Gut Microbiome Associates With Lifetime Cardiovascular Disease Risk Profile Among Bogalusa Heart Study Participants
Open accessAbstract
Rationale: Few studies have systematically assessed the influence of gut microbiota on cardiovascular disease (CVD) risk. Objective: To examine the association between gut microbiota and lifetime CVD risk profile among 55 Bogalusa Heart Study participants with the highest and 57 with the lowest lifetime burdens of CVD risk factors. Methods and Results: 16S ribosomal RNA sequencing was conducted on microbial DNA extracted from stool samples of the Bogalusa Heart Study participants. α Diversity, including measures of richness and evenness, and individual genera were tested for associations with lifetime CVD risk profile. Multivariable regression techniques were used to adjust for age, sex, and race (model 1), along with body mass index (model 2) and both body mass index and diet (model 3). In model 1, odds ratios (95% confidence intervals) for each SD increase in richness, measured by the number of observed operational taxonomic units, Chao 1 index, and abundance-based coverage estimator, were 0.62 (0.39–0.99), 0.61 (0.38–0.98), and 0.63 (0.39–0.99), respectively. Associations were consistent in models 2 and 3. Four genera were enriched among those with high versus low CVD risk profile in all models. Model 1 P values were 2.12×10 −3 , 7.95×10 −5 , 4.39×10 −4 , and 1.51×10 −4 for Prevotella 2, Prevotella 7 , Tyzzerella , and Tyzzerella 4 , respectively. Two genera were depleted among those with high versus low CVD risk profile in all models. Model 1 P values were 2.96×10 −6 and 1.82×10 −4 for Alloprevotella and Catenibacterium , respectively. Conclusions: The current study identified associations of overall microbial richness and 6 microbial genera with lifetime CVD risk.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Tyzzerella can form spores and is associated with coronary heart disease.
“Tyzzerella can form spores and is associated with coronary heart disease (Kelly et al., 2016).”
From <i>Akkermansia muciniphila</i> alleviates <scp>high‐fat‐diet</scp> ‐related metabolic‐associated fatty liver disease by modulating gut microbiota and bile acids (2023) · cites this paper as Kelly et al., 2016
The Results and Discussion (page numbers unavailable) report that Tyzzerella was enriched among Bogalusa Heart Study participants with a high lifetime cardiovascular disease risk profile. They do not establish an association with diagnosed coronary heart disease or say that Tyzzerella can form spores; searches for spore formation and coronary heart disease found no supporting passage. (LLM, conf=0.90)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 41 · Cited by 345
Research works printed but not linked: 34
- [1]Weinstock GM Genomic approaches to studying the human microbiota Nature 2012 489 250 256 22972298 PMC3665339
- [2]Kuczynski J Lauber CL Walters WA Parfrey LW Clemente JC Gevers D Knight R Experimental and analytical tools for studying the human microbiome Nat Rev Genet 2012 13 47 58 22179717 PMC5119550
- [3]Turnbaugh PJ Ley RE Mahowald MA Magrini V Mardis ER Gordon JI An obesity-associated gut microbiome with increased capacity for energy harvest Nature 2006 444 1027 1031 17183312
- [4]Joyce S MacSharry J Casey P Kinsella M Murphy E Shanahan F Hill C Gahan C Regulation of host weight gain and lipid metabolism by bacterial bile acid modification in the gut Proc Natl Acad Sci U S A 2014 111 7421 7426 24799697 PMC4034235
- [5]Cani PD Amar J Iglesias MA Metabolic endotoxemia initiates obesity and insulin resistance Diabetes 2007 56 1761 1772 17456850
- [6]Moran CP Shanahan F Gut microbiota and obesity: Role in aetiology and potential therapeutic target Baillieres Best Pract Res Clin Gastroenterol 2014 28 585 597 25194177
- [7]Turnbaugh PJ Hamady M Yatsunenko T A core gut microbiome in obese and lean twins Nature 2009 457 480 484 19043404 PMC2677729
- [8]Tilg H Moschen AR Microbiota and diabetes: An evolving relationship Gut 2014 63 1513 1521 24833634
- [12]Zhang AQ Mitchell SC Smith RL Dietary precursors to trimethylamine in man: a pilot study Food Chem Toxicol 1999 37 515 520 10456680
- [15]Dolphin CT Janmohamed A Smith RL Shephard EA Phillips IR Missense mutation in the flavin-containing mono-oxygenase 3 gene, FMO3, underlies fish-odour syndrome Nat Genet 1997 17 491 494 9398858
- [16]Foster TA Berenson GS Measurement error and reliability in four pediatric cross-sectional surveys of cardiovascular disease risk factor variables--the bogalusa heart study J Chronic Dis 1987 40 13 21 3492509
- [17]Foster TA Webber LS Srinivasan SR Voors AW Berenson GS Measurement error of risk factor variables in an epidemiologic study of children-the bogalusa heart study J Chronic Dis 1980 33 661 672 6967874
- [18]Rockett HR Breitenbach M Frazier AL Witschi J Wolf AM Field AE Colditz GA Validation of a youth/adolescent food frequency questionnaire Prev Med 1997 26 808 816 9388792
- [19]Bucolo G David H Quantitative determination of serum triglycerides by the use of enzymes Clin Chem 1973 19 476 482 4703655
- [20]Srinivasan SR Berenson GS Serum lipoproteins in children and methods for study Lewis LA CRC handbook of electrophoresis. Vol. 3. Lipoprotein methodology and human studies Boca Raton, Fla CRC Press 1983 185 203
- [21]Human Microbiome Project A framework for human microbiome research Nature 2012 486 215 221 22699610 PMC3377744
- [22]Human Microbiome Project Structure, function and diversity of the healthy human microbiome Nature 2012 486 207 214 22699609 PMC3564958
- [23]Caporaso JG Lauber CL Walters WA Berg-Lyons D Huntley J Fierer N Owens SM Betley J Fraser L Bauer M Gormley N Gilbert JA Smith G Knight R Ultra-high-throughput microbial community analysis on the illumina hiseq and miseq platforms ISME J 2012 6 1621 1624 22402401 PMC3400413
- [24]Edgar RC Search and clustering orders of magnitude faster than blast Bioinformatics 2010 26 2460 2461 20709691
- [25]Caporaso JG Kuczynski J Stombaugh J Qiime allows analysis of high-throughput community sequencing data Nat Methods 2010 7 335 336 20383131 PMC3156573
- [26]Quast C Pruesse E Yilmaz P Gerken J Schweer T Yarza P Peplies J Glockner FO The silva ribosomal rna gene database project: Improved data processing and web-based tools Nucleic Acids Res 2013 41 D590 596 23193283 PMC3531112
- [27]Lozupone CA Knight R Species divergence and the measurement of microbial diversity FEMS Microbiol Rev 2008 32 557 578 18435746 PMC2443784
- [28]McMurdie PJ Holmes S Phyloseq: An r package for reproducible interactive analysis and graphics of microbiome census data PLoS ONE 2013 8 e61217 23630581 PMC3632530
- [30]Xu L Paterson AD Turpin W Xu W Assessment and selection of competing models for zero-inflated microbiome data PLoS ONE 2015 10 e0129606 26148172 PMC4493133
- [31]Willet WC Howe GR Kushi LH Adjustment of total energy intake in epidemiologic studies Am J Clin Nutr 1997 65 1220S 1228S 9094926
- [33]Lambeth SM Carson T Lowe J Ramaraj T Leff JW Luo L Bell CJ Shah VO Composition, diversity, and abundance of gut microbiome in prediabetes and type 2 diabetes J Diabetes Obes 2015 2 1 7 26756039 PMC4705851
- [34]Sepp E Kolk H Loivukene K Mikelsaar M Higher blood glucose level associated with body mass index and gut microbiota in elderly people Microb Ecol Health Dis 2014 25 PMC4048595 24936169
- [36]Zhang H DiBaise JK Zuccolo A Kudrna D Braidotti M Yu Y Parameswaran P Crowell MD Wing R Rittmann BE Krajmalnik-Brown R Human gut microbiota in obesity and after gastric bypass Proc Natl Acad Sci U S A 2009 106 2365 2370 19164560 PMC2629490
- [37]Fugmann M Breier M Rottenkolber M Banning F Ferrari U Sacco V Grallert H Parhofer KG Seissler J Clavel T Lechner A The stool microbiota of insulin resistant women with recent gestational diabetes, a high risk group for type 2 diabetes Sci Rep 2015 5 13212 26279179 PMC4538691
- [38]Alkanani AK Hara N Gottlieb PA Ir D Robertson CE Wagner BD Frank DN Zipris D Alterations in intestinal microbiota correlate with susceptibility to type 1 diabetes Diabetes 2015 64 3510 3520 26068542 PMC4587635
- [39]Larsen N Vogensen FK van den Berg FWJ Nielsen DS Andreasen AS Pedersen BK Al-Soud WA Sorensen SJ Hansen LH Jakobsen M Gut microbiota in human adults with type 2 diabetes differs from non-diabetic adults PLoS ONE 2010 5 e9085 20140211 PMC2816710
- [40]Zhang X Shen D Fang Z Jie Z Qiu X Zhang C Chen Y Ji L Human gut microbiota changes reveal the progression of glucose intolerance PLoS ONE 2013 8 e71108 24013136 PMC3754967
- [41]Fei N Zhao L An opportunistic pathogen isolated from the gut of an obese human causes obesity in germfree mice ISME J 2013 7 880 884 23235292 PMC3603399
- [42]Million M Lagier JC Yahav D Paul M Gut bacterial microbiota and obesity Clin Microbiol Infect 2013 19 305 313 23452229
- Authors
- Kelly, T. N., Bazzano, L. A., Ajami, N. J., He, H., Zhao, J., Petrosino, J. F., Correa, A., & He, J.
- Affiliations
- Tulane University (US)
- ORCID
- Venue
- Circulation Research
- Published
- 2016-09-30
- Volume
- 119
- Issue
- 8
- Pages
- 956-964
- ISSN
- 0009-7330 (ISSN-L)
- 1524-4571
- PMC
- PMC5045790
- OpenAlex
- W2506779819
- Cited by
- 345
- References
- 41
- Citations by year
- 2026: 17 · 2025: 28 · 2024: 34 · 2023: 36 · 2022: 65 · 2021: 47 · 2020: 40 · 2019: 29 · 2018: 30 · 2017: 17 · 2016: 2
- FWCI
- 13.52
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Circulation Research (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Aging (RF1AG041200, R21AG051914, R01AG041200)
- National Institute of General Medical Sciences (P20GM109036)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
- Keywords
- gut microbiota, cardiovascular risk, lifetime cardiovascular risk, microbial diversity, Prevotella, Tyzzerella, Alloprevotella, Catenibacterium, Bogalusa Heart Study, body mass index, diet, 16S rRNA gene sequencing
- MeSH terms
- Gastrointestinal Microbiome, Adolescent, Adult, Cardiovascular Diseases, Child, Child, Preschool, Female, Humans, Longitudinal Studies, Louisiana, Male, Middle Aged, Risk Factors, RNA, Ribosomal, 16S, Cohort Studies, Young Adult
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review