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Frontiers of Medicine

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Front. Med.    2019, Vol. 13 Issue (4) : 411-419    https://doi.org/10.1007/s11684-018-0659-3
REVIEW
Genetic and clinical markers for predicting treatment responsiveness in rheumatoid arthritis
Xin Wu1, Xiaobao Sheng2,3, Rong Sheng1, Hongjuan Lu1, Huji Xu1,4,5()
1. Department of Rheumatology and Immunology, Shanghai Changzheng Hospital, the Second Military Medical University, Shanghai 200003, China
2. School of Economics and Management, Tongji University, Shanghai 200092, China
3. The Third Research Institute of the Ministry of Public Security, Shanghai 200031, China
4. Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing 100084, China
5. Peking-Tsinghua Center for Life Sciences, Tsinghua University, Beijing 100084, China
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Abstract

Although many drugs and therapeutic strategies have been developed for rheumatoid arthritis (RA) treatment, numerous patients with RA fail to respond to currently available agents. In this review, we provide an overview of the complexity of this autoimmune disease by showing the rapidly increasing number of genes associated with RA. We then systematically review various factors that have a predictive value (predictors) for the response to different drugs in RA treatment, especially recent advances. These predictors include but are certainly not limited to genetic variations, clinical factors, and demographic factors. However, no clinical application is currently available. This review also describes the challenges in treating patients with RA and the need for personalized medicine. At the end of this review, we discuss possible strategies to enhance the prediction of drug responsiveness in patients with RA.
Keywords rheumatoid arthritis      gene      clinical markers      therapy     
Corresponding Author(s): Huji Xu   
Just Accepted Date: 20 November 2018   Online First Date: 14 January 2019    Issue Date: 02 August 2019
 Cite this article:   
Xin Wu,Xiaobao Sheng,Rong Sheng, et al. Genetic and clinical markers for predicting treatment responsiveness in rheumatoid arthritis[J]. Front. Med., 2019, 13(4): 411-419.
 URL:  
https://academic.hep.com.cn/fmd/EN/10.1007/s11684-018-0659-3
https://academic.hep.com.cn/fmd/EN/Y2019/V13/I4/411
Fig.1  Overview of the MEDLINE/PubMed records related to RA (left panel) and the associated human genes (right panel), stratified by the year of publication. The left panel shows the number of related publications per year from the 1950s to 2013, whereas the right panel shows the total number of genes that are known to be associated with RA in a particular year and the years prior (cumulative sum). Related data are provided in Supplementary Table 1.
Interpro ID Annotation No. of genes
IPR007110 Immunoglobulin-like domain 68
IPR003599 Immunoglobulin subtype 51
IPR011009 Protein kinase-like domain 40
IPR000719 Protein kinase domain 37
IPR001245 Serine-threonine/tyrosine-protein kinase catalytic domain 37
IPR002290 Serine/threonine/dual specificity protein kinase, catalytic domain 37
IPR020635 Tyrosine-protein kinase, catalytic domain 37
IPR013106 Immunoglobulin V-set domain 34
IPR001811 Chemokine interleukin-8-like domain 30
IPR003598 Immunoglobulin subtype 2 25
Tab.1  Top 10 most frequently occurring protein families and functional domains (according to InterPro) in the 610 RA-associated genes
NCBI Entrez ID No. of PubMed abstracts HGNC gene symbol Note
7124 574 TNF Cytokine
3123 173 HLA-DRB1 Immunoglobulin
3569 157 IL6 Cytokine
3605 68 IL17A Cytokine
26191 64 PTPN22 Kinase
7422 61 VEGFA Cytokine
920 56 CD4 Immunoglobulin
4790 53 NFKB1 Transcription factor
8797 50 TNFRSF10A TNF receptor
3586 47 IL10 Cytokine
Tab.2  Top 10 most studied RA genes according to their associated MEDLINE/PubMed records
NCBI Entrez ID HGNC gene symbol Associated variations DMARD/TNF-blocking agent Note (reference and statistics)
1544 CYP1A2 SNP Leflunomide CYP1A2*1F allele is associated with leflunomide toxicity [17]; CC vs. A allele: OR= 9.7 (95% CI= 2.276–41.403), P = 0.002
s1557 CYP2C19 SNP Leflunomide CYP2C19*2 allele influences leflunomide metabolite concentrations that are associated with treatment responses but not with leflunomide-induced toxicity [18]; leflunomide metabolite concentration was ~71% higher in carriers in the CYP2C19*2 allele than in noncarriers
2212 FCGR2A Infliximab Infliximab treatment in patients with RA is influenced by the FCGR2A and FCGR3A genotypes; this effect is observed at different times during follow-up (6 and 30 weeks, respectively) [19]; in patients with low-affinity homozygotes, FCGR2A and FCGR3A alleles could achieve better responses to infliximab (P<0.05 for both cases)
2214 FCGR3A Infliximab Stated in the comment above and also in the reference [19]
SNP rs396991 Infliximab The wild-type allele is associated with better treatment responses, and the strength of the response depends on the type and stage of disease [20]; patients with homozygous V158F polymorphism achieved better response to infliximab (P<0.05)
3135 HLA-G Indel Methotrexate A –14bp deletion in the 3′-unstranslated region (3′ UTR) of HLA-G was clinically advantageous for methotrexate treatment; however, the results were controversial among studies [21–23]; for example, one study showed that the –14/–14 bp deletion was enriched in the responder group (OR= 2.46 with 95% CI= 1.26–4.84, P = 0.009) [21], whereas another study reported the lack of significant results [23]
3569 IL6 SNP; −174 Rituximab −174 CC genotype is associated with a lack of response to rituximab [24] (OR= 2.83; 95% CI= 1.10–7.27; P = 0.031)
3586 IL10 Etanercept Promoter polymorphisms in IL10 are useful in predicting clinical response to etanercept treatment [25]
4524 MTHFR SNP; C677T and A1298C Methotrexate C667T polymorphism is associated with responses to methotrexate; however, controversial results were recorded among different populations [26–29]
5243 ABCB1 SNP; C3435T Methotrexate More nonresponders to methotrexate were found in patients with the TT allele than the CC allele [30] (OR= 8.78, P = 0.038)
7124 TNF SNP; −308 Adalimumab Promoter SNP −308 is associated with treatment responses to adalimumab [31]; 88.2% of G/G versus 68.4% of G/A for the −308 polymorphism were responders (P = 0.05)
SNP; −308 Etanercept Promoter SNP −308 is not associated with treatment responses to etanercept [32]
SNP; −238 and+489 Methotrexate Promoter SNP −238 GG homozygosity is associated with severity and unresponsiveness, but the coding+489 polymorphism is not; the −238 AG genotype is absent in severe-unresponsive RA but present in mild-responsive RA subjects; thus, −238 GG homozygosity is associated with severity and unresponsiveness [33]
SNP; −308 and −238 Infliximab Promoter SNP −238 is associated with treatment responses to infliximab, but the −308 SNP is not; A allele carrier state was significantly lower among responders (OR 0.344, 95% CI= 0.152–0.779, P = 0.01) [34]
7133 TNFRSF1B SNP; M296R Infliximab The M196R SNP leads to lower responsiveness to infliximab [35]
7298 TYMS Indel Methotrexate 3′ UTR indel is associated with responses to methotrexate [27]; in patients with RA with the CC genotype, the OR (95% CI) for the risk of toxicity was 3.8 (2.29–6.33) for the CT genotype and 4.7 (2.40–9.04) for the TT genotype)
Tab.3  Gene polymorphisms and associations with response to DMARDs and drugs
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