Understand SLE heterogeneity in the era of omics,big data,and artificial intelligence

查看全文 作　　者：Prianka [1,2]Puri;Simon [3,4,5]H.Jiang;Yang [2]Yang;Fabienne [6]Mackay;Di [2]Yu

机构地区：[1]Kidney Health Service,Royal Brisbane and Women's Hospital,Brisbane,Queensland,Australia;[2]The University of Queensland Diamantina Institute,Faculty of Medicine,The University of Queensland,Woolloongabba,Queensland,Australia;[3]Department of Immunology and Infectious Disease,John Curtin School of Medical Research,Acton,Australian Capital Territory,Australia;[4]Centre for Personalised Immunology,NHMRC Centre for Research Excellence,Acton,Australian Capital Territory,Australia;[5]Department of Renal Medicine,The Canberra Hospital,Garran,Australian Capital Territory,Australia;[6]QIMR Berghofer Medical Research Institute in Brisbane QLD,Herston,Queensland,Australia

出　　处：《Rheumatology & Autoimmunity》索引2021年第1卷第1期,共12页

基　　金：Bellberry Limited and The Viertel Charitable Foundation,Grant/Award Number:Bellberry Limited and The Viertel Charitable Foundation。 摘　　要：Systemic lupus erythematosus(SLE)is a systemic autoimmune disease characterized by extraordinary heterogeneity,due to the complex pathogenesis and diverse manifestations.Stratification of patients for therapy and prognosis represents a major challenge to manage SLE.Conventional biomarkers for disease diagnosis and activity assessment provide very limited insight into immunological pathogenesis and therapeutic response rates.The advancement of“omics”technologies including genomics,transcriptomics,proteomics,and metabolomics has constituted an unprecedented opportunity to characterize the immunopathological landscape in individual patients with SLE.Indeed,genomic studies reveal a subset of SLE patients carrying one or more functional single nucleotide polymorphisms(SNPs)underlying immune dysregulation while transcriptomic studies have revealed subgroups in SLE patients showing distinct signatures for Type I interferon(TI-IFN)pathway activation or aberrant differentiation of B cells into plasma cells.This review will summarize results from the latest studies using omics technology to understand SLE heterogeneity.In addition,we propose that the application of artificial intelligence,such as by machine learning-based nonlinear dimensionality reduction method uniform manifold approximation and projection(UMAP)can further strengthen the analysis of omics big data.The combination of new technology and novel analysis pipeline can lead to breakthroughs in stratifying SLE patients for a better monitoring of disease activity and more precise design of treatment regime,not only for conventional immunosuppression but also novel immunotherapies targeting B-cell activating factor(BAFF),TI-IFN,and interleukin 2(IL-2). 关键词：classification GENOMICS metabolomics PROTEOMICS TRANSCRIPTOMICS

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Understand SLE heterogeneity in the era of omics,big data,and artificial intelligence

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