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Abstract
Objective To refine the spectrum of anti-Ku-associated disease, a condition that is equivocally described by current diagnostic criteria for connective tissue diseases.
Methods Among 42 consecutive patients harbouring anti-Ku antibodies, subgroups with similar phenotypes and prognosis were delineated without an a priori diagnosis using hierarchical clustering analysis of the cumulative clinico-biological features recorded during the follow-up. Features present at baseline that most efficiently predicted the outcomes were then identified using a sensitivity–specificity sum maximisation approach.
Results Clinico-biological features were clustered into three groups. Glomerulonephritis and ILD, the two fatal complications in this cohort, were unequally distributed between the three clusters that additionally differed on six clinico-biological features.
Among features present at baseline, elevated serum level of creatine kinase (CK) and anti-dsDNA antibodies were generally mutually exclusive and most efficiently predicted the cluster belonging at last follow-up. Anti-Ku patients with elevated CK had a 22-fold higher risk of ILD while anti-Ku patients with anti-dsDNA antibodies had a 13-fold higher risk of glomerulonephritis
Conclusion “Anti-Ku with elevated CK” syndrome and “anti-Ku with anti-dsDNA” syndrome represent two distinct entities that are important to recognise in order to best tailor patient care.
- autoantibodies
- autoimmune diseases
- autoimmunity
- Dermatomyositis
- Polymyositis
- Inflammatory myopathies
- Inflammatory myopathy
- Myositis
- Necrotizing myopathy
- necrotizing myopathies
- Inflammatory skeletal muscle
- Antisynthetase
- Interstitial lung disease
- Systemic lupus erythematosus
- Systemic sclerosis
- scleroderma
- Classification
- Anti-Ku antibodies
- Undifferentiated connective tissue disease
- Mixed connective tissue disease
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- autoantibodies
- autoimmune diseases
- autoimmunity
- Dermatomyositis
- Polymyositis
- Inflammatory myopathies
- Inflammatory myopathy
- Myositis
- Necrotizing myopathy
- necrotizing myopathies
- Inflammatory skeletal muscle
- Antisynthetase
- Interstitial lung disease
- Systemic lupus erythematosus
- Systemic sclerosis
- scleroderma
- Classification
- Anti-Ku antibodies
- Undifferentiated connective tissue disease
- Mixed connective tissue disease
Key messages
What is already known about this subject?
Autoantibodies are useful biomarkers when they delineate subgroups of patients with homogeneous manifestations and prognosis. In this regard, the usefulness of anti-Ku, a rare autoantibody, is not yet established.
What does this study add?
We demonstrate herein that anti-Ku patients with anti-dsDNA and anti-Ku patients with elevated creatine kinase (CK) are two distinct subgroups, rarely overlapping, with significant implications for patient care. Glomerulonephritis frequently occurred in anti-Ku patients with anti-dsDNA at baseline, whereas anti-Ku patients with elevated CK at baseline frequently developed interstitial lung disease.
How might this impact on clinical practice or future developments?
“Anti-Ku with elevated CK” syndrome and “anti-Ku with anti-dsDNA” syndrome represent two distinct entities that are important to recognise in order to best tailor patient care.
Introduction
Autoantibodies are useful biomarkers when they delineate subgroups of patients with homogeneous manifestations and prognosis. In this regard, the usefulness of anti-Ku, a rare autoantibody, is not yet established.
On the one hand, anti-Ku antibodies have been associated with various clinical manifestations and subsequent diagnoses which require distinct management. These diagnoses include myositis, systemic sclerosis (SSc), systemic lupus erythematosus (SLE), mixed connective tissue disease (MCTD), Sjögren’s syndrome (SS) and rheumatoid arthritis (RA). In addition, a proportion of anti-Ku patients are moreover not classifiable either because they do not match available criteria (undifferentiated connective tissue disease (UCTD)) or because they conversely match criteria for several connective tissues diseases (overlap syndrome).1–4
On the other hand, data have indicated that, in the setting of a given condition, anti-Ku-related disease may represent an entity in its own right. Indeed, in SSc patients, anti-Ku-antibodies have been linked with myositis and arthritis but negatively associated with fingertip ulcers.5 6 Accordingly, myositis patients with anti-Ku antibodies have a higher risk of lung involvement but lower risk of associated cancer,2 7 this distinct phenotype being additionally associated with a distinct genotype.8 In SLE, anti-Ku antibodies are common in African but rare in white-American patients,9 10 although whether this translates at the clinical level remains unanswered.
In light of the above, we endeavoured to refine the spectrum of anti-Ku-associated disease by identifying subgroups of anti-Ku-positive patients with similar clinico-biological features and prognosis, without an a priori diagnosis. This enabled us to overcome the heterogeneity of diagnoses yielded by available criteria for connective tissue diseases.
Methods
Patients
Patients with anti-Ku antibodies (positive line immunoassay, verified by immunodiffusion) were identified in the database of the University Hospital of Strasbourg which includes data recorded from consecutive inpatients and outpatients over the 1995–2018 period. Our hospital hosts the national accredited public referral centre for rare autoimmune diseases (Centre de Référence des Maladies Auto-immunes Rares).
Serological data
All sera from patients with suspected connective tissue disease were tested for immunofluorescence on HEp-2 cells (Zeus Scientific, Branchburg, New Jersey, USA). Titres ≥1/160 were considered positive. The antinuclear antibody (ANA) pattern originally associated with anti-Ku is nuclear fine speckled (AC-4 as defined by the ICAP11) without nucleoli staining.12 However, homogeneous (AC-1), nuclear fine speckled with nucleoli (AC-4) and nuclear large/coarse speckled (AC-5) staining patterns hampered the assessment of this ANA pattern. Thus, all sera that yielded AC-1, AC-4 or AC-5 ANA patterns were tested for anti-Ku antibodies at a serum dilution of 1/150 using line immunoassay (ANA10DIV-24, D-Tek, Mons, Belgium). Positivity was confirmed by immunodiffusion (Auto I.D. ref 6050 Immuno Concept). Anti-SSA/Ro60, anti-SSB/La, anti-Sm, anti-RNP, anti-Scl70, anticentromere and anti-Jo1 antibodies were investigated using line immunoassay (D-Tek). Anti-dsDNA antibodies (Kallestad Anti-dsDNA Microplate EIA, Bio-Rad, Hercules, California, USA), anticitrullinated peptide/protein antibodies (Euro Diagnostica, Malmö, Sweden) and rheumatoid factors (in-house assay) were detected by ELISA. Anticardiolipin antibodies were detected by fluorescence enzyme immunoassay (ThermoScientific, Waltham, Massachusetts, USA), anti-β2GPI antibodies were detected by QUANTA-Lite (Werfen, Artarmon, Australia) and lupus anticoagulant activity was detected according to the guidelines of the International Society of Thrombosis and Hemostasis.13
Clinical data
The prospective public referral centre for rare autoimmune diseases registry database was used to summarise the presenting clinical features during follow-up.
Elevated serum levels of creatine kinase (CK) was defined by levels above the upper limit of normal.14
Dysphagia was defined as pharyngeal and/or oesophageal signs when eating and/or drinking (eg, difficulty swallowing solid and/or liquids, food sticking in throat, coughing while eating).
Pulmonary involvement was defined by interstitial lung disease (ILD) on high resolution CT scan of the chest, sufficient for the diagnosis as previously defined.15
Arthralgia was defined by inflammatory joint pain.
Renal involvement was defined and categorised as follows: (1) renal crisis: new onset of blood pressure >150/85 mm Hg, with decrease in renal function16 or (2) glomerulonephritis: proteinuria (>0.5 g/24 hours)17 without alternative cause and/or kidney biopsy demonstrating immune-mediated glomerulonephritis.
Cutaneous involvement was diagnosed and categorised as lupus rash, skin thickening, telangiectasia, dermatomyositis rash and/or mechanic’s hand ascertained by experienced physicians.
Haematological involvement consisted of cytopenia on two blood samples, without other causes than the connectivitis.
Thrombotic manifestations included arterial or venous thrombosis.
Echocardiography was used to screen for pulmonary hypertension.18
Serositis was defined as pericarditis and/or pleural effusion.
Diagnoses were systematically retrospectively reviewed, using American College of Rheumatology/European League Against Rheumatism (ACR/EULAR) criteria for SSc, myositis, SLE, RA and SS.19 MCTD and antiphospholipid syndrome (APLS) were respectively diagnosed using criteria proposed by Alarcón-Segovia et al 20 and Miyakis et al.13 When symptoms recorded during the entire follow-up did not match available criteria for a connective tissue disease, the patient was classified as UCTD.
Statistical analyses
Detailed description of the statistical methods used in this study is available in the online supplementary material 1.
Supplemental material
Results
A total of 47 anti-Ku-positive patients were identified (eg, representing), 188 out of 34 486 sera tested for anti-Ku after ANA pattern screening. Complete data were available in 42 cases. The study flowchart is illustrated in online supplementary figure S1.
Supplemental material
Clinical features are summarised in table 1. Patients most frequently matched the criteria for SLE, myositis and primary Sjögren’s syndrome. However, a third of the patients were equivocally classified with available criteria since 5 (12%) met the criteria for several connective tissue diseases (even after exclusion of secondary SS and APLS) while 7 (17%) had UCTD.
Clinical characteristics of anti-Ku patients in cluster numbers 1–3
During the 63.7 months of follow-up (range 12–226), three patients (7%) died: one from complications of lung transplantation for ILD, one from pulmonary infection during cyclophosphamide treatment for ILD and one from complications of terminal renal failure due to glomerulonephritis. In addition, another patient was on chronic haemodialysis after extramembranous glomerulonephritis relapse on a kidney-graft.
Given that anti-Ku-positive patients were heterogeneously classified with available criteria, hierarchical clustering was performed on 28 clinico-biological data (table 1) in order to identify subgroups with similar clinico-biological features and prognosis. Three clusters were identified (figure 1A).
(A) Factorial map of the 42 anti-Ku patients plotted in a multidimensional Euclidean space according to the results of the multiple correspondence analyses of their 28 cumulative clinico-biological features. Each patient is represented by a dot coloured according to the cluster to which she/he belongs (see also partitioning in B). The first two dimensions (DIMs) cumulatively explained 31.7% of the total variance. (B) Dendrogram generated using Euclidean distance in the first three DIMs of the factorial map and the ward agglomerative method. The bold vertical line indicates the height of the fusion into clusters and the x-axis indicates the patients (n=42) at the bottom of the dendrogram. Coloured lines indicate the partitioning of the dendrogram used to delineate the clusters (see the Methods section). (C) Proportion of glomerulonephritis and ILD, the two fatal complications in this series, in the three clusters. (D) Diagnostic performance (assessed by the sum of sensitivity and specificity) of clinico-biological features present at baseline for the diagnosis of cluster numbers 1–3. ACPA,anticitrullinated peptide antibodies; ANA, antinuclear antibodies; CK, creatine kinase; ILD, interstitial lung disease; MCP, metacarpophalangeal joints; RNP, ribonucleoprotein. **, ***, NS: p value <0.005;<0.001 and >0.05, respectively.
Importantly, glomerulonephritis and ILD, the two fatal complications in this series, were differentially distributed between these three groups: lung involvement was exclusively present in cluster no 1 while renal involvement was 6-fold and 14-fold higher in cluster no 3 comparatively to clusters numbers 1 and 2 (p<0.0001) (figure 1C). The three clusters also significantly differed on six other clinico-biological parameters including elevated CK level and muscle weakness, which were more frequent in cluster no 1, while lupus rash, cytopenia, positive anti-dsDNA and positive anti-RNP were more frequent in cluster no 3 (table 1).
In a sensitivity–specificity sum maximisation approach (figure 1D), among signs present at baseline examination, elevated CK was the most powerful parameter for identifying patients from cluster no 1 (sensitivity 93%; specificity 96%) while presence of anti-dsDNA antibodies was the most powerful criterion for identifying patients from cluster no 3 (sensitivity 89%; specificity 94%).
Moreover, as shown in table 2, patients with elevated CK at baseline had a higher risk of ILD (relative risk 21.6; 95% CI 2.2 to 266.1) while patients with anti-dsDNA antibodies at baseline had a higher risk of renal involvement (relative risk 12.8; 95% CI 1.3 to 32.2).
Clinical characteristics of anti-Ku patients with versus without increased CK and with versus without anti-DNA
Discussion
The present findings demonstrate that patients with anti-Ku antibodies can be clustered into three subgroups with distinct phenotypes and outcomes, easily distinguishable at first evaluation by simple testing, namely: CK serum-level measurement and anti-dsDNA antibodies testing. Anti-Ku patients with elevated CK have a high risk of ILD whereas patients with anti-dsDNA antibodies have a high risk of glomerulonephritis.
This study benefited from a large cohort with regard to the rarity of anti-Ku antibodies.7 To overcome recruitment bias, patients were identified on the basis of laboratory screening of both inpatients and outpatients from all departments of our institution. To improve the specificity of anti-Ku testing, a combination of immunofluorescence, LIA assay and immunodiffusion was used. Patient charts, along with extensive follow-up, were systematically reviewed. Thus, our data are likely to provide an accurate reflection of the entire spectrum of anti-Ku-related diseases. A potential limitation is that the status for the most recent autoantibodies associated with myositis was not available in all anti-Ku patients with elevated CK.
In accordance with previous findings, our patients with anti-Ku antibodies were not efficiently categorised using currently available criteria for connective tissue diseases. Indeed, our anti-Ku patients initially accounted for a total of seven different CTD diagnoses, which frequently overlapped, while other patients were not categorisable (UCTD). Yet, separate previous studies had indicated that anti-Ku patients with anti-dsDNA rarely had myositis,4 and that anti-Ku patients with myositis frequently had ILD.2 We demonstrate herein that anti-Ku patients with anti-dsDNA and anti-Ku patients with elevated CK are two distinct subgroups, rarely overlapping, with significant implications for patient care. Furthermore, in contrast with previous reports based on a single department,10 our data from unbiased recruitment highlight that glomerulonephritis frequently occurred in anti-Ku patients with anti-dsDNA at baseline and even resulted in terminal renal failure in two cases, one of which was fatal. On the other hand, anti-Ku patients with elevated CK at baseline frequently developed ILD which resulted in a fatal complication in two cases. Although patients in this last subgroup more frequently exhibited signs suggestive of SSc, only two matched the ACR–EULAR criteria for SSc even after a long follow-up. In addition, despite having elevated CK, one-third did not match the ACR–EULAR criteria for myositis. Moreover, it has been reported that even when fulfilling SSc and/or myositis criteria, patients with anti-Ku antibodies have a distinct phenotype comparatively to anti-Ku-negative patients.5–8 Altogether, the above data indicate that “anti-Ku with elevated CK” syndrome and “anti-Ku with anti-dsDNA” syndrome represent two distinct entities that are important to recognise in order to best tailor patient care.
References
Footnotes
Handling editor Josef S Smolen
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Patient consent for publication Not required.
Ethics approval The study was approved by the Commission nationale de l’informatique et des libertés (CNIL—French national data protection authority) under No. 912027.
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement All data relevant to the study are included in the article or uploaded as supplementary information.