Display options
Cite
Galié S, Papandreou C, Arcelin P, et al. Examining the Interaction of the Gut Microbiome with Host Metabolism and Cardiometabolic Health in Metabolic Syndrome. Nutrients. 2021;13(12)doi: 10.3390/nu13124318.
Galié, S., Papandreou, C., Arcelin, P., Garcia, D., Palau-Galindo, A., Gutiérrez-Tordera, L., Folch, �. �., & Bulló, 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
Galié, Serena, et al. "Examining the Interaction of the Gut Microbiome with Host Metabolism and Cardiometabolic Health in Metabolic Syndrome." Nutrients vol. 13,12 (2021). doi: https://doi.org/10.3390/nu13124318
Galié S, Papandreou C, Arcelin P, Garcia D, Palau-Galindo A, Gutiérrez-Tordera L, Folch À, Bulló M. Examining the Interaction of the Gut Microbiome with Host Metabolism and Cardiometabolic Health in Metabolic Syndrome. Nutrients. 2021 Nov 29;13(12). doi: 10.3390/nu13124318. PMID: 34959869; PMCID: PMC8706982.
Copy Download .nbib Format: NLM
Share it on

Nutrients. 2021 Nov 29;13(12). doi: 10.3390/nu13124318.

Examining the Interaction of the Gut Microbiome with Host Metabolism and Cardiometabolic Health in Metabolic Syndrome.

Nutrients

Serena Galié, Christopher Papandreou, Pierre Arcelin, David Garcia, Antoni Palau-Galindo, Laia Gutiérrez-Tordera, Àlex Folch, Mònica Bulló

Affiliations

  1. Department of Biochemistry and Biotechnology, Faculty of Medicine and Health Sciences, University RoviraiVirgili (URV), 43201 Reus, Spain.
  2. Institute of Health Pere Virgili-IISPV, University Hospital Sant Joan, 43202 Reus, Spain.
  3. CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.
  4. Atención Basica de Salut (ABS) Reus V. Centre d'Assistència Primària Marià Fortuny, SAGESSA, 43204 Reus, Spain.
  5. ABS Alt Camp Oest, Centre d'Atenció Primària, 43460 Alcover, Spain.

PMID: 34959869 PMCID: PMC8706982 DOI: 10.3390/nu13124318

Abstract

(1) Background: The microbiota-host cross-talk has been previously investigated, while its role in health is not yet clear. This study aimed to unravel the network of microbial-host interactions and correlate it with cardiometabolic risk factors. (2) Methods: A total of 47 adults with overweight/obesity and metabolic syndrome from the METADIET study were included in this cross-sectional analysis. Microbiota composition (151 genera) was assessed by 16S rRNA sequencing, fecal (m = 203) and plasma (m = 373) metabolites were profiled. An unsupervised sparse generalized canonical correlation analysis was used to construct a network of microbiota-metabolite interactions. A multi-omics score was derived for each cluster of the network and associated with cardiometabolic risk factors. (3) Results: Five multi-omics clusters were identified. Thirty-one fecal metabolites formed these clusters and were correlated with plasma sphingomyelins, lysophospholipids and medium to long-chain acylcarnitines. Seven genera from Ruminococcaceae and a member from the Desulfovibrionaceae family were correlated with fecal and plasma metabolites. Positive correlations were found between the multi-omics scores from two clusters with cholesterol and triglycerides levels. (4) Conclusions: We identified a correlated network between specific microbial genera and fecal/plasma metabolites in an adult population with metabolic syndrome, suggesting an interplay between gut microbiota and host lipid metabolism on cardiometabolic health.

Keywords: cardiovascular risk; cross-talk; gut microbiota; metabolic syndrome; metabolism; metabolites; metabolomics; microbial metabolites; obesity; omics

References

  1. J Lipid Res. 2012 Sep;53(9):1723-37 - PubMed
  2. Lipids. 1980 Aug;15(8):572-9 - PubMed
  3. Diabetologia. 2016 Nov;59(11):2349-2359 - PubMed
  4. Gut Microbes. 2021 Jan-Dec;13(1):1-19 - PubMed
  5. Lipids Health Dis. 2019 Feb 2;18(1):38 - PubMed
  6. Sci Data. 2020 Mar 16;7(1):92 - PubMed
  7. Nat Commun. 2020 Oct 14;11(1):5153 - PubMed
  8. Biochem Biophys Res Commun. 2018 Jun 7;500(3):671-675 - PubMed
  9. Appl Environ Microbiol. 2009 Jul;75(14):4821-8 - PubMed
  10. Am J Hypertens. 2018 Jul 16;31(8):941-944 - PubMed
  11. Cell. 2008 Sep 5;134(5):708-13 - PubMed
  12. Clin Chem. 2016 Apr;62(4):582-92 - PubMed
  13. J Formos Med Assoc. 2019 Mar;118 Suppl 1:S10-S22 - PubMed
  14. Annu Rev Biochem. 2003;72:137-74 - PubMed
  15. Nat Rev Immunol. 2016 May 27;16(6):341-52 - PubMed
  16. Pediatr Obes. 2018 Jun;13(6):381-388 - PubMed
  17. Cell Syst. 2016 Dec 21;3(6):572-584.e3 - PubMed
  18. Mol Nutr Food Res. 2018 Mar;62(6):e1700756 - PubMed
  19. Sci Rep. 2020 Jan 20;10(1):669 - PubMed
  20. Nat Commun. 2019 Dec 20;10(1):5813 - PubMed
  21. Gastroenterology. 2009 Nov;137(5):1716-24.e1-2 - PubMed
  22. J Am Heart Assoc. 2020 Sep 15;9(18):e016518 - PubMed
  23. Biostatistics. 2014 Jul;15(3):569-83 - PubMed
  24. Nat Genet. 2018 Jun;50(6):790-795 - PubMed
  25. Diabetes Metab. 2011 Jun;37(3):179-88 - PubMed
  26. Clin Nutr. 2021 Jun;40(6):3798-3806 - PubMed
  27. Nat Commun. 2019 Oct 3;10(1):4505 - PubMed
  28. Nature. 2012 Oct 4;490(7418):55-60 - PubMed
  29. Clin Nutr. 2020 Jul;39(7):2292-2300 - PubMed
  30. Environ Microbiol. 2017 Jan;19(1):29-41 - PubMed
  31. BMC Biol. 2019 Oct 28;17(1):83 - PubMed
  32. Lipids Health Dis. 2019 Apr 6;18(1):88 - PubMed
  33. World J Gastroenterol. 2014 Nov 21;20(43):16079-94 - PubMed
  34. PLoS One. 2018 Dec 21;13(12):e0208584 - PubMed
  35. Diabetologia. 2018 Jul;61(7):1560-1571 - PubMed
  36. Nature. 2016 Jul 06;535(7610):56-64 - PubMed
  37. Arterioscler Thromb Vasc Biol. 2000 Dec;20(12):2614-8 - PubMed
  38. Gut Microbes. 2020 Nov 9;12(1):1-13 - PubMed
  39. Cancer Epidemiol Biomarkers Prev. 2020 Nov;29(11):2289-2299 - PubMed

Publication Types

Grant support