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Identification of rheumatoid arthritis causal genes using functional genomics
Author(s) -
Ding James,
Orozco Gisela
Publication year - 2019
Publication title -
scandinavian journal of immunology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.934
H-Index - 88
eISSN - 1365-3083
pISSN - 0300-9475
DOI - 10.1111/sji.12753
Subject(s) - disease , computational biology , identification (biology) , rheumatoid arthritis , genome wide association study , biology , genome , genomics , genetic association , genetics , gene , medicine , single nucleotide polymorphism , genotype , immunology , pathology , botany
Over the past decade, genome‐wide association studies have contributed a wealth of knowledge to our understanding of polygenic disorders such as rheumatoid arthritis. As the size of sample cohorts has improved so too have the computational and experimental methods used to robustly define variants associated with disease susceptibility. The challenge now remains to translate these findings into improved understanding of disease aetiology and patient care. Whilst much of the focus of translating the findings of genome‐wide association studies has been on global analysis of all variants identified, careful functional study of individual disease susceptibility loci will be required in order to refine our understanding of how individual variants contribute to disease risk. Here, we present the argument behind such an approach and describe some of the novel tools being used to investigate risk loci. This includes the use of chromosomal conformation capture techniques and modifications of the CRISPR‐Cas9 system, with several examples of their implementation being described.