Literature DB >> 31295546

Functional annotation of noncoding causal variants in autoimmune diseases.

Ali Yousefian-Jazi1, Jieun Jung1, Jung Kyoon Choi2, Jinwook Choi3.   

Abstract

Interpretation of noncoding disease variants, which comprise the vast majority of Genome-wide association studies (GWAS) hits, remains a momentous challenge due to haplotype structure and our limited understanding of the mechanisms and physiological contexts of noncoding elements. GWAS have identified loci underlying human diseases, but assigning the causal nucleotide changes still remain a controversial issue. Here we addressed these issues through the combination of high-density genotyping and epigenomic data using a random forest model to discover the noncoding causal variants. Focusing on autoimmune diseases, we triaged putative causal variants for atopic dermatitis and inflammatory bowel diseases. Making a filtering pipeline, we found three interesting single nucleotide polymorphisms (rs1800630, rs1799964 and rs4796793) in the upstream site of TNF and STAT3 genes, two frequent genes shared in some autoimmune diseases, and show how those variants affect on TNF and STAT3 expression levels. All data and source codes related to this manuscript are available at https://github.com/jieunjung511/Autoimmune-research.
Copyright © 2019. Published by Elsevier Inc.

Entities:  

Keywords:  Autoimmune diseases; Epigenetics; Genome-wide association study; Random Forest

Mesh:

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Year:  2019        PMID: 31295546     DOI: 10.1016/j.ygeno.2019.07.006

Source DB:  PubMed          Journal:  Genomics        ISSN: 0888-7543            Impact factor:   5.736


  1 in total

1.  Functional fine-mapping of noncoding risk variants in amyotrophic lateral sclerosis utilizing convolutional neural network.

Authors:  Ali Yousefian-Jazi; Min Kyung Sung; Taeyeop Lee; Yoon-Ho Hong; Jung Kyoon Choi; Jinwook Choi
Journal:  Sci Rep       Date:  2020-07-30       Impact factor: 4.379

  1 in total

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