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. 2026 May 11;28:137. doi: 10.1186/s13075-026-03823-9

Clinical characteristics and response to standard-of-care treatment in systemic lupus erythematosus patients with or without anti-ribonucleoprotein (RNP) antibodies: an Australian, multi-centre cohort study

Rangi Kandane-Rathnayake 1,✉, Rachel Koelmeyer 1, Shereen Oon 2, Maureen Rischmueller 3, Yumi Oh 4, Sean O’Neill 5,6, Geraldine Hassett 5, Sachin Khetan 7, Ted Tsai 8, Fiona Goldblatt 9, Ashleigh Hennessey 10, Dwarakanathan Ranganathan 11, Adrienne Lefeber 12, Tamas Shisha 13, Peter Gergely 13, Mandana Nikpour 2,14, Eric Morand 1,15, Alberta Hoi 1,15
PMCID: PMC13330039  PMID: 42116187

Abstract

Background

Anti-ribonucleoprotein (RNP) (auto)antibodies are frequently detected in patients with systemic lupus erythematosus (SLE) although their associations with SLE disease activity remain incompletely understood. We compared patient characteristics, including disease severity outcomes, between adult patients with SLE with or without anti-RNP antibodies (RNP + versus RNP-).

Methods

We used data from a national, multicentre registry of SLE patients in Australia, collected prospectively between 2007 and 2023. Anti-RNP status and other serological profiles along with demographics were recorded at enrolment. At each routine clinic visit, medication details and disease activity indicators (SLEDAI-2 K, PGA) were captured, and treat-to-target (T2T) states, lupus low disease activity state (LLDAS) and DORIS remission (REM), were determined. Clinical characteristics were compared between RNP + and RNP- patients at 6 months (182 ± 30 days) and 12 months (365 ± 30 days) from enrolment.

Results

A total of 587 patients were studied. 174 (29.6% (95%CI: 26.1%, 33.4%)) were RNP + with significantly higher disease activity and more medication use at enrolment compared with RNP- patients (SLEDAI-2 K median [IQR]: 8.0 [4.0, 10.0] versus 4.0 [2.0, 8.0], p < 0.001; PGA: 0.9 [0.4, 1.2] versus 0.5 [0.2, 1.0], p < 0.001; daily glucocorticoid dose 6.8 [0.0, 15.0] versus 3.0 [0.0, 10.0] mg/day, p < 0.001). RNP + group had more patients with renal, cutaneous, and serological activity. At enrolment, a greater proportion of RNP + patients had active disease (SLEDAI-2 K ≥ 6) compared with RNP- patients (53% versus 41%, p < 0.007), whereas significantly fewer RNP + patients were in LLDAS (20% versus 32.2%, p-value = 0.004) or REM (11.6% versus 22.6%, p-value = 0.006). RNP + patients were 18-fold more likely to be positive for anti-Sm antibodies, and associations with disease activity attenuated upon adjustment for this, though highest disease activity was observed in patients positive to both anti-RNP and anti-Sm autoantibodies (RNP + Sm +).

Disease activity indicators between RNP + and RNP- groups converged within the first 12 months following enrolment. Glucocorticoid and immunosuppressant use remained significantly higher in RNP + Sm + patients.

Conclusions

Anti-RNP positive patients presented with a higher burden of disease activity, and required more intensive treatment with glucocorticoids and immunosuppressants during the first year since study of follow-up, but this was largely driven by the strong association of anti-RNP positivity with anti-Sm positivity.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13075-026-03823-9.

Keywords: SLE, Anti-RNP autoantibodies, Disease activity, Standard of care, Cohort study

Introduction

Autoreactivity to ribonucleoproteins (RNPs) is commonly observed in systemic lupus erythematosus (SLE). Multiple RNP targets have been described, including small nuclear and small cytoplasmic RNPs, that play essential roles in cellular processes such as mRNA splicing and the regulation of gene expression [1]. While the mechanism(s) by which autoantibodies to these antigens contribute to inflammation and tissue damage in SLE remains incompletely understood, previous studies have reported associations with specific disease phenotypes [2–6]. Among these, antibodies to U1 RNP are classically associated with the mixed connective tissue disease (MCTD) phenotype, characterised by arthritis and Raynaud’s phenomenon. However, their association with clinical outcomes and response to standard of care (SoC) therapy in patients who have SLE rather than MCTD remains poorly defined.

In this study, we examined clinical characteristics of SLE patients withanti-RNP autoantibodies, using a large national cohort with detailed serological profiles alongside longitudinal clinical data. Among patients with active disease at enrolment, we further compared disease activity and treatment during the first year of follow-up.

Patients and methods

Study population

We conducted this study using data from patients with SLE, enrolled in the Australian Lupus Registry and Biobank (ALRB) with documented results for anti-RNP antibodies (Fig. 1). All patients were adults aged ≥ 18 years who met either the 1997 American College of Rheumatology (ACR) Modified Classification Criteria for SLE [7] or the Systemic Lupus International Collaborating Clinics (SLICC) 2012 Classification Criteria [8]. All patients have provided written informed consent prior to registry enrolment to collect and use their data for research studies.

Fig. 1.

Fig. 1

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Flow diagram showing patient selection for the study, and the number of patients with or without anti-RNP antibodies (RNP+ versus RNP-)

Research ethics approval

We obtained ethics approval from Monash Health to conduct this study (Ethics committee reference: 14262 A).

Study design

This was a retrospective, longitudinal cohort study, in which the risk factor/exposure was defined based on anti-U1 RNP antibody status, (which targets the U1 particle of the ribonucleoprotein complex), classifying patients as RNP + or RNP- based on its presence or absence. We compared their sociodemographic and clinical characteristics at enrolment, and further evaluated outcomes at 6 months (182 ± 30 days) and 12 months (365 ± 30 days) following enrolment. Additionally, we identified a subset of patients with active disease at enrolment aligned to enrolment criteria for clinical trials, defined as a SLEDAI-2 K ≥ 6 at the enrolment visit, and repeated the comparative analysis between RNP + and RNP- patients in this subset.

Data collection and variables

The ALRB captures socio­ demographic data, SLE classification criteria (ACR [7] and SLICC [8]), serological profiles and comorbidities at enrolment; disease activity indicators, laboratory tests and medications details are captured at each visit, and organ damage and health-related quality of life annually [9].

More specifically for this study, we used SLE Disease Activity Index‐2 K (SLEDAI-2 K) [10] and Physician Global Assessment (PGA) [11] as measures of SLE disease activity. SLEDAI-2 K ≥ 6 was considered as active disease. SELENA-SLEDAI SLE Flare Index (SFI) [12] was used to assess mild-to-moderate (M/M) or severe flares. Medications assessed included glucocorticoids (GC, prednisolone or equivalent), anti-malarials (AM, hydroxychloroquine), immunosuppressants (IS, methotrexate, azathioprine, mycophenolate mofetil, mycophenolic acid, leflunomide, cyclosporine, tacrolimus or cyclophosphamide), and biologics (abatacept, belimumab, rituximab). Lupus Low Disease Activity State (LLDAS: SLEDAI-2 K ≤ 4 with no major organ or new activity, PGA ≤ 1, GC ≤ 7·5 mg/day, AM, IS allowed [13]), and DORIS remission (REM: clinical SLEDAI-2 K = 0 (i.e., excluding serological domains), PGA < 0.5, GC ≤ 5 mg/day, AM, IS allowed [14]) were defined as treat-to-target (T2T) states. An additional REM state disallowing any exposure to GC was defined and referred to as REM-0. Irreversible organ damage was determined using the SLICC/ACR Damage Index (SDI) [15]; SDI > 0 was defined as organ damage present, and change in SDI score (Δ SDI > 0) during the study observation period was defined as accrual of new damage.

Statistical analysis

Patient characteristics were described at enrolment and at 6- and 12-month follow-up using the median and interquartile range [IQR] for continuous variables, and frequencies and proportions (%) for categorical variables. These characteristics were compared between RNP + and RNP- patients using Wilcoxon rank sum tests (comparing medians), and chi-squared tests (comparing proportions). Group differences were considered to be statistically significant of p values were < 0.05. Furthermore, baseline patient characteristics associated with RNP-positivity were examined using univariable and multivariable logistic regressions, and collinearity between binary variables were examined using tetrachoric correlation (ρ). Variables with univariable associations with p-values < 0.1 were included in the initial multivariable model. The final multivariable model was restricted to variables, which retained p-values < 0.1.

All analyses were performed using Stata statistical software (version 19).

Results

Of the 775 patients enrolled in the ALRB between 2007 and 2023, 587 adult patients with known anti-RNP antibody results were included in this study. Of them, nearly 30% (n = 174) were RNP + (Fig. 1).

Patient characteristics at enrolment, including demographics, serological profile, medication use and clinical indicators of the whole cohort, and by RNP ± status are shown in Table 1. Briefly, in the whole study cohort, about 87% of patients were female and 49.5% were of European ancestry. The median [IQR] age at enrolment, and at SLE diagnosis was 39 years [28, 51] and 28 years [20, 39.5], respectively. Approximately 11% reported a family history of SLE; 13% were smokers at enrolment, and 59% of patients had tertiary level education (Table 1).

Table 1.

Patient characteristics at enrolment, stratified by anti-RNP autoantibodies status

All patients Anti-RNP status
Negative (RNP-) Positive (RNP +)
Median [IQR] or n (%) p-value
n = 587 n = 413 n = 174
Demographics
 Age at enrolment (years) 39 [29, 51] 40 [29, 53] 38 [27, 47] 0.023
 Age at SLE onset (years)1 28 [20, 39.5] 29 [20, 42] 27 [20, 35] 0.084
 Age at SLE diagnosis (years) 30 [22, 43] 31 [22, 45] 28 [21, 37] 0.013
 Study observation period 4.8 [1.2, 9.6] 5.2 [1.5, 9.8] 3.9 [0.8, 8.6] 0.040
 Females 510 (86.9%) 356 (86.2%) 154 (88.5%) 0.45
 Race2  < 0.001
  European 268 (49.5%) 219 (57.5%) 49 (30.6%)
  South-Eastern/North-Eastern Asian 186 (34.4%) 107 (28.1%) 79 (49.4%)
  Southern and Central Asian 34 (6.3%) 23 (6.0%) 11 (6.9%)
  Aboriginal/Torres strait Islander 7 (1.3%) 4 (1.0%) 3 (1.9%)
  Sub-Saharan African 9 (1.7%) 4 (1.0%) 5 (3.1%)
  Other 37 (6.8%) 24 (6.3%) 13 (8.1%)
 Family history of SLE3 52 (10.7%) 30 (8.9%) 22 (14.7%) 0.056
 Education level4 0.31
  Primary 55 (10.5%) 34 (9.3%) 21 (13.5%)
  Secondary 161 (30.8%) 117 (32.0%) 44 (28.2%)
  Tertiary 306 (58.6%) 215 (58.7%) 91 (58.3%)
 Smoking status at enrolment5 0.12
  Current Smoker 69 (13.1%) 52 (14.1%) 17 (10.9%)
  Ex-smoker 96 (18.3%) 74 (20.1%) 22 (14.1%)
  Never Smoked 360 (68.6%) 243 (65.9%) 117 (75.0%)
 Weekly alcohol consumption3 0.0 (0.0, 1.0) 0.0 (0.0, 2.0) 0.0 (0.0, 1.0)  < 0.001
 Weekly alcohol consumption—categories3
  0 317 (65.0%) 206 (60.9%) 111 (74.0%) 0.012
  1–10 149 (30.5%) 112 (33.1%) 37 (24.7%)
  11–20 12 (2.5%) 12 (3.6%) 0 (0.0%)
   > 20 10 (2.0%) 8 (2.4%) 2 (1.3%)
 Body Mass Index (BMI)6 24.0 [21.1, 28.1] 24.2 [21.5, 28.7] 23.1 [20.3, 26.1]  < 0.001
 BMI categories6 0.030
  Underweight (BMI < 18.5) 21 (4.4%) 10 (3.0%) 11 (7.4%)
  Healthy Weight (≥ 18.5 & ≤ 24.9) 260 (54.2%) 175 (52.7%) 85 (57.4%)
  Overweight (≥ 25.0 & ≤ 29.9) 113 (23.5%) 79 (23.8%) 34 (23.0%)
  Obesity (≥ 30.0) 86 (17.9%) 68 (20.5%) 18 (12.2%)
Serological profile
 Anti-nuclear antibodies (ANA)7  < 0.001
  Low (< 160) 26 (4.5%) 24 (5.9%) 2 (1.2%)
  Moderate (> = 160 & < 1280) 127 (21.8%) 108 (26.7%) 19 (10.9%)
  High (> = 1280) 426 (73.7%) 273 (67.4%) 153 (87.9%)
 Anti-Sm8 121 (20.8%) 23 (5.6%) 98 (58.0%)  < 0.001
 Anti-Ro9 276 (47.6%) 180 (43.6%) 96 (57.5%) 0.002
 Anti-La10 101 (17.5%) 80 (19.4%) 21 (12.8%) 0.060
 Anti-Jo111 7 (1.2%) 5 (1.2%) 2 (1.2%) 0.98
 Anti-Scl7012 14 (2.5%) 6 (1.5%) 8 (5.1%) 0.013
 Anti-dsDNA13 470 (80.9%) 316 (77.1%) 154 (90.1%)  < 0.001
 Low C37 430 (74.3%) 288 (70.9%) 142 (82.1%) 0.005
 Low C47 462 (79.8%) 322 (78.7%) 140 (82.4%) 0.32
Medication use
 Glucocorticoids (GC, prednisolone equivalent) 348 (59.3%) 223 (54.0%) 125 (71.8%)  < 0.001
 GC dose (mg/day) 5.0 [0.0, 12.0] 3.0 [0.0, 10.0] 6.8 [0.0, 15.0]  < 0.001
 Anti-malarial therapy (AM, hydroxychloroquine) 469 (79.9%) 318 (77.0%) 151 (86.8%) 0.007
 Immunosuppressants (IS) 323 (55.0%) 204 (49.4%) 119 (68.4%)  < 0.001
  Azathioprine 104 (17.7%) 74 (17.9%) 30 (17.2%) 0.84
  Ciclosporin 2 (0.3%) 1 (0.2%) 1 (0.6%) 0.53
  Cyclophosphamide 4 (0.7%) 2 (0.5%) 2 (1.1%) 0.37
  Leflunomide 4 (0.7%) 2 (0.5%) 2 (1.1%) 0.37
  Methotrexate 64 (10.9%) 46 (11.1%) 18 (10.3%) 0.78
  Mycophenolate 130 (22.1%) 74 (17.9%) 56 (32.2%)  < 0.001
  Mycophenolic acid 24 (4.1%) 12 (2.9%) 12 (6.9%) 0.026
  Tacrolimus 8 (1.4%) 5 (1.2%) 3 (1.7%) 0.62
 biologics 16 (2.7%) 5 (1.2%) 11 (6.3%)  < 0.001
  Abatacept 1 (0.2%) 1 (0.2%) 0 (0.0%) 0.52
  Belimumab 3 (0.5%) 0 (0.0%) 3 (1.7%) 0.007
  Rituximab 12 (2.0%) 4 (1.0%) 8 (4.6%) 0.005
Clinical indicators
 SLEDAI-2K14 6.0 [2.0, 8.0] 4.0 [2.0, 8.0] 8.0 [4.0, 10.0]  < 0.001
  SLEDAI-2 K ≥ 614 262 (51.7%) 170 (47.8%) 92 (60.9%) 0.007
 Disease activity by domain14*
  Central nervous system (CNS) 18 (3.5%) 12 (3.4%) 6 (3.9%) 0.75
  Vasculitis 10 (2.0%) 3 (0.8%) 7 (4.6%) 0.005
  Musculoskeletal (MSK) 114 (19.4%) 80 (19.4%) 34 (19.5%) 0.96
  Renal 139 (23.7%) 82 (19.9%) 57 (32.8%)  < 0.001
  Cutaneous 188 (32.0%) 121 (29.3%) 67 (38.5%) 0.029
  Serositis 29 (4.9%) 22 (5.3%) 7 (4.0%) 0.51
  Serological 403 (68.7%) 269 (65.1%) 134 (77.0%) 0.005
  Fever 5 (1.0%) 0 (0.0%) 5 (3.3%)  < 0.001
  Haematological 44 (7.5%) 28 (6.8%) 16 (9.2%) 0.31
 PGA15 0.6 [0.3, 1.1] 0.5 [0.2, 1.0] 0.9 [0.4, 1.2]  < 0.001
  PGA > 115 138 (25.5%) 83 (21.7%) 55 (34.8%) 0.001
 Mild/moderate/severe flare 116 (19.8%) 76 (18.4%) 40 (23.0%) 0.20
 Organ damage at enrollment16 217 (42.3%) 149 (41.2%) 68 (45.0%) 0.42
Treat-to-target states
 LLDAS17 150 (28.5%) 118 (32.2%) 32 (20.0%) 0.004
 REM18 92 (19.4%) 76 (22.6%) 16 (11.6%) 0.006
 REM-019 69 (14.5%) 60 (17.8%) 9 (6.5%) 0.002
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Data missing for 151, 246, 399, 465, 562, 6107, 78, 85, 97, 1011, 1114, 1214, 136, 1480, 1546, 1674, 1761, 1841, and 1934 patients

SLEDAI-2 K SLE Disease Activity State 2000, PGA Physician Global Assessment, LLDAS lupus low disease activity state, REM DORIS remission, REM-O remission off glucocorticoids

*Determined based on SLEDAI-2 K descriptors

When comparing RNP + and RNP- patients, significantly higher proportions of RNP + patients were of Asian ethnicity; more had a family history of SLE, and they were younger at SLE diagnosis. RNP + patients also had more likely to have positivity to ANA, anti-dsDNA, anti-Sm and anti-Ro antibodies and low C3 (Table 1). anti-Sm was strongly correlated with anti-RNP positivity (tetrachoric ρ = 0.83). We further compared the ACR and SLICC classification criteria and comorbidities between RNP + and RNP- patients to assess clinical phenotypes (Supplementary Tables 1 & 2). Significantly higher proportions of renal and immunological involvement in RNP + patients were observed. In contrast, proportions of patients with photosensitivity (per defined by ACR criteria) and haemolytic anaemia (SLICC classification criteria) were lower in the RNP + patient group (Supplementary Table 1).

RNP + patients had significantly lower proportions of another rheumatological diagnosis at enrolment (33.3 versus 42.6%, p = 0.036), especially SjÖgren’s syndrome (4.0% versus 9.4%, p = 0.026), anti-phospholipid syndrome (5.7% versus 10.9%, p = 0.051) and osteoarthritis (1.7% versus 6.3%, p = 0.02). In contrast, RNP + patients had a significantly higher proportion of patients with concomitant scleroderma (4.0% versus 0.5%, p = 0.001) (Supplementary Table 2), although absolute numbers were small. In terms of other rheumatological comorbidities, Raynaud’s phenomenon (32.2% versus 17.2%, p < 0.001) and transverse myelitis (2.3% versus 0.5%, p = 0.013) was significantly more common in the RNP + group, whereas venous thrombosis (2.9% versus 9.4%, p = 0.006), mood (8.6% versus 16.5%, p = 0.013) and anxiety disorders (8.6% versus 16.5%, p = 0.053) were significantly less common (Supplementary Table 2).

Clinical indicators at enrolment, stratified by RNP status

The median [IQR] SLEDAI-2 K of the study cohort at enrolment was 6 [2, 8] (Table 1). SLEDAI-2 K at enrolment was significantly higher in the RNP + group than the RNP- group (8 [4, 10] versus 4 [2, 8], p < 0.001) (Fig. 2a). Accordingly, approximately 61% of RNP + patients had active disease (SLEDAI-2 K ≥ 6) at enrolment, compared with 46% in the RNP- group (p = 0.007). Baseline disease activity was more frequently recorded in RNP + patients in vasculitis, renal, rash and serological SLEDAI-2 K domains (Table 1). Similarly, disease activity at enrolment measured by PGA was significantly higher in the RNP + group with about 35% of RNP + group having PGA > 1, compared to 22% in the RNP- group (p = 0.001).

Fig. 2.

Fig. 2

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SLEDAI-2 K score at enrolment, 6-month visit and at 12-month visit (a) in patients stratified by anti-RNP negative (RNP-) and anti-RNP-positive (RNP +) status, and (b-c) in patients stratified by ant-RNP and anti-Sm status

Significantly greater proportions of RNP + patients were using all medication types at enrolment (i.e., GC, AM, IS and biologics), compared with RNP- patients (Table 1). Approximately 72% of RNP + patients and 54% of RNP- patients received GC (p < 0.001). The median [IQR] daily GC dose of RNP + and RNP- patients was 6.8 mg [0, 15] and 3 mg [0, 10] (p < 0.001), respectively. Moreover, 87% of RNP + patients versus 77% of RNP- patients received AM (hydroxychloroquine) (p < 0.001). In terms of IS, a significantly higher proportion of RNP + patients received mycophenolate (32% versus 18%, p < 0.001) and mycophenolic acid (7% versus 3%, p = 0.026). With respect to biologics, more RNP + patients received rituximab (~ 5% versus 1%, p = 0.005) and belimumab (~ 2% versus 0, p = 0.007) (Table 1).

Significantly fewer RNP + patients were in LLDAS and remission at enrolment, compared with the RNP- patients. In the RNP + group, 20% of the were in LLDAS; 12% in REM, and 6.5% in REM-0, compared with the RNP- group, where 32% was in LLDAS, 23% in REM and 18% in REM-0 (Table 1).

These associations were also examined using logistic regression analysis. Univariable analysis demonstrated strong associations with younger age, Asian ancestry, and markers of disease severity including GC and IS use, and baseline disease activity overall and in renal, cutaneous and serological domains. In contrast, RNP + was negatively associated with being in LLDAS or REM/REM-0. RNP + patients were also had 23-fold higher odds of being positive to anti-Sm antibodies, compared with RNP-ve patients (Table 2).

Table 2.

Univariable logistic regression analysis of characteristics associated with anti-RNP + patients compared with anti-RNP- patients

OR (95% CI) p-value
Demographics
 Age at registry enrolment (years)
   < 40 1.00
   ≥ 40 & < 60 0.93 (0.63,1.36) 0.694
   ≥ 60 0.38 (0.20,0.71) 0.003
 Race categories
  European 1.00
  Asian 3.09 (2.05,4.66)  < 0.001
  Other 2.93 (1.56,5.52) 0.001
 Weekly alcohol consumption—categories
  0 1.00
  1–10 0.61 (0.40,0.95) 0.028
   > 10 0.19 (0.04,0.81) 0.025
 BMI categories
  Healthy Weight (≥ 18.5 & ≤ 24.9) 1.00
  Underweight (BMI < 18.5) 2.26 (0.93,5.54) 0.073
  Overweight (≥ 25.0 & ≤ 29.9) 0.73 (0.48,1.10) 0.129
 Family history of SLE 1.76 (0.98,3.18) 0.058
Serological profile
 High_ANA (≥ 1280) 3.52 (2.13,5.82)  < 0.001
 Anti-Sm 23.40 (13.92,39.36)  < 0.001
 Anti-Ro 1.75 (1.22,2.52) 0.003
 Anti-La 0.61 (0.36,1.02) 0.061
 Anti-dsDNA 2.69 (1.55,4.68)  < 0.001
 Low C3 1.88 (1.20,2.92) 0.005
 Medication use
 Glucocorticoids 2.17 (1.48,3.19)  < 0.001
 Anti-malarial therapy 1.96 (1.20,3.22) 0.008
 Immunosuppressants 2.22 (1.53,3.22)  < 0.001
  Mycophenolate 2.17 (1.45,3.26)  < 0.001
  Mycophenolic acid 2.48 (1.09,5.62) 0.03
 Clinical indicators
 SLEDAI-2 K ≥ 6 1.71 (1.16,2.51) 0.007
 Domain-specific activity
  Renal 1.97 (1.32,2.93) 0.001
  Cutaneous 1.51 (1.04,2.19) 0.029
  Serological 1.79 (1.19,2.69) 0.005
 PGA > 1 1.93 (1.28,2.90) 0.002
Treat-to-target states
 LLDAS 0.53 (0.34,0.82) 0.005
 REM 0.41 (0.23,0.73) 0.003
 REM-0 0.30 (0.14,0.62) 0.001
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In multivariable logistic regression model, only Asian ethnicity, family history of SLE, high ANA titre (≥ 1,280), and anti-Sm positivity remained statistically significant, and associations of disease activity attenuated (Table 4). Despite this, an additive effect on disease activity of RNP positivity was observed in patients who were Sm-positive: the highest individual disease activity scores were observed in double-positive patients (Fig. 2B &2C).

Table 4.

Comparison of outcomes between RNP + and RNP- patients at 6 and 12 months from enrolment

6 months 12 months
All patients Anti-RNP status All patients Anti-RNP status
Negative (RNP-) Positive (RNP +) Negative (RNP-) Positive (RNP +)
n = 344 n = 243 n = 101 n = 298 n = 211 n = 87
Median [IQR] or n (%) p-value Median [IQR] or n (%) p-value
Medication use
 Glucocorticoids (GC) 217 (63.1%) 144 (59.3%) 73 (72.3%) 0.023 178 (59.7%) 115 (54.5%) 63 (72.4%) 0.004
 Daily GC dose 4.0 (0.0, 7.5) 2.5 (0.0, 7.5) 5.0 (0.0, 7.5) 0.023 2.5 (0.0, 5.0) 2.0 (0.0, 5.0) 5.0 (0.0, 7.5) 0.006
 Anti-malarials (AM) 298 (86.6%) 208 (85.6%) 90 (89.1%) 0.38 258 (86.6%) 182 (86.3%) 76 (87.4%) 0.8
 Immunosuppressants (IS) 213 (61.9%) 139 (57.2%) 74 (73.3%) 0.005 188 (63.1%) 123 (58.3%) 65 (74.7%) 0.008
 Biologics 14 (4.1%) 8 (3.3%) 6 (5.9%) 0.26 11 (3.7%) 7 (3.3%) 4 (4.6%) 0.59
Clinical indicators
 SLEDAI-2 K 4.0 (2.0, 6.0) 4.0 (2.0, 6.0) 4.0 (2.0, 7.0) 0.018 4.0 (2.0, 6.0) 4.0 (2.0, 6.0) 4.0 (2.0, 6.0) 0.35
  SLEDAI-2 K ≥ 6 96 (31.4%) 61 (28.4%) 35 (38.5%) 0.082 76 (29.3%) 51 (27.6%) 25 (33.8%) 0.32
 Disease activity by domain
  CNS 5 (1.6%) 3 (1.4%) 2 (2.2%) 0.61 1 (0.4%) 1 (0.5%) 0 (0.0%) 0.53
  Vasculitis 4 (1.3%) 1 (0.5%) 3 (3.3%) 0.046 1 (0.4%) 1 (0.5%) 0 (0.0%) 0.53
  MSK 31 (9.0%) 18 (7.4%) 13 (12.9%) 0.11 25 (8.4%) 20 (9.5%) 5 (5.7%) 0.29
  Renal 72 (20.9%) 50 (20.6%) 22 (21.8%) 0.8 62 (20.8%) 40 (19.0%) 22 (25.3%) 0.22
  Cutaneous 53 (15.4%) 33 (13.6%) 20 (19.8%) 0.15 47 (15.8%) 31 (14.7%) 16 (18.4%) 0.43
  Serositis 7 (2.0%) 7 (2.9%) 0 (0.0%) 0.085 7 (2.3%) 5 (2.4%) 2 (2.3%) 0.97
  Serological 235 (68.3%) 155 (63.8%) 80 (79.2%) 0.005 195 (65.4%) 136 (64.5%) 59 (67.8%) 0.58
  Fever 3 (1.0%) 2 (0.9%) 1 (1.1%) 0.89 0 0
  Haematological 36 (10.5%) 23 (9.5%) 13 (12.9%) 0.35 24 (8.1%) 17 (8.1%) 7 (8.0%) 0.99
 PGA 0.3 (0.1, 0.8) 0.3 (0.1, 0.8) 0.5 (0.2, 0.9) 0.12 0.3 (0.1, 0.8) 0.3 (0.1, 0.8) 0.4 (0.2, 0.9) 0.15
  PGA > 1 40 (12.3%) 28 (12.0%) 12 (13.0%) 0.8 36 (12.5%) 25 (12.3%) 11 (12.9%) 0.88
 Mild/moderate/severe flare 62 (18.0%) 47 (19.3%) 15 (14.9%) 0.32 53 (17.8%) 39 (18.5%) 14 (16.1%) 0.62
 Organ damage present 145 (45.5%) 97 (42.9%) 48 (51.6%) 0.16 153 (53.1%) 104 (51.5%) 49 (57.0%) 0.39
 Damage accrual 1 (0.3%) 0 (0.0%) 1 (1.0%) 0.12 21 (7.0%) 14 (6.6%) 7 (8.0%) 0.67
Treat-to-target states
 LLDAS 101 (33.8%) 81 (38.4%) 20 (22.7%) 0.009 105 (40.2%) 75 (39.9%) 30 (41.1%) 0.86
 REM 94 (29.3%) 79 (35.3%) 15 (15.5%)  < 0.001 90 (33.2%) 65 (34.0%) 25 (31.2%) 0.66
 REM-0 61 (18.7%) 53 (23.3%) 8 (8.1%) 0.001 54 (19.3%) 44 (22.6%) 10 (11.8%) 0.035
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CNS central nervous system, MSK musculoskeletal, SLEDAI-2 K SLE Disease Activity State 2000, PGA Physician Global Assessment, LLDAS lupus low disease activity state, REM DORIS remission, REM-O remission off glucocorticoids

Outcomes at 6-months and 12-months

Follow-up data were available for 344 patients at 6 months (RNP + = 101 (29%)), and for 298 patients at 12 months (RNP + = 87 (29%)) (Table 4). By 6 and 12 months, the median SLEDAI-2 K had reduced from 6 at enrolment to 4. At 6 months, the RNP + group exhibited higher disease activity than the RNP- group (Table 3). Additionally, the higher proportion of RNP + patients with active disease (SLEDAI-2 K ≥ 6) remained, with borderline statistical significance (p = 0.082) and vasculitis and serological activity remained significantly high in the RNP + group at 6 months (Table 3). By 12 months, disease activity was similar between RNP + and RNP- groups. However, a significantly higher proportion of RNP + patients received GC and IS, accompanied by higher daily GC doses at both 6 and 12 months, and significantly fewer RNP + patients achieved LLDAS or REM at 6 months, and although there was no difference in the proportions of patients attaining LLDAS or REM at 12 months, the proportion attaining REM-0 remained significantly lower in the RNP + group (Table 4).

Table 3.

Multivariable logistic regression model including characteristics independently associated with anti-RNP + patients compared with anti-RNP- patients

OR (95% CI) p-value
Age at registry enrolment (years)
  < 40 1.00
  ≥ 40 & < 60 1.03 (0.61,1.74) 0.9
  ≥ 60 0.42 (0.16,1.07) 0.069
Race categories
 European 1.00
 Asian 2.03 (1.20,3.44) 0.008
 Other 1.66 (0.72,3.83) 0.2
Family history of SLE 2.15 (1.02,4.53) 0.044
high ANA (≥ 1280) 2.57 (1.30,4.53) 0.007
Anti-Sm 18.1 (10.1,32.2)  < 0.001
Model properties
ll (null) −293.4318
ll (model) −205.0034
AIC 426.0068
BIC 459.3302
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ll(null) = log likelihood of the model with the intercept only (no predictors) to serve as the baseline measure of the model’s fit to the data

ll(model) = log likelihood of the model including the predictors to assess how well the model fits the data compared to ll(null)

AIC Akaike Information Criterion, BIC Bayesian Information Criterion, both measures of the quality of statistical models for a given set of data. BIC includes a penalty for the number of parameters to avoid overfitting

Further examination of outcomes at these time points across RNP −/Sm −, RNP −/Sm +, RNP +/Sm −, and RNP +/Sm + groups showed the highest GC and IS use in the RNP +/Sm + group (Table 5). This group also had the highest proportion of patients with active disease (SLEDAI ≥ 6, although not statistically significant) and the lowest attainment of treat-to-target states, supporting an additive effect of anti-RNP and anti-Sm autoantibodies on disease activity. Organ damage was highest in RNP +/Sm − patients. Given the small numbers in these subgroups, analyses were limited to bivariate comparisons.

Table 5.

Comparison of outcomes at 6- and 12- month follow-up from enrolment across patients in RNP & Sm categories

6 months 12-months
RNP-Sm- RNP-Sm +  RNP + Sm- RNP + Sm +  RNP-Sm- RNP-Sm +  RNP + Sm- RNP + Sm + 
n = 229 n = 14 n = 39 n = 59 n = 200 n = 11 n = 41 n = 44
Median [IQR] or n (%) p-value Median [IQR] or n (%) p-value
Medication use
 Glucocorticoids (GC) 135 (59.0%) 9 (64.3%) 25 (64.1%) 46 (78.0%) 0.063 110 (55.0%) 5 (45.5%) 27 (65.9%) 34 (77.3%) 0.029
 Daily GC dose 2.5 [0, 7.5] 2.5 [0, 10.0] 3.0 [0, 7.5] 6.0 [1.0, 10.0] 0.019 2.0 [0.0, 5.0] 0.0 [0.0, 5.0] 3.0 [0.0, 5.0] 5.0 [1.5, 10.0] 0.013
 Anti-malarials (AM) 196 (85.6%) 12 (85.7%) 35 (89.7%) 53 (89.8%) 0.78 173 (86.5%) 9 (81.8%) 35 (85.4%) 39 (88.6%) 0.94
 Immunosuppressants (IS) 128 (55.9%) 11 (78.6%) 24 (61.5%) 49 (83.1%)  < 0.001 118 (59.0%) 5 (45.5%) 26 (63.4%) 37 (84.1%) 0.011
 Biologics 8 (3.5%) 0 3 (7.7%) 3 (5.1%) 0.53 7 (3.5%) 0 2 (4.9%) 1 (2.3%) 0.84
Clinical indicators
 SLEDAI-2 K 4 [2, 6] 4 [2, 8] 4 [2, 6] 4 [2, 8] 0.073 4 [2, 6] 4 [1, 8] 3 [0, 6] 4 [3, 8] 0.12
 SLEDAI-2 K ≥ 6 56 (27.7%) 5 (38.5%) 11 (29.7%) 23 (44.2%) 0.13 47 (26.9%) 4 (40.0%) 9 (25.7%) 15 (40.5%) 0.32
 Disease activity by domain
  CNS 3 (1.5%) 0 0 2 (3.8%) 0.49 1 (0.6%) 0 0 0 0.93
  Vasculitis 1 (0.5%) 0 0 2 (3.8%) 0.15 1 (0.6%) 0 0 0 0.93
  MSK 16 (7.0%) 2 (14.3%) 5 (12.8%) 7 (11.9%) 0.40 18 (9.0%) 2 (18.2%) 1 (2.4%) 3 (6.8%) 0.31
  Renal 46 (20.1%) 4 (28.6%) 6 (15.4%) 15 (25.4%) 0.56 37 (18.5%) 3 (27.3%) 8 (19.5%) 13 (29.5%) 0.39
  Cutaneous 29 (12.7%) 4 (28.6%) 10 (25.6%) 8 (13.6%) 0.087 28 (14.0%) 3 (27.3%) 5 (12.2%) 9 (20.5%) 0.44
  Serositis 5 (2.2%) 2 (14.3%) 0 0 0.006 5 (2.5%) 0 1 (2.4%) 0 0.71
  Serological 146 (63.8%) 9 (64.3%) 30 (76.9%) 48 (81.4%) 0.041 129 (64.5%) 7 (63.6%) 25 (61.0%) 33 (75.0%) 0.53
  Fever 1 (0.5%) 1 (7.7%) 0 1 (1.9%) 0.062 0 0 0 0
  Haematological 21 (9.2%) 2 (14.3%) 4 (10.3%) 8 (13.6%) 0.74 16 (8.0%) 1 (9.1%) 2 (4.9%) 5 (11.4%) 0.75
 PGA 0.3 [0.1, 0.8] 0.6 [0.2, 1.1] 0.5 [0.2, 0.9] 0.5 [0.2, 0.9] 0.23 0.3 [0.1, 0.7] 0.3 [0.0, 1.5] 0.4 [0.1, 0.7] 0.4 [0.2, 1.0] 0.26
  PGA > 1 24 (11.0%) 4 (28.6%) 5 (13.9%) 7 (12.7%) 0.27 22 (11.5%) 3 (27.3%) 4 (10.0%) 6 (13.6%) 0.44
 Mild/moderate/severe flare 41 (17.9%) 6 (42.9%) 4 (10.3%) 10 (16.9%) 0.057 35 (17.5%) 4 (36.4%) 6 (14.6%) 7 (15.9%) 0.39
 Organ damage present 96 (45.1%) 1 (7.7%) 22 (59.5%) 25 (46.3%) 0.015 100 (52.1%) 4 (40.0%) 25 (61.0%) 22 (51.2%) 0.61
 New damage accrued 0 0 1 (2.6%) 0 0.051 12 (6.0%) 2 (18.2%) 3 (7.3%) 3 (6.8%) 0.48
Treat-to-target states
 LLDAS 78 (39.4%) 3 (23.1%) 12 (35.3%) 8 (15.4%) 0.010 72 (40.7%) 3 (27.3%) 20 (60.6%) 10 (25.6%) 0.019
 REM 77 (36.7%) 2 (14.3%) 9 (24.3%) 6 (10.3%)  < 0.001 62 (34.3%) 3 (30.0%) 16 (43.2%) 9 (22.0%) 0.25
 REM-0 51 (23.9%) 2 (14.3%) 5 (13.2%) 3 (5.1%) 0.008 41 (22.2%) 3 (30.0%) 7 (17.5%) 3 (7.0%) 0.11
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In order to focus on patients with disease activity similar to that of cohorts typically enrolled in clinical trials, we examined patients who had SLEDAI-2 K ≥ 6 at the enrolment visit (262/507). In this subset, we observed a higher proportion of RNP + patients with disease activity in the vasculitis, constitutional (fever) and renal domains (Supplementary Table 3). Median SLEDAI-2 K was significantly higher in the RNP + group (9 [8, 13.5] versus 8 [6, 12], p = 0.008) and the daily GC dose was significantly higher in RNP + patients (10 mg/D [2.5, 25]) compared to RNP- patients (6.0 mg/D [0, 16], p = 0.015) (Supplementary Table 3). Follow-up data at 6- and 12 months were available for 157 and 144 patients, respectively. A higher proportion of RNP + patients received IS at 12 months, and significantly fewer RNP + patients attained LLDAS or remission at 6 months, although the differences in T2T states attainment at 12 months were no longer significant (Supplementary Table 4). A sensitivity analysis limited to 104 patients who had data at both time points showed similar findings (data not shown).

Discussion

This study provides an assessment of clinical characteristics of SLE patients positive for antibodies to RNP, using data from a national, multi-site prospective lupus registry. The prevalence of anti-RNP positivity was approximately 30%, consistent with prior studies reporting rates between 13 and 32% [16]. Multiple features of disease severity were associated with anti-RNP positivity, but these were largely driven by the strong association with anti-Sm antibody positivity, notwithstanding which the patients with highest individual disease activity were RNP/Sm double positive.

The association between RNP and anti-Sm antibodies is in fact, well recognised. Both antigens are in the spliceosome, although anti-U1 RNP targets one of five small nuclear ribonucleoprotein particles (U1, U2, U4, U5, and U6), whereas anti-Sm antibodies recognise a distinct set of the 7 common core proteins (called Smith proteins). A subset of patients harbour both autoantibody specificities, recognising overlapping Sm proteins (usually B, B’ and D1) and U1 RNP [17]. The tight MHC association of anti-Sm reactivity, and the divergence of these MHC associations from those associated with isolated RNP positivity, suggest the possibility that in SLE Sm reactivity precedes epitope spreading, amplified by innate immune activation triggered by these antigens, to result in concomitant anti-RNP reactivity [18, 19]. Our multivariable analysis demonstrated that the baseline disease activity associations with anti-RNP attenuated when adjusted for the 18-fold higher rate of anti-Sm reactivity, suggesting that the clinical profile of anti-RNP positivity overlaps with or is chiefly driven by the anti-Sm phenotype.

Compared with RNP- patients, a significantly higher proportion of RNP + patients were of Asian ethnicity, reported a family history of SLE, and had active disease at enrolment, especially renal and serological activity. The high prevalence of renal activity among RNP + patients contrasts with reports from mixed connective tissue disease cohorts, in which U1 RNP positivity has been associated with less severe renal involvement [20], and may be driven by the strong association of lupus nephritis with anti-Sm reactivity. RNP + patients exhibited significantly higher serological activity, including higher frequency of ANA, anti-Sm, anti-Ro, anti-Scl-70, anti-dsDNA antibodies and low C3, but not anti-La antibodies, which were less frequent than in the RNP- group with borderline statistical significance. We did not observe a difference in the prevalence of arthritis between RNP + and RNP- patients. The association between arthritis and anti-RNP antibodies in SLE has been variably reported, with some studies demonstrating strong associations [3, 4], and others reporting no significant relationship [21, 22].

More than 30% of RNP + patients had Raynaud's phenomenon, nearly doubled the proportion observed in RNP- group. Ahmad et al. reported more frequent Raynaud's phenomenon in RNP + Swedish patients with SLE [2], with similar associations observed in cohorts from Italy [4], South China [5], and Malta [23]. Many studies have reported scleroderma-like features in RNP + SLE patients [6, 23]. In our SLE cohort, nine patients had a comorbid diagnosis of scleroderma, of whom seven were RNP +. In contrast, RNP + patients were significantly less likely to have other comorbid rheumatic conditions, such as osteoarthritis, SjÖgren’s disease and anti-phospholipid syndrome, as well as anxiety and mood disorders. Although RNP positivity has been reported as a risk factor for pulmonary hypertension in connective tissue disease [24], pulmonary hypertension was not a prominent comorbidity in our study population.

Patients were followed longitudinally for one year from enrolment, both in the overall cohort, and in a subset with active disease (SLEDAI-2 K ≥ 6) at baseline. This follow-up duration and stratification mirror the parameters commonly used in interventional clinical trials in SLE. At most time points, the individuals with higher disease activity and medications use were RNP/Sm double positive, suggesting that despite the influence of Sm reactivity on the clinical profile of RNP + patients, RNP positivity still contributes to these associations.

This study has several limitations. Autoantibody profiles were assessed only at enrolment precluding evaluation of temporal changes of anti-RNP status over time. Serum titres of anti-RNP antibodies have been previously reported to fluctuate in association with disease activity in SLE, and we have similarly observed variability in autoantibody positivity among patients with repeat testings [25]. Although analyses in the present study were conducted retrospectively, data were collected prospectively in academic centres using a standardised protocol.

Overall, the present report was primarily designed to describe the clinical characteristics of patients with anti-U1 RNP positivity, rather than to fully disentangle the independent effects of coexisting autoantibodies. Although our additional multivariable analyses suggest that the broader autoantibody profile, particularly anti-Sm positivity, has a confounding effect on some observed associations, autoantibody specificities are unlikely to act in isolation. Accordingly, the associations reported here should be interpreted within the context of the broader serological profile, and further studies examining the independent and combined effects of specific autoantibody patterns on disease outcomes are warranted.

Conclusions

In this multi-centre, prospectively followed national SLE cohort, anti-RNP autoantibody positivity identified a clinically distinct subgroup, characterised by higher disease activity, a high burden of renal and serological activity, greater exposure to glucocorticoids and immunosuppressant medications, and delayed attainment of the treat-to-target states of LLDAS and remission. However, the strong association of RNP positivity with anti-Sm positivity means the specific contribution of RNP positivity to this phenotype is only partial. Future studies of anti-RNP associations in SLE should countenance the contribution of associated anti-Sm reactivity, and the underlying mechanisms of these associations should be elucidated.

Supplementary Information

Supplementary Material 1. (36.6KB, docx)

Acknowledgements

We acknowledge the study participants and the data collectors of the ALRB.

Abbreviations

ACR

American College of Rheumatology

ALRB

Australian Lupus Registry & Biobank

AM

Anti-malarial medications

ANA

Anti-nuclear antibodies

DORIS

Definitions of remission in SLE

ENA

Extractable nuclear antigens

GC

Glucocorticoids

IQR

Interquartile range

IS

Immunosuppressants

LLDAS

Lupus low disease activity state

MCTD

Mixed connective tissue disease

PGA

Physician Global Assessment

REM

DORIS remission

RNP

Ribonucleoprotein

SDI

SLICC/ACR Damage Index

SFI

SELENA-SLEDAI SLE Flare Index

SLE

Systemic lupus erythematosus

SLEDAI-2K

SLE Disease Activity Index 2000

SLICC

Systemic Lupus International Collaborating Clinics

SoC

Standard of care

T2T

Treat-to-target

Authors’ contributions

The authors meet criteria for authorship as recommended by the International Committee of Medical Journal Editors. RKR, EM, PG & TS contributed to the study concept/design and data interpretation. SO, MR, YO SO’N GH, SK, TT, FG, AH, DR, MN, EM, AH were responsible for patient recruitment and data collection. RKR, RK were involved in data extraction, pooling and preparation of analytical dataset. RKR was responsible for data analysis and writing of the first draft manuscript. All authors have reviewed first and final draft manuscript and approve it for submission.

Funding

This work was supported by Novartis.

Data availability

The datasets used in this study are not publicly available due to the strict governance policies of the Australian Lupus Registry & Biobank (ALRB). Access to deidentified data may be considered upon reasonable request, and subject to ALRB’s data access policy.

Declarations

Ethics approval and consent to participate

We received ethics approval from Monash Health to conduct and publish this study (Ethics committee reference: 14262 A).

Informed consent was obtained from all subjects involved in the study.

Consent for publication

Not applicable.

Competing interests

Rangi Kandane-Rathnayake (RKR): has received grants from BMS, GSK, Janssen and Novartis Rachel Koelmeyer (RK): none Shereen Oon (SO): has received speaker fees from Astra Zeneca and The Limbic Maureen Rischmueller (MR): has received research grants from AbbVie, Amgen, Argenx, AstraZeneca, BMS, GSK, Horizon, J&J, LG Chem, Novartis, UCB; and consultant/speaker honoraria from AbbVie, Amgen, Boehringer Ingelheim, J&J, Novartis, Pfizer, Recordati, Sandoz, UCB. Yumi Oh (YO): none Sean O’Neill (SO’N): none Geraldine Hassett (GH): none Sachin Khetan (SK): none Ted Tsai (TT): none Fiona Goldblatt (FG): none Ashleigh Hennessey (AH): none Dwarakanathan Ranganathan (DR): has received unrestricted Grant for POEMSLUN study from Novartis, Australia Astrid Jullion (AJ): is employed by Novartis Tamas Shisha (TS): is employed by Novartis Peter Gergely (PG): is employed by Novartis Mandana Nikpour (MN): has received an Investigator Grant from the National Health and Medical Research Council of Australia (NHMRC GNT1176538), research grants from Boehringer Ingelheim and Janssen, consulting fees from AstraZeneca and GSK; honoraria for presentations from AstraZeneca, Boehringer Ingelheim and GSK, and support for conference attendance from Boehringer Ingelheim. Eric Morand (EM): has received consulting fees from AbbVie, AstraZeneca, Biogen, Bristol Myers Squibb, Genentech, Gilead, Janssen, Novartis, and EMD Serono. Alberta Hoi: has received a research grant from AstraZeneca, consulting fees from EUSA Pharma (UK), GSK and UCB Australia, and speaker fees/honoraria from AbbVie, Eli Lilly, Janssen, Limbic, Moose Republic and Novartis.

Footnotes

Publisher’s Note

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1. (36.6KB, docx)

Data Availability Statement

The datasets used in this study are not publicly available due to the strict governance policies of the Australian Lupus Registry & Biobank (ALRB). Access to deidentified data may be considered upon reasonable request, and subject to ALRB’s data access policy.

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