Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Nov;11(11):e575.
doi: 10.1002/ctm2.575.

Changes in glucagon-like peptide 1 and 2 levels in people with obesity after a diet-induced weight-loss intervention are related to a specific microbiota signature: A prospective cohort study

M-Mar Rodríguez-Peña  1   2 , Brenno Astiarraga  1   3 , Jesus Seco  1 , Victoria Ceperuelo-Mallafré  1   3 , Adrià Caballé  4 , Vicente Pérez-Brocal  5   6 , Camille Stephan-Otto Attolini  4 , Andrés Moya  5   6   7 , Gemma Llauradó  2   8 , Ana Megía  1   2 , Silvia Pellitero  9 , Núria Vilarrasa  2   10 , Sonia Fernández-Veledo  1   2 , Joan Vendrell  1   2   3
Affiliations

Changes in glucagon-like peptide 1 and 2 levels in people with obesity after a diet-induced weight-loss intervention are related to a specific microbiota signature: A prospective cohort study

M-Mar Rodríguez-Peña et al. Clin Transl Med. 2021 Nov.
No abstract available

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

FIGURE 1
FIGURE 1
Taxonomy composition of the study population. (A) Comparison of relative abundances of different taxa at the family level between post‐intervention (outerchart) and basal (inner chart) faecal microbiota, showing no significant differences. (B) Individual variability between basal (B) and post‐intervention (6 M). The presence of different microorganisms is indicated by colours; the same colour indicates the same family. Microbial taxa are based on the family level. Significant differences were observed for each individual after diet intervention (p‐value < 0.05). The chi‐square test was used for analysis (n = 18 classified as basal (B) and post‐intervention (6 M)). (C) Associations of gut microbiota with clinical variables and intestinal hormones. Heatmap depicting Spearman's rank correlation coefficient of the relative abundances at the family level of different gut microbiota and clinical variables and incretin hormones in all individuals. For correlational studies, all gathered data (basal and 6 months) are included in the analysis. Adjusted p‐values: #padj < 0.25; *padj < 0.05. Peptostreptococcaceae, Clostridiaceae, Ruminococcaceae, Oscillospiraceae, Eubacteriaceae, and Lachnospiraceae showed negative associations with BMI, HOMA‐IR index, and/or plasma urates. By contrast, Streptococcaceae, Prevotellaceae, Selenomonadaceae, Coriobacteriaceae, Bacteriodaceae, Rikenellaceae, Porphyromonadaceae, and Sutterellaceae showed positive associations with the afore mentioned parameters. Odoribacteriaceae showed a negative association with body mass index (BMI) and a positive association with plasma urates
FIGURE 2
FIGURE 2
Diet‐induced microbiota changes and associations between species and variables related to metabolic health status. Log fold‐change (FC) and Spearman correlation analyses of the relative abundance at the species level of gut microbiota and clinical variables and incretin hormones in all individuals. For FC analysis, a zero‐inflated Gaussian mixture model (fitZig) from the metagenomeSeq R package was used, contrasting 6 M/basal. The subject factor in the patient identifier variable (IDPAT) is used as a batch effect, as the inter‐individual differences in the microbiota were greater than the changes caused by the diet. As a consequence, the IDPAT variable was introduced as an adjusting covariate in the model to investigate diet‐induced changes after the 6‐month weight‐loss program. Spearman correlation analysis revealed a negative correlation between most of the Clostridium species, Hemophilus_uc, and Eubacterium sp. CAG 192 and plasma urates, whereas Clostridium sp. CAG:75 and Eubacterium sp. CAG 202 were negatively correlated with HOMA‐IR index. Proteobacteria sp. CAG:873 and Mitsuokella multocida, showed a significant positive correlation with body mass index (BMI) and HOMA‐IR, respectively. All padj < 0.005 in FC and #padj < 0.25; *padj < 0.05 for Spearman correlation analyses
FIGURE 3
FIGURE 3
Spearman correlation analysis of microbiota species and metabolic bacterial function for a set of 45 genes. (A) Hierarchical clustering of the correlation data matrix was conducted at the gene level, which revealed the presence of two highly populated clusters (labelled as 1 and 2). Annotation of metabolic pathways according to the KEGG database, sorted in alphabetical order: [C]: energy production and conversion; [E]: amino acid transport and metabolism; [G]: carbohydrate transport and metabolism; [H]: coenzyme transport and metabolism; [J]: translation; ribosomal structure and biogenesis; [K]: transcription; [L]: replication, recombination, and repair; [M]: cell wall/membrane/envelope biogenesis; [O]: post‐translational modification; protein turnover, chaperones; [P]: inorganic ion transport and metabolism; [T]: signal transduction mechanism; [U|W]: intracellular trafficking and vesicular transport; [V]: defence mechanism. Correlations where an associated p‐adjusted value was greater than 0.25 were neglected for additional analysis. Genes associated with replication, recombination, and repair (encoded as [L]), such as MobA/MobB, site‐specific recombinases, integrases, and transposases, were found to positively correlate with an increase in the presence of Clostridium species. A similar pattern was found (with an equivalent number of enzymes, 4) with post‐translational modification enzymes ([O]) and enzymes involved in signal transduction ([T]). An increase in the abundance of the metabolic enzymes glycosyltransferase_36, dicarboxylate transporter, and carbohydrate‐solute binding proteins were positively correlated with Clostridiaceae family members. Genes associated with amino‐acid transport and metabolism ([E]) and inorganic ion transport ([P]), such as branched‐amino acid transporter and ABC‐related transporter, were also modified. (B) Gene projection of statistically relevant enzyme subset on a KEGG‐modified metabolic enzyme pathway. This analysis revealed only a minor fraction of the total studied genes (12%, seven genes) that could be projected into a metabolic map constellation:Aln‐; Gln‐t‐RNA synthase ([J]), PALM hydrolase ([L]), nicotinate‐phosphoribosyltransferase ([H]), N‐acetylmuranoyl‐l‐alanine amidase ([M]), glycerol‐phosphoryl‐diester‐phospho‐diesterase ([C]), glycosyltransferase 36 ([G]), and branched‐amino acid transporter ([E]). All correspond to different biological pathways
See this image and copyright information in PMC

References

    1. Drucker DJ. Mechanisms of action and therapeutic application of glucagon‐like peptide‐1. Cell Metab. 2018;27(4):740‐756. 10.1016/j.cmet.2018.03.001. - DOI - PubMed
    1. Guan X. The CNS glucagon‐like peptide‐2 receptor in the control of energy balance and glucose homeostasis. Am. J Physiol. 2014;307(6):R585‐R596. 10.1152/ajpregu.00096.2014. - DOI - PMC - PubMed
    1. Carr RD, Larsen MO, Jelic K, et al. Secretion and dipeptidyl peptidase‐4‐mediated metabolism of incretin hormones after a mixed meal or glucose ingestion in obese compared to lean, nondiabetic men. J Clin Endocrinol Metab. 2010;95(2):872‐878. 10.1210/jc.2009-2054. - DOI - PubMed
    1. Greiner TU, Bäckhed F. Microbial regulation of GLP‐1 and L‐cell biology. Mol Metab. 2016;5(9):753‐758. 10.1016/j.molmet.2016.05.012. - DOI - PMC - PubMed
    1. Seganfredo FB, Blume CA, Moehlecke M, et al. Weight‐loss interventions and gut microbiota changes in overweight and obese patients: a systematic review. Obes Rev. 2017;18(8):832‐851. 10.1111/obr.12541. - DOI - PubMed

Publication types

MeSH terms

Substances