title: Enterotype May Drive the Dietary-Associated Cardiometabolic Risk Factors.
abstract: Analyses of typical bacterial clusters in humans named enterotypes may facilitate understanding the host differences in the cardiometabolic profile. It stills unknown whether the three previously described enterotypes were present in populations living below the equator. We examined how the identification of enterotypes could be useful to explain the dietary associations with cardiometabolic risk factors in Brazilian subjects. In this cross-sectional study, a convenience sample of 268 adults (54.2% women) reported their dietary habits and had clinical and biological samples collected. In this study, we analyzed biochemical data and metagenomics of fecal microbiota (16SrRNA sequencing, V4 region). Continuous variables were compared using ANOVA, and categorical variables using chi-square test. Vsearch clustered the operational taxonomic units, and Silva Database provided the taxonomic signatures. Spearman coefficient was used to verify the correlation between bacteria abundances within each enterotype. One hundred subjects were classified as omnivore, 102 lacto-ovo-vegetarians, and 66 strict vegetarians. We found the same structure as the three previously described enterotypes: 111 participants were assigned toBacteroides, 55 toPrevotella, and 102 toRuminococcaceaeenterotype. ThePrevotellacluster contained higher amount of strict vegetarians individuals than the other enterotypes (40.0 vs. 20.7 and 20.6,p= 0.04). Subjects in this enterotype had a similar anthropometric profile but a lower mean LDL-c concentration than theBacteroidesenterotype (96 ± 23 vs. 109 ± 32 mg/dL,p= 0.04). We observed significant correlations between bacterial abundances and cardiometabolic risk factors, but coefficients differed depending on the enterotype. InPrevotellaenterotype,Eubacterium ventriosum(r BMI = -0.33,p= 0.03, and r HDL-c = 0.33,p= 0.04),Akkermansia(r 2h glucose = -0.35,p= 0.02),Roseburia(r BMI = -0.36,p= 0.02 and r waist = -0.36,p= 0.02), andFaecalibacterium(r insulin = -0.35,p= 0.02) abundances were associated to better cardiometabolic profile. The three enterotypes previously described are present in Brazilians, supporting that those bacterial clusters are not population-specific. Diet-independent lower LDL-c levels in subjects fromPrevotellathan in other enterotypes suggest that a protective bacterial cluster in the former should be driving this association. Enterotypes seem to be useful to understand the impact of daily diet exposure on cardiometabolic risk factors. Prospective studies are needed to confirm their utility for predicting phenotypes in humans.
authors.affiliation: Department of Epidemiology, School of Public Health, University of São Paulo São Paulo, Brazil.
authors.forename: Ana C F
authors.initials: AC
authors.lastname: de Moraes
authors.affiliation: René Rachou Research Center, Oswaldo Cruz Foundation Belo Horizonte, Brazil.
authors.forename: Gabriel R
authors.initials: GR
authors.lastname: Fernandes
authors.affiliation: Department of Epidemiology, School of Public Health, University of São Paulo São Paulo, Brazil.
authors.forename: Isis T
authors.initials: IT
authors.lastname: da Silva
authors.affiliation: Department of Preventive Medicine, Federal University of São Paulo São Paulo, Brazil.
authors.forename: Bianca
authors.initials: B
authors.lastname: Almeida-Pititto
authors.affiliation: Laboratory of Genetics and Molecular Cardiology, Heart Institute (Incor), University of São Paulo Medical School São Paulo, Brazil.
authors.forename: Everton P
authors.initials: EP
authors.lastname: Gomes
authors.affiliation: Laboratory of Genetics and Molecular Cardiology, Heart Institute (Incor), University of São Paulo Medical School São Paulo, Brazil.
authors.forename: Alexandre da Costa
authors.initials: AD
authors.lastname: Pereira
authors.affiliation: Department of Epidemiology, School of Public Health, University of São Paulo São Paulo, Brazil.
authors.forename: Sandra R G
authors.initials: SR
authors.lastname: Ferreira
mesh_terms: D000328:Adult; D001419:Bacteria / Q000145:classification / Q000235:genetics; D001938:Brazil / Q000453:epidemiology; D002318:Cardiovascular Diseases / Q000453:epidemiology*; D008078:Cholesterol, LDL / Q000097:blood*; D003430:Cross-Sectional Studies; D004269:DNA, Bacterial / Q000737:chemistry / Q000235:genetics; D004275:DNA, Ribosomal / Q000737:chemistry / Q000235:genetics; D005247:Feeding Behavior; D005260:Female; D000069196:Gastrointestinal Microbiome; D006801:Humans; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies; D012336:RNA, Ribosomal, 16S / Q000235:genetics; D012307:Risk Factors; D017422:Sequence Analysis, DNA
chemical_list: D008078:Cholesterol, LDL; D004269:DNA, Bacterial; D004275:DNA, Ribosomal; D012336:RNA, Ribosomal, 16S
keywords: cardiometabolic risk; diet; enterotype; gut microbiota; lipid profile