Session Type: ACR Poster Session B
Session Time: 9:00AM-11:00AM
Rheumatoid arthritis (RA) is a complex genetics disease driven by multiple genetic contributors as evidenced by association with over 100 risk SNPs by GWAS. However, the majority of risk SNPs are not causal and explain only a small proportion of heritability in RA. Novel approaches for the analysis and interpretation of large-scale genomics data are needed to detect the missing heritability of and gain further insight into RA. Additionally, risk gene and SNP associations differ in European and Asian RA populations (1). Regulatory genetic elements, such as non-coding micro RNAs (miRNA), are thought to play an important role in RA and have been identified by gene-based testing in Europeans with RA (2). Our aim was to identify non-coding genetic elements in Asians with RA with gene-based association testing.
Our dataset consisted of 4,873 RA cases and 17,642 controls from GWAS meta-analysis in Asians (1). All RA cases fulfilled the 1987 ACR criteria or were diagnosed by a rheumatologist. We used the Knowledge-based mining system for Genome-wide Genetic studies (KGG v.4) for gene-based association testing using extended Simes procedure (GATES) with SNPs outside the extended MHC [Chr. 6, 25.7-33.3 Mb] (3). Genes were defined as ± 5kb. Genomic control was calculated by median of Chi-square statistic. We accounted for linkage disequilibrium (LD) between SNPs with 1000 Genomes Phase 1 for Asians. Benjamini & Hochberg false discovery rate (FDR) was used to correct for multiple testing. UCSC Genome Browser was used for visualization of findings.
Our genome analysis build used 6,581,301 million SNPs and a total of 25,550 genes (including 5189 non-coding RNAs); 51.66% of SNPs were located inside genes. A total of 108 genes were found to be significant by GATES (FDR <0.05). Amongst the top genes by GATES, we identified several non-coding RNAs associated with RA in Asians. The significant long non-coding RNAs were TNFRSF14-AS1 (Chr.1 at RA risk locus TNFRSF14-MMEL1), LINC01843 (Chr. 5 near JADE2), LINC00336 (Chr.6 near GGNBP1-BAK1) and LINC01016 (Chr.6 near MLN). The significant miRNAs were MIR3934 (Chr.6 near UQCC2-ITPR3), MIR7159 (Chr. 6 near MLN), MIR4647 (Chr.6 at RA risk locus NFKBIE), MIR3939 (Chr.6 at RA risk locus CCR6), MIR4658 (Chr.7 near C7orf43) and MIR4308 (Chr. 14 near GCH1). There was no overlap of these non-coding RNAs identified in Asians with RA compared with RA in Europeans.
Through large-scale gene-based association testing, we identified novel non-coding RNA associations specific for RA in Asians. These novel regulatory genetic elements, in addition to established RA risk loci, may improve our understanding of the complex genetics of RA. Non-coding RNAs could also play a role as potential biomarkers and novel drug targets in RA.
1. Okada Y, et al. Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature. 2014 Feb 20;506(7488):376-81.
2. Lenert A, Fardo DW. Detecting novel micro RNAs in rheumatoid arthritis with gene-based association testing. Clin Exp Rheumatol. 2017 Jan 27. PMID: 28134081.
3. Li MX, et al. GATES: a rapid and powerful gene-based association test using extended Simes procedure. Am J Hum Genet. 2011 Mar 11;88(3):283-93.
To cite this abstract in AMA style:Lenert A, Fardo DW. Novel Non-Coding RNAs Associated with Rheumatoid Arthritis in Asians By Gene-Based Testing [abstract]. Arthritis Rheumatol. 2017; 69 (suppl 10). https://acrabstracts.org/abstract/novel-non-coding-rnas-associated-with-rheumatoid-arthritis-in-asians-by-gene-based-testing/. Accessed September 28, 2021.
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