416 Big data in systemic lupus erythematosus: phenotypic disease expression of 171,000 adult patients

Background and aimsStudying the distribution of SLE across geographic regions using a big data-driven approach may facilitate understanding of the corresponding genetic and environmental underpinnings.MethodsWe explored the potential of the Google search engine to collect and merge cohorts (>100 patients) of patients with systemic lupus erythematosus (SLE) reported in the Pubmed library. We made a text-word search in Google between 8th and 15th May 2015 using SLE and ”100...100000000 patients” and “site:http://www.ncbi.nlm.nih.gov/pubmed”. We collected the available data about study design, country, ethnicities, age and gender, clinical features and immunological markers.ResultsWe merged the data of 133 SLE cohorts including 1 71 000 patients; gender was detailed in 130 cohorts:88% women(female:male ratio, 8,4). mean age at onset (29.89±3.48), at diagnosis (32.33±2.99).The countries contributing the most cohorts were the USA (31), Japan (8) and Spain (5). The main clinical features included arthritis in 72%,haematological abnormalities in 62%,malar rash in 50%,photosensitivity in 48%, renal involvement in 38%, oral ulcers in 34%, serositis in 30% and neurological involvement in 14%. Haematological abnormalities included lymphopenia in 43%,leukopenia in 38%,thrombocytopenia in13% and hemolytic anaemia in 4%.Positive autoantibodies included ANA in 91%,dSDNA in 62%,anti-Ro/SSA in 35%,antiRNP in 25%,antiSm in 21% and anti-La/SSB in 15%.ConclusionsThis is the largest reported study in SLE including nearly 2 00 000 cases that provides a big data picture of the worldwide expression of the disease, with a female:male ratio of 8,4, a mean age at diagnosis of 32 years, and with joints, haematological, skin and kidneys being the most frequent organs involved.