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 |
|---|---|
| Pages (from-to) | 1120-1125 |
| Number of pages | 6 |
| Journal | Nature Genetics |
| Volume | 49 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - 01-07-2017 |
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All Science Journal Classification (ASJC) codes
- Genetics
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Polygenic burdens on cell-specific pathways underlie the risk of rheumatoid arthritis. / Ishigaki, Kazuyoshi; Kochi, Yuta; Suzuki, Akari; Tsuchida, Yumi; Tsuchiya, Haruka; Sumitomo, Shuji; Yamaguchi, Kensuke; Nagafuchi, Yasuo; Nakachi, Shinichiro; Kato, Rika; Sakurai, Keiichi; Shoda, Hirofumi; Ikari, Katsunori; Taniguchi, Atsuo; Yamanaka, Hisashi; Miya, Fuyuki; Tsunoda, Tatsuhiko; Okada, Yukinori; Momozawa, Yukihide; Kamatani, Yoichiro; Yamada, Ryo; Kubo, Michiaki; Fujio, Keishi; Yamamoto, Kazuhiko.
In: Nature Genetics, Vol. 49, No. 7, 01.07.2017, p. 1120-1125.Research output: Contribution to journal › Article
TY - JOUR
T1 - Polygenic burdens on cell-specific pathways underlie the risk of rheumatoid arthritis
AU - Ishigaki, Kazuyoshi
AU - Kochi, Yuta
AU - Suzuki, Akari
AU - Tsuchida, Yumi
AU - Tsuchiya, Haruka
AU - Sumitomo, Shuji
AU - Yamaguchi, Kensuke
AU - Nagafuchi, Yasuo
AU - Nakachi, Shinichiro
AU - Kato, Rika
AU - Sakurai, Keiichi
AU - Shoda, Hirofumi
AU - Ikari, Katsunori
AU - Taniguchi, Atsuo
AU - Yamanaka, Hisashi
AU - Miya, Fuyuki
AU - Tsunoda, Tatsuhiko
AU - Okada, Yukinori
AU - Momozawa, Yukihide
AU - Kamatani, Yoichiro
AU - Yamada, Ryo
AU - Kubo, Michiaki
AU - Fujio, Keishi
AU - Yamamoto, Kazuhiko
PY - 2017/7/1
Y1 - 2017/7/1
N2 - 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.
AB - 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.
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U2 - 10.1038/ng.3885
DO - 10.1038/ng.3885
M3 - Article
VL - 49
SP - 1120
EP - 1125
JO - Nature Genetics
JF - Nature Genetics
SN - 1061-4036
IS - 7
ER -