The LEARN Study
Research type
Research Study
Full title
Learning the Essential Analytical & Risk parameters Necessary for validation
IRAS ID
284573
Contact name
Oyeniyi Diya
Contact email
Sponsor organisation
Genomics plc
Duration of Study in the UK
0 years, 1 months, 12 days
Research summary
Summary of Research
This is a single site study involving participants who will not be screened for or selected based on any diseases or traits.
It will involve one study visit, during which biological samples (two cheek swabs, one saliva and one blood sample) will be collected for data analysis. No results will be returned to participants.
This study will recruit 25 participants, male and female, self reported, from the subject for data analysis European, South Asian, East Asian, African, Middle Eastern or mixed European/South Asian, European/East Asian, European/African, African/East Asian, African/South Asian or East Asian/South Asian ancestry, aged 18 or older.
The primary aim of this study is to assess the validity of different sample types (for example saliva or blood) and technologies (such as DNA sequencing instruments) for the computation of polygenic risk scores (PRS) and integrated risk scores (IRS). PRS is a measure of the predicted risk for a person to get a disease based on their genetic information. IRS refers to the combination of PRS with other non-genetic variables such as age or blood lipids.
The secondary aim of the study is to identify the best metrics to assess the quality of genetic data for the purpose of PRS and IRS computations. These metrics can then be used in future experiments to identify data of sufficient quality for risk prediction applications.
Summary of Results
We characterised the result accuracy and protocol robustness of different genetic-based disease risk prediction algorithms developed by Genomics plc. We tested three alternative experimental methods to measure individual genetic makeup from blood, saliva and buccal samples. We found that different sample types provide comparable results and the experimental methods have slightly different measurement errors. Overall, the result accuracy of the different algorithms was satisfactory across conditions.
REC name
South Central - Oxford A Research Ethics Committee
REC reference
20/SC/0252
Date of REC Opinion
16 Jun 2020
REC opinion
Further Information Favourable Opinion