short-chain fatty acids is positively Associated with the blood lipid\u2013lowering effect of Lupin Kernel Fiber in moderately hypercholesterolemic Adults1, 2, 3. The Journal of Nutrition, 144(5), 599\u2013607. https:\/\/doi.org\/10.3945\/jn.113.186858","journal-title":"The Journal of Nutrition"},{"key":"2166_CR19","doi-asserted-by":"publisher","unstructured":"Fomenko, M. V., Yanshole, L. V., & Tsentalovich, Y. P. (2022). Stability of Metabolomic Content during Sample Preparation: Blood and brain tissues. Metabolites, 12(9). https:\/\/doi.org\/10.3390\/metabo12090811","DOI":"10.3390\/metabo12090811"},{"key":"2166_CR20","doi-asserted-by":"publisher","unstructured":"Gali\u00e9, S., Papandreou, C., Arcelin, P., Garcia, D., Palau-Galindo, A., Guti\u00e9rrez-Tordera, L., Folch, \u00c0., & Bull\u00f3, M. (2021). Examining the Interaction of the gut microbiome with Host Metabolism and Cardiometabolic Health in Metabolic Syndrome. Nutrients, 13(12). https:\/\/doi.org\/10.3390\/nu13124318","DOI":"10.3390\/nu13124318"},{"key":"2166_CR21","doi-asserted-by":"publisher","unstructured":"Gegner, H. M., Naake, T., Dugourd, A., M\u00fcller, T., Czernilofsky, F., Kliewer, G., J\u00e4ger, E., Helm, B., Kunze-Rohrbach, N., Klingm\u00fcller, U., Hopf, C., M\u00fcller-Tidow, C., Dietrich, S., Saez-Rodriguez, J., Huber, W., Hell, R., Poschet, G., & Krijgsveld, J. (2022). Pre-analytical processing of plasma and serum samples for combined proteome and metabolome analysis. Frontiers in Molecular Biosciences, 9. https:\/\/doi.org\/10.3389\/fmolb.2022.961448","DOI":"10.3389\/fmolb.2022.961448"},{"key":"2166_CR22","doi-asserted-by":"publisher","unstructured":"Gerl, M. J., Klose, C., Surma, M. A., Fernandez, C., Melander, O., M\u00e4nnist\u00f6, S., Borodulin, K., Havulinna, A. S., Salomaa, V., Ikonen, E., Cannistraci, C. V., & Simons, K. (2019). Machine learning of human plasma lipidomes for obesity estimation in a large population cohort. PLoS Biology, 17(10). https:\/\/doi.org\/10.1371\/JOURNAL.PBIO.3000443","DOI":"10.1371\/JOURNAL.PBIO.3000443"},{"issue":"1","key":"2166_CR23","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1186\/s12933-020-01166-6","volume":"19","author":"MJ Guembe","year":"2020","unstructured":"Guembe, M. J., Fernandez-Lazaro, C. I., Sayon-Orea, C., Toledo, E., Moreno-Iribas, C., Cosials, J. B., Reyero, J. B., Mart\u00ednez, J. D., Diego, P. G., Uche, A. M. G., Setas, D. G., Vila, E. M., Mart\u00ednez, M. S., Tornos, I. S., & Rueda, J. J. V. (2020). Risk for cardiovascular disease associated with metabolic syndrome and its components: A 13-year prospective study in the RIVANA cohort. Cardiovascular Diabetology, 19(1), 195. https:\/\/doi.org\/10.1186\/s12933-020-01166-6. & Investigators, for the R.","journal-title":"Cardiovascular Diabetology"},{"issue":"JUN","key":"2166_CR24","doi-asserted-by":"publisher","first-page":"237451","DOI":"10.3389\/FMICB.2017.01162\/BIBTEX","volume":"8","author":"VK Gupta","year":"2017","unstructured":"Gupta, V. K., Paul, S., & Dutta, C. (2017). Geography, ethnicity or subsistence-specific variations in human microbiome composition and diversity. Frontiers in Microbiology, 8(JUN), 237451. https:\/\/doi.org\/10.3389\/FMICB.2017.01162\/BIBTEX","journal-title":"Frontiers in Microbiology"},{"issue":"1","key":"2166_CR25","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1021\/acs.jproteome.7b00518","volume":"17","author":"M Haid","year":"2018","unstructured":"Haid, M., Muschet, C., Wahl, S., R\u00f6misch-Margl, W., Prehn, C., M\u00f6ller, G., & Adamski, J. (2018). Long-Term Stability of Human plasma metabolites during storage at \u2013\u200980\u00b0C. Journal of Proteome Research, 17(1), 203\u2013211. https:\/\/doi.org\/10.1021\/acs.jproteome.7b00518","journal-title":"Journal of Proteome Research"},{"issue":"7640","key":"2166_CR26","doi-asserted-by":"publisher","first-page":"177","DOI":"10.1038\/nature21363","volume":"542","author":"GS Hotamisligil","year":"2017","unstructured":"Hotamisligil, G. S. (2017). Inflammation, metaflammation and immunometabolic disorders. Nature, 542(7640), 177\u2013185. https:\/\/doi.org\/10.1038\/nature21363","journal-title":"Nature"},{"issue":"1","key":"2166_CR27","doi-asserted-by":"publisher","first-page":"e001321","DOI":"10.1136\/bmjdrc-2020-001321","volume":"8","author":"MT Huemer","year":"2020","unstructured":"Huemer, M. T., Huth, C., Schederecker, F., Klug, S. J., Meisinger, C., Koenig, W., Rathmann, W., Peters, A., & Thorand, B. (2020). Association of endothelial dysfunction with incident prediabetes, type 2 diabetes and related traits: The KORA F4\/FF4 study. BMJ Open Diabetes Research &Amp Care, 8(1), e001321. https:\/\/doi.org\/10.1136\/bmjdrc-2020-001321","journal-title":"BMJ Open Diabetes Research &Amp Care"},{"key":"2166_CR28","doi-asserted-by":"publisher","first-page":"288","DOI":"10.1186\/1471-2105-12-288","volume":"12","author":"K Jung","year":"2011","unstructured":"Jung, K., Friede, T., & Beissbarth, T. (2011). Reporting FDR analogous confidence intervals for the log fold change of differentially expressed genes. Bmc Bioinformatics, 12, 288. https:\/\/doi.org\/10.1186\/1471-2105-12-288","journal-title":"Bmc Bioinformatics"},{"issue":"10","key":"2166_CR29","doi-asserted-by":"publisher","first-page":"101566","DOI":"10.1016\/j.isci.2020.101566","volume":"23","author":"SR Khan","year":"2020","unstructured":"Khan, S. R., Manialawy, Y., Obersterescu, A., Cox, B. J., Gunderson, E. P., & Wheeler, M. B. (2020). Diminished sphingolipid metabolism, a Hallmark of Future Type 2 diabetes pathogenesis, is linked to pancreatic \u03b2 cell dysfunction. IScience, 23(10), 101566. https:\/\/doi.org\/10.1016\/j.isci.2020.101566","journal-title":"IScience"},{"key":"2166_CR30","doi-asserted-by":"publisher","unstructured":"Kowall, B., Rathmann, W., Stang, A., Bongaerts, B., Kuss, O., Herder, C., Roden, M., Quante, A., Holle, R., Huth, C., Peters, A., & Meisinger, C. (2017). Perceived risk of diabetes seriously underestimates actual diabetes risk: The KORA FF4 study. Plos One, 12(1). https:\/\/doi.org\/10.1371\/JOURNAL.PONE.0171152","DOI":"10.1371\/JOURNAL.PONE.0171152"},{"issue":"9","key":"2166_CR31","doi-asserted-by":"publisher","first-page":"4208","DOI":"10.1021\/pr2003598","volume":"10","author":"G Le Gall","year":"2011","unstructured":"Le Gall, G., Noor, S. O., Ridgway, K., Scovell, L., Jamieson, C., Johnson, I. T., Colquhoun, I. J., Kemsley, E. K., & Narbad, A. (2011). Metabolomics of fecal extracts detects altered metabolic activity of gut microbiota in Ulcerative Colitis and irritable bowel syndrome. Journal of Proteome Research, 10(9), 4208\u20134218. https:\/\/doi.org\/10.1021\/pr2003598","journal-title":"Journal of Proteome Research"},{"issue":"6","key":"2166_CR32","doi-asserted-by":"publisher","first-page":"e13830","DOI":"10.1111\/nmo.13830","volume":"32","author":"JS Lee","year":"2020","unstructured":"Lee, J. S., Kim, S. Y., Chun, Y. S., Chun, Y. J., Shin, S. Y., Choi, C. H., & Choi, H. K. (2020). Characteristics of fecal metabolic profiles in patients with irritable bowel syndrome with predominant diarrhea investigated using 1H-NMR coupled with multivariate statistical analysis. Neurogastroenterology & Motility, 32(6), e13830. https:\/\/doi.org\/10.1111\/nmo.13830","journal-title":"Neurogastroenterology & Motility"},{"issue":"12","key":"2166_CR33","doi-asserted-by":"publisher","first-page":"2083","DOI":"10.1007\/s00726-017-2493-3","volume":"49","author":"R Lin","year":"2017","unstructured":"Lin, R., Liu, W., Piao, M., & Zhu, H. (2017). A review of the relationship between the gut microbiota and amino acid metabolism. Amino Acids, 49(12), 2083\u20132090. https:\/\/doi.org\/10.1007\/s00726-017-2493-3","journal-title":"Amino Acids"},{"issue":"7503","key":"2166_CR34","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1038\/nature13475","volume":"510:7503","author":"M MacEyka","year":"2014","unstructured":"MacEyka, M., & Spiegel, S. (2014). Sphingolipid metabolites in inflammatory disease. Nature 2014, 510:7503(7503), 58\u201367. https:\/\/doi.org\/10.1038\/nature13475. 510.","journal-title":"Nature 2014"},{"issue":"3","key":"2166_CR35","doi-asserted-by":"publisher","first-page":"326","DOI":"10.1177\/0004563218817798","volume":"56","author":"ER McGlone","year":"2019","unstructured":"McGlone, E. R., & Bloom, S. R. (2019). Bile acids and the metabolic syndrome. Annals of Clinical Biochemistry, 56(3), 326\u2013337. https:\/\/doi.org\/10.1177\/0004563218817798","journal-title":"Annals of Clinical Biochemistry"},{"key":"2166_CR36","doi-asserted-by":"publisher","unstructured":"Mir, F. A., Ullah, E., Mall, R., Iskandarani, A., Samra, T. A., Cyprian, F., Parray, A., Alkasem, M., Abdalhakam, I., Farooq, F., & Abou-Samra, A. B. (2022). Dysregulated metabolic pathways in subjects with obesity and metabolic syndrome. International Journal of Molecular Sciences, 23(17). https:\/\/doi.org\/10.3390\/IJMS23179821","DOI":"10.3390\/IJMS23179821"},{"issue":"3","key":"2166_CR37","doi-asserted-by":"publisher","first-page":"309","DOI":"10.1017\/S000711451900103X","volume":"122","author":"P Mitry","year":"2019","unstructured":"Mitry, P., Wawro, N., Sharma, S., Kriebel, J., Artati, A., Adamski, J., Heier, M., Meisinger, C., Thorand, B., Grallert, H., Peters, A., & Linseisen, J. (2019a). Associations between usual food intake and faecal sterols and bile acids: Results from the Cooperative Health Research in the Augsburg Region (KORA FF4) study. British Journal of Nutrition, 122(3), 309\u2013321. https:\/\/doi.org\/10.1017\/S000711451900103X","journal-title":"British Journal of Nutrition"},{"key":"2166_CR38","doi-asserted-by":"publisher","first-page":"145","DOI":"10.3389\/fnut.2019.00145","volume":"6","author":"P Mitry","year":"2019","unstructured":"Mitry, P., Wawro, N., Six-Merker, J., Zoller, D., Jourdan, C., Meisinger, C., Thierry, S., N\u00f6thlings, U., Kn\u00fcppel, S., Boeing, H., & Linseisen, J. (2019b). Usual dietary intake estimation based on a combination of repeated 24-H food lists and a food frequency questionnaire in the KORA FF4 cross-sectional study. Frontiers in Nutrition, 6, 145. https:\/\/doi.org\/10.3389\/fnut.2019.00145","journal-title":"Frontiers in Nutrition"},{"issue":"4","key":"2166_CR39","doi-asserted-by":"publisher","first-page":"2930","DOI":"10.3390\/nu7042930","volume":"7","author":"EPJG Neis","year":"2015","unstructured":"Neis, E. P. J. G., Dejong, C. H. C., & Rensen, S. S. (2015). The role of microbial amino acid metabolism in host metabolism. Nutrients, 7(4), 2930\u20132946. https:\/\/doi.org\/10.3390\/nu7042930","journal-title":"Nutrients"},{"key":"2166_CR40","doi-asserted-by":"publisher","first-page":"109924","DOI":"10.1016\/j.diabres.2022.109924","volume":"188","author":"JJ Noubiap","year":"2022","unstructured":"Noubiap, J. J., Nansseu, J. R., Lontchi-Yimagou, E., Nkeck, J. R., Nyaga, U. F., Ngouo, A. T., Tounouga, D. N., Tianyi, F. L., Foka, A. J., Ndoadoumgue, A. L., & Bigna, J. J. (2022). Geographic distribution of metabolic syndrome and its components in the general adult population: A meta-analysis of global data from 28 million individuals. Diabetes Research and Clinical Practice, 188, 109924. https:\/\/doi.org\/10.1016\/j.diabres.2022.109924","journal-title":"Diabetes Research and Clinical Practice"},{"issue":"11","key":"2166_CR41","doi-asserted-by":"publisher","first-page":"1021","DOI":"10.1016\/j.numecd.2017.07.006","volume":"27","author":"A Ntzouvani","year":"2017","unstructured":"Ntzouvani, A., Nomikos, T., Panagiotakos, D., Fragopoulou, E., Pitsavos, C., McCann, A., Ueland, P. M., & Antonopoulou, S. (2017). Amino acid profile and metabolic syndrome in a male Mediterranean population: A cross-sectional study. Nutrition Metabolism and Cardiovascular Diseases, 27(11), 1021\u20131030. https:\/\/doi.org\/10.1016\/j.numecd.2017.07.006","journal-title":"Nutrition Metabolism and Cardiovascular Diseases"},{"issue":"5","key":"2166_CR42","doi-asserted-by":"publisher","first-page":"328","DOI":"10.1152\/physiol.00011.2020","volume":"35","author":"JN Rao","year":"2020","unstructured":"Rao, J. N., Xiao, L., & Wang, J. Y. (2020). Polyamines in Gut Epithelial Renewal and barrier function. Physiology, 35(5), 328\u2013337. https:\/\/doi.org\/10.1152\/physiol.00011.2020","journal-title":"Physiology"},{"issue":"1","key":"2166_CR43","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/S12933-023-01862-Z\/FIGURES\/6","volume":"22","author":"M Shi","year":"2023","unstructured":"Shi, M., Han, S., Klier, K., Fobo, G., Montrone, C., Yu, S., Harada, M., Henning, A. K., Friedrich, N., Bahls, M., D\u00f6rr, M., Nauck, M., V\u00f6lzke, H., Homuth, G., Grabe, H. J., Prehn, C., Adamski, J., Suhre, K., Rathmann, W., & Wang-Sattler, R. (2023). Identification of candidate metabolite biomarkers for metabolic syndrome and its five components in population-based human cohorts. Cardiovascular Diabetology, 22(1), 1\u201316. https:\/\/doi.org\/10.1186\/S12933-023-01862-Z\/FIGURES\/6","journal-title":"Cardiovascular Diabetology"},{"issue":"4","key":"2166_CR44","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1007\/s00125-009-1620-4","volume":"53","author":"RK Simmons","year":"2010","unstructured":"Simmons, R. K., Alberti, K. G. M. M., Gale, E. A. M., Colagiuri, S., Tuomilehto, J., Qiao, Q., Ramachandran, A., Tajima, N., Mirchov, B., Ben-Nakhi, I., Reaven, A., Hama Sambo, G., Mendis, B., S., & Roglic, G. (2010). The metabolic syndrome: Useful concept or clinical tool? Report of a WHO Expert Consultation. Diabetologia, 53(4), 600\u2013605. https:\/\/doi.org\/10.1007\/s00125-009-1620-4","journal-title":"Diabetologia"},{"issue":"1","key":"2166_CR45","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1007\/s00253-016-8006-6","volume":"101","author":"C Staley","year":"2017","unstructured":"Staley, C., Weingarden, A. R., Khoruts, A., & Sadowsky, M. J. (2017). Interaction of gut microbiota with bile acid metabolism and its influence on disease states. Applied Microbiology and Biotechnology, 101(1), 47\u201364. https:\/\/doi.org\/10.1007\/s00253-016-8006-6","journal-title":"Applied Microbiology and Biotechnology"},{"key":"2166_CR46","doi-asserted-by":"publisher","unstructured":"Surowiec, I., Noordam, R., Bennett, K., Beekman, M., Slagboom, P. E., Lundstedt, T., & van Heemst, D. (2019). Metabolomic and lipidomic assessment of the metabolic syndrome in Dutch middle-aged individuals reveals novel biological signatures separating health and disease. Metabolomics: Official Journal of the Metabolomic Society, 15(2). https:\/\/doi.org\/10.1007\/S11306-019-1484-7","DOI":"10.1007\/S11306-019-1484-7"},{"issue":"1","key":"2166_CR47","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1016\/J.CMET.2016.05.005","volume":"24","author":"A Wahlstr\u00f6m","year":"2016","unstructured":"Wahlstr\u00f6m, A., Sayin, S. I., Marschall, H. U., & B\u00e4ckhed, F. (2016). Intestinal crosstalk between bile acids and microbiota and its impact on host metabolism. Cell Metabolism, 24(1), 41\u201350. https:\/\/doi.org\/10.1016\/J.CMET.2016.05.005","journal-title":"Cell Metabolism"},{"issue":"6","key":"2166_CR48","doi-asserted-by":"publisher","first-page":"1684","DOI":"10.3390\/nu12061684","volume":"12","author":"N Wawro","year":"2020","unstructured":"Wawro, N., Pestoni, G., Riedl, A., Breuninger, T. A., Peters, A., Rathmann, W., Koenig, W., Huth, C., Meisinger, C., Rohrmann, S., & Linseisen, J. (2020). Association of Dietary Patterns and Type-2 diabetes Mellitus in metabolically homogeneous subgroups in the KORA FF4 study. Nutrients, 12(6), 1684. https:\/\/doi.org\/10.3390\/nu12061684","journal-title":"Nutrients"},{"key":"2166_CR49","doi-asserted-by":"publisher","unstructured":"Wieder, C., Frainay, C., Poupin, N., Rodr\u00edguez-Mier, P., Vinson, F., Cooke, J., Lai, R. P. J., Bundy, J. G., Jourdan, F., & Ebbels, T. (2021). Pathway analysis in metabolomics: Recommendations for the use of over-representation analysis. PLoS Computational Biology, 17(9). https:\/\/doi.org\/10.1371\/JOURNAL.PCBI.1009105","DOI":"10.1371\/JOURNAL.PCBI.1009105"},{"issue":"22","key":"2166_CR50","doi-asserted-by":"publisher","first-page":"3534","DOI":"10.3748\/WJG.V29.I22.3534","volume":"29","author":"YF Xu","year":"2023","unstructured":"Xu, Y. F., Hao, Y. X., Ma, L., Zhang, M. H., Niu, X. X., Li, Y., Zhang, Y. Y., Liu, T. T., Han, M., Yuan, X. X., Wan, G., & Xing, H. C. (2023). Difference and clinical value of metabolites in plasma and feces of patients with alcohol-related liver cirrhosis. World Journal of Gastroenterology, 29(22), 3534. https:\/\/doi.org\/10.3748\/WJG.V29.I22.3534","journal-title":"World Journal of Gastroenterology"},{"issue":"1","key":"2166_CR51","doi-asserted-by":"publisher","first-page":"11918","DOI":"10.1038\/srep11918","volume":"5","author":"M Yamakado","year":"2015","unstructured":"Yamakado, M., Nagao, K., Imaizumi, A., Tani, M., Toda, A., Tanaka, T., Jinzu, H., Miyano, H., Yamamoto, H., Daimon, T., Horimoto, K., & Ishizaka, Y. (2015). Plasma free amino acid profiles predict four-year risk of developing diabetes, metabolic syndrome, Dyslipidemia and Hypertension in Japanese Population. Scientific Reports, 5(1), 11918. https:\/\/doi.org\/10.1038\/srep11918","journal-title":"Scientific Reports"},{"key":"2166_CR52","doi-asserted-by":"publisher","first-page":"107632","DOI":"10.1016\/J.ENVINT.2022.107632","volume":"170","author":"Y Yao","year":"2022","unstructured":"Yao, Y., Schneider, A., Wolf, K., Zhang, S., Wang-Sattler, R., Peters, A., & Breitner, S. (2022). Longitudinal associations between metabolites and long-term exposure to ambient air pollution: Results from the KORA cohort study. Environment International, 170, 107632. https:\/\/doi.org\/10.1016\/J.ENVINT.2022.107632","journal-title":"Environment International"},{"issue":"6","key":"2166_CR53","doi-asserted-by":"publisher","first-page":"790","DOI":"10.1038\/s41588-018-0135-7","volume":"50","author":"J Zierer","year":"2018","unstructured":"Zierer, J., Jackson, M. A., Kastenm\u00fcller, G., Mangino, M., Long, T., Telenti, A., Mohney, R. P., Small, K. S., Bell, J. T., Steves, C. J., Valdes, A. M., Spector, T. D., & Menni, C. (2018). The fecal metabolome as a functional readout of the gut microbiome. Nature Genetics, 50(6), 790\u2013795. https:\/\/doi.org\/10.1038\/s41588-018-0135-7","journal-title":"Nature Genetics"},{"issue":"1","key":"2166_CR54","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1007\/s11306-017-1312-x","volume":"14","author":"S Zukunft","year":"2018","unstructured":"Zukunft, S., Prehn, C., R\u00f6hring, C., M\u00f6ller, G., Hrab\u011b de Angelis, M., Adamski, J., & Tokarz, J. (2018). High-throughput extraction and quantification method for targeted metabolomics in murine tissues. Metabolomics, 14(1), 18. https:\/\/doi.org\/10.1007\/s11306-017-1312-x","journal-title":"Metabolomics"}],"container-title":["Metabolomics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11306-024-02166-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11306-024-02166-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11306-024-02166-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,23]],"date-time":"2024-10-23T05:16:06Z","timestamp":1729660566000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11306-024-02166-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,21]]},"references-count":54,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2024,10]]}},"alternative-id":["2166"],"URL":"https:\/\/doi.org\/10.1007\/s11306-024-02166-3","relation":{},"ISSN":["1573-3890"],"issn-type":[{"value":"1573-3890","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,21]]},"assertion":[{"value":"12 May 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 August 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 September 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and\/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"Informed consent was obtained from all individual participants included in the study.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"105"}}