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Abstract Number: 2409

Genetic Insights into Juvenile Idiopathic Arthritis Derived from Deep Whole Genome Sequencing

James Jarvis1, Lai Ping Wong2 and Kaiyu Jiang2, 1Pediatrics, SUNY Buffalo School of Medicine, Buffalo, NY, 2Pediatrics, University at Buffalo, Buffalo, NY

Meeting: 2016 ACR/ARHP Annual Meeting

Date of first publication: September 28, 2016

Keywords: Genetics and juvenile idiopathic arthritis-enthesitis (ERA)

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Session Information

Date: Tuesday, November 15, 2016

Title: Pediatric Rheumatology – Pathogenesis and Genetics - Poster

Session Type: ACR Poster Session C

Session Time: 9:00AM-11:00AM

Background/Purpose: Deep whole genome sequencing (WGS) provides an unprecedented opportunity to comprehensively study genetic landscapes at finer resolution than can be achieved with chip-based methods. We studied juvenile idiopathic arthritis (JIA), a complex trait that represents one of the most common chronic disease conditions in children. While previous candidate gene approaches and genome-wide association studies (Hersh et al J Autoimmunity 2015) and genetic fine-mapping studies (Hinks et al Nature Genet 2013) have revealed some useful information about genetic risk in JIA, a finer mapping is needed to decipher genetic landscapes of children with this disease to gain insights into pathogenesis and treatment responses.

Methods: We conducted deep WGS on 48 children with JIA over 2 independent cohorts, comparing results with publically available WGS data from healthy individuals. Each cohort contained a replicate to ascertain the fidelity of the sequencing reactions, the first cohort (n= 29) was homogeneous, consisting of non-Hispanic Caucasian children. The second cohort (n=19) was a more heterogeneous group including Hispanic and Caucasian-Native American ancestry children.

Results: We achieved an average of 38.7X sequencing depth per sample, and 41 Giga passed quality control measures. Paired-end reads gave an average per sample mapping rate of 97.9%. We found 1,205,197 novel SNPs and 283,554 novel indels in JIA patients that are not reported in dbSNP141 public repository. We also identified 1,902 novel structural variants (SV) not present in Database of Genomic Variants. By tabulating SNP density in 1Mb windows across the entire genome, we identified 24 SNP hotspots when compared with the 1000 Genome Projects (1KGP). It is of interest to note that some of the genes located within 5kb upstream or downstream 5kb to those SNP hotspots show statistically significant enrichment in immunological processes (including T cell receptor signaling pathways and innate immune responses). Further analyses indicated that JIA SNPs have significantly more regulatory potential (e.g. transcription factor binding motifs, DNase1 hypersensitivity sites, eQTL) compared to 1KGP SNPs. It is also important to note that the JIA specific genetic variation (indels and SNPs) showed ~72% concordance between the 2 cohorts despite the ethnic heterogeneity between the 2 cohorts.

Conclusion: These studies demonstrate the utility of WGS, even on relatively small sample numbers, for elucidating underlying genetics of JIA and its response to therapy. For example, segregation of variants from WGS of JIA individuals in array-based SNP LD blocks overcomes the limitations of depth and coverage of arrays in identifying JIA risk variants. Distribution of JIA novel variants in regulatory elements serves as valuable resource from which to develop insights into epigenetic alterations underlying the effects of genetic variants.


Disclosure: J. Jarvis, None; L. P. Wong, None; K. Jiang, None.

To cite this abstract in AMA style:

Jarvis J, Wong LP, Jiang K. Genetic Insights into Juvenile Idiopathic Arthritis Derived from Deep Whole Genome Sequencing [abstract]. Arthritis Rheumatol. 2016; 68 (suppl 10). https://acrabstracts.org/abstract/genetic-insights-into-juvenile-idiopathic-arthritis-derived-from-deep-whole-genome-sequencing/. Accessed .
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