Gut microbiota composition and arterial stiffness measured by pulse wave velocity: case-control study protocol (MIVAS study)

Rita Salvado, Sandra Santos-Minguez, Cristina Agudo-Conde, Cristina Lugones-Sanchez, Angela Cabo-Laso, Jesus Mª Hernandez-Sanchez, Rocio Benito, Emiliano Rodriguez-Sanchez, Manuel A Gomez-Marcos, Jesus M Hernandez-Rivas, Pedro Guimarães Cunha, Luis Garcia-Ortiz, Mivas Investigators, Rita Salvado, Sandra Santos-Minguez, Cristina Agudo-Conde, Cristina Lugones-Sanchez, Angela Cabo-Laso, Jesus Mª Hernandez-Sanchez, Rocio Benito, Emiliano Rodriguez-Sanchez, Manuel A Gomez-Marcos, Jesus M Hernandez-Rivas, Pedro Guimarães Cunha, Luis Garcia-Ortiz, Mivas Investigators

Abstract

Introduction: Intestinal microbiota is arising as a new element in the physiopathology of cardiovascular diseases. A healthy microbiota includes a balanced representation of bacteria with health promotion functions (symbiotes). The aim of this study is to analyse the relationship between intestinal microbiota composition and arterial stiffness.

Methods and analysis: An observational case-control study will be developed. Cases will be defined by the presence of at least one of the following: carotid-femoral pulse wave velocity (cf-PWV), Cardio-Ankle Vascular Index (CAVI), brachial ankle pulse wave velocity (ba or ba-PWV) above the 90th percentile, for age and sex, of the reference population. Controls will be selected from the same population as cases. The study will be developed in Primary Healthcare Centres. We will select 500 subjects (250 cases and 250 controls), between 45 and 74 years of age. Cases will be selected from a database that combines data from EVA study (Spain) and Guimarães/Vizela study (Portugal).

Measurements: cf-PWV will be measured using the SphygmoCor system, CAVI, ba-PWV and Ankle-Brachial Index will be determined using VaSera device. Gut microbiome composition in faecal samples will be determined by 16S ribosomal RNA sequencing. Lifestyle will be assessed by food frequency questionnaire, adherence to the Mediterranean diet and IPAQ (International Physical Activity Questionnaire). Body composition will be evaluated by bioimpedance.

Ethics and dissemination: The study has been approved by 'Committee of ethics of research with medicines of the health area of Salamanca' on 14 December 2018 (cod. 2018-11-136) and the 'Ethics committee for health of Guimaraes' (Portugal) on 15 October 2019 (ref: 67/2019). All study participants will sign an informed consent form agreeing to participate in the study, in compliance with the Declaration of Helsinki and the WHO standards for observational studies. The results of this study will allow a better description of gut microbiota in patients with arterial stiffness.

Trial registration details: ClinicalTrials.gov, identifier NCT03900338.

Keywords: microbiology; preventive medicine; protocols & guidelines; vascular medicine.

Conflict of interest statement

Competing interests: None declared.

© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Figures

Figure 1
Figure 1
Study flow chart. cf-PWV, carotid-femoral PWV; CAVI, Cardio-Ankle VascularIndex; ba-PWV, brachial-ankle PWV; PWV, pulse wave velocity.

References

    1. Piepoli MF, Hoes AW, Agewall S. European guidelines on cardiovascular disease prevention in clinical practiceThe sixth joint Task force of the European Society of cardiology and other societies on cardiovascular disease prevention in clinical practice (constituted by representative. Eur Heart J 2016;2016:2315–81.
    1. Vlachopoulos C, Xaplanteris P, Aboyans V, et al. . The role of vascular biomarkers for primary and secondary prevention. A position paper from the European Society of cardiology Working group on peripheral circulation: endorsed by the association for research into arterial structure and physiology (artery) Society. Atherosclerosis 2015;241:507–32. 10.1016/j.atherosclerosis.2015.05.007
    1. Vlachopoulos C, Aznaouridis K, Stefanadis C. Prediction of cardiovascular events and all-cause mortality with arterial stiffness: a systematic review and meta-analysis. J Am Coll Cardiol 2010;55:1318–27. 10.1016/j.jacc.2009.10.061
    1. Vlachopoulos C, Aznaouridis K, Stefanadis C. Aortic stiffness for cardiovascular risk prediction. J Am Coll Cardiol 2014;63:647–9. 10.1016/j.jacc.2013.10.040
    1. Laurent S, Marais L, Boutouyrie P. The noninvasive assessment of vascular aging. Can J Cardiol 2016;32:669–79. 10.1016/j.cjca.2016.01.039
    1. The Reference Values for Arterial Stiffness' Collaboration . Determinants of pulse wave velocity in healthy people and in the presence of cardiovascular risk factors: ‘establishing normal and reference values’. Eur Heart J 2010;31:2338–50. 10.1093/eurheartj/ehq165
    1. Shirai K, Hiruta N, Song M, et al. . Cardio-ankle vascular index (CAVI) as a novel indicator of arterial stiffness: theory, evidence and perspectives. J Atheroscler Thromb 2011;18:924–38. 10.5551/jat.7716
    1. Munakata M. Brachial-ankle pulse wave velocity in the measurement of arterial stiffness: recent evidence and clinical applications. Curr Hypertens Rev 2014;10:49–57. 10.2174/157340211001141111160957
    1. Kashtanova D, Tkacheva O, Popenko A, et al. . Gut microbiota and vascular biomarkers in patients without clinical cardiovascular diseases. Artery Res 2017;18:41–8. 10.1016/j.artres.2017.02.007
    1. Marques FZ, Mackay CR, Kaye DM. Beyond gut feelings: how the gut microbiota regulates blood pressure. Nat Rev Cardiol 2018;15:20–32. 10.1038/nrcardio.2017.120
    1. Boulangé CL, Neves AL, Chilloux J, et al. . Impact of the gut microbiota on inflammation, obesity, and metabolic disease. Genome Med 2016;8:42. 10.1186/s13073-016-0303-2
    1. Blandino G, Inturri R, Lazzara F. Impact of gut microbiota on diabetes mellitus. Diabetes and Metabolism: Elsevier Masson, 2016: 303–15.
    1. Suez J, Korem T, Zeevi D, et al. . Artificial sweeteners induce glucose intolerance by altering the gut microbiota. Nature 2014;514:181–6. 10.1038/nature13793
    1. Chassaing B, Koren O, Goodrich JK, et al. . Dietary emulsifiers impact the mouse gut microbiota promoting colitis and metabolic syndrome. Nature 2015;519:92–6. 10.1038/nature14232
    1. Schnorr SL, Candela M, Rampelli S, et al. . Gut microbiome of the Hadza hunter-gatherers. Nat Commun 2014;5:3654. 10.1038/ncomms4654
    1. Hung S-C, Yang T-M, Tarng D-C. SP260HIGH salt diet alters gut microbiota leading to inflammation and progression of CKD. Nephrology Dialysis Transplantation 2017;32:iii194–iii94. 10.1093/ndt/gfx145.SP260
    1. Wu H, Tremaroli V, Bäckhed F. Linking microbiota to human diseases: a systems biology perspective. Trends Endocrinol Metab 2015;26:758–70. 10.1016/j.tem.2015.09.011
    1. David LA, Maurice CF, Carmody RN, et al. . Diet rapidly and reproducibly alters the human gut microbiome. Nature 2014;505:559–63. 10.1038/nature12820
    1. Wu GD, Chen J, Hoffmann C, et al. . Linking long-term dietary patterns with gut microbial enterotypes. Science 2011;334:105–8. 10.1126/science.1208344
    1. Hall AB, Tolonen AC, Xavier RJ. Human genetic variation and the gut microbiome in disease. Nat Rev Genet 2017;18:690–9. 10.1038/nrg.2017.63
    1. Yiu JHC, Dorweiler B, Woo CW. Interaction between gut microbiota and Toll-like receptor: from immunity to metabolism. J Mol Med 2017;95:13–20. 10.1007/s00109-016-1474-4
    1. Cox AJ, West NP, Cripps AW. Obesity, inflammation, and the gut microbiota. Lancet Diabetes Endocrinol 2015;3:207–15. 10.1016/S2213-8587(14)70134-2
    1. Qi J, You T, Li J, et al. . Circulating trimethylamine N-oxide and the risk of cardiovascular diseases: a systematic review and meta-analysis of 11 prospective cohort studies. J Cell Mol Med 2018;22:185–94. 10.1111/jcmm.13307
    1. Tang WHW, Wang Z, Levison BS, et al. . Intestinal microbial metabolism of phosphatidylcholine and cardiovascular risk. N Engl J Med 2013;368:1575–84. 10.1056/NEJMoa1109400
    1. Cho CE, Taesuwan S, Malysheva OV. Trimethylamine- N -oxide (TMAO) response to animal source foods varies among healthy young men and is influenced by their gut microbiota composition: A randomized controlled trial. Mol Nutr Food Res 2017;61:1600324. 10.1002/mnfr.201600324
    1. Gomez-Marcos MA, Martinez-Salgado C, Gonzalez-Sarmiento R, et al. . Association between different risk factors and vascular accelerated ageing (EVA study): study protocol for a cross-sectional, descriptive observational study. BMJ Open 2016;6:e011031. 10.1136/bmjopen-2016-011031
    1. Cunha PG, Cotter J, Oliveira P, et al. . The Rationale/Design of the Guimarães/Vizela study. Journal of Investigative Medicine 2014;62:813–20. 10.2310/JIM.0000000000000069
    1. Williams B, Mancia G, Spiering W, et al. . 2018 ESC/ESH guidelines for the management of arterial hypertension. Eur Heart J 2018;39:3021–104. 10.1093/eurheartj/ehy339
    1. Schröder H, Fitó M, Estruch R, et al. . A short screener is valid for assessing Mediterranean diet adherence among older Spanish men and women. J Nutr 2011;141:1140–5. 10.3945/jn.110.135566
    1. Recio-Rodriguez JI, Gómez-Marcos MA, Agudo-Conde C, et al. . Evident 3 study: a randomized, controlled clinical trial to reduce inactivity and caloric intake in sedentary and overweight or obese people using a smartphone application: study protocol. Medicine 2018;97:e9633. 10.1097/MD.0000000000009633
    1. Martin-Moreno JM, Boyle P, Gorgojo L, et al. . Development and validation of a food frequency questionnaire in Spain. Int J Epidemiol 1993;22:512–9. 10.1093/ije/22.3.512
    1. Pedro Moreira DS. Maria Daniel Vaz de Almeida. Validade relativa de um questionário de frequ|encia alimentar através dA comparação CoM um registo alimentar de quatro dias. Acta Médica Portuguesa 2003;16:412–20.
    1. Craig CL, Marshall AL, Sjöström M, et al. . International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 2003;35:1381–95. 10.1249/01.MSS.0000078924.61453.FB
    1. Marshall AL, Miller YD, Burton NW, et al. . Measuring total and domain-specific sitting: a study of reliability and validity. Med Sci Sports Exerc 2010;42:1094–102. 10.1249/MSS.0b013e3181c5ec18
    1. Klindworth A, Pruesse E, Schweer T, et al. . Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res 2013;41:e1. 10.1093/nar/gks808
    1. Yang B, Wang Y, Qian P-Y. Sensitivity and correlation of hypervariable regions in 16S rRNA genes in phylogenetic analysis. BMC Bioinformatics 2016;17:135. 10.1186/s12859-016-0992-y
    1. Gohl D, Gohl DM, MacLean A, et al. . An optimized protocol for high-throughput amplicon-based microbiome profiling. Protoc Exch 2016. 10.1038/protex.2016.030
    1. Edgar RC, Haas BJ, Clemente JC, et al. . UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 2011;27:2194–200. 10.1093/bioinformatics/btr381
    1. Reference Values for Arterial Stiffness' Collaboration . Determinants of pulse wave velocity in healthy people and in the presence of cardiovascular risk factors: 'establishing normal and reference values'. Eur Heart J 2010;31:2338–50. 10.1093/eurheartj/ehq165
    1. Shirai K, Utino J, Otsuka K, et al. . A novel blood pressure-independent arterial wall stiffness parameter; cardio-ankle vascular index (CAVI). J Atheroscler Thromb 2006;13:101–7. 10.5551/jat.13.101
    1. Yamashina A, Tomiyama H, Takeda K, et al. . Validity, reproducibility, and clinical significance of noninvasive brachial-ankle pulse wave velocity measurement. Hypertens Res 2002;25:359–64. 10.1291/hypres.25.359
    1. Kawai T, Ohishi M, Onishi M, et al. . Cut-Off value of brachial-ankle pulse wave velocity to predict cardiovascular disease in hypertensive patients: a cohort study. J Atheroscler Thromb 2013;20:391–400. 10.5551/jat.15040
    1. García-Ortiz L, Recio-Rodríguez JI, Agudo-Conde C, et al. . Noninvasive validation of central and peripheral augmentation index estimated by a novel wrist-worn tonometer. J Hypertens 2018;36:2204–14. 10.1097/HJH.0000000000001806
    1. Levey AS, Stevens LA, Schmid CH, et al. . A new equation to estimate glomerular filtration rate. Ann Intern Med 2009;150:604–12. 10.7326/0003-4819-150-9-200905050-00006
    1. Delgado C, Araneda A, Behrens MI. Validation of the Spanish-language version of the Montreal cognitive assessment test in adults older than 60 years. Neurologia 2019;34:376–85. 10.1016/j.nrl.2017.01.013
    1. Freitas S, Simões MR, Alves L, et al. . Montreal cognitive assessment (MoCA): validation study for vascular dementia. J Int Neuropsychol Soc 2012;18:1031–40. 10.1017/S135561771200077X
    1. Harris PA, Taylor R, Thielke R, et al. . Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009;42:377–81. 10.1016/j.jbi.2008.08.010
    1. van den Munckhof ICL, Kurilshikov A, Ter Horst R, et al. . Role of gut microbiota in chronic low-grade inflammation as potential driver for atherosclerotic cardiovascular disease: a systematic review of human studies. Obes Rev 2018;19:1719–34. 10.1111/obr.12750
    1. Menni C, Lin C, Cecelja M, et al. . Gut microbial diversity is associated with lower arterial stiffness in women. Eur Heart J 2018;39:2390–7. 10.1093/eurheartj/ehy226
    1. Kashtanova DA, Tkacheva ON, Doudinskaya EN, et al. . Gut microbiota in patients with different metabolic statuses: Moscow study. Microorganisms 2018;6. 10.3390/microorganisms6040098

Source: PubMed

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