Federica Del Chierico1, Melania Manco2, Simone Gardini3, Valerio Guarrasi3,4, Alessandra Russo5, Marzia Bianchi6, Valentina Tortosa1, Andrea Quagliariello1, Blegina Shashaj6, Danilo Fintini7, Lorenza Putignani8. 1. Unit of Human Microbiome, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy. 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@opbg.net. 3. GenomeUp SRL, Rome, Italy. 4. Department of Computer, Control, and Management Engineering Antonio Ruberti, Sapienza University, Rome, Italy. 5. Unit of Parasitology, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy. 6. Research Area for Multifactorial Diseases and Complex Phenotypes, Obesity and Diabetes, Bambino Gesù Children's Hospital, IRCCS, Via Ferdinando Baldelli 38, 00146, Rome, Italy. 7. Endocrinology Unit, Bambino Gesù Children's Hospital, IRCCS, Palidoro, Rome, Italy. 8. Unit of Parasitology and Unit of Human Microbiome, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy.
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.
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.
Authors: Brian V Jones; Máire Begley; Colin Hill; Cormac G M Gahan; Julian R Marchesi Journal: Proc Natl Acad Sci U S A Date: 2008-08-29 Impact factor: 11.205
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