Integrative Analysis of Quantitative Trait Loci
||Integrative Analysis of Quantitative Trait Loci|
||Wen Zhong <email@example.com>|
||2023-09-28 – 2024-04-01|
In the proposed study, we aim to investigate the genetic influence on multi-omics molecules and cell levels in healthy individuals by utilizing a quantitative trait loci (QTL) analysis approach. QTL analysis is a powerful computational method that allows the identification of genetic regions that influence complex traits, such as those related to human health. By combining genetics sequencing data with multi-omics data, including transcriptomic, proteomic, metabolomic, and immune cell data, we will be able to identify genetic variants that are associated with the levels of various molecules and cells in human blood.
The Swedish SciLifeLab SCAPIS Wellness Profiling (S3WP) study is a longitudinal observational study of healthy individuals. The study design includes a repeated sampling of 100 participants at six different time points over a two-year period with the collection of various data types including clinical chemistry, medical imaging, genomic, transcriptomic, proteomic, metabolomic, and immune cellular data. We will use the longitudinal data to conduct our QTL analysis and identify the dynamic changes in the genetic regulation of multi-omics molecules and cell levels. Furthermore, we will also use data from INTERVAL to increase the sample size and increase the generalizability of the findings.
The proposed study will not only provide new insights into the genetic factors that influence multi-omics molecules and cell levels in healthy individuals but also have the potential to inform the development of new strategies for disease prevention and treatment, as well as the identification of new biomarkers for early disease detection.