OBJECTIVE: Clinical diagnosis of SLE is currently challenging due to its 
heterogeneity. Many autoantibodies are associated with SLE and are considered 
potential diagnostic markers, but systematic screening and validation of such 
autoantibodies is lacking. This study aimed to systematically discover new 
autoantibodies that may be good biomarkers for use in SLE diagnosis.
METHODS: Sera from 15 SLE patients and 5 healthy volunteers were analysed using 
human proteome microarrays to identify candidate SLE-related autoantibodies. The 
results were validated by screening of sera from 107 SLE patients, 94 healthy 
volunteers and 60 disease controls using focussed arrays comprised of 
autoantigens corresponding to the identified candidate antibodies. Logistic 
regression was used to derive and validate autoantibody panels that can 
discriminate SLE disease. Extensive ELISA screening of sera from 294 SLE 
patients and 461 controls was performed to validate one of the newly discovered 
autoantibodies.
RESULTS: A total of 31, 11 and 18 autoantibodies were identified to be expressed 
at significantly higher levels in the SLE group than in the healthy volunteers, 
disease controls and healthy volunteers plus disease control groups, 
respectively, with 25, 7 and 13 of these differentially expressed autoantibodies 
being previously unreported. Diagnostic panels comprising anti-RPLP2, anti-SNRPC 
and anti-PARP1, and anti-RPLP2, anti-PARP1, anti-MAK16 and anti- RPL7A were 
selected. Performance of the newly discovered anti-MAK16 autoantibody was 
confirmed by ELISA. Some associations were seen with clinical characteristics of 
SLE patients, such as disease activity with the level of anti-PARP1 and rash 
with the level of anti-RPLP2, anti-MAK16 and anti- RPL7A.
CONCLUSION: The combined autoantibody panels identified here show promise for 
the diagnosis of SLE and for differential diagnosis of other major rheumatic 
immune diseases.