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Genetic advances in systemic lupus erythematosus: an update

Research output: Contribution to journalArticle

Original languageEnglish
Pages (from-to)423-433
Number of pages11
JournalCurrent Opinion in Rheumatology
Volume29
Issue number5
Early online date15 May 2017
DOIs
Accepted/In press27 Apr 2017
E-pub ahead of print15 May 2017
PublishedSep 2017

Documents

  • Genetic advances in systemic_CHEN_Publishedonline15May2017_GREEN AAM

    Genetic_advances_in_systemic_CHEN_Publishedonline15May2017_GREEN_AAM.pdf, 1.4 MB, application/pdf

    Uploaded date:02 Aug 2017

    Version:Accepted author manuscript

    This is the peer-reviewed accepted manuscript version of a paper published in its final form in Current Opinion in Rheumatology, v. 29 no. 5 (© Wolters Kluwer Health Inc., 2017). It can be viewed online at http://dx.doi.org/10.1097/BOR.0000000000000411

King's Authors

Abstract

PURPOSE OF REVIEW: More than 80 susceptibility loci are now reported to show robust genetic association with systemic lupus erythematosus (SLE). The differential functional effects of the risk alleles for the majority of these loci remain to be defined. Here, we review current SLE association findings and the recent progress in the annotation of noncoding regions of the human genome as well as the new technologies and statistical methods that can be applied to further the understanding of SLE genetics.

RECENT FINDINGS: Genome-wide association studies (GWAS) have markedly expanded the catalogue of genetic signals contributing to SLE development; we can now explain more than 50% of the disease's heritability. Expression quantitative trait loci mapping with colocalization analysis of GWAS results help to identify the underlying causal genes. The Encyclopedia of DNA elements, Roadmap Epigenome, and the Blueprint Epigenome projects have jointly annotated more than 80% of the noncoding genome, providing a wealth of information (from healthy individuals) to define the functional elements within the risk loci. Technologies, such as next-generation sequencing, chromatin structure determination, and genome editing, will help elucidate the actual mechanisms that underpin SLE risk alleles.

SUMMARY: Gene expression and epigenetic databases provide a valuable resource to interpret genetic association in SLE. Expansion of such resources to include disease status and multiple ancestries will further aid the exploration of the biology underlying the genetics.

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