Dataset Information

Deletion at 2q14.3 is associated with worse response to TNF-? blockers in patients with rheumatoid arthritis.

ABSTRACT:

Background

Structural variations such as copy number variations (CNVs) have a functional impact on various human traits. This study profiled genome-wide CNVs in Korean patients with rheumatoid arthritis (RA) to investigate the efficacy of treatment with TNF-? blockers.

Methods

A total of 357 Korean patients with RA were examined for the efficacy of TNF-? blocker treatment. Disease activity indexes were measured at baseline and 6?months after the treatment. The patients were classified as responders and non-responders based on the change in disease activity indexes according to the EULAR response criteria. CNVs in the same patients were profiled using fluorescence signal intensity data generated by a genome-wide SNP array. The association of CNVs with response to TNF-? blockers was analyzed by multivariate logistic regression accounting for genetic background and clinical factors including body mass index, gender, baseline disease activity, TNF-? blocker used, and methotrexate treatment.

Results

The study subjects varied in their responses to TNF-? blockers and had 286 common CNVs in autosomes. We identified that the 3.8-kb deletion at 2q14.3 in 5% of the subjects was associated with response to TNF-? blockers (1.37?×?10^-?5???P???4.07?×?10^-?4) at a false discovery rate threshold of 5%. The deletion in the identified CNV was significantly more frequent in the non-responders than in the responders, indicating worse response to TNF-? blockers in the deletion carriers. The 3.8-kb deletion at 2q14.3 is located in an intergenic region with the binding sites of two transcription factors, MAFF and MAFK.

Conclusions

This study obtained the CNV landscape of Korean patients with RA and identified the common regional deletion associated with poor response to treatment with TNF-? blockers.

SUBMITTER: Gu KN

PROVIDER: S-EPMC6714408 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Deletion at 2q14.3 is associated with worse response to TNF-α blockers in patients with rheumatoid arthritis.

Gu Ki-Nam KN Bang So-Young SY Lee Hye-Soon HS Park Youngho Y Kang Ju-Yeon JY Kim Ji-Soong JS Nam Bora B Yoo Hyun-Seung HS Shin Jung-Min JM Lee Yeon-Kyung YK Lee Tae-Han TH Chun Sehwan S Cho Soo-Kyung SK Choi Chan-Bum CB Sung Yoon-Kyoung YK Kim Tae-Hwan TH Jun Jae-Bum JB Yoo Dae Hyun DH Kim Kwangwoo K Bae Sang-Cheol SC

Arthritis research & therapy 20190828 1

<h4>Background</h4>Structural variations such as copy number variations (CNVs) have a functional impact on various human traits. This study profiled genome-wide CNVs in Korean patients with rheumatoid arthritis (RA) to investigate the efficacy of treatment with TNF-α blockers.<h4>Methods</h4>A total of 357 Korean patients with RA were examined for the efficacy of TNF-α blocker treatment. Disease activity indexes were measured at baseline and 6 months after the treatment. The patients were classi ...[more]

PMID: 31462329

Similar Datasets

Project description:In clinical practice, approximately one-third of patients with rheumatoid arthritis (RA) respond insufficiently to TNF-α inhibitors (TNFis). The aim of the study was to explore the use of a metabolomics to identify predictors for the outcome of TNFi therapy, and study the metabolomic fingerprint in active RA irrespective of patients' response. In the metabolomic profiling, lipids, oxylipins, and amines were measured in serum samples of RA patients from the observational BiOCURA cohort, before start of biological treatment. Multivariable logistic regression models were established to identify predictors for good- and non-response in patients receiving TNFi (n = 124). The added value of metabolites over prediction using clinical parameters only was determined by comparing the area under receiver operating characteristic curve (AUC-ROC), sensitivity, specificity, positive- and negative predictive value and by the net reclassification index (NRI). The models were further validated by 10-fold cross validation and tested on the complete TNFi treatment cohort including moderate responders. Additionally, metabolites were identified that cross-sectionally associated with the RA disease activity score based on a 28-joint count (DAS28), erythrocyte sedimentation rate (ESR) or C-reactive protein (CRP). Out of 139 metabolites, the best-performing predictors were sn1-LPC(18:3-ω3/ω6), sn1-LPC(15:0), ethanolamine, and lysine. The model that combined the selected metabolites with clinical parameters showed a significant larger AUC-ROC than that of the model containing only clinical parameters (p = 0.01). The combined model was able to discriminate good- and non-responders with good accuracy and to reclassify non-responders with an improvement of 30% (total NRI = 0.23) and showed a prediction error of 0.27. For the complete TNFi cohort, the NRI was 0.22. In addition, 88 metabolites were associated with DAS28, ESR or CRP (p<0.05). Our study established an accurate prediction model for response to TNFi therapy, containing metabolites and clinical parameters. Associations between metabolites and disease activity may help elucidate additional pathologic mechanisms behind RA.

Project description:ObjectiveMany patients with rheumatoid arthritis (RA) benefit from tumor necrosis factor-α blocking treatment (anti-TNF), but about one third do not respond. The objective of this study was to replicate and extend previously found associations between anti-TNF treatment response and genetic variation in the TNF-, NF-κB- and pattern recognition receptor signalling pathways.MethodsForty-one single nucleotide polymorphisms (SNPs), including 34 functional, in 28 genes involved in inflammatory pathways were assessed in 538 anti-TNF naive Danish RA patients with clinical data. Multivariable logistic regression analyses were performed to test associations between genotypes and treatment response at 3-6 months using the European League Against Rheumatism (EULAR) response criterion. American College of Rheumatology treatment response (ACR50) and relative change in 28-joint disease activity score (relDAS28) were used as secondary outcomes. Subgroup analyses were stratified according to smoking status, type of anti-TNF drug and IgM-Rheumatoid Factor (IgM-RF) status. False discovery rate (FDR) controlling was used to adjust for multiple testing.ResultsStatistically significant associations with EULAR response were found for two SNPs in NLRP3(rs4612666) (OR (odds ratio) for good/moderate response = 0.64 (95% confidence interval: 0.44-0.95), p = 0.025, q = 0.95) and INFG(rs2430561) (OR = 0.40 (0.21-0.76), p = 0.005, q = 0.18) and among IgM-RF positive patients for TNFRS1A(rs4149570) (0.59 (0.36-0.98), p = 0.040, q = 0.76). Current smokers who carried the NLRP3(rs4612666) variant allele were less likely to benefit from anti-TNF treatment (OR = 0.24 (0.10-0.56), p = 0.001, q = 0.04).ConclusionsIn a population of Danish RA patients, we confirm the NLRP3 gene as associated with EULAR anti-TNF response as previously reported. The NLRP3 variant (T) allele is associated with lower treatment response, in particular among current smokers. Furthermore, we find that a functional polymorphism in the interferon-γ gene is associated with anti-TNF response. All findings should be tested by replication in independent validation cohorts and augmented by assessing cytokine levels and activities of the relevant gene products.

Project description:Background: Rheumatoid arthritis (RA) is a chronic inflammatory disorder primarily targeting joints, significantly impacting patients' quality of life. The introduction of tumor necrosis factor-alpha (TNF-α) inhibitors has markedly improved RA management by reducing inflammation. However, these medications are associated with adverse skin reactions, which can vary greatly among patients due to genetic differences. Objectives: This study aimed to identify risk factors associated with skin adverse events by TNF-α in RA patients. Methods: A cohort study was conducted, encompassing patients with RA who were prescribed TNF-α inhibitors. This study utilized machine learning algorithms to analyze genetic data and identify markers associated with skin-related adverse events. Various machine learning algorithms were employed to predict skin and subcutaneous tissue-related outcomes, leading to the development of a risk-scoring system. Multivariable logistic regression analysis identified independent risk factors for skin and subcutaneous tissue-related complications. Results: After adjusting for covariates, individuals with the TT genotype of rs12551103, A allele carriers of rs13265933, and C allele carriers of rs73210737 exhibited approximately 20-, 14-, and 10-fold higher incidences of skin adverse events, respectively, compared to those with the C allele, GG genotype, and TT genotype. The machine learning algorithms used for risk prediction showed excellent performance. The risk of skin adverse events among patients receiving TNF-α inhibitors varied based on the risk score: 0 points, 0.6%; 2 points, 3.6%; 3 points, 8.5%; 4 points, 18.9%; 5 points, 36.7%; 6 points, 59.2%; 8 points, 90.0%; 9 points, 95.7%; and 10 points, 98.2%. Conclusions: These findings, emerging from this preliminary study, lay the groundwork for personalized intervention strategies to prevent TNF-α inhibitor-associated skin adverse events. This approach has the potential to improve patient outcomes by minimizing the risk of adverse effects while optimizing therapeutic efficacy.

Project description:ObjectivesTo determine whether genetic variation within genes related to the Toll-like receptor, inflammasome and interferon-γ pathways contributes to the differences in treatment response to tumour necrosis factor inhibitors (anti-TNF) in patients with rheumatoid arthritis (RA).MethodsIn a retrospective case-case study, we assessed 23 functional single nucleotide polymorphisms (SNPs) in 15 genes. We included 538 anti-TNF naïve Danish RA patients from the nationwide DANBIO database. Multivariable logistic regression analyses were performed to detect associations (p-value<0.05) between genotypes and European League Against Rheumatism (EULAR) treatment responses. False Discovery Rate corrections for multiple testing (q-value) and stratified analyses were performed to investigate association with individual therapies and IgM-rheumatoid factor (RF) status.ResultsSix of twenty successfully genotyped polymorphisms were nominally associated with EULAR treatment response. Three of these were in weak to moderate linkage disequilibrium with polymorphisms previously reported associated with anti-TNF treatment response. TLR5(rs5744174) variant allele carriers (odds ratio(OR) = 1.7(1.1-2.5),p = 0.010,q = 0.46) and TLR1(rs4833095) homozygous variant carriers (OR = 2.8(1.1-7.4),p = 0.037,q = 0.46) had higher odds for a positive treatment response. NLRP3(rs10754558) variant allele carriers (odds ratio(OR) = 0.6(0.4-1.0),p = 0.045,q = 0.46) were more likely to have a negative treatment response. The association in TLR5(rs5744174) remained significant after correction for multiple comparisons among patients negative for RF (OR = 6.2(2.4-16.3),p = 0.0002,q = 0.024). No other association withstood correction for multiple testing. Post hoc analyses showed that change in Patient Global score on a visual analogue scale (VAS) and change in pain VAS were the main factors responsible for the association.ConclusionsWe reproduced previously reported associations between genetic variation in the TLR10/1/6 gene cluster, TLR5, and NLRP3 loci and response to anti-TNF treatment in RA. Changes in VAS pain and patient global scores were the main contributors to the association found for TLR5. Furthermore, we identified other candidate genes that require replication in independent cohorts.

Project description:BackgroundRheumatoid arthritis (RA) is a genetically predisposed, systemic, chronic, inflammatory disease. Immune system dysregulation and inherited susceptibility polymorphisms suggest that this type of variation is functional and may help predict disease susceptibility and develop new therapeutic strategies. Anti-TNF-alpha (TNF-α) drugs are highly effective RA treatments, but not all patients respond the same way. It's important to figure out whether RA risk alleles can identify and predict anti-TNF-α-responsiveness in RA patients.Aims of the studyExamine the function of the NLR family pyrin domain containing 3 (NLRP3) and caspase recruitment domain family member 8 (CARD8) genes polymorphisms and their morbid genotypes and alleles in RA patients and apparently healthy controls. In addition, their role in disease susceptibility, severity, and response to anti-TNF-α therapy. Also, examine how single nucleotide polymorphisms (SNPs) affect serum levels of pro-inflammatory cytokines like TNF-α and interleukin (IL)-1β.Materials and methods100 RA patients (88 females, 12 males) and 100 apparently healthy people (86 females, 14 males) were examined. To measure serum TNF-α and IL-1β, Elabscience sandwich ELISA kits were used. Iraq Biotech, Turkey DNA extraction kit was used to extract genomic DNA from whole blood. CARD8 (rs2043211) and NLRP3 (rs4612666) were genotyped using Agilent, AriaMx, USA, through Tri-Plex SYBR Green-based real-time PCR allelic discrimination assays. Geneious software, version 2019.2.2, used to design primers from published sequences (GenBank accession no. GCA 009914755.1). Primer specificity was determined by NCBI's BLAST.ResultsStudy found that there is association between cytokines serum level and 28-joints disease activity score (DAS-28). The level of TNF-α increases with the higher DAS-28 (r2 = 0.45, P < 0.0001). Also, IL- 1β level increases with higher DAS-28 (r2 = 0.51, P < 0.0001). There were no statistically significant variations between patients with RA and the control group in the distribution of CARD8 SNP rs2043211 and NLRP3 SNP rs4612666 genotypes (P = 0.17 and 0.08 respectively) as well their alleles (P = 0.059 and 0.879 respectively). CARD8 (rs2043211) TT genotype was more frequent in patients with higher DAS-28 (P < 0.0001) and higher TNF-α and IL-1β serum levels (P < 0.0001 for both). Also, NLRP3 (rs4612666) TT genotype was more frequent in patients with higher DAS-28 (P < 0.0001) and higher TNF-α and IL- 1β serum levels (P < 0.0001 for both). Interestingly, this study revealed that CARD8 (rs2043211) and NLRP3 (rs4612666) variant genotypes are associated with lower response to anti-TNF-α drugs.ConclusionsSerum TNF-α and IL-1β correlate with DAS-28 and disease activity. Non-responders have elevated TNF-α and IL-1β. CARD8 rs2043211 and NLRP3 rs4612666 variant polymorphisms are associated with high serum TNF-α and IL-1β, active disease course, poor disease outcomes, and low response to anti-TNF-α therapy.

Project description:Objectives: To assess whether the histopathological features of the synovium before starting treatment with the TNFi certolizumab-pegol could predict clinical outcome and examine the modulation of histopathology by treatment. Methods: Thirty-seven RA patients fulfilling UK NICE guidelines for biologic therapy were enrolled at Barts Health NHS trust and underwent synovial sampling of an actively inflamed joint using ultrasound-guided needle biopsy before commencing certolizumab-pegol and after 12-weeks. At 12-weeks, patients were categorized as responders if they had a DAS28 fall >1.2. A minimum of 6 samples was collected for histological analysis. Based on H&E and immunohistochemistry (IHC) staining for CD3 (T cells), CD20 (B cells), CD138 (plasma cells), and CD68 (macrophages) patients were categorized into three distinct synovial pathotypes (lympho-myeloid, diffuse-myeloid, and pauci-immune). Results: At baseline, as per inclusion criteria, DAS28 mean was 6.4 ± 0.9. 94.6% of the synovial tissue was retrieved from the wrist or a metacarpophalangeal joint. Histological pathotypes were distributed as follows: 58% lympho-myeloid, 19.4% diffuse-myeloid, and 22.6% pauci-immune. Patients with a pauci-immune pathotype had lower levels of CRP but higher VAS fatigue compared to lympho- and diffuse-myeloid. Based on DAS28 fall >1.2, 67.6% of patients were deemed as responders and 32.4% as non-responders. However, by categorizing patients according to the baseline synovial pathotype, we demonstrated that a significantly higher number of patients with a lympho-myeloid and diffuse-myeloid pathotype in comparison with pauci-immune pathotype [83.3% (15/18), 83.3 % (5/6) vs. 28.6% (2/7), p = 0.022) achieved clinical response to certolizumab-pegol. Furthermore, we observed a significantly higher level of post-treatment tender joint count and VAS scores for pain, fatigue and global health in pauci-immune in comparison with lympho- and diffuse-myeloid patients but no differences in the number of swollen joints, ESR and CRP. Finally, we confirmed a significant fall in the number of CD68+ sublining macrophages post-treatment in responders and a correlation between the reduction in the CD20+ B-cells score and the improvement in the DAS28 at 12-weeks. Conclusions: The analysis of the synovial histopathology may be a helpful tool to identify among clinically indistinguishable patients those with lower probability of response to TNF?-blockade.