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

Background and aims Studying the distribution of SLE across geographic regions using a big data-driven approach may facilitate understanding of the corresponding genetic and environmental underpinnings. Methods We explored the potential of the Google search engine to collect and merge cohorts (u003e100 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. Results We 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%. Conclusions This 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.