Polygenic burdens on cell-specific pathways underlie the risk of rheumatoid arthritis.
Kazuyoshi IshigakiYuta KochiAkari SuzukiYumi TsuchidaHaruka TsuchiyaShuji SumitomoKensuke YamaguchiYasuo NagafuchiShinichiro NakachiRika KatoKeiichi SakuraiHirofumi ShodaKatsunori IkariAtsuo TaniguchiHisashi YamanakaFuyuki MiyaTatsuhiko TsunodaYukinori OkadaYukihide MomozawaYoichiro KamataniRyo YamadaMichiaki KuboKeishi FujioKazuhiko YamamotoPublished in: Nature genetics (2017)
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.
Keyphrases
- rheumatoid arthritis
- gene expression
- genome wide
- peripheral blood
- dna methylation
- single cell
- poor prognosis
- cell therapy
- disease activity
- healthcare
- mental health
- emergency department
- stem cells
- genome wide identification
- interstitial lung disease
- signaling pathway
- machine learning
- binding protein
- transcription factor
- long non coding rna
- systemic sclerosis
- climate change