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Abstract Number: 896

Pharmacogenomics Study of Predicting Response of TNF Blocker and Medical Image Progression in Chinese Han Ankylosing Spondylitis Population

Jing Liu1, Weilin Pu1, Qi Zhu2, He Fan1, Wei Wan3, Hejian Zou4, Xiaodong Zhou5, John D. Reveille6, Dongyi He2 and Jiucun Wang1, 1State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China, 2Institute of Arthritis Research, Shanghai Academy of Chinese Medical Sciences, Guanghua Integrative Medicine Hospital, Shanghai, China, 3Division of Rheumatology, Changhai Hospital, Shanghai, China, 4Division of Rheumatology, Huashan Hospital, Fudan University, Shanghai, China, 5Internal Medicine-Rheumatology, McGovern Medical School at the University of Texas Health Science Center at Houston, Houston, TX, 6McGovern Medical School at the University of Texas Health Science Center at Houston, Houston, TX

Meeting: 2018 ACR/ARHP Annual Meeting

Keywords: ankylosing spondylitis (AS) and treatment, Genetic Biomarkers, Imaging

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Session Information

Date: Sunday, October 21, 2018

Session Title: 3S088 ACR Abstract: Spondyloarthritis Incl PsA–Clinical I: Axial SpA Epidemiology (892–897)

Session Type: ACR Concurrent Abstract Session

Session Time: 2:30PM-4:00PM

Background/Purpose:

TNF blockers, have been widely used in immune-mediated diseases and many genetic variations predicting treatment response have been described. We applied previously published genetic variations relevant in response of TNF blockers of rheumatoid arthritis (RA) and spondyloarthritis (SpA) to predict treatment response and radiographic progression of ankylosing spondylitis (AS) patients.

Methods:

We recruited 142 AS patients from three medical centers (Guanghua, Changhai and Zhongshan hospital in China). All patients have stopped treatment for more than 6 months before we recruited them or never been treated with TNF blockers. The response to etanercept or adalimumab was evaluated at 3-month and 6-month followup visits by different criteria (BASDAI 50, ASAS20, ASAS 40, ASAS5/6, partial remission and difference of ASDAS) and 62 of AS patients were evaluated for disease activity or progression with MRI (SPARCC) and radiographic imaging. Sixty-two genetic variations were collected by searching in PUBMED. Statistical analyses included Fisher’s exact test and logistic regression analysis.

Results:

Most of key loci identified belonged to genes in the Toll-like receptor signaling pathway and other immune-relevant loci. The results showed important differences between etanercept and adalimumab when associations between genetic polymorphisms and treatment response were examined. Genetic variations in ARFGAP2 alleles showed significantly difference between responders and non-responders, especially in patients treated with etanercept (OR = 0.21, P-value = 0.0004). When ASDAS was performed as the response criterion, a SLCO1C1 allele was highly associated with treatment response (OR = 12.72, P-value = 0.0004), and in the etanercept subgroup, none of the non-responders carried it (P-value = 0.008). In addition, genetic loci in LRPAP1 had strong linkage with the variation of fat metaplasia and erosion. It was associated with the variation of erosion both in 3-month follow-up and 6-month follow-up. Genetic loci in MYOM2 was associated with the variation of backfill after 6-month treatment. IL10 were associated with ankyloses at baseline. ACE and S100A8 are significantly associated with mSASSS score of sacroiliac and spine at baseline, respectively (Table 1).

Conclusion:

Several genetic loci showed significantly differences between responders and non-responders to anti-TNF agents in AS and may also predict the MRI/radiographic inflammation and disease progression. This suggests an important role of pharmacogenomics profiling in predicting treatment response and disease progression.

Table 1 Genetic loci associated with Image progression

Gene

β

P-value

MRI (N=65)

sacroiliac joint inflammation

ARFGAP2

8

0.02

spine inflammation

TNF

-7.6

0.02

fat metaplasia

LRPAP1

-1.8

0.004

erosion

LRPAP1

1.1

0.006

backfill

MYOM2

-1.6

0.003

ankylosis

IL10

8.1

0.003

mSASSS (N=65)

sacroiliac

ACE

0.66

0.04

spine

S100A8

11.2

0.01


Disclosure: J. Liu, None; W. Pu, None; Q. Zhu, None; H. Fan, None; W. Wan, None; H. Zou, None; X. Zhou, None; J. D. Reveille, None; D. He, None; J. Wang, None.

To cite this abstract in AMA style:

Liu J, Pu W, Zhu Q, Fan H, Wan W, Zou H, Zhou X, Reveille JD, He D, Wang J. Pharmacogenomics Study of Predicting Response of TNF Blocker and Medical Image Progression in Chinese Han Ankylosing Spondylitis Population [abstract]. Arthritis Rheumatol. 2018; 70 (suppl 9). https://acrabstracts.org/abstract/pharmacogenomics-study-of-predicting-response-of-tnf-blocker-and-medical-image-progression-in-chinese-han-ankylosing-spondylitis-population/. Accessed March 23, 2023.
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