Rekha Parmar

Mutations in the gene encoding the 3'-5' DNA exonuclease TREX1 cause Aicardi-Goutières syndrome at the AGS1 locus

Aicardi-Goutières syndrome (AGS) presents as a severe neurological brain disease and is a genetic mimic of the sequelae of transplacentally acquired viral infection. Evidence exists for a perturbation of innate immunity as a primary pathogenic event in the disease phenotype. Here, we show that TREX1, encoding the major mammalian 3′ → 5′ DNA exonuclease, is the AGS1 gene, and AGS-causing mutations result in abrogation of TREX1 enzyme activity. Similar loss of function in the Trex1−/− mouse leads to an inflammatory phenotype. Our findings suggest an unanticipated role for TREX1 in processing or clearing anomalous DNA structures, failure of which results in the triggering of an abnormal innate immune response.

Mutations in genes encoding ribonuclease H2 subunits cause Aicardi-Goutières syndrome and mimic congenital viral brain infection

Aicardi-Goutières syndrome (AGS) is an autosomal recessive neurological disorder, the clinical and immunological features of which parallel those of congenital viral infection. Here we define the composition of the human ribonuclease H2 enzyme complex and show that AGS can result from mutations in the genes encoding any one of its three subunits. Our findings demonstrate a role for ribonuclease H in human neurological disease and suggest an unanticipated relationship between ribonuclease H2 and the antiviral immune response that warrants further investigation.

Patients with RA in remission on TNF blockers: when and in whom can TNF blocker therapy be stopped?

Objectives Combination therapy with methotrexate (MTX) and tumour necrosis factor (TNF) blockade has increased remission rates in patients with rheumatoid arthritis. However, there are no guidelines regarding cessation of therapy. There is a need for markers predictive of sustained remission following cessation of TNF blocker therapy. Methods Patients in remission (DAS28 <2.6) treated with a TNF blocker and MTX as initial or delayed therapy were recruited. Joints were assessed for grey scale synovitis and power Doppler (PD) activity. Immunological assessment involved advanced six-colour flow cytometry. Results Of the 47 patients recruited, 27 had received initial treatment and 20 delayed treatment with TNF blocking drugs. Two years after stopping TNF blocker therapy, the main predictor of successful cessation was timing of treatment; 59% of patients in the initial treatment group sustained remission compared with 15% in the delayed treatment group (p=0.003). Within the initial treatment group, secondary analysis showed that the only clinical predictor of successful cessation of treatment was shorter symptom duration before receiving treatment (median 5.5 months vs 9 months; p=0.008). No other clinical features were associated with successful cessation of therapy. Thirty-five per cent of patients had low PD activity but levels were not informative. Several immunological parameters were significantly associated with sustained remission including abnormal differentiation subset of T cells and regulatory T cells. Similar non-significant trends were observed in the delayed treatment group. Conclusion In patients in remission with low levels of imaging synovitis receiving combination treatment with a TNF blocker and MTX, immunological parameters and short duration of untreated symptoms were associated with successful cessation of TNF blocker therapy.

An immunological biomarker to predict MTX response in early RA

Objectives The therapeutic goal for patients with rheumatoid arthritis (RA) is clinical remission. This is best achieved by early diagnosis and appropriate therapeutic intervention. RA is associated with dysregulation of T-cell subsets (naïve, regulatory (Treg) and inflammation-related cells (IRC)) early in the disease. Our aim was to test the hypothesis that T-cell subset quantification can predict the achievement of clinical remission with early treatment in RA. Methods T-cell subsets were quantified in 108 drug-naïve, early RA patients commencing methotrexate (MTX) or MTX+antitumor necrosis factor (anti-TNF) and in 105 healthy controls (HC). The primary outcome assessed was remission (DAS28<2.6). A pilot study used frozen cells (38 patients and 35 HCs, see online supplementary material) and was validated with fresh blood (70 patients and 70 HCs). Results Immune dysregulation in early RA was confirmed with an association between age and reduced naïve cells compared with HCs (p=0.006), a lower age-adjusted Treg and higher IRC frequency (p=0.001). Anticitrullinated peptide antibody (ACPA) positivity was associated with lower naïve (p=0.031) and Treg frequencies (p=0.039). In 50 patients treated with MTX, ACPA/age-adjusted analysis demonstrated that higher naïve cell frequency (relative to HC) was associated with remission (OR 5.90 (1.66 to 20.98), p=0.006, sensitivity/specificity 62%/79%, Positive Predictive Value (PPV)/Negative Predictive Value (NPV) 66%/76%). Remission with MTX+anti-TNF (n=20) was not found to be associated with naïve cell frequency, and for patients with reduced naïve cells the remission rate increased from 24% (MTX) to 42% (MTX+anti-TNF). Conclusions Baseline T-cell subset analysis has a value in predicting early RA remission with first therapy with MTX. Immunological analysis could be used in conjunction with clinical/serological features to predict response to MTX and help select the most appropriate therapy at disease presentation.

Progression to rheumatoid arthritis in early inflammatory arthritis is associated with low IL-7 serum levels

Objective Early diagnosis of rheumatoid arthritis (RA) remains a challenge. Interleukin (IL)-7 is a pleiotropic cytokine that plays a central role in the development and maintenance of T-cells and has been associated with T-cell dysfunction in RA. Serum levels of IL-7 are reduced in both early and established disease. The aim of this study was to determine whether serum IL-7 can identify patients with very early inflammatory joint symptoms who will progress to RA, and to examine whether IL-7 levels predict disease persistence and radiographic progression. Methods Patients with inflammatory joint symptoms <6 months followed over 5 years for progression to RA and 80 healthy controls were studied. Baseline IL-7 levels were measured by ELISA. Results Of 250 patients, 108 developed RA (ACR 1987- criteria). IL-7 at inclusion was reduced significantly in RA compared with non-RA patients (p=0.009). IL-7 was categorised using the lower limit of the healthy control distribution (10 pg/ml). In multivariate analysis, independent predictors of RA development were: antibodies against citrullinated peptides (ACPA) positivity (p=0.001), IL-7<10 pg/ml (p=0.003) and swollen joint count (p=0.050). In the ACPA-negative subgroup (n=199), the only predictors were: DAS-44 (p=0.001), IL-7<10 pg/ml (p=0.010) and radiographic erosions (p=0.050). At 1-year follow-up, remission (DAS<1.6) was only predicted by ACPA negativity (p=0.019) and IL-7>17 pg/ml at recruitment (p=0.013). Conclusion These data demonstrate that low IL-7 levels in patients with recent onset of symptoms may have value as a diagnostic biomarker predicting the progression to RA, particularly in ACPA-negative disease, as well as being related to RA progression.

A1.22 NaÏve and memory CD4+T-cell DNA methylation profile in RA

Introduction Several abnormal features of T-cell responses are observed in RA. These range from MHC disease association, repertoire distortion, compromised thymic activity, accelerated ageing, abnormal signalling, formation of secondary ectopic lymphoid structure. More recently the RA genetic predisposition has been shown to reside mostly in T-cell related genes. We investigated DNA methylation profiles in naïve and memory T-cells isolated from healthy controls and RA patients to identify additional levels of regulation in T-cell functionalities. Methods 6 HC and 10 RA patients (5 ACPA+) were recruited. 30 ml of EDTA blood was collected and naïve and memory T-cells purified using cell sorting. DNA was extracted and treated for bi-sulfite conversion. A 450k micro-bead array (Illumina) was used to investigate genome-wide DNA methylation. QA/QC procedure included inspection of beta-value density plots generated using the “minfi” R package. Results 30/32 samples passed QA/QC procedure. Signal from methylated and un-methylated probes was normalised and converted in to M values using the “minfi” package. M values were analysed using t-tests in the “gene filter” R package. Multidimentional scaling analysis clearly separated naïve from memory cells suggesting that the phenotype of the cells (notably between two CD4+ subsets) is essential for the detection of disease specific changes. Memory cell analysis revealed 37050 differentially methylated positions between health and RA and 36750 for naïve cells (P < 0.05). We selected the top 1000 most significant differences for both subsets and compared them. Surprisingly only 180 positions were common to the 2 subsets but importantly included 5 positions for the IL-6 gene, 15 for histone deacethylation-4 (HDAC4), 26 in Wnt3/Frizzle8 and homeobox-1 pathway and 43 in various transcription factors (notably FoxP1) all suggestive of a strong disease effect. Memory cells showed additional differential methylation of positions near genes such SMAD 2/7, p21-CIP-1, FGFR-3, HSP70 and TNFR-member-13. Naïve cells showed similar differential methylation but for different members of these gene families (TNFR-I, TGFR-3, FGFR-1, HSP40) in addition to other specific genes such as interferon regulator 1, SUMO-1, several PAX transcription factors, P-selectin and importantly the IL-17R. Conclusion These pilot data demonstrate that there are important differences in the methylation of DNA between RA patients and HC that can be identified in relevant pathways provided cells are separated into the same phenotype (naïve vs. memory) even if from the same lineage (both CD4+T-cells).

A3.3 An Immunological Window of Opportunity Defines the Ability of Early RA Patient to Achieve Remission with First Anti-Rheumatic Treatment

Background and Objectives The therapeutic goal for patients with rheumatoid arthritis (RA) is clinical remission. This is best achieved by early diagnosis followed by appropriate therapeutic intervention. RA is associated with dys-regulation of T-cell subsets early in the disease with naïve cells and regulatory T-cell losses and acquisition of abnormal subset in realtion with inflammation (IRC). Our aim was to test the hypothesis that T-cell subset quantification can predict the achievement of clinical remission in patients with early RA. Materials and Methods T-cell subsets (naive, Treg and IRC) were quantified using flow cytometry in 108 DMARDs-naïve, early RA patients (<24 months) symptom duration commencing methot-rexate MTX or MTX + anti-tumour necrosis factor agents (anti-TNF) and in 105 healthy controls (HC). The primary outcome assessed was remission (DAS28 < 2.6). The pilot analysis was performed on frozen PBMC obtained from 38 RA patients and 35 HC. These results were validated using fresh blood samples on a cohort of 70 RA patients and 70 HC. Results In the pilot study, T-cell subset analysis in early RA confirmed immune dysregulation compared to HC with reduced frequency of naïve CD4+ T-cells and Treg and increased IRC (all p < 0.001) compared to HC. Naive T-cell above median was associated with remission (p = 0.001). In the validation study, 50 patients were treated with MTX and showed the same relationship with naïve cell frequency above median being associated with remission (p = 0.011). Individual analysis on each patient’s naïve cell frequency deviation from expected (using 70 HC) demonstrated that “normal” naïve cell frequency (observed in 30 patients) was associated with remission whereas reduced naïve cell frequency was more frequently observed in patients with poor response to MTX (p = 0.03). Patients with poor immunological status were not prevented to achieve remission when treated with MTX + anti-TNF (n = 20 including 10 patients with normal and 10 with reduced naïve cells) raising the rate of remission from 20% in the MTX group (n = 4 of the 20 patients with reduced naïve cells at baseline) to 60% in the MTX + anti-TNF group (n = 6 of the 10 patients). Conclusions These data show that baseline naïve T-cell subset analysis has a value in predicting early RA MTX treatment outcome. Immunological analysis could be used in conjunction with clinical/serological features to predict response to MTX and select the most appropriate therapy at disease presentation.

A1.33 Predicting the evolution of inflammatory arthritis in ACPA-positive individuals: can T-cell subsets help?

Background and Objectives ACPA+ individuals with non-specific musculoskeletal symptoms are at high risk of developing rheumatoid arthritis (RA). We previously demonstrated dys-regulation of T-cell subsets with loss of naïve and regulatory T-cells (Treg) in early disease. The aim of the current study is to demonstrate the predictive value of T-cell subset analysis for progression towards symptom onset in ACPA+ individuals. Materials and Methods 84 ACPA+ individuals without clinical synovitis at recruitment were followed. 95 healthy controls (HC) provided a reference group. At baseline T-cell subset analyses were performed using 6-colour flowcytometry for naïve T-cells (CD4+ CD45RB + CD45RA+ CD62L+), Treg (CD4+ CD25highFoxp3 + CD127low) and inflammation related cells (IRC: CD4+ CD45RB + CD45RA+ CD62L-). The relationship between naïve cell frequency and age was established in HC and used to age-correct values in ACPA+ . ROC curve analysis was used to identify 2 T-cell cut-offs predicting progression to IA at any time; one which maximised the Youden index (sensitivity + specificity-1), and one which prioritised specificity over sensitivity. Results 42/84 (50%) of patients developed clinical synovitis within a median follow-up of 6.0 months (range 1 week-46 months). For age-corrected naïve T-cells area under the ROC curve (AUC) was 0.67 (95% CI 0.55, 0.79; n = 84, p = 0.007), for IRC 0.70 (0.59, 0.81; n = 81, p = 0.002) and for Treg 0.67 (0.53, 0.80; n = 65, p = 0.021). For each of the three subsets, the Youden index cut-off correctly classified >65% of patients (Table 1). Cut-offs prioritising specificity were identified which did not greatly reduce overall classification success. The confidence intervals for these estimates remain wide and our sample size may still be limited for running such analysis. Youden index cut-off Specificity priority cut-off Subset Cut-off Sensitivity Specificity % Correct Cut-off Sensitivity Specificity % Correct Naïve ≤-6.4 59.5 (43.3, 74.4) 76.2 (60.5, 87.9) 67.9 ≤-14.0 26.2 (13.9, 42.0) 90.5 (77.4, 97.3) 58.3 IRC ≥2.8 56.4 (39.6, 72.2) 76.2 (60.5, 87.9) 66.7 ≥4.5 30.8 (17.0, 47.6) 90.5 (77.4, 97.3) 61.7 Treg ≤4.15 90.6 (75.0, 98.0) 41.2 (24.6, 98.0) 65.1 ≤1.6 34.4 (18.6, 53.2) 91.2 (76.3, 98.1) 63.7 Abstract A1.33 Table 1 Sensitivity and specificity of T-cell subset frequencies for progression to IA, using two different cut-off values for each subset; one where the Youden index was maximised and another that prioritised specificity over sensitivity. Conclusions T-cell dys-regulation in ACPA+ individuals with non-specific musculoskeletal pain may be useful in predicting progression to inflammatory arthritis. Multivariable modelling in larger cohorts is needed to quantify the utility of T-cell subsets in predicting progression to IA.

A tissue-specific promoter derived from a SINE retrotransposon drives biallelic expression of PLAGL1 in human lymphocytes

The imprinted gene PLAGL1 is an important regulator of apoptosis and cell cycle arrest. Loss of its expression has been implicated in tumorigenesis in a range of different cancers, and overexpression during fetal development causes transient neonatal diabetes mellitus (TNDM). PLAGL1 lies within an imprinted region of chromosome 6q24, and monoallelic expression from the major, differentially methylated promoter (P1) occurs in most human tissues. However, in peripheral blood leukocytes, the active promoter (P2) is non-imprinted and drives biallelic transcription. We report here a novel PLAGL1 promoter (P5) derived from the insertion of a primate-specific, MIR3 SINE retrotransposon. P5 is highly utilized in lymphocytes, particularly in T cells, and like P2, directs biallelic transcription. Our results show that it is important to consider P5 in relation to PLAGL1 function in T cells when investigating the dysregulation of this gene.

05.03 Differential methylation profile of tnf-signalling genes in t-cells and monocytes

Background Recently, epigenetics has become an important field of research, with several diseases related to alteration in methylation patterns. Whether these epimutations are early events due to a local perturbation causing the initial epigenetic event and then leading to pathogenesis, or a later consequence of the pathology itself remains open for discussion. The objective of this study is to assess the methylation patterns of CpG islands in naïve and memory T-cells and monocytes from drug-naïve, early Rheumatoid arthritis (RA) patients. Materials and methods The methylation patterns of 480,000 CpGs were measured in 6 healthy controls and 10 RA patients using an Illumina methylation genome-wide array (EWAS). T-tests were used to calculate the significance of the methylation differences at each CpG site. A p-value of 1 × 10–4 was used to elucidate highly specific differences. Methylation patterns of individual promoters were then reconstructed using the Human genome database for the position and length of CpG islands. The genes with 3 or more differentially methylated CpGs clustered over a short distance and localised in potentially regulatory regions of the gene were deemed relevant. Results Analysis of the EWAS data showed 4123 CpG sites differently methylated in naïve T-cells, 2672 in memory T-cells and 904 in monocytes. Of the relevant genes, TNFR1 appeared particularly interesting. We therefore focused our next analysis on the TNF-α signalling pathway as this has proven pivotal in early disease. Results highlight 9 genes implicated in the 3 TNF-signalling cascades: TNFR1, LTBR, TRAF1, BCL2, UACA, RNF36, MIR21, DAXX and MAP3K14-AS1. These 9 loci exhibited different methylation patterns in naïve T-cells. Each had between 3 and 10 CpGs with differential methylation over short DNA regions (<250 bp) suggesting a potential effect the 3-dimentional structure of the DNA possibly affecting gene expression. These patterns were highly specific to naïve T-cells and were not observed in memory T-cells or monocytes in RA. Conclusion Naïve T-cells have been implicated in RA pathogenesis through activation/differentiation by cytokine rather than antigen.1 This data confirms the selective role of naïve T-cells in early RA primarily linked to differences in up- and down-regulation of elements involved in the TNF-signalling pathway. Reference Blood, 2002;100:4550–6.