国际传统医学临床试验注册平台

注册号： Registration number：	ITMCTR2024000050
最近更新日期： Date of Last Refreshed on：	2024-04-24
注册时间： Date of Registration：	2024-04-24
注册号状态： Registration Status：	补注册 Retrospective registration
注册题目：
Public title：	Influence of Peanut Consumption on Cardiovascular Risk Factors and the Gut Microbiome: A Randomized Clinical Trial
注册题目简写：
English Acronym：
研究课题的正式科学名称：
Scientific title：	Influence of Peanut Consumption on Cardiovascular Risk Factors and the Gut Microbiome: A Randomized Clinical Trial
研究课题的正式科学名称简写：
Scientific title acronym：
研究课题代号(代码)： Study subject ID：
在二级注册机构或其它机构的注册号： The registration number of the Partner Registry or other register：

申请注册联系人：		研究负责人：
Applicant：	Thi Du Chi TRAN	Study leader：	Xiao-Ou SHU
申请注册联系人电话： Applicant telephone：	+84 947611475	研究负责人电话： Study leader's telephone：	615-936-0713
申请注册联系人传真： Applicant Fax：		研究负责人传真： Study leader's fax：
申请注册联系人电子邮件： Applicant E-mail：	v.chittd@vinmec.com	研究负责人电子邮件： Study leader's E-mail：	xiao-ou.shu@vumc.org
申请单位网址(自愿提供)： Study leader's website(voluntary supply)：		研究负责人网址(自愿提供)： Study leader's website (voluntary supply)：
申请注册联系人通讯地址：		研究负责人通讯地址：
Applicant address：	Vinmec International General Hospital JSC, 458 Minh Khai street, Vinh Tuy ward, Hai Ba Trung district, Hanoi, Vietnam	Study leader's address：	Vanderbilt University School of Medicine, 1211 Medical Center Drive, Nashville, TN 37232, USA
申请注册联系人邮政编码： Applicant postcode：		研究负责人邮政编码： Study leader's postcode：
申请人所在单位：
Applicant's institution：	Vinmec International General Hospital JSC

是否获伦理委员会批准： Approved by ethic committee：	是 Yes
伦理委员会批件文号： Approved No. of ethic committee：	319/2018/QD-VMEC	伦理委员会批件附件： Approved file of Ethical Committee：	查看附件
批准本研究的伦理委员会名称：
Name of the ethic committee：	Institutional Ethical Review Board for Biomedical Research - Vinmec International General Hospital JSC
伦理委员会批准日期： Date of approved by ethic committee：	2018/9/20 0:00:00
伦理委员会联系人：
Contact Name of the ethic committee：	Quynh Hoa PHAM
伦理委员会联系地址：
Contact Address of the ethic committee：	Institutional Ethical Review Board for Biomedical Research - Vinmec International General Hospital JSC, 458 Minh Khai street, Vinh Tuy ward, Hai Ba Trung district, Hanoi, Vietnam
伦理委员会联系人电话： Contact phone of the ethic committee：	+84 2439750028-6236	伦理委员会联系人邮箱： Contact email of the ethic committee：	v.hoapq@vinmec.com
国家FDA批准文号： Approved No. of SFDA：		国家FDA批准附件： Approved file of SFDA：
国家FDA批准日期： Date of approved by SFDA：
研究计划书： Study plan file：
知情同意书： Informed consent file：

研究实施负责（组长）单位：

Primary sponsor：

Division of Epidemiology, Vanderebilt University School of Medicine

研究实施负责（组长）单位地址：

Primary sponsor's address：

Vanderbilt University School of Medicine, 1211 Medical Center Drive, Nashville, TN 37232, USA

试验主办单位(项目批准或申办者)：

Secondary sponsor：

国家：		省(直辖市)：		市(区县)：
Country：	Vietnam	Province：	Hanoi	City：	Hanoi
单位(医院)：		具体地址：
Institution hospital：	Vinmec International General Hospital JSC	Address：	458 Minh Khai street, Vinh Tuy ward, Hai Ba Trung district, Hanoi, Vietnam

经费或物资来源：

Source(s) of funding：

US Peanut Institute

研究疾病：		研究疾病代码：
Target disease：	Cardiovascular risk biomarkers and gut microbiome	Target disease code：
研究类型： Study type：	干预性研究 Interventional study	研究设计： Study design：	随机平行对照 randomized controlled trial(parallel group design)
研究所处阶段： Study phase：	其它 Others
研究目的：
Objectives of Study：	The objectives of the study are to conduct a randomized clinical trial among a population at high risk for CVD, to evaluate the influence of short-term peanut supplementation on CVD risk factors and the gut microbiome, and to investigate whether peanut consumption may alter gut microbiota to lower the risk of CVD. By means of this study, we anticipate obtaining strong and direct scientific evidence regarding the effect of peanut consumption on cardiovascular health while gaining an in-depth understanding of the underlying biological mechanisms for the protective association between peanut intake and CVD risk.
药物成份或治疗方案详述：
Description for medicine or protocol of treatment in detail：
纳入标准：
Inclusion criteria	100 participants (50 each arm) 1. Age: 40 – 70, FOBT negative 2. Do not consume peanut or other tree nuts/seeds more than 1 time per week. 3. Self-reported diabetes/prediabetes but not on diabetes medication 4. Or self-reported dyslipidemia but not on lipid or triglyceride lowing medication 5. Or BMI>=25 or waist circumference >90 cm for man or >80 cm for women 6. Or systolic/diastolic blood pressure ≥ 130/85 mmHg
排除标准：
Exclusion criteria：	Individuals meet any of the following conditions are not eligible for the study 1. Known and suspected peanut/peanut containing products allergy 2. Kidney disease 3. Liver disease 4. Cardiovascular disease 5. Myocardial infarction 6. Cancer 7. Stroke 8. Drink more than 2 units of alcohol (2 cups of wine, 2 shuts of liquid or 2 cans of beer) weekly 9. On diabetes medications currently or during past 3 months 10. On lipid or triglyceride lowing medications currently or during past 3 months 11. Hospitalized in the past three months 12. Received chemotherapy, immune suppressive treatment, antibiotics during last 3 months 13. Have gained or lost more than 2.5 kg of weight in the last 3 months
研究实施时间： Study execute time：	从From 2019-04-10 至To 2020-10-01	征募观察对象时间： Recruiting time：	从From 2019-04-18 至To 2020-06-01

干预措施：

Interventions：

组别：		样本量：	51
Group：	Arm A (Peanut Intervention)	Sample size：	51
干预措施：		干预措施代码：
Intervention：	consume 50 gram plain peanuts (unsalted and unsweetened) daily for 16 weeks	Intervention code：

组别：		样本量：	49
Group：	Arm B (Control)	Sample size：	49
干预措施：		干预措施代码：
Intervention：	No intervention. The controls follow their usual dietary habits for 16 weeks	Intervention code：

样本总量 Total sample size ： 100

研究实施地点：

Countries of recruitment
and research settings：

国家：		省(直辖市)：		市(区县)：
Country：	Vietnam	Province：	Hanoi	City：	Hanoi
单位(医院)：		单位级别：
Institution/hospital：	Vinmec International General Hospital Joint Stock Company	Level of the institution：	unclassified

测量指标：

Outcomes：

指标中文名：		指标类型：	主要指标
Outcome：	Urinary metabolites	Type：	Primary indicator
测量时间点：		测量方法：
Measure time point of outcome：		Measure method：

指标中文名：		指标类型：	主要指标
Outcome：	HbA1C	Type：	Primary indicator
测量时间点：		测量方法：
Measure time point of outcome：		Measure method：

指标中文名：		指标类型：	主要指标
Outcome：	Gut microbiome profile	Type：	Primary indicator
测量时间点：		测量方法：
Measure time point of outcome：		Measure method：

指标中文名：		指标类型：	主要指标
Outcome：	Plasma CRP	Type：	Primary indicator
测量时间点：		测量方法：
Measure time point of outcome：		Measure method：

指标中文名：		指标类型：	主要指标
Outcome：	Lipid profile	Type：	Primary indicator
测量时间点：		测量方法：
Measure time point of outcome：		Measure method：

指标中文名：		指标类型：	主要指标
Outcome：	Plasma insulin	Type：	Primary indicator
测量时间点：		测量方法：
Measure time point of outcome：		Measure method：

指标中文名：		指标类型：	主要指标
Outcome：	Glucose	Type：	Primary indicator
测量时间点：		测量方法：
Measure time point of outcome：		Measure method：

采集人体标本：

Collecting sample(s)
from participants：

标本中文名：		组织：
Sample Name：	Urine	Tissue：
人体标本去向	使用后保存	说明
Fate of sample	Preservation after use	Note：

标本中文名：		组织：
Sample Name：	Stool	Tissue：
人体标本去向	使用后保存	说明
Fate of sample	Preservation after use	Note：

标本中文名：		组织：
Sample Name：	Blood	Tissue：
人体标本去向	使用后保存	说明
Fate of sample	Preservation after use	Note：

征募研究对象情况：

结束

Completed

年龄范围：

最小	40	岁
Min age	40	years
最大	70	岁
Max age	70	years

Recruiting status：

Participant age：

性别：

Gender：

男女均可

Both

随机方法（请说明由何人用什么方法产生随机序列）：

Randomization Procedure (please state who generates the random number sequence and by what method)：

100 enrolled study participants was randomized on rolling basis. Once a study participant signed a written informed consent and was determined to be eligible for enrollment, the field operation director allocate him/her into either intervention group or control group using a stratified permuted block randomization schedule. This randomization list was generated by the study statistician using R with block size of 4 and stratified by gender and age (<55 and >=55 years old) and diabetes status (yes/no).

研究对象是否签署知情同意书：

Sign the informed consent：

是

Yes

随访时间：

Length of follow-up (include time point of outcome measure)：

16

周

Week(s)

隐蔽分组方法和过程：
Process of allocation concealment：	NA
盲法：
Blinding：	NA
揭盲或破盲原则和方法：
Rules of uncover or ceasing blinding：	NA
统计方法名称：
Statistical method：	For the blood- and urine based biomarkers, the primary analysis will be a two-sample t-test for comparing the change in each biomarker (including total cholesterol, LDL, HDL, triglyceride, glucose, insulin, and CRP levels) from pre-intervention to Week 16 after intervention, between the two study Arms. The nonparametric Wilcoxon rank sum test will be used if assumptions for the t-test cannot be met. Multivariable analysis will be performed using a linear regression model, where the dependent/outcome variables are the biomarker levels at Week 16 and the primary independent variable is the intervention arm, adjusted for baseline biomarker level and other potential confounding factors such as dietary intake, medication use, smoking and physical activity. Changes in biomarkers from baseline to Weeks 16 post-intervention within each arm will also be evaluated using the same univariate analysis methods mentioned above. Multivariate analysis will apply a linear mixed model to account for the correlated data collected from repeated measurements (baseline, and Week 16). For the microbiome data, the impact of peanut intervention with changes in overall microbial diversity, including α-diversity, β-diversity, and overall stability of human gut microbiota was evaluated. The species-level absolute abundance was rarefied using the R function VEGAN::RAREFY. The α-diversity and β-diversity were estimated based on the rarefied species-level absolute abundance data and relative abundance data of gut microbial metabolic pathways using the R functions VEGAN::DIVERSITY and VEGAN::VEGDIST, respectively. α-diversity was measured by the Chao1 richness index, Shannon - Wiener diversity index and Pielou evenness index. Differences across groups and time were compared using non-parametric tests. β-diversity was measured by the Bray-Curtis dissimilarity matrix and Jaccard dissimilarity matrix. The Permutational Multivariate Analysis of Variance (PERMANOVA) test was applied to assess whether there was a difference in β-diversity by study group and time with 999 permutations using the R functions vegan. The associations of peanut intervention with changes in the Chao1, the Shannon, Pielou, Bray-Curtis, and Jaccard indexes were examined using general linear regression models via the R package MicrobiomeStat. Covariates included in the models are age, gender, body mass index, and other legume intake with exclusion of peanut consumption. The overall stability of human gut microbiota from baseline to post-16 weeks was determined based on β-diversity distance within-sample and subtracted them from 1. Species stability and the stability of gut microbial metabolic pathway was determined using formula 1 – Bray-Curtis Index within-sample (baseline vs. 16-week follow-up). Beta regression analysis was performed using the R package “betareg.” β coefficients, standard error (SE), and p values were calculated in models with adjustment for the aforementioned covariates. The statistical analyses were performed at two-sided tests, and associations with p value<0.05 were considered statistically significant. The association of peanut intervention with individual gut microbial taxa from phylum to species for those microbial taxa that were present in >10% of samples and had a median relative abundance >0.001% were evaluated. Linear mixed-effects models (LMM) within a linear regression for differential abundance analysis (LinDA) were applied with adjustment for age, gender, BMI, and another legume intake via the R package “MicrobiomeStat” v.1.1.3. LinDA-LMM used the centered log-ratio (clr) transformation to normalize the absolute abundance of taxa at each taxonomic level from phylum to species, with zeros replaced by the next minimal read count value of the whole dataset. β coefficients, standard error (SE), and p values for individual microbial taxa were produced. False discovery rate (FDR) was calculated at each taxonomic level for multiple testing sets. The same approach was applied to evaluate peanut intervention with individual microbial metabolic pathways for those microbial metabolic pathways observed in > 10% of samples and median relative abundance >0.001%. All associations with FDR-corrected p-values of <0.1 were considered statistically significant. The impact of peanut intervention on gut microbiome sub-community structure was also examined. Latent Dirichlet Allocation (LDA), a three-level Bayesian probabilistic generative model that reveals latent structures in unlabeled data, was utilized to infer sub-communities in gut microbiota. The abundance data of species-level subgroups and evaluated the associations of gut microbial taxa with peanut intervention for species-level subgroups was estimated using Linear mixed-effects models. The Bray-Curtis metric was used to calculate the stability of those individual species and metabolic pathways that were present in >20% of samples and median of relative abundance >0.01%, via comparing the absolute abundance/ relative abundance of each species/metabolic pathway across all participants at baseline and post-16 weeks. Beta regression analysis was applied to estimate the β coefficients, standard error (SE), p values, and FDR of each single feature in association with peanut intervention. All statistical analyses were performed using R version 4.3.2.
试验完成后的统计结果（上传文件）：
Calculated Results ater the Study Completed：	This study will provide direct evidence on how peanut consumption affects cardiovascular risks. It will also generate new knowledge on how peanut consumption influences the gut microbiome, the newly recognized human organ that plays a critical role in human health. The research findings will be essential for promoting peanut consumption to improve cardiovascular health, particularly among low-income populations who bear a high risk of CVD but are less able to afford tree nuts on a regular basis
上传试验完成后的统计结果： Statistical results after completion of the test file upload
是否公开试验完成后的统计结果： Calculated Results after the Study Completed(upload file)：	公开 Public
全球唯一识别码： UTN

是否共享原始数据： IPD sharing：	否 No
共享原始数据的方式（说明：请填入公开原始数据日期和方式，如采用网络平台，需填该网络平台名称和网址）：
The way of sharing IPD”(include metadata and protocol, If use web-based public database, please provide the url)：	Data is available on request. The data will be shared upon reasonable request to the study leader
数据采集和管理（说明：数据采集和管理由两部分组成，一为病例记录表(Case Record Form, CRF)，二为电子采集和管理系统(Electronic Data Capture, EDC)，如ResMan即为一种基于互联网的EDC：
Data collection and Management (A standard data collection and management system include a CRF and an electronic data capture：	Study data were collected and managed using REDCap electronic data capture tools hosted at Vinmec International General Hospital JSC (1,2). REDCap (Research Electronic Data Capture) is a secure, web-based software platform designed to support data capture for research studies, providing 1) an intuitive interface for validated data capture; 2) audit trails for tracking data manipulation and export procedures; 3) automated export procedures for seamless data downloads to common statistical packages; and 4) procedures for data integration and interoperability with external sources. 1) PA Harris, R Taylor, R Thielke, J Payne, N Gonzalez, JG. Conde, Research electronic data capture (REDCap) – A metadata-driven methodology and workflow process for providing translational research informatics support, J Biomed Inform. 2009 Apr;42(2):377-81. 2) PA Harris, R Taylor, BL Minor, V Elliott, M Fernandez, L O’Neal, L McLeod, G Delacqua, F Delacqua, J Kirby, SN Duda, REDCap Consortium, The REDCap consortium: Building an international community of software partners, J Biomed Inform. 2019 May 9 [doi: 10.1016/j.jbi.2019.103208]
数据管理委员会： Data Managemen Committee：	有 Yes
研究计划书或研究结果报告发表信息（杂志名称、期、卷、页，时间；或网址）：
Publication information of the protocol/research results report (name of the journal, volume, issue, pages, time; or website):