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Fecal microbiota signatures of insulin resistance, inflammation, and metabolic syndrome in youth with obesity: a pilot study

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Abstract

Aims

To identify fecal microbiota profiles associated with metabolic abnormalities belonging to the metabolic syndrome (MS), high count of white blood cells (WBCs) and insulin resistance (IR).

Methods

Sixty-eight young patients with obesity were stratified for percentile distribution of MS abnormalities. A MS risk score was defined as low, medium, and high MS risk. High WBCs were defined as a count ≥ 7.0 103/µL; severe obesity as body mass index Z-score ≥ 2 standard deviations; IR as homeostatic assessment model algorithm of IR (HOMA) ≥ 3.7. Stool samples were analyzed by 16S rRNA-based metagenomics.

Results

We found reduced bacterial richness of fecal microbiota in patients with IR and high diastolic blood pressure (BP). Distinct microbial markers were associated to high BP (Clostridium and Clostridiaceae), low high-density lipoprotein cholesterol (Lachnospiraceae, Gemellaceae, Turicibacter), and high MS risk (Coriobacteriaceae), WBCs (Bacteroides caccae, Gemellaceae), severe obesity (Lachnospiraceae), and impaired glucose tolerance (Bacteroides ovatus and Enterobacteriaceae). Conversely, taxa such as Faecalibacterium prausnitzii, Parabacterodes, Bacteroides caccae, Oscillospira, Parabacterodes distasonis, Coprococcus, and Haemophilus parainfluenzae were associated to low MS risk score, triglycerides, fasting glucose and HOMA-IR, respectively. Supervised multilevel analysis grouped clearly “variable” patients based on the MS risk.

Conclusions

This was a proof-of-concept study opening the way at the identification of fecal microbiota signatures, precisely associated with cardiometabolic risk factors in young patients with obesity. These evidences led us to infer, while some gut bacteria have a detrimental role in exacerbating metabolic risk factors some others are beneficial ameliorating cardiovascular host health.

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Availability of data and materials

Sequencing reads and the associated metadata are available at BioProject database of NCBI (PRJNA356507 and PRJNA280490) (https://www.ncbi.nlm.nih.gov/bioproject/).

Abbreviations

2HPG:

2H plasma glucose

ALT:

Alanine aminotransferase

AST:

Aspartate aminotransferase

BMI:

Body mass index

CVD:

Cardiovascular disease

DBP:

Diastolic blood pressures

HbA1c:

Hemoglobin A1c

HDL-C:

High-density lipoprotein cholesterol

HFD:

High-fat diet

HOMA-IR:

Homeostatic assessment model algorithm of insulin resistance

IGT:

Impaired glucose tolerance

IQR:

Interquartile range

IR:

Insulin resistance

LDA:

Linear discriminant analysis

LEfSe:

Linear discriminant analysis effect size

MS:

Metabolic syndrome

NAST:

Nearest Alignment Space Termination

NGT:

Normal glucose tolerance

OPBG:

''Bambino Gesù'' Children’s Hospital

OTUs:

Operational taxonomic units

PCA:

Principal component analysis

PCoA:

Principal coordinate analysis

PLS:

Sparse partial least squares

QIIME:

Quantitative Insights Into Microbial Ecology

SBP:

Systolic blood pressures

SDS:

Standard deviation score

T2D:

Type 2 diabetes

WBCs:

White blood cells

γ-GT:

γ-Glutamyl transferase

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Acknowledgments

None.

Funding

This work was supported by the European Commission under the 7th FP_Information Communication Technologies Programme_MD-Paedigree, Model Driven Paediatric European Digital Repository, (Grant Agreement No. 600932).

Author information

Authors and Affiliations

  1. Unit of Human Microbiome, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy

    Federica Del Chierico, Valentina Tortosa & Andrea Quagliariello

  2. Research Area for Multifactorial Diseases and Complex Phenotypes, Obesity and Diabetes, Bambino Gesù Children’s Hospital, IRCCS, Via Ferdinando Baldelli 38, 00146, Rome, Italy

    Melania Manco, Marzia Bianchi & Blegina Shashaj

  3. GenomeUp SRL, Rome, Italy

    Simone Gardini & Valerio Guarrasi

  4. Department of Computer, Control, and Management Engineering Antonio Ruberti, Sapienza University, Rome, Italy

    Valerio Guarrasi

  5. Unit of Parasitology, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy

    Alessandra Russo

  6. Endocrinology Unit, Bambino Gesù Children’s Hospital, IRCCS, Palidoro, Rome, Italy

    Danilo Fintini

  7. Unit of Parasitology and Unit of Human Microbiome, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy

    Lorenza Putignani

Authors
  1. Federica Del Chierico
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Contributions

Conceptualization, Melania Manco; Data curation, Marzia Bianchi; Formal analysis, Federica Del Chierico, Valentina Tortosa and Andrea Quagliariello, Simone Gardini, Valerio Guarrasi; Funding acquisition, Melania Manco; Investigation, Alessandra Russo, Blegina Shashaj and Danilo Fintini; Methodology, Alessandra Russo; Project administration, Marzia Bianchi; Resources, Danilo Fintini and Lorenza Putignani; Software, Valentina Tortosa, Andrea Quagliariello, Simone Gardini, Valerio Guarrasi; Supervision, Lorenza Putignani; Writing – original draft, Federica Del Chierico and Melania Manco; Writing – review & editing, Federica Del Chierico, Melania Manco, Alessandra Russo, Marzia Bianchi, Valentina Tortosa, Andrea Quagliariello, Simone Gardini, Valerio Guarrasi, Blegina Shashaj, Danilo Fintini and Lorenza Putignani. All authors had final approval of the submitted and published versions.

Corresponding author

Correspondence to Melania Manco.

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Conflict of interest

The authors have declared no conflict of interest.

Ethics approval

The study was approved by the OPBG ethical committee (protocol #615/2013) and was conducted in accordance with the Principles of Good Clinical Practice and the Declaration of Helsinki.

Informed consent

Written informed consent was obtained from all participants.

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This article belongs to the topical collection Gut Microbiome and Metabolic Disorders, managed by Massimo Federici.

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Del Chierico, F., Manco, M., Gardini, S. et al. Fecal microbiota signatures of insulin resistance, inflammation, and metabolic syndrome in youth with obesity: a pilot study. Acta Diabetol 58, 1009–1022 (2021). https://doi.org/10.1007/s00592-020-01669-4

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  • DOI: https://doi.org/10.1007/s00592-020-01669-4

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