| Title: | SNP-Biomarker Interactions in Blood Pressure Regulation |
| Lead Institution: | Xidian University |
| Principal investigator: | Dr Gang Shi |
Application 44080
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
About
Recent study shows that effects of 15 blood pressure (BP) genomic loci are modulated by smoking behavior, such interaction effects of the newly identified single-nucleotide polymorphisms (SNPs) explained additional variations of systolic and diastolic blood pressures in populations. Biomarkers, determined by complex genetic and environmental factors, are indicators of some particular biological states or conditions and represent specific contexts for some biological processes. We aim to examine whether SNPs interact with cardiovascular-related biomarkers in BP regulation. We will test whether SNPs with known associations to BP interact with biomarkers, and how much BP variations could be accounted for by the SNP-biomarker interactions. Since functional roles of BP-associated SNPs are largely unknown, positive interactions may provide some insights into possible connections of complex biological networks involved in BP regulation. We will further perform genome-wide SNP-biomarker interaction analyses looking for novel SNPs and SNP-biomarker interactions. Statistical models and machine learning techniques will be used in our analyses. We would also like to extend the work to examining other cardiovascular-related traits and testing interactions with other cardiovascular-related factors as well as extend our work to methodological developments. Novel SNPs and SNP-biomarker interactions could help understanding complex genetic architecture of BP regulation, provide potential targets for novel pharmacotherapy, as well as facilitate the development of future personalized prevention and treatment of hypertension.2 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 10373 | Genome-wide variance quantitative trait locus analysis suggests small interaction effects in blood pressure traits | Gang Shi | 2022 | Scientific Reports |
| 10565 | Kernel-based gene-environment interaction tests for rare variants with multiple quantitative phenotypes | Xiaoqin Jin (+1) | 2022 | PLOS ONE |
Enabling scientific discoveries that improve human health