Risk factors for Keshan disease: a prospective cohort study protocol of gut flora
Abstract Background Keshan disease is an endemic cardiomyopathy of undefined causes. Being involved in the unclear pathogenesis of Keshan disease, a clear diagnosis, and effective treatment cannot be initiated. However, the rapid development of gut flora in cardiovascular disease combined with omics...
Main Authors: | , , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2020-11-01
|
Series: | BMC Cardiovascular Disorders |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s12872-020-01765-x |
id |
doaj-e5544fb6fb514f398e39970b998e0018 |
---|---|
record_format |
Article |
spelling |
doaj-e5544fb6fb514f398e39970b998e00182020-11-25T04:02:17ZengBMCBMC Cardiovascular Disorders1471-22612020-11-012011710.1186/s12872-020-01765-xRisk factors for Keshan disease: a prospective cohort study protocol of gut floraZhenzhen Li0Jin Wei1Yanping Zhang2Gaopeng Li3Huange Zhu4Na Lei5Qian He6Yan Geng7Jianhong Zhu8Department of Clinical Laboratory, The Second Affiliated Hospital of Xi’an Jiaotong UniversityDepartment of Cardiology, The Second Affiliated Hospital of Xi’an Jiaotong UniversityDepartment of Clinical Laboratory, The Second Affiliated Hospital of Xi’an Jiaotong UniversityKey Laboratory of Synthetic and Natural Functional Molecule Chemistry of the Ministry of Education, Shaanxi Key Laboratory of Physico-Inorganic Chemistry, College of Chemistry and Materials Science, Northwest UniversityDepartment of Clinical Laboratory, The Second Affiliated Hospital of Xi’an Jiaotong UniversityDepartment of Clinical Laboratory, The Second Affiliated Hospital of Xi’an Jiaotong UniversityDepartment of Clinical Laboratory, The Second Affiliated Hospital of Xi’an Jiaotong UniversityDepartment of Clinical Laboratory, The Second Affiliated Hospital of Xi’an Jiaotong UniversityDepartment of Clinical Laboratory, The Second Affiliated Hospital of Xi’an Jiaotong UniversityAbstract Background Keshan disease is an endemic cardiomyopathy of undefined causes. Being involved in the unclear pathogenesis of Keshan disease, a clear diagnosis, and effective treatment cannot be initiated. However, the rapid development of gut flora in cardiovascular disease combined with omics and big data platforms may promote the discovery of new diagnostic markers and provide new therapeutic options. This study aims to identify biomarkers for the early diagnosis and further explore new therapeutic targets for Keshan disease. Methods This cohort study consists of two parts. Though the first part includes 300 participants, however, recruiting will be continued for the eligible participants. After rigorous screening, the blood samples, stools, electrocardiograms, and ultrasonic cardiogram data would be collected from participants to elucidate the relationship between gut flora and host. The second part includes a prospective follow-up study for every 6 months within 2 years. Finally, deep mining of big data and rapid machine learning will be employed to analyze the baseline data, experimental data, and clinical data to seek out the new biomarkers to predict the pathogenesis of Keshan disease. Discussion Our study will clarify the distribution of gut flora in patients with Keshan disease and the abundance and population changes of gut flora in different stages of the disease. Through the big data platform analyze the relationship between environmental factors, clinical factors, and gut flora, the main factors affecting the occurrence of Keshan disease were identified, and the changed molecular pathways of gut flora were predicted. Finally, the specific gut flora and molecular pathways affecting Keshan disease were identified by metagenomics combined with metabonomic analysis. Trial registration: ChiCTR1900026639. Registered on 16 October 2019.http://link.springer.com/article/10.1186/s12872-020-01765-xKeshan diseaseGut floraThe big data platformCohort studyMetabonomic analysis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zhenzhen Li Jin Wei Yanping Zhang Gaopeng Li Huange Zhu Na Lei Qian He Yan Geng Jianhong Zhu |
spellingShingle |
Zhenzhen Li Jin Wei Yanping Zhang Gaopeng Li Huange Zhu Na Lei Qian He Yan Geng Jianhong Zhu Risk factors for Keshan disease: a prospective cohort study protocol of gut flora BMC Cardiovascular Disorders Keshan disease Gut flora The big data platform Cohort study Metabonomic analysis |
author_facet |
Zhenzhen Li Jin Wei Yanping Zhang Gaopeng Li Huange Zhu Na Lei Qian He Yan Geng Jianhong Zhu |
author_sort |
Zhenzhen Li |
title |
Risk factors for Keshan disease: a prospective cohort study protocol of gut flora |
title_short |
Risk factors for Keshan disease: a prospective cohort study protocol of gut flora |
title_full |
Risk factors for Keshan disease: a prospective cohort study protocol of gut flora |
title_fullStr |
Risk factors for Keshan disease: a prospective cohort study protocol of gut flora |
title_full_unstemmed |
Risk factors for Keshan disease: a prospective cohort study protocol of gut flora |
title_sort |
risk factors for keshan disease: a prospective cohort study protocol of gut flora |
publisher |
BMC |
series |
BMC Cardiovascular Disorders |
issn |
1471-2261 |
publishDate |
2020-11-01 |
description |
Abstract Background Keshan disease is an endemic cardiomyopathy of undefined causes. Being involved in the unclear pathogenesis of Keshan disease, a clear diagnosis, and effective treatment cannot be initiated. However, the rapid development of gut flora in cardiovascular disease combined with omics and big data platforms may promote the discovery of new diagnostic markers and provide new therapeutic options. This study aims to identify biomarkers for the early diagnosis and further explore new therapeutic targets for Keshan disease. Methods This cohort study consists of two parts. Though the first part includes 300 participants, however, recruiting will be continued for the eligible participants. After rigorous screening, the blood samples, stools, electrocardiograms, and ultrasonic cardiogram data would be collected from participants to elucidate the relationship between gut flora and host. The second part includes a prospective follow-up study for every 6 months within 2 years. Finally, deep mining of big data and rapid machine learning will be employed to analyze the baseline data, experimental data, and clinical data to seek out the new biomarkers to predict the pathogenesis of Keshan disease. Discussion Our study will clarify the distribution of gut flora in patients with Keshan disease and the abundance and population changes of gut flora in different stages of the disease. Through the big data platform analyze the relationship between environmental factors, clinical factors, and gut flora, the main factors affecting the occurrence of Keshan disease were identified, and the changed molecular pathways of gut flora were predicted. Finally, the specific gut flora and molecular pathways affecting Keshan disease were identified by metagenomics combined with metabonomic analysis. Trial registration: ChiCTR1900026639. Registered on 16 October 2019. |
topic |
Keshan disease Gut flora The big data platform Cohort study Metabonomic analysis |
url |
http://link.springer.com/article/10.1186/s12872-020-01765-x |
work_keys_str_mv |
AT zhenzhenli riskfactorsforkeshandiseaseaprospectivecohortstudyprotocolofgutflora AT jinwei riskfactorsforkeshandiseaseaprospectivecohortstudyprotocolofgutflora AT yanpingzhang riskfactorsforkeshandiseaseaprospectivecohortstudyprotocolofgutflora AT gaopengli riskfactorsforkeshandiseaseaprospectivecohortstudyprotocolofgutflora AT huangezhu riskfactorsforkeshandiseaseaprospectivecohortstudyprotocolofgutflora AT nalei riskfactorsforkeshandiseaseaprospectivecohortstudyprotocolofgutflora AT qianhe riskfactorsforkeshandiseaseaprospectivecohortstudyprotocolofgutflora AT yangeng riskfactorsforkeshandiseaseaprospectivecohortstudyprotocolofgutflora AT jianhongzhu riskfactorsforkeshandiseaseaprospectivecohortstudyprotocolofgutflora |
_version_ |
1724443575152803840 |