RT Journal Article
SR Electronic
T1 Single-cell resolution of longitudinal blood transcriptome profiles in rheumatoid arthritis, systemic lupus erythematosus and healthy control pregnancies
JF Annals of the Rheumatic Diseases
JO Ann Rheum Dis
FD BMJ Publishing Group Ltd and European League Against Rheumatism
SP 300
OP 311
DO 10.1136/ard-2023-224644
VO 83
IS 3
A1 Lien, Hilde Julie T
A1 Pedersen, Tina T
A1 Jakobsen, Bente
A1 Flatberg, Arnar
A1 Chawla, Konika
A1 Sætrom, Pål
A1 Fenstad, Mona H
YR 2024
UL http://ard.bmj.com/content/83/3/300.abstract
AB Objectives Comparative longitudinal analyses of cellular composition and peripheral blood gene expression in Rheumatoid arthritis (RA), systemic lupus erythematosus (SLE) and healthy pregnancies.Methods In total, 335 whole blood samples from 84 RA, SLE and healthy controls before pregnancy, at each trimester, 6 weeks, 6 months and 12 months post partum were analysed. We combined bulk and single cell RNA analyses for cell-type estimation, validated by flow cytometry, before combining this in a cell-type adjusted analysis for an improved resolution of unrecognised gene expression changes associated with RA and SLE pregnancies.Results Patients were well regulated throughout pregnancy, and few had pregnancy complications. In SLE, the interferon signature was augmented during pregnancy, and the pregnancy signature was continued post partum. An altered cell type composition strongly influences the profile. In the pregnancy signature, transcripts involved in galactosylation potentially altering the effector functions of autoantibodies became more evident. Several genes in the adjusted RA signature are expressed in mucosal associated invariant T cells.Conclusion We found distinct RA, SLE and pregnancy signatures, and no expression patterns could be attributed to medication or disease activity. Our results support the need for close postpartum follow-up of patients with SLE. Gene expression patterns in RA were closer to healthy controls than to SLE, and primarily became evident after cell-type adjustment. Adjusting for cell abundance unravelled gene expression signatures less associated with variation in cell-composition and highlighted genes with expression profiles associated with changes in specialised cell populations.Data are available in a public, open access repository. Our data can be found at Gene Expression Omnibus repository (GEO), accession number GSE235508.