Literature DB >> 25205356

Five regulatory genes detected by matching signatures of eQTL and GWAS in psoriasis.

Xianyong Yin1, Hui Cheng2, Yan Lin2, Xing Fan2, Yong Cui2, Fusheng Zhou2, Changbing Shen2, Xianbo Zuo2, Xiaodong Zheng2, Weijia Zhang2, Sen Yang2, Xuejun Zhang2.   

Abstract

BACKGROUND: Psoriasis is a common immune-mediated inflammatory skin disease with strong genetic dispositions. Although more than 40 susceptibility loci have been revealed mostly through psoriasis genome wide association studies, genetic variants with small effect remain to be identified.
OBJECTIVE: In order to explore the susceptibility genes with potential regulatory function, we queried jointly two psoriasis genome wide association cohorts and an expression dataset.
METHODS: We integrated conventional genome-wide association evidences in 2326 Han Chinese and 2719 Caucasian populations, and the signature of expression quantitative trait loci (eQTL) in lymphoblastoid B cells, with application of Bayesian algorithm.
RESULTS: Five genes with implied regulatory effect were revealed to be associated significantly with the risk of psoriasis, with one novel signal in FAM20B gene which is significantly expressed (P=3.24×10(-5)). Besides, seven single nucleotide polymorphisms were identified to be involved in the mechanism of psoriasis through eQTL effect.
CONCLUSIONS: We identified FAM20B as a risk regulatory gene in the etiology of psoriasis at first time. This study shed a spotlight on the immune regulatory mechanism in psoriasis.
Copyright © 2014 Japanese Society for Investigative Dermatology. Published by Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Genome wide association; Psoriasis; Susceptibility gene

Mesh:

Year:  2014        PMID: 25205356     DOI: 10.1016/j.jdermsci.2014.07.007

Source DB:  PubMed          Journal:  J Dermatol Sci        ISSN: 0923-1811            Impact factor:   4.563


  5 in total

Review 1.  The Molecular Revolution in Cutaneous Biology: The Era of Genome-Wide Association Studies and Statistical, Big Data, and Computational Topics.

Authors:  Hima Anbunathan; Anne M Bowcock
Journal:  J Invest Dermatol       Date:  2017-05       Impact factor: 8.551

2.  eSNPO: An eQTL-based SNP Ontology and SNP functional enrichment analysis platform.

Authors:  Jin Li; Limei Wang; Tao Jiang; Jizhe Wang; Xue Li; Xiaoyan Liu; Chunyu Wang; Zhixia Teng; Ruijie Zhang; Hongchao Lv; Maozu Guo
Journal:  Sci Rep       Date:  2016-07-29       Impact factor: 4.379

3.  Integrative Genome-Wide Association Studies of eQTL and GWAS Data for Gout Disease Susceptibility.

Authors:  Meng-Tse Gabriel Lee; Tzu-Chun Hsu; Shyr-Chyr Chen; Ya-Chin Lee; Po-Hsiu Kuo; Jenn-Hwai Yang; Hsiu-Hao Chang; Chien-Chang Lee
Journal:  Sci Rep       Date:  2019-03-21       Impact factor: 4.379

4.  Genome-wide analysis of expression QTL (eQTL) and allele-specific expression (ASE) in pig muscle identifies candidate genes for meat quality traits.

Authors:  Yan Liu; Xiaolei Liu; Zhiwei Zheng; Tingting Ma; Ying Liu; Huan Long; Huijun Cheng; Ming Fang; Jing Gong; Xinyun Li; Shuhong Zhao; Xuewen Xu
Journal:  Genet Sel Evol       Date:  2020-10-09       Impact factor: 4.297

5.  Chondroitin 6-sulfate represses keratinocyte proliferation in mouse skin, which is associated with psoriasis.

Authors:  Kazuyuki Kitazawa; Satomi Nadanaka; Kenji Kadomatsu; Hiroshi Kitagawa
Journal:  Commun Biol       Date:  2021-01-25
  5 in total

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