Establishment of eQTL/sQTL-based and trans-ancestry polygenic risk score for immune-related complex traits
Approved Research ID: 78657
Approval date: December 8th 2021
Human immune system defends ourselves against foreign invaders such as bacteria and viruses. However, it sometimes loses its control and leads to critical conditions, as exemplified by the case of severe COVID-19. It also triggers the development of immunological disorders such autoimmune diseases, allergic diseases, and inflammatory diseases. Furthermore, immune system is involved in wide range of common diseases including neuropsychiatric diseases, metabolic diseases, thrombotic diseases, atherosclerotic cardiovascular diseases, and cancer diseases. Immune responses and their contribution to these diseases substantially vary among individuals, where both genetic and environmental factors are involved. Genomic studies have identified hundreds of genetic factors for these immune-related diseases, and most of these genetic factors (genetic variations), are now known to regulate the expression level of disease-related genes. We call these genetic variations as expression quantitative trait loci (eQTL) and splicing quantitative trait loci (sQTL). Indeed, we have shown that eQTL and sQTL identified in the immune cells of Japanese individuals are likely to cause immunological diseases. Therefore, we think the combination of these genetic factors would determine an individual's immune response and its contribution to immune-related diseases. We need to establish a method to estimate this combination, and we think polygenic risk score (PRS), calculated by the sum of an individual's genetic factors, is a potent estimator. In the present project, we aim to establish PRS for multiple immune pathways, which are constructed of eQTL, sQTL and other genetic variations that work in immune cells. Using this PRS, we will predict the disease states (onset, severe progression, drug response, etc.) of the immune-related diseases. Because it is known that PRS constructed in European populations would bias the prediction when used in Asian populations, we will try to establish trans-ancestry PRS in addition to population specific PRS. This study will promote the development of novel prediction methods for the genome-based precision medicine in various immune-related diseases. This project will be 36 months in duration but may be extended to use newly-released data which warrant extra validation of our findings.