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Peer-reviewedCC BY 4.0International Journal of Molecular Sciences

Use of 16S rRNA Gut Microbiome Analysis to Identify Shared Microbial Signatures Across Metabolic Syndrome Components in Obese Subjects

  • Lorenzo Antonetti1
  • Susanna Longo1
  • Marina Cardellini1
  • Viviana Casagrande1
  • Rossella Menghini1
  • Ilaria Cicalini2,3
  • Damiana Pieragostino2,3
  • Eleonora Poggiogalle4
  • Francesco Frigerio5,6
  • Claudia Piciocchi4
  • Vincenzo De Laurenzi2,3
  • Silvia Savastano7
3 more authors
  • Lorenzo Maria Donini4
  • Geltrude Mingrone8,9,10
  • Massimo Federici1,11
11 affiliations
  1. 1Department of Systems Medicine, University of Rome Tor Vergata, 00133 Rome, Italy
  2. 2Center for Advanced Studies and Technology (CAST), ‘G. D’Annunzio’ University of Chieti-Pescara, 66013 Chieti, Italy
  3. 3Department of Innovative Technologies in Medicine and Dentistry, ‘G. D’Annunzio’ University of Chieti-Pescara, 66013 Chieti, Italy
  4. 4Department of Experimental Medicine, Sapienza University, 00185 Rome, Italy
  5. 5Department for the Promotion of Human Sciences and Quality of Life, San Raffaele Roma University, Via di Val Cannuta 247, 00166 Rome, Italy
  6. 6Laboratory of Cardiovascular Endocrinology, IRCCS San Raffaele Roma, Via di Val Cannuta 247, 00166 Rome, Italy
  7. 7Unità di Endocrinologia, Diabetologia ed Andrologia, Dipartimento di Medicina Clinica e Chirurgia, Università degli Studi di Napoli Federico II, 80131 Naples, Italy
  8. 8Università Cattolica del Sacro Cuore, 00168 Rome, Italy
  9. 9Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy
  10. 10Division of Diabetes & Nutritional Sciences, School of Cardiovascular and Metabolic Medicine & Sciences, King’s College London, London WC2R 2LS, UK
  11. 11IRCCS NeuroMED, 86077 Pozzilli, Italy
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Abstract

Gut microbiota (GM) alterations and related metabolic outputs have been implicated in metabolic syndrome (MetS) and early cardiometabolic risk. However, the associations between GM alterations and MetS, and their relationship with the marked interindividual variability in cardiovascular risk, remain incompletely defined. We conducted a cross-sectional study in individuals with obesity (n = 176) to evaluate associations between GM features and MetS clinical traits using 16S amplicon profiling data. Prevalence of individual MetS traits was 37.4% for hyperglycemia, 23.4% for hypertriglyceridemia, 54.0% for hypertension, and 52.1% for low HDL cholesterol, with 51.1% of participants meeting criteria for MetS overall. Comparative analysis of 16S rRNA amplicon sequencing data identified a shared gut microbial signature comprising 45 ASVs across MetS clinical components. Members of Prevotellaceae and Ruminococcaceae were consistently reduced in MetS, whereas Veillonella and Streptococcus were enriched. Reduced microbial alpha diversity was observed in individuals with MetS. PICRUSt2-based functional inference indicated lower representation of pathways related to complex carbohydrate utilization and short-chain fatty acid (SCFA) metabolism in MetS-positive individuals. Our results, derived from two independent datasets, indicate that MetS is associated with a depletion of bacterial taxa involved in complex carbohydrate metabolism and SCFA production.

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Cite

BibTeXRIS
BibTeX
@article{antonetti2026rrna,
  title = {{Use of 16S rRNA Gut Microbiome Analysis to Identify Shared Microbial Signatures Across Metabolic Syndrome Components in Obese Subjects}},
  author = {Lorenzo Antonetti and Susanna Longo and Marina Cardellini and Viviana Casagrande and Rossella Menghini and Ilaria Cicalini and Damiana Pieragostino and Eleonora Poggiogalle and Francesco Frigerio and Claudia Piciocchi and Vincenzo De Laurenzi and Silvia Savastano and Lorenzo Maria Donini and Geltrude Mingrone and Massimo Federici},
  journal = {International Journal of Molecular Sciences},
  year = {2026},
  month = oct,
  doi = {10.3390/ijms27219701},
  url = {https://www.mdpi.com/1422-0067/27/21/9701},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Use of 16S rRNA Gut Microbiome Analysis to Identify Shared Microbial Signatures Across Metabolic Syndrome Components in Obese Subjects
AU  - Lorenzo Antonetti
AU  - Susanna Longo
AU  - Marina Cardellini
AU  - Viviana Casagrande
AU  - Rossella Menghini
AU  - Ilaria Cicalini
AU  - Damiana Pieragostino
AU  - Eleonora Poggiogalle
AU  - Francesco Frigerio
AU  - Claudia Piciocchi
AU  - Vincenzo De Laurenzi
AU  - Silvia Savastano
AU  - Lorenzo Maria Donini
AU  - Geltrude Mingrone
AU  - Massimo Federici
PY  - 2026
DA  - 2026/10/29
JO  - International Journal of Molecular Sciences
DO  - 10.3390/ijms27219701
UR  - https://www.mdpi.com/1422-0067/27/21/9701
AB  - Gut microbiota (GM) alterations and related metabolic outputs have been implicated in metabolic syndrome (MetS) and early cardiometabolic risk. However, the associations between GM alterations and MetS, and their relationship with the marked interindividual variability in cardiovascular risk, remain incompletely defined. We conducted a cross-sectional study in individuals with obesity (n = 176) to evaluate associations between GM features and MetS clinical traits using 16S amplicon profiling data. Prevalence of individual MetS traits was 37.4% for hyperglycemia, 23.4% for hypertriglyceridemia, 54.0% for hypertension, and 52.1% for low HDL cholesterol, with 51.1% of participants meeting criteria for MetS overall. Comparative analysis of 16S rRNA amplicon sequencing data identified a shared gut microbial signature comprising 45 ASVs across MetS clinical components. Members of Prevotellaceae and Ruminococcaceae were consistently reduced in MetS, whereas Veillonella and Streptococcus were enriched. Reduced microbial alpha diversity was observed in individuals with MetS. PICRUSt2-based functional inference indicated lower representation of pathways related to complex carbohydrate utilization and short-chain fatty acid (SCFA) metabolism in MetS-positive individuals. Our results, derived from two independent datasets, indicate that MetS is associated with a depletion of bacterial taxa involved in complex carbohydrate metabolism and SCFA production.
SN  - 1422-0067
ER  -