Harnessing DNA methylation variation between populations to understand disease discordance across ancestries.
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 发起方
- 入组人数
- 500
- 试验地点
- 1
- 主要终点
- Pre-study power calculations to detect cis and trans mQTLs in 13,278 participants showed that we will have 80% power to detect a cis mQTL at a p-val threshold of 1e-8 with rsq is equal to 0.003.
研究概览
简要总结
DNA methylation (DNAm) plays a central role in gene regulation. It helps to define how cells respond to genetic and environmental signals and, ultimately, contributes to the whole system’s health and disease status. Levels of DNAm differ from one person to another. Some of these variation in DNAm levels is caused by genetic or environmental factors. Understanding the variation in DNAm levels will helps us to understand that why the disease risk and response to treatment is different for different population. Evaluating DNAm variation in diverse population groups allows comparison across varying genetic and environmental exposure profiles.
This will allow the identification of molecular mechanisms that underpin difference in disease prevalence across the global population. Aim is to map genetic and environmental determinants of human DNAm variation to understand mechanisms of DNAm variability. We will generate a catalogue of genetic associations with DNAm across populations worldwide. This will help us to understand functional role of genetic variability in descending disease risk.
The second aim of the project is to understand mechanisms of disease and differences in disease and risk in different population. This research builds a global partnership of teams to bring together genetic and epigenetic data collected from individuals worldwide. A key aspect of this proposal is building equitable partnerships between these teams. This is essential in order to build capacity for research in genetically diverse datasets.
Identification of common and context-specific mechanisms of health and disease mediated by DNAm is of high health impact because it will enable actions to reduce global health disparity and inequity via targeted interventions or treatments.
研究设计
- 研究类型
- Observational
入排标准
- 年龄范围
- 20.00 Year(s) 至 70.00 Year(s)(—)
- 性别
- All
入选标准
- •1.Male or Female who participated in the previous study (Project No.3114) 2.Age: 20-70 (at the time of the enrolment of Project no.3114).
排除标准
- •Unwilling to participate
- •Has a history of cough, cold, and fever
- •Unable to lie still
- •Unable to hold breath voluntarily or hear instructions
- •Unable to complete the process because of physical disabilities.
- •Pregnant women /lactating women
- •Had surgery in the last 6 weeks
- •Had a scan or x-ray in the last 2 weeks which involved taking a contrast medium.
结局指标
主要结局
Pre-study power calculations to detect cis and trans mQTLs in 13,278 participants showed that we will have 80% power to detect a cis mQTL at a p-val threshold of 1e-8 with rsq is equal to 0.003.
时间窗: Total 1 year of the project, consist of 6 months of laboratory execution and 6 months of data analysis
We have included a robust and reproducible federated analysis approach. We will develop a github pipeline where collaborators will download a suite of scripts and run the analyses in their cohort.
时间窗: Total 1 year of the project, consist of 6 months of laboratory execution and 6 months of data analysis
1.mQTL analyses
时间窗: Total 1 year of the project, consist of 6 months of laboratory execution and 6 months of data analysis
2.EWAS analyses
时间窗: Total 1 year of the project, consist of 6 months of laboratory execution and 6 months of data analysis
3.Replication
时间窗: Total 1 year of the project, consist of 6 months of laboratory execution and 6 months of data analysis
4.MR analyses
时间窗: Total 1 year of the project, consist of 6 months of laboratory execution and 6 months of data analysis
次要结局
- NA(NA)
研究者
Dr Sharayu Mhatre
Centre for Cancer Epidemiology, Tata Memorial Centre
