Machine learning integration of scleroderma histology and gene expression identifies fibroblast polarisation as a hallmark of clinical severity and improvement.
Kimberly S LakinRobert SpieraCynthia MagroPhaedra AgiusViktor MartyanovJennifer M FranksRoshan SharmaHeather GeigerTammara A WoodYaxia ZhangCaryn R HaleJackie FinikMichael L WhitfieldDana E OrangeJessica K GordonPublished in: Annals of the rheumatic diseases (2020)
CD34 and aSMA stains describe distinct fibroblast polarisation states, are associated with gene expression subsets and clinical assessments, and may be useful biomarkers of clinical severity and improvement in dcSSc.