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Abstract

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES

Objective

To examine autoantibody clusters and their associations with clinical features and organ damage accrual in patients with systemic lupus erythematosus (SLE).

Methods

The study group comprised 1,357 consecutive patients with SLE who were recruited to participate in a prospective longitudinal cohort study. In the cohort, 92.6% of the patients were women, the mean ± SD age of the patients was 41.3 ± 12.7 years, 55.9% were Caucasian, 39.1% were African American, and 5% were Asian. Seven autoantibodies (anti–double-stranded DNA [anti-dsDNA], anti-Sm, anti-Ro, anti-La, anti-RNP, lupus anticoagulant (LAC), and anticardiolipin antibody [aCL]) were selected for cluster analysis using the K-means cluster analysis procedure.

Results

Three distinct autoantibody clusters were identified: cluster 1 (anti-Sm and anti-RNP), cluster 2 (anti-dsDNA, anti-Ro, and anti-La), and cluster 3 (anti-dsDNA, LAC, and aCL). Patients in cluster 1 (n = 451), when compared with patients in clusters 2 (n = 470) and 3 (n = 436), had the lowest incidence of proteinuria (39.7%), anemia (52.8%), lymphopenia (33.9%), and thrombocytopenia (13.7%). The incidence of nephrotic syndrome and leukopenia was also lower in cluster 1 than in cluster 2. Cluster 2 had the highest female-to-male ratio (22:1) and the greatest proportion of Asian patients. Among the 3 clusters, cluster 2 had significantly more patients presenting with secondary Sjögren's syndrome (15.7%). Cluster 3, when compared with the other 2 clusters, consisted of more Caucasian and fewer African American patients and was characterized by the highest incidence of arterial thrombosis (17.4%), venous thrombosis (25.7%), and livedo reticularis (31.4%). By using the Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index, the greatest frequency of nephrotic syndrome (8.9%) was observed in patients in cluster 2, whereas cluster 3 patients had the highest percentage of damage due to cerebrovascular accident (12.8%) and venous thrombosis (7.8%). Osteoporotic fracture (11.9%) was also more common in cluster 3 than in cluster 2.

Conclusion

Autoantibody clustering is a valuable tool to differentiate between various subsets of SLE, allowing prediction of subsequent clinical course and organ damage.

Individual autoantibodies have some association with the clinical features of patients with systemic lupus erythematosus (SLE). Examples of such associations include anti–doubled-stranded DNA (anti-dsDNA) antibody and lupus nephropathy (1), anti-Ro/La antibodies and keratoconjunctivitis sicca (2, 3), anti-RNP and Raynaud's phenomenon (4), and lupus anticoagulant (LAC) and/or anticardiolipin antibodies (aCL) and thromboembolism (5). Hoffman et al described the presence of 5 clusters of autoantibodies (anti-Sm/RNP, anti-Ro/La, anti–ribosomal P, antihistone, and anti-dsDNA antibodies) in the setting of SLE (2). Tapanes et al reported that the presence of anti-Sm/RNP or anti-Ro/La/Sm/RNP was associated with a more benign form of lupus nephropathy (6). In this study, we used the statistical technique of cluster analysis to identify groups of lupus patients with similar autoantibody patterns and to describe the clinical differences between these groups.

PATIENTS AND METHODS

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES

All patients who previously consented to participate in the Hopkins Lupus Cohort Study were included. The cohort comprises 1,500 patients with SLE (7). All patients were followed up prospectively at intervals of every 3 months, beginning at the time of entry into the cohort. Clinical features, serologic data, and damage accrual data were recorded at the time of entry into the cohort and were updated at subsequent visits. The following clinical features were defined according to the 1982 American College of Rheumatology (ACR) revised classification criteria for SLE (7): malar rash, discoid rash, photosensitivity, oral ulcer, arthritis, pleuritis, pericarditis, proteinuria (>0.5 gm/day), hemolysis, leukopenia (<4,000/mm3), lymphopenia (<1,500/mm3), and thrombocytopenia (<100,000/mm3).

Other clinical features were defined as follows. Raynaud's phenomenon was identified by blanching of fingers and/or toes induced by exposure to cold or stress, while livedo reticularis was characterized by reddish or cyanotic discoloration of the skin with a reticular pattern. Arthralgia was characterized by symptoms of joint pain but no signs of inflammation, while nephrotic syndrome was defined by daily proteinuria (>3 gm/day), and anemia was defined by hemoglobin concentration of <11.0 gm/dl in a woman and <12.0 gm/dl in a man, or a hematocrit of <33% in a woman and <36% in a man. Sjögren's syndrome consisted of dry eyes, confirmed by abnormal results of Schirmer's test, not attributable to medications (e.g., antidepressants, diuretics) or dry eyes or mouth and abnormal results of a salivary gland biopsy or dry eyes and mouth and the presence of anti-Ro and/or anti-La antibodies. Seizure, psychosis, organic brain syndrome (acute confusional state), meningitis (aseptic meningitis), depression, headache, and peripheral neuropathy were defined according to the ACR nomenclature and case definitions for neuropsychiatric lupus (8).

Stroke due to lupus was defined as a cerebrovascular event attributed to lupus activity rather than atherosclerosis, hypertension, or cardiac emboli. Myocarditis was defined as inflammation of the myocardium for which viral, bacterial, and drug causes were excluded. Gastrointestinal lupus was defined as colitis, vasculitis, or serositis of the abdominal cavity. Pancreatitis due to lupus was confirmed by imaging and/or the presence of raised levels of lipase/amylase. Arterial thrombosis included cerebrovascular accident, myocardial infarction, and transient ischemic events, confirmed by imaging, electrocardiography, cardiac enzymes, or clinical examination and history. Venous thrombosis was defined as deep vein thrombosis and/or pulmonary embolism, as ascertained by imaging. Items considered to reflect damage in SLE were defined and scored using the Systemic Lupus International Collaborating Clinics/ACR Damage Index (SDI) (9).

Laboratory tests.

Baseline immunologic tests for 7 autoantibodies were performed at the first cohort visit. They included detection of anti-dsDNA by Crithidia assay; detection of anti-Ro, anti-La, anti-Sm, anti-RNP, and LAC by dilute Russell's viper venom time and confirmatory tests (10); and determination of IgG/IgM aCL. Before May 1999, the Ouchterlony double diffusion assay was performed for the detection of Ro, La, Sm, and RNP antibodies. Subsequently, enzyme-linked immunosorbent assay (ELISA) was used for detection of Ro, La, Sm, and RNP antibodies in patients enrolled after May 1999. The ELISA kits used were QUANTA Lite SS-A, QUANTA Lite SS-B, QUANTA Lite Sm, and QUANTA Lite RNP (all from Inova Diagnostics, San Diego, CA). The QUANTA Lite SS-A ELISA detects both 60-kd and 52-kd Ro antigens but does not allow differentiation of the 2 Ro antigens. The kits used for detection of aCL were ACA IgG, ACA IgM, and ACA IgA (all from Inova Diagnostics). IgG aCL levels >10 IgG phospholipid units and IgM aCL levels of >10 IgM phospholipid units were considered positive.

Statistical analysis.

K-means cluster analysis (non-hierarchical clustering or Quick Cluster; SPSS version 10 software; SPSS, Chicago, IL) was used to identify groups of SLE patients with similar antoantibody patterns. Briefly, this first involves defining a disease metric with which to quantify the degree of similarity between autoantibody patterns in 2 patients. We used Euclidian distance (the square root of the sums of squared differences between patients with respect to each autoantibody). The initial centers for the clusters are chosen in a first pass of data, and patients are assigned to the closest center. Next, the cluster centers are recalculated based on the patients in the cluster, and the patients are reassigned. This iterative process continues until the clusters' means do not shift more than a given cutoff value or until the iteration limit is reached. Because we did not know in advance how many autoantibody clusters would be observed, we specified 3, 4, and then 5 clusters, respectively, in the K-means analysis, and ran the analysis several times. The outputs from the analyses with 3, 4, and 5 clusters of patients were then compared with each other with respect to the prevalence of the individual autoantibody. In order to be clinically meaningful in comparing the clinical features, the prevalence of the autoantibody should be statistically different between clusters. Finally, by clustering antibodies into 3 clusters, we identified 3 distinct groups of patients with very different autoantibody profiles.

In order for a patient with SLE to be eligible for the cluster analysis, information for all 7 selected autoantibodies (anti-dsDNA, anti-Ro, anti-La, anti-Sm, anti-RNP, LAC, and IgG/IgM aCL) had to be available at the time of the study. Eligible patients were then clustered by the K-means cluster procedure, based on these 7 autoantibodies as binary variables. Demographic variables (age at diagnosis, sex, ethnicity, annual household income, education, and smoking status), 32 clinical manifestations, and 27 items on the SDI were compared between the 3 autoantibody clusters. The conventional chi-square test was used to compare categorical variables. P values less than 0.05 were considered significant. All statistical analyses were performed using SPSS for Windows version 10.0.

RESULTS

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES

A total of 1,357 patients with SLE were eligible for the analysis (143 patients were excluded because their autoantibody profiles were incomplete at the time of the study). The mean ± SD age of the patients was 41.3 ± 12.7 years; 92.6% were women, 55.9% were Caucasian, 39.1% were African American, and 5% were Asian. The mean ± SD age at diagnosis was 32 ± 12.6 years, and the mean ± SD duration of followup was 9.2 ± 15.3 years. The demographic characteristics and the frequency of specific autoantibodies are shown in Table 1.

Table 1. Baseline characterics of the patients (n = 1,357)*
CharacteristicValue
  • *

    Except where indicated otherwise, values are the number (%) of patients. Anti-dsDNA = anti–double-stranded DNA; aCL = anticardiolipin antibodies.

Age at diagnosis, years 
 <20232 (17.1)
 20–40797 (58.7)
 >40328 (24.2)
Duration of followup, years 
 <4347 (25.6)
 4–10485 (35.7)
 >10525 (38.7)
No. women/no. men (ratio)1,257/100 (12:1)
Ethinicity 
 African American530 (39.1)
 Caucasian759 (55.9)
 Asian68 (5)
Anti-dsDNA790 (58.2)
Anti-Ro375 (27.6)
Anti-La150 (11.1)
Anti-Sm209 (15.4)
Anti-RNP338 (24.9)
Lupus anticoagulant351 (25.9)
IgG/IgM aCL504 (37.1)

Autoantibody clusters.

When the 1,357 study patients were clustered based on their antibody profiles, 3 distinctive antibody clusters were obtained: cluster 1 (anti-Sm and anti-RNP [Sm/RNP]), cluster 2 (anti-dsDNA, anti-Ro, and anti-La [DNA/Ro/La]), and cluster 3 (anti-dsDNA, LAC, and aCL [DNA/LAC/aCL]). Four hundred fifty-one patients were assigned to cluster 1, 470 patients were assigned to cluster 2, and 436 patients were assigned to cluster 3. The frequency of the specific autoantibodies in each cluster is shown in Table 2. The results of the cluster analyses did not change when only patients enrolled in the cohort after May 1999 were analyzed. Thus, the results did not change when ELISAs were used instead of double diffusion assays for detection of anti-Ro, anti-La, anti-Sm, and anti-RNP.

Table 2. Frequency of specific antoantibodies in various clusters*
AutoantibodyCluster 1 (n = 451)Cluster 2 (n = 470)Cluster 3 (n = 436)P
  • *

    Values are the number (%) of patients. Anti-dsDNA = anti–double-stranded DNA; LAC = lupus anticoagulant; aCL = anticardiolipin antibodies.

  • Values are significantly different from the 2 other clusters.

Anti-dsDNA109 (24.2)362 (77)319 (73.2)<0.001
Anti-Ro12 (2.7)324 (68.9)39 (8.9)<0.001
Anti-La11 (2.4)112 (23.8)27 (6.2)<0.001
Anti-Sm100 (22.2)59 (12.6)50 (11.5)<0.001
Anti-RNP178 (39.5)90 (19.1)70 (16.1)<0.001
LAC63 (14)39 (8.3)249 (57.1)<0.001
IgG/IgM aCL17 (3.8)91 (19.4)396 (90.8)<0.001

Demographic characteristics.

The demographic characteristics of SLE patients in the 3 clusters are shown in Table 3. Cluster 2 (DNA/Ro/La), compared with clusters 1 and 3, had the highest female-to-male ratio (22:1; P = 0.002) and the greatest proportion of Asian patients (4.7%; P = 0.002). Cluster 3 (DNA/LAC/aCL) had significantly more Caucasian patients (65.8%; P < 0.001) and fewer African American patients (30.5%; P < 0.001). Patients in cluster 3 also had significantly longer followup compared with patients in cluster 1 (44.7% of patients in cluster 3 had followup of >10 years, compared with 32.2% of patients in cluster 1; P = 0.001). In contrast, no significant difference between the 3 clusters was observed for age at diagnosis, annual household income, education level, and smoking status.

Table 3. Comparison of demographic features according to autoantibody cluster*
CharacteristicSm/RNP (n = 451)DNA/Ro/La (n = 470)DNA/LAC/aCL (n = 436)P
  • *

    Values are the number (%) of patients. LAC = lupus anticoagulant; aCL = anticardiolipin antibodies.

  • Values are significantly different from the other 2 clusters.

Age at diagnosis, years    
 <2066 (14.6)82 (17.4)85 (19.5)0.18
 20–40264 (58.5)282 (60)251 (57.6)0.75
 >40121 (26.8)106 (22.6)100 (22.9)0.23
Duration of followup, years    
 <4127 (28.2)120 (25.5)100 (22.9)0.14
 4–10179 (39.7)165 (35.1)141 (32.3)0.06
 >10145 (32.2)185 (39.4)195 (44.7)0.001
Sex    
 Female416 (92.2)450 (95.7)391 (89.7)0.002
 Male35 (7.8)20 (4.3)45 (10.3)0.002
Ethnicity    
 African American197 (43.7)200 (42.6)133 (30.5)<0.001
 Caucasian237 (52.5)235 (50)287 (65.8)<0.001
 Asian8 (1.8)22 (4.7)5 (1.1)0.002
Annual household income <$25,000134 (29.7)151 (32.1)139 (31.9)0.67
Education <12 years165 (36.8)183 (38.9)171 (39.2)0.68
Smoking ever179 (39.7)182 (38.7)183 (42)0.59

Clinical manifestations.

The clinical features of the patients in the 3 autoantibody-cluster groups are shown in Table 4. Patients in cluster 1 (Sm/RNP), when compared with those in clusters 2 and 3, had a significantly lower incidence of proteinuria (39.7%; P < 0.001), anemia (52.8%; P < 0.001), lymphopenia (33.9%; P < 0.001), and thrombocytopenia (13.7%; P < 0.001). Other features less commonly observed in cluster 1 were nephrotic syndrome (P < 0.007 versus cluster 2), leukopenia (P = 0.013 versus cluster 2), and hemolytic anemia (P = 0.026 versus cluster 3).

Table 4. Comparison of clinical features according to antibody cluster*
CharacteristicSm/RNP (n = 451)DNA/Ro/La (n = 470)DNA/LAC/aCL (n = 436)P
  • *

    Values are the number (%) of patients. See Patients and Methods for definitions of anemia, gastrointestinal lupus, arterial thrombosis, and venous thrombosis. LAC = lupus anticoagulant; aCL = anticardiolipin antibodies.

  • Values are significantly different from only 1 other cluster.

  • Values are significantly different from the other 2 clusters.

Malar rash269 (59.6)252 (53.6)215 (49.3)0.008
Discoid lupus109 (24.2)104 (22.1)73 (16.7)0.02
Photosensitivity rash269 (59.6)257 (54.7)220 (50.5)0.02
Oral ulcer228 (50.6)206 (43.8)201 (46.1)0.11
Raynaud's phenomenon243 (53.9)225 (47.9)212 (48.6)0.14
Livedo reticularis98 (21.7)98 (20.9)137 (31.4)<0.001
Arthralgia421 (93.3)428 (91.1)395 (90.6)0.28
Arthritis355 (78.7)349 (74.3)319 (73.2)0.12
Pleuritis197 (43.7)209 (44.5)202 (46.3)0.71
Pericarditis91 (20.2)104 (22.1)101 (23.2)0.54
Proteinuria (>0.5 gm/day)179 (39.7)244 (51.9)210 (48.2)<0.001
Nephrotic syndrome (>3 gm/day)69 (15.3)108 (23)80 (18.3)<0.007
Anemia238 (52.8)310 (66)273 (62.6)<0.001
Hemolysis37 (8.2)54 (11.5)62 (14.2)0.026
Leukopenia (<4,000/mm3)187 (41.5)240 (51.1)197 (45.2)0.013
Lymphopenia (<1,500/mm3)153 (33.9)223 (47.4)207 (47.5)<0.001
Thrombocytopenia (<100,000/mm3)62 (13.7)100 (21.3)127 (29.1)<0.001
Sjögren's syndrome48 (10.6)74 (15.7)35 (8)<0.001
Seizure53 (11.8)41 (8.7)45 (10.3)0.31
Psychosis16 (3.5)20 (4.3)19 (4.4)0.79
Organic brain syndrome23 (5.1)25 (5.3)30 (6.9)0.46
Meningitis13 (2.9)15 (3.2)8 (1.8)0.41
Stroke due to lupus11 (2.4)21 (4.5)28 (6.4)0.016
Depression172 (38.1)153 (32.6)165 (33.8)0.13
Lupus headache46 (10.2)50 (10.6)54 (12.4)0.54
Peripheral neuropathy24 (5.3)21 (4.5)25 (5.7)0.67
Myocarditis5 (1.1)9 (1.9)13 (3)0.13
Hepatomegaly27 (6)18 (3.8)13 (3)0.08
Gastrointestinal lupus12 (2.7)20 (4.3)20 (4.6)0.23
Pancreatitis15 (3.3)19 (4)19 (4.4)0.65
Arterial thrombosis42 (9.3)48 (10.2)76 (17.4)<0.001
Venous thrombosis49 (10.9)61 (13)112 (25.7)<0.001

In cluster 2 (DNA/Ro/La), the incidence of secondary Sjögren's syndrome (15.7%) was significantly greater than that in clusters 1 and 3 (P < 0.001). Cluster 3 (DNA/LAC/aCL) was characterized by the highest incidence of arterial thrombosis (cerebrovascular accident, myocardial infarction, transient ischemic attack) (17.4%), venous thrombosis (deep vein thrombosis or pulmonary embolism) (25.7%), and livedo reticularis (31.4%) (P < 0.001 versus clusters 1 and 2 for all comparisons). Compared with patients in cluster 1 (Sm/RNP), patients in cluster 3 (DNA/LAC/aCL) had significantly more stroke events attributable to lupus activity rather than to atherosclerosis, hypertension, or cardiac embolism (6.4% versus 2.4%; P = 0.016) and a lower incidence of malar rash (49.3% versus 59.6%; P = 0.008), discoid rash (16.7% versus 24.2%; P = 0.02), and photosensitivity (50.5% versus 59.6%; P = 0.02).

Damage accrual.

The organ damage sustained by patients in the 3 autoantibody-cluster groups is shown in Table 5. Patients in cluster 3 (DNA/LAC/aCL) had a greater incidence of cerebrovascular accidents (12.8%; P < 0.001 versus clusters 1 and 2), venous thrombosis (7.8%; P < 0.001 versus clusters 1 and 2), and osteoporotic fracture (11.9% P = 0.049 versus cluster 2), whereas patients in cluster 2 (DNA/Ro/La) had the greatest frequency of persistent nephrotic syndrome (8.9%; P = 0.05 versus cluster 1).

Table 5. Comparison of organ damage according to antoantibody cluster*
VariableSm/RNP (n = 451)DNA/Ro/La (n = 470)DNA/LAC/aCL (n = 436)P
  • *

    Values are the number (%) of patients. Gastrointestinal damage was defined as infarction or resection of bowel, mesenteric insufficiency, chronic pancreatitis, stricture, gastrointestinal tract surgery, or pancreatic insufficiency. Musculoskeletal damage was defined as muscle atrophy, deforming or erosive arthritis, osteomyelitis, or ruptured tendon. Dermatologic damage was defined as scarring chronic alopecia, extensive scarring of panniculum, and skin ulceration. LAC = lupus anticoagulant; aCL = anticardiolipin antibodies; GFR = glomerular filtration rate; CABG = coronary artery bypass graft.

  • Values are significantly different from the other 2 clusters.

  • Values are significantly different from only 1 other cluster.

Any cataract64 (14.2)55 (11.7)59 (13.5)0.51
Retinal changes25 (5.5)20 (4.3)29 (6.7)0.28
Cognitive impairment31 (6.9)35 (7.4)27 (6.2)0.75
Seizure27 (6)15 (3.2)24 (5.5)0.10
Cerebrovascular accident27 (6)33 (7)56 (12.8)<0.001
Cranial/peripheral neuropathy39 (8.6)32 (6.8)48 (11)0.08
Reduced GFR (<50%)21 (4.7)27 (5.7)33 (7.6)0.18
Proteinuria (>3.5 gm/day)23 (5.1)42 (8.9)26 (6)0.05
End-stage renal failure12 (2.7)27 (5.7)20 (4.6)0.069
Pulmonary hypertension11 (2.4)18 (3.8)21 (4.8)0.16
Pulmonary fibrosis21 (4.7)30 (6.4)25 (5.7)0.51
Pleural fibrosis11 (2.4)9 (1.9)8 (1.8)0.78
Angina or CABG14 (3.1)16 (3.4)15 (3.4)0.95
Myocardial infarction14 (3.1)20 (4.3)20 (4.6)0.49
Cardiomyopathy15 (3.3)16 (3.4)21 (4.8)0.42
Valvular heart disease7 (1.6)10 (2.1)11 (2.5)0.59
Pericarditis7 (1.6)6 (1.3)6 (1.4)0.93
Venous thrombosis10 (2.2)11 (2.3)34 (7.8)<0.001
Gastrointestinal damage41 (9.1)42 (8.9)50 (11.5)0.36
Musculoskeletal damage42 (9.3)46 (9.8)45 (10.3)0.88
Osteoporotic fracture40 (8.9)34 (7.2)52 (11.9)0.049
Avascular necrosis38 (8.4)43 (9.1)44 (10.1)0.69
Dermatologic damage23 (5.1)22 (4.7)24 (5.5)0.85
Premature gonadal failure16 (3.5)16 (3.4)18 (4.1)0.83
Diabetic mellitus43 (9.5)29 (6.2)33 (7.6)0.15
Malignancy31 (6.9)33 (7)37 (8.5)0.60

DISCUSSION

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES

This study is the largest observational study evaluating the clinical associations of autoantibody clusters in patients with SLE. The cluster analysis procedure, although rarely performed in SLE research, is an appropriate tool for examining serologic or clinical clusters in a heterogeneous disease such as SLE. All autoantibodies selected for the study were readily available and can be measured routinely in most medical centers. Thus, the observed associations are considered very clinically relevant and applicable in the daily management of patients with lupus.

The 3 distinct autoantibody clusters we observed have not been previously recognized in SLE. The prevalence of individual autoantibodies was significantly different among the 3 clusters. An exception was anti-dsDNA (as determined by Crithidia assay), a high proportion of which was present in 2 of the clusters (77% in cluster 2 and 73.2% in cluster 3). Our study confirmed the observations in several previous studies, in which autoantibodies tended to occur in pairs, such as anti-Sm and anti-RNP (2, 6), anti-Ro and anti-La (2, 11), and LAC and aCL (5).

African American patients with lupus have been reported to have more severe organ manifestations and poorer survival compared with Caucasian SLE patients (12, 13). This ethnic difference in lupus morbidity is likely multifactorial, involving the interplay of genetic, socioeconomic, and immunologic factors. Petri et al (14) and Ward et al (15) reported that noncompliance to medical therapy (as assessed by physician global assessment and percent of protocol visits) and/or low socioeconomic status, instead of African American ethnicity, was predictive of poor outcomes. However, few studies have examined the relationship between ethnicity and immunologic factors in terms of autoantibody profiles. Tikly et al (16) and Garcia et al (17) reported a high prevalence of anti-Sm and anti-RNP in African American patients. We also observed a similar association, but it failed to reach statistical significance. In addition, we also observed new associations not previously reported: the DNA/Ro/La cluster was associated with female sex (P = 0.002) and Asian ethnicity (P = 0.002), and the DNA/LAC/aCL cluster was associated with Caucasian ethnicity (P < 0.001). Although these associations need to be confirmed by further studies, they provide evidence that ethnicity differences in autoantibody clusters do exist and might be responsible for the divergent clinical presentations in various ethnic groups.

The Sm/RNP cluster has been previously linked to “the absence and the most benign form of SLE nephropathy” (6). Hoffman et al also reported that SLE patients with Sm/RNP antibodies had a lower prevalence of urine cellular casts (2). We observed that patients in the Sm/RNP cluster had the lowest incidence of renal manifestations (for proteinuria, P < 0.001 versus clusters 2 and 3; for nephrotic syndrome, P < 0.007 versus cluster 2). Of note, the Sm/RNP cluster also has the lowest percentage of anti-dsDNA (24.2%; P < 0.001). Because of the role of anti-dsDNA antibodies in disease activity (1, 18, 19) and in active lupus nephritis (20, 21), the relatively low frequency of renal involvement among patients in the Sm/RNP cluster may be attributable simply to the absence of anti-dsDNA rather than the presence of Sm/RNP. Nevertheless, this autoantibody cluster does provide a good indicator for the subset with the least frequent renal involvement and probably the most favorable renal prognosis.

Apart from the reported associations of LAC/aCL with thrombocytopenia (22) and hemolytic anemia (23), the relationship between autoantibody clusters and hematologic lupus has not been well established. We observed a negative association between Sm/RNP and anemia (P < 0.001), hemolytic anemia (P = 0.026 versus cluster 3), leukopenia (P = 0.013 versus cluster 2), lymphopenia (P < 0.001), and thrombocytopenia (P < 0.001). On the contrary, several cutaneous manifestations of lupus were more common in this cluster, including malar rash (P = 0.008 versus cluster 3), discoid lupus (P = 0.02 versus cluster 3), photosensitivity (P = 0.02 versus cluster 3), and Raynaud's phenomenon (increased trend but not statistically significant). The Sm/RNP cluster may represent the subset of SLE that is most benign, in which renal and hematologic manifestations are less common and the major manifestations are dermatologic. This is somewhat reminiscent of another report that the Sm/RNP cluster represented the subset of lupus patients with less major organ involvement (24).

The causative role of antiphospholipid antibodies, including LAC/aCL, in thromboembolism has been well described (5, 22, 25). Several groups of investigators have reported that high titers of IgG aCL were predictive of central nervous system involvement in patients with SLE (26, 27, 28). Correspondingly, we also observed the highest incidence of arterial thrombosis (P < 0.001) and venous thrombosis (P < 0.001), livedo reticularis (P < 0.001), and lupus-related stroke event (P = 0.016 versus cluster 1) in cluster 3 (DNA/LAC/aCL). However, in comparison with cluster 1 (Sm/RNP), cutaneous manifestations of lupus (malar rash, discoid lupus, photosensitivity, and Raynaud's phenomenon) were relatively less common in cluster 3 (DNA/LAC/aCL). Taken together, DNA/LAC/aCL represents a subset of SLE patients with predominantly neurologic and thrombotic events and in whom livedo reticularis is the main cutaneous manifestation.

Risk factors for organ damage in patients with SLE include older age at disease onset (29), longer duration of disease (30, 31), persistently active disease (31, 32), high cumulative dose of corticosteroid (33), and the use of cyclophosphamide (34). Antiphospholipid antibodies have been shown to be predictive of early damage in patients with SLE (35). Mikdashi and Handwerger observed that seizure and cerebrovascular accident (as measured using the SDI) were highly associated with antiphospholipid antibodies, whereas the presence of anti-dsDNA was predictive of polyneuropathy (32). However, Yee et al observed no significant association between organ damage and various autoantibodies (anti-Ro, anti-La, anti-Sm, anti-RNP, anti-dsDNA) (29). Of note, we observed strong associations between the DNA/LAC/aCL cluster and cerebrovascular accident, venous thrombosis, and an increased prevalence of cranial/peripheral neuropathy (although the difference was not statistically significant) as measured using the SDI. Interestingly, the incidence of osteoporotic fracture was also found to be highest in cluster 3 (DNA/LAC/aCL), but no similar trend was observed for other complications of corticosteroid therapy, such as cataract and avascular necrosis. Aside from the DNA/LAC/aCL cluster, the other clusters (Sm/RNP and DNA/Ro/La) seem to have a minimal role in predicting organ damage, except that an increased incidence of nephrotic syndrome was observed in patients in the DNA/Ro/La cluster. This supports results of an earlier study, in which autoantibodies other than antiphospholipid antibodies were not predictive of organ damage in SLE (29).

The current study is an exploratory analysis of 3 autoantibody clusters and their clinical correlates in a large cohort of patients with lupus. A patient in cluster 1, for instance, need not have only anti-Sm and anti-RNP antibodies. In fact, the interpretation of a “cluster” is that only the anti-Sm and anti-RNP antibodies were overrepresented in that particular cluster of patients. In other words, their autoantibody profiles were most similar, according to the clustering procedure. We characterized the individual clusters by these overrepresented autoantibodies and reported their clinical correlates. Although the laboratory technique for detection of Ro/La/Sm/RNP was changed from the Ouchterlony double diffusion assay to an ELISA in May 1999, a separate analysis of patients enrolled after this time point revealed the same autoantibody clusters. Thus, our observations are likely genuine and were not biased by this change in laboratory method. From a clinical standpoint, we can conclude that patients with these predefined autoantibody profiles might manifest the disease as we have reported. The present study cannot test the causal association between the individual autoantibodies and the specific clinical features and also cannot be used to predict the clinical manifestations in patients with other autoantibody combinations.

The results of our study confirm that in the setting of lupus, autoantibodies do exist in clusters. All of the subjects in the current study were unselected. Therefore, the clusters observed are likely to be a true reflection of different disease patterns and are likely to be generalizable to other centers. From the clinical standpoint, autoantibody clusters, similar to individual autoantibodies, help to differentiate between various subsets of SLE.

REFERENCES

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES