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Extended report
Autoantibodies as biomarkers for the prediction of neuropsychiatric events in systemic lupus erythematosus
  1. J G Hanly1,2,
  2. M B Urowitz3,
  3. L Su4,
  4. S-C Bae5,
  5. C Gordon6,
  6. A Clarke9,
  7. S Bernatsky10,
  8. A Vasudevan11,
  9. D Isenberg12,
  10. A Rahman12,
  11. D J Wallace8,
  12. P R Fortin3,
  13. D Gladman3,
  14. J Romero-Dirz7,
  15. J Sanchez-Guerrero7,
  16. M A Dooley13,
  17. I Bruce14,
  18. K Steinsson15,
  19. M Khamashta16,
  20. S Manzi17,
  21. R Ramsey-Goldman18,
  22. G Sturfelt19,
  23. O Nived19,
  24. R van Vollenhoven20,
  25. M Ramos-Casals21,
  26. C Aranow22,
  27. M Mackay22,
  28. K Kalunian23,
  29. G S Alarcón24,
  30. B J Fessler24,
  31. G Ruiz-Irastorza25,
  32. M Petri26,
  33. S Lim27,
  34. D Kamen28,
  35. C Peschken29,
  36. V Farewell4,
  37. K Thompson1,
  38. C Theriault1,
  39. J T Merrill30
  1. 1Department of Medicine, Division of Rheumatology, Queen Elizabeth II Health Sciences Centre and Dalhousie University, Halifax, Nova Scotia, Canada
  2. 2Department of Pathology, Division of Rheumatology, Queen Elizabeth II Health Sciences Centre and Dalhousie University, Halifax, Nova Scotia, Canada
  3. 3Centre for Prognosis Studies in the Rheumatic Diseases, Toronto Western Hospital and University of Toronto, Toronto, Ontario, Canada
  4. 4MRC Biostatistics Unit, Institute of Public Health, University Forvie Site, Cambridge, UK
  5. 5Department of Rheumatology, Hanyang University Hospital for Rheumatic Diseases, Seoul, Korea
  6. 6Rheumatology Research Group, School of Immunity and Infection, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
  7. 7Instituto Nacional de Ciencias Medicas y Nutrición, Mexico City, Mexico
  8. 8Cedars-Sinai/David Geffen School of Medicine at UCLA, Los Angeles, California, USA
  9. 9Divisions of Clinical Immunology/Allergy and Clinical Epidemiology, Montreal General Hospital, McGill University Health Centre, Montreal, Quebec, Canada
  10. 10Divisions of Rheumatology and Clinical Epidemiology, Montreal General Hospital, McGill University Health Centre, Montreal, Quebec, Canada
  11. 11Department of Medicine, SUNY Downstate Medical Center, Brooklyn, New York, USA
  12. 12Centre for Rheumatology Research, University College, London, UK
  13. 13University of North Carolina, Chapel Hill, North Carolina, USA
  14. 14Arthritis Research UK Epidemiology Unit, School of Translational Medicine, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
  15. 15Center for Rheumatology Research, Landspitali University hospital, Reykjavik, Iceland
  16. 16Lupus Research Unit, The Rayne Institute, St Thomas' Hospital, King's College London School of Medicine, London, UK
  17. 17Division of Rheumatology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
  18. 18Northwestern University and Feinberg School of Medicine, Chicago, Illinois, USA
  19. 19Department of Rheumatology, University Hospital Lund, Lund, Sweden
  20. 20Department of Rheumatology, Karolinska Institute, Stockholm, Sweden
  21. 21Servicio Enfermedades Autoinmunes Hospital Clínico y Provincial, Barcelona, Spain
  22. 22Columbia University Medical Center, New York, New York, USA
  23. 23UCSD School of Medicine, La Jolla, California, USA
  24. 24Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA
  25. 25Autoimmune Disease Unit, Department of Internal Medicine, Hospital de Cruces, University of the Basque Country, Barakaldo, Spain
  26. 26Department of Rheumatology, Johns Hopkins University, Baltimore, Maryland, USA
  27. 27Emory University, Atlanta, Georgia, USA
  28. 28Medical University of South Carolina, Charleston, South Carolina, USA
  29. 29University of Manitoba, Winnipeg, Manitoba, Canada
  30. 30Department of Clinical Pharmacology, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, USA
  1. Correspondence to Dr J G Hanly, Division of Rheumatology, Nova Scotia Rehabilitation Centre (2nd Floor), 1341 Summer Street, Halifax, NS B3H 4K4, Canada; john.hanly{at}


Objective Neuropsychiatric events occur unpredictably in systemic lupus erythematosus (SLE) and most biomarker associations remain to be prospectively validated. This study examined a disease inception cohort of 1047 SLE patients to determine which autoantibodies at enrolment predicted subsequent neuropsychiatric events.

Methods Patients with a recent SLE diagnosis were assessed prospectively for up to 10 years for neuropsychiatric events using the American College of Rheumatology case definitions. Decision rules of graded stringency determined whether neuropsychiatric events were attributable to SLE. Associations between the first neuropsychiatric event and baseline autoantibodies (lupus anticoagulant (LA), anticardiolipin, anti-β2 glycoprotein-I, anti-ribosomal P and anti-NR2 glutamate receptor) were tested by Cox proportional hazards regression.

Results Disease duration at enrolment was 5.4±4.2 months, follow-up was 3.6±2.6 years. Patients were 89.1% female with mean (±SD) age 35.2±13.7 years. 495/1047 (47.3%) developed one or more neuropsychiatric event (total 917 events). Neuropsychiatric events attributed to SLE were 15.4% (model A) and 28.2% (model B). At enrolment 21.9% of patients had LA, 13.4% anticardiolipin, 15.1% anti-β2 glycoprotein-I, 9.2% anti-ribosomal P and 13.7% anti-NR2 antibodies. LA at baseline was associated with subsequent intracranial thrombosis (total n=22) attributed to SLE (model B) (HR 2.54, 95% CI 1.08 to 5.94). Anti-ribosomal P antibody was associated with subsequent psychosis (total n=14) attributed to SLE (model B) (HR 3.92, 95% CI 1.23 to 12.5, p=0.02). Other autoantibodies did not predict neuropsychiatric events.

Conclusion In a prospective study of 1047 recently diagnosed SLE patients, LA and anti-ribosomal P antibodies are associated with an increased future risk of intracranial thrombosis and lupus psychosis, respectively.

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Nervous system involvement in systemic lupus erythematosus (SLE) encompasses a variety of neurological and psychiatric features. Using the American College of Rheumatology (ACR) case definitions,1 the prevalence of neuropsychiatric disease in SLE varies from 21% to 95%, but only 19–38% of events are attributable to lupus.2,,6 Neuropsychiatric events present or reoccur at any time in the disease course, although the majority occurs around the time of diagnosis of SLE, particularly those attributable to SLE.7,,11 The identification of biomarkers at the time of diagnosis to quantify the subsequent risk of neuropsychiatric events attributable to systemic lupus erythematosus (NPSLE) would be helpful.

NPSLE is probably mediated by autoantibodies, microvasculopathy and the intracranial production of inflammatory mediators,12,,15 often in combination. Lupus-related autoantibodies most frequently associated with NPSLE include antiphospholipid antibodies, anti-ribosomal P antibodies and autoantibodies that bind to neuronal antigens such as the N-methyl-d-aspartate glutamate receptor (anti-NR2).16 Although there is biological plausibility and experimental data16,,20 to implicate these autoantibodies in the causality of nervous system disease, studies of human SLE have provided inconsistent findings.21,,25 Limitations of previous studies include their cross-sectional design, inclusion of patients with variable disease duration, and lack of standardisation in both the classification of neuropsychiatric events and the methodology used for autoantibody detection. We have assembled an international, inception cohort of SLE patients to examine the association between a panel of autoantibodies measured within a mean of 6 months of the time of diagnosis and subsequent nervous system events over a mean follow-up of 3.6 years. Attribution models of different stringency were used to distinguish neuropsychiatric events attributed to SLE and non-SLE causes.

Patients and methods

Research study network

The study was conducted by members of the Systemic Lupus International Collaborating Clinics (SLICC),26 a network of 37 investigators in 30 international academic medical centres in 11 countries. Twenty-one centres participated in the study. Data were collected prospectively on patients presenting with a new diagnosis of SLE. All information was submitted to the coordinating centre in Halifax, Nova Scotia, Canada, and entered into a centralised access database. Appropriate procedures ensured data quality, management and security. The study was approved by the Capital Health Research Ethics Board, Halifax, Nova Scotia, Canada, and by each of the participating centre's own institutional research ethics review boards.


Patients who fulfilled the ACR classification criteria for SLE27 provided written informed consent. The date of diagnosis was when these cumulative criteria were first recognised. Enrolment was permitted up to 15 months following the diagnosis. Variables collected included age, gender, ethnicity, education and medication history. Lupus-related variables included the ACR classification criteria for SLE,27 the SLE disease activity index (SLEDAI)28 and the SLICC/ACR damage index (SDI).29 Laboratory variables were haematology, serum and urine chemistry and immunological variables (including anti-DNA antibodies) required for the generation of SLEDAI and SDI scores.

Neuropsychiatric events

An enrolment window within which all neuropsychiatric events were captured extended from 6 months before the diagnosis of SLE up to the enrolment date. Neuropsychiatric events were characterised using the ACR nomenclature and case definitions for 19 neuropsychiatric syndromes.1 These were diagnosed by clinical evaluation and investigations were performed if clinically warranted.

Patients were reviewed annually with a 6-month window around the anticipated assessment date. New neuropsychiatric events since the previous study visit and their attribution were determined.

Supplementary information was recorded as per the ACR glossary for neuropsychiatric syndromes1 to identify other potential causes (‘exclusions’) or contributing factors (‘associations’) for each of the neuropsychiatric events. These ‘non-SLE factors’ were used partly to determine the attribution of neuropsychiatric events. Patients could have more than one type of neuropsychiatric event, and repeated episodes of the same event within the enrolment window or within a follow-up assessment period were recorded once. The date of the first episode was taken as the onset of the neuropsychiatric event within the particular time frame.

Attribution of neuropsychiatric events

Decision rules were used to determine the attribution of all neuropsychiatric events. Factors considered in the decision rules included: (1) onset of neuropsychiatric event(s) before the diagnosis of SLE; (2) concurrent non-SLE factor(s) identified from the ACR glossary for each neuropsychiatric syndrome; and (3) ‘common’ neuropsychiatric events that are frequent in normal population controls, as described by Ainiala et al.30 These include all headaches, anxiety, mild depression (mood disorders failing to meet criteria for ‘major depressive-like episodes’), mild cognitive impairment (deficits in less than three of the eight specified cognitive domains) and polyneuropathy without electrophysiological confirmation.

Attribution of neuropsychiatric events was determined by the central application of decision rules of different stringency (models A and B), as described in detail elsewhere.31 32 Neuropsychiatric events that fulfilled the criteria for model A (the most stringent) or for model B (the least stringent) were attributed to SLE. By definition, all neuropsychiatric events attributed to SLE using model A were included in the group of neuropsychiatric events attributed to SLE using model B. Those events that did not fulfil these criteria were attributed to non-SLE causes

Determination of autoantibodies

Autoantibodies were measured in Dr Joan Merrill's laboratory at the Oklahoma Medical Research Foundation, USA. Autoantibody determinations were made without knowledge of the occurrence of neuropsychiatric events or their attribution in individual patients.

ELISA for anti-NR2 antibodies

The NR2 human peptide sequence, (Asp Trp Glu Tyr Ser Val Trp Leu Ser Asn)8 Lys 4 Lys2 Lys-β Ala, was synthesised using f-moc chemistry, purified by high-performance liquid chromatography and confirmed by Edman degradation at the Molecular Biology Proteomics Facility of the University of Oklahoma Health Sciences Centre, Oklahoma City, Oklahoma, USA. High binding, Nunc 96-well polystyrene plates were coated with 5 μg/ml of NR2 peptide in borate-buffered saline and blocked with borate-buffered saline, bovine serum albumin (Fraction V; Sigma, St Louis, Missouri, USA) and 1.2% Tween 80. Patient sera, positive and negative controls were added, diluted 1/100 in the same blocking buffer. Plates were washed with borate-buffered saline between each step with vigorous pounding to eliminate non-specific binding. The secondary antibody was an alkaline phosphatase conjugated goat anti-human IgG (Sigma) with the addition of goat serum to block non-specific binding (donor herd; Sigma). Plates were developed using p-Nitrophenyl Phosphate (p-NPP) substrate buffer (Sigma). The optical density of the enzyme-linked immune assay was read at 405 (primary wavelength) and 450 (secondary wavelength). Serial dilutions of a high binding positive control were used as a calibrator.

Antiphosphilipid, anti-β2 glycoprotein-I and anti-ribosomal P antibodies

Lupus anticoagulant (LA) and ELISA for anticardiolipin, anti-β2 glycoprotein-I and anti-ribosomal P protein were performed as previously described.33,,35 The LA assay was performed using screen and confirm reagents from Rainbow Scientific (Windsor, Connecticut, USA). Each reagent was standardised against 20 plasma samples (collected in citrate) from healthy donors. A normal reference range was derived from calculating 2 SD above the mean of healthy controls on the screen and confirm (phospholipid quenched) tests and calculating the ratio of screen value/confirm value. Patient's clotting time for the LA screen was divided by the LA confirm's clotting time. If this number was above the normal reference range, the patient was considered positive for LA. β2 Glycoprotein-I, purified from human plasma, was the gift of Drs Naomi and Charles Esmon, and ribosomal P protein was provided by Dr Morris Reichlin, Oklahoma Medical Research Foundation. Each ELISA was validated against a curve, constructed using serial dilutions of a high binding serum. In the case of anticardiolipin and anti-ribosomal P protein, these calibrators were previously established in Dr Reichlin's laboratory. In the case of anti-β2 glycoprotein-I the calibrator was established by the Registry for the Antiphospholipid Syndrome at Oklahoma. The cut-off for positive was defined as 2 SD above the mean of 60 healthy controls and/or the position on the flat part of the calibrator curve, whichever was associated with the higher OD. On each ELISA plate, positive and negative control sera (established previously from the laboratory collection and frozen at −80°C in assay-specific aliquots) were run to ensure a valid assay.

Statistical analysis

χ2-Tests were used to examine the association of autoantibody prevalence at enrolment with geographical regions or ethnic/racial groups. The associations of autoantibodies at enrolment with the time to the first occurrence of neuropsychiatric events overall, or events attributed to SLE (model A or model B) as well as the time to the first occurrence of individual events (cerebrovascular disease and psychosis) were examined using Cox proportional hazards regression.



A total of 1047 patients was recruited between October 1999 and April 2010. The median (range) number of patients enrolled in each of the 21 centres was 31 (6–161). The patients were predominantly women, with a mean (±SD) age of 35.2±13.7 years and a wide ethnic distribution, although they were predominantly Caucasian (table 1).

Table 1

Demographic and clinical manifestations of SLE patients at enrolment

At enrolment the mean disease duration was only 5.4±4.2 months despite the opportunity to recruit patients up to 15 months following the diagnosis of SLE. The prevalence of individual ACR classification criteria at enrolment reflected an unselected patient population. The mean SLEDAI and SDI scores revealed moderate global disease activity and minimal cumulative organ damage, respectively. Therapy at enrolment reflected the typical range of lupus medications. The number of assessments in individual patients varied from one to 10 over a mean follow-up of 3.6±2.6 years.

Neuropsychiatric manifestations

Four hundred and ninety-five out of 1047 (47.2%) patients had one or more neuropsychiatric event and 226/1047 (21.5%) had two or more events. The events and their attributions are summarised in table 2.

Table 2

Characteristics of cumulative neuropsychiatric syndromes over the study period in SLE patients with one or more autoantibody measurement at enrolment (n=1047)

There were 917 neuropsychiatric events, encompassing 17 of the 19 neuropsychiatric syndromes: headache (52.0%); mood disorders (14.4%); seizure disorder (5.8%); anxiety disorder (5.7%); cerebrovascular disease (5.1%); cognitive dysfunction (4.5%); polyneuropathy (2.5%); acute confusional state (2.3%); mononeuropathy (1.7%); psychosis (1.7%); cranial neuropathy (1.2%); movement disorder (0.9%); myelopathy (0.9%); aseptic meningitis (0.7%); demyelinating syndrome (0.4%); autonomic neuropathy (0.1%) and plexopathy (0.1%). The proportion of neuropsychiatric events attributed to SLE varied from 15.4% to 28.2% using alternative attribution models and occurred in 9.7% (model A) to 16.5% (model B) of patients. There were no patients with Guillain–Barré syndrome or myasthenia gravis. Of the 917 neuropsychiatric events, 865 (94.3%) affected the central nervous system and 52 (5.7%) involved the peripheral nervous system. The classification of events into diffuse and focal was 749 (81.7%) and 168 (18.3%), respectively.

Autoantibodies and racial/ethnic group

The prevalence of autoantibodies is illustrated in figure 1. This varied from 9.2% (91/991) for anti-ribosomal P antibodies, 13.4% (133/995) for anticardiolipin, 13.7% (126/923) for anti-NR2, 15.1% (150/994) for anti-β2 glycoprotein-I and 21.9% (228/1042) for LA. The number of patients with one, two or three or more positive antibody tests was 312, 107 and 61, respectively. The frequency of autoantibodies varied by geographical region. In particular, the frequency of LA was lower in Canadian centres (15.2%) compared with centres in the USA (26.0%), Europe (23.1%), Asia (22.6%) and Mexico (30.8%) (p=0.015), and the frequency of anti-ribosomal P antibodies was higher in Mexico (29.0%) compared with Canada (7.3%), USA (7.5%), Europe (8.0%) and Asia (13.7%) (p<0.001). In large part these findings were due to the association of racial/ethnic group with autoantibody frequencies (table 3).

Figure 1

Frequency of autoantibodies at enrolment. aCL, IgG anticardiolipin antibody; anti-β2-GPI IgG, anti-β2 glycoprotein I antibody; anti-NR2, IgG anti-NR2 glutamate receptor antibody; anti-ribo P, IgG anti-ribosomal P antibody; LA, lupus anticoagulant.

Table 3

The association between autoantibody frequency and racial/ethnic group

Autoantibodies and overall neuropsychiatric events

There was no significant positive association between autoantibodies and the first occurrence of neuropsychiatric events overall, or events attributed to SLE (model A or model B). Clustering of neuropsychiatric events into diffuse/focal and central/peripheral manifestations did not change the outcome of this analysis. In keeping with our previous findings36 the presence of anti-DNA antibodies measured at individual SLICC sites did not positively predict the occurrence of neuropsychiatric events (data not shown).

Autoantibodies and individual neuropsychiatric events

Analyses were also performed to examine specific a priori clinical–serological associations. The association between antiphospholipid antibodies and cerebrovascular disease and between anti-ribosomal P antibodies and psychosis were of particular interest (table 4 and figure 2).Cerebrovascular disease includes stroke, transient ischaemic attack, chronic multifocal disease, subarachnoid or intracranial haemorrhage and sinus thrombosis. No strong relationship was demonstrated between cerebrovascular disease, so defined, and the presence of any one of either anti-β2 glycoprotein-I, anticardiolipin antibody or LA (HR 1.26, 95% CI 0.69 to 2.30). However, LA at baseline and the occurrence of cerebrovascular disease approached statistical significance (HR 1.84, 95% CI 0.92 to 3.68) and the association with stroke/sinus thrombosis (total n=22) attributed to SLE (model B) was statistically significant (HR 2.54, 95% CI 1.08 to 5.94). The median (range) between the detection of LA and first stroke/sinus thrombosis was 5.02 (0–7.36) years. In addition, anti-ribosomal P antibody at baseline was associated with psychosis (total n=14) attributed to SLE (model B) (HR 3.92, 95% 1.23 to 12.5). Seven of the patients with psychosis were African, five were Caucasian and one each was Hispanic and Asian. Given the higher rate of psychosis in African patients (p<0.01), adjustment for racial/ethnic group (African/others) was undertaken. This led to a reduction in the HR for anti-ribosomal P antibody and subsequent psychosis to 3.1, with a corresponding shift in the CI (0.95 to 9.99). The median (range) between the detection of anti-ribosomal P antibody and the first episode of psychosis was 5.69 (0–9.16) years.

Figure 2

Kaplan–Meier time-to-event curves for intracranial thrombosis in patients with and without lupus anticoagulant (LA) (left panel) and for psychosis in patients with and without anti-ribosomal P antibodies (anti-P) (right panel). SLE, systemic lupus erythematosus.

Table 4

The association between autoantibodies and the time to specific neuropsychiatric manifestations as indicated by HR (95% CI)


We have evaluated the usefulness of measuring selected autoantibodies for predicting the occurrence of NPSLE in a large, international, inception cohort of SLE patients over the first 10 years of disease. Our findings provide some evidence that LA and anti-ribosomal P antibodies are significantly associated with specific manifestations of neuropsychiatric disease attributed to SLE, namely intracranial thrombosis and psychosis, respectively. Variability in the frequency of some autoantibodies with racial/ethnic group supports previous observations of this kind36 37 and probably alters the risk profile for the occurrence of neuropsychiatric events in some groups of patients.

There are several strengths to our study. In contrast with previous retrospective and cross-sectional clinical studies of NPSLE, ours was prospective to identify the characteristics and attribution of all neuropsychiatric events using a predefined annual data collection protocol. The multicentre, international, longitudinal study design provides a basis for extrapolating our findings to the broader community of SLE patients. Although nervous system involvement by SLE has long been recognised, the lack of specificity of multiple individual manifestations and difficulty in identifying the correct attribution of the clinical neuropsychiatric events has been challenging. The ACR case definitions of 19 neuropsychiatric syndromes,1 which were developed over a decade ago have provided a much needed and now widely used platform for the classification of neuropsychiatric events in SLE cohorts. We have also used the accompanying ACR glossary with other information to derive decision rules for determining the attribution of neuropsychiatric events to SLE or non-SLE causes.32 In previous studies the application of these decision rules has demonstrated significant correlations with clinical outcomes and selected autoantibodies.31 32 38 39 The use of these rules in the current study provides an excellent platform for the prospective evaluation of potential biomarkers of NPSLE.

The search for biomarkers of NPSLE is based upon what is already known of the pathogenesis of the disease. There is robust evidence from several sources to implicate a pathogenic role for autoantibodies, microvasculopathy and the intracranial production of inflammatory mediators. These studies have provided a menu of biomarker candidates, including autoantibodies, cytokines and other inflammatory molecules40 as well as soluble markers of neuronal and glial degradation.41 Detailed discussion is not possible here but a few general observations are worthy of comment. First, given the multitude of clinical manifestations it is very unlikely that a single biomarker will reliably predict all neuropsychiatric events. Second, the anatomical location of biomarkers is important in some cases. For example, the association of diffuse neuropsychiatric events with autoantibodies is significantly stronger if these are measured in the cerebrospinal fluid (CSF), whereas autoantibodies associated with focal neuropsychiatric events are best studied in peripheral blood. An alternative to accessing CSF is to find a biomarker of increased permeability of the blood–brain barrier, a critical factor if some autoantibodies are to reach their target antigen and cause clinical disease. Finally, it is possible that combinations of biomarkers reflecting different components of the pathogenic model of NPSLE will best predict clinical events. To our knowledge, there are no previous studies that have set out to evaluate biomarkers of NPSLE in a large multi-ethnic cohort of patients specifically recruited as close to the diagnosis of SLE as possible and followed over an extended period. Some but not all previous cross-sectional studies with smaller sample sizes have found an association between LA and intracranial thrombosis42 and between anti-ribosomal P antibodies and lupus psychosis.24 43,,47 However, in those studies the autoantibodies were measured in close temporal proximity to the clinical event. In contrast, our study is the first to demonstrate the risk of a single autoantibody determination around the time of diagnosis of SLE for a subsequent and often remote neuropsychiatric event.

There are several limitations to the current study. First, the number of autoantibodies studied was limited and CSF samples were not available. The selection of autoantibodies was based upon the evidence of their pathogenic role. Access to CSF samples in our study was infrequent and was restricted to situations when a lumbar puncture was clinically indicated. Also, the small number of specific neuropsychiatric events allowed little power for adjusted analyses. Second, as the study involved antibody determination at a single point in time, no information is yet available on the predictive value of sustained circulating levels of autoantibodies. Third, the classification of neuropsychiatric status was determined primarily by clinical assessment and using appropriate investigations only when clinically indicated. Specialised and sensitive investigations such as MRI neuroimaging studies and formal neuropsychological assessment of cognitive function were not routinely performed on all patients. Their use would very likely have resulted in the recognition of additional structural and function abnormalities of the nervous system. However, many of the abnormalities would be of dubious clinical significance and the routine use of such investigations, although justified in the context of a clinical study, would not mirror what is most commonly done in clinical practice. Finally, the duration of follow-up in the current study does not reflect the lifetime experience with neuropsychiatric events experienced by the majority of SLE patients. We and others have previously reported that neuropsychiatric events, especially those attributed to SLE, occur most frequently within the first 2 years of the diagnosis of SLE,7,,11 thus emphasising the importance of this period of observation. Nevertheless, further follow-up is required to identify the longer-term association between autoantibodies detected either at baseline or over the duration of a patients' illness and the clinical expression of NPSLE. The long-term objective of our prospective study is to follow all patients for 10 years, which will provide an excellent platform to find new and stronger associations with circulating serological biomarkers.



  • Funding JGH was supported by Canadian Institutes of Health Research grant MOP-57752, Capital Health Research Fund. MBU's work was supported by the Canadian Institutes of Health Research (grant MOP-49529), the Lupus Foundation of Ontario, the Ontario Lupus Association, Lupus UK, the Lupus Foundation of America, the Lupus Alliance of Western New York, the Conn Smythe Foundation, the Lupus Flare Foundation and the Tolfo Family of Toronto, Ontario, Canada. LS was supported by MRC (UK) grant U.1052.00.009 and VF was supported by MRC (UK) grant U.1052.00.009. S-CB's work was supported by the Korea Healthcare technology R&D project, Ministry for Health and Welfare, Republic of Korea (A080588). The Montreal General Hospital Lupus Clinic is partially supported by the Singer Family Fund for Lupus Research. AC is a national scholar of the Fonds de la Recherché en Santé de Quebec. PRF is a distinguished senior investigator of the Arthritis Society, with additional support from the Arthritis Centre of Excellence, University of Toronto. RR-G's work was supported by the NIH (grants UL-1RR-025741, K24-AR-02318 and P60-AR-48098). GR-I is supported by the Department of Education, Universities and Research of the Basque Government.

  • Competing interests None.

  • Patient consent Obtained.

  • Ethics approval This study was conducted with the approval of the Capital Health Research Ethics Board, Halifax, Nova Scotia, Canada, and by each of the participating centre's own institutional research ethics review boards.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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