| Literature DB >> 28553958 |
Kazuyoshi Ishigaki1,2,3, Yuta Kochi1,4, Akari Suzuki1, Yumi Tsuchida2, Haruka Tsuchiya2, Shuji Sumitomo2, Kensuke Yamaguchi1,2, Yasuo Nagafuchi2, Shinichiro Nakachi2, Rika Kato2, Keiichi Sakurai2, Hirofumi Shoda2, Katsunori Ikari4,5, Atsuo Taniguchi5, Hisashi Yamanaka5, Fuyuki Miya4,6,7, Tatsuhiko Tsunoda4,6,7, Yukinori Okada1,8,9, Yukihide Momozawa10, Yoichiro Kamatani3, Ryo Yamada1,11, Michiaki Kubo10, Keishi Fujio2, Kazuhiko Yamamoto1,2.
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.Entities:
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Year: 2017 PMID: 28553958 DOI: 10.1038/ng.3885
Source DB: PubMed Journal: Nat Genet ISSN: 1061-4036 Impact factor: 38.330