Abstract
Recent evidence suggests that a substantial portion of complex disease risk alleles modify gene expression in a cell-specific manner. To identify candidate causal genes and biological pathways of immune-related complex diseases, we conducted expression quantitative trait loci (eQTL) analysis on five subsets of immune cells (CD4 + T cells, CD8 + T cells, B cells, natural killer (NK) cells and monocytes) and unfractionated peripheral blood from 105 healthy Japanese volunteers. We developed a three-step analytical pipeline comprising (i) prediction of individual gene expression using our eQTL database and public epigenomic data, (ii) gene-level association analysis and (iii) prediction of cell-specific pathway activity by integrating the direction of eQTL effects. By applying this pipeline to rheumatoid arthritis data sets, we identified candidate causal genes and a cytokine pathway (upregulation of tumor necrosis factor (TNF) in CD4 + T cells). Our approach is an efficient way to characterize the polygenic contributions and potential biological mechanisms of complex diseases.
Original language | English |
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Pages (from-to) | 1120-1125 |
Number of pages | 6 |
Journal | Nature Genetics |
Volume | 49 |
Issue number | 7 |
DOIs | |
Publication status | Published - 01-07-2017 |
Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Genetics